,abstract,author,category,date,doi,journal,key,open_access,primary_category,provenance,score,title,unique_key,url
0,The success of the Internet is remarkable in light of the decentralized manner in which it is designed and operated. Unlike small scale networks  the Internet is built and controlled by a large number of disparate service providers who are not interested in any global optimization. Instead  providers simply seek to maximize their own profit by charging users for access to their service. Users themselves also behave selfishly  optimizing over price and quality of service. Game theory provides a natural framework for the study of such a situation. However  recent work in this area tends to focus on either the service providers or the network users  but not both. This paper introduces a new model for exploring the interaction of these two elements  in which network managers compete for users via prices and the quality of service provided. We study the extent to which competition between service providers hurts the overall social utility of the system.,ara hayrapetyan,Not available,2007.0,10.1007/s00446-006-0020-y,Distributed Computing,Ara2007,False,,Springer,Not available,A network pricing game for selfish traffic,1e6ace55d7fedd0e4eeed19012c6755b,http://dx.doi.org/10.1007/s00446-006-0020-y
1,The success of the Internet is remarkable in light of the decentralized manner in which it is designed and operated. Unlike small scale networks  the Internet is built and controlled by a large number of disparate service providers who are not interested in any global optimization. Instead  providers simply seek to maximize their own profit by charging users for access to their service. Users themselves also behave selfishly  optimizing over price and quality of service. Game theory provides a natural framework for the study of such a situation. However  recent work in this area tends to focus on either the service providers or the network users  but not both. This paper introduces a new model for exploring the interaction of these two elements  in which network managers compete for users via prices and the quality of service provided. We study the extent to which competition between service providers hurts the overall social utility of the system.,eva tardos,Not available,2007.0,10.1007/s00446-006-0020-y,Distributed Computing,Ara2007,False,,Springer,Not available,A network pricing game for selfish traffic,1e6ace55d7fedd0e4eeed19012c6755b,http://dx.doi.org/10.1007/s00446-006-0020-y
2,Contrary to early expectations  recent studies have shown near-perfect adherence to HIV antiretrovirals in sub-Saharan Africa We conducted qualitative interviews with patients purchasing low-cost  generic antiretroviral therapy to better understand the social dynamics underlying these findings. We found that concerns for family well-being motivate adherence  yet  the financial sacrifices necessary to secure therapy may paradoxically undermine family welfare. We suggest that missed doses may be more due to a failure to ,j. oyugi,Not available,2006.0,10.1007/s10461-006-9080-z,AIDS and Behavior,T.2006,False,,Springer,Not available,The Price of Adherence: Qualitative Findings From HIV Positive Individuals Purchasing Fixed-Dose Combination Generic HIV Antiretroviral Therapy in Kampala  Uganda,3546dd01c0a6376828bbafaaa37b87c7,http://dx.doi.org/10.1007/s10461-006-9080-z
3,According to the proportional allocation mechanism from the network optimization literature  users compete for a divisible resource – such as bandwidth – by submitting bids. The mechanism allocates to each user a fraction of the resource that is proportional to her bid and collects an amount equal to her bid as payment. Since users act as utility-maximizers  this naturally defines a proportional allocation game. Syrgkanis and Tardos (STOC 2013) quantified the inefficiency of equilibria in this game with respect to the social welfare and presented a lower bound of 26.8 ,alexandros voudouris,Not available,2016.0,10.1007/s00224-016-9674-4,Theory of Computing Systems,Ioannis2016,False,,Springer,Not available,Welfare Guarantees for Proportional Allocations,1d8ae082a051688dbd93e495f0ef4f8e,http://dx.doi.org/10.1007/s00224-016-9674-4
4,We study profit sharing games in which players select projects to participate in and share the reward resulting from that project equally. Unlike most existing work  in which it is assumed that the player utility is monotone in the number of participants working on their project  we consider non-monotone player utilities. Such utilities could result  for example  from “threshold” or “phase transition” effects  when the total benefit from a project improves slowly until the number of participants reaches some critical mass  then improves rapidly  and then slows again due to diminishing returns.Non-monotone player utilities result in a lot of instability: strong Nash equilibrium may no longer exist  and the quality of Nash equilibria may be far away from the centralized optimum. We show  however  that by adding additional requirements such as players needing permission to leave a project from the players currently on this project  or instead players needing permission to join a project from players on that project  we ensure that strong Nash equilibrium always exists. Moreover  just the addition of permission to leave already guarantees the existence of strong Nash equilibrium within a factor of 2 of the social optimum. In this paper  we provide results on the existence and quality of several different coalitional solution concepts  focusing especially on permission to leave and join projects  and show that such requirements result in the existence of good stable solutions even for the case when player utilities are non-monotone.,elliot anshelevich,Not available,2016.0,10.1007/s00224-015-9667-8,Theory of Computing Systems,Elliot2016,False,,Springer,Not available,Profit Sharing with Thresholds and Non-monotone Player Utilities,84428d0eedf0a0623e846ca61245a388,http://dx.doi.org/10.1007/s00224-015-9667-8
5,We study profit sharing games in which players select projects to participate in and share the reward resulting from that project equally. Unlike most existing work  in which it is assumed that the player utility is monotone in the number of participants working on their project  we consider non-monotone player utilities. Such utilities could result  for example  from “threshold” or “phase transition” effects  when the total benefit from a project improves slowly until the number of participants reaches some critical mass  then improves rapidly  and then slows again due to diminishing returns.Non-monotone player utilities result in a lot of instability: strong Nash equilibrium may no longer exist  and the quality of Nash equilibria may be far away from the centralized optimum. We show  however  that by adding additional requirements such as players needing permission to leave a project from the players currently on this project  or instead players needing permission to join a project from players on that project  we ensure that strong Nash equilibrium always exists. Moreover  just the addition of permission to leave already guarantees the existence of strong Nash equilibrium within a factor of 2 of the social optimum. In this paper  we provide results on the existence and quality of several different coalitional solution concepts  focusing especially on permission to leave and join projects  and show that such requirements result in the existence of good stable solutions even for the case when player utilities are non-monotone.,john postl,Not available,2016.0,10.1007/s00224-015-9667-8,Theory of Computing Systems,Elliot2016,False,,Springer,Not available,Profit Sharing with Thresholds and Non-monotone Player Utilities,84428d0eedf0a0623e846ca61245a388,http://dx.doi.org/10.1007/s00224-015-9667-8
6,We continue the study of the performance of mildly greedy players in cut games initiated by Christodoulou et al. (Theoret Comput Sci 438:13–27  ,vittorio bilo,Not available,2016.0,10.1007/s10878-015-9898-2,Journal of Combinatorial Optimization,Vittorio2016,False,,Springer,Not available,On the performance of mildly greedy players in cut games,b5501f437688ea148cdea4c2c372bc56,http://dx.doi.org/10.1007/s10878-015-9898-2
7,We continue the study of the performance of mildly greedy players in cut games initiated by Christodoulou et al. (Theoret Comput Sci 438:13–27  ,mauro paladini,Not available,2016.0,10.1007/s10878-015-9898-2,Journal of Combinatorial Optimization,Vittorio2016,False,,Springer,Not available,On the performance of mildly greedy players in cut games,b5501f437688ea148cdea4c2c372bc56,http://dx.doi.org/10.1007/s10878-015-9898-2
8,We study assignment games in which jobs select machines  and in which certain pairs of jobs may conflict  which is to say they may incur an additional cost when they are both assigned to the same machine  beyond that associated with the increase in load. Questions regarding such interactions apply beyond allocating jobs to machines: when people in a social network choose to align themselves with a group or party  they typically do so based upon not only the inherent quality of that group  but also who amongst their friends (or enemies) chooses that group as well. We show how ,elliot anshelevich,Not available,2016.0,10.1007/s00224-015-9646-0,Theory of Computing Systems,Elliot2016,False,,Springer,Not available,Assignment Games with Conflicts: Robust Price of Anarchy and Convergence Results via Semi-Smoothness,95f09acb09119ebc9f01d2ff79c0c96a,http://dx.doi.org/10.1007/s00224-015-9646-0
9,We study assignment games in which jobs select machines  and in which certain pairs of jobs may conflict  which is to say they may incur an additional cost when they are both assigned to the same machine  beyond that associated with the increase in load. Questions regarding such interactions apply beyond allocating jobs to machines: when people in a social network choose to align themselves with a group or party  they typically do so based upon not only the inherent quality of that group  but also who amongst their friends (or enemies) chooses that group as well. We show how ,john postl,Not available,2016.0,10.1007/s00224-015-9646-0,Theory of Computing Systems,Elliot2016,False,,Springer,Not available,Assignment Games with Conflicts: Robust Price of Anarchy and Convergence Results via Semi-Smoothness,95f09acb09119ebc9f01d2ff79c0c96a,http://dx.doi.org/10.1007/s00224-015-9646-0
10,We study assignment games in which jobs select machines  and in which certain pairs of jobs may conflict  which is to say they may incur an additional cost when they are both assigned to the same machine  beyond that associated with the increase in load. Questions regarding such interactions apply beyond allocating jobs to machines: when people in a social network choose to align themselves with a group or party  they typically do so based upon not only the inherent quality of that group  but also who amongst their friends (or enemies) chooses that group as well. We show how ,tom wexler,Not available,2016.0,10.1007/s00224-015-9646-0,Theory of Computing Systems,Elliot2016,False,,Springer,Not available,Assignment Games with Conflicts: Robust Price of Anarchy and Convergence Results via Semi-Smoothness,95f09acb09119ebc9f01d2ff79c0c96a,http://dx.doi.org/10.1007/s00224-015-9646-0
11,The Generalized Second Price (GSP) auction used typically to model sponsored search auctions does not include the notion of budget constraints  which is present in practice. Motivated by this  we introduce the different variants of GSP auctions that take budgets into account in natural ways. We examine their stability by focusing on the existence of Nash equilibria and envy-free assignments. We highlight the differences between these mechanisms and find that only some of them exhibit both notions of stability. This shows the importance of carefully picking the right mechanism to ensure stable outcomes in the presence of budgets.,josep diaz,Not available,2016.0,10.1007/s00224-015-9634-4,Theory of Computing Systems,Josep2016,False,,Springer,Not available,On the Stability of Generalized Second Price Auctions with Budgets,a44e816a23f03bce55812dfcdfe4d704,http://dx.doi.org/10.1007/s00224-015-9634-4
12,The Generalized Second Price (GSP) auction used typically to model sponsored search auctions does not include the notion of budget constraints  which is present in practice. Motivated by this  we introduce the different variants of GSP auctions that take budgets into account in natural ways. We examine their stability by focusing on the existence of Nash equilibria and envy-free assignments. We highlight the differences between these mechanisms and find that only some of them exhibit both notions of stability. This shows the importance of carefully picking the right mechanism to ensure stable outcomes in the presence of budgets.,ioannis giotis,Not available,2016.0,10.1007/s00224-015-9634-4,Theory of Computing Systems,Josep2016,False,,Springer,Not available,On the Stability of Generalized Second Price Auctions with Budgets,a44e816a23f03bce55812dfcdfe4d704,http://dx.doi.org/10.1007/s00224-015-9634-4
13,Contrary to early expectations  recent studies have shown near-perfect adherence to HIV antiretrovirals in sub-Saharan Africa We conducted qualitative interviews with patients purchasing low-cost  generic antiretroviral therapy to better understand the social dynamics underlying these findings. We found that concerns for family well-being motivate adherence  yet  the financial sacrifices necessary to secure therapy may paradoxically undermine family welfare. We suggest that missed doses may be more due to a failure to ,j. byakika,Not available,2006.0,10.1007/s10461-006-9080-z,AIDS and Behavior,T.2006,False,,Springer,Not available,The Price of Adherence: Qualitative Findings From HIV Positive Individuals Purchasing Fixed-Dose Combination Generic HIV Antiretroviral Therapy in Kampala  Uganda,3546dd01c0a6376828bbafaaa37b87c7,http://dx.doi.org/10.1007/s10461-006-9080-z
14,The Generalized Second Price (GSP) auction used typically to model sponsored search auctions does not include the notion of budget constraints  which is present in practice. Motivated by this  we introduce the different variants of GSP auctions that take budgets into account in natural ways. We examine their stability by focusing on the existence of Nash equilibria and envy-free assignments. We highlight the differences between these mechanisms and find that only some of them exhibit both notions of stability. This shows the importance of carefully picking the right mechanism to ensure stable outcomes in the presence of budgets.,lefteris kirousis,Not available,2016.0,10.1007/s00224-015-9634-4,Theory of Computing Systems,Josep2016,False,,Springer,Not available,On the Stability of Generalized Second Price Auctions with Budgets,a44e816a23f03bce55812dfcdfe4d704,http://dx.doi.org/10.1007/s00224-015-9634-4
15,The Generalized Second Price (GSP) auction used typically to model sponsored search auctions does not include the notion of budget constraints  which is present in practice. Motivated by this  we introduce the different variants of GSP auctions that take budgets into account in natural ways. We examine their stability by focusing on the existence of Nash equilibria and envy-free assignments. We highlight the differences between these mechanisms and find that only some of them exhibit both notions of stability. This shows the importance of carefully picking the right mechanism to ensure stable outcomes in the presence of budgets.,evangelos markakis,Not available,2016.0,10.1007/s00224-015-9634-4,Theory of Computing Systems,Josep2016,False,,Springer,Not available,On the Stability of Generalized Second Price Auctions with Budgets,a44e816a23f03bce55812dfcdfe4d704,http://dx.doi.org/10.1007/s00224-015-9634-4
16,The Generalized Second Price (GSP) auction used typically to model sponsored search auctions does not include the notion of budget constraints  which is present in practice. Motivated by this  we introduce the different variants of GSP auctions that take budgets into account in natural ways. We examine their stability by focusing on the existence of Nash equilibria and envy-free assignments. We highlight the differences between these mechanisms and find that only some of them exhibit both notions of stability. This shows the importance of carefully picking the right mechanism to ensure stable outcomes in the presence of budgets.,maria serna,Not available,2016.0,10.1007/s00224-015-9634-4,Theory of Computing Systems,Josep2016,False,,Springer,Not available,On the Stability of Generalized Second Price Auctions with Budgets,a44e816a23f03bce55812dfcdfe4d704,http://dx.doi.org/10.1007/s00224-015-9634-4
17,We investigate the impact of heterogeneity in the amount of incoming traffic routed by dispatchers in a non-cooperative load balancing game. For a fixed amount of total incoming traffic  we show that for a broad class of cost functions the worst-case social cost occurs when each dispatcher routes the same amount of traffic  that is  the game is symmetric. Using this result  we give lower bounds on the Price of Anarchy for (i) cost functions that are polynomial on server loads; and (ii) cost functions representing the mean delay of the shortest remaining processing time service discipline.,olivier brun,Not available,2016.0,10.1007/s10479-014-1747-7,Annals of Operations Research,Olivier2016,False,,Springer,Not available,Worst-case analysis of non-cooperative load balancing,a35c54308972d359ec339fda21c2755e,http://dx.doi.org/10.1007/s10479-014-1747-7
18,We investigate the impact of heterogeneity in the amount of incoming traffic routed by dispatchers in a non-cooperative load balancing game. For a fixed amount of total incoming traffic  we show that for a broad class of cost functions the worst-case social cost occurs when each dispatcher routes the same amount of traffic  that is  the game is symmetric. Using this result  we give lower bounds on the Price of Anarchy for (i) cost functions that are polynomial on server loads; and (ii) cost functions representing the mean delay of the shortest remaining processing time service discipline.,balakrishna prabhu,Not available,2016.0,10.1007/s10479-014-1747-7,Annals of Operations Research,Olivier2016,False,,Springer,Not available,Worst-case analysis of non-cooperative load balancing,a35c54308972d359ec339fda21c2755e,http://dx.doi.org/10.1007/s10479-014-1747-7
19,,george christodoulou,Not available,2016.0,10.1007/978-1-4939-2864-4_299,Encyclopedia of Algorithms,George2016,False,,Springer,Not available,Price of Anarchy,fcd6bed110f10ec45e94a927ec4ac7ba,http://dx.doi.org/10.1007/978-1-4939-2864-4_299
20,,artur czumaj,Not available,2016.0,10.1007/978-1-4939-2864-4_300,Encyclopedia of Algorithms,Artur2016,False,,Springer,Not available,Price of Anarchy for Machines Models,9f2ee54d3c95dcdcfdcda39883fd1efe,http://dx.doi.org/10.1007/978-1-4939-2864-4_300
21,,berthold vocking,Not available,2016.0,10.1007/978-1-4939-2864-4_300,Encyclopedia of Algorithms,Artur2016,False,,Springer,Not available,Price of Anarchy for Machines Models,9f2ee54d3c95dcdcfdcda39883fd1efe,http://dx.doi.org/10.1007/978-1-4939-2864-4_300
22,,erik demaine,Not available,2016.0,10.1007/978-1-4939-2864-4_752,Encyclopedia of Algorithms,D.2016,False,,Springer,Not available,Network Creation Games,d22cd8ac4b8a2b411b0a1731451d2935,http://dx.doi.org/10.1007/978-1-4939-2864-4_752
23,,mohammad hajiaghayi,Not available,2016.0,10.1007/978-1-4939-2864-4_752,Encyclopedia of Algorithms,D.2016,False,,Springer,Not available,Network Creation Games,d22cd8ac4b8a2b411b0a1731451d2935,http://dx.doi.org/10.1007/978-1-4939-2864-4_752
24,Contrary to early expectations  recent studies have shown near-perfect adherence to HIV antiretrovirals in sub-Saharan Africa We conducted qualitative interviews with patients purchasing low-cost  generic antiretroviral therapy to better understand the social dynamics underlying these findings. We found that concerns for family well-being motivate adherence  yet  the financial sacrifices necessary to secure therapy may paradoxically undermine family welfare. We suggest that missed doses may be more due to a failure to ,a. moss,Not available,2006.0,10.1007/s10461-006-9080-z,AIDS and Behavior,T.2006,False,,Springer,Not available,The Price of Adherence: Qualitative Findings From HIV Positive Individuals Purchasing Fixed-Dose Combination Generic HIV Antiretroviral Therapy in Kampala  Uganda,3546dd01c0a6376828bbafaaa37b87c7,http://dx.doi.org/10.1007/s10461-006-9080-z
25,,hamid mahini,Not available,2016.0,10.1007/978-1-4939-2864-4_752,Encyclopedia of Algorithms,D.2016,False,,Springer,Not available,Network Creation Games,d22cd8ac4b8a2b411b0a1731451d2935,http://dx.doi.org/10.1007/978-1-4939-2864-4_752
26,,morteza zadimoghaddam,Not available,2016.0,10.1007/978-1-4939-2864-4_752,Encyclopedia of Algorithms,D.2016,False,,Springer,Not available,Network Creation Games,d22cd8ac4b8a2b411b0a1731451d2935,http://dx.doi.org/10.1007/978-1-4939-2864-4_752
27,It is a maxim of Public Choice that voluntary exchanges should not be interfered with by the state. But what makes a voluntary market exchange truly voluntary? We suggest  ,ricardo guzman,Not available,2014.0,10.1007/s11127-013-0090-x,Public Choice,Andrés2014,False,,Springer,Not available,Euvoluntariness and just market exchange: moral dilemmas from Locke’s ,efc084cf7965ee5fc046abdfdf6a5f9d,http://dx.doi.org/10.1007/s11127-013-0090-x
28,It is a maxim of Public Choice that voluntary exchanges should not be interfered with by the state. But what makes a voluntary market exchange truly voluntary? We suggest  ,michael munger,Not available,2014.0,10.1007/s11127-013-0090-x,Public Choice,Andrés2014,False,,Springer,Not available,Euvoluntariness and just market exchange: moral dilemmas from Locke’s ,efc084cf7965ee5fc046abdfdf6a5f9d,http://dx.doi.org/10.1007/s11127-013-0090-x
29,All justice ethics aim at finding balance between liberty and equality  between individual autonomy and the common good. However  each raises objections that demonstrate their own limitations. Three paradigms in which the theories fit will be presented  as well as four models that illustrate how the theories apply to bioethical problems. Moreover  the theoretical perception of justice has set the foundations for a multiplicity of responses given to the most prominent ethical questionings.,michel renaud,Not available,2014.0,10.1007/978-3-319-05544-2_260-1,Encyclopedia of Global Bioethics,Michel2014,False,,Springer,Not available,Justice: Theories of,7b0ddbdbaaa008eae50078d933ad27ea,http://dx.doi.org/10.1007/978-3-319-05544-2_260-1
30,All justice ethics aim at finding balance between liberty and equality  between individual autonomy and the common good. However  each raises objections that demonstrate their own limitations. Three paradigms in which the theories fit will be presented  as well as four models that illustrate how the theories apply to bioethical problems. Moreover  the theoretical perception of justice has set the foundations for a multiplicity of responses given to the most prominent ethical questionings.,cintia aguas,Not available,2014.0,10.1007/978-3-319-05544-2_260-1,Encyclopedia of Global Bioethics,Michel2014,False,,Springer,Not available,Justice: Theories of,7b0ddbdbaaa008eae50078d933ad27ea,http://dx.doi.org/10.1007/978-3-319-05544-2_260-1
31,We focus on the problem of scheduling ,konstantinos kollias,Not available,2013.0,10.1007/s00224-012-9429-9,Theory of Computing Systems,Konstantinos2013,False,,Springer,Not available,Nonpreemptive Coordination Mechanisms for Identical Machines,375535f67e33dc2ebcf6f7a98fb986c0,http://dx.doi.org/10.1007/s00224-012-9429-9
32,In this paper  we present a game analysis of the Binary Exponential Backoff (BEB)  a popular bandwidth allocation mechanism used by a large number of distributed wireless technologies. A Markov chain analysis is used to obtain equilibrium retransmission probabilities and throughput. Numerical results show that when the arrival probability increases  the behavior of mobile stations MSs become more and more aggressive resulting in a global deterioration of the system throughput. We then consider a non-cooperative game framework to study the operation and evaluate the performance of the BEB algorithm when a group of MSs competing with each other to gain access to the wireless channel. We focus our attention to the case when an MS acts selfishly by attempting to gain access to the channel using a higher retransmission probability as a means to increase its own throughput. As a means to improve the system performance  we further explore the use of two transmission mechanisms and policies. First  we introduce the use of multiple power levels (MPLs) for the data transmission. The use of multiple power levels results on a capture effect allowing the receiver to properly decode the message even in the presence of a collision. Under the proposed scheme  named MPL-BEB  the effect of the aggressive behavior  higher transmission probabilities  is diminished since the power level is chosen randomly and independently by each and every station. Second  we introduce a disutility policy for power consumption. The resulting mechanism  named MPL-BEB with costs  is of prime interest in wireless networks composed of battery-powered nodes. Under this scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via price of anarchy  our results identify a behavior similar to the well-know prisoner’s dilemma. A non-efficiency of Nash equilibrium is observed for all schemes (BEB  MPL-BEB  MPL-BEB with costs) under heavy traffic with a notable outperformance of MPL-BEB with costs over both MPL-BEB and BEB.,abdelillah karouit,Not available,2013.0,10.1007/s10852-012-9190-8,Journal of Mathematical Modelling and Algorithms in Operations Research,Abdelillah2013,False,,Springer,Not available,A Stochastic Game Analysis of the Binary Exponential Backoff Algorithm with Multi-Power Diversity and Transmission Cost,d176841bd5a783d7ab3973724188c230,http://dx.doi.org/10.1007/s10852-012-9190-8
33,In this paper  we present a game analysis of the Binary Exponential Backoff (BEB)  a popular bandwidth allocation mechanism used by a large number of distributed wireless technologies. A Markov chain analysis is used to obtain equilibrium retransmission probabilities and throughput. Numerical results show that when the arrival probability increases  the behavior of mobile stations MSs become more and more aggressive resulting in a global deterioration of the system throughput. We then consider a non-cooperative game framework to study the operation and evaluate the performance of the BEB algorithm when a group of MSs competing with each other to gain access to the wireless channel. We focus our attention to the case when an MS acts selfishly by attempting to gain access to the channel using a higher retransmission probability as a means to increase its own throughput. As a means to improve the system performance  we further explore the use of two transmission mechanisms and policies. First  we introduce the use of multiple power levels (MPLs) for the data transmission. The use of multiple power levels results on a capture effect allowing the receiver to properly decode the message even in the presence of a collision. Under the proposed scheme  named MPL-BEB  the effect of the aggressive behavior  higher transmission probabilities  is diminished since the power level is chosen randomly and independently by each and every station. Second  we introduce a disutility policy for power consumption. The resulting mechanism  named MPL-BEB with costs  is of prime interest in wireless networks composed of battery-powered nodes. Under this scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via price of anarchy  our results identify a behavior similar to the well-know prisoner’s dilemma. A non-efficiency of Nash equilibrium is observed for all schemes (BEB  MPL-BEB  MPL-BEB with costs) under heavy traffic with a notable outperformance of MPL-BEB with costs over both MPL-BEB and BEB.,essaid sabir,Not available,2013.0,10.1007/s10852-012-9190-8,Journal of Mathematical Modelling and Algorithms in Operations Research,Abdelillah2013,False,,Springer,Not available,A Stochastic Game Analysis of the Binary Exponential Backoff Algorithm with Multi-Power Diversity and Transmission Cost,d176841bd5a783d7ab3973724188c230,http://dx.doi.org/10.1007/s10852-012-9190-8
34,In this paper  we present a game analysis of the Binary Exponential Backoff (BEB)  a popular bandwidth allocation mechanism used by a large number of distributed wireless technologies. A Markov chain analysis is used to obtain equilibrium retransmission probabilities and throughput. Numerical results show that when the arrival probability increases  the behavior of mobile stations MSs become more and more aggressive resulting in a global deterioration of the system throughput. We then consider a non-cooperative game framework to study the operation and evaluate the performance of the BEB algorithm when a group of MSs competing with each other to gain access to the wireless channel. We focus our attention to the case when an MS acts selfishly by attempting to gain access to the channel using a higher retransmission probability as a means to increase its own throughput. As a means to improve the system performance  we further explore the use of two transmission mechanisms and policies. First  we introduce the use of multiple power levels (MPLs) for the data transmission. The use of multiple power levels results on a capture effect allowing the receiver to properly decode the message even in the presence of a collision. Under the proposed scheme  named MPL-BEB  the effect of the aggressive behavior  higher transmission probabilities  is diminished since the power level is chosen randomly and independently by each and every station. Second  we introduce a disutility policy for power consumption. The resulting mechanism  named MPL-BEB with costs  is of prime interest in wireless networks composed of battery-powered nodes. Under this scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via price of anarchy  our results identify a behavior similar to the well-know prisoner’s dilemma. A non-efficiency of Nash equilibrium is observed for all schemes (BEB  MPL-BEB  MPL-BEB with costs) under heavy traffic with a notable outperformance of MPL-BEB with costs over both MPL-BEB and BEB.,fernando ramirez-mireles,Not available,2013.0,10.1007/s10852-012-9190-8,Journal of Mathematical Modelling and Algorithms in Operations Research,Abdelillah2013,False,,Springer,Not available,A Stochastic Game Analysis of the Binary Exponential Backoff Algorithm with Multi-Power Diversity and Transmission Cost,d176841bd5a783d7ab3973724188c230,http://dx.doi.org/10.1007/s10852-012-9190-8
35,Contrary to early expectations  recent studies have shown near-perfect adherence to HIV antiretrovirals in sub-Saharan Africa We conducted qualitative interviews with patients purchasing low-cost  generic antiretroviral therapy to better understand the social dynamics underlying these findings. We found that concerns for family well-being motivate adherence  yet  the financial sacrifices necessary to secure therapy may paradoxically undermine family welfare. We suggest that missed doses may be more due to a failure to ,p. bourgois,Not available,2006.0,10.1007/s10461-006-9080-z,AIDS and Behavior,T.2006,False,,Springer,Not available,The Price of Adherence: Qualitative Findings From HIV Positive Individuals Purchasing Fixed-Dose Combination Generic HIV Antiretroviral Therapy in Kampala  Uganda,3546dd01c0a6376828bbafaaa37b87c7,http://dx.doi.org/10.1007/s10461-006-9080-z
36,In this paper  we present a game analysis of the Binary Exponential Backoff (BEB)  a popular bandwidth allocation mechanism used by a large number of distributed wireless technologies. A Markov chain analysis is used to obtain equilibrium retransmission probabilities and throughput. Numerical results show that when the arrival probability increases  the behavior of mobile stations MSs become more and more aggressive resulting in a global deterioration of the system throughput. We then consider a non-cooperative game framework to study the operation and evaluate the performance of the BEB algorithm when a group of MSs competing with each other to gain access to the wireless channel. We focus our attention to the case when an MS acts selfishly by attempting to gain access to the channel using a higher retransmission probability as a means to increase its own throughput. As a means to improve the system performance  we further explore the use of two transmission mechanisms and policies. First  we introduce the use of multiple power levels (MPLs) for the data transmission. The use of multiple power levels results on a capture effect allowing the receiver to properly decode the message even in the presence of a collision. Under the proposed scheme  named MPL-BEB  the effect of the aggressive behavior  higher transmission probabilities  is diminished since the power level is chosen randomly and independently by each and every station. Second  we introduce a disutility policy for power consumption. The resulting mechanism  named MPL-BEB with costs  is of prime interest in wireless networks composed of battery-powered nodes. Under this scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via price of anarchy  our results identify a behavior similar to the well-know prisoner’s dilemma. A non-efficiency of Nash equilibrium is observed for all schemes (BEB  MPL-BEB  MPL-BEB with costs) under heavy traffic with a notable outperformance of MPL-BEB with costs over both MPL-BEB and BEB.,luis barbosa,Not available,2013.0,10.1007/s10852-012-9190-8,Journal of Mathematical Modelling and Algorithms in Operations Research,Abdelillah2013,False,,Springer,Not available,A Stochastic Game Analysis of the Binary Exponential Backoff Algorithm with Multi-Power Diversity and Transmission Cost,d176841bd5a783d7ab3973724188c230,http://dx.doi.org/10.1007/s10852-012-9190-8
37,In this paper  we present a game analysis of the Binary Exponential Backoff (BEB)  a popular bandwidth allocation mechanism used by a large number of distributed wireless technologies. A Markov chain analysis is used to obtain equilibrium retransmission probabilities and throughput. Numerical results show that when the arrival probability increases  the behavior of mobile stations MSs become more and more aggressive resulting in a global deterioration of the system throughput. We then consider a non-cooperative game framework to study the operation and evaluate the performance of the BEB algorithm when a group of MSs competing with each other to gain access to the wireless channel. We focus our attention to the case when an MS acts selfishly by attempting to gain access to the channel using a higher retransmission probability as a means to increase its own throughput. As a means to improve the system performance  we further explore the use of two transmission mechanisms and policies. First  we introduce the use of multiple power levels (MPLs) for the data transmission. The use of multiple power levels results on a capture effect allowing the receiver to properly decode the message even in the presence of a collision. Under the proposed scheme  named MPL-BEB  the effect of the aggressive behavior  higher transmission probabilities  is diminished since the power level is chosen randomly and independently by each and every station. Second  we introduce a disutility policy for power consumption. The resulting mechanism  named MPL-BEB with costs  is of prime interest in wireless networks composed of battery-powered nodes. Under this scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via price of anarchy  our results identify a behavior similar to the well-know prisoner’s dilemma. A non-efficiency of Nash equilibrium is observed for all schemes (BEB  MPL-BEB  MPL-BEB with costs) under heavy traffic with a notable outperformance of MPL-BEB with costs over both MPL-BEB and BEB.,abdelkrim haqiq,Not available,2013.0,10.1007/s10852-012-9190-8,Journal of Mathematical Modelling and Algorithms in Operations Research,Abdelillah2013,False,,Springer,Not available,A Stochastic Game Analysis of the Binary Exponential Backoff Algorithm with Multi-Power Diversity and Transmission Cost,d176841bd5a783d7ab3973724188c230,http://dx.doi.org/10.1007/s10852-012-9190-8
38,We consider a model whereby players compete for a set of shared resources to produce and sell substitute products in the same market  which can be viewed as a generalization of the classical Cournot oligopolistic competition model  or  from a different angle  the Wardrop type routing model. In particular  we suppose that there are ,simai he,Not available,2013.0,10.1007/s10898-012-9844-0,Journal of Global Optimization,Simai2013,False,,Springer,Not available,On a generalized Cournot oligopolistic competition game,f0240ce8c1d2fbb6362a107fad009591,http://dx.doi.org/10.1007/s10898-012-9844-0
39,We consider a model whereby players compete for a set of shared resources to produce and sell substitute products in the same market  which can be viewed as a generalization of the classical Cournot oligopolistic competition model  or  from a different angle  the Wardrop type routing model. In particular  we suppose that there are ,xiaoguo wang,Not available,2013.0,10.1007/s10898-012-9844-0,Journal of Global Optimization,Simai2013,False,,Springer,Not available,On a generalized Cournot oligopolistic competition game,f0240ce8c1d2fbb6362a107fad009591,http://dx.doi.org/10.1007/s10898-012-9844-0
40,We consider a model whereby players compete for a set of shared resources to produce and sell substitute products in the same market  which can be viewed as a generalization of the classical Cournot oligopolistic competition model  or  from a different angle  the Wardrop type routing model. In particular  we suppose that there are ,shuzhong zhang,Not available,2013.0,10.1007/s10898-012-9844-0,Journal of Global Optimization,Simai2013,False,,Springer,Not available,On a generalized Cournot oligopolistic competition game,f0240ce8c1d2fbb6362a107fad009591,http://dx.doi.org/10.1007/s10898-012-9844-0
41,We study the price of anarchy and the structure of equilibria in network creation games. A network creation game is played by ,matus mihalak,Not available,2013.0,10.1007/s00224-013-9459-y,Theory of Computing Systems,Matúš2013,False,,Springer,Not available,The Price of Anarchy in Network Creation Games Is (Mostly) Constant,9e3a187ca11096845834402342b63d20,http://dx.doi.org/10.1007/s00224-013-9459-y
42,We study the price of anarchy and the structure of equilibria in network creation games. A network creation game is played by ,jan schlegel,Not available,2013.0,10.1007/s00224-013-9459-y,Theory of Computing Systems,Matúš2013,False,,Springer,Not available,The Price of Anarchy in Network Creation Games Is (Mostly) Constant,9e3a187ca11096845834402342b63d20,http://dx.doi.org/10.1007/s00224-013-9459-y
43,We present three new coordination mechanisms for scheduling ,ioannis caragiannis,Not available,2013.0,10.1007/s00453-012-9650-6,Algorithmica,Ioannis2013,False,,Springer,Not available,Efficient Coordination Mechanisms for Unrelated Machine Scheduling,f57729b86078f1e0e5a3a904bf1084d5,http://dx.doi.org/10.1007/s00453-012-9650-6
44,We consider cut games where players want to cut themselves off from different parts of a network. These games arise when players want to secure themselves from areas of potential infection. For the game-theoretic version of Multiway Cut  we prove that the price of stability is 1  i.e.  there exists a Nash equilibrium as good as the centralized optimum. For the game-theoretic version of Multicut  we show that there exists a 2-approximate equilibrium as good as the centralized optimum. We also give poly-time algorithms for finding exact and approximate equilibria in these games.,elliot anshelevich,Not available,2013.0,10.1007/s00224-011-9380-1,Theory of Computing Systems,Elliot2013,False,,Springer,Not available,Strategic Multiway Cut and Multicut Games,521fb5a76051b399f41947a9294af0a7,http://dx.doi.org/10.1007/s00224-011-9380-1
45,We consider cut games where players want to cut themselves off from different parts of a network. These games arise when players want to secure themselves from areas of potential infection. For the game-theoretic version of Multiway Cut  we prove that the price of stability is 1  i.e.  there exists a Nash equilibrium as good as the centralized optimum. For the game-theoretic version of Multicut  we show that there exists a 2-approximate equilibrium as good as the centralized optimum. We also give poly-time algorithms for finding exact and approximate equilibria in these games.,bugra caskurlu,Not available,2013.0,10.1007/s00224-011-9380-1,Theory of Computing Systems,Elliot2013,False,,Springer,Not available,Strategic Multiway Cut and Multicut Games,521fb5a76051b399f41947a9294af0a7,http://dx.doi.org/10.1007/s00224-011-9380-1
46,Contrary to early expectations  recent studies have shown near-perfect adherence to HIV antiretrovirals in sub-Saharan Africa We conducted qualitative interviews with patients purchasing low-cost  generic antiretroviral therapy to better understand the social dynamics underlying these findings. We found that concerns for family well-being motivate adherence  yet  the financial sacrifices necessary to secure therapy may paradoxically undermine family welfare. We suggest that missed doses may be more due to a failure to ,d. bangsberg,Not available,2006.0,10.1007/s10461-006-9080-z,AIDS and Behavior,T.2006,False,,Springer,Not available,The Price of Adherence: Qualitative Findings From HIV Positive Individuals Purchasing Fixed-Dose Combination Generic HIV Antiretroviral Therapy in Kampala  Uganda,3546dd01c0a6376828bbafaaa37b87c7,http://dx.doi.org/10.1007/s10461-006-9080-z
47,We consider cut games where players want to cut themselves off from different parts of a network. These games arise when players want to secure themselves from areas of potential infection. For the game-theoretic version of Multiway Cut  we prove that the price of stability is 1  i.e.  there exists a Nash equilibrium as good as the centralized optimum. For the game-theoretic version of Multicut  we show that there exists a 2-approximate equilibrium as good as the centralized optimum. We also give poly-time algorithms for finding exact and approximate equilibria in these games.,ameya hate,Not available,2013.0,10.1007/s00224-011-9380-1,Theory of Computing Systems,Elliot2013,False,,Springer,Not available,Strategic Multiway Cut and Multicut Games,521fb5a76051b399f41947a9294af0a7,http://dx.doi.org/10.1007/s00224-011-9380-1
48,The Internet has emerged as perhaps the most important network in modern computing  but rather miraculously  it was created through the individual actions of a multitude of agents rather than by a central planning authority. This motivates the game theoretic study of network formation  and our paper considers one of the most-well studied models  originally proposed by Fabrikant et al. In it  each of ,ronald graham,Not available,2013.0,10.1007/978-3-319-03536-9_17,Algorithms and Models for the Web Graph,Ronald2013,False,,Springer,Not available,Anarchy Is Free in Network Creation,db204103043cd662c972f58331663e04,http://dx.doi.org/10.1007/978-3-319-03536-9_17
49,The Internet has emerged as perhaps the most important network in modern computing  but rather miraculously  it was created through the individual actions of a multitude of agents rather than by a central planning authority. This motivates the game theoretic study of network formation  and our paper considers one of the most-well studied models  originally proposed by Fabrikant et al. In it  each of ,linus hamilton,Not available,2013.0,10.1007/978-3-319-03536-9_17,Algorithms and Models for the Web Graph,Ronald2013,False,,Springer,Not available,Anarchy Is Free in Network Creation,db204103043cd662c972f58331663e04,http://dx.doi.org/10.1007/978-3-319-03536-9_17
50,The Internet has emerged as perhaps the most important network in modern computing  but rather miraculously  it was created through the individual actions of a multitude of agents rather than by a central planning authority. This motivates the game theoretic study of network formation  and our paper considers one of the most-well studied models  originally proposed by Fabrikant et al. In it  each of ,ariel levavi,Not available,2013.0,10.1007/978-3-319-03536-9_17,Algorithms and Models for the Web Graph,Ronald2013,False,,Springer,Not available,Anarchy Is Free in Network Creation,db204103043cd662c972f58331663e04,http://dx.doi.org/10.1007/978-3-319-03536-9_17
51,The Internet has emerged as perhaps the most important network in modern computing  but rather miraculously  it was created through the individual actions of a multitude of agents rather than by a central planning authority. This motivates the game theoretic study of network formation  and our paper considers one of the most-well studied models  originally proposed by Fabrikant et al. In it  each of ,po-shen loh,Not available,2013.0,10.1007/978-3-319-03536-9_17,Algorithms and Models for the Web Graph,Ronald2013,False,,Springer,Not available,Anarchy Is Free in Network Creation,db204103043cd662c972f58331663e04,http://dx.doi.org/10.1007/978-3-319-03536-9_17
52,Historically  the analysis of matching has centered on designing algorithms to produce stable matchings as well as on analyzing the incentive compatibility of matching mechanisms. Less attention has been paid to questions related to the social welfare of stable matchings in cardinal utility models. We examine the loss in social welfare that arises from requiring matchings to be stable  the natural equilibrium concept under individual rationality. While this loss can be arbitrarily bad under general preferences  when there is some structure to the underlying graph corresponding to natural conditions on preferences  we prove worst case bounds on the price of anarchy. Surprisingly  under simple distributions of utilities  the average case loss turns out to be significantly smaller than the worst-case analysis would suggest. Furthermore  we derive conditions for the existence of approximately stable matchings that are also close to socially optimal  demonstrating that adding small switching costs can make socially (near-)optimal matchings stable. Our analysis leads to several concomitant results of interest on the convergence of decentralized partner-switching algorithms  and on the impact of heterogeneity of tastes on social welfare.,elliot anshelevich,Not available,2013.0,10.1007/s10458-011-9184-3,Autonomous Agents and Multi-Agent Systems,Elliot2013,False,,Springer,Not available,Anarchy  stability  and utopia: creating better matchings,d575115360866aef8fbaf30a0faa0d56,http://dx.doi.org/10.1007/s10458-011-9184-3
53,Historically  the analysis of matching has centered on designing algorithms to produce stable matchings as well as on analyzing the incentive compatibility of matching mechanisms. Less attention has been paid to questions related to the social welfare of stable matchings in cardinal utility models. We examine the loss in social welfare that arises from requiring matchings to be stable  the natural equilibrium concept under individual rationality. While this loss can be arbitrarily bad under general preferences  when there is some structure to the underlying graph corresponding to natural conditions on preferences  we prove worst case bounds on the price of anarchy. Surprisingly  under simple distributions of utilities  the average case loss turns out to be significantly smaller than the worst-case analysis would suggest. Furthermore  we derive conditions for the existence of approximately stable matchings that are also close to socially optimal  demonstrating that adding small switching costs can make socially (near-)optimal matchings stable. Our analysis leads to several concomitant results of interest on the convergence of decentralized partner-switching algorithms  and on the impact of heterogeneity of tastes on social welfare.,sanmay das,Not available,2013.0,10.1007/s10458-011-9184-3,Autonomous Agents and Multi-Agent Systems,Elliot2013,False,,Springer,Not available,Anarchy  stability  and utopia: creating better matchings,d575115360866aef8fbaf30a0faa0d56,http://dx.doi.org/10.1007/s10458-011-9184-3
54,Historically  the analysis of matching has centered on designing algorithms to produce stable matchings as well as on analyzing the incentive compatibility of matching mechanisms. Less attention has been paid to questions related to the social welfare of stable matchings in cardinal utility models. We examine the loss in social welfare that arises from requiring matchings to be stable  the natural equilibrium concept under individual rationality. While this loss can be arbitrarily bad under general preferences  when there is some structure to the underlying graph corresponding to natural conditions on preferences  we prove worst case bounds on the price of anarchy. Surprisingly  under simple distributions of utilities  the average case loss turns out to be significantly smaller than the worst-case analysis would suggest. Furthermore  we derive conditions for the existence of approximately stable matchings that are also close to socially optimal  demonstrating that adding small switching costs can make socially (near-)optimal matchings stable. Our analysis leads to several concomitant results of interest on the convergence of decentralized partner-switching algorithms  and on the impact of heterogeneity of tastes on social welfare.,yonatan naamad,Not available,2013.0,10.1007/s10458-011-9184-3,Autonomous Agents and Multi-Agent Systems,Elliot2013,False,,Springer,Not available,Anarchy  stability  and utopia: creating better matchings,d575115360866aef8fbaf30a0faa0d56,http://dx.doi.org/10.1007/s10458-011-9184-3
55,"We investigate the convergence of the price of anarchy after a limited number of moves in the classical multicast communication game when the underlying communication network is directed. Namely  a subset of nodes of the network are interested in receiving the transmission from a given source node and can share the cost of the used links according to fixed cost sharing methods. At each step  a single receiver is allowed to modify its communication strategy  that is to select a communication path from the source  and assuming a selfish or rational behavior  it will make a best response move  that is it will select a solution yielding the minimum possible payment or shared cost. We determine lower and upper bounds on the price of anarchy  that is the highest possible ratio among the overall cost of the links used by the receivers and the minimum possible cost realizing the required communications  after a limited number of moves under the fundamental Shapley cost sharing method. In particular  assuming that the initial set of connecting paths can be arbitrary  we show an 
",angelo fanelli,Not available,2010.0,10.1007/s00453-008-9212-0,Algorithmica,Angelo2010,False,,Springer,Not available,On the Convergence of Multicast Games in Directed Networks,d0f698dd7c372bcbeaf215ca89a3b678,http://dx.doi.org/10.1007/s00453-008-9212-0
56,"We investigate the convergence of the price of anarchy after a limited number of moves in the classical multicast communication game when the underlying communication network is directed. Namely  a subset of nodes of the network are interested in receiving the transmission from a given source node and can share the cost of the used links according to fixed cost sharing methods. At each step  a single receiver is allowed to modify its communication strategy  that is to select a communication path from the source  and assuming a selfish or rational behavior  it will make a best response move  that is it will select a solution yielding the minimum possible payment or shared cost. We determine lower and upper bounds on the price of anarchy  that is the highest possible ratio among the overall cost of the links used by the receivers and the minimum possible cost realizing the required communications  after a limited number of moves under the fundamental Shapley cost sharing method. In particular  assuming that the initial set of connecting paths can be arbitrary  we show an 
",michele flammini,Not available,2010.0,10.1007/s00453-008-9212-0,Algorithmica,Angelo2010,False,,Springer,Not available,On the Convergence of Multicast Games in Directed Networks,d0f698dd7c372bcbeaf215ca89a3b678,http://dx.doi.org/10.1007/s00453-008-9212-0
57,In this work  we consider ,dominic dumrauf,Not available,2006.0,10.1007/11944874_29,Internet and Network Economics,Dominic2006,False,,Springer,Not available,Price of Anarchy for Polynomial Wardrop Games,fcb638cf3582182b2975c543abe4709e,http://dx.doi.org/10.1007/11944874_29
58,"We investigate the convergence of the price of anarchy after a limited number of moves in the classical multicast communication game when the underlying communication network is directed. Namely  a subset of nodes of the network are interested in receiving the transmission from a given source node and can share the cost of the used links according to fixed cost sharing methods. At each step  a single receiver is allowed to modify its communication strategy  that is to select a communication path from the source  and assuming a selfish or rational behavior  it will make a best response move  that is it will select a solution yielding the minimum possible payment or shared cost. We determine lower and upper bounds on the price of anarchy  that is the highest possible ratio among the overall cost of the links used by the receivers and the minimum possible cost realizing the required communications  after a limited number of moves under the fundamental Shapley cost sharing method. In particular  assuming that the initial set of connecting paths can be arbitrary  we show an 
",luca moscardelli,Not available,2010.0,10.1007/s00453-008-9212-0,Algorithmica,Angelo2010,False,,Springer,Not available,On the Convergence of Multicast Games in Directed Networks,d0f698dd7c372bcbeaf215ca89a3b678,http://dx.doi.org/10.1007/s00453-008-9212-0
59,Efficient spectrum-sharing mechanisms are crucial to alleviate the bandwidth limitation in wireless networks. In this paper  we consider the following question: can free spectrum be shared efficiently? We study this problem in the context of 802.11 or WiFi networks. Each access point (AP) in a WiFi network must be assigned a channel for it to service users. There are only finitely many possible channels that can be assigned. Moreover  neighboring access points must use different channels so as to avoid interference. Currently these channels are assigned by administrators who carefully consider channel conflicts and network loads. Channel conflicts among APs operated by different entities are currently resolved in an ad hoc manner (i.e.  not in a coordinated way) or not resolved at all. We view the channel assignment problem as a game  where the players are the service providers and APs are acquired sequentially. We consider the price of anarchy of this game  which is the ratio between the total coverage of the APs in the worst Nash equilibrium of the game and what the total coverage of the APs would be if the channel assignment were done optimally by a central authority. We provide bounds on the price of anarchy depending on assumptions on the underlying network and the type of bargaining allowed between service providers. The key tool in the analysis is the identification of the Nash equilibria with the solutions to a maximal coloring problem in an appropriate graph. We relate the price of anarchy of these games to the approximation factor of local optimization algorithms for the maximum ,magnus halldorsson,Not available,2010.0,10.1007/s00446-010-0098-0,Distributed Computing,M.2010,False,,Springer,Not available,On spectrum sharing games,a27d9f2a8416792a88fd03419e9fc4db,http://dx.doi.org/10.1007/s00446-010-0098-0
60,Efficient spectrum-sharing mechanisms are crucial to alleviate the bandwidth limitation in wireless networks. In this paper  we consider the following question: can free spectrum be shared efficiently? We study this problem in the context of 802.11 or WiFi networks. Each access point (AP) in a WiFi network must be assigned a channel for it to service users. There are only finitely many possible channels that can be assigned. Moreover  neighboring access points must use different channels so as to avoid interference. Currently these channels are assigned by administrators who carefully consider channel conflicts and network loads. Channel conflicts among APs operated by different entities are currently resolved in an ad hoc manner (i.e.  not in a coordinated way) or not resolved at all. We view the channel assignment problem as a game  where the players are the service providers and APs are acquired sequentially. We consider the price of anarchy of this game  which is the ratio between the total coverage of the APs in the worst Nash equilibrium of the game and what the total coverage of the APs would be if the channel assignment were done optimally by a central authority. We provide bounds on the price of anarchy depending on assumptions on the underlying network and the type of bargaining allowed between service providers. The key tool in the analysis is the identification of the Nash equilibria with the solutions to a maximal coloring problem in an appropriate graph. We relate the price of anarchy of these games to the approximation factor of local optimization algorithms for the maximum ,joseph halpern,Not available,2010.0,10.1007/s00446-010-0098-0,Distributed Computing,M.2010,False,,Springer,Not available,On spectrum sharing games,a27d9f2a8416792a88fd03419e9fc4db,http://dx.doi.org/10.1007/s00446-010-0098-0
61,Efficient spectrum-sharing mechanisms are crucial to alleviate the bandwidth limitation in wireless networks. In this paper  we consider the following question: can free spectrum be shared efficiently? We study this problem in the context of 802.11 or WiFi networks. Each access point (AP) in a WiFi network must be assigned a channel for it to service users. There are only finitely many possible channels that can be assigned. Moreover  neighboring access points must use different channels so as to avoid interference. Currently these channels are assigned by administrators who carefully consider channel conflicts and network loads. Channel conflicts among APs operated by different entities are currently resolved in an ad hoc manner (i.e.  not in a coordinated way) or not resolved at all. We view the channel assignment problem as a game  where the players are the service providers and APs are acquired sequentially. We consider the price of anarchy of this game  which is the ratio between the total coverage of the APs in the worst Nash equilibrium of the game and what the total coverage of the APs would be if the channel assignment were done optimally by a central authority. We provide bounds on the price of anarchy depending on assumptions on the underlying network and the type of bargaining allowed between service providers. The key tool in the analysis is the identification of the Nash equilibria with the solutions to a maximal coloring problem in an appropriate graph. We relate the price of anarchy of these games to the approximation factor of local optimization algorithms for the maximum ,li li,Not available,2010.0,10.1007/s00446-010-0098-0,Distributed Computing,M.2010,False,,Springer,Not available,On spectrum sharing games,a27d9f2a8416792a88fd03419e9fc4db,http://dx.doi.org/10.1007/s00446-010-0098-0
62,Efficient spectrum-sharing mechanisms are crucial to alleviate the bandwidth limitation in wireless networks. In this paper  we consider the following question: can free spectrum be shared efficiently? We study this problem in the context of 802.11 or WiFi networks. Each access point (AP) in a WiFi network must be assigned a channel for it to service users. There are only finitely many possible channels that can be assigned. Moreover  neighboring access points must use different channels so as to avoid interference. Currently these channels are assigned by administrators who carefully consider channel conflicts and network loads. Channel conflicts among APs operated by different entities are currently resolved in an ad hoc manner (i.e.  not in a coordinated way) or not resolved at all. We view the channel assignment problem as a game  where the players are the service providers and APs are acquired sequentially. We consider the price of anarchy of this game  which is the ratio between the total coverage of the APs in the worst Nash equilibrium of the game and what the total coverage of the APs would be if the channel assignment were done optimally by a central authority. We provide bounds on the price of anarchy depending on assumptions on the underlying network and the type of bargaining allowed between service providers. The key tool in the analysis is the identification of the Nash equilibria with the solutions to a maximal coloring problem in an appropriate graph. We relate the price of anarchy of these games to the approximation factor of local optimization algorithms for the maximum ,vahab mirrokni,Not available,2010.0,10.1007/s00446-010-0098-0,Distributed Computing,M.2010,False,,Springer,Not available,On spectrum sharing games,a27d9f2a8416792a88fd03419e9fc4db,http://dx.doi.org/10.1007/s00446-010-0098-0
63,We study selfish routing in ring networks with respect to minimizing the maximum latency. Our main result is an establishment of constant bounds on the price of stability (PoS) for routing unsplittable flows with linear latency. We show that the PoS is at most 6.83  which reduces to 4.57 when the linear latency functions are homogeneous. We also show the existence of a (54 1)-approximate Nash equilibrium. Additionally we address some algorithmic issues for computing an approximate Nash equilibrium.,bo chen,Not available,2010.0,10.1007/s10878-008-9171-z,Journal of Combinatorial Optimization,Bo2010,False,,Springer,Not available,The price of atomic selfish ring routing,4ba89cca52e9517e1a6e09a4ad435035,http://dx.doi.org/10.1007/s10878-008-9171-z
64,We study selfish routing in ring networks with respect to minimizing the maximum latency. Our main result is an establishment of constant bounds on the price of stability (PoS) for routing unsplittable flows with linear latency. We show that the PoS is at most 6.83  which reduces to 4.57 when the linear latency functions are homogeneous. We also show the existence of a (54 1)-approximate Nash equilibrium. Additionally we address some algorithmic issues for computing an approximate Nash equilibrium.,xujin chen,Not available,2010.0,10.1007/s10878-008-9171-z,Journal of Combinatorial Optimization,Bo2010,False,,Springer,Not available,The price of atomic selfish ring routing,4ba89cca52e9517e1a6e09a4ad435035,http://dx.doi.org/10.1007/s10878-008-9171-z
65,We study selfish routing in ring networks with respect to minimizing the maximum latency. Our main result is an establishment of constant bounds on the price of stability (PoS) for routing unsplittable flows with linear latency. We show that the PoS is at most 6.83  which reduces to 4.57 when the linear latency functions are homogeneous. We also show the existence of a (54 1)-approximate Nash equilibrium. Additionally we address some algorithmic issues for computing an approximate Nash equilibrium.,xiaodong hu,Not available,2010.0,10.1007/s10878-008-9171-z,Journal of Combinatorial Optimization,Bo2010,False,,Springer,Not available,The price of atomic selfish ring routing,4ba89cca52e9517e1a6e09a4ad435035,http://dx.doi.org/10.1007/s10878-008-9171-z
66,Network creation games have been studied in many different settings recently. These games are motivated by social networks in which selfish agents want to construct a connection graph among themselves. Each node wants to minimize its average or maximum distance to the others  without paying much to construct the network. Many generalizations have been considered  including non-uniform interests between nodes  general graphs of allowable edges  bounded budget agents  etc. In all of these settings  there is no known constant bound on the price of anarchy. In fact  in many cases  the price of anarchy can be very large  namely  a constant power of the number of agents. This means that we have no control on the behavior of network when agents act selfishly. On the other hand  the price of stability in all these models is constant  which means that there is chance that agents act selfishly and we end up with a reasonable social cost.In this paper  we show how to use an advertising campaign (as introduced in SODA 2009 [2]) to find such efficient equilibria. More formally  we present advertising strategies such that  if an ,erik demaine,Not available,2010.0,10.1007/978-3-642-18009-5_12,Algorithms and Models for the Web-Graph,D.2010,False,,Springer,Not available,Constant Price of Anarchy in Network Creation Games via Public Service Advertising,4ed6429c04f27f429fc8c82aebd74961,http://dx.doi.org/10.1007/978-3-642-18009-5_12
67,Network creation games have been studied in many different settings recently. These games are motivated by social networks in which selfish agents want to construct a connection graph among themselves. Each node wants to minimize its average or maximum distance to the others  without paying much to construct the network. Many generalizations have been considered  including non-uniform interests between nodes  general graphs of allowable edges  bounded budget agents  etc. In all of these settings  there is no known constant bound on the price of anarchy. In fact  in many cases  the price of anarchy can be very large  namely  a constant power of the number of agents. This means that we have no control on the behavior of network when agents act selfishly. On the other hand  the price of stability in all these models is constant  which means that there is chance that agents act selfishly and we end up with a reasonable social cost.In this paper  we show how to use an advertising campaign (as introduced in SODA 2009 [2]) to find such efficient equilibria. More formally  we present advertising strategies such that  if an ,morteza zadimoghaddam,Not available,2010.0,10.1007/978-3-642-18009-5_12,Algorithms and Models for the Web-Graph,D.2010,False,,Springer,Not available,Constant Price of Anarchy in Network Creation Games via Public Service Advertising,4ed6429c04f27f429fc8c82aebd74961,http://dx.doi.org/10.1007/978-3-642-18009-5_12
68,In this work  we consider ,martin gairing,Not available,2006.0,10.1007/11944874_29,Internet and Network Economics,Dominic2006,False,,Springer,Not available,Price of Anarchy for Polynomial Wardrop Games,fcb638cf3582182b2975c543abe4709e,http://dx.doi.org/10.1007/11944874_29
69,In this chapter we consider fundamental optimization problems arising in communication networks. We consider scenarios where there is no central authority that coordinates the network users in order to achieve efficient solutions. Instead  the users act in an uncoordinated and selfish manner and reach solutions to the above problems that are consistent only with their selfishness. In this sense  the users act aiming to optimize their own objectives with no regard to the globally optimum system performance. Such a behavior poses several intriguing questions ranging from the definition of reasonable and practical models for studying it to the quantification of the efficiency loss due to the lack of users’ cooperation. We present several results we achieved recently in this research area and propose interesting future research directions.,vittorio bilo,Not available,2010.0,10.1007/978-3-642-02250-0_9,Graphs and Algorithms in Communication Networks,Vittorio2010,False,,Springer,Not available,Game-Theoretic Approaches to Optimization Problems in Communication Networks,2edbed58851f9af4ba4c905577f405eb,http://dx.doi.org/10.1007/978-3-642-02250-0_9
70,In this chapter we consider fundamental optimization problems arising in communication networks. We consider scenarios where there is no central authority that coordinates the network users in order to achieve efficient solutions. Instead  the users act in an uncoordinated and selfish manner and reach solutions to the above problems that are consistent only with their selfishness. In this sense  the users act aiming to optimize their own objectives with no regard to the globally optimum system performance. Such a behavior poses several intriguing questions ranging from the definition of reasonable and practical models for studying it to the quantification of the efficiency loss due to the lack of users’ cooperation. We present several results we achieved recently in this research area and propose interesting future research directions.,ioannis caragiannis,Not available,2010.0,10.1007/978-3-642-02250-0_9,Graphs and Algorithms in Communication Networks,Vittorio2010,False,,Springer,Not available,Game-Theoretic Approaches to Optimization Problems in Communication Networks,2edbed58851f9af4ba4c905577f405eb,http://dx.doi.org/10.1007/978-3-642-02250-0_9
71,In this chapter we consider fundamental optimization problems arising in communication networks. We consider scenarios where there is no central authority that coordinates the network users in order to achieve efficient solutions. Instead  the users act in an uncoordinated and selfish manner and reach solutions to the above problems that are consistent only with their selfishness. In this sense  the users act aiming to optimize their own objectives with no regard to the globally optimum system performance. Such a behavior poses several intriguing questions ranging from the definition of reasonable and practical models for studying it to the quantification of the efficiency loss due to the lack of users’ cooperation. We present several results we achieved recently in this research area and propose interesting future research directions.,angelo fanelli,Not available,2010.0,10.1007/978-3-642-02250-0_9,Graphs and Algorithms in Communication Networks,Vittorio2010,False,,Springer,Not available,Game-Theoretic Approaches to Optimization Problems in Communication Networks,2edbed58851f9af4ba4c905577f405eb,http://dx.doi.org/10.1007/978-3-642-02250-0_9
72,In this chapter we consider fundamental optimization problems arising in communication networks. We consider scenarios where there is no central authority that coordinates the network users in order to achieve efficient solutions. Instead  the users act in an uncoordinated and selfish manner and reach solutions to the above problems that are consistent only with their selfishness. In this sense  the users act aiming to optimize their own objectives with no regard to the globally optimum system performance. Such a behavior poses several intriguing questions ranging from the definition of reasonable and practical models for studying it to the quantification of the efficiency loss due to the lack of users’ cooperation. We present several results we achieved recently in this research area and propose interesting future research directions.,michele flammini,Not available,2010.0,10.1007/978-3-642-02250-0_9,Graphs and Algorithms in Communication Networks,Vittorio2010,False,,Springer,Not available,Game-Theoretic Approaches to Optimization Problems in Communication Networks,2edbed58851f9af4ba4c905577f405eb,http://dx.doi.org/10.1007/978-3-642-02250-0_9
73,In this chapter we consider fundamental optimization problems arising in communication networks. We consider scenarios where there is no central authority that coordinates the network users in order to achieve efficient solutions. Instead  the users act in an uncoordinated and selfish manner and reach solutions to the above problems that are consistent only with their selfishness. In this sense  the users act aiming to optimize their own objectives with no regard to the globally optimum system performance. Such a behavior poses several intriguing questions ranging from the definition of reasonable and practical models for studying it to the quantification of the efficiency loss due to the lack of users’ cooperation. We present several results we achieved recently in this research area and propose interesting future research directions.,christos kaklamanis,Not available,2010.0,10.1007/978-3-642-02250-0_9,Graphs and Algorithms in Communication Networks,Vittorio2010,False,,Springer,Not available,Game-Theoretic Approaches to Optimization Problems in Communication Networks,2edbed58851f9af4ba4c905577f405eb,http://dx.doi.org/10.1007/978-3-642-02250-0_9
74,In this chapter we consider fundamental optimization problems arising in communication networks. We consider scenarios where there is no central authority that coordinates the network users in order to achieve efficient solutions. Instead  the users act in an uncoordinated and selfish manner and reach solutions to the above problems that are consistent only with their selfishness. In this sense  the users act aiming to optimize their own objectives with no regard to the globally optimum system performance. Such a behavior poses several intriguing questions ranging from the definition of reasonable and practical models for studying it to the quantification of the efficiency loss due to the lack of users’ cooperation. We present several results we achieved recently in this research area and propose interesting future research directions.,gianpiero monaco,Not available,2010.0,10.1007/978-3-642-02250-0_9,Graphs and Algorithms in Communication Networks,Vittorio2010,False,,Springer,Not available,Game-Theoretic Approaches to Optimization Problems in Communication Networks,2edbed58851f9af4ba4c905577f405eb,http://dx.doi.org/10.1007/978-3-642-02250-0_9
75,In this chapter we consider fundamental optimization problems arising in communication networks. We consider scenarios where there is no central authority that coordinates the network users in order to achieve efficient solutions. Instead  the users act in an uncoordinated and selfish manner and reach solutions to the above problems that are consistent only with their selfishness. In this sense  the users act aiming to optimize their own objectives with no regard to the globally optimum system performance. Such a behavior poses several intriguing questions ranging from the definition of reasonable and practical models for studying it to the quantification of the efficiency loss due to the lack of users’ cooperation. We present several results we achieved recently in this research area and propose interesting future research directions.,luca moscardelli,Not available,2010.0,10.1007/978-3-642-02250-0_9,Graphs and Algorithms in Communication Networks,Vittorio2010,False,,Springer,Not available,Game-Theoretic Approaches to Optimization Problems in Communication Networks,2edbed58851f9af4ba4c905577f405eb,http://dx.doi.org/10.1007/978-3-642-02250-0_9
76,This paper studies the selfish routing game in ring networks with a load-dependent linear latency on each link. We adopt the asymmetric atomic routing model. Each player selfishly chooses a route to connect his source-destination pair  aiming at a lowest latency of his route  while the system objective is to minimize the maximum latency among all routes of players. Such a routing game always has a Nash equilibrium (NE) that is a “stable state” among all players  from which no player has the incentive to deviate unilaterally. Furthermore  16 is the current best upper bound on its price of anarchy (PoA)  the worst-case ratio between the maximum latencies in a NE and in a system optimum. In this paper we show that the PoA is at most 10.16 provided cooperations within pairs of players are allowed  where any two players could change their routes simultaneously if neither would experience a longer latency and at least one would experience a shorter latency.,xujin chen,Not available,2010.0,10.1007/978-3-642-17461-2_3,Combinatorial Optimization and Applications,Xujin2010,False,,Springer,Not available,Reducing the Maximum Latency of Selfish Ring Routing via Pairwise Cooperations,1ed8294379f6ab6a5545e4147dd03d96,http://dx.doi.org/10.1007/978-3-642-17461-2_3
77,This paper studies the selfish routing game in ring networks with a load-dependent linear latency on each link. We adopt the asymmetric atomic routing model. Each player selfishly chooses a route to connect his source-destination pair  aiming at a lowest latency of his route  while the system objective is to minimize the maximum latency among all routes of players. Such a routing game always has a Nash equilibrium (NE) that is a “stable state” among all players  from which no player has the incentive to deviate unilaterally. Furthermore  16 is the current best upper bound on its price of anarchy (PoA)  the worst-case ratio between the maximum latencies in a NE and in a system optimum. In this paper we show that the PoA is at most 10.16 provided cooperations within pairs of players are allowed  where any two players could change their routes simultaneously if neither would experience a longer latency and at least one would experience a shorter latency.,xiaodong hu,Not available,2010.0,10.1007/978-3-642-17461-2_3,Combinatorial Optimization and Applications,Xujin2010,False,,Springer,Not available,Reducing the Maximum Latency of Selfish Ring Routing via Pairwise Cooperations,1ed8294379f6ab6a5545e4147dd03d96,http://dx.doi.org/10.1007/978-3-642-17461-2_3
78,This paper studies the selfish routing game in ring networks with a load-dependent linear latency on each link. We adopt the asymmetric atomic routing model. Each player selfishly chooses a route to connect his source-destination pair  aiming at a lowest latency of his route  while the system objective is to minimize the maximum latency among all routes of players. Such a routing game always has a Nash equilibrium (NE) that is a “stable state” among all players  from which no player has the incentive to deviate unilaterally. Furthermore  16 is the current best upper bound on its price of anarchy (PoA)  the worst-case ratio between the maximum latencies in a NE and in a system optimum. In this paper we show that the PoA is at most 10.16 provided cooperations within pairs of players are allowed  where any two players could change their routes simultaneously if neither would experience a longer latency and at least one would experience a shorter latency.,weidong ma,Not available,2010.0,10.1007/978-3-642-17461-2_3,Combinatorial Optimization and Applications,Xujin2010,False,,Springer,Not available,Reducing the Maximum Latency of Selfish Ring Routing via Pairwise Cooperations,1ed8294379f6ab6a5545e4147dd03d96,http://dx.doi.org/10.1007/978-3-642-17461-2_3
79,We show exact values for the price of anarchy of weighted and unweighted congestion games with polynomial latency functions. The given values also hold for weighted and unweighted ,sebastian aland,Not available,2006.0,10.1007/11672142_17,STACS 2006,Sebastian2006,False,,Springer,Not available,Exact Price of Anarchy for Polynomial Congestion Games,245a0c76ddfba9cc496ac7b222f4ca7d,http://dx.doi.org/10.1007/11672142_17
80,Mobile ad hoc and sensor networks often contain a mixture of nodes  some of which may be selfish and non-cooperative in providing network services such as forwarding packets in order to conserve energy. Existing trust management protocols for mobile ad hoc networks (MANETs) advocate isolating selfish nodes as soon as they are detected. Further  altruistic behaviors are encouraged with incentive mechanisms. In this paper  we propose and analyze a trust management protocol based on the demand and pricing theory for managing group communication systems where system survivability is highly critical to mission execution. Rather than always encouraging altruistic behaviors  we consider the tradeoff between a node’s individual welfare (e.g.  saving energy for survivability) versus global welfare (e.g.  providing service availability) and identify the best design condition so that the system lifetime is maximized while the mission requirements are satisfied.,jin-hee cho,Not available,2010.0,10.1007/978-3-642-13446-3_10,Trust Management IV,Jin-Hee2010,False,,Springer,Not available,Modeling and Analysis of Trust Management Protocols: Altruism versus Selfishness in MANETs,799f9bd47ace3c92a5b6200626df7703,http://dx.doi.org/10.1007/978-3-642-13446-3_10
81,Mobile ad hoc and sensor networks often contain a mixture of nodes  some of which may be selfish and non-cooperative in providing network services such as forwarding packets in order to conserve energy. Existing trust management protocols for mobile ad hoc networks (MANETs) advocate isolating selfish nodes as soon as they are detected. Further  altruistic behaviors are encouraged with incentive mechanisms. In this paper  we propose and analyze a trust management protocol based on the demand and pricing theory for managing group communication systems where system survivability is highly critical to mission execution. Rather than always encouraging altruistic behaviors  we consider the tradeoff between a node’s individual welfare (e.g.  saving energy for survivability) versus global welfare (e.g.  providing service availability) and identify the best design condition so that the system lifetime is maximized while the mission requirements are satisfied.,ananthram swami,Not available,2010.0,10.1007/978-3-642-13446-3_10,Trust Management IV,Jin-Hee2010,False,,Springer,Not available,Modeling and Analysis of Trust Management Protocols: Altruism versus Selfishness in MANETs,799f9bd47ace3c92a5b6200626df7703,http://dx.doi.org/10.1007/978-3-642-13446-3_10
82,Mobile ad hoc and sensor networks often contain a mixture of nodes  some of which may be selfish and non-cooperative in providing network services such as forwarding packets in order to conserve energy. Existing trust management protocols for mobile ad hoc networks (MANETs) advocate isolating selfish nodes as soon as they are detected. Further  altruistic behaviors are encouraged with incentive mechanisms. In this paper  we propose and analyze a trust management protocol based on the demand and pricing theory for managing group communication systems where system survivability is highly critical to mission execution. Rather than always encouraging altruistic behaviors  we consider the tradeoff between a node’s individual welfare (e.g.  saving energy for survivability) versus global welfare (e.g.  providing service availability) and identify the best design condition so that the system lifetime is maximized while the mission requirements are satisfied.,ing-ray chen,Not available,2010.0,10.1007/978-3-642-13446-3_10,Trust Management IV,Jin-Hee2010,False,,Springer,Not available,Modeling and Analysis of Trust Management Protocols: Altruism versus Selfishness in MANETs,799f9bd47ace3c92a5b6200626df7703,http://dx.doi.org/10.1007/978-3-642-13446-3_10
83,Braess’s paradox  in its original context  is the counter-intuitive observation that  without lessening demand  closing roads can improve traffic flow. With the explosion of distributed (selfish) routing situations understanding this paradox has become an important concern in a broad range of network design situations. However  the previous theoretical work on Braess’s paradox has focused on “designer” graphs or dense graphs  which are unrealistic in practical situations. In this work  we exploit the expansion properties of Erdős-Rényi random graphs to show that Braess’s paradox occurs when ,fan chung,Not available,2010.0,10.1007/978-3-642-17572-5_16,Internet and Network Economics,Fan2010,False,,Springer,Not available,Braess’s Paradox in Large Sparse Graphs,c7959ef6576d4ce646eee2a7cbec9e70,http://dx.doi.org/10.1007/978-3-642-17572-5_16
84,Braess’s paradox  in its original context  is the counter-intuitive observation that  without lessening demand  closing roads can improve traffic flow. With the explosion of distributed (selfish) routing situations understanding this paradox has become an important concern in a broad range of network design situations. However  the previous theoretical work on Braess’s paradox has focused on “designer” graphs or dense graphs  which are unrealistic in practical situations. In this work  we exploit the expansion properties of Erdős-Rényi random graphs to show that Braess’s paradox occurs when ,stephen young,Not available,2010.0,10.1007/978-3-642-17572-5_16,Internet and Network Economics,Fan2010,False,,Springer,Not available,Braess’s Paradox in Large Sparse Graphs,c7959ef6576d4ce646eee2a7cbec9e70,http://dx.doi.org/10.1007/978-3-642-17572-5_16
85,We study Congestion Games with non-increasing cost functions (Cost Sharing Games) from a complexity perspective and resolve their computational hardness  which has been an open question. Specifically we prove that when the cost functions have the form ,vasilis syrgkanis,Not available,2010.0,10.1007/978-3-642-17572-5_30,Internet and Network Economics,Vasilis2010,False,,Springer,Not available,The Complexity of Equilibria in Cost Sharing Games,b0a7b4bac7825cb698df6abaeea96398,http://dx.doi.org/10.1007/978-3-642-17572-5_30
86,This article provides an in-depth review of the state-of-the-art and describes methodological advances in the design and evaluation of road network pricing schemes. A number of paradigm shifts from the two polar cases of the marginal social cost pricing of road traffic congestion and revenue-maximizing road toll pricing are analyzed  as induced by the need to address realistic design complexities and constraints. The crucial role of the joint consideration of pricing strategies with optimal capacity provision and several network management measures is manifested and an integrated evaluation framework is suggested to incorporate a wide range of road pricing impacts into the scheme design process.,theodore tsekeris,Not available,2009.0,10.1007/s11066-008-9024-z,NETNOMICS: Economic Research and Electronic Networking,Theodore2009,False,,Springer,Not available,Design and evaluation of road pricing: state-of-the-art and methodological advances,26231300faf219f2a623f5db28e0d593,http://dx.doi.org/10.1007/s11066-008-9024-z
87,This article provides an in-depth review of the state-of-the-art and describes methodological advances in the design and evaluation of road network pricing schemes. A number of paradigm shifts from the two polar cases of the marginal social cost pricing of road traffic congestion and revenue-maximizing road toll pricing are analyzed  as induced by the need to address realistic design complexities and constraints. The crucial role of the joint consideration of pricing strategies with optimal capacity provision and several network management measures is manifested and an integrated evaluation framework is suggested to incorporate a wide range of road pricing impacts into the scheme design process.,stefan voss,Not available,2009.0,10.1007/s11066-008-9024-z,NETNOMICS: Economic Research and Electronic Networking,Theodore2009,False,,Springer,Not available,Design and evaluation of road pricing: state-of-the-art and methodological advances,26231300faf219f2a623f5db28e0d593,http://dx.doi.org/10.1007/s11066-008-9024-z
88,We consider weighted linear congestion games  and investigate how social ignorance  namely lack of information about the presence of some players  affects the inefficiency of pure Nash equilibria (PNE) and the convergence rate of the ,dimitris fotakis,Not available,2012.0,10.1007/s00224-011-9355-2,Theory of Computing Systems,Dimitris2012,False,,Springer,Not available,The Impact of Social Ignorance on Weighted Congestion Games,c51e1fb56b6dd7f811b44c629fe4d1ed,http://dx.doi.org/10.1007/s00224-011-9355-2
89,We consider weighted linear congestion games  and investigate how social ignorance  namely lack of information about the presence of some players  affects the inefficiency of pure Nash equilibria (PNE) and the convergence rate of the ,vasilis gkatzelis,Not available,2012.0,10.1007/s00224-011-9355-2,Theory of Computing Systems,Dimitris2012,False,,Springer,Not available,The Impact of Social Ignorance on Weighted Congestion Games,c51e1fb56b6dd7f811b44c629fe4d1ed,http://dx.doi.org/10.1007/s00224-011-9355-2
90,We show exact values for the price of anarchy of weighted and unweighted congestion games with polynomial latency functions. The given values also hold for weighted and unweighted ,dominic dumrauf,Not available,2006.0,10.1007/11672142_17,STACS 2006,Sebastian2006,False,,Springer,Not available,Exact Price of Anarchy for Polynomial Congestion Games,245a0c76ddfba9cc496ac7b222f4ca7d,http://dx.doi.org/10.1007/11672142_17
91,We consider weighted linear congestion games  and investigate how social ignorance  namely lack of information about the presence of some players  affects the inefficiency of pure Nash equilibria (PNE) and the convergence rate of the ,alexis kaporis,Not available,2012.0,10.1007/s00224-011-9355-2,Theory of Computing Systems,Dimitris2012,False,,Springer,Not available,The Impact of Social Ignorance on Weighted Congestion Games,c51e1fb56b6dd7f811b44c629fe4d1ed,http://dx.doi.org/10.1007/s00224-011-9355-2
92,We consider weighted linear congestion games  and investigate how social ignorance  namely lack of information about the presence of some players  affects the inefficiency of pure Nash equilibria (PNE) and the convergence rate of the ,paul spirakis,Not available,2012.0,10.1007/s00224-011-9355-2,Theory of Computing Systems,Dimitris2012,False,,Springer,Not available,The Impact of Social Ignorance on Weighted Congestion Games,c51e1fb56b6dd7f811b44c629fe4d1ed,http://dx.doi.org/10.1007/s00224-011-9355-2
93,In this paper  we use the variational method to study the efficiency loss of user equilibrium for the multi-class  multi-criterion traffic equilibrium with general tolls and a discrete set of value of time. By introducing three important parameters ters ,kedong chen,Not available,2012.0,10.1007/s11518-011-5175-9,Journal of Systems Science and Systems Engineering,Kedong2012,False,,Springer,Not available,The bound of price of anarchy for multi-class and multi-criteria traffic equilibrium problem,7b2d7e23997f29aa5c367cc7bf253b2d,http://dx.doi.org/10.1007/s11518-011-5175-9
94,In this paper  we use the variational method to study the efficiency loss of user equilibrium for the multi-class  multi-criterion traffic equilibrium with general tolls and a discrete set of value of time. By introducing three important parameters ters ,daoli zhu,Not available,2012.0,10.1007/s11518-011-5175-9,Journal of Systems Science and Systems Engineering,Kedong2012,False,,Springer,Not available,The bound of price of anarchy for multi-class and multi-criteria traffic equilibrium problem,7b2d7e23997f29aa5c367cc7bf253b2d,http://dx.doi.org/10.1007/s11518-011-5175-9
95,In this paper  we use the variational method to study the efficiency loss of user equilibrium for the multi-class  multi-criterion traffic equilibrium with general tolls and a discrete set of value of time. By introducing three important parameters ters ,yihong hu,Not available,2012.0,10.1007/s11518-011-5175-9,Journal of Systems Science and Systems Engineering,Kedong2012,False,,Springer,Not available,The bound of price of anarchy for multi-class and multi-criteria traffic equilibrium problem,7b2d7e23997f29aa5c367cc7bf253b2d,http://dx.doi.org/10.1007/s11518-011-5175-9
96,In this paper  we use the variational method to study the efficiency loss of user equilibrium for the multi-class  multi-criterion traffic equilibrium with general tolls and a discrete set of value of time. By introducing three important parameters ters ,jianlin liu,Not available,2012.0,10.1007/s11518-011-5175-9,Journal of Systems Science and Systems Engineering,Kedong2012,False,,Springer,Not available,The bound of price of anarchy for multi-class and multi-criteria traffic equilibrium problem,7b2d7e23997f29aa5c367cc7bf253b2d,http://dx.doi.org/10.1007/s11518-011-5175-9
97,We introduce a new class of network creation games  called ,michele flammini,Not available,2012.0,10.1007/978-3-642-31104-8_14,Structural Information and Communication Complexity,Michele2012,False,,Springer,Not available,Mobile Network Creation Games,8d10803a01df5b10e011db3deaca2696,http://dx.doi.org/10.1007/978-3-642-31104-8_14
98,We introduce a new class of network creation games  called ,vasco gallotti,Not available,2012.0,10.1007/978-3-642-31104-8_14,Structural Information and Communication Complexity,Michele2012,False,,Springer,Not available,Mobile Network Creation Games,8d10803a01df5b10e011db3deaca2696,http://dx.doi.org/10.1007/978-3-642-31104-8_14
99,We introduce a new class of network creation games  called ,giovanna melideo,Not available,2012.0,10.1007/978-3-642-31104-8_14,Structural Information and Communication Complexity,Michele2012,False,,Springer,Not available,Mobile Network Creation Games,8d10803a01df5b10e011db3deaca2696,http://dx.doi.org/10.1007/978-3-642-31104-8_14
100,We introduce a new class of network creation games  called ,gianpiero monaco,Not available,2012.0,10.1007/978-3-642-31104-8_14,Structural Information and Communication Complexity,Michele2012,False,,Springer,Not available,Mobile Network Creation Games,8d10803a01df5b10e011db3deaca2696,http://dx.doi.org/10.1007/978-3-642-31104-8_14
101,We show exact values for the price of anarchy of weighted and unweighted congestion games with polynomial latency functions. The given values also hold for weighted and unweighted ,martin gairing,Not available,2006.0,10.1007/11672142_17,STACS 2006,Sebastian2006,False,,Springer,Not available,Exact Price of Anarchy for Polynomial Congestion Games,245a0c76ddfba9cc496ac7b222f4ca7d,http://dx.doi.org/10.1007/11672142_17
102,We introduce a new class of network creation games  called ,luca moscardelli,Not available,2012.0,10.1007/978-3-642-31104-8_14,Structural Information and Communication Complexity,Michele2012,False,,Springer,Not available,Mobile Network Creation Games,8d10803a01df5b10e011db3deaca2696,http://dx.doi.org/10.1007/978-3-642-31104-8_14
103,We study time-dependent strategies for playing congestion games. The players can time their participation in the game with the hope that fewer players will compete for the same resources. We study two models: the boat model  in which the latency of a player is influenced only by the players that start at the same time  and the conveyor belt model in which the latency of a player is affected by the players that share the system  even if they started earlier or later; unlike standard congestion games  in these games the order of the edges in the paths affect the latency of the players. We characterize the symmetric Nash equilibria of the games with affine latencies of networks of parallel links in the boat model and we bound their price of anarchy and stability. For the conveyor belt model  we characterize the symmetric Nash equilibria of two players on parallel links. We also show that the games of the boat model are themselves congestion games. The same is true for the games of two players for the conveyor belt model; however  for this model the games of three or more players are not in general congestion games and may not have pure equilibria.,elias koutsoupias,Not available,2012.0,10.1007/978-3-642-31585-5_55,Automata  Languages  and Programming,Elias2012,False,,Springer,Not available,Contention Issues in Congestion Games,c46ef6b789d6d1fa4725c694772f1443,http://dx.doi.org/10.1007/978-3-642-31585-5_55
104,We study time-dependent strategies for playing congestion games. The players can time their participation in the game with the hope that fewer players will compete for the same resources. We study two models: the boat model  in which the latency of a player is influenced only by the players that start at the same time  and the conveyor belt model in which the latency of a player is affected by the players that share the system  even if they started earlier or later; unlike standard congestion games  in these games the order of the edges in the paths affect the latency of the players. We characterize the symmetric Nash equilibria of the games with affine latencies of networks of parallel links in the boat model and we bound their price of anarchy and stability. For the conveyor belt model  we characterize the symmetric Nash equilibria of two players on parallel links. We also show that the games of the boat model are themselves congestion games. The same is true for the games of two players for the conveyor belt model; however  for this model the games of three or more players are not in general congestion games and may not have pure equilibria.,katia papakonstantinopoulou,Not available,2012.0,10.1007/978-3-642-31585-5_55,Automata  Languages  and Programming,Elias2012,False,,Springer,Not available,Contention Issues in Congestion Games,c46ef6b789d6d1fa4725c694772f1443,http://dx.doi.org/10.1007/978-3-642-31585-5_55
105,We consider routing games on grid network topologies. The social cost is the worst congestion in any of the network edges (bottleneck congestion). Each player’s objective is to find a path that minimizes the bottleneck congestion in its path. We show that the price of anarchy in bottleneck games in grids is proportional to the number of bends ,costas busch,Not available,2012.0,10.1007/978-3-642-30373-9_21,Game Theory for Networks,Costas2012,False,,Springer,Not available,Bottleneck Routing Games on Grids,82735dda86dc95f1e5792f0f884f0e6b,http://dx.doi.org/10.1007/978-3-642-30373-9_21
106,We consider routing games on grid network topologies. The social cost is the worst congestion in any of the network edges (bottleneck congestion). Each player’s objective is to find a path that minimizes the bottleneck congestion in its path. We show that the price of anarchy in bottleneck games in grids is proportional to the number of bends ,rajgopal kannan,Not available,2012.0,10.1007/978-3-642-30373-9_21,Game Theory for Networks,Costas2012,False,,Springer,Not available,Bottleneck Routing Games on Grids,82735dda86dc95f1e5792f0f884f0e6b,http://dx.doi.org/10.1007/978-3-642-30373-9_21
107,We consider routing games on grid network topologies. The social cost is the worst congestion in any of the network edges (bottleneck congestion). Each player’s objective is to find a path that minimizes the bottleneck congestion in its path. We show that the price of anarchy in bottleneck games in grids is proportional to the number of bends ,alfred samman,Not available,2012.0,10.1007/978-3-642-30373-9_21,Game Theory for Networks,Costas2012,False,,Springer,Not available,Bottleneck Routing Games on Grids,82735dda86dc95f1e5792f0f884f0e6b,http://dx.doi.org/10.1007/978-3-642-30373-9_21
108,In bottleneck congestion games the social cost is the worst congestion (bottleneck) on any resource  and each player selfishly minimizes the worst resource congestion in its strategy. We examine the price of anarchy with respect to the ,costas busch,Not available,2012.0,10.1007/978-3-642-32241-9_50,Computing and Combinatorics,Costas2012,False,,Springer,Not available,Stretch in Bottleneck Games,3af9dde1a11516ffb353e0d6b9336c40,http://dx.doi.org/10.1007/978-3-642-32241-9_50
109,In bottleneck congestion games the social cost is the worst congestion (bottleneck) on any resource  and each player selfishly minimizes the worst resource congestion in its strategy. We examine the price of anarchy with respect to the ,rajgopal kannan,Not available,2012.0,10.1007/978-3-642-32241-9_50,Computing and Combinatorics,Costas2012,False,,Springer,Not available,Stretch in Bottleneck Games,3af9dde1a11516ffb353e0d6b9336c40,http://dx.doi.org/10.1007/978-3-642-32241-9_50
110,We consider a Cournot oligopoly model where multiple suppliers (oligopolists) compete by choosing quantities. We compare the social welfare achieved at a Cournot equilibrium to the maximum possible  for the case where the inverse market demand function is convex. We establish a lower bound on the efficiency of Cournot equilibria in terms of a scalar parameter derived from the inverse demand function. Our results provide nontrivial quantitative bounds on the loss of social welfare and aggregate profit for several convex inverse demand functions that appear in the economics literature.,john tsitsiklis,Not available,2012.0,10.1007/978-3-642-35582-0_5,Game Theory for Networks,N.2012,False,,Springer,Not available,Efficiency Loss in a Cournot Oligopoly with Convex Market Demand,9db6698ccc67675c60552fdd03980caf,http://dx.doi.org/10.1007/978-3-642-35582-0_5
111,We consider a Cournot oligopoly model where multiple suppliers (oligopolists) compete by choosing quantities. We compare the social welfare achieved at a Cournot equilibrium to the maximum possible  for the case where the inverse market demand function is convex. We establish a lower bound on the efficiency of Cournot equilibria in terms of a scalar parameter derived from the inverse demand function. Our results provide nontrivial quantitative bounds on the loss of social welfare and aggregate profit for several convex inverse demand functions that appear in the economics literature.,yunjian xu,Not available,2012.0,10.1007/978-3-642-35582-0_5,Game Theory for Networks,N.2012,False,,Springer,Not available,Efficiency Loss in a Cournot Oligopoly with Convex Market Demand,9db6698ccc67675c60552fdd03980caf,http://dx.doi.org/10.1007/978-3-642-35582-0_5
112,The success of the Internet is remarkable in light of the decentralized manner in which it is designed and operated. Unlike small scale networks  the Internet is built and controlled by a large number of disparate service providers who are not interested in any global optimization. Instead  providers simply seek to maximize their own profit by charging users for access to their service. Users themselves also behave selfishly  optimizing over price and quality of service. Game theory provides a natural framework for the study of such a situation. However  recent work in this area tends to focus on either the service providers or the network users  but not both. This paper introduces a new model for exploring the interaction of these two elements  in which network managers compete for users via prices and the quality of service provided. We study the extent to which competition between service providers hurts the overall social utility of the system.,tom wexler,Not available,2007.0,10.1007/s00446-006-0020-y,Distributed Computing,Ara2007,False,,Springer,Not available,A network pricing game for selfish traffic,1e6ace55d7fedd0e4eeed19012c6755b,http://dx.doi.org/10.1007/s00446-006-0020-y
113,We show exact values for the price of anarchy of weighted and unweighted congestion games with polynomial latency functions. The given values also hold for weighted and unweighted ,burkhard monien,Not available,2006.0,10.1007/11672142_17,STACS 2006,Sebastian2006,False,,Springer,Not available,Exact Price of Anarchy for Polynomial Congestion Games,245a0c76ddfba9cc496ac7b222f4ca7d,http://dx.doi.org/10.1007/11672142_17
114,In this paper we formulate and study a capacity allocation game between a set of receivers (players) that are interested in receiving multicast data (video/multimedia) being streamed from a server through a multihop network. We consider ,elliot anshelevich,Not available,2012.0,10.1007/978-3-642-30373-9_45,Game Theory for Networks,Elliot2012,False,,Springer,Not available,Capacity Allocation Games for Network-Coded Multicast Streaming,679bc3956072d1a8742b2d191fab8034,http://dx.doi.org/10.1007/978-3-642-30373-9_45
115,In this paper we formulate and study a capacity allocation game between a set of receivers (players) that are interested in receiving multicast data (video/multimedia) being streamed from a server through a multihop network. We consider ,bugra caskurlu,Not available,2012.0,10.1007/978-3-642-30373-9_45,Game Theory for Networks,Elliot2012,False,,Springer,Not available,Capacity Allocation Games for Network-Coded Multicast Streaming,679bc3956072d1a8742b2d191fab8034,http://dx.doi.org/10.1007/978-3-642-30373-9_45
116,In this paper we formulate and study a capacity allocation game between a set of receivers (players) that are interested in receiving multicast data (video/multimedia) being streamed from a server through a multihop network. We consider ,koushik kar,Not available,2012.0,10.1007/978-3-642-30373-9_45,Game Theory for Networks,Elliot2012,False,,Springer,Not available,Capacity Allocation Games for Network-Coded Multicast Streaming,679bc3956072d1a8742b2d191fab8034,http://dx.doi.org/10.1007/978-3-642-30373-9_45
117,In this paper we formulate and study a capacity allocation game between a set of receivers (players) that are interested in receiving multicast data (video/multimedia) being streamed from a server through a multihop network. We consider ,hang zhang,Not available,2012.0,10.1007/978-3-642-30373-9_45,Game Theory for Networks,Elliot2012,False,,Springer,Not available,Capacity Allocation Games for Network-Coded Multicast Streaming,679bc3956072d1a8742b2d191fab8034,http://dx.doi.org/10.1007/978-3-642-30373-9_45
118,In this paper we consider the task allocation problem from a game theoretic perspective. We assume that tasks and machines are ,xujin chen,Not available,2012.0,10.1007/978-3-642-31770-5_28,Combinatorial Optimization and Applications,Xujin2012,False,,Springer,Not available,Efficiency of Dual Equilibria in Selfish Task Allocation to Selfish Machines,2bee2368794b11ecf8243783fa0be16b,http://dx.doi.org/10.1007/978-3-642-31770-5_28
119,In this paper we consider the task allocation problem from a game theoretic perspective. We assume that tasks and machines are ,xiaodong hu,Not available,2012.0,10.1007/978-3-642-31770-5_28,Combinatorial Optimization and Applications,Xujin2012,False,,Springer,Not available,Efficiency of Dual Equilibria in Selfish Task Allocation to Selfish Machines,2bee2368794b11ecf8243783fa0be16b,http://dx.doi.org/10.1007/978-3-642-31770-5_28
120,In this paper we consider the task allocation problem from a game theoretic perspective. We assume that tasks and machines are ,weidong ma,Not available,2012.0,10.1007/978-3-642-31770-5_28,Combinatorial Optimization and Applications,Xujin2012,False,,Springer,Not available,Efficiency of Dual Equilibria in Selfish Task Allocation to Selfish Machines,2bee2368794b11ecf8243783fa0be16b,http://dx.doi.org/10.1007/978-3-642-31770-5_28
121,In this paper we consider the task allocation problem from a game theoretic perspective. We assume that tasks and machines are ,changjun wang,Not available,2012.0,10.1007/978-3-642-31770-5_28,Combinatorial Optimization and Applications,Xujin2012,False,,Springer,Not available,Efficiency of Dual Equilibria in Selfish Task Allocation to Selfish Machines,2bee2368794b11ecf8243783fa0be16b,http://dx.doi.org/10.1007/978-3-642-31770-5_28
122,The popularity of Peer-to-Peer (P2P) file sharing has resulted in large flows between different ISPs  which imposes significant transit fees on the ISPs in whose domains the communicating peers are located. The fundamental tradeoff faced by a peer-swarm is between free  yet delayed content exchange between intra-domain peers  and inter-domain communication of content  which results in transit fees. This dilemma is complex  since peers who possess the content dynamically increase the content capacity of the ISP domain to which they belong.In this paper  we study the decision problem faced by peer swarms as a ,parimal parag,Not available,2012.0,10.1007/978-3-642-30373-9_25,Game Theory for Networks,Parimal2012,False,,Springer,Not available,Service Routing in Multi-ISP Peer-to-Peer Content Distribution: Local or Remote?,55630154550974a1044533f30da7a574,http://dx.doi.org/10.1007/978-3-642-30373-9_25
123,The popularity of Peer-to-Peer (P2P) file sharing has resulted in large flows between different ISPs  which imposes significant transit fees on the ISPs in whose domains the communicating peers are located. The fundamental tradeoff faced by a peer-swarm is between free  yet delayed content exchange between intra-domain peers  and inter-domain communication of content  which results in transit fees. This dilemma is complex  since peers who possess the content dynamically increase the content capacity of the ISP domain to which they belong.In this paper  we study the decision problem faced by peer swarms as a ,srinivas shakkottai,Not available,2012.0,10.1007/978-3-642-30373-9_25,Game Theory for Networks,Parimal2012,False,,Springer,Not available,Service Routing in Multi-ISP Peer-to-Peer Content Distribution: Local or Remote?,55630154550974a1044533f30da7a574,http://dx.doi.org/10.1007/978-3-642-30373-9_25
124,We show exact values for the price of anarchy of weighted and unweighted congestion games with polynomial latency functions. The given values also hold for weighted and unweighted ,florian schoppmann,Not available,2006.0,10.1007/11672142_17,STACS 2006,Sebastian2006,False,,Springer,Not available,Exact Price of Anarchy for Polynomial Congestion Games,245a0c76ddfba9cc496ac7b222f4ca7d,http://dx.doi.org/10.1007/11672142_17
125,The popularity of Peer-to-Peer (P2P) file sharing has resulted in large flows between different ISPs  which imposes significant transit fees on the ISPs in whose domains the communicating peers are located. The fundamental tradeoff faced by a peer-swarm is between free  yet delayed content exchange between intra-domain peers  and inter-domain communication of content  which results in transit fees. This dilemma is complex  since peers who possess the content dynamically increase the content capacity of the ISP domain to which they belong.In this paper  we study the decision problem faced by peer swarms as a ,ishai menache,Not available,2012.0,10.1007/978-3-642-30373-9_25,Game Theory for Networks,Parimal2012,False,,Springer,Not available,Service Routing in Multi-ISP Peer-to-Peer Content Distribution: Local or Remote?,55630154550974a1044533f30da7a574,http://dx.doi.org/10.1007/978-3-642-30373-9_25
126,Competition based on service frequency influences capacity decisions in airline markets and has important implications for airline profitability and airport congestion. The market share of a competing airline is a function of its frequency share. This relationship is pivotal for understanding the impacts of frequency competition on airport congestion and on the airline business in general. Additionally  airport congestion is closely related to several aspects of runway  taxiway  and airborne safety. Based on the most popular form of the relationship between market share and frequency share  we propose a game-theoretic model of frequency competition. We characterize the conditions for Nash equilibrium’s existence and uniqueness for the two-player case. We analyze myopic learning dynamics for the non-equilibrium situations and prove their convergence to Nash equilibrium under mild conditions. For the N-player symmetric game  we characterize all the pure strategy equilibria and identify the worst-case equilibrium  i.e.  the equilibrium with maximum total cost. We provide a measure of the congestion level  based on the concept of price of anarchy and investigate its dependence on game parameters.,vikrant vaze,Not available,2015.0,10.1007/978-3-319-13009-5_7,Game Theoretic Analysis of Congestion  Safety and Security,Vikrant2015,False,,Springer,Not available,The Price of Airline Frequency Competition,2fc25752a60defa6f712e621c3b78db0,http://dx.doi.org/10.1007/978-3-319-13009-5_7
127,Competition based on service frequency influences capacity decisions in airline markets and has important implications for airline profitability and airport congestion. The market share of a competing airline is a function of its frequency share. This relationship is pivotal for understanding the impacts of frequency competition on airport congestion and on the airline business in general. Additionally  airport congestion is closely related to several aspects of runway  taxiway  and airborne safety. Based on the most popular form of the relationship between market share and frequency share  we propose a game-theoretic model of frequency competition. We characterize the conditions for Nash equilibrium’s existence and uniqueness for the two-player case. We analyze myopic learning dynamics for the non-equilibrium situations and prove their convergence to Nash equilibrium under mild conditions. For the N-player symmetric game  we characterize all the pure strategy equilibria and identify the worst-case equilibrium  i.e.  the equilibrium with maximum total cost. We provide a measure of the congestion level  based on the concept of price of anarchy and investigate its dependence on game parameters.,cynthia barnhart,Not available,2015.0,10.1007/978-3-319-13009-5_7,Game Theoretic Analysis of Congestion  Safety and Security,Vikrant2015,False,,Springer,Not available,The Price of Airline Frequency Competition,2fc25752a60defa6f712e621c3b78db0,http://dx.doi.org/10.1007/978-3-319-13009-5_7
128,We study the performance of subgame perfect equilibria  a solution concept which better captures the players’ rationality in sequential games with respect to the classical myopic dynamics based on the notions of improving deviations and Nash equilibria  in the context of sequential isolation games. In particular  for two important classes of sequential isolation games  we show upper and lower bounds on the sequential price of anarchy  that is the worst-case ratio between the social performance of an optimal solution and that of a subgame perfect equilibrium  under the two classical social functions mostly investigated in the scientific literature  namely  the minimum utility per player and the sum of the players’ utilities.,anna angelucci,Not available,2015.0,10.1007/s10878-013-9694-9,Journal of Combinatorial Optimization,Anna2015,False,,Springer,Not available,On the sequential price of anarchy of isolation games,231198b42bfe495d6cbd5cc4aece6cf3,http://dx.doi.org/10.1007/s10878-013-9694-9
129,We study the performance of subgame perfect equilibria  a solution concept which better captures the players’ rationality in sequential games with respect to the classical myopic dynamics based on the notions of improving deviations and Nash equilibria  in the context of sequential isolation games. In particular  for two important classes of sequential isolation games  we show upper and lower bounds on the sequential price of anarchy  that is the worst-case ratio between the social performance of an optimal solution and that of a subgame perfect equilibrium  under the two classical social functions mostly investigated in the scientific literature  namely  the minimum utility per player and the sum of the players’ utilities.,vittorio bilo,Not available,2015.0,10.1007/s10878-013-9694-9,Journal of Combinatorial Optimization,Anna2015,False,,Springer,Not available,On the sequential price of anarchy of isolation games,231198b42bfe495d6cbd5cc4aece6cf3,http://dx.doi.org/10.1007/s10878-013-9694-9
130,We study the performance of subgame perfect equilibria  a solution concept which better captures the players’ rationality in sequential games with respect to the classical myopic dynamics based on the notions of improving deviations and Nash equilibria  in the context of sequential isolation games. In particular  for two important classes of sequential isolation games  we show upper and lower bounds on the sequential price of anarchy  that is the worst-case ratio between the social performance of an optimal solution and that of a subgame perfect equilibrium  under the two classical social functions mostly investigated in the scientific literature  namely  the minimum utility per player and the sum of the players’ utilities.,michele flammini,Not available,2015.0,10.1007/s10878-013-9694-9,Journal of Combinatorial Optimization,Anna2015,False,,Springer,Not available,On the sequential price of anarchy of isolation games,231198b42bfe495d6cbd5cc4aece6cf3,http://dx.doi.org/10.1007/s10878-013-9694-9
131,We study the performance of subgame perfect equilibria  a solution concept which better captures the players’ rationality in sequential games with respect to the classical myopic dynamics based on the notions of improving deviations and Nash equilibria  in the context of sequential isolation games. In particular  for two important classes of sequential isolation games  we show upper and lower bounds on the sequential price of anarchy  that is the worst-case ratio between the social performance of an optimal solution and that of a subgame perfect equilibrium  under the two classical social functions mostly investigated in the scientific literature  namely  the minimum utility per player and the sum of the players’ utilities.,luca moscardelli,Not available,2015.0,10.1007/s10878-013-9694-9,Journal of Combinatorial Optimization,Anna2015,False,,Springer,Not available,On the sequential price of anarchy of isolation games,231198b42bfe495d6cbd5cc4aece6cf3,http://dx.doi.org/10.1007/s10878-013-9694-9
132,We consider a version of the Gale-Shapley stable matching setting  where each pair of nodes is associated with a (symmetric) matching cost and the preferences are determined with respect to these costs. This stable matching version is analyzed through the Price of Anarchy (PoA) and Price of Stability (PoS) lens under the objective of minimizing the total cost of matched nodes (for both the marriage and roommates variants). A simple example demonstrates that in the general case  the PoA and PoS are unbounded  hence we restrict our attention to metric costs. We use the notion of ,yuval emek,Not available,2015.0,10.1007/978-3-662-48350-3_39,Algorithms - ESA 2015,Yuval2015,False,,Springer,Not available,The Price of Matching with Metric Preferences,9f9bf59c39ab94cbfb4909533db79e3a,http://dx.doi.org/10.1007/978-3-662-48350-3_39
133,We consider a version of the Gale-Shapley stable matching setting  where each pair of nodes is associated with a (symmetric) matching cost and the preferences are determined with respect to these costs. This stable matching version is analyzed through the Price of Anarchy (PoA) and Price of Stability (PoS) lens under the objective of minimizing the total cost of matched nodes (for both the marriage and roommates variants). A simple example demonstrates that in the general case  the PoA and PoS are unbounded  hence we restrict our attention to metric costs. We use the notion of ,tobias langner,Not available,2015.0,10.1007/978-3-662-48350-3_39,Algorithms - ESA 2015,Yuval2015,False,,Springer,Not available,The Price of Matching with Metric Preferences,9f9bf59c39ab94cbfb4909533db79e3a,http://dx.doi.org/10.1007/978-3-662-48350-3_39
134,We consider a version of the Gale-Shapley stable matching setting  where each pair of nodes is associated with a (symmetric) matching cost and the preferences are determined with respect to these costs. This stable matching version is analyzed through the Price of Anarchy (PoA) and Price of Stability (PoS) lens under the objective of minimizing the total cost of matched nodes (for both the marriage and roommates variants). A simple example demonstrates that in the general case  the PoA and PoS are unbounded  hence we restrict our attention to metric costs. We use the notion of ,roger wattenhofer,Not available,2015.0,10.1007/978-3-662-48350-3_39,Algorithms - ESA 2015,Yuval2015,False,,Springer,Not available,The Price of Matching with Metric Preferences,9f9bf59c39ab94cbfb4909533db79e3a,http://dx.doi.org/10.1007/978-3-662-48350-3_39
135,We look at the scenario of having to route a continuous rate of traffic from a source node to a sink node in a network  where the objective is to maximize throughput. This is of interest  e.g.  for providers of streaming content in communication networks. The overall path latency  which was relevant in other non-cooperative network routing games such as the classic Wardrop model  is of lesser concern here.To that end  we define bottleneck games with splittable traffic where the throughput on a path is inversely proportional to the maximum latency of an edge on that very path—the bottleneck latency. Therefore  we define a Wardrop equilibrium as a traffic distribution where this bottleneck latency is at minimum on all used paths. As a measure for the overall system well-being—called social cost—we take the weighted sum of the bottleneck latencies of all paths.Our main findings are as follows: First  we prove social cost of Wardrop equilibria on series parallel graphs to be unique. Even more  for any graph whose subgraph induced by all simple start-destination paths is not series parallel  there exist games having equilibria with different social cost. For the price of stability  we give an independence result with regard to the network topology. Finally  our main result is giving a new exact price of stability for Wardrop/bottleneck games on parallel links with M/M/1 latency functions. This result is at the same time the exact price of stability for bottleneck games on general graphs.,vladimir mazalov,Not available,2006.0,10.1007/11944874_30,Internet and Network Economics,Vladimir2006,False,,Springer,Not available,Wardrop Equilibria and Price of Stability for Bottleneck Games with Splittable Traffic,573f1e83e896f0a96fc61c2b5b6dc0c6,http://dx.doi.org/10.1007/11944874_30
136,We devise a unified framework for quantifying the inefficiency of equilibria in clustering games on networks. This class of games has two properties exhibited by many real-life social and economic settings: (a) an agent’s utility is affected only by the behavior of her direct neighbors rather than that of the entire society  and (b) an agent’s utility does not depend on the actual strategies chosen by agents  but rather by whether or not other agents selected the same strategy. Our framework is sufficiently general to account for unilateral versus coordinated deviations by coalitions of different sizes  different types of relationships between agents  and different structures of strategy spaces. Many settings that have been recently studied are special cases of clustering games on networks. Using our framework: (1) We recover previous results for special cases and provide extended and improved results in a unified way. (2) We identify new settings that fall into the class of clustering games on networks and establish price of anarchy and strong price of anarchy bounds for them.,michal feldman,Not available,2015.0,10.1007/978-3-662-47666-6_48,Automata  Languages  and Programming,Michal2015,False,,Springer,Not available,A Unified Framework for Strong Price of Anarchy in Clustering Games,2c5ee0143a861e1eba8f5c30247f466d,http://dx.doi.org/10.1007/978-3-662-47666-6_48
137,We devise a unified framework for quantifying the inefficiency of equilibria in clustering games on networks. This class of games has two properties exhibited by many real-life social and economic settings: (a) an agent’s utility is affected only by the behavior of her direct neighbors rather than that of the entire society  and (b) an agent’s utility does not depend on the actual strategies chosen by agents  but rather by whether or not other agents selected the same strategy. Our framework is sufficiently general to account for unilateral versus coordinated deviations by coalitions of different sizes  different types of relationships between agents  and different structures of strategy spaces. Many settings that have been recently studied are special cases of clustering games on networks. Using our framework: (1) We recover previous results for special cases and provide extended and improved results in a unified way. (2) We identify new settings that fall into the class of clustering games on networks and establish price of anarchy and strong price of anarchy bounds for them.,ophir friedler,Not available,2015.0,10.1007/978-3-662-47666-6_48,Automata  Languages  and Programming,Michal2015,False,,Springer,Not available,A Unified Framework for Strong Price of Anarchy in Clustering Games,2c5ee0143a861e1eba8f5c30247f466d,http://dx.doi.org/10.1007/978-3-662-47666-6_48
138,With the recent emergence of the cloud market  cloud resource pricing fundamentally determines cloud revenue  cloud resource allocation and tenant demand dynamics. However  strategic interactions between cloud providers and tenant users are largely unknown. In this chapter  we consider a monopoly cloud market by formulating a competitive market among tenants. A novel Stackelberg game is proposed to tractably analyze such strategic interactions for optimal cloud resource pricing. To empirically evaluate our analyses  we conduct extensive simulations driven by 40 GB of realistic workload traces from Google.,xin jin,Not available,2015.0,10.1007/978-1-4939-2092-1_19,Handbook on Data Centers,Xin2015,False,,Springer,Not available,Cloud Resource Pricing Under Tenant Rationality,dd02bbada3f9846bca4c7dd8c14dffe5,http://dx.doi.org/10.1007/978-1-4939-2092-1_19
139,With the recent emergence of the cloud market  cloud resource pricing fundamentally determines cloud revenue  cloud resource allocation and tenant demand dynamics. However  strategic interactions between cloud providers and tenant users are largely unknown. In this chapter  we consider a monopoly cloud market by formulating a competitive market among tenants. A novel Stackelberg game is proposed to tractably analyze such strategic interactions for optimal cloud resource pricing. To empirically evaluate our analyses  we conduct extensive simulations driven by 40 GB of realistic workload traces from Google.,yu-kwong kwok,Not available,2015.0,10.1007/978-1-4939-2092-1_19,Handbook on Data Centers,Xin2015,False,,Springer,Not available,Cloud Resource Pricing Under Tenant Rationality,dd02bbada3f9846bca4c7dd8c14dffe5,http://dx.doi.org/10.1007/978-1-4939-2092-1_19
140,We study the efficiency of allocations in large markets with a network structure where every seller owns an edge in a graph and every buyer desires a path connecting some nodes. While it is known that stable allocations can be very inefficient  the exact properties of equilibria in markets with multiple sellers are not fully understood  even in single-source single-sink networks. In this work  we show that for a large class of buyer demand functions  equilibrium always exists and allocations can often be close to optimal. In the process  we characterize the structure and properties of equilibria using techniques from min-cost flows  and obtain tight bounds on efficiency in terms of the various parameters governing the market  especially the number of monopolies ,elliot anshelevich,Not available,2015.0,10.1007/978-3-662-48995-6_2,Web and Internet Economics,Elliot2015,False,,Springer,Not available,Price Competition in Networked Markets: How Do Monopolies Impact Social Welfare?,3e50dde9688fc377814a9ea8a5d42fba,http://dx.doi.org/10.1007/978-3-662-48995-6_2
141,We study the efficiency of allocations in large markets with a network structure where every seller owns an edge in a graph and every buyer desires a path connecting some nodes. While it is known that stable allocations can be very inefficient  the exact properties of equilibria in markets with multiple sellers are not fully understood  even in single-source single-sink networks. In this work  we show that for a large class of buyer demand functions  equilibrium always exists and allocations can often be close to optimal. In the process  we characterize the structure and properties of equilibria using techniques from min-cost flows  and obtain tight bounds on efficiency in terms of the various parameters governing the market  especially the number of monopolies ,shreyas sekar,Not available,2015.0,10.1007/978-3-662-48995-6_2,Web and Internet Economics,Elliot2015,False,,Springer,Not available,Price Competition in Networked Markets: How Do Monopolies Impact Social Welfare?,3e50dde9688fc377814a9ea8a5d42fba,http://dx.doi.org/10.1007/978-3-662-48995-6_2
142,We study Nash and strong equilibria in weighted and unweighted bottleneck games. In such a game every (weighted) player chooses a subset of a given set of resources as her strategy. The cost of a resource depends on the total weight of players choosing it and the personal cost every player tries to minimize is the cost of the most expensive resource in her strategy  the ,t. werth,Not available,2014.0,10.1007/s10100-013-0295-6,Central European Journal of Operations Research,L.2014,False,,Springer,Not available,Computation of equilibria and the price of anarchy in bottleneck congestion games,a34859b024f4f0a44de82957f390b36d,http://dx.doi.org/10.1007/s10100-013-0295-6
143,We study Nash and strong equilibria in weighted and unweighted bottleneck games. In such a game every (weighted) player chooses a subset of a given set of resources as her strategy. The cost of a resource depends on the total weight of players choosing it and the personal cost every player tries to minimize is the cost of the most expensive resource in her strategy  the ,h. sperber,Not available,2014.0,10.1007/s10100-013-0295-6,Central European Journal of Operations Research,L.2014,False,,Springer,Not available,Computation of equilibria and the price of anarchy in bottleneck congestion games,a34859b024f4f0a44de82957f390b36d,http://dx.doi.org/10.1007/s10100-013-0295-6
144,We study Nash and strong equilibria in weighted and unweighted bottleneck games. In such a game every (weighted) player chooses a subset of a given set of resources as her strategy. The cost of a resource depends on the total weight of players choosing it and the personal cost every player tries to minimize is the cost of the most expensive resource in her strategy  the ,s. krumke,Not available,2014.0,10.1007/s10100-013-0295-6,Central European Journal of Operations Research,L.2014,False,,Springer,Not available,Computation of equilibria and the price of anarchy in bottleneck congestion games,a34859b024f4f0a44de82957f390b36d,http://dx.doi.org/10.1007/s10100-013-0295-6
145,We study a game that models a market in which heterogeneous producers of perfect substitutes make pricing decisions in a first stage  followed by consumers that select a producer that sells at lowest price. As opposed to Cournot or Bertrand competition  producers select prices using a ,jose correa,Not available,2014.0,10.1007/s10107-013-0682-8,Mathematical Programming,R.2014,False,,Springer,Not available,Pricing with markups in industries with increasing marginal costs,a03a68420b7252a468207e6f535595ca,http://dx.doi.org/10.1007/s10107-013-0682-8
146,We look at the scenario of having to route a continuous rate of traffic from a source node to a sink node in a network  where the objective is to maximize throughput. This is of interest  e.g.  for providers of streaming content in communication networks. The overall path latency  which was relevant in other non-cooperative network routing games such as the classic Wardrop model  is of lesser concern here.To that end  we define bottleneck games with splittable traffic where the throughput on a path is inversely proportional to the maximum latency of an edge on that very path—the bottleneck latency. Therefore  we define a Wardrop equilibrium as a traffic distribution where this bottleneck latency is at minimum on all used paths. As a measure for the overall system well-being—called social cost—we take the weighted sum of the bottleneck latencies of all paths.Our main findings are as follows: First  we prove social cost of Wardrop equilibria on series parallel graphs to be unique. Even more  for any graph whose subgraph induced by all simple start-destination paths is not series parallel  there exist games having equilibria with different social cost. For the price of stability  we give an independence result with regard to the network topology. Finally  our main result is giving a new exact price of stability for Wardrop/bottleneck games on parallel links with M/M/1 latency functions. This result is at the same time the exact price of stability for bottleneck games on general graphs.,burkhard monien,Not available,2006.0,10.1007/11944874_30,Internet and Network Economics,Vladimir2006,False,,Springer,Not available,Wardrop Equilibria and Price of Stability for Bottleneck Games with Splittable Traffic,573f1e83e896f0a96fc61c2b5b6dc0c6,http://dx.doi.org/10.1007/11944874_30
147,We study a game that models a market in which heterogeneous producers of perfect substitutes make pricing decisions in a first stage  followed by consumers that select a producer that sells at lowest price. As opposed to Cournot or Bertrand competition  producers select prices using a ,nicolas figueroa,Not available,2014.0,10.1007/s10107-013-0682-8,Mathematical Programming,R.2014,False,,Springer,Not available,Pricing with markups in industries with increasing marginal costs,a03a68420b7252a468207e6f535595ca,http://dx.doi.org/10.1007/s10107-013-0682-8
148,We study a game that models a market in which heterogeneous producers of perfect substitutes make pricing decisions in a first stage  followed by consumers that select a producer that sells at lowest price. As opposed to Cournot or Bertrand competition  producers select prices using a ,roger lederman,Not available,2014.0,10.1007/s10107-013-0682-8,Mathematical Programming,R.2014,False,,Springer,Not available,Pricing with markups in industries with increasing marginal costs,a03a68420b7252a468207e6f535595ca,http://dx.doi.org/10.1007/s10107-013-0682-8
149,We study a game that models a market in which heterogeneous producers of perfect substitutes make pricing decisions in a first stage  followed by consumers that select a producer that sells at lowest price. As opposed to Cournot or Bertrand competition  producers select prices using a ,nicolas stier-moses,Not available,2014.0,10.1007/s10107-013-0682-8,Mathematical Programming,R.2014,False,,Springer,Not available,Pricing with markups in industries with increasing marginal costs,a03a68420b7252a468207e6f535595ca,http://dx.doi.org/10.1007/s10107-013-0682-8
150,We reconsider the well-studied Selfish Routing game with affine latency functions. The Price of Anarchy for this class of games takes maximum value 4/3; this maximum is attained already for a simple network of two parallel links  known as Pigou’s network. We improve upon the value 4/3 by means of Coordination Mechanisms.We increase the latency functions of the edges in the network  i.e.  if ,giorgos christodoulou,Not available,2014.0,10.1007/s00453-013-9753-8,Algorithmica,Giorgos2014,False,,Springer,Not available,Improving the Price of Anarchy for Selfish Routing via Coordination Mechanisms,84d043946de74a546a65147685ae0130,http://dx.doi.org/10.1007/s00453-013-9753-8
151,We reconsider the well-studied Selfish Routing game with affine latency functions. The Price of Anarchy for this class of games takes maximum value 4/3; this maximum is attained already for a simple network of two parallel links  known as Pigou’s network. We improve upon the value 4/3 by means of Coordination Mechanisms.We increase the latency functions of the edges in the network  i.e.  if ,kurt mehlhorn,Not available,2014.0,10.1007/s00453-013-9753-8,Algorithmica,Giorgos2014,False,,Springer,Not available,Improving the Price of Anarchy for Selfish Routing via Coordination Mechanisms,84d043946de74a546a65147685ae0130,http://dx.doi.org/10.1007/s00453-013-9753-8
152,We reconsider the well-studied Selfish Routing game with affine latency functions. The Price of Anarchy for this class of games takes maximum value 4/3; this maximum is attained already for a simple network of two parallel links  known as Pigou’s network. We improve upon the value 4/3 by means of Coordination Mechanisms.We increase the latency functions of the edges in the network  i.e.  if ,evangelia pyrga,Not available,2014.0,10.1007/s00453-013-9753-8,Algorithmica,Giorgos2014,False,,Springer,Not available,Improving the Price of Anarchy for Selfish Routing via Coordination Mechanisms,84d043946de74a546a65147685ae0130,http://dx.doi.org/10.1007/s00453-013-9753-8
153,We consider a model of next-hop routing by self-interested agents. In this model  nodes in a graph (representing ISPs  Autonomous Systems  etc.) make pricing decisions of how much to charge for forwarding traffic from each of their upstream neighbors  and routing decisions of which downstream neighbors to forward traffic to (i.e.  choosing the next hop). Traffic originates at a subset of these nodes that derive a utility when the traffic is routed to its destination node; the traffic demand is elastic and the utility derived from it can be different for different source nodes. Our next-hop routing and pricing model is in sharp contrast with the more common source routing and pricing models  in which the source of traffic determines the entire route from source to destination. For our model  we begin by showing sufficient conditions for prices to result in a Nash equilibrium  and in fact give an efficient algorithm to compute a Nash equilibrium which is as good as the centralized optimum  thus proving that the price of stability is 1. When only a single source node exists  then the price of anarchy is 1 as well  as long as some minor assumptions on player behavior is made. The above results hold for arbitrary convex pricing functions  but with the assumption that the utilities derived from getting traffic to its destination are linear. When utilities can be non-linear functions  we show that Nash equilibrium may not exist  even with simple discrete pricing models.,elliot anshelevich,Not available,2014.0,10.1007/s00224-012-9435-y,Theory of Computing Systems,Elliot2014,False,,Springer,Not available,Strategic Pricing in Next-Hop Routing with Elastic Demands,0f921513b90b6c8b8b550ca12a19d19e,http://dx.doi.org/10.1007/s00224-012-9435-y
154,We consider a model of next-hop routing by self-interested agents. In this model  nodes in a graph (representing ISPs  Autonomous Systems  etc.) make pricing decisions of how much to charge for forwarding traffic from each of their upstream neighbors  and routing decisions of which downstream neighbors to forward traffic to (i.e.  choosing the next hop). Traffic originates at a subset of these nodes that derive a utility when the traffic is routed to its destination node; the traffic demand is elastic and the utility derived from it can be different for different source nodes. Our next-hop routing and pricing model is in sharp contrast with the more common source routing and pricing models  in which the source of traffic determines the entire route from source to destination. For our model  we begin by showing sufficient conditions for prices to result in a Nash equilibrium  and in fact give an efficient algorithm to compute a Nash equilibrium which is as good as the centralized optimum  thus proving that the price of stability is 1. When only a single source node exists  then the price of anarchy is 1 as well  as long as some minor assumptions on player behavior is made. The above results hold for arbitrary convex pricing functions  but with the assumption that the utilities derived from getting traffic to its destination are linear. When utilities can be non-linear functions  we show that Nash equilibrium may not exist  even with simple discrete pricing models.,ameya hate,Not available,2014.0,10.1007/s00224-012-9435-y,Theory of Computing Systems,Elliot2014,False,,Springer,Not available,Strategic Pricing in Next-Hop Routing with Elastic Demands,0f921513b90b6c8b8b550ca12a19d19e,http://dx.doi.org/10.1007/s00224-012-9435-y
155,We consider a model of next-hop routing by self-interested agents. In this model  nodes in a graph (representing ISPs  Autonomous Systems  etc.) make pricing decisions of how much to charge for forwarding traffic from each of their upstream neighbors  and routing decisions of which downstream neighbors to forward traffic to (i.e.  choosing the next hop). Traffic originates at a subset of these nodes that derive a utility when the traffic is routed to its destination node; the traffic demand is elastic and the utility derived from it can be different for different source nodes. Our next-hop routing and pricing model is in sharp contrast with the more common source routing and pricing models  in which the source of traffic determines the entire route from source to destination. For our model  we begin by showing sufficient conditions for prices to result in a Nash equilibrium  and in fact give an efficient algorithm to compute a Nash equilibrium which is as good as the centralized optimum  thus proving that the price of stability is 1. When only a single source node exists  then the price of anarchy is 1 as well  as long as some minor assumptions on player behavior is made. The above results hold for arbitrary convex pricing functions  but with the assumption that the utilities derived from getting traffic to its destination are linear. When utilities can be non-linear functions  we show that Nash equilibrium may not exist  even with simple discrete pricing models.,koushik kar,Not available,2014.0,10.1007/s00224-012-9435-y,Theory of Computing Systems,Elliot2014,False,,Springer,Not available,Strategic Pricing in Next-Hop Routing with Elastic Demands,0f921513b90b6c8b8b550ca12a19d19e,http://dx.doi.org/10.1007/s00224-012-9435-y
156,As defined by Aumann in 1959  a strong equilibrium is a Nash equilibrium that is resilient to deviations by coalitions. We give tight bounds on the strong price of anarchy for load balancing on related machines. We also give tight bounds for ,amos fiat,Not available,2007.0,10.1007/978-3-540-73420-8_51,Automata  Languages and Programming,Amos2007,False,,Springer,Not available,Strong Price of Anarchy for Machine Load Balancing,e62a88eac6ef598fa8bf2eb73a687dae,http://dx.doi.org/10.1007/978-3-540-73420-8_51
157,We look at the scenario of having to route a continuous rate of traffic from a source node to a sink node in a network  where the objective is to maximize throughput. This is of interest  e.g.  for providers of streaming content in communication networks. The overall path latency  which was relevant in other non-cooperative network routing games such as the classic Wardrop model  is of lesser concern here.To that end  we define bottleneck games with splittable traffic where the throughput on a path is inversely proportional to the maximum latency of an edge on that very path—the bottleneck latency. Therefore  we define a Wardrop equilibrium as a traffic distribution where this bottleneck latency is at minimum on all used paths. As a measure for the overall system well-being—called social cost—we take the weighted sum of the bottleneck latencies of all paths.Our main findings are as follows: First  we prove social cost of Wardrop equilibria on series parallel graphs to be unique. Even more  for any graph whose subgraph induced by all simple start-destination paths is not series parallel  there exist games having equilibria with different social cost. For the price of stability  we give an independence result with regard to the network topology. Finally  our main result is giving a new exact price of stability for Wardrop/bottleneck games on parallel links with M/M/1 latency functions. This result is at the same time the exact price of stability for bottleneck games on general graphs.,florian schoppmann,Not available,2006.0,10.1007/11944874_30,Internet and Network Economics,Vladimir2006,False,,Springer,Not available,Wardrop Equilibria and Price of Stability for Bottleneck Games with Splittable Traffic,573f1e83e896f0a96fc61c2b5b6dc0c6,http://dx.doi.org/10.1007/11944874_30
158,As defined by Aumann in 1959  a strong equilibrium is a Nash equilibrium that is resilient to deviations by coalitions. We give tight bounds on the strong price of anarchy for load balancing on related machines. We also give tight bounds for ,haim kaplan,Not available,2007.0,10.1007/978-3-540-73420-8_51,Automata  Languages and Programming,Amos2007,False,,Springer,Not available,Strong Price of Anarchy for Machine Load Balancing,e62a88eac6ef598fa8bf2eb73a687dae,http://dx.doi.org/10.1007/978-3-540-73420-8_51
159,As defined by Aumann in 1959  a strong equilibrium is a Nash equilibrium that is resilient to deviations by coalitions. We give tight bounds on the strong price of anarchy for load balancing on related machines. We also give tight bounds for ,meital levy,Not available,2007.0,10.1007/978-3-540-73420-8_51,Automata  Languages and Programming,Amos2007,False,,Springer,Not available,Strong Price of Anarchy for Machine Load Balancing,e62a88eac6ef598fa8bf2eb73a687dae,http://dx.doi.org/10.1007/978-3-540-73420-8_51
160,As defined by Aumann in 1959  a strong equilibrium is a Nash equilibrium that is resilient to deviations by coalitions. We give tight bounds on the strong price of anarchy for load balancing on related machines. We also give tight bounds for ,svetlana olonetsky,Not available,2007.0,10.1007/978-3-540-73420-8_51,Automata  Languages and Programming,Amos2007,False,,Springer,Not available,Strong Price of Anarchy for Machine Load Balancing,e62a88eac6ef598fa8bf2eb73a687dae,http://dx.doi.org/10.1007/978-3-540-73420-8_51
161,We consider applications of probabilistic techniques in the framework of algorithmic game theory. We focus on three distinct case studies: (i) The exploitation of the probabilistic method to demonstrate the existence of approximate Nash equilibria of logarithmic support sizes in bimatrix games; (ii) the analysis of the statistical conflict that mixed strategies cause in network congestion games; (iii) the effect of coalitions in the quality of congestion games on parallel links.,spyros kontogiannis,Not available,2007.0,10.1007/978-3-540-74871-7_4,Stochastic Algorithms: Foundations and Applications,C.2007,False,,Springer,Not available,Probabilistic Techniques in Algorithmic Game Theory,4e44984d87ee0362f08b6248a51e40c9,http://dx.doi.org/10.1007/978-3-540-74871-7_4
162,We consider applications of probabilistic techniques in the framework of algorithmic game theory. We focus on three distinct case studies: (i) The exploitation of the probabilistic method to demonstrate the existence of approximate Nash equilibria of logarithmic support sizes in bimatrix games; (ii) the analysis of the statistical conflict that mixed strategies cause in network congestion games; (iii) the effect of coalitions in the quality of congestion games on parallel links.,paul spirakis,Not available,2007.0,10.1007/978-3-540-74871-7_4,Stochastic Algorithms: Foundations and Applications,C.2007,False,,Springer,Not available,Probabilistic Techniques in Algorithmic Game Theory,4e44984d87ee0362f08b6248a51e40c9,http://dx.doi.org/10.1007/978-3-540-74871-7_4
163,We consider non cooperative games in all-optical networks where users share the cost of the used ADM switches for realizing given communication patterns. We show that the two fundamental cost sharing methods  Shapley and Egalitarian  induce polynomial converging games with price of anarchy at most 5/3  regardless of the network topology. Such a bound is tight even for rings. Then  we show that if collusion of at most ,stefania giannantonio,Not available,2007.0,10.1007/978-3-540-77105-0_45,Internet and Network Economics,Stefania2007,False,,Springer,Not available,Selfishness  Collusion and Power of Local Search for the ADMs Minimization Problem ,a9e86ddae5e6430bd43ba9f66fee7f44,http://dx.doi.org/10.1007/978-3-540-77105-0_45
164,We consider non cooperative games in all-optical networks where users share the cost of the used ADM switches for realizing given communication patterns. We show that the two fundamental cost sharing methods  Shapley and Egalitarian  induce polynomial converging games with price of anarchy at most 5/3  regardless of the network topology. Such a bound is tight even for rings. Then  we show that if collusion of at most ,michele flammini,Not available,2007.0,10.1007/978-3-540-77105-0_45,Internet and Network Economics,Stefania2007,False,,Springer,Not available,Selfishness  Collusion and Power of Local Search for the ADMs Minimization Problem ,a9e86ddae5e6430bd43ba9f66fee7f44,http://dx.doi.org/10.1007/978-3-540-77105-0_45
165,We consider non cooperative games in all-optical networks where users share the cost of the used ADM switches for realizing given communication patterns. We show that the two fundamental cost sharing methods  Shapley and Egalitarian  induce polynomial converging games with price of anarchy at most 5/3  regardless of the network topology. Such a bound is tight even for rings. Then  we show that if collusion of at most ,gianpiero monaco,Not available,2007.0,10.1007/978-3-540-77105-0_45,Internet and Network Economics,Stefania2007,False,,Springer,Not available,Selfishness  Collusion and Power of Local Search for the ADMs Minimization Problem ,a9e86ddae5e6430bd43ba9f66fee7f44,http://dx.doi.org/10.1007/978-3-540-77105-0_45
166,We consider non cooperative games in all-optical networks where users share the cost of the used ADM switches for realizing given communication patterns. We show that the two fundamental cost sharing methods  Shapley and Egalitarian  induce polynomial converging games with price of anarchy at most 5/3  regardless of the network topology. Such a bound is tight even for rings. Then  we show that if collusion of at most ,luca moscardelli,Not available,2007.0,10.1007/978-3-540-77105-0_45,Internet and Network Economics,Stefania2007,False,,Springer,Not available,Selfishness  Collusion and Power of Local Search for the ADMs Minimization Problem ,a9e86ddae5e6430bd43ba9f66fee7f44,http://dx.doi.org/10.1007/978-3-540-77105-0_45
167,We consider non cooperative games in all-optical networks where users share the cost of the used ADM switches for realizing given communication patterns. We show that the two fundamental cost sharing methods  Shapley and Egalitarian  induce polynomial converging games with price of anarchy at most 5/3  regardless of the network topology. Such a bound is tight even for rings. Then  we show that if collusion of at most ,mordechai shalom,Not available,2007.0,10.1007/978-3-540-77105-0_45,Internet and Network Economics,Stefania2007,False,,Springer,Not available,Selfishness  Collusion and Power of Local Search for the ADMs Minimization Problem ,a9e86ddae5e6430bd43ba9f66fee7f44,http://dx.doi.org/10.1007/978-3-540-77105-0_45
168,We look at the scenario of having to route a continuous rate of traffic from a source node to a sink node in a network  where the objective is to maximize throughput. This is of interest  e.g.  for providers of streaming content in communication networks. The overall path latency  which was relevant in other non-cooperative network routing games such as the classic Wardrop model  is of lesser concern here.To that end  we define bottleneck games with splittable traffic where the throughput on a path is inversely proportional to the maximum latency of an edge on that very path—the bottleneck latency. Therefore  we define a Wardrop equilibrium as a traffic distribution where this bottleneck latency is at minimum on all used paths. As a measure for the overall system well-being—called social cost—we take the weighted sum of the bottleneck latencies of all paths.Our main findings are as follows: First  we prove social cost of Wardrop equilibria on series parallel graphs to be unique. Even more  for any graph whose subgraph induced by all simple start-destination paths is not series parallel  there exist games having equilibria with different social cost. For the price of stability  we give an independence result with regard to the network topology. Finally  our main result is giving a new exact price of stability for Wardrop/bottleneck games on parallel links with M/M/1 latency functions. This result is at the same time the exact price of stability for bottleneck games on general graphs.,karsten tiemann,Not available,2006.0,10.1007/11944874_30,Internet and Network Economics,Vladimir2006,False,,Springer,Not available,Wardrop Equilibria and Price of Stability for Bottleneck Games with Splittable Traffic,573f1e83e896f0a96fc61c2b5b6dc0c6,http://dx.doi.org/10.1007/11944874_30
169,We consider non cooperative games in all-optical networks where users share the cost of the used ADM switches for realizing given communication patterns. We show that the two fundamental cost sharing methods  Shapley and Egalitarian  induce polynomial converging games with price of anarchy at most 5/3  regardless of the network topology. Such a bound is tight even for rings. Then  we show that if collusion of at most ,shmuel zaks,Not available,2007.0,10.1007/978-3-540-77105-0_45,Internet and Network Economics,Stefania2007,False,,Springer,Not available,Selfishness  Collusion and Power of Local Search for the ADMs Minimization Problem ,a9e86ddae5e6430bd43ba9f66fee7f44,http://dx.doi.org/10.1007/978-3-540-77105-0_45
170,We consider the problem of characterizing user equilibria and optimal solutions for selfish routing in a given network. We extend the known models by considering users ,george karakostas,Not available,2007.0,10.1007/978-3-540-72951-8_25,Structural Information and Communication Complexity,George2007,False,,Springer,Not available,Selfish Routing with Oblivious Users,61908748bb399d06bdc6fa888b9ba563,http://dx.doi.org/10.1007/978-3-540-72951-8_25
171,We consider the problem of characterizing user equilibria and optimal solutions for selfish routing in a given network. We extend the known models by considering users ,taeyon kim,Not available,2007.0,10.1007/978-3-540-72951-8_25,Structural Information and Communication Complexity,George2007,False,,Springer,Not available,Selfish Routing with Oblivious Users,61908748bb399d06bdc6fa888b9ba563,http://dx.doi.org/10.1007/978-3-540-72951-8_25
172,We consider the problem of characterizing user equilibria and optimal solutions for selfish routing in a given network. We extend the known models by considering users ,anastasios viglas,Not available,2007.0,10.1007/978-3-540-72951-8_25,Structural Information and Communication Complexity,George2007,False,,Springer,Not available,Selfish Routing with Oblivious Users,61908748bb399d06bdc6fa888b9ba563,http://dx.doi.org/10.1007/978-3-540-72951-8_25
173,We consider the problem of characterizing user equilibria and optimal solutions for selfish routing in a given network. We extend the known models by considering users ,hao xia,Not available,2007.0,10.1007/978-3-540-72951-8_25,Structural Information and Communication Complexity,George2007,False,,Springer,Not available,Selfish Routing with Oblivious Users,61908748bb399d06bdc6fa888b9ba563,http://dx.doi.org/10.1007/978-3-540-72951-8_25
174,We consider algorithmic questions concerning the existence  tractability and quality of atomic congestion games  among users that are considered to participate in (static) selfish coalitions. We carefully define a coalitional congestion model among atomic players.Our findings in this model are quite interesting  in the sense that we demonstrate many similarities with the non–cooperative case. For example  there exist potentials proving the existence of Pure Nash Equilibria (PNE) in the (even unrelated) parallel links setting; the Finite Improvement Property collapses as soon as we depart from linear delays  but there is an exact potential (and thus PNE) for the case of linear delays  in the network setting; the Price of Anarchy on identical parallel links demonstrates a quite surprising threshold behavior: it persists on being asymptotically equal to that in the case of the non–cooperative KP–model  unless we enforce a sublogarithmic number of coalitions.We also show crucial differences  mainly concerning the hardness of algorithmic problems that are solved efficiently in the non–cooperative case. Although we demonstrate convergence to robust PNE  we also prove the hardness of computing them. On the other hand  we can easily construct a generalized fully mixed Nash Equilibrium. Finally  we propose a new improvement policy that converges to PNE that are robust against (even dynamically forming) coalitions of small size  in pseudo–polynomial time.,dimitris fotakis,Not available,2006.0,10.1007/11786986_50,Automata  Languages and Programming,Dimitris2006,False,,Springer,Not available,Atomic Congestion Games Among Coalitions,cd5791e326b01ba40fca07b5c8a56089,http://dx.doi.org/10.1007/11786986_50
175,We consider algorithmic questions concerning the existence  tractability and quality of atomic congestion games  among users that are considered to participate in (static) selfish coalitions. We carefully define a coalitional congestion model among atomic players.Our findings in this model are quite interesting  in the sense that we demonstrate many similarities with the non–cooperative case. For example  there exist potentials proving the existence of Pure Nash Equilibria (PNE) in the (even unrelated) parallel links setting; the Finite Improvement Property collapses as soon as we depart from linear delays  but there is an exact potential (and thus PNE) for the case of linear delays  in the network setting; the Price of Anarchy on identical parallel links demonstrates a quite surprising threshold behavior: it persists on being asymptotically equal to that in the case of the non–cooperative KP–model  unless we enforce a sublogarithmic number of coalitions.We also show crucial differences  mainly concerning the hardness of algorithmic problems that are solved efficiently in the non–cooperative case. Although we demonstrate convergence to robust PNE  we also prove the hardness of computing them. On the other hand  we can easily construct a generalized fully mixed Nash Equilibrium. Finally  we propose a new improvement policy that converges to PNE that are robust against (even dynamically forming) coalitions of small size  in pseudo–polynomial time.,spyros kontogiannis,Not available,2006.0,10.1007/11786986_50,Automata  Languages and Programming,Dimitris2006,False,,Springer,Not available,Atomic Congestion Games Among Coalitions,cd5791e326b01ba40fca07b5c8a56089,http://dx.doi.org/10.1007/11786986_50
176,We consider algorithmic questions concerning the existence  tractability and quality of atomic congestion games  among users that are considered to participate in (static) selfish coalitions. We carefully define a coalitional congestion model among atomic players.Our findings in this model are quite interesting  in the sense that we demonstrate many similarities with the non–cooperative case. For example  there exist potentials proving the existence of Pure Nash Equilibria (PNE) in the (even unrelated) parallel links setting; the Finite Improvement Property collapses as soon as we depart from linear delays  but there is an exact potential (and thus PNE) for the case of linear delays  in the network setting; the Price of Anarchy on identical parallel links demonstrates a quite surprising threshold behavior: it persists on being asymptotically equal to that in the case of the non–cooperative KP–model  unless we enforce a sublogarithmic number of coalitions.We also show crucial differences  mainly concerning the hardness of algorithmic problems that are solved efficiently in the non–cooperative case. Although we demonstrate convergence to robust PNE  we also prove the hardness of computing them. On the other hand  we can easily construct a generalized fully mixed Nash Equilibrium. Finally  we propose a new improvement policy that converges to PNE that are robust against (even dynamically forming) coalitions of small size  in pseudo–polynomial time.,paul spirakis,Not available,2006.0,10.1007/11786986_50,Automata  Languages and Programming,Dimitris2006,False,,Springer,Not available,Atomic Congestion Games Among Coalitions,cd5791e326b01ba40fca07b5c8a56089,http://dx.doi.org/10.1007/11786986_50
177,We study a multicast game in communication networks in which a source sends the same message or service to a set of destinations and the cost of the used links is divided among the receivers according to given cost sharing methods. Assuming a selfish and rational behavior  each receiving user is willing to select a strategy yielding the minimum shared cost. A Nash equilibrium is a solution in which no user can decrease its payment by adopting a different strategy  and the price of anarchy is defined as the worst case ratio between the overall communication cost yielded by an equilibrium and the minimum possible one. Nash equilibria requiring an excessive number of steps to be reached or being hard to compute or not existing at all  we are interested in the determination of the price of anarchy reached in a limited number of rounds  each of which containing at least one move per receiving user. We consider different reasonable cost sharing methods  including the well-known Shapley and egalitarian ones  and investigate their performances versus two possible global criteria: the overall cost of the used links and the maximum shared cost of users. We show that  even in case of two receivers making the best possible move at each step  the number of steps needed to reach a Nash equilibrium can be arbitrarily large. Moreover  we determine the cost sharing methods for which a single round is already sufficient to get a price of anarchy comparable to the one at equilibria  and the ones not satisfying such a property. Finally  we show that finding the sequence of moves leading to the best possible global performance after one-round is already an intractable problem  i.e.  NP-hard.,angelo fanelli,Not available,2006.0,10.1007/11821069_32,Mathematical Foundations of Computer Science 2006,Angelo2006,False,,Springer,Not available,Multicast Transmissions in Non-cooperative Networks with a Limited Number of Selfish Moves,17b741875bdf5dc37b39e7abec886ce5,http://dx.doi.org/10.1007/11821069_32
178,We study a multicast game in communication networks in which a source sends the same message or service to a set of destinations and the cost of the used links is divided among the receivers according to given cost sharing methods. Assuming a selfish and rational behavior  each receiving user is willing to select a strategy yielding the minimum shared cost. A Nash equilibrium is a solution in which no user can decrease its payment by adopting a different strategy  and the price of anarchy is defined as the worst case ratio between the overall communication cost yielded by an equilibrium and the minimum possible one. Nash equilibria requiring an excessive number of steps to be reached or being hard to compute or not existing at all  we are interested in the determination of the price of anarchy reached in a limited number of rounds  each of which containing at least one move per receiving user. We consider different reasonable cost sharing methods  including the well-known Shapley and egalitarian ones  and investigate their performances versus two possible global criteria: the overall cost of the used links and the maximum shared cost of users. We show that  even in case of two receivers making the best possible move at each step  the number of steps needed to reach a Nash equilibrium can be arbitrarily large. Moreover  we determine the cost sharing methods for which a single round is already sufficient to get a price of anarchy comparable to the one at equilibria  and the ones not satisfying such a property. Finally  we show that finding the sequence of moves leading to the best possible global performance after one-round is already an intractable problem  i.e.  NP-hard.,michele flammini,Not available,2006.0,10.1007/11821069_32,Mathematical Foundations of Computer Science 2006,Angelo2006,False,,Springer,Not available,Multicast Transmissions in Non-cooperative Networks with a Limited Number of Selfish Moves,17b741875bdf5dc37b39e7abec886ce5,http://dx.doi.org/10.1007/11821069_32
179,We study the price of anarchy for selfish multicast routing games in directed multigraphs with latency functions on the edges  extending the known theory for the unicast situation  and exhibiting new phenomena not present in the unicast model. In the multicast model we have ,andreas baltz,Not available,2006.0,10.1007/11922377_2,Combinatorial and Algorithmic Aspects of Networking,Andreas2006,False,,Springer,Not available,The Price of Anarchy in Selfish Multicast Routing,b1d401e386f330d746ee0d1e8c066dc0,http://dx.doi.org/10.1007/11922377_2
180,We study a multicast game in communication networks in which a source sends the same message or service to a set of destinations and the cost of the used links is divided among the receivers according to given cost sharing methods. Assuming a selfish and rational behavior  each receiving user is willing to select a strategy yielding the minimum shared cost. A Nash equilibrium is a solution in which no user can decrease its payment by adopting a different strategy  and the price of anarchy is defined as the worst case ratio between the overall communication cost yielded by an equilibrium and the minimum possible one. Nash equilibria requiring an excessive number of steps to be reached or being hard to compute or not existing at all  we are interested in the determination of the price of anarchy reached in a limited number of rounds  each of which containing at least one move per receiving user. We consider different reasonable cost sharing methods  including the well-known Shapley and egalitarian ones  and investigate their performances versus two possible global criteria: the overall cost of the used links and the maximum shared cost of users. We show that  even in case of two receivers making the best possible move at each step  the number of steps needed to reach a Nash equilibrium can be arbitrarily large. Moreover  we determine the cost sharing methods for which a single round is already sufficient to get a price of anarchy comparable to the one at equilibria  and the ones not satisfying such a property. Finally  we show that finding the sequence of moves leading to the best possible global performance after one-round is already an intractable problem  i.e.  NP-hard.,giovanna melideo,Not available,2006.0,10.1007/11821069_32,Mathematical Foundations of Computer Science 2006,Angelo2006,False,,Springer,Not available,Multicast Transmissions in Non-cooperative Networks with a Limited Number of Selfish Moves,17b741875bdf5dc37b39e7abec886ce5,http://dx.doi.org/10.1007/11821069_32
181,We study a multicast game in communication networks in which a source sends the same message or service to a set of destinations and the cost of the used links is divided among the receivers according to given cost sharing methods. Assuming a selfish and rational behavior  each receiving user is willing to select a strategy yielding the minimum shared cost. A Nash equilibrium is a solution in which no user can decrease its payment by adopting a different strategy  and the price of anarchy is defined as the worst case ratio between the overall communication cost yielded by an equilibrium and the minimum possible one. Nash equilibria requiring an excessive number of steps to be reached or being hard to compute or not existing at all  we are interested in the determination of the price of anarchy reached in a limited number of rounds  each of which containing at least one move per receiving user. We consider different reasonable cost sharing methods  including the well-known Shapley and egalitarian ones  and investigate their performances versus two possible global criteria: the overall cost of the used links and the maximum shared cost of users. We show that  even in case of two receivers making the best possible move at each step  the number of steps needed to reach a Nash equilibrium can be arbitrarily large. Moreover  we determine the cost sharing methods for which a single round is already sufficient to get a price of anarchy comparable to the one at equilibria  and the ones not satisfying such a property. Finally  we show that finding the sequence of moves leading to the best possible global performance after one-round is already an intractable problem  i.e.  NP-hard.,luca moscardelli,Not available,2006.0,10.1007/11821069_32,Mathematical Foundations of Computer Science 2006,Angelo2006,False,,Springer,Not available,Multicast Transmissions in Non-cooperative Networks with a Limited Number of Selfish Moves,17b741875bdf5dc37b39e7abec886ce5,http://dx.doi.org/10.1007/11821069_32
182,In WCDMA networks  most economic-based resource management algorithms only assumed that network users were obedient  that is  users only accepted the price declared by network  which is called as price acceptation mechanism. Many research issues argued that it is necessary to accommodate  if possible  to use self-interest behaviours of users to strengthen the technical architecture of network engineering. Thus  this paper explicitly considered the selfishness of users  investigated the price anticipation mechanism in WCDMA networks  in which users acted as price anticipators. By price anticipator it meant users anticipated the effect of their behaviours on the network resource allocation  and adopted strategy correspondingly. From the view point of game theory  we investigated equilibrium properties of the price anticipation mechanism in WCDMA networks  and  through two scenarios  illustrated the relationship between price anticipation mechanism and price acceptation mechanism from the viewpoint of network revenue. Finally  we drew the conclusion that  the network revenue generated in price anticipation mechanism was less than revenue generated in price acceptation mechanism  (the difference between those two mechanisms is called as “price as anarchy”)  and the network revenue generated in those two mechanisms tends to be consistent  when the effect of individual user is negligible.,yufeng wang,Not available,2006.0,10.1007/11814856_65,Wireless Algorithms  Systems  and Applications,Yufeng2006,False,,Springer,Not available,Studying Rational User Behavior in WCDMA Network and Its Effect on Network Revenue,1b05432706b334448c36b26154e7b6db,http://dx.doi.org/10.1007/11814856_65
183,In WCDMA networks  most economic-based resource management algorithms only assumed that network users were obedient  that is  users only accepted the price declared by network  which is called as price acceptation mechanism. Many research issues argued that it is necessary to accommodate  if possible  to use self-interest behaviours of users to strengthen the technical architecture of network engineering. Thus  this paper explicitly considered the selfishness of users  investigated the price anticipation mechanism in WCDMA networks  in which users acted as price anticipators. By price anticipator it meant users anticipated the effect of their behaviours on the network resource allocation  and adopted strategy correspondingly. From the view point of game theory  we investigated equilibrium properties of the price anticipation mechanism in WCDMA networks  and  through two scenarios  illustrated the relationship between price anticipation mechanism and price acceptation mechanism from the viewpoint of network revenue. Finally  we drew the conclusion that  the network revenue generated in price anticipation mechanism was less than revenue generated in price acceptation mechanism  (the difference between those two mechanisms is called as “price as anarchy”)  and the network revenue generated in those two mechanisms tends to be consistent  when the effect of individual user is negligible.,wendong wang,Not available,2006.0,10.1007/11814856_65,Wireless Algorithms  Systems  and Applications,Yufeng2006,False,,Springer,Not available,Studying Rational User Behavior in WCDMA Network and Its Effect on Network Revenue,1b05432706b334448c36b26154e7b6db,http://dx.doi.org/10.1007/11814856_65
184,In this paper we characterize the “price of anarchy”  i.e.  the inefficiency between user and system optimal solutions  when costs are non-separable  asymmetric and nonlinear  generalizing earlier work that has addressed “the price of anarchy” under separable costs. This generalization models traffic equilibria  competitive multi-period pricing and competitive supply chains. The bounds established in this paper are tight and explicitly account for the degree of asymmetry and nonlinearity of the cost function. We introduce an alternate proof method for providing bounds that uses ideas from semidefinite optimization. Finally  in the context of multi-period pricing our analysis establishes that user and system optimal solutions coincide.,g. perakis,Not available,2004.0,10.1007/978-3-540-25960-2_4,Integer Programming and Combinatorial Optimization,G.2004,False,,Springer,Not available,The Price of Anarchy when Costs Are Non-separable and Asymmetric,4c6dd54b590e6cc300e83bf2ee728f11,http://dx.doi.org/10.1007/978-3-540-25960-2_4
185,In this paper we study a general bin packing game with an interest matrix  which is a generalization of all the currently known bin packing games. In this game  there are some items with positive sizes and identical bins with unit capacity as in the classical bin packing problem; additionally we are given an interest matrix with rational entries  whose element ,zhenbo wang,Not available,2018.0,10.1007/s00453-017-0361-x,Algorithmica,Zhenbo2018,False,,Springer,Not available,A General Bin Packing Game: Interest Taken into Account,bbc1a81ba82e6f5c23ee9b1de73f53db,http://dx.doi.org/10.1007/s00453-017-0361-x
186,In this paper we study a general bin packing game with an interest matrix  which is a generalization of all the currently known bin packing games. In this game  there are some items with positive sizes and identical bins with unit capacity as in the classical bin packing problem; additionally we are given an interest matrix with rational entries  whose element ,xin han,Not available,2018.0,10.1007/s00453-017-0361-x,Algorithmica,Zhenbo2018,False,,Springer,Not available,A General Bin Packing Game: Interest Taken into Account,bbc1a81ba82e6f5c23ee9b1de73f53db,http://dx.doi.org/10.1007/s00453-017-0361-x
187,In this paper we study a general bin packing game with an interest matrix  which is a generalization of all the currently known bin packing games. In this game  there are some items with positive sizes and identical bins with unit capacity as in the classical bin packing problem; additionally we are given an interest matrix with rational entries  whose element ,gyorgy dosa,Not available,2018.0,10.1007/s00453-017-0361-x,Algorithmica,Zhenbo2018,False,,Springer,Not available,A General Bin Packing Game: Interest Taken into Account,bbc1a81ba82e6f5c23ee9b1de73f53db,http://dx.doi.org/10.1007/s00453-017-0361-x
188,In this paper we study a general bin packing game with an interest matrix  which is a generalization of all the currently known bin packing games. In this game  there are some items with positive sizes and identical bins with unit capacity as in the classical bin packing problem; additionally we are given an interest matrix with rational entries  whose element ,zsolt tuza,Not available,2018.0,10.1007/s00453-017-0361-x,Algorithmica,Zhenbo2018,False,,Springer,Not available,A General Bin Packing Game: Interest Taken into Account,bbc1a81ba82e6f5c23ee9b1de73f53db,http://dx.doi.org/10.1007/s00453-017-0361-x
189,We study the inefficiency of mixed Nash equilibria  expressed as the price of anarchy  of all-pay auctions in three different environments: combinatorial  multi-unit and single-item auctions. First  we consider item-bidding combinatorial auctions where ,george christodoulou,Not available,2018.0,10.1007/s00453-017-0296-2,Algorithmica,George2018,True,,Springer,Not available,On the Efficiency of All-Pay Mechanisms,04c230dd92fae5c7277091b2deb0615b,http://dx.doi.org/10.1007/s00453-017-0296-2
190,We study the price of anarchy for selfish multicast routing games in directed multigraphs with latency functions on the edges  extending the known theory for the unicast situation  and exhibiting new phenomena not present in the unicast model. In the multicast model we have ,sandro esquivel,Not available,2006.0,10.1007/11922377_2,Combinatorial and Algorithmic Aspects of Networking,Andreas2006,False,,Springer,Not available,The Price of Anarchy in Selfish Multicast Routing,b1d401e386f330d746ee0d1e8c066dc0,http://dx.doi.org/10.1007/11922377_2
191,We study the inefficiency of mixed Nash equilibria  expressed as the price of anarchy  of all-pay auctions in three different environments: combinatorial  multi-unit and single-item auctions. First  we consider item-bidding combinatorial auctions where ,alkmini sgouritsa,Not available,2018.0,10.1007/s00453-017-0296-2,Algorithmica,George2018,True,,Springer,Not available,On the Efficiency of All-Pay Mechanisms,04c230dd92fae5c7277091b2deb0615b,http://dx.doi.org/10.1007/s00453-017-0296-2
192,We study the inefficiency of mixed Nash equilibria  expressed as the price of anarchy  of all-pay auctions in three different environments: combinatorial  multi-unit and single-item auctions. First  we consider item-bidding combinatorial auctions where ,bo tang,Not available,2018.0,10.1007/s00453-017-0296-2,Algorithmica,George2018,True,,Springer,Not available,On the Efficiency of All-Pay Mechanisms,04c230dd92fae5c7277091b2deb0615b,http://dx.doi.org/10.1007/s00453-017-0296-2
193,Coordination mechanisms aim to mitigate the impact of selfishness when scheduling jobs to different machines. Such a mechanism defines a scheduling policy within each machine and naturally induces a game among the selfish job owners. The desirable properties of a coordination mechanism includes simplicity in its definition and efficiency of the outcomes of the induced game. We present a broad class of coordination mechanisms for unrelated machine scheduling that are simple to define and we identify one of its members (mechanism ,ioannis caragiannis,Not available,2018.0,10.1007/s00224-018-9857-2,Theory of Computing Systems,Ioannis2018,False,,Springer,Not available,An Almost Ideal Coordination Mechanism for Unrelated Machine Scheduling,1bcad636cf5fc38beba9f4d7016b83f1,http://dx.doi.org/10.1007/s00224-018-9857-2
194,Coordination mechanisms aim to mitigate the impact of selfishness when scheduling jobs to different machines. Such a mechanism defines a scheduling policy within each machine and naturally induces a game among the selfish job owners. The desirable properties of a coordination mechanism includes simplicity in its definition and efficiency of the outcomes of the induced game. We present a broad class of coordination mechanisms for unrelated machine scheduling that are simple to define and we identify one of its members (mechanism ,angelo fanelli,Not available,2018.0,10.1007/s00224-018-9857-2,Theory of Computing Systems,Ioannis2018,False,,Springer,Not available,An Almost Ideal Coordination Mechanism for Unrelated Machine Scheduling,1bcad636cf5fc38beba9f4d7016b83f1,http://dx.doi.org/10.1007/s00224-018-9857-2
195,We consider the bin packing problem in the non-cooperative game setting. In the game there are a set of items with sizes between 0 and 1 and a number of bins each with a capacity of 1. Each item seeks to be packed in one of the bins so as to minimize its cost (payoff). The social cost is the number of bins used in the packing. Existing research has focused on three bin packing games with selfish items  namely the Unit game  the Proportional game  and the General Weight game  each of which uses a unique payoff rule. In this paper we propose a new bin packing game in which the payoff of an item is a function of its own size and the size of the maximum item in the same bin. We find that the new payoff rule induces the items to reach a better Nash equilibrium. We show that the price of anarchy of the new bin packing game is ,q. nong,Not available,2018.0,10.1007/s10878-017-0201-6,Journal of Combinatorial Optimization,Q.2018,False,,Springer,Not available,Bin packing game with a price of anarchy of ,28065c382f0bd8af770924056bfea4a6,http://dx.doi.org/10.1007/s10878-017-0201-6
196,We consider the bin packing problem in the non-cooperative game setting. In the game there are a set of items with sizes between 0 and 1 and a number of bins each with a capacity of 1. Each item seeks to be packed in one of the bins so as to minimize its cost (payoff). The social cost is the number of bins used in the packing. Existing research has focused on three bin packing games with selfish items  namely the Unit game  the Proportional game  and the General Weight game  each of which uses a unique payoff rule. In this paper we propose a new bin packing game in which the payoff of an item is a function of its own size and the size of the maximum item in the same bin. We find that the new payoff rule induces the items to reach a better Nash equilibrium. We show that the price of anarchy of the new bin packing game is ,t. sun,Not available,2018.0,10.1007/s10878-017-0201-6,Journal of Combinatorial Optimization,Q.2018,False,,Springer,Not available,Bin packing game with a price of anarchy of ,28065c382f0bd8af770924056bfea4a6,http://dx.doi.org/10.1007/s10878-017-0201-6
197,We consider the bin packing problem in the non-cooperative game setting. In the game there are a set of items with sizes between 0 and 1 and a number of bins each with a capacity of 1. Each item seeks to be packed in one of the bins so as to minimize its cost (payoff). The social cost is the number of bins used in the packing. Existing research has focused on three bin packing games with selfish items  namely the Unit game  the Proportional game  and the General Weight game  each of which uses a unique payoff rule. In this paper we propose a new bin packing game in which the payoff of an item is a function of its own size and the size of the maximum item in the same bin. We find that the new payoff rule induces the items to reach a better Nash equilibrium. We show that the price of anarchy of the new bin packing game is ,t. cheng,Not available,2018.0,10.1007/s10878-017-0201-6,Journal of Combinatorial Optimization,Q.2018,False,,Springer,Not available,Bin packing game with a price of anarchy of ,28065c382f0bd8af770924056bfea4a6,http://dx.doi.org/10.1007/s10878-017-0201-6
198,We consider the bin packing problem in the non-cooperative game setting. In the game there are a set of items with sizes between 0 and 1 and a number of bins each with a capacity of 1. Each item seeks to be packed in one of the bins so as to minimize its cost (payoff). The social cost is the number of bins used in the packing. Existing research has focused on three bin packing games with selfish items  namely the Unit game  the Proportional game  and the General Weight game  each of which uses a unique payoff rule. In this paper we propose a new bin packing game in which the payoff of an item is a function of its own size and the size of the maximum item in the same bin. We find that the new payoff rule induces the items to reach a better Nash equilibrium. We show that the price of anarchy of the new bin packing game is ,q. fang,Not available,2018.0,10.1007/s10878-017-0201-6,Journal of Combinatorial Optimization,Q.2018,False,,Springer,Not available,Bin packing game with a price of anarchy of ,28065c382f0bd8af770924056bfea4a6,http://dx.doi.org/10.1007/s10878-017-0201-6
199,Pricing plays a central rule to a company’s profitability  and therefore has been extensively studied in the literature of economics. When designing a pricing mechanism/ model  an important principle to consider is “price discrimination”  which refers to selling the same resources with different prices according to different values of buyers. To meet the “price discrimination” principle  especially when the number of buyers is large  computational methods  which act in a more accurate and principled way  are usually needed to determine the optimal allocation of sellers’ resources (,fei tian,Not available,2018.0,10.1007/s11704-017-6005-0,Frontiers of Computer Science,Fei2018,False,,Springer,Not available,Computational pricing in Internet era,d76995e376a077d380108ee6ce23c027,http://dx.doi.org/10.1007/s11704-017-6005-0
200,Pricing plays a central rule to a company’s profitability  and therefore has been extensively studied in the literature of economics. When designing a pricing mechanism/ model  an important principle to consider is “price discrimination”  which refers to selling the same resources with different prices according to different values of buyers. To meet the “price discrimination” principle  especially when the number of buyers is large  computational methods  which act in a more accurate and principled way  are usually needed to determine the optimal allocation of sellers’ resources (,tao qin,Not available,2018.0,10.1007/s11704-017-6005-0,Frontiers of Computer Science,Fei2018,False,,Springer,Not available,Computational pricing in Internet era,d76995e376a077d380108ee6ce23c027,http://dx.doi.org/10.1007/s11704-017-6005-0
201,We study the price of anarchy for selfish multicast routing games in directed multigraphs with latency functions on the edges  extending the known theory for the unicast situation  and exhibiting new phenomena not present in the unicast model. In the multicast model we have ,lasse kliemann,Not available,2006.0,10.1007/11922377_2,Combinatorial and Algorithmic Aspects of Networking,Andreas2006,False,,Springer,Not available,The Price of Anarchy in Selfish Multicast Routing,b1d401e386f330d746ee0d1e8c066dc0,http://dx.doi.org/10.1007/11922377_2
202,Pricing plays a central rule to a company’s profitability  and therefore has been extensively studied in the literature of economics. When designing a pricing mechanism/ model  an important principle to consider is “price discrimination”  which refers to selling the same resources with different prices according to different values of buyers. To meet the “price discrimination” principle  especially when the number of buyers is large  computational methods  which act in a more accurate and principled way  are usually needed to determine the optimal allocation of sellers’ resources (,tie-yan liu,Not available,2018.0,10.1007/s11704-017-6005-0,Frontiers of Computer Science,Fei2018,False,,Springer,Not available,Computational pricing in Internet era,d76995e376a077d380108ee6ce23c027,http://dx.doi.org/10.1007/s11704-017-6005-0
203,In this paper  we analytically compare centralized and decentralized market designs involving a national and local market operators  strategic generators having market power and bidding sequentially in local markets  to determine which design is more efficient for the procurement of energy. In the centralized design  used as benchmark  the national market operator optimizes the exchanges between local markets and the generators’ block bids. In the decentralized design  generators act as Stackelberg leaders  anticipating the local market prices and the flows on the transmission lines. Clearing of the local markets can be either simultaneous or sequential. The resulting two-stage game with competitive leaders that are not price takers is formulated as a bilevel mathematical programming problem which is reformulated as a Nash–Cournot game  and conditions for existence and uniqueness of market equilibrium are studied. Imperfect information is also considered  resulting from the lack of incentives from the generators to share their RES-based generations. Through a case study  we determine that the decentralized design is as efficient as the centralized one with high share of renewables  using as performance measure the price of anarchy  and that imperfect information has a limited impact on the efficiency of the decentralized market design. Furthermore  we check numerically that there exists an upper-limit on the block bid length maximizing the social welfare under both centralized and decentralized designs.,cadre le,Not available,2018.0,10.1007/s10100-018-0521-3,Central European Journal of Operations Research,Hélène2018,False,,Springer,Not available,On the efficiency of local electricity markets under decentralized and centralized designs: a multi-leader Stackelberg game analysis,d60c05a492f15b18a01ddbe27b24e2dc,http://dx.doi.org/10.1007/s10100-018-0521-3
204,We consider nonatomic routing games with one source and one destination connected by multiple parallel edges. We examine the asymptotic behavior of the price of anarchy as the inflow increases. In accordance with some empirical observations  we prove that under suitable conditions on the costs the price of anarchy is asymptotic to one. We show with some counterexamples that this is not always the case  and that these counterexamples already occur in simple networks with only 2 parallel links.,riccardo colini-baldeschi,Not available,2018.0,10.1007/s00224-017-9834-1,Theory of Computing Systems,Riccardo2018,False,,Springer,Not available,Price of Anarchy for Highly Congested Routing Games in Parallel Networks,4616b27e20dd04e8e2a90385909df9e4,http://dx.doi.org/10.1007/s00224-017-9834-1
205,We consider nonatomic routing games with one source and one destination connected by multiple parallel edges. We examine the asymptotic behavior of the price of anarchy as the inflow increases. In accordance with some empirical observations  we prove that under suitable conditions on the costs the price of anarchy is asymptotic to one. We show with some counterexamples that this is not always the case  and that these counterexamples already occur in simple networks with only 2 parallel links.,roberto cominetti,Not available,2018.0,10.1007/s00224-017-9834-1,Theory of Computing Systems,Riccardo2018,False,,Springer,Not available,Price of Anarchy for Highly Congested Routing Games in Parallel Networks,4616b27e20dd04e8e2a90385909df9e4,http://dx.doi.org/10.1007/s00224-017-9834-1
206,We consider nonatomic routing games with one source and one destination connected by multiple parallel edges. We examine the asymptotic behavior of the price of anarchy as the inflow increases. In accordance with some empirical observations  we prove that under suitable conditions on the costs the price of anarchy is asymptotic to one. We show with some counterexamples that this is not always the case  and that these counterexamples already occur in simple networks with only 2 parallel links.,marco scarsini,Not available,2018.0,10.1007/s00224-017-9834-1,Theory of Computing Systems,Riccardo2018,False,,Springer,Not available,Price of Anarchy for Highly Congested Routing Games in Parallel Networks,4616b27e20dd04e8e2a90385909df9e4,http://dx.doi.org/10.1007/s00224-017-9834-1
207,We consider the atomic version of congestion games with affine cost functions  and analyze the quality of worst case Nash equilibria when the strategy spaces of the players are the set of bases of a ,jasper jong,Not available,2018.0,10.1007/978-3-319-89441-6_23,Approximation and Online Algorithms,Jasper2018,False,,Springer,Not available,The Asymptotic Price of Anarchy for ,00618f82c04fd214aaeab77c1c407304,http://dx.doi.org/10.1007/978-3-319-89441-6_23
208,We consider the atomic version of congestion games with affine cost functions  and analyze the quality of worst case Nash equilibria when the strategy spaces of the players are the set of bases of a ,walter kern,Not available,2018.0,10.1007/978-3-319-89441-6_23,Approximation and Online Algorithms,Jasper2018,False,,Springer,Not available,The Asymptotic Price of Anarchy for ,00618f82c04fd214aaeab77c1c407304,http://dx.doi.org/10.1007/978-3-319-89441-6_23
209,We consider the atomic version of congestion games with affine cost functions  and analyze the quality of worst case Nash equilibria when the strategy spaces of the players are the set of bases of a ,berend steenhuisen,Not available,2018.0,10.1007/978-3-319-89441-6_23,Approximation and Online Algorithms,Jasper2018,False,,Springer,Not available,The Asymptotic Price of Anarchy for ,00618f82c04fd214aaeab77c1c407304,http://dx.doi.org/10.1007/978-3-319-89441-6_23
210,We consider the atomic version of congestion games with affine cost functions  and analyze the quality of worst case Nash equilibria when the strategy spaces of the players are the set of bases of a ,marc uetz,Not available,2018.0,10.1007/978-3-319-89441-6_23,Approximation and Online Algorithms,Jasper2018,False,,Springer,Not available,The Asymptotic Price of Anarchy for ,00618f82c04fd214aaeab77c1c407304,http://dx.doi.org/10.1007/978-3-319-89441-6_23
211,This chapter provides a general overview of the topic of network games  its application in a number of areas  and recent advances  by focusing on four major types of games  namely  congestion games  resource allocation games  diffusion games  and network formation games. Several algorithmic aspects and methodologies for analyzing such games are discussed  and connections between network games and other relevant topical areas are identified.,s. etesami,Not available,2018.0,10.1007/978-3-319-44374-4_10,Handbook of Dynamic Game Theory,Rasoul2018,False,,Springer,Not available,Network Games,d317f06cd95b03b4058dbc1a3cc788bf,http://dx.doi.org/10.1007/978-3-319-44374-4_10
212,We study the price of anarchy for selfish multicast routing games in directed multigraphs with latency functions on the edges  extending the known theory for the unicast situation  and exhibiting new phenomena not present in the unicast model. In the multicast model we have ,anand srivastav,Not available,2006.0,10.1007/11922377_2,Combinatorial and Algorithmic Aspects of Networking,Andreas2006,False,,Springer,Not available,The Price of Anarchy in Selfish Multicast Routing,b1d401e386f330d746ee0d1e8c066dc0,http://dx.doi.org/10.1007/11922377_2
213,This chapter provides a general overview of the topic of network games  its application in a number of areas  and recent advances  by focusing on four major types of games  namely  congestion games  resource allocation games  diffusion games  and network formation games. Several algorithmic aspects and methodologies for analyzing such games are discussed  and connections between network games and other relevant topical areas are identified.,tamer basar,Not available,2018.0,10.1007/978-3-319-44374-4_10,Handbook of Dynamic Game Theory,Rasoul2018,False,,Springer,Not available,Network Games,d317f06cd95b03b4058dbc1a3cc788bf,http://dx.doi.org/10.1007/978-3-319-44374-4_10
214,Globally operating suppliers face the rising challenge of wholesale pricing under scarce data about retail demand  in contrast to better informed  locally operating retailers. At the same time  as local businesses proliferate  markets congest and retail competition increases. To capture these strategic considerations  we employ the classic Cournot model and extend it to a two-stage supply chain with an upstream supplier who operates under demand uncertainty and multiple downstream retailers who compete over quantity. The supplier’s belief about retail demand is modeled via a continuous probability distribution function ,costis melolidakis,Not available,2018.0,10.1007/978-3-319-99383-6_21,Belief Functions: Theory and Applications,Costis2018,False,,Springer,Not available,Measuring Market Performance with Stochastic Demand: Price of Anarchy and Price of Uncertainty,22c259144d733592b1bdbb752fbd0c16,http://dx.doi.org/10.1007/978-3-319-99383-6_21
215,Globally operating suppliers face the rising challenge of wholesale pricing under scarce data about retail demand  in contrast to better informed  locally operating retailers. At the same time  as local businesses proliferate  markets congest and retail competition increases. To capture these strategic considerations  we employ the classic Cournot model and extend it to a two-stage supply chain with an upstream supplier who operates under demand uncertainty and multiple downstream retailers who compete over quantity. The supplier’s belief about retail demand is modeled via a continuous probability distribution function ,stefanos leonardos,Not available,2018.0,10.1007/978-3-319-99383-6_21,Belief Functions: Theory and Applications,Costis2018,False,,Springer,Not available,Measuring Market Performance with Stochastic Demand: Price of Anarchy and Price of Uncertainty,22c259144d733592b1bdbb752fbd0c16,http://dx.doi.org/10.1007/978-3-319-99383-6_21
216,Globally operating suppliers face the rising challenge of wholesale pricing under scarce data about retail demand  in contrast to better informed  locally operating retailers. At the same time  as local businesses proliferate  markets congest and retail competition increases. To capture these strategic considerations  we employ the classic Cournot model and extend it to a two-stage supply chain with an upstream supplier who operates under demand uncertainty and multiple downstream retailers who compete over quantity. The supplier’s belief about retail demand is modeled via a continuous probability distribution function ,constandina koki,Not available,2018.0,10.1007/978-3-319-99383-6_21,Belief Functions: Theory and Applications,Costis2018,False,,Springer,Not available,Measuring Market Performance with Stochastic Demand: Price of Anarchy and Price of Uncertainty,22c259144d733592b1bdbb752fbd0c16,http://dx.doi.org/10.1007/978-3-319-99383-6_21
217,We study the Price of Anarchy (PoA) of the competitive cascade game following the framework proposed by Goyal and Kearns in [11]. Our main insight is that a reduction to a Linear Threshold Model in a time-expanded graph establishes the submodularity of the social utility function. From this observation  we deduce that the game is a valid utility game  which in turn implies an upper bound of 2 on the (coarse) PoA. This cleaner understanding of the model yields a simpler proof of a much more general result than that established by Goyal and Kearns: for the ,xinran he,Not available,2013.0,10.1007/978-3-642-45046-4_20,Web and Internet Economics,Xinran2013,False,,Springer,Not available,Price of Anarchy for the ,a424a10c12b175f7eec2a2d2ecdc92b7,http://dx.doi.org/10.1007/978-3-642-45046-4_20
218,We study the Price of Anarchy (PoA) of the competitive cascade game following the framework proposed by Goyal and Kearns in [11]. Our main insight is that a reduction to a Linear Threshold Model in a time-expanded graph establishes the submodularity of the social utility function. From this observation  we deduce that the game is a valid utility game  which in turn implies an upper bound of 2 on the (coarse) PoA. This cleaner understanding of the model yields a simpler proof of a much more general result than that established by Goyal and Kearns: for the ,david kempe,Not available,2013.0,10.1007/978-3-642-45046-4_20,Web and Internet Economics,Xinran2013,False,,Springer,Not available,Price of Anarchy for the ,a424a10c12b175f7eec2a2d2ecdc92b7,http://dx.doi.org/10.1007/978-3-642-45046-4_20
219,Game theory plays a central role in studying systems with a number of interacting players competing for a common resource. A communication network serves as a prototypical example of such a system  where the common resource is the network  consisting of nodes and links with limited capacities  and the players are the computers  web servers  and other end hosts who want to transfer information over the shared network. In this entry  we present several examples of game-theoretic interaction in communication networks and present a simple mathematical model to study one such instance  namely  resource allocation in the Internet.,r. srikant,Not available,2013.0,10.1007/978-1-4471-5102-9_35-1,Encyclopedia of Systems and Control,R.2013,False,,Springer,Not available,Network Games,169479e102f801b987a530838c1c3aa4,http://dx.doi.org/10.1007/978-1-4471-5102-9_35-1
220,In this paper we show that the price of stability of Shapley network design games on undirected graphs with ,yann disser,Not available,2013.0,10.1007/978-3-642-38233-8_14,Algorithms and Complexity,Yann2013,False,,Springer,Not available,Improving the ,0e4d0d3699d5f568fde88f6a68005b45,http://dx.doi.org/10.1007/978-3-642-38233-8_14
221,In this paper we show that the price of stability of Shapley network design games on undirected graphs with ,andreas feldmann,Not available,2013.0,10.1007/978-3-642-38233-8_14,Algorithms and Complexity,Yann2013,False,,Springer,Not available,Improving the ,0e4d0d3699d5f568fde88f6a68005b45,http://dx.doi.org/10.1007/978-3-642-38233-8_14
222,In this paper we show that the price of stability of Shapley network design games on undirected graphs with ,max klimm,Not available,2013.0,10.1007/978-3-642-38233-8_14,Algorithms and Complexity,Yann2013,False,,Springer,Not available,Improving the ,0e4d0d3699d5f568fde88f6a68005b45,http://dx.doi.org/10.1007/978-3-642-38233-8_14
223,As defined by Aumann in 1959  a strong equilibrium is a Nash equilibrium that is resilient to deviations by coalitions. We give tight bounds on the strong price of anarchy for load balancing on related machines. We also give tight bounds for ,amos fiat,Not available,2007.0,10.1007/978-3-540-73420-8_51,Automata  Languages and Programming,Amos2007,False,,Springer,Not available,Strong Price of Anarchy for Machine Load Balancing,e62a88eac6ef598fa8bf2eb73a687dae,http://dx.doi.org/10.1007/978-3-540-73420-8_51
224,In this paper we address the open problem of bounding the price of stability for network design with fair cost allocation for undirected graphs posed in [1]. We consider the case where there is an agent in every vertex. We show that the price of stability is ,amos fiat,Not available,2006.0,10.1007/11786986_53,Automata  Languages and Programming,Amos2006,False,,Springer,Not available,On the Price of Stability for Designing Undirected Networks with Fair Cost Allocations,dc7702590c158b52ac38c43e29c1c89a,http://dx.doi.org/10.1007/11786986_53
225,In this paper we show that the price of stability of Shapley network design games on undirected graphs with ,matus mihalak,Not available,2013.0,10.1007/978-3-642-38233-8_14,Algorithms and Complexity,Yann2013,False,,Springer,Not available,Improving the ,0e4d0d3699d5f568fde88f6a68005b45,http://dx.doi.org/10.1007/978-3-642-38233-8_14
226,In value-cost dynamic games multiple agents adjust the flow and allocation of investments to action pathways that affect the value of other agents. This article determines conditions for cooperation among agents who invest to gain value from each other. These conditions are specified in a game-theoretic setting for agents that invest to realize cooperative benefits and value targets. The dynamic interaction of allocation priorities and the stability of equilibrium concepts is analyzed. One focus is to determine solutions concepts based on cost-exchange ratios and benefit-exchange ratios that represent trade-offs between the agents  as a function of the action and interaction effects of the respective action pathways. The general approach is applied to the trading between buyers and sellers of goods to determine conditions for mutually beneficial market exchange  the price of goods  and the specialization between consumers and producers.,jurgen scheffran,Not available,2013.0,10.1007/978-3-319-02690-9_9,Advances in Dynamic Games,Jürgen2013,False,,Springer,Not available,Conditions for Cooperation and Trading in Value-Cost Dynamic Games,aaaa637a09237fde43d4792415b0cbce,http://dx.doi.org/10.1007/978-3-319-02690-9_9
227,Social networks offer users new means of accessing information  essentially relying on “social filtering”  i.e. propagation and filtering of information by social contacts. The sheer amount of data flowing in these networks  combined with the limited budget of attention of each user  makes it difficult to ensure that social filtering brings relevant content to interested users. Our motivation in this paper is to measure to what extent self-organization of a social network results in efficient social filtering.To this end we introduce ,nidhi hegde,Not available,2013.0,10.1007/978-3-319-03578-9_10,Structural Information and Communication Complexity,Nidhi2013,False,,Springer,Not available,Self-organizing Flows in Social Networks,3f475e9f2293015bd17f1ff301821246,http://dx.doi.org/10.1007/978-3-319-03578-9_10
228,Social networks offer users new means of accessing information  essentially relying on “social filtering”  i.e. propagation and filtering of information by social contacts. The sheer amount of data flowing in these networks  combined with the limited budget of attention of each user  makes it difficult to ensure that social filtering brings relevant content to interested users. Our motivation in this paper is to measure to what extent self-organization of a social network results in efficient social filtering.To this end we introduce ,laurent massoulie,Not available,2013.0,10.1007/978-3-319-03578-9_10,Structural Information and Communication Complexity,Nidhi2013,False,,Springer,Not available,Self-organizing Flows in Social Networks,3f475e9f2293015bd17f1ff301821246,http://dx.doi.org/10.1007/978-3-319-03578-9_10
229,Social networks offer users new means of accessing information  essentially relying on “social filtering”  i.e. propagation and filtering of information by social contacts. The sheer amount of data flowing in these networks  combined with the limited budget of attention of each user  makes it difficult to ensure that social filtering brings relevant content to interested users. Our motivation in this paper is to measure to what extent self-organization of a social network results in efficient social filtering.To this end we introduce ,laurent viennot,Not available,2013.0,10.1007/978-3-319-03578-9_10,Structural Information and Communication Complexity,Nidhi2013,False,,Springer,Not available,Self-organizing Flows in Social Networks,3f475e9f2293015bd17f1ff301821246,http://dx.doi.org/10.1007/978-3-319-03578-9_10
230,This paper studies a two-stage game with a manufacturer and a subcontractor who are faced by a production scheduling problem. The manufacturer has a set of jobs to process  a subset of which can be subcontracted to the subcontractor to reduce the tardiness cost. In the game  the subcontractor makes the first decision to ask for a unit price of his machine time to be used by the manufacturer  and then the manufacturer follows to decide which jobs to be subcontracted to process and how the production scheduling is made. We analyze the game and derive how the subcontractor can optimize the unit price to maximize his profit. We then investigate the performance of such a simple contract from the viewpoint of coordination  and propose two other contracts that can achieve coordination between the two players.,xiangtong qi,Not available,2012.0,10.1007/s10951-012-0273-1,Journal of Scheduling,Xiangtong2012,False,,Springer,Not available,Production scheduling with subcontracting: the subcontractor’s pricing game,25dcec3a107fca1ef8b79a5024c7437c,http://dx.doi.org/10.1007/s10951-012-0273-1
231,Communication networks are becoming ubiquitous and more and more competitive among revenue-maximizing providers  operating on potentially different technologies. In this paper  we propose to analyze thanks to game theory the competition of providers playing with access prices and fighting for customers. Considering a slotted-time model  the part of demand exceeding capacity is lost and has to be resent. We consider an access price for submitted packets  thus inducing a congestion pricing through losses. Customers therefore choose the provider with the cheapest average price per correctly transmitted unit of traffic.The model is a two-level game  the lower level for the distribution of customers among providers  and the upper level for the competition on prices among providers  taking into account what the subsequent repartition at the lower level will be. We prove that the upper level has a unique Nash equilibrium  for which the user repartition among different available providers is also unique  and  remarkably  efficient in the sense of social welfare (with a so-called price of anarchy equal to one). Moreover  even when adding a higher level game on capacity disclosure with a possibility of lying for providers  providers are better off being truthful  and the unique Nash equilibrium is thus unchanged.,patrick maille,Not available,2012.0,10.1007/s10479-011-0914-3,Annals of Operations Research,Patrick2012,False,,Springer,Not available,Competition among providers in loss networks,ea5fa8e4c115086a2bc1aa1ec8fcda26,http://dx.doi.org/10.1007/s10479-011-0914-3
232,Communication networks are becoming ubiquitous and more and more competitive among revenue-maximizing providers  operating on potentially different technologies. In this paper  we propose to analyze thanks to game theory the competition of providers playing with access prices and fighting for customers. Considering a slotted-time model  the part of demand exceeding capacity is lost and has to be resent. We consider an access price for submitted packets  thus inducing a congestion pricing through losses. Customers therefore choose the provider with the cheapest average price per correctly transmitted unit of traffic.The model is a two-level game  the lower level for the distribution of customers among providers  and the upper level for the competition on prices among providers  taking into account what the subsequent repartition at the lower level will be. We prove that the upper level has a unique Nash equilibrium  for which the user repartition among different available providers is also unique  and  remarkably  efficient in the sense of social welfare (with a so-called price of anarchy equal to one). Moreover  even when adding a higher level game on capacity disclosure with a possibility of lying for providers  providers are better off being truthful  and the unique Nash equilibrium is thus unchanged.,bruno tuffin,Not available,2012.0,10.1007/s10479-011-0914-3,Annals of Operations Research,Patrick2012,False,,Springer,Not available,Competition among providers in loss networks,ea5fa8e4c115086a2bc1aa1ec8fcda26,http://dx.doi.org/10.1007/s10479-011-0914-3
233,We study the network routing problem with restricted and related links. There are parallel links with possibly different speeds  between a source and a sink. Also there are users  and each user has a traffic of some weight to assign to one of the links from a subset of all the links  named his/her allowable set. The users choosing the same link suffer the same delay  which is equal to the total weight assigned to that link over its speed. A state of the system is called a Nash equilibrium if no user can decrease his/her delay by unilaterally changing his/her link. To measure the performance degradation of the system due to the selfish behavior of all the users  Koutsoupias and Papadimitriou proposed the notion Price of Anarchy (denoted by PoA)  which is the ratio of the maximum delay in the worst-case Nash equilibrium and in an optimal solution. The PoA for this restricted related model has been studied  and a linear lower bound was obtained. However in their bad instance  some users can only use extremely slow links. This is a little artificial and unlikely to appear in a real world. So in order to better understand this model  we introduce a parameter for the system  and prove a better Price of Anarchy in terms of the parameter. We also show an important application of our result in coordination mechanism design for task scheduling game. We propose a new coordination mechanism  ,pin-yan lu,Not available,2012.0,10.1007/s11390-012-1257-5,Journal of Computer Science and Technology,Pin-Yan2012,False,,Springer,Not available,Worst-Case Nash Equilibria in Restricted Routing,2de3bea0b186ce80b66b8537cd6e3825,http://dx.doi.org/10.1007/s11390-012-1257-5
234,We study the network routing problem with restricted and related links. There are parallel links with possibly different speeds  between a source and a sink. Also there are users  and each user has a traffic of some weight to assign to one of the links from a subset of all the links  named his/her allowable set. The users choosing the same link suffer the same delay  which is equal to the total weight assigned to that link over its speed. A state of the system is called a Nash equilibrium if no user can decrease his/her delay by unilaterally changing his/her link. To measure the performance degradation of the system due to the selfish behavior of all the users  Koutsoupias and Papadimitriou proposed the notion Price of Anarchy (denoted by PoA)  which is the ratio of the maximum delay in the worst-case Nash equilibrium and in an optimal solution. The PoA for this restricted related model has been studied  and a linear lower bound was obtained. However in their bad instance  some users can only use extremely slow links. This is a little artificial and unlikely to appear in a real world. So in order to better understand this model  we introduce a parameter for the system  and prove a better Price of Anarchy in terms of the parameter. We also show an important application of our result in coordination mechanism design for task scheduling game. We propose a new coordination mechanism  ,chang-yuan yu,Not available,2012.0,10.1007/s11390-012-1257-5,Journal of Computer Science and Technology,Pin-Yan2012,False,,Springer,Not available,Worst-Case Nash Equilibria in Restricted Routing,2de3bea0b186ce80b66b8537cd6e3825,http://dx.doi.org/10.1007/s11390-012-1257-5
235,In this paper we address the open problem of bounding the price of stability for network design with fair cost allocation for undirected graphs posed in [1]. We consider the case where there is an agent in every vertex. We show that the price of stability is ,haim kaplan,Not available,2006.0,10.1007/11786986_53,Automata  Languages and Programming,Amos2006,False,,Springer,Not available,On the Price of Stability for Designing Undirected Networks with Fair Cost Allocations,dc7702590c158b52ac38c43e29c1c89a,http://dx.doi.org/10.1007/11786986_53
236,We consider ,elliot anshelevich,Not available,2012.0,10.1007/s00453-011-9520-7,Algorithmica,Elliot2012,False,,Springer,Not available,Contribution Games in Networks,67c3e1f0d68025f386c69939ce1bb409,http://dx.doi.org/10.1007/s00453-011-9520-7
237,We consider ,martin hoefer,Not available,2012.0,10.1007/s00453-011-9520-7,Algorithmica,Elliot2012,False,,Springer,Not available,Contribution Games in Networks,67c3e1f0d68025f386c69939ce1bb409,http://dx.doi.org/10.1007/s00453-011-9520-7
238,In this paper  we study two models of resource allocation games: the classical load-balancing game and its new variant involving resource activation costs. The resources we consider are identical and the social costs of the games are utilitarian  which are the average of all individual players’ costs.Using the social costs we assess the quality of pure Nash equilibria in terms of the price of anarchy (PoA) and the price of stability (PoS). For each game problem  we identify suitable problem parameters and provide a parametric bound on the PoA and the PoS. In the case of the load-balancing game  the parametric bounds we provide are sharp and asymptotically tight.,bo chen,Not available,2012.0,10.1007/s10951-011-0247-8,Journal of Scheduling,Bo2012,False,,Springer,Not available,Efficiency analysis of load balancing games with and without activation costs,1b69d40d89f6aa6e1406fba8462c99fb,http://dx.doi.org/10.1007/s10951-011-0247-8
239,In this paper  we study two models of resource allocation games: the classical load-balancing game and its new variant involving resource activation costs. The resources we consider are identical and the social costs of the games are utilitarian  which are the average of all individual players’ costs.Using the social costs we assess the quality of pure Nash equilibria in terms of the price of anarchy (PoA) and the price of stability (PoS). For each game problem  we identify suitable problem parameters and provide a parametric bound on the PoA and the PoS. In the case of the load-balancing game  the parametric bounds we provide are sharp and asymptotically tight.,sinan gurel,Not available,2012.0,10.1007/s10951-011-0247-8,Journal of Scheduling,Bo2012,False,,Springer,Not available,Efficiency analysis of load balancing games with and without activation costs,1b69d40d89f6aa6e1406fba8462c99fb,http://dx.doi.org/10.1007/s10951-011-0247-8
240,In this paper we consider all-optical networks in which a service provider has to satisfy a given set of communication requests. Each request is charged a cost depending on its wavelength and on the wavelengths of the other requests met along its path in the network. Under the assumption that each request is issued by a selfish agent  we seek for payment strategies which can guarantee the existence of a pure Nash equilibrium  that is an assignment of paths to the requests so that no request can lower its cost by choosing a different path in the network. For such strategies  we bound the loss of performance of the network (price of anarchy) by comparing the number of wavelengths used by the worst pure Nash equilibrium with that of a centralized optimal solution.,vittorio bilo,Not available,2004.0,DOItmp_0558_015963,Structural Information and Communication Complexity,Vittorio2004,False,,Springer,Not available,The Price of Anarchy in All-Optical Networks,ca89bb010b2d3d94036b6372c72b15d7,http://dx.doi.org/DOItmp_0558_015963
241,In this paper we consider all-optical networks in which a service provider has to satisfy a given set of communication requests. Each request is charged a cost depending on its wavelength and on the wavelengths of the other requests met along its path in the network. Under the assumption that each request is issued by a selfish agent  we seek for payment strategies which can guarantee the existence of a pure Nash equilibrium  that is an assignment of paths to the requests so that no request can lower its cost by choosing a different path in the network. For such strategies  we bound the loss of performance of the network (price of anarchy) by comparing the number of wavelengths used by the worst pure Nash equilibrium with that of a centralized optimal solution.,luca moscardelli,Not available,2004.0,DOItmp_0558_015963,Structural Information and Communication Complexity,Vittorio2004,False,,Springer,Not available,The Price of Anarchy in All-Optical Networks,ca89bb010b2d3d94036b6372c72b15d7,http://dx.doi.org/DOItmp_0558_015963
242,In this paper we consider all-optical networks in which a service provider has to satisfy a given set of communication requests. Each request is charged a cost depending on its wavelength and on the wavelengths of the other requests met along its path in the network. Under the assumption that each request is issued by a selfish agent  we seek for payment strategies which can guarantee the existence of a pure Nash equilibrium  that is an assignment of paths to the requests so that no request can lower its cost by choosing a different path in the network. For such strategies  we bound the loss of performance of the network (price of anarchy) by comparing the number of wavelengths used by the worst pure Nash equilibrium with that of a centralized optimal solution.,vittorio bilo,Not available,2004.0,10.1007/978-3-540-27796-5_2,Structural Information and Communication Complexity,Vittorio2004,False,,Springer,Not available,The Price of Anarchy in All-Optical Networks,ca89bb010b2d3d94036b6372c72b15d7,http://dx.doi.org/10.1007/978-3-540-27796-5_2
243,In this paper we consider all-optical networks in which a service provider has to satisfy a given set of communication requests. Each request is charged a cost depending on its wavelength and on the wavelengths of the other requests met along its path in the network. Under the assumption that each request is issued by a selfish agent  we seek for payment strategies which can guarantee the existence of a pure Nash equilibrium  that is an assignment of paths to the requests so that no request can lower its cost by choosing a different path in the network. For such strategies  we bound the loss of performance of the network (price of anarchy) by comparing the number of wavelengths used by the worst pure Nash equilibrium with that of a centralized optimal solution.,luca moscardelli,Not available,2004.0,10.1007/978-3-540-27796-5_2,Structural Information and Communication Complexity,Vittorio2004,False,,Springer,Not available,The Price of Anarchy in All-Optical Networks,ca89bb010b2d3d94036b6372c72b15d7,http://dx.doi.org/10.1007/978-3-540-27796-5_2
244,Commutative justice is dependent upon the guideline of the prevailing price. Without the prevailing price as the bench mark  one cannot determine which individual price and contract satisfies the demands of commutative justice. If the individual price is subject to (individual-)ethical norms of justice and fairness  the standard of the individual price  the prevailing price  must satisfy ethical norms. Since the prevailing price in a market economy is the market price  the market price  as the standard of individual actual prices  must also satisfy ethical and social-ethical norms.,peter koslowski,Not available,2001.0,10.1007/978-94-010-0956-0_10,Principles of Ethical Economy,Peter2001,False,,Springer,Not available,Just Price Theory,22c2ed3ac531032a0e822a0d2f963daf,http://dx.doi.org/10.1007/978-94-010-0956-0_10
245,This paper considers a network comprised of parallel routes with the Bureau of Public Road (BPR) latency function and suggests an optimal distribution method for incoming traffic flow. The authors analytically derive a system of equations defining the optimal distribution of the incoming flow with minimum social costs  as well as a corresponding system of equations for the Wardrop equilibrium in this network. In particular  the Wardrop equilibrium is applied to the competition model with rational consumers who use the carriers with minimal cost  where cost is equal to the price for service plus the waiting time for the service. Finally  the social costs under the equilibrium and under the optimal distribution are compared. It is shown that the price of anarchy can be infinitely large in the model with strategic pricing.,jaimie lien,Not available,2016.0,10.1007/978-3-319-44914-2_4,Discrete Optimization and Operations Research,W.2016,False,,Springer,Not available,Wardrop Equilibrium for Networks with the BPR Latency Function,e93d33cf6628afbfee78e7571d796b02,http://dx.doi.org/10.1007/978-3-319-44914-2_4
246,In this paper we address the open problem of bounding the price of stability for network design with fair cost allocation for undirected graphs posed in [1]. We consider the case where there is an agent in every vertex. We show that the price of stability is ,meital levy,Not available,2006.0,10.1007/11786986_53,Automata  Languages and Programming,Amos2006,False,,Springer,Not available,On the Price of Stability for Designing Undirected Networks with Fair Cost Allocations,dc7702590c158b52ac38c43e29c1c89a,http://dx.doi.org/10.1007/11786986_53
247,This paper considers a network comprised of parallel routes with the Bureau of Public Road (BPR) latency function and suggests an optimal distribution method for incoming traffic flow. The authors analytically derive a system of equations defining the optimal distribution of the incoming flow with minimum social costs  as well as a corresponding system of equations for the Wardrop equilibrium in this network. In particular  the Wardrop equilibrium is applied to the competition model with rational consumers who use the carriers with minimal cost  where cost is equal to the price for service plus the waiting time for the service. Finally  the social costs under the equilibrium and under the optimal distribution are compared. It is shown that the price of anarchy can be infinitely large in the model with strategic pricing.,vladimir mazalov,Not available,2016.0,10.1007/978-3-319-44914-2_4,Discrete Optimization and Operations Research,W.2016,False,,Springer,Not available,Wardrop Equilibrium for Networks with the BPR Latency Function,e93d33cf6628afbfee78e7571d796b02,http://dx.doi.org/10.1007/978-3-319-44914-2_4
248,This paper considers a network comprised of parallel routes with the Bureau of Public Road (BPR) latency function and suggests an optimal distribution method for incoming traffic flow. The authors analytically derive a system of equations defining the optimal distribution of the incoming flow with minimum social costs  as well as a corresponding system of equations for the Wardrop equilibrium in this network. In particular  the Wardrop equilibrium is applied to the competition model with rational consumers who use the carriers with minimal cost  where cost is equal to the price for service plus the waiting time for the service. Finally  the social costs under the equilibrium and under the optimal distribution are compared. It is shown that the price of anarchy can be infinitely large in the model with strategic pricing.,anna melnik,Not available,2016.0,10.1007/978-3-319-44914-2_4,Discrete Optimization and Operations Research,W.2016,False,,Springer,Not available,Wardrop Equilibrium for Networks with the BPR Latency Function,e93d33cf6628afbfee78e7571d796b02,http://dx.doi.org/10.1007/978-3-319-44914-2_4
249,This paper considers a network comprised of parallel routes with the Bureau of Public Road (BPR) latency function and suggests an optimal distribution method for incoming traffic flow. The authors analytically derive a system of equations defining the optimal distribution of the incoming flow with minimum social costs  as well as a corresponding system of equations for the Wardrop equilibrium in this network. In particular  the Wardrop equilibrium is applied to the competition model with rational consumers who use the carriers with minimal cost  where cost is equal to the price for service plus the waiting time for the service. Finally  the social costs under the equilibrium and under the optimal distribution are compared. It is shown that the price of anarchy can be infinitely large in the model with strategic pricing.,jie zheng,Not available,2016.0,10.1007/978-3-319-44914-2_4,Discrete Optimization and Operations Research,W.2016,False,,Springer,Not available,Wardrop Equilibrium for Networks with the BPR Latency Function,e93d33cf6628afbfee78e7571d796b02,http://dx.doi.org/10.1007/978-3-319-44914-2_4
250,The subset sum algorithm is a natural heuristic for the classical Bin Packing problem: In each iteration  the algorithm finds among the unpacked items  a maximum size set of items that fits into a new bin. More than 35 years after its first mention in the literature  establishing the worst-case performance of this heuristic remains  surprisingly  an open problem. Due to their simplicity and intuitive appeal  greedy algorithms are the heuristics of choice of many practitioners. Therefore  better understanding simple greedy heuristics is  in general  an interesting topic in its own right. Very recently  Epstein and Kleiman (Proc. ESA 2008  pp. 368–380) provided another incentive to study the subset sum algorithm by showing that the Strong Price of Anarchy of the game theoretic version of the Bin Packing problem is ,leah epstein,Not available,2016.0,10.1007/s00453-014-9942-0,Algorithmica,Leah2016,False,,Springer,Not available,Parametric Packing of Selfish Items and the Subset Sum Algorithm,867ca204a875c6e243fc9bcf532405c1,http://dx.doi.org/10.1007/s00453-014-9942-0
251,The subset sum algorithm is a natural heuristic for the classical Bin Packing problem: In each iteration  the algorithm finds among the unpacked items  a maximum size set of items that fits into a new bin. More than 35 years after its first mention in the literature  establishing the worst-case performance of this heuristic remains  surprisingly  an open problem. Due to their simplicity and intuitive appeal  greedy algorithms are the heuristics of choice of many practitioners. Therefore  better understanding simple greedy heuristics is  in general  an interesting topic in its own right. Very recently  Epstein and Kleiman (Proc. ESA 2008  pp. 368–380) provided another incentive to study the subset sum algorithm by showing that the Strong Price of Anarchy of the game theoretic version of the Bin Packing problem is ,elena kleiman,Not available,2016.0,10.1007/s00453-014-9942-0,Algorithmica,Leah2016,False,,Springer,Not available,Parametric Packing of Selfish Items and the Subset Sum Algorithm,867ca204a875c6e243fc9bcf532405c1,http://dx.doi.org/10.1007/s00453-014-9942-0
252,The subset sum algorithm is a natural heuristic for the classical Bin Packing problem: In each iteration  the algorithm finds among the unpacked items  a maximum size set of items that fits into a new bin. More than 35 years after its first mention in the literature  establishing the worst-case performance of this heuristic remains  surprisingly  an open problem. Due to their simplicity and intuitive appeal  greedy algorithms are the heuristics of choice of many practitioners. Therefore  better understanding simple greedy heuristics is  in general  an interesting topic in its own right. Very recently  Epstein and Kleiman (Proc. ESA 2008  pp. 368–380) provided another incentive to study the subset sum algorithm by showing that the Strong Price of Anarchy of the game theoretic version of the Bin Packing problem is ,julian mestre,Not available,2016.0,10.1007/s00453-014-9942-0,Algorithmica,Leah2016,False,,Springer,Not available,Parametric Packing of Selfish Items and the Subset Sum Algorithm,867ca204a875c6e243fc9bcf532405c1,http://dx.doi.org/10.1007/s00453-014-9942-0
253,Work at the intersection of computer science and game theory is briefly surveyed  with a focus on the work in computer science. In particular  the following topics are considered: various roles of computational complexity in game theory  including modelling bounded rationality  its role in mechanism design  and the problem of computing Nash equilibria; the ,joseph halpern,Not available,2016.0,10.1057/978-1-349-95121-5_2133-1,The New Palgrave Dictionary of Economics,Y.2016,False,,Springer,Not available,Computer Science and Game Theory,f24f1666c7eaa6d0033f8c99c65ed523,http://dx.doi.org/10.1057/978-1-349-95121-5_2133-1
254,In this paper  we consider the selfish bin covering problems  which can be viewed as the bin covering problems in game theoretic settings. Our main contribution is an incentive mechanism with better price of anarchy. Under this mechanism  for any instance with a Nash equilibrium (NE)  we show that price of anarchy is 2/3. For the cases that the NE does not exist  we propose a concept of modified NE  named M-NE  which can be obtained in finite steps from any initial state. We further show that for M-NE  the price of anarchy is 1/2 and the price of stability is 1.,weian li,Not available,2016.0,10.1007/978-3-319-48749-6_46,Combinatorial Optimization and Applications,Weian2016,False,,Springer,Not available,An Incentive Mechanism for Selfish Bin Covering,78c77fbb29b225438c3c6a6267afaf87,http://dx.doi.org/10.1007/978-3-319-48749-6_46
255,In this paper  we consider the selfish bin covering problems  which can be viewed as the bin covering problems in game theoretic settings. Our main contribution is an incentive mechanism with better price of anarchy. Under this mechanism  for any instance with a Nash equilibrium (NE)  we show that price of anarchy is 2/3. For the cases that the NE does not exist  we propose a concept of modified NE  named M-NE  which can be obtained in finite steps from any initial state. We further show that for M-NE  the price of anarchy is 1/2 and the price of stability is 1.,qizhi fang,Not available,2016.0,10.1007/978-3-319-48749-6_46,Combinatorial Optimization and Applications,Weian2016,False,,Springer,Not available,An Incentive Mechanism for Selfish Bin Covering,78c77fbb29b225438c3c6a6267afaf87,http://dx.doi.org/10.1007/978-3-319-48749-6_46
256,In this paper  we consider the selfish bin covering problems  which can be viewed as the bin covering problems in game theoretic settings. Our main contribution is an incentive mechanism with better price of anarchy. Under this mechanism  for any instance with a Nash equilibrium (NE)  we show that price of anarchy is 2/3. For the cases that the NE does not exist  we propose a concept of modified NE  named M-NE  which can be obtained in finite steps from any initial state. We further show that for M-NE  the price of anarchy is 1/2 and the price of stability is 1.,wenjing liu,Not available,2016.0,10.1007/978-3-319-48749-6_46,Combinatorial Optimization and Applications,Weian2016,False,,Springer,Not available,An Incentive Mechanism for Selfish Bin Covering,78c77fbb29b225438c3c6a6267afaf87,http://dx.doi.org/10.1007/978-3-319-48749-6_46
257,In this paper we address the open problem of bounding the price of stability for network design with fair cost allocation for undirected graphs posed in [1]. We consider the case where there is an agent in every vertex. We show that the price of stability is ,svetlana olonetsky,Not available,2006.0,10.1007/11786986_53,Automata  Languages and Programming,Amos2006,False,,Springer,Not available,On the Price of Stability for Designing Undirected Networks with Fair Cost Allocations,dc7702590c158b52ac38c43e29c1c89a,http://dx.doi.org/10.1007/11786986_53
258,We study the design of cost-sharing protocols for two fundamental resource allocation problems  the ,george christodoulou,Not available,2016.0,10.1007/978-3-662-53354-3_26,Algorithmic Game Theory,George2016,False,,Springer,Not available,Designing Cost-Sharing Methods for Bayesian Games,c1421ef7ca0260ead94d8c5003bb4a14,http://dx.doi.org/10.1007/978-3-662-53354-3_26
259,We study the design of cost-sharing protocols for two fundamental resource allocation problems  the ,stefano leonardi,Not available,2016.0,10.1007/978-3-662-53354-3_26,Algorithmic Game Theory,George2016,False,,Springer,Not available,Designing Cost-Sharing Methods for Bayesian Games,c1421ef7ca0260ead94d8c5003bb4a14,http://dx.doi.org/10.1007/978-3-662-53354-3_26
260,We study the design of cost-sharing protocols for two fundamental resource allocation problems  the ,alkmini sgouritsa,Not available,2016.0,10.1007/978-3-662-53354-3_26,Algorithmic Game Theory,George2016,False,,Springer,Not available,Designing Cost-Sharing Methods for Bayesian Games,c1421ef7ca0260ead94d8c5003bb4a14,http://dx.doi.org/10.1007/978-3-662-53354-3_26
261,In this model of network formation  players anticipate the destruction of one link  which is chosen according to a known probability distribution. Their cost is the cost for building links plus the expected number of other players to which connection will be lost as a result of the link destruction. We consider different equilibrium concepts (Nash equilibrium  pairwise Nash equilibrium  pairwise stability) and two different ways in which the probability distribution depends on the network.,lasse kliemann,Not available,2016.0,10.1007/978-3-319-28697-6_40,Operations Research Proceedings 2014,Lasse2016,False,,Springer,Not available,Price of Anarchy in the Link Destruction (Adversary) Model,f3e7be9ccca40b9fbd5102561eade60f,http://dx.doi.org/10.1007/978-3-319-28697-6_40
262,In this chapter the authors describe Juglar cycles  provide a brief history of their study  and then concentrate on aspects of the relationship between the medium-term (7–11 years) Juglar cycles (J-cycles) and long (40–60 years) Kondratieff cycles (K-waves). Such an approach can greatly clarify the causes of alternation of upward and downward phases within the Kondratieff waves  and the reasons for the relative stability of the length of these waves. They proceed from the fact that long-term processes must have appropriate causes. For K-waves such causes are rooted in the very nature of the expanded reproduction of the economy  but less long pulses (associated with alternating J-cycles) streamline periodicity. J-cycles are the only real factor that can set the rhythm of Kondratieff waves and their phases.The point is that adjacent 2–4 medium cycles form a system that affects dynamics of economic trend. The latter can be an upswing (active) or a downswing (depressive). The mechanisms of formation of such medium-term trends and changing tendencies are explained in this chapter. The presence of such clusters of medium cycles (general duration of which is 20–30 years) determines to a large degree the long-wave dynamics and its timing characteristics. It also can provide certain means for forecasting  and the respective chapter contains such forecasts.This chapter provides a verbal model of Kondratieff waves  based on the close relationship between the medium-term (7–11 years) Juglar cycles and K-waves as well as on idea that the relative duration and regularity of change of K-wave phases is determined by the nature of nearby chains or clusters of J-cycles.A chain-cluster of J-cycles with less pronounced depressions  and more durable pronounced expansions is denoted as “A-cluster”  whereas a chain-cluster of J-cycles with more pronounced depressions and less intense and less prolonged expansions is denoted as “B-cluster”. During the K-wave A-phase the fast economic expansion leads inevitably to the necessity of societal change; as a result  B-phase starts. But the possibilities of societal transformation lag behind the demands of the economy  that is why periods of such a restructuring correspond to periods of more difficult development  that is  to K-wave downswings.The model proposed in this chapter suggests that one can observe an evident negative feedback between the K-wave trends  which strengthens with each new medium-term cycle (until the trend does not change)  since the nature and results of each J-cycle is a signal for a particular type of action of active participants in the process (from individual entrepreneurs to governments and supranational organizations). The model also shows that for an adequate understanding of the nature of Kondratieff waves it is necessary to consider their effect firstly at the World System level.The authors also focus on how and why the main K-wave dynamics indicators change. Starting from the Great Depression the economic growth became one of the main concerns of the state. However the price upswings and downswings have not vanished completely; indeed  the recent deflation trend demonstrates this quite convincingly.,leonid grinin,Not available,2016.0,10.1007/978-3-319-41262-7_3,Economic Cycles  Crises  and the Global Periphery,Leonid2016,False,,Springer,Not available,Interaction between Kondratieff Waves and Juglar Cycles,37ae34a2084cd39981185a1da013c8c3,http://dx.doi.org/10.1007/978-3-319-41262-7_3
263,In this chapter the authors describe Juglar cycles  provide a brief history of their study  and then concentrate on aspects of the relationship between the medium-term (7–11 years) Juglar cycles (J-cycles) and long (40–60 years) Kondratieff cycles (K-waves). Such an approach can greatly clarify the causes of alternation of upward and downward phases within the Kondratieff waves  and the reasons for the relative stability of the length of these waves. They proceed from the fact that long-term processes must have appropriate causes. For K-waves such causes are rooted in the very nature of the expanded reproduction of the economy  but less long pulses (associated with alternating J-cycles) streamline periodicity. J-cycles are the only real factor that can set the rhythm of Kondratieff waves and their phases.The point is that adjacent 2–4 medium cycles form a system that affects dynamics of economic trend. The latter can be an upswing (active) or a downswing (depressive). The mechanisms of formation of such medium-term trends and changing tendencies are explained in this chapter. The presence of such clusters of medium cycles (general duration of which is 20–30 years) determines to a large degree the long-wave dynamics and its timing characteristics. It also can provide certain means for forecasting  and the respective chapter contains such forecasts.This chapter provides a verbal model of Kondratieff waves  based on the close relationship between the medium-term (7–11 years) Juglar cycles and K-waves as well as on idea that the relative duration and regularity of change of K-wave phases is determined by the nature of nearby chains or clusters of J-cycles.A chain-cluster of J-cycles with less pronounced depressions  and more durable pronounced expansions is denoted as “A-cluster”  whereas a chain-cluster of J-cycles with more pronounced depressions and less intense and less prolonged expansions is denoted as “B-cluster”. During the K-wave A-phase the fast economic expansion leads inevitably to the necessity of societal change; as a result  B-phase starts. But the possibilities of societal transformation lag behind the demands of the economy  that is why periods of such a restructuring correspond to periods of more difficult development  that is  to K-wave downswings.The model proposed in this chapter suggests that one can observe an evident negative feedback between the K-wave trends  which strengthens with each new medium-term cycle (until the trend does not change)  since the nature and results of each J-cycle is a signal for a particular type of action of active participants in the process (from individual entrepreneurs to governments and supranational organizations). The model also shows that for an adequate understanding of the nature of Kondratieff waves it is necessary to consider their effect firstly at the World System level.The authors also focus on how and why the main K-wave dynamics indicators change. Starting from the Great Depression the economic growth became one of the main concerns of the state. However the price upswings and downswings have not vanished completely; indeed  the recent deflation trend demonstrates this quite convincingly.,andrey korotayev,Not available,2016.0,10.1007/978-3-319-41262-7_3,Economic Cycles  Crises  and the Global Periphery,Leonid2016,False,,Springer,Not available,Interaction between Kondratieff Waves and Juglar Cycles,37ae34a2084cd39981185a1da013c8c3,http://dx.doi.org/10.1007/978-3-319-41262-7_3
264,In this chapter the authors describe Juglar cycles  provide a brief history of their study  and then concentrate on aspects of the relationship between the medium-term (7–11 years) Juglar cycles (J-cycles) and long (40–60 years) Kondratieff cycles (K-waves). Such an approach can greatly clarify the causes of alternation of upward and downward phases within the Kondratieff waves  and the reasons for the relative stability of the length of these waves. They proceed from the fact that long-term processes must have appropriate causes. For K-waves such causes are rooted in the very nature of the expanded reproduction of the economy  but less long pulses (associated with alternating J-cycles) streamline periodicity. J-cycles are the only real factor that can set the rhythm of Kondratieff waves and their phases.The point is that adjacent 2–4 medium cycles form a system that affects dynamics of economic trend. The latter can be an upswing (active) or a downswing (depressive). The mechanisms of formation of such medium-term trends and changing tendencies are explained in this chapter. The presence of such clusters of medium cycles (general duration of which is 20–30 years) determines to a large degree the long-wave dynamics and its timing characteristics. It also can provide certain means for forecasting  and the respective chapter contains such forecasts.This chapter provides a verbal model of Kondratieff waves  based on the close relationship between the medium-term (7–11 years) Juglar cycles and K-waves as well as on idea that the relative duration and regularity of change of K-wave phases is determined by the nature of nearby chains or clusters of J-cycles.A chain-cluster of J-cycles with less pronounced depressions  and more durable pronounced expansions is denoted as “A-cluster”  whereas a chain-cluster of J-cycles with more pronounced depressions and less intense and less prolonged expansions is denoted as “B-cluster”. During the K-wave A-phase the fast economic expansion leads inevitably to the necessity of societal change; as a result  B-phase starts. But the possibilities of societal transformation lag behind the demands of the economy  that is why periods of such a restructuring correspond to periods of more difficult development  that is  to K-wave downswings.The model proposed in this chapter suggests that one can observe an evident negative feedback between the K-wave trends  which strengthens with each new medium-term cycle (until the trend does not change)  since the nature and results of each J-cycle is a signal for a particular type of action of active participants in the process (from individual entrepreneurs to governments and supranational organizations). The model also shows that for an adequate understanding of the nature of Kondratieff waves it is necessary to consider their effect firstly at the World System level.The authors also focus on how and why the main K-wave dynamics indicators change. Starting from the Great Depression the economic growth became one of the main concerns of the state. However the price upswings and downswings have not vanished completely; indeed  the recent deflation trend demonstrates this quite convincingly.,arno tausch,Not available,2016.0,10.1007/978-3-319-41262-7_3,Economic Cycles  Crises  and the Global Periphery,Leonid2016,False,,Springer,Not available,Interaction between Kondratieff Waves and Juglar Cycles,37ae34a2084cd39981185a1da013c8c3,http://dx.doi.org/10.1007/978-3-319-41262-7_3
265,In this paper  we develop a competitive freight service provision network model for disaster relief. A humanitarian relief organization is interested in determining its most cost-effective deliveries of needed supplies in a crisis setting. Multiple freight service providers are engaged in competition to acquire the business of carrying the supplies in the amounts desired to the destinations. We describe the objective functions faced by the various decision-makers and their underlying constraints  and present the optimality conditions. We then define the freight service provision network equilibrium for disaster relief and formulate it as a variational inequality problem. We provide qualitative results for the equilibrium product shipment pattern in terms of existence and uniqueness. For completeness  we also construct a new cooperative system-optimization model and discuss the price of anarchy relating the two models  along with additional theoretical results. In addition  we propose algorithmic schemes that take advantage of the underlying network structure of the problem. We present a case study on the shipment of personal protective equipment supplies in the context of the Ebola humanitarian healthcare crisis in west Africa. The computational results in this paper yield insights on the equilibrium shipment and price patterns in the freight service provision sector for humanitarian operations in terms of enhanced or reduced competition  as well as increases in demand.,anna nagurney,Not available,2016.0,10.1007/978-3-319-43709-5_11,Dynamics of Disasters—Key Concepts  Models  Algorithms  and Insights,Anna2016,False,,Springer,Not available,Freight Service Provision for Disaster Relief: A Competitive Network Model with Computations,e02058159b903bbd4e317fa3ccc86543,http://dx.doi.org/10.1007/978-3-319-43709-5_11
266,,leah epstein,Not available,2016.0,10.1007/978-1-4939-2864-4_494,Encyclopedia of Algorithms,Leah2016,False,,Springer,Not available,Selfish Bin Packing Problems,a6f539efb1751a1db74ff23bceee3886,http://dx.doi.org/10.1007/978-1-4939-2864-4_494
267,In multicast network design games  a set of agents choose paths from their source locations to a common sink with the goal of minimizing their individual costs  where the cost of an edge is divided equally among the agents using it. Since the work of Anshelevich et al. (FOCS 2004) that introduced network design games  the main open problem in this field has been the price of stability (PoS) of multicast games. For the special case of broadcast games (every vertex is a terminal  i.e.  has an agent)  a series of works has culminated in a constant upper bound on the PoS (Bilò et al.  FOCS 2013). However  no significantly sub-logarithmic bound is known for multicast games. In this paper  we make progress toward resolving this question by showing a constant upper bound on the PoS of multicast games for quasi-bipartite graphs. These are graphs where all edges are between two terminals (as in broadcast games) or between a terminal and a nonterminal  but there is no edge between nonterminals. This represents a natural class of intermediate generality between broadcast and multicast games. In addition to the result itself  our techniques overcome some of the fundamental difficulties of analyzing the PoS of general multicast games  and are a promising step toward resolving this major open problem.,rupert freeman,Not available,2016.0,10.1007/978-3-662-54110-4_25,Web and Internet Economics,Rupert2016,False,,Springer,Not available,On the Price of Stability of Undirected Multicast Games,4770485068ce16dc56c401c90d24c15c,http://dx.doi.org/10.1007/978-3-662-54110-4_25
268,In this paper we address the open problem of bounding the price of stability for network design with fair cost allocation for undirected graphs posed in [1]. We consider the case where there is an agent in every vertex. We show that the price of stability is ,ronen shabo,Not available,2006.0,10.1007/11786986_53,Automata  Languages and Programming,Amos2006,False,,Springer,Not available,On the Price of Stability for Designing Undirected Networks with Fair Cost Allocations,dc7702590c158b52ac38c43e29c1c89a,http://dx.doi.org/10.1007/11786986_53
269,In multicast network design games  a set of agents choose paths from their source locations to a common sink with the goal of minimizing their individual costs  where the cost of an edge is divided equally among the agents using it. Since the work of Anshelevich et al. (FOCS 2004) that introduced network design games  the main open problem in this field has been the price of stability (PoS) of multicast games. For the special case of broadcast games (every vertex is a terminal  i.e.  has an agent)  a series of works has culminated in a constant upper bound on the PoS (Bilò et al.  FOCS 2013). However  no significantly sub-logarithmic bound is known for multicast games. In this paper  we make progress toward resolving this question by showing a constant upper bound on the PoS of multicast games for quasi-bipartite graphs. These are graphs where all edges are between two terminals (as in broadcast games) or between a terminal and a nonterminal  but there is no edge between nonterminals. This represents a natural class of intermediate generality between broadcast and multicast games. In addition to the result itself  our techniques overcome some of the fundamental difficulties of analyzing the PoS of general multicast games  and are a promising step toward resolving this major open problem.,samuel haney,Not available,2016.0,10.1007/978-3-662-54110-4_25,Web and Internet Economics,Rupert2016,False,,Springer,Not available,On the Price of Stability of Undirected Multicast Games,4770485068ce16dc56c401c90d24c15c,http://dx.doi.org/10.1007/978-3-662-54110-4_25
270,In multicast network design games  a set of agents choose paths from their source locations to a common sink with the goal of minimizing their individual costs  where the cost of an edge is divided equally among the agents using it. Since the work of Anshelevich et al. (FOCS 2004) that introduced network design games  the main open problem in this field has been the price of stability (PoS) of multicast games. For the special case of broadcast games (every vertex is a terminal  i.e.  has an agent)  a series of works has culminated in a constant upper bound on the PoS (Bilò et al.  FOCS 2013). However  no significantly sub-logarithmic bound is known for multicast games. In this paper  we make progress toward resolving this question by showing a constant upper bound on the PoS of multicast games for quasi-bipartite graphs. These are graphs where all edges are between two terminals (as in broadcast games) or between a terminal and a nonterminal  but there is no edge between nonterminals. This represents a natural class of intermediate generality between broadcast and multicast games. In addition to the result itself  our techniques overcome some of the fundamental difficulties of analyzing the PoS of general multicast games  and are a promising step toward resolving this major open problem.,debmalya panigrahi,Not available,2016.0,10.1007/978-3-662-54110-4_25,Web and Internet Economics,Rupert2016,False,,Springer,Not available,On the Price of Stability of Undirected Multicast Games,4770485068ce16dc56c401c90d24c15c,http://dx.doi.org/10.1007/978-3-662-54110-4_25
271,We consider the solution concept of stochastic stability  and propose the ,christine chung,Not available,2008.0,10.1007/978-3-540-79309-0_27,Algorithmic Game Theory,Christine2008,False,,Springer,Not available,The Price of Stochastic Anarchy,9e51e4972fd1f48f00cfdbc82f691338,http://dx.doi.org/10.1007/978-3-540-79309-0_27
272,We consider the solution concept of stochastic stability  and propose the ,katrina ligett,Not available,2008.0,10.1007/978-3-540-79309-0_27,Algorithmic Game Theory,Christine2008,False,,Springer,Not available,The Price of Stochastic Anarchy,9e51e4972fd1f48f00cfdbc82f691338,http://dx.doi.org/10.1007/978-3-540-79309-0_27
273,We consider the solution concept of stochastic stability  and propose the ,kirk pruhs,Not available,2008.0,10.1007/978-3-540-79309-0_27,Algorithmic Game Theory,Christine2008,False,,Springer,Not available,The Price of Stochastic Anarchy,9e51e4972fd1f48f00cfdbc82f691338,http://dx.doi.org/10.1007/978-3-540-79309-0_27
274,We consider the solution concept of stochastic stability  and propose the ,aaron roth,Not available,2008.0,10.1007/978-3-540-79309-0_27,Algorithmic Game Theory,Christine2008,False,,Springer,Not available,The Price of Stochastic Anarchy,9e51e4972fd1f48f00cfdbc82f691338,http://dx.doi.org/10.1007/978-3-540-79309-0_27
275,Recent interest in Nash equilibria led to a study of the ,leah epstein,Not available,2008.0,10.1007/978-3-540-79309-0_6,Algorithmic Game Theory,Leah2008,False,,Springer,Not available,The Price of Anarchy on Uniformly Related Machines Revisited,7a85847f1cba6bb30abffb576d051fa4,http://dx.doi.org/10.1007/978-3-540-79309-0_6
276,Recent interest in Nash equilibria led to a study of the ,rob stee,Not available,2008.0,10.1007/978-3-540-79309-0_6,Algorithmic Game Theory,Leah2008,False,,Springer,Not available,The Price of Anarchy on Uniformly Related Machines Revisited,7a85847f1cba6bb30abffb576d051fa4,http://dx.doi.org/10.1007/978-3-540-79309-0_6
277,We investigate the effect of linear independence in the strategies of congestion games on the convergence time of best response dynamics and on the pure Price of Anarchy. In particular  we consider symmetric congestion games on extension-parallel networks  an interesting class of networks with linearly independent paths  and establish two remarkable properties previously known only for parallel-link games. More precisely  we show that for arbitrary non-negative and non-decreasing latency functions  any best improvement sequence converges to a pure Nash equilibrium in at most ,dimitris fotakis,Not available,2008.0,10.1007/978-3-540-79309-0_5,Algorithmic Game Theory,Dimitris2008,False,,Springer,Not available,Congestion Games with Linearly Independent Paths: Convergence Time and Price of Anarchy,fb67d20ca8dade7e15aad3312acdefa9,http://dx.doi.org/10.1007/978-3-540-79309-0_5
278,This paper initiates a study of connections between local and global properties of graphical games. Specifically  we introduce a concept of local price of anarchy that quantifies how well subsets of agents respond to their environments. We then show several methods of bounding the global price of anarchy of a game in terms of the local price of anarchy. All our bounds are essentially tight.,oren ben-zwi,Not available,2008.0,10.1007/978-3-540-79309-0_23,Algorithmic Game Theory,Oren2008,False,,Springer,Not available,The Local and Global Price of Anarchy of Graphical Games,3fe9a68dd37a9a3fdd5a2f4bffefb455,http://dx.doi.org/10.1007/978-3-540-79309-0_23
279,We consider the price of stability for Nash and correlated equilibria of linear congestion games. The price of stability is the optimistic price of anarchy  the ratio of the cost of the best Nash or correlated equilibrium over the social optimum. We show that for the sum social cost  which corresponds to the average cost of the players  every linear congestion game has Nash and correlated price of stability at most 1.6. We also give an almost matching lower bound of ,george christodoulou,Not available,2005.0,10.1007/11561071_8,Algorithms – ESA 2005,George2005,False,,Springer,Not available,On the Price of Anarchy and Stability of Correlated Equilibria of Linear Congestion Games    ,c42f76437a6708ae2c3f3a830752cb0e,http://dx.doi.org/10.1007/11561071_8
280,This paper initiates a study of connections between local and global properties of graphical games. Specifically  we introduce a concept of local price of anarchy that quantifies how well subsets of agents respond to their environments. We then show several methods of bounding the global price of anarchy of a game in terms of the local price of anarchy. All our bounds are essentially tight.,amir ronen,Not available,2008.0,10.1007/978-3-540-79309-0_23,Algorithmic Game Theory,Oren2008,False,,Springer,Not available,The Local and Global Price of Anarchy of Graphical Games,3fe9a68dd37a9a3fdd5a2f4bffefb455,http://dx.doi.org/10.1007/978-3-540-79309-0_23
281,We analyze a graph process (or network creation game) where the vertices as players can establish mutual relations between each other at a fixed price. Each vertex receives income from every other vertex  exponentially decreasing with their distance. To establish an edge  both players have to make a consent acting selfishly. This process has originially been proposed in economics to analyse social networks of cooperation. Though the exponential payoff is a desirable principle to model the benefit of distributed systems  it has so far been an obstacle for analysis.We show that the process has a positive probability to cycle. We reduce the creation rule with payoff functions to graph theoretic criteria. Moreover  these criteria can be evaluated locally. This allows us to thoroughly reveal the structure of all stable states. In addition  the question for the price of anarchy can be reduced to counting the maximum number of edges of a stable graph. This together with a probabilistic argument allows to determine the price of anarchy exactly.,nadine baumann,Not available,2008.0,10.1007/978-3-540-79309-0_20,Algorithmic Game Theory,Nadine2008,False,,Springer,Not available,The Price of Anarchy of a Network Creation Game with Exponential Payoff,3fbc4dac20370302fcffaeed792b4b2e,http://dx.doi.org/10.1007/978-3-540-79309-0_20
282,We analyze a graph process (or network creation game) where the vertices as players can establish mutual relations between each other at a fixed price. Each vertex receives income from every other vertex  exponentially decreasing with their distance. To establish an edge  both players have to make a consent acting selfishly. This process has originially been proposed in economics to analyse social networks of cooperation. Though the exponential payoff is a desirable principle to model the benefit of distributed systems  it has so far been an obstacle for analysis.We show that the process has a positive probability to cycle. We reduce the creation rule with payoff functions to graph theoretic criteria. Moreover  these criteria can be evaluated locally. This allows us to thoroughly reveal the structure of all stable states. In addition  the question for the price of anarchy can be reduced to counting the maximum number of edges of a stable graph. This together with a probabilistic argument allows to determine the price of anarchy exactly.,sebastian stiller,Not available,2008.0,10.1007/978-3-540-79309-0_20,Algorithmic Game Theory,Nadine2008,False,,Springer,Not available,The Price of Anarchy of a Network Creation Game with Exponential Payoff,3fbc4dac20370302fcffaeed792b4b2e,http://dx.doi.org/10.1007/978-3-540-79309-0_20
283,,alexis kaporis,Not available,2008.0,10.1007/978-0-387-30162-4_398,Encyclopedia of Algorithms,Alexis2008,False,,Springer,Not available,Stackelberg Games: The Price of Optimum,05e5623331a0085f9138418ca22179ae,http://dx.doi.org/10.1007/978-0-387-30162-4_398
284,,paul spirakis,Not available,2008.0,10.1007/978-0-387-30162-4_398,Encyclopedia of Algorithms,Alexis2008,False,,Springer,Not available,Stackelberg Games: The Price of Optimum,05e5623331a0085f9138418ca22179ae,http://dx.doi.org/10.1007/978-0-387-30162-4_398
285,We study the ,aaron roth,Not available,2008.0,10.1007/978-3-540-92185-1_20,Internet and Network Economics,Aaron2008,False,,Springer,Not available,The Price of Malice in Linear Congestion Games,57c5eeb0ab11bfcd868f4ec9073b0759,http://dx.doi.org/10.1007/978-3-540-92185-1_20
286,Given a graph ,hiro ito,Not available,2008.0,10.1007/978-3-540-77891-2_16,WALCOM: Algorithms and Computation,Hiro2008,False,,Springer,Not available,Multi-commodity Source Location Problems and Price of Greed,4cb58ba91ae82fc0716c03eb5afd16e5,http://dx.doi.org/10.1007/978-3-540-77891-2_16
287,Given a graph ,mike paterson,Not available,2008.0,10.1007/978-3-540-77891-2_16,WALCOM: Algorithms and Computation,Hiro2008,False,,Springer,Not available,Multi-commodity Source Location Problems and Price of Greed,4cb58ba91ae82fc0716c03eb5afd16e5,http://dx.doi.org/10.1007/978-3-540-77891-2_16
288,Given a graph ,kenya sugihara,Not available,2008.0,10.1007/978-3-540-77891-2_16,WALCOM: Algorithms and Computation,Hiro2008,False,,Springer,Not available,Multi-commodity Source Location Problems and Price of Greed,4cb58ba91ae82fc0716c03eb5afd16e5,http://dx.doi.org/10.1007/978-3-540-77891-2_16
289,A central function of money is as a unit of account and this raises moral questions; most notably  what price a good should bear. It is not a question of what things should ,adrian walsh,Not available,2008.0,10.1057/9780230227804_5,The Morality of Money,Adrian2008,False,,Springer,Not available,The Morality of Pricing: Just Prices and Moral Traders,dfe225b6e14e5fddcfa3f5077912294f,http://dx.doi.org/10.1057/9780230227804_5
290,We consider the price of stability for Nash and correlated equilibria of linear congestion games. The price of stability is the optimistic price of anarchy  the ratio of the cost of the best Nash or correlated equilibrium over the social optimum. We show that for the sum social cost  which corresponds to the average cost of the players  every linear congestion game has Nash and correlated price of stability at most 1.6. We also give an almost matching lower bound of ,elias koutsoupias,Not available,2005.0,10.1007/11561071_8,Algorithms – ESA 2005,George2005,False,,Springer,Not available,On the Price of Anarchy and Stability of Correlated Equilibria of Linear Congestion Games    ,c42f76437a6708ae2c3f3a830752cb0e,http://dx.doi.org/10.1007/11561071_8
291,A central function of money is as a unit of account and this raises moral questions; most notably  what price a good should bear. It is not a question of what things should ,tony lynch,Not available,2008.0,10.1057/9780230227804_5,The Morality of Money,Adrian2008,False,,Springer,Not available,The Morality of Pricing: Just Prices and Moral Traders,dfe225b6e14e5fddcfa3f5077912294f,http://dx.doi.org/10.1057/9780230227804_5
292,,li-sha huang,Not available,2008.0,10.1007/978-0-387-30162-4_94,Encyclopedia of Algorithms,Li-Sha2008,False,,Springer,Not available,CPU Time Pricing,6726d7f1ff02ba3e924f48edf2160cfd,http://dx.doi.org/10.1007/978-0-387-30162-4_94
293,,george christodoulou,Not available,2016.0,10.1007/978-1-4939-2864-4_299,Encyclopedia of Algorithms,George2016,False,,Springer,Not available,Price of Anarchy,fcd6bed110f10ec45e94a927ec4ac7ba,http://dx.doi.org/10.1007/978-1-4939-2864-4_299
294,,artur czumaj,Not available,2016.0,10.1007/978-1-4939-2864-4_300,Encyclopedia of Algorithms,Artur2016,False,,Springer,Not available,Price of Anarchy for Machines Models,9f2ee54d3c95dcdcfdcda39883fd1efe,http://dx.doi.org/10.1007/978-1-4939-2864-4_300
295,,berthold vocking,Not available,2016.0,10.1007/978-1-4939-2864-4_300,Encyclopedia of Algorithms,Artur2016,False,,Springer,Not available,Price of Anarchy for Machines Models,9f2ee54d3c95dcdcfdcda39883fd1efe,http://dx.doi.org/10.1007/978-1-4939-2864-4_300
296,One of the main results shown through Roughgarden’s notions of smooth games and robust price of anarchy is that  for any sum-bounded utilitarian social function  the worst-case price of anarchy of coarse correlated equilibria coincides with that of pure Nash equilibria in the class of weighted congestion games with non-negative and non-decreasing latency functions and that such a value can always be derived through the  so called  smoothness argument. We significantly extend this result by proving that  for a variety of (even non-sum-bounded) utilitarian and egalitarian social functions and for a broad generalization of the class of weighted congestion games with non-negative (and possibly decreasing) latency functions  the worst-case price of anarchy of ,vittorio bilo,Not available,2016.0,10.1007/978-3-662-53354-3_8,Algorithmic Game Theory,Vittorio2016,False,,Springer,Not available,On the Robustness of the Approximate Price of Anarchy in Generalized Congestion Games,8900a7475043d2ff3552e370f42705d6,http://dx.doi.org/10.1007/978-3-662-53354-3_8
297,We describe and analyze a simple mechanism for the Combinatorial Public Project Problem (,evangelos markakis,Not available,2016.0,10.1007/978-3-319-41168-2_1,Algorithmic Aspects in Information and Management,Evangelos2016,False,,Springer,Not available,Item Pricing for Combinatorial Public Projects,0be31729cc8d8304697dea914285fa92,http://dx.doi.org/10.1007/978-3-319-41168-2_1
298,We describe and analyze a simple mechanism for the Combinatorial Public Project Problem (,orestis telelis,Not available,2016.0,10.1007/978-3-319-41168-2_1,Algorithmic Aspects in Information and Management,Evangelos2016,False,,Springer,Not available,Item Pricing for Combinatorial Public Projects,0be31729cc8d8304697dea914285fa92,http://dx.doi.org/10.1007/978-3-319-41168-2_1
299,In this model of network formation  players anticipate the destruction of one link  which is chosen according to a known probability distribution. Their cost is the cost for building links plus the expected number of other players to which connection will be lost as a result of the link destruction. We consider different equilibrium concepts (Nash equilibrium  pairwise Nash equilibrium  pairwise stability) and two different ways in which the probability distribution depends on the network.,lasse kliemann,Not available,2016.0,10.1007/978-3-319-28697-6_40,Operations Research Proceedings 2014,Lasse2016,False,,Springer,Not available,Price of Anarchy in the Link Destruction (Adversary) Model,f3e7be9ccca40b9fbd5102561eade60f,http://dx.doi.org/10.1007/978-3-319-28697-6_40
300,Given that risk is a pertinent issue in designing supply chain contracts with stochastic demand  Chap. 3 is devoted to developing a mean-risk analysis for the commonly adopted wholesale price contract. The research incorporates contract value risk into the wholesale price contract model. Regarding the contract value risk  it actually relates to the uncertainty in the true value of the contract and arises from various uncertainty sources inherent in the supply chain  such as demand uncertainty  price uncertainty  etc. In addition  given that the supply chain agents with different risk preferences will have different risk attitudes towards the contract value risk  which in turn affects their contracting decisions  the research also considers the degree of supply chain agents risk-aversion towards the contract value risk. This chapter makes the first attempt to assess the efficiency of wholesale price contracts  incorporating contract value risk and risk preferences attached to it; thereby some interesting managerial and academic insights are generated for supply chain contracts.,yingxue zhao,Not available,2016.0,10.1007/978-1-4899-7633-8_3,Contract Analysis and Design for Supply Chains with Stochastic Demand,Yingxue2016,False,,Springer,Not available,Mean-Risk Analysis of Wholesale Price Contracts with Stochastic Price-Dependent Demand,c7e20a252712a5263c83cc01e67f324d,http://dx.doi.org/10.1007/978-1-4899-7633-8_3
301,Most work in algorithmic game theory assumes that players ignore costs incurred by their fellow players. In this paper  we consider superimposing a social network over a game  where players are concerned with minimizing not only their own costs  but also the costs of their neighbors in the network. We aim to understand how properties of the underlying game are affected by this alteration to the standard model. The new social game has its own equilibria  and the ,russell buehler,Not available,2011.0,10.1007/978-3-642-25510-6_32,Internet and Network Economics,Russell2011,False,,Springer,Not available,The Price of Civil Society,9baab19fbad6f8cdd30475f481a22030,http://dx.doi.org/10.1007/978-3-642-25510-6_32
302,Given that risk is a pertinent issue in designing supply chain contracts with stochastic demand  Chap. 3 is devoted to developing a mean-risk analysis for the commonly adopted wholesale price contract. The research incorporates contract value risk into the wholesale price contract model. Regarding the contract value risk  it actually relates to the uncertainty in the true value of the contract and arises from various uncertainty sources inherent in the supply chain  such as demand uncertainty  price uncertainty  etc. In addition  given that the supply chain agents with different risk preferences will have different risk attitudes towards the contract value risk  which in turn affects their contracting decisions  the research also considers the degree of supply chain agents risk-aversion towards the contract value risk. This chapter makes the first attempt to assess the efficiency of wholesale price contracts  incorporating contract value risk and risk preferences attached to it; thereby some interesting managerial and academic insights are generated for supply chain contracts.,xiaoge meng,Not available,2016.0,10.1007/978-1-4899-7633-8_3,Contract Analysis and Design for Supply Chains with Stochastic Demand,Yingxue2016,False,,Springer,Not available,Mean-Risk Analysis of Wholesale Price Contracts with Stochastic Price-Dependent Demand,c7e20a252712a5263c83cc01e67f324d,http://dx.doi.org/10.1007/978-1-4899-7633-8_3
303,Given that risk is a pertinent issue in designing supply chain contracts with stochastic demand  Chap. 3 is devoted to developing a mean-risk analysis for the commonly adopted wholesale price contract. The research incorporates contract value risk into the wholesale price contract model. Regarding the contract value risk  it actually relates to the uncertainty in the true value of the contract and arises from various uncertainty sources inherent in the supply chain  such as demand uncertainty  price uncertainty  etc. In addition  given that the supply chain agents with different risk preferences will have different risk attitudes towards the contract value risk  which in turn affects their contracting decisions  the research also considers the degree of supply chain agents risk-aversion towards the contract value risk. This chapter makes the first attempt to assess the efficiency of wholesale price contracts  incorporating contract value risk and risk preferences attached to it; thereby some interesting managerial and academic insights are generated for supply chain contracts.,shouyang wang,Not available,2016.0,10.1007/978-1-4899-7633-8_3,Contract Analysis and Design for Supply Chains with Stochastic Demand,Yingxue2016,False,,Springer,Not available,Mean-Risk Analysis of Wholesale Price Contracts with Stochastic Price-Dependent Demand,c7e20a252712a5263c83cc01e67f324d,http://dx.doi.org/10.1007/978-1-4899-7633-8_3
304,Given that risk is a pertinent issue in designing supply chain contracts with stochastic demand  Chap. 3 is devoted to developing a mean-risk analysis for the commonly adopted wholesale price contract. The research incorporates contract value risk into the wholesale price contract model. Regarding the contract value risk  it actually relates to the uncertainty in the true value of the contract and arises from various uncertainty sources inherent in the supply chain  such as demand uncertainty  price uncertainty  etc. In addition  given that the supply chain agents with different risk preferences will have different risk attitudes towards the contract value risk  which in turn affects their contracting decisions  the research also considers the degree of supply chain agents risk-aversion towards the contract value risk. This chapter makes the first attempt to assess the efficiency of wholesale price contracts  incorporating contract value risk and risk preferences attached to it; thereby some interesting managerial and academic insights are generated for supply chain contracts.,t. cheng,Not available,2016.0,10.1007/978-1-4899-7633-8_3,Contract Analysis and Design for Supply Chains with Stochastic Demand,Yingxue2016,False,,Springer,Not available,Mean-Risk Analysis of Wholesale Price Contracts with Stochastic Price-Dependent Demand,c7e20a252712a5263c83cc01e67f324d,http://dx.doi.org/10.1007/978-1-4899-7633-8_3
305,The institution of citizenship is the prize of formal belonging for immigrant rights SMOs. “Civic-economic participation” justifies a path to citizenship for unauthorized immigrants. Because they work hard and contribute  these deserving de facto Americans ,bernadette jaworsky,Not available,2016.0,10.1007/978-3-319-43747-7_4,The Boundaries of Belonging,Nadya2016,False,,Springer,Not available,The Price of Citizenship,741baa7919ffa56ecb5c044d13c49fe7,http://dx.doi.org/10.1007/978-3-319-43747-7_4
306,,alexis kaporis,Not available,2016.0,10.1007/978-1-4939-2864-4_398,Encyclopedia of Algorithms,Alexis2016,False,,Springer,Not available,Stackelberg Games: The Price of Optimum,988f95516b32b1c9a9001f5ffd177cef,http://dx.doi.org/10.1007/978-1-4939-2864-4_398
307,,paul spirakis,Not available,2016.0,10.1007/978-1-4939-2864-4_398,Encyclopedia of Algorithms,Alexis2016,False,,Springer,Not available,Stackelberg Games: The Price of Optimum,988f95516b32b1c9a9001f5ffd177cef,http://dx.doi.org/10.1007/978-1-4939-2864-4_398
308,In multicast network design games  a set of agents choose paths from their source locations to a common sink with the goal of minimizing their individual costs  where the cost of an edge is divided equally among the agents using it. Since the work of Anshelevich et al. (FOCS 2004) that introduced network design games  the main open problem in this field has been the price of stability (PoS) of multicast games. For the special case of broadcast games (every vertex is a terminal  i.e.  has an agent)  a series of works has culminated in a constant upper bound on the PoS (Bilò et al.  FOCS 2013). However  no significantly sub-logarithmic bound is known for multicast games. In this paper  we make progress toward resolving this question by showing a constant upper bound on the PoS of multicast games for quasi-bipartite graphs. These are graphs where all edges are between two terminals (as in broadcast games) or between a terminal and a nonterminal  but there is no edge between nonterminals. This represents a natural class of intermediate generality between broadcast and multicast games. In addition to the result itself  our techniques overcome some of the fundamental difficulties of analyzing the PoS of general multicast games  and are a promising step toward resolving this major open problem.,rupert freeman,Not available,2016.0,10.1007/978-3-662-54110-4_25,Web and Internet Economics,Rupert2016,False,,Springer,Not available,On the Price of Stability of Undirected Multicast Games,4770485068ce16dc56c401c90d24c15c,http://dx.doi.org/10.1007/978-3-662-54110-4_25
309,In multicast network design games  a set of agents choose paths from their source locations to a common sink with the goal of minimizing their individual costs  where the cost of an edge is divided equally among the agents using it. Since the work of Anshelevich et al. (FOCS 2004) that introduced network design games  the main open problem in this field has been the price of stability (PoS) of multicast games. For the special case of broadcast games (every vertex is a terminal  i.e.  has an agent)  a series of works has culminated in a constant upper bound on the PoS (Bilò et al.  FOCS 2013). However  no significantly sub-logarithmic bound is known for multicast games. In this paper  we make progress toward resolving this question by showing a constant upper bound on the PoS of multicast games for quasi-bipartite graphs. These are graphs where all edges are between two terminals (as in broadcast games) or between a terminal and a nonterminal  but there is no edge between nonterminals. This represents a natural class of intermediate generality between broadcast and multicast games. In addition to the result itself  our techniques overcome some of the fundamental difficulties of analyzing the PoS of general multicast games  and are a promising step toward resolving this major open problem.,samuel haney,Not available,2016.0,10.1007/978-3-662-54110-4_25,Web and Internet Economics,Rupert2016,False,,Springer,Not available,On the Price of Stability of Undirected Multicast Games,4770485068ce16dc56c401c90d24c15c,http://dx.doi.org/10.1007/978-3-662-54110-4_25
310,In multicast network design games  a set of agents choose paths from their source locations to a common sink with the goal of minimizing their individual costs  where the cost of an edge is divided equally among the agents using it. Since the work of Anshelevich et al. (FOCS 2004) that introduced network design games  the main open problem in this field has been the price of stability (PoS) of multicast games. For the special case of broadcast games (every vertex is a terminal  i.e.  has an agent)  a series of works has culminated in a constant upper bound on the PoS (Bilò et al.  FOCS 2013). However  no significantly sub-logarithmic bound is known for multicast games. In this paper  we make progress toward resolving this question by showing a constant upper bound on the PoS of multicast games for quasi-bipartite graphs. These are graphs where all edges are between two terminals (as in broadcast games) or between a terminal and a nonterminal  but there is no edge between nonterminals. This represents a natural class of intermediate generality between broadcast and multicast games. In addition to the result itself  our techniques overcome some of the fundamental difficulties of analyzing the PoS of general multicast games  and are a promising step toward resolving this major open problem.,debmalya panigrahi,Not available,2016.0,10.1007/978-3-662-54110-4_25,Web and Internet Economics,Rupert2016,False,,Springer,Not available,On the Price of Stability of Undirected Multicast Games,4770485068ce16dc56c401c90d24c15c,http://dx.doi.org/10.1007/978-3-662-54110-4_25
311,We consider simple symmetric fractional hedonic games  in which a group of utility maximizing players have hedonic preferences over the players’ set  and wish to be partitioned into clusters so that they are grouped together with players they prefer. Each player either wishes to be in the same cluster with another player (and  hence  values this agent at 1) or is indifferent (and values this player at 0). Given a cluster  the utility of each player is defined as the number of players inside the cluster that are valued at 1 divided by the cluster size  and a player will deviate to another cluster if this leads to higher utility. We are interested in Nash equilibria of such games  where no player has an incentive to unilaterally deviate to another cluster  and we focus on the notion of the price of stability. We present new and improved bounds on the price of stability both for the normal utility function and for a slightly modified one.,christos kaklamanis,Not available,2016.0,10.1007/978-3-662-53354-3_18,Algorithmic Game Theory,Christos2016,False,,Springer,Not available,The Price of Stability of Simple Symmetric Fractional Hedonic Games,a9692ae471bbf78fd99263ebedbc15e3,http://dx.doi.org/10.1007/978-3-662-53354-3_18
312,Most work in algorithmic game theory assumes that players ignore costs incurred by their fellow players. In this paper  we consider superimposing a social network over a game  where players are concerned with minimizing not only their own costs  but also the costs of their neighbors in the network. We aim to understand how properties of the underlying game are affected by this alteration to the standard model. The new social game has its own equilibria  and the ,zachary goldman,Not available,2011.0,10.1007/978-3-642-25510-6_32,Internet and Network Economics,Russell2011,False,,Springer,Not available,The Price of Civil Society,9baab19fbad6f8cdd30475f481a22030,http://dx.doi.org/10.1007/978-3-642-25510-6_32
313,We consider simple symmetric fractional hedonic games  in which a group of utility maximizing players have hedonic preferences over the players’ set  and wish to be partitioned into clusters so that they are grouped together with players they prefer. Each player either wishes to be in the same cluster with another player (and  hence  values this agent at 1) or is indifferent (and values this player at 0). Given a cluster  the utility of each player is defined as the number of players inside the cluster that are valued at 1 divided by the cluster size  and a player will deviate to another cluster if this leads to higher utility. We are interested in Nash equilibria of such games  where no player has an incentive to unilaterally deviate to another cluster  and we focus on the notion of the price of stability. We present new and improved bounds on the price of stability both for the normal utility function and for a slightly modified one.,panagiotis kanellopoulos,Not available,2016.0,10.1007/978-3-662-53354-3_18,Algorithmic Game Theory,Christos2016,False,,Springer,Not available,The Price of Stability of Simple Symmetric Fractional Hedonic Games,a9692ae471bbf78fd99263ebedbc15e3,http://dx.doi.org/10.1007/978-3-662-53354-3_18
314,We consider simple symmetric fractional hedonic games  in which a group of utility maximizing players have hedonic preferences over the players’ set  and wish to be partitioned into clusters so that they are grouped together with players they prefer. Each player either wishes to be in the same cluster with another player (and  hence  values this agent at 1) or is indifferent (and values this player at 0). Given a cluster  the utility of each player is defined as the number of players inside the cluster that are valued at 1 divided by the cluster size  and a player will deviate to another cluster if this leads to higher utility. We are interested in Nash equilibria of such games  where no player has an incentive to unilaterally deviate to another cluster  and we focus on the notion of the price of stability. We present new and improved bounds on the price of stability both for the normal utility function and for a slightly modified one.,konstantinos papaioannou,Not available,2016.0,10.1007/978-3-662-53354-3_18,Algorithmic Game Theory,Christos2016,False,,Springer,Not available,The Price of Stability of Simple Symmetric Fractional Hedonic Games,a9692ae471bbf78fd99263ebedbc15e3,http://dx.doi.org/10.1007/978-3-662-53354-3_18
315,Let ,daniel li,Not available,2017.0,10.1007/s10878-016-0099-4,Journal of Combinatorial Optimization,Li2017,False,,Springer,Not available,Cost sharing on prices for games on graphs,58849e03f4c51bf0742c189218799cd5,http://dx.doi.org/10.1007/s10878-016-0099-4
316,Let ,erfang shan,Not available,2017.0,10.1007/s10878-016-0099-4,Journal of Combinatorial Optimization,Li2017,False,,Springer,Not available,Cost sharing on prices for games on graphs,58849e03f4c51bf0742c189218799cd5,http://dx.doi.org/10.1007/s10878-016-0099-4
317,We introduce natural strategic games on graphs  which capture the idea of coordination in a local setting. We study the existence of equilibria that are resilient to coalitional deviations of unbounded and bounded size (i.e.  ,krzysztof apt,Not available,2017.0,10.1007/s00182-016-0560-8,International Journal of Game Theory,R.2017,False,,Springer,Not available,Coordination games on graphs,43f007a9ab64669f6009dbc3dc4403c9,http://dx.doi.org/10.1007/s00182-016-0560-8
318,We introduce natural strategic games on graphs  which capture the idea of coordination in a local setting. We study the existence of equilibria that are resilient to coalitional deviations of unbounded and bounded size (i.e.  ,bart keijzer,Not available,2017.0,10.1007/s00182-016-0560-8,International Journal of Game Theory,R.2017,False,,Springer,Not available,Coordination games on graphs,43f007a9ab64669f6009dbc3dc4403c9,http://dx.doi.org/10.1007/s00182-016-0560-8
319,We introduce natural strategic games on graphs  which capture the idea of coordination in a local setting. We study the existence of equilibria that are resilient to coalitional deviations of unbounded and bounded size (i.e.  ,mona rahn,Not available,2017.0,10.1007/s00182-016-0560-8,International Journal of Game Theory,R.2017,False,,Springer,Not available,Coordination games on graphs,43f007a9ab64669f6009dbc3dc4403c9,http://dx.doi.org/10.1007/s00182-016-0560-8
320,We introduce natural strategic games on graphs  which capture the idea of coordination in a local setting. We study the existence of equilibria that are resilient to coalitional deviations of unbounded and bounded size (i.e.  ,guido schafer,Not available,2017.0,10.1007/s00182-016-0560-8,International Journal of Game Theory,R.2017,False,,Springer,Not available,Coordination games on graphs,43f007a9ab64669f6009dbc3dc4403c9,http://dx.doi.org/10.1007/s00182-016-0560-8
321,We introduce natural strategic games on graphs  which capture the idea of coordination in a local setting. We study the existence of equilibria that are resilient to coalitional deviations of unbounded and bounded size (i.e.  ,sunil simon,Not available,2017.0,10.1007/s00182-016-0560-8,International Journal of Game Theory,R.2017,False,,Springer,Not available,Coordination games on graphs,43f007a9ab64669f6009dbc3dc4403c9,http://dx.doi.org/10.1007/s00182-016-0560-8
322,We study the stable roommates problem in networks where players are embedded in a social context and may incorporate positive externalities into their decisions. Each player is a node in a social network and strives to form a good match with a neighboring player. We consider the existence  computation  and inefficiency of stable matchings from which no pair of players wants to deviate. We characterize prices of anarchy and stability  which capture the ratio of the total profit in the optimum matching over the total profit of the worst and best stable matching  respectively. When the benefit from a match (which we model by associating a reward with each edge) is the same for both players  we show that externalities can significantly improve the price of stability  while the price of anarchy remains unaffected. Furthermore  a good stable matching achieving the bound on the price of stability can be obtained in polynomial time. We extend these results to more general matching rewards  when players matched to each other may receive different benefits from the match. For this more general case  we show that network externalities (i.e.  “caring about your friends”) can make an even larger difference and greatly reduce the price of anarchy. We show a variety of existence results and present upper and lower bounds on the prices of anarchy and stability for various structures of matching benefits. All our results on stable matchings immediately extend to the more general case of fractional stable matchings.,elliot anshelevich,Not available,2017.0,10.1007/s00453-016-0197-9,Algorithmica,Elliot2017,False,,Springer,Not available,Stable Matching with Network Externalities,f5cc9f0a77f44250fb9a789c70d857f2,http://dx.doi.org/10.1007/s00453-016-0197-9
323,Most work in algorithmic game theory assumes that players ignore costs incurred by their fellow players. In this paper  we consider superimposing a social network over a game  where players are concerned with minimizing not only their own costs  but also the costs of their neighbors in the network. We aim to understand how properties of the underlying game are affected by this alteration to the standard model. The new social game has its own equilibria  and the ,david liben-nowell,Not available,2011.0,10.1007/978-3-642-25510-6_32,Internet and Network Economics,Russell2011,False,,Springer,Not available,The Price of Civil Society,9baab19fbad6f8cdd30475f481a22030,http://dx.doi.org/10.1007/978-3-642-25510-6_32
324,We study the stable roommates problem in networks where players are embedded in a social context and may incorporate positive externalities into their decisions. Each player is a node in a social network and strives to form a good match with a neighboring player. We consider the existence  computation  and inefficiency of stable matchings from which no pair of players wants to deviate. We characterize prices of anarchy and stability  which capture the ratio of the total profit in the optimum matching over the total profit of the worst and best stable matching  respectively. When the benefit from a match (which we model by associating a reward with each edge) is the same for both players  we show that externalities can significantly improve the price of stability  while the price of anarchy remains unaffected. Furthermore  a good stable matching achieving the bound on the price of stability can be obtained in polynomial time. We extend these results to more general matching rewards  when players matched to each other may receive different benefits from the match. For this more general case  we show that network externalities (i.e.  “caring about your friends”) can make an even larger difference and greatly reduce the price of anarchy. We show a variety of existence results and present upper and lower bounds on the prices of anarchy and stability for various structures of matching benefits. All our results on stable matchings immediately extend to the more general case of fractional stable matchings.,onkar bhardwaj,Not available,2017.0,10.1007/s00453-016-0197-9,Algorithmica,Elliot2017,False,,Springer,Not available,Stable Matching with Network Externalities,f5cc9f0a77f44250fb9a789c70d857f2,http://dx.doi.org/10.1007/s00453-016-0197-9
325,We study the stable roommates problem in networks where players are embedded in a social context and may incorporate positive externalities into their decisions. Each player is a node in a social network and strives to form a good match with a neighboring player. We consider the existence  computation  and inefficiency of stable matchings from which no pair of players wants to deviate. We characterize prices of anarchy and stability  which capture the ratio of the total profit in the optimum matching over the total profit of the worst and best stable matching  respectively. When the benefit from a match (which we model by associating a reward with each edge) is the same for both players  we show that externalities can significantly improve the price of stability  while the price of anarchy remains unaffected. Furthermore  a good stable matching achieving the bound on the price of stability can be obtained in polynomial time. We extend these results to more general matching rewards  when players matched to each other may receive different benefits from the match. For this more general case  we show that network externalities (i.e.  “caring about your friends”) can make an even larger difference and greatly reduce the price of anarchy. We show a variety of existence results and present upper and lower bounds on the prices of anarchy and stability for various structures of matching benefits. All our results on stable matchings immediately extend to the more general case of fractional stable matchings.,martin hoefer,Not available,2017.0,10.1007/s00453-016-0197-9,Algorithmica,Elliot2017,False,,Springer,Not available,Stable Matching with Network Externalities,f5cc9f0a77f44250fb9a789c70d857f2,http://dx.doi.org/10.1007/s00453-016-0197-9
326,This paper deals with a matching game in which the nodes of a simple graph are independent agents who try to form pairs. If we let the agents make their decision without any central control then a possible outcome is a Nash equilibrium  that is a situation in which no unmatched player can change his strategy and find a partner. However  there can be a big difference between two possible outcomes of the same instance  in terms of number of matched nodes. A possible solution is to force all the nodes to follow a centrally computed maximum matching but it can be difficult to implement this approach. This article proposes a tradeoff between the total absence and the full presence of a central control. Concretely  we study the optimization problem where the action of a ,bruno escoffier,Not available,2017.0,10.1007/s00453-015-0108-5,Algorithmica,Bruno2017,False,,Springer,Not available,The Price of Optimum: Complexity and Approximation for a Matching Game,ec3502323307798f30e098f0564fccb6,http://dx.doi.org/10.1007/s00453-015-0108-5
327,This paper deals with a matching game in which the nodes of a simple graph are independent agents who try to form pairs. If we let the agents make their decision without any central control then a possible outcome is a Nash equilibrium  that is a situation in which no unmatched player can change his strategy and find a partner. However  there can be a big difference between two possible outcomes of the same instance  in terms of number of matched nodes. A possible solution is to force all the nodes to follow a centrally computed maximum matching but it can be difficult to implement this approach. This article proposes a tradeoff between the total absence and the full presence of a central control. Concretely  we study the optimization problem where the action of a ,laurent gourves,Not available,2017.0,10.1007/s00453-015-0108-5,Algorithmica,Bruno2017,False,,Springer,Not available,The Price of Optimum: Complexity and Approximation for a Matching Game,ec3502323307798f30e098f0564fccb6,http://dx.doi.org/10.1007/s00453-015-0108-5
328,This paper deals with a matching game in which the nodes of a simple graph are independent agents who try to form pairs. If we let the agents make their decision without any central control then a possible outcome is a Nash equilibrium  that is a situation in which no unmatched player can change his strategy and find a partner. However  there can be a big difference between two possible outcomes of the same instance  in terms of number of matched nodes. A possible solution is to force all the nodes to follow a centrally computed maximum matching but it can be difficult to implement this approach. This article proposes a tradeoff between the total absence and the full presence of a central control. Concretely  we study the optimization problem where the action of a ,jerome monnot,Not available,2017.0,10.1007/s00453-015-0108-5,Algorithmica,Bruno2017,False,,Springer,Not available,The Price of Optimum: Complexity and Approximation for a Matching Game,ec3502323307798f30e098f0564fccb6,http://dx.doi.org/10.1007/s00453-015-0108-5
329,We study the bilateral version of the adversary network formation game introduced by the author in 2010. In bilateral network formation  a link is formed only if both endpoints agree on it and then both have to pay the link cost ,lasse kliemann,Not available,2017.0,10.1007/s00453-016-0120-4,Algorithmica,Lasse2017,False,,Springer,Not available,The Price of Anarchy in Bilateral Network Formation in an Adversary Model,bcb1da0435cbf1b3c2d3327909bc5a18,http://dx.doi.org/10.1007/s00453-016-0120-4
330,In this paper we consider the scheduling problem with parallel-batching machines from a game theoretic perspective. There are ,q. nong,Not available,2017.0,10.1007/s10878-015-9980-9,Journal of Combinatorial Optimization,Q.2017,False,,Springer,Not available,A coordination mechanism for a scheduling game with parallel-batching machines,08257e0f683236ab4ee7b9dd2e4f40d3,http://dx.doi.org/10.1007/s10878-015-9980-9
331,In this paper we consider the scheduling problem with parallel-batching machines from a game theoretic perspective. There are ,g. fan,Not available,2017.0,10.1007/s10878-015-9980-9,Journal of Combinatorial Optimization,Q.2017,False,,Springer,Not available,A coordination mechanism for a scheduling game with parallel-batching machines,08257e0f683236ab4ee7b9dd2e4f40d3,http://dx.doi.org/10.1007/s10878-015-9980-9
332,In this paper we consider the scheduling problem with parallel-batching machines from a game theoretic perspective. There are ,q. fang,Not available,2017.0,10.1007/s10878-015-9980-9,Journal of Combinatorial Optimization,Q.2017,False,,Springer,Not available,A coordination mechanism for a scheduling game with parallel-batching machines,08257e0f683236ab4ee7b9dd2e4f40d3,http://dx.doi.org/10.1007/s10878-015-9980-9
333,The techniques that some large multinational corporations use to reduce their tax liability have come under increasing public scrutiny in recent years  alongside governmental investigations and international commitments aimed at curbing opportunities for tax avoidance. Although discussion of tax avoidance activities  and their regulatory responses  is often conducted with reference to moral concepts (such as ‘fairness’)  philosophical analysis of the ethics of multinational tax avoidance remains limited. In particular  the virtue ethics tradition that emphasises the agent (and his/her character) and the performance of specific roles has not been considered in detail. This paper examines how the contemporary virtue ethics of Alasdair MacIntyre can be applied to the issue of multinational tax avoidance  and considers the role that accountants play in these activities. It argues  firstly  that MacIntyre’s approach provides a more useful philosophical analysis of the issue (when compared to utilitarian and deontological approaches for example) and  secondly  that the main parties involved (MNC accountants and regulators) are likely to agree with the main tenets of this approach. The paper also contributes by reconceptualising  using MacIntyre’s scheme  the issue of tax avoidance in relation to Donald Cressey’s ‘fraud triangle’.,andrew west,Not available,2017.0,10.1007/s10551-016-3428-8,Journal of Business Ethics,Andrew2017,False,,Springer,Not available,Multinational Tax Avoidance: Virtue Ethics and the Role of Accountants,7d51d40f40d8ce4d2b6df2da5022d47f,http://dx.doi.org/10.1007/s10551-016-3428-8
334,As defined by Aumann in 1959  a strong equilibrium is a Nash equilibrium that is resilient to deviations by coalitions. We give tight bounds on the strong price of anarchy for load balancing on related machines. We also give tight bounds for ,haim kaplan,Not available,2007.0,10.1007/978-3-540-73420-8_51,Automata  Languages and Programming,Amos2007,False,,Springer,Not available,Strong Price of Anarchy for Machine Load Balancing,e62a88eac6ef598fa8bf2eb73a687dae,http://dx.doi.org/10.1007/978-3-540-73420-8_51
335,Most work in algorithmic game theory assumes that players ignore costs incurred by their fellow players. In this paper  we consider superimposing a social network over a game  where players are concerned with minimizing not only their own costs  but also the costs of their neighbors in the network. We aim to understand how properties of the underlying game are affected by this alteration to the standard model. The new social game has its own equilibria  and the ,yuechao pei,Not available,2011.0,10.1007/978-3-642-25510-6_32,Internet and Network Economics,Russell2011,False,,Springer,Not available,The Price of Civil Society,9baab19fbad6f8cdd30475f481a22030,http://dx.doi.org/10.1007/978-3-642-25510-6_32
336,We consider a scheduling game  in which both the machines and the jobs are players. A job attempts to minimize its completion time by switching machines  while each machine would like to maximize its workload by choosing a scheduling policy from the given set of policies. We consider a two-stage game. In the first stage every machine simultaneously chooses a policy from some given set of policies  and in the second stage  every job simultaneously chooses a machine. In this work  we use the price of anarchy to measure the efficiency of such equilibria where each machine is allowed to use at most two policies. We provide nearly tight bounds for every combination of two deterministic scheduling policies with respect to two social objectives: minimizing the maximum job completion  and maximizing the minimum machine completion time.,deshi ye,Not available,2017.0,10.1007/978-3-319-71147-8_15,Combinatorial Optimization and Applications,Deshi2017,False,,Springer,Not available,The Price of Anarchy in Two-Stage Scheduling Games,4c7ac61186fb18db069c663a0902133a,http://dx.doi.org/10.1007/978-3-319-71147-8_15
337,We consider a scheduling game  in which both the machines and the jobs are players. A job attempts to minimize its completion time by switching machines  while each machine would like to maximize its workload by choosing a scheduling policy from the given set of policies. We consider a two-stage game. In the first stage every machine simultaneously chooses a policy from some given set of policies  and in the second stage  every job simultaneously chooses a machine. In this work  we use the price of anarchy to measure the efficiency of such equilibria where each machine is allowed to use at most two policies. We provide nearly tight bounds for every combination of two deterministic scheduling policies with respect to two social objectives: minimizing the maximum job completion  and maximizing the minimum machine completion time.,lin chen,Not available,2017.0,10.1007/978-3-319-71147-8_15,Combinatorial Optimization and Applications,Deshi2017,False,,Springer,Not available,The Price of Anarchy in Two-Stage Scheduling Games,4c7ac61186fb18db069c663a0902133a,http://dx.doi.org/10.1007/978-3-319-71147-8_15
338,We consider a scheduling game  in which both the machines and the jobs are players. A job attempts to minimize its completion time by switching machines  while each machine would like to maximize its workload by choosing a scheduling policy from the given set of policies. We consider a two-stage game. In the first stage every machine simultaneously chooses a policy from some given set of policies  and in the second stage  every job simultaneously chooses a machine. In this work  we use the price of anarchy to measure the efficiency of such equilibria where each machine is allowed to use at most two policies. We provide nearly tight bounds for every combination of two deterministic scheduling policies with respect to two social objectives: minimizing the maximum job completion  and maximizing the minimum machine completion time.,guochuan zhang,Not available,2017.0,10.1007/978-3-319-71147-8_15,Combinatorial Optimization and Applications,Deshi2017,False,,Springer,Not available,The Price of Anarchy in Two-Stage Scheduling Games,4c7ac61186fb18db069c663a0902133a,http://dx.doi.org/10.1007/978-3-319-71147-8_15
339,This chapter provides a general overview of the topic of network games  its application in a number of areas  and recent advances  by focusing on four major types of games  namely  congestion games  resource allocation games  diffusion games  and network formation games. Several algorithmic aspects and methodologies for analyzing such games are discussed  and connections between network games and other relevant topical areas are identified.,s. etesami,Not available,2017.0,10.1007/978-3-319-27335-8_10-1,Handbook of Dynamic Game Theory,Rasoul2017,False,,Springer,Not available,Network Games,fbe586b158110c9db2acfc7c50450235,http://dx.doi.org/10.1007/978-3-319-27335-8_10-1
340,This chapter provides a general overview of the topic of network games  its application in a number of areas  and recent advances  by focusing on four major types of games  namely  congestion games  resource allocation games  diffusion games  and network formation games. Several algorithmic aspects and methodologies for analyzing such games are discussed  and connections between network games and other relevant topical areas are identified.,tamer basar,Not available,2017.0,10.1007/978-3-319-27335-8_10-1,Handbook of Dynamic Game Theory,Rasoul2017,False,,Springer,Not available,Network Games,fbe586b158110c9db2acfc7c50450235,http://dx.doi.org/10.1007/978-3-319-27335-8_10-1
341,In this paper  we consider a routing game in a network that contains lossy links. We consider a multi-objective problem where the players have each a weighted sum of a delay cost and a cost for losses. We compute the equilibrium and optimal solution (which are unique). We discover here in addition to the classical Kameda type paradox another paradoxical behavior in which higher loss rates have a positive impact on delay and therefore higher quality links may cause a worse performance even in the case of a single player.,amina boukoftane,Not available,2017.0,10.1007/978-3-319-67540-4_15,Game Theory for Networks,Amina2017,False,,Springer,Not available,Paradoxes in a Multi-criteria Routing Game,9088663b5e78b6689d3626851fc91220,http://dx.doi.org/10.1007/978-3-319-67540-4_15
342,In this paper  we consider a routing game in a network that contains lossy links. We consider a multi-objective problem where the players have each a weighted sum of a delay cost and a cost for losses. We compute the equilibrium and optimal solution (which are unique). We discover here in addition to the classical Kameda type paradox another paradoxical behavior in which higher loss rates have a positive impact on delay and therefore higher quality links may cause a worse performance even in the case of a single player.,eitan altman,Not available,2017.0,10.1007/978-3-319-67540-4_15,Game Theory for Networks,Amina2017,False,,Springer,Not available,Paradoxes in a Multi-criteria Routing Game,9088663b5e78b6689d3626851fc91220,http://dx.doi.org/10.1007/978-3-319-67540-4_15
343,In this paper  we consider a routing game in a network that contains lossy links. We consider a multi-objective problem where the players have each a weighted sum of a delay cost and a cost for losses. We compute the equilibrium and optimal solution (which are unique). We discover here in addition to the classical Kameda type paradox another paradoxical behavior in which higher loss rates have a positive impact on delay and therefore higher quality links may cause a worse performance even in the case of a single player.,majed haddad,Not available,2017.0,10.1007/978-3-319-67540-4_15,Game Theory for Networks,Amina2017,False,,Springer,Not available,Paradoxes in a Multi-criteria Routing Game,9088663b5e78b6689d3626851fc91220,http://dx.doi.org/10.1007/978-3-319-67540-4_15
344,In this paper  we consider a routing game in a network that contains lossy links. We consider a multi-objective problem where the players have each a weighted sum of a delay cost and a cost for losses. We compute the equilibrium and optimal solution (which are unique). We discover here in addition to the classical Kameda type paradox another paradoxical behavior in which higher loss rates have a positive impact on delay and therefore higher quality links may cause a worse performance even in the case of a single player.,nadia oukid,Not available,2017.0,10.1007/978-3-319-67540-4_15,Game Theory for Networks,Amina2017,False,,Springer,Not available,Paradoxes in a Multi-criteria Routing Game,9088663b5e78b6689d3626851fc91220,http://dx.doi.org/10.1007/978-3-319-67540-4_15
345,We consider the well-studied game-theoretic version of machine scheduling in which jobs correspond to ,cong chen,Not available,2017.0,10.1007/978-3-319-71147-8_16,Combinatorial Optimization and Applications,Cong2017,False,,Springer,Not available,Selfish Jobs with Favorite Machines: Price of Anarchy vs. Strong Price of Anarchy,400a7546be6883c396c5e95a941f98ac,http://dx.doi.org/10.1007/978-3-319-71147-8_16
346,Most work in algorithmic game theory assumes that players ignore costs incurred by their fellow players. In this paper  we consider superimposing a social network over a game  where players are concerned with minimizing not only their own costs  but also the costs of their neighbors in the network. We aim to understand how properties of the underlying game are affected by this alteration to the standard model. The new social game has its own equilibria  and the ,jamie quadri,Not available,2011.0,10.1007/978-3-642-25510-6_32,Internet and Network Economics,Russell2011,False,,Springer,Not available,The Price of Civil Society,9baab19fbad6f8cdd30475f481a22030,http://dx.doi.org/10.1007/978-3-642-25510-6_32
347,We consider the well-studied game-theoretic version of machine scheduling in which jobs correspond to ,paolo penna,Not available,2017.0,10.1007/978-3-319-71147-8_16,Combinatorial Optimization and Applications,Cong2017,False,,Springer,Not available,Selfish Jobs with Favorite Machines: Price of Anarchy vs. Strong Price of Anarchy,400a7546be6883c396c5e95a941f98ac,http://dx.doi.org/10.1007/978-3-319-71147-8_16
348,We consider the well-studied game-theoretic version of machine scheduling in which jobs correspond to ,yinfeng xu,Not available,2017.0,10.1007/978-3-319-71147-8_16,Combinatorial Optimization and Applications,Cong2017,False,,Springer,Not available,Selfish Jobs with Favorite Machines: Price of Anarchy vs. Strong Price of Anarchy,400a7546be6883c396c5e95a941f98ac,http://dx.doi.org/10.1007/978-3-319-71147-8_16
349,This paper examines the behavior of the price of anarchy as a function of the traffic inflow in nonatomic congestion games with multiple origin-destination (O/D) pairs. Empirical studies in real-world networks show that the price of anarchy is close to 1 in both light and heavy traffic  thus raising the question: can these observations be justified theoretically? We first show that this is not always the case: the price of anarchy may remain bounded away from 1 for all values of the traffic inflow  even in simple three-link networks with a single O/D pair and smooth  convex costs. On the other hand  for a large class of cost functions (including all polynomials)  the price of anarchy ,riccardo colini-baldeschi,Not available,2017.0,10.1007/978-3-319-71924-5_10,Web and Internet Economics,Riccardo2017,False,,Springer,Not available,The Asymptotic Behavior of the Price of Anarchy,34663bc31d32422a33beca456d291087,http://dx.doi.org/10.1007/978-3-319-71924-5_10
350,This paper examines the behavior of the price of anarchy as a function of the traffic inflow in nonatomic congestion games with multiple origin-destination (O/D) pairs. Empirical studies in real-world networks show that the price of anarchy is close to 1 in both light and heavy traffic  thus raising the question: can these observations be justified theoretically? We first show that this is not always the case: the price of anarchy may remain bounded away from 1 for all values of the traffic inflow  even in simple three-link networks with a single O/D pair and smooth  convex costs. On the other hand  for a large class of cost functions (including all polynomials)  the price of anarchy ,roberto cominetti,Not available,2017.0,10.1007/978-3-319-71924-5_10,Web and Internet Economics,Riccardo2017,False,,Springer,Not available,The Asymptotic Behavior of the Price of Anarchy,34663bc31d32422a33beca456d291087,http://dx.doi.org/10.1007/978-3-319-71924-5_10
351,This paper examines the behavior of the price of anarchy as a function of the traffic inflow in nonatomic congestion games with multiple origin-destination (O/D) pairs. Empirical studies in real-world networks show that the price of anarchy is close to 1 in both light and heavy traffic  thus raising the question: can these observations be justified theoretically? We first show that this is not always the case: the price of anarchy may remain bounded away from 1 for all values of the traffic inflow  even in simple three-link networks with a single O/D pair and smooth  convex costs. On the other hand  for a large class of cost functions (including all polynomials)  the price of anarchy ,panayotis mertikopoulos,Not available,2017.0,10.1007/978-3-319-71924-5_10,Web and Internet Economics,Riccardo2017,False,,Springer,Not available,The Asymptotic Behavior of the Price of Anarchy,34663bc31d32422a33beca456d291087,http://dx.doi.org/10.1007/978-3-319-71924-5_10
352,This paper examines the behavior of the price of anarchy as a function of the traffic inflow in nonatomic congestion games with multiple origin-destination (O/D) pairs. Empirical studies in real-world networks show that the price of anarchy is close to 1 in both light and heavy traffic  thus raising the question: can these observations be justified theoretically? We first show that this is not always the case: the price of anarchy may remain bounded away from 1 for all values of the traffic inflow  even in simple three-link networks with a single O/D pair and smooth  convex costs. On the other hand  for a large class of cost functions (including all polynomials)  the price of anarchy ,marco scarsini,Not available,2017.0,10.1007/978-3-319-71924-5_10,Web and Internet Economics,Riccardo2017,False,,Springer,Not available,The Asymptotic Behavior of the Price of Anarchy,34663bc31d32422a33beca456d291087,http://dx.doi.org/10.1007/978-3-319-71924-5_10
353,We consider a scheduling game  in which both the machines and the jobs are players. A job attempts to minimize its completion time by switching machines  while each machine would like to maximize its workload by choosing a scheduling policy from the given set of policies. We consider a two-stage game. In the first stage every machine simultaneously chooses a policy from some given set of policies  and in the second stage  every job simultaneously chooses a machine. In this work  we use the price of anarchy to measure the efficiency of such equilibria where each machine is allowed to use at most two policies. We provide nearly tight bounds for every combination of two deterministic scheduling policies with respect to two social objectives: minimizing the maximum job completion  and maximizing the minimum machine completion time.,deshi ye,Not available,2017.0,10.1007/978-3-319-71147-8_15,Combinatorial Optimization and Applications,Deshi2017,False,,Springer,Not available,The Price of Anarchy in Two-Stage Scheduling Games,4c7ac61186fb18db069c663a0902133a,http://dx.doi.org/10.1007/978-3-319-71147-8_15
354,We consider a scheduling game  in which both the machines and the jobs are players. A job attempts to minimize its completion time by switching machines  while each machine would like to maximize its workload by choosing a scheduling policy from the given set of policies. We consider a two-stage game. In the first stage every machine simultaneously chooses a policy from some given set of policies  and in the second stage  every job simultaneously chooses a machine. In this work  we use the price of anarchy to measure the efficiency of such equilibria where each machine is allowed to use at most two policies. We provide nearly tight bounds for every combination of two deterministic scheduling policies with respect to two social objectives: minimizing the maximum job completion  and maximizing the minimum machine completion time.,lin chen,Not available,2017.0,10.1007/978-3-319-71147-8_15,Combinatorial Optimization and Applications,Deshi2017,False,,Springer,Not available,The Price of Anarchy in Two-Stage Scheduling Games,4c7ac61186fb18db069c663a0902133a,http://dx.doi.org/10.1007/978-3-319-71147-8_15
355,We consider a scheduling game  in which both the machines and the jobs are players. A job attempts to minimize its completion time by switching machines  while each machine would like to maximize its workload by choosing a scheduling policy from the given set of policies. We consider a two-stage game. In the first stage every machine simultaneously chooses a policy from some given set of policies  and in the second stage  every job simultaneously chooses a machine. In this work  we use the price of anarchy to measure the efficiency of such equilibria where each machine is allowed to use at most two policies. We provide nearly tight bounds for every combination of two deterministic scheduling policies with respect to two social objectives: minimizing the maximum job completion  and maximizing the minimum machine completion time.,guochuan zhang,Not available,2017.0,10.1007/978-3-319-71147-8_15,Combinatorial Optimization and Applications,Deshi2017,False,,Springer,Not available,The Price of Anarchy in Two-Stage Scheduling Games,4c7ac61186fb18db069c663a0902133a,http://dx.doi.org/10.1007/978-3-319-71147-8_15
356,Incorporating budget constraints into the analysis of auctions has become increasingly important  as they model practical settings more accurately. The social welfare function  which is the standard measure of efficiency in auctions  is inadequate for settings with budgets  since there may be a large disconnect between the value a bidder derives from obtaining an item and what can be liquidated from her. The ,yossi azar,Not available,2017.0,10.1007/978-3-319-66700-3_1,Algorithmic Game Theory,Yossi2017,False,,Springer,Not available,Liquid Price of Anarchy,f933153babb546a2284d6e57fb9afe43,http://dx.doi.org/10.1007/978-3-319-66700-3_1
357,Most work in algorithmic game theory assumes that players ignore costs incurred by their fellow players. In this paper  we consider superimposing a social network over a game  where players are concerned with minimizing not only their own costs  but also the costs of their neighbors in the network. We aim to understand how properties of the underlying game are affected by this alteration to the standard model. The new social game has its own equilibria  and the ,alexa sharp,Not available,2011.0,10.1007/978-3-642-25510-6_32,Internet and Network Economics,Russell2011,False,,Springer,Not available,The Price of Civil Society,9baab19fbad6f8cdd30475f481a22030,http://dx.doi.org/10.1007/978-3-642-25510-6_32
358,Incorporating budget constraints into the analysis of auctions has become increasingly important  as they model practical settings more accurately. The social welfare function  which is the standard measure of efficiency in auctions  is inadequate for settings with budgets  since there may be a large disconnect between the value a bidder derives from obtaining an item and what can be liquidated from her. The ,michal feldman,Not available,2017.0,10.1007/978-3-319-66700-3_1,Algorithmic Game Theory,Yossi2017,False,,Springer,Not available,Liquid Price of Anarchy,f933153babb546a2284d6e57fb9afe43,http://dx.doi.org/10.1007/978-3-319-66700-3_1
359,Incorporating budget constraints into the analysis of auctions has become increasingly important  as they model practical settings more accurately. The social welfare function  which is the standard measure of efficiency in auctions  is inadequate for settings with budgets  since there may be a large disconnect between the value a bidder derives from obtaining an item and what can be liquidated from her. The ,nick gravin,Not available,2017.0,10.1007/978-3-319-66700-3_1,Algorithmic Game Theory,Yossi2017,False,,Springer,Not available,Liquid Price of Anarchy,f933153babb546a2284d6e57fb9afe43,http://dx.doi.org/10.1007/978-3-319-66700-3_1
360,Incorporating budget constraints into the analysis of auctions has become increasingly important  as they model practical settings more accurately. The social welfare function  which is the standard measure of efficiency in auctions  is inadequate for settings with budgets  since there may be a large disconnect between the value a bidder derives from obtaining an item and what can be liquidated from her. The ,alan roytman,Not available,2017.0,10.1007/978-3-319-66700-3_1,Algorithmic Game Theory,Yossi2017,False,,Springer,Not available,Liquid Price of Anarchy,f933153babb546a2284d6e57fb9afe43,http://dx.doi.org/10.1007/978-3-319-66700-3_1
361,We revisit the inefficiency of the uniform price auction  one of the standard multi-unit auction formats  for allocating multiple units of a single good. In the uniform price auction  each bidder submits a sequence of non-increasing marginal bids  one for each additional unit. The per unit price is then set to be the highest losing bid. We focus on the pure Nash equilibria of such auctions  for bidders with submodular valuation functions. Our result is a tight upper and lower bound on the inefficiency of equilibria  showing that the Price of Anarchy is bounded by 2.188. This resolves one of the open questions posed in previous works on multi-unit auctions.,georgios birmpas,Not available,2017.0,10.1007/978-3-319-66700-3_2,Algorithmic Game Theory,Georgios2017,False,,Springer,Not available,Tight Welfare Guarantees for Pure Nash Equilibria of the Uniform Price Auction,465373c9ad74b0f572f6c8930af08b4a,http://dx.doi.org/10.1007/978-3-319-66700-3_2
362,We revisit the inefficiency of the uniform price auction  one of the standard multi-unit auction formats  for allocating multiple units of a single good. In the uniform price auction  each bidder submits a sequence of non-increasing marginal bids  one for each additional unit. The per unit price is then set to be the highest losing bid. We focus on the pure Nash equilibria of such auctions  for bidders with submodular valuation functions. Our result is a tight upper and lower bound on the inefficiency of equilibria  showing that the Price of Anarchy is bounded by 2.188. This resolves one of the open questions posed in previous works on multi-unit auctions.,evangelos markakis,Not available,2017.0,10.1007/978-3-319-66700-3_2,Algorithmic Game Theory,Georgios2017,False,,Springer,Not available,Tight Welfare Guarantees for Pure Nash Equilibria of the Uniform Price Auction,465373c9ad74b0f572f6c8930af08b4a,http://dx.doi.org/10.1007/978-3-319-66700-3_2
363,We revisit the inefficiency of the uniform price auction  one of the standard multi-unit auction formats  for allocating multiple units of a single good. In the uniform price auction  each bidder submits a sequence of non-increasing marginal bids  one for each additional unit. The per unit price is then set to be the highest losing bid. We focus on the pure Nash equilibria of such auctions  for bidders with submodular valuation functions. Our result is a tight upper and lower bound on the inefficiency of equilibria  showing that the Price of Anarchy is bounded by 2.188. This resolves one of the open questions posed in previous works on multi-unit auctions.,orestis telelis,Not available,2017.0,10.1007/978-3-319-66700-3_2,Algorithmic Game Theory,Georgios2017,False,,Springer,Not available,Tight Welfare Guarantees for Pure Nash Equilibria of the Uniform Price Auction,465373c9ad74b0f572f6c8930af08b4a,http://dx.doi.org/10.1007/978-3-319-66700-3_2
364,We revisit the inefficiency of the uniform price auction  one of the standard multi-unit auction formats  for allocating multiple units of a single good. In the uniform price auction  each bidder submits a sequence of non-increasing marginal bids  one for each additional unit. The per unit price is then set to be the highest losing bid. We focus on the pure Nash equilibria of such auctions  for bidders with submodular valuation functions. Our result is a tight upper and lower bound on the inefficiency of equilibria  showing that the Price of Anarchy is bounded by 2.188. This resolves one of the open questions posed in previous works on multi-unit auctions.,artem tsikiridis,Not available,2017.0,10.1007/978-3-319-66700-3_2,Algorithmic Game Theory,Georgios2017,False,,Springer,Not available,Tight Welfare Guarantees for Pure Nash Equilibria of the Uniform Price Auction,465373c9ad74b0f572f6c8930af08b4a,http://dx.doi.org/10.1007/978-3-319-66700-3_2
365,This chapter considers three fundamental problems in the general area of communication networks and their relationship to game theory. These problems are (i) allocation of shared bandwidth resources  (ii) routing across shared links  and (iii) scheduling across shared spectrum. Each problem inherently involves agents that experience negative externalities under which the presence of one degrades the utility perceived by others. Two approaches to solving such problems are (i) to find a globally optimal allocation and simply implement it in a fait accompli fashion  and (ii) request information from the competing agents (traffic flows) and construct a mechanism to allocate resources. Often  only the second option is viable  since a centralized solution using complete information might be impractical (or impossible) with many millions of competing flows  each one having private information about the application that it corresponds to. Hence  a game theoretical analysis of these problems is natural. In what follows  we will present results on each problem and characterize the efficiency loss that results from the mechanism employed.,srinivas shakkottai,Not available,2017.0,10.1007/978-3-319-27335-8_29-1,Handbook of Dynamic Game Theory,Srinivas2017,False,,Springer,Not available,Communication Networks: Pricing  Congestion Control  Routing  and Scheduling,8ebee6f6893e047dbf568e08bd43ecae,http://dx.doi.org/10.1007/978-3-319-27335-8_29-1
366,This chapter considers three fundamental problems in the general area of communication networks and their relationship to game theory. These problems are (i) allocation of shared bandwidth resources  (ii) routing across shared links  and (iii) scheduling across shared spectrum. Each problem inherently involves agents that experience negative externalities under which the presence of one degrades the utility perceived by others. Two approaches to solving such problems are (i) to find a globally optimal allocation and simply implement it in a fait accompli fashion  and (ii) request information from the competing agents (traffic flows) and construct a mechanism to allocate resources. Often  only the second option is viable  since a centralized solution using complete information might be impractical (or impossible) with many millions of competing flows  each one having private information about the application that it corresponds to. Hence  a game theoretical analysis of these problems is natural. In what follows  we will present results on each problem and characterize the efficiency loss that results from the mechanism employed.,r. srikant,Not available,2017.0,10.1007/978-3-319-27335-8_29-1,Handbook of Dynamic Game Theory,Srinivas2017,False,,Springer,Not available,Communication Networks: Pricing  Congestion Control  Routing  and Scheduling,8ebee6f6893e047dbf568e08bd43ecae,http://dx.doi.org/10.1007/978-3-319-27335-8_29-1
367,Recently  there has been an increased research interest in telecommunication network pricing  which leads to many proposals for new pricing schemes motivated by different objectives namely: to maximize service provider’s revenue  to guarantee fairness among users and to satisfy QoS requirements for differentiated network services.In present paper  we consider a Bertrand model with ,omar ait,Not available,2017.0,10.1007/978-3-319-59647-1_33,Networked Systems,Driss2017,False,,Springer,Not available,Joint Price and QoS Competition with Bounded Rational Customers,a5e86c9aa2e048137a40f11663f50628,http://dx.doi.org/10.1007/978-3-319-59647-1_33
368,Most work in algorithmic game theory assumes that players ignore costs incurred by their fellow players. In this paper  we consider superimposing a social network over a game  where players are concerned with minimizing not only their own costs  but also the costs of their neighbors in the network. We aim to understand how properties of the underlying game are affected by this alteration to the standard model. The new social game has its own equilibria  and the ,sam taggart,Not available,2011.0,10.1007/978-3-642-25510-6_32,Internet and Network Economics,Russell2011,False,,Springer,Not available,The Price of Civil Society,9baab19fbad6f8cdd30475f481a22030,http://dx.doi.org/10.1007/978-3-642-25510-6_32
369,Recently  there has been an increased research interest in telecommunication network pricing  which leads to many proposals for new pricing schemes motivated by different objectives namely: to maximize service provider’s revenue  to guarantee fairness among users and to satisfy QoS requirements for differentiated network services.In present paper  we consider a Bertrand model with ,m'hamed outanoute,Not available,2017.0,10.1007/978-3-319-59647-1_33,Networked Systems,Driss2017,False,,Springer,Not available,Joint Price and QoS Competition with Bounded Rational Customers,a5e86c9aa2e048137a40f11663f50628,http://dx.doi.org/10.1007/978-3-319-59647-1_33
370,Recently  there has been an increased research interest in telecommunication network pricing  which leads to many proposals for new pricing schemes motivated by different objectives namely: to maximize service provider’s revenue  to guarantee fairness among users and to satisfy QoS requirements for differentiated network services.In present paper  we consider a Bertrand model with ,mohamed baslam,Not available,2017.0,10.1007/978-3-319-59647-1_33,Networked Systems,Driss2017,False,,Springer,Not available,Joint Price and QoS Competition with Bounded Rational Customers,a5e86c9aa2e048137a40f11663f50628,http://dx.doi.org/10.1007/978-3-319-59647-1_33
371,Recently  there has been an increased research interest in telecommunication network pricing  which leads to many proposals for new pricing schemes motivated by different objectives namely: to maximize service provider’s revenue  to guarantee fairness among users and to satisfy QoS requirements for differentiated network services.In present paper  we consider a Bertrand model with ,mohamed fakir,Not available,2017.0,10.1007/978-3-319-59647-1_33,Networked Systems,Driss2017,False,,Springer,Not available,Joint Price and QoS Competition with Bounded Rational Customers,a5e86c9aa2e048137a40f11663f50628,http://dx.doi.org/10.1007/978-3-319-59647-1_33
372,Recently  there has been an increased research interest in telecommunication network pricing  which leads to many proposals for new pricing schemes motivated by different objectives namely: to maximize service provider’s revenue  to guarantee fairness among users and to satisfy QoS requirements for differentiated network services.In present paper  we consider a Bertrand model with ,belaid bouikhalne,Not available,2017.0,10.1007/978-3-319-59647-1_33,Networked Systems,Driss2017,False,,Springer,Not available,Joint Price and QoS Competition with Bounded Rational Customers,a5e86c9aa2e048137a40f11663f50628,http://dx.doi.org/10.1007/978-3-319-59647-1_33
373,We study assignment games in which jobs select machines  and in which certain pairs of jobs may conflict  which is to say they may incur an additional cost when they are both assigned to the same machine  beyond that associated with the increase in load. Questions regarding such interactions apply beyond allocating jobs to machines: when people in a social network choose to align themselves with a group or party  they typically do so based upon not only the inherent quality of that group  but also who amongst their friends (or enemies) chooses that group as well. We show how ,elliot anshelevich,Not available,2016.0,10.1007/s00224-015-9646-0,Theory of Computing Systems,Elliot2016,False,,Springer,Not available,Assignment Games with Conflicts: Robust Price of Anarchy and Convergence Results via Semi-Smoothness,95f09acb09119ebc9f01d2ff79c0c96a,http://dx.doi.org/10.1007/s00224-015-9646-0
374,We study assignment games in which jobs select machines  and in which certain pairs of jobs may conflict  which is to say they may incur an additional cost when they are both assigned to the same machine  beyond that associated with the increase in load. Questions regarding such interactions apply beyond allocating jobs to machines: when people in a social network choose to align themselves with a group or party  they typically do so based upon not only the inherent quality of that group  but also who amongst their friends (or enemies) chooses that group as well. We show how ,john postl,Not available,2016.0,10.1007/s00224-015-9646-0,Theory of Computing Systems,Elliot2016,False,,Springer,Not available,Assignment Games with Conflicts: Robust Price of Anarchy and Convergence Results via Semi-Smoothness,95f09acb09119ebc9f01d2ff79c0c96a,http://dx.doi.org/10.1007/s00224-015-9646-0
375,We study assignment games in which jobs select machines  and in which certain pairs of jobs may conflict  which is to say they may incur an additional cost when they are both assigned to the same machine  beyond that associated with the increase in load. Questions regarding such interactions apply beyond allocating jobs to machines: when people in a social network choose to align themselves with a group or party  they typically do so based upon not only the inherent quality of that group  but also who amongst their friends (or enemies) chooses that group as well. We show how ,tom wexler,Not available,2016.0,10.1007/s00224-015-9646-0,Theory of Computing Systems,Elliot2016,False,,Springer,Not available,Assignment Games with Conflicts: Robust Price of Anarchy and Convergence Results via Semi-Smoothness,95f09acb09119ebc9f01d2ff79c0c96a,http://dx.doi.org/10.1007/s00224-015-9646-0
376,The Generalized Second Price (GSP) auction used typically to model sponsored search auctions does not include the notion of budget constraints  which is present in practice. Motivated by this  we introduce the different variants of GSP auctions that take budgets into account in natural ways. We examine their stability by focusing on the existence of Nash equilibria and envy-free assignments. We highlight the differences between these mechanisms and find that only some of them exhibit both notions of stability. This shows the importance of carefully picking the right mechanism to ensure stable outcomes in the presence of budgets.,josep diaz,Not available,2016.0,10.1007/s00224-015-9634-4,Theory of Computing Systems,Josep2016,False,,Springer,Not available,On the Stability of Generalized Second Price Auctions with Budgets,a44e816a23f03bce55812dfcdfe4d704,http://dx.doi.org/10.1007/s00224-015-9634-4
377,The Generalized Second Price (GSP) auction used typically to model sponsored search auctions does not include the notion of budget constraints  which is present in practice. Motivated by this  we introduce the different variants of GSP auctions that take budgets into account in natural ways. We examine their stability by focusing on the existence of Nash equilibria and envy-free assignments. We highlight the differences between these mechanisms and find that only some of them exhibit both notions of stability. This shows the importance of carefully picking the right mechanism to ensure stable outcomes in the presence of budgets.,ioannis giotis,Not available,2016.0,10.1007/s00224-015-9634-4,Theory of Computing Systems,Josep2016,False,,Springer,Not available,On the Stability of Generalized Second Price Auctions with Budgets,a44e816a23f03bce55812dfcdfe4d704,http://dx.doi.org/10.1007/s00224-015-9634-4
378,The Generalized Second Price (GSP) auction used typically to model sponsored search auctions does not include the notion of budget constraints  which is present in practice. Motivated by this  we introduce the different variants of GSP auctions that take budgets into account in natural ways. We examine their stability by focusing on the existence of Nash equilibria and envy-free assignments. We highlight the differences between these mechanisms and find that only some of them exhibit both notions of stability. This shows the importance of carefully picking the right mechanism to ensure stable outcomes in the presence of budgets.,lefteris kirousis,Not available,2016.0,10.1007/s00224-015-9634-4,Theory of Computing Systems,Josep2016,False,,Springer,Not available,On the Stability of Generalized Second Price Auctions with Budgets,a44e816a23f03bce55812dfcdfe4d704,http://dx.doi.org/10.1007/s00224-015-9634-4
379,Most work in algorithmic game theory assumes that players ignore costs incurred by their fellow players. In this paper  we consider superimposing a social network over a game  where players are concerned with minimizing not only their own costs  but also the costs of their neighbors in the network. We aim to understand how properties of the underlying game are affected by this alteration to the standard model. The new social game has its own equilibria  and the ,tom wexler,Not available,2011.0,10.1007/978-3-642-25510-6_32,Internet and Network Economics,Russell2011,False,,Springer,Not available,The Price of Civil Society,9baab19fbad6f8cdd30475f481a22030,http://dx.doi.org/10.1007/978-3-642-25510-6_32
380,The Generalized Second Price (GSP) auction used typically to model sponsored search auctions does not include the notion of budget constraints  which is present in practice. Motivated by this  we introduce the different variants of GSP auctions that take budgets into account in natural ways. We examine their stability by focusing on the existence of Nash equilibria and envy-free assignments. We highlight the differences between these mechanisms and find that only some of them exhibit both notions of stability. This shows the importance of carefully picking the right mechanism to ensure stable outcomes in the presence of budgets.,evangelos markakis,Not available,2016.0,10.1007/s00224-015-9634-4,Theory of Computing Systems,Josep2016,False,,Springer,Not available,On the Stability of Generalized Second Price Auctions with Budgets,a44e816a23f03bce55812dfcdfe4d704,http://dx.doi.org/10.1007/s00224-015-9634-4
381,The Generalized Second Price (GSP) auction used typically to model sponsored search auctions does not include the notion of budget constraints  which is present in practice. Motivated by this  we introduce the different variants of GSP auctions that take budgets into account in natural ways. We examine their stability by focusing on the existence of Nash equilibria and envy-free assignments. We highlight the differences between these mechanisms and find that only some of them exhibit both notions of stability. This shows the importance of carefully picking the right mechanism to ensure stable outcomes in the presence of budgets.,maria serna,Not available,2016.0,10.1007/s00224-015-9634-4,Theory of Computing Systems,Josep2016,False,,Springer,Not available,On the Stability of Generalized Second Price Auctions with Budgets,a44e816a23f03bce55812dfcdfe4d704,http://dx.doi.org/10.1007/s00224-015-9634-4
382,We consider nonatomic network games with one source and one destination. We examine the asymptotic behavior of the price of anarchy as the inflow increases. In accordance with some empirical observations  we show that  under suitable conditions  the price of anarchy is asymptotic to one. We show with some counterexamples that this is not always the case. The counterexamples occur in simple parallel graphs.,riccardo colini-baldeschi,Not available,2016.0,10.1007/978-3-662-53354-3_10,Algorithmic Game Theory,Riccardo2016,False,,Springer,Not available,On the Price of Anarchy of Highly Congested Nonatomic Network Games,e24ca9f9a216e4f32b1d73a5d3de0be9,http://dx.doi.org/10.1007/978-3-662-53354-3_10
383,We consider nonatomic network games with one source and one destination. We examine the asymptotic behavior of the price of anarchy as the inflow increases. In accordance with some empirical observations  we show that  under suitable conditions  the price of anarchy is asymptotic to one. We show with some counterexamples that this is not always the case. The counterexamples occur in simple parallel graphs.,roberto cominetti,Not available,2016.0,10.1007/978-3-662-53354-3_10,Algorithmic Game Theory,Riccardo2016,False,,Springer,Not available,On the Price of Anarchy of Highly Congested Nonatomic Network Games,e24ca9f9a216e4f32b1d73a5d3de0be9,http://dx.doi.org/10.1007/978-3-662-53354-3_10
384,We consider nonatomic network games with one source and one destination. We examine the asymptotic behavior of the price of anarchy as the inflow increases. In accordance with some empirical observations  we show that  under suitable conditions  the price of anarchy is asymptotic to one. We show with some counterexamples that this is not always the case. The counterexamples occur in simple parallel graphs.,marco scarsini,Not available,2016.0,10.1007/978-3-662-53354-3_10,Algorithmic Game Theory,Riccardo2016,False,,Springer,Not available,On the Price of Anarchy of Highly Congested Nonatomic Network Games,e24ca9f9a216e4f32b1d73a5d3de0be9,http://dx.doi.org/10.1007/978-3-662-53354-3_10
385,We design a new class of vertex and set cover games  where the price of anarchy bounds match the best known constant factor approximation guarantees for the centralized optimization problems for linear and also for submodular costs. This is in contrast to all previously studied covering games  where the price of anarchy grows linearly with the size of the game. Both the game design and the price of anarchy results are based on structural properties of the linear programming relaxations. For linear costs we also exhibit simple best response dynamics that converge to Nash equilibria in linear time.,georgios piliouras,Not available,2015.0,10.1007/s00224-014-9587-z,Theory of Computing Systems,Georgios2015,False,,Springer,Not available,LP-Based Covering Games with Low Price of Anarchy,947517ac299f93abfdd6ffa322e3ff0b,http://dx.doi.org/10.1007/s00224-014-9587-z
386,We design a new class of vertex and set cover games  where the price of anarchy bounds match the best known constant factor approximation guarantees for the centralized optimization problems for linear and also for submodular costs. This is in contrast to all previously studied covering games  where the price of anarchy grows linearly with the size of the game. Both the game design and the price of anarchy results are based on structural properties of the linear programming relaxations. For linear costs we also exhibit simple best response dynamics that converge to Nash equilibria in linear time.,tomas valla,Not available,2015.0,10.1007/s00224-014-9587-z,Theory of Computing Systems,Georgios2015,False,,Springer,Not available,LP-Based Covering Games with Low Price of Anarchy,947517ac299f93abfdd6ffa322e3ff0b,http://dx.doi.org/10.1007/s00224-014-9587-z
387,We design a new class of vertex and set cover games  where the price of anarchy bounds match the best known constant factor approximation guarantees for the centralized optimization problems for linear and also for submodular costs. This is in contrast to all previously studied covering games  where the price of anarchy grows linearly with the size of the game. Both the game design and the price of anarchy results are based on structural properties of the linear programming relaxations. For linear costs we also exhibit simple best response dynamics that converge to Nash equilibria in linear time.,laszlo vegh,Not available,2015.0,10.1007/s00224-014-9587-z,Theory of Computing Systems,Georgios2015,False,,Springer,Not available,LP-Based Covering Games with Low Price of Anarchy,947517ac299f93abfdd6ffa322e3ff0b,http://dx.doi.org/10.1007/s00224-014-9587-z
388,The efficient design of networks has been an important engineering task that involves challenging combinatorial optimization problems. Typically  a network designer has to select among several alternatives which links to establish so that the resulting network satisfies a given set of connectivity requirements and the cost of establishing the network links is as low as possible. The ,john augustine,Not available,2015.0,10.1007/s00453-013-9845-5,Algorithmica,John2015,False,,Springer,Not available,Enforcing Efficient Equilibria in Network Design Games via Subsidies,e0aba591d3ed6cf52a933dd5f4b169df,http://dx.doi.org/10.1007/s00453-013-9845-5
389,The efficient design of networks has been an important engineering task that involves challenging combinatorial optimization problems. Typically  a network designer has to select among several alternatives which links to establish so that the resulting network satisfies a given set of connectivity requirements and the cost of establishing the network links is as low as possible. The ,ioannis caragiannis,Not available,2015.0,10.1007/s00453-013-9845-5,Algorithmica,John2015,False,,Springer,Not available,Enforcing Efficient Equilibria in Network Design Games via Subsidies,e0aba591d3ed6cf52a933dd5f4b169df,http://dx.doi.org/10.1007/s00453-013-9845-5
390,Most work in algorithmic game theory assumes that players ignore costs incurred by their fellow players. In this paper  we consider superimposing a social network over a game  where players are concerned with minimizing not only their own costs  but also the costs of their neighbors in the network. We aim to understand how properties of the underlying game are affected by this alteration to the standard model. The new social game has its own equilibria  and the ,kevin woods,Not available,2011.0,10.1007/978-3-642-25510-6_32,Internet and Network Economics,Russell2011,False,,Springer,Not available,The Price of Civil Society,9baab19fbad6f8cdd30475f481a22030,http://dx.doi.org/10.1007/978-3-642-25510-6_32
391,The efficient design of networks has been an important engineering task that involves challenging combinatorial optimization problems. Typically  a network designer has to select among several alternatives which links to establish so that the resulting network satisfies a given set of connectivity requirements and the cost of establishing the network links is as low as possible. The ,angelo fanelli,Not available,2015.0,10.1007/s00453-013-9845-5,Algorithmica,John2015,False,,Springer,Not available,Enforcing Efficient Equilibria in Network Design Games via Subsidies,e0aba591d3ed6cf52a933dd5f4b169df,http://dx.doi.org/10.1007/s00453-013-9845-5
392,The efficient design of networks has been an important engineering task that involves challenging combinatorial optimization problems. Typically  a network designer has to select among several alternatives which links to establish so that the resulting network satisfies a given set of connectivity requirements and the cost of establishing the network links is as low as possible. The ,christos kalaitzis,Not available,2015.0,10.1007/s00453-013-9845-5,Algorithmica,John2015,False,,Springer,Not available,Enforcing Efficient Equilibria in Network Design Games via Subsidies,e0aba591d3ed6cf52a933dd5f4b169df,http://dx.doi.org/10.1007/s00453-013-9845-5
393,Public regulatory agencies have traditionally assigned radio-electric spectrum in a static way. This has led to an almost fully assigned but sparsely and unevenly used spectrum  in which it is becoming more difficult to accommodate the increasing demand of wireless communication. This work presents a general view of automated spectrum trading  one of the mechanisms proposed to improve spectrum efficiency. Licensed operators would be able to lease their unused bandwidth to unlicensed ones in secondary markets  satisfying real time demands from users. This results in a higher and more dynamic use of spectrum while providing incentives to spectrum owners for allowing secondary users to access their unused spectrum. Several approaches can be found in this research area combining game theory  economic models and auction design  among others. We describe and organize the main objectives and challenges of spectrum trading  and present a comprehensive classification and explanation of the existing research lines  showing how different works addressed each relevant issue  discussing the benefits and drawbacks of each approach. Finally  we highlight future research trends in this topic and identify critical but possibly overlooked problems.,mario lopez-martinez,Not available,2015.0,10.1007/s11276-014-0812-0,Wireless Networks,Mario2015,False,,Springer,Not available,Automated spectrum trading mechanisms: understanding the big picture,17116cfc34007f8a542005401461a4d2,http://dx.doi.org/10.1007/s11276-014-0812-0
394,Public regulatory agencies have traditionally assigned radio-electric spectrum in a static way. This has led to an almost fully assigned but sparsely and unevenly used spectrum  in which it is becoming more difficult to accommodate the increasing demand of wireless communication. This work presents a general view of automated spectrum trading  one of the mechanisms proposed to improve spectrum efficiency. Licensed operators would be able to lease their unused bandwidth to unlicensed ones in secondary markets  satisfying real time demands from users. This results in a higher and more dynamic use of spectrum while providing incentives to spectrum owners for allowing secondary users to access their unused spectrum. Several approaches can be found in this research area combining game theory  economic models and auction design  among others. We describe and organize the main objectives and challenges of spectrum trading  and present a comprehensive classification and explanation of the existing research lines  showing how different works addressed each relevant issue  discussing the benefits and drawbacks of each approach. Finally  we highlight future research trends in this topic and identify critical but possibly overlooked problems.,juan alcaraz,Not available,2015.0,10.1007/s11276-014-0812-0,Wireless Networks,Mario2015,False,,Springer,Not available,Automated spectrum trading mechanisms: understanding the big picture,17116cfc34007f8a542005401461a4d2,http://dx.doi.org/10.1007/s11276-014-0812-0
395,Public regulatory agencies have traditionally assigned radio-electric spectrum in a static way. This has led to an almost fully assigned but sparsely and unevenly used spectrum  in which it is becoming more difficult to accommodate the increasing demand of wireless communication. This work presents a general view of automated spectrum trading  one of the mechanisms proposed to improve spectrum efficiency. Licensed operators would be able to lease their unused bandwidth to unlicensed ones in secondary markets  satisfying real time demands from users. This results in a higher and more dynamic use of spectrum while providing incentives to spectrum owners for allowing secondary users to access their unused spectrum. Several approaches can be found in this research area combining game theory  economic models and auction design  among others. We describe and organize the main objectives and challenges of spectrum trading  and present a comprehensive classification and explanation of the existing research lines  showing how different works addressed each relevant issue  discussing the benefits and drawbacks of each approach. Finally  we highlight future research trends in this topic and identify critical but possibly overlooked problems.,javier vales-alonso,Not available,2015.0,10.1007/s11276-014-0812-0,Wireless Networks,Mario2015,False,,Springer,Not available,Automated spectrum trading mechanisms: understanding the big picture,17116cfc34007f8a542005401461a4d2,http://dx.doi.org/10.1007/s11276-014-0812-0
396,Public regulatory agencies have traditionally assigned radio-electric spectrum in a static way. This has led to an almost fully assigned but sparsely and unevenly used spectrum  in which it is becoming more difficult to accommodate the increasing demand of wireless communication. This work presents a general view of automated spectrum trading  one of the mechanisms proposed to improve spectrum efficiency. Licensed operators would be able to lease their unused bandwidth to unlicensed ones in secondary markets  satisfying real time demands from users. This results in a higher and more dynamic use of spectrum while providing incentives to spectrum owners for allowing secondary users to access their unused spectrum. Several approaches can be found in this research area combining game theory  economic models and auction design  among others. We describe and organize the main objectives and challenges of spectrum trading  and present a comprehensive classification and explanation of the existing research lines  showing how different works addressed each relevant issue  discussing the benefits and drawbacks of each approach. Finally  we highlight future research trends in this topic and identify critical but possibly overlooked problems.,joan garcia-haro,Not available,2015.0,10.1007/s11276-014-0812-0,Wireless Networks,Mario2015,False,,Springer,Not available,Automated spectrum trading mechanisms: understanding the big picture,17116cfc34007f8a542005401461a4d2,http://dx.doi.org/10.1007/s11276-014-0812-0
397,In this paper we study quality measures of different solution concepts for the multicast network design game on a ring topology. We recall from the literature a lower bound of ,akaki mamageishvili,Not available,2015.0,10.1007/978-3-319-26626-8_32,Combinatorial Optimization and Applications,Akaki2015,False,,Springer,Not available,Multicast Network Design Game on a Ring,bfd6c336b6a530acd364a94c67fe7909,http://dx.doi.org/10.1007/978-3-319-26626-8_32
398,In this paper we study quality measures of different solution concepts for the multicast network design game on a ring topology. We recall from the literature a lower bound of ,matus mihalak,Not available,2015.0,10.1007/978-3-319-26626-8_32,Combinatorial Optimization and Applications,Akaki2015,False,,Springer,Not available,Multicast Network Design Game on a Ring,bfd6c336b6a530acd364a94c67fe7909,http://dx.doi.org/10.1007/978-3-319-26626-8_32
399,Competition based on service frequency influences capacity decisions in airline markets and has important implications for airline profitability and airport congestion. The market share of a competing airline is a function of its frequency share. This relationship is pivotal for understanding the impacts of frequency competition on airport congestion and on the airline business in general. Additionally  airport congestion is closely related to several aspects of runway  taxiway  and airborne safety. Based on the most popular form of the relationship between market share and frequency share  we propose a game-theoretic model of frequency competition. We characterize the conditions for Nash equilibrium’s existence and uniqueness for the two-player case. We analyze myopic learning dynamics for the non-equilibrium situations and prove their convergence to Nash equilibrium under mild conditions. For the N-player symmetric game  we characterize all the pure strategy equilibria and identify the worst-case equilibrium  i.e.  the equilibrium with maximum total cost. We provide a measure of the congestion level  based on the concept of price of anarchy and investigate its dependence on game parameters.,vikrant vaze,Not available,2015.0,10.1007/978-3-319-13009-5_7,Game Theoretic Analysis of Congestion  Safety and Security,Vikrant2015,False,,Springer,Not available,The Price of Airline Frequency Competition,2fc25752a60defa6f712e621c3b78db0,http://dx.doi.org/10.1007/978-3-319-13009-5_7
400,Competition based on service frequency influences capacity decisions in airline markets and has important implications for airline profitability and airport congestion. The market share of a competing airline is a function of its frequency share. This relationship is pivotal for understanding the impacts of frequency competition on airport congestion and on the airline business in general. Additionally  airport congestion is closely related to several aspects of runway  taxiway  and airborne safety. Based on the most popular form of the relationship between market share and frequency share  we propose a game-theoretic model of frequency competition. We characterize the conditions for Nash equilibrium’s existence and uniqueness for the two-player case. We analyze myopic learning dynamics for the non-equilibrium situations and prove their convergence to Nash equilibrium under mild conditions. For the N-player symmetric game  we characterize all the pure strategy equilibria and identify the worst-case equilibrium  i.e.  the equilibrium with maximum total cost. We provide a measure of the congestion level  based on the concept of price of anarchy and investigate its dependence on game parameters.,cynthia barnhart,Not available,2015.0,10.1007/978-3-319-13009-5_7,Game Theoretic Analysis of Congestion  Safety and Security,Vikrant2015,False,,Springer,Not available,The Price of Airline Frequency Competition,2fc25752a60defa6f712e621c3b78db0,http://dx.doi.org/10.1007/978-3-319-13009-5_7
401,Due to the lack of coordination  it is unlikely that the selfish players of a strategic game reach a socially good state. Using Stackelberg strategies is a popular way to improve the system’s performance. Stackelberg strategies consist of controlling the action of a fraction ,bruno escoffier,Not available,2011.0,10.1007/978-3-642-24829-0_9,Algorithmic Game Theory,Bruno2011,False,,Springer,Not available,The Price of Optimum in a Matching Game,4a4ffd5f6795ff456a16886aef9e7f1e,http://dx.doi.org/10.1007/978-3-642-24829-0_9
402,We investigate the loss in optimality due to the presence of selfish players in sequential games  a relevant subclass of extensive form games with perfect information recently introduced in Paes Leme et al. (Proceedings of innovations in theoretical computer science (ITCS)  ACM  New York  pp. 60–67  ,vittorio bilo,Not available,2015.0,10.1007/s00224-013-9529-1,Theory of Computing Systems,Vittorio2015,False,,Springer,Not available,Some Anomalies of Farsighted Strategic Behavior,e341391e3f8f5b37a888d26bb89cb063,http://dx.doi.org/10.1007/s00224-013-9529-1
403,We investigate the loss in optimality due to the presence of selfish players in sequential games  a relevant subclass of extensive form games with perfect information recently introduced in Paes Leme et al. (Proceedings of innovations in theoretical computer science (ITCS)  ACM  New York  pp. 60–67  ,michele flammini,Not available,2015.0,10.1007/s00224-013-9529-1,Theory of Computing Systems,Vittorio2015,False,,Springer,Not available,Some Anomalies of Farsighted Strategic Behavior,e341391e3f8f5b37a888d26bb89cb063,http://dx.doi.org/10.1007/s00224-013-9529-1
404,We investigate the loss in optimality due to the presence of selfish players in sequential games  a relevant subclass of extensive form games with perfect information recently introduced in Paes Leme et al. (Proceedings of innovations in theoretical computer science (ITCS)  ACM  New York  pp. 60–67  ,gianpiero monaco,Not available,2015.0,10.1007/s00224-013-9529-1,Theory of Computing Systems,Vittorio2015,False,,Springer,Not available,Some Anomalies of Farsighted Strategic Behavior,e341391e3f8f5b37a888d26bb89cb063,http://dx.doi.org/10.1007/s00224-013-9529-1
405,We investigate the loss in optimality due to the presence of selfish players in sequential games  a relevant subclass of extensive form games with perfect information recently introduced in Paes Leme et al. (Proceedings of innovations in theoretical computer science (ITCS)  ACM  New York  pp. 60–67  ,luca moscardelli,Not available,2015.0,10.1007/s00224-013-9529-1,Theory of Computing Systems,Vittorio2015,False,,Springer,Not available,Some Anomalies of Farsighted Strategic Behavior,e341391e3f8f5b37a888d26bb89cb063,http://dx.doi.org/10.1007/s00224-013-9529-1
406,We study the performance of subgame perfect equilibria  a solution concept which better captures the players’ rationality in sequential games with respect to the classical myopic dynamics based on the notions of improving deviations and Nash equilibria  in the context of sequential isolation games. In particular  for two important classes of sequential isolation games  we show upper and lower bounds on the sequential price of anarchy  that is the worst-case ratio between the social performance of an optimal solution and that of a subgame perfect equilibrium  under the two classical social functions mostly investigated in the scientific literature  namely  the minimum utility per player and the sum of the players’ utilities.,anna angelucci,Not available,2015.0,10.1007/s10878-013-9694-9,Journal of Combinatorial Optimization,Anna2015,False,,Springer,Not available,On the sequential price of anarchy of isolation games,231198b42bfe495d6cbd5cc4aece6cf3,http://dx.doi.org/10.1007/s10878-013-9694-9
407,We study the performance of subgame perfect equilibria  a solution concept which better captures the players’ rationality in sequential games with respect to the classical myopic dynamics based on the notions of improving deviations and Nash equilibria  in the context of sequential isolation games. In particular  for two important classes of sequential isolation games  we show upper and lower bounds on the sequential price of anarchy  that is the worst-case ratio between the social performance of an optimal solution and that of a subgame perfect equilibrium  under the two classical social functions mostly investigated in the scientific literature  namely  the minimum utility per player and the sum of the players’ utilities.,vittorio bilo,Not available,2015.0,10.1007/s10878-013-9694-9,Journal of Combinatorial Optimization,Anna2015,False,,Springer,Not available,On the sequential price of anarchy of isolation games,231198b42bfe495d6cbd5cc4aece6cf3,http://dx.doi.org/10.1007/s10878-013-9694-9
408,We study the performance of subgame perfect equilibria  a solution concept which better captures the players’ rationality in sequential games with respect to the classical myopic dynamics based on the notions of improving deviations and Nash equilibria  in the context of sequential isolation games. In particular  for two important classes of sequential isolation games  we show upper and lower bounds on the sequential price of anarchy  that is the worst-case ratio between the social performance of an optimal solution and that of a subgame perfect equilibrium  under the two classical social functions mostly investigated in the scientific literature  namely  the minimum utility per player and the sum of the players’ utilities.,michele flammini,Not available,2015.0,10.1007/s10878-013-9694-9,Journal of Combinatorial Optimization,Anna2015,False,,Springer,Not available,On the sequential price of anarchy of isolation games,231198b42bfe495d6cbd5cc4aece6cf3,http://dx.doi.org/10.1007/s10878-013-9694-9
409,We study the performance of subgame perfect equilibria  a solution concept which better captures the players’ rationality in sequential games with respect to the classical myopic dynamics based on the notions of improving deviations and Nash equilibria  in the context of sequential isolation games. In particular  for two important classes of sequential isolation games  we show upper and lower bounds on the sequential price of anarchy  that is the worst-case ratio between the social performance of an optimal solution and that of a subgame perfect equilibrium  under the two classical social functions mostly investigated in the scientific literature  namely  the minimum utility per player and the sum of the players’ utilities.,luca moscardelli,Not available,2015.0,10.1007/s10878-013-9694-9,Journal of Combinatorial Optimization,Anna2015,False,,Springer,Not available,On the sequential price of anarchy of isolation games,231198b42bfe495d6cbd5cc4aece6cf3,http://dx.doi.org/10.1007/s10878-013-9694-9
410,Game theory plays a central role in studying systems with a number of interacting players competing for a common resource. A communication network serves as a prototypical example of such a system  where the common resource is the network  consisting of nodes and links with limited capacities  and the players are the computers  web servers  and other end hosts who want to transfer information over the shared network. In this entry  we present several examples of game-theoretic interaction in communication networks and present a simple mathematical model to study one such instance  namely  resource allocation in the Internet.,r srikant,Not available,2015.0,10.1007/978-1-4471-5058-9_35,Encyclopedia of Systems and Control,R2015,False,,Springer,Not available,Network Games,029ce67583bb38195fcb19d65b1ccd6a,http://dx.doi.org/10.1007/978-1-4471-5058-9_35
411,We study Nash and strong equilibria in weighted and unweighted bottleneck games. In such a game every (weighted) player chooses a subset of a given set of resources as her strategy. The cost of a resource depends on the total weight of players choosing it and the personal cost every player tries to minimize is the cost of the most expensive resource in her strategy  the ,t. werth,Not available,2014.0,10.1007/s10100-013-0295-6,Central European Journal of Operations Research,L.2014,False,,Springer,Not available,Computation of equilibria and the price of anarchy in bottleneck congestion games,a34859b024f4f0a44de82957f390b36d,http://dx.doi.org/10.1007/s10100-013-0295-6
412,Due to the lack of coordination  it is unlikely that the selfish players of a strategic game reach a socially good state. Using Stackelberg strategies is a popular way to improve the system’s performance. Stackelberg strategies consist of controlling the action of a fraction ,laurent gourves,Not available,2011.0,10.1007/978-3-642-24829-0_9,Algorithmic Game Theory,Bruno2011,False,,Springer,Not available,The Price of Optimum in a Matching Game,4a4ffd5f6795ff456a16886aef9e7f1e,http://dx.doi.org/10.1007/978-3-642-24829-0_9
413,We study Nash and strong equilibria in weighted and unweighted bottleneck games. In such a game every (weighted) player chooses a subset of a given set of resources as her strategy. The cost of a resource depends on the total weight of players choosing it and the personal cost every player tries to minimize is the cost of the most expensive resource in her strategy  the ,h. sperber,Not available,2014.0,10.1007/s10100-013-0295-6,Central European Journal of Operations Research,L.2014,False,,Springer,Not available,Computation of equilibria and the price of anarchy in bottleneck congestion games,a34859b024f4f0a44de82957f390b36d,http://dx.doi.org/10.1007/s10100-013-0295-6
414,We study Nash and strong equilibria in weighted and unweighted bottleneck games. In such a game every (weighted) player chooses a subset of a given set of resources as her strategy. The cost of a resource depends on the total weight of players choosing it and the personal cost every player tries to minimize is the cost of the most expensive resource in her strategy  the ,s. krumke,Not available,2014.0,10.1007/s10100-013-0295-6,Central European Journal of Operations Research,L.2014,False,,Springer,Not available,Computation of equilibria and the price of anarchy in bottleneck congestion games,a34859b024f4f0a44de82957f390b36d,http://dx.doi.org/10.1007/s10100-013-0295-6
415,In game theory  it is well known that being able to commit to a strategy before other players move can be beneficial. In this paper  we analyze ,joshua letchford,Not available,2014.0,10.1007/s10458-013-9246-9,Autonomous Agents and Multi-Agent Systems,Joshua2014,False,,Springer,Not available,On the value of commitment,bb23a7f6514833c79a4bc8c22f0264e3,http://dx.doi.org/10.1007/s10458-013-9246-9
416,In game theory  it is well known that being able to commit to a strategy before other players move can be beneficial. In this paper  we analyze ,dmytro korzhyk,Not available,2014.0,10.1007/s10458-013-9246-9,Autonomous Agents and Multi-Agent Systems,Joshua2014,False,,Springer,Not available,On the value of commitment,bb23a7f6514833c79a4bc8c22f0264e3,http://dx.doi.org/10.1007/s10458-013-9246-9
417,In game theory  it is well known that being able to commit to a strategy before other players move can be beneficial. In this paper  we analyze ,vincent conitzer,Not available,2014.0,10.1007/s10458-013-9246-9,Autonomous Agents and Multi-Agent Systems,Joshua2014,False,,Springer,Not available,On the value of commitment,bb23a7f6514833c79a4bc8c22f0264e3,http://dx.doi.org/10.1007/s10458-013-9246-9
418,We examine how to induce selfish heterogeneous users in a multicommodity network to reach an equilibrium that minimizes the social cost. In the absence of centralized coordination  we use the classical method of imposing appropriate taxes (tolls) on the edges of the network. We significantly generalize previous work (Yang and Huang in Transp. Res. Part B 38:1–15  [,george karakostas,Not available,2009.0,10.1007/s00453-008-9181-3,Algorithmica,George2009,False,,Springer,Not available,Edge Pricing of Multicommodity Networks for Selfish Users with Elastic Demands,2f8d57f929337aab3a1e744abf3fc6a1,http://dx.doi.org/10.1007/s00453-008-9181-3
419,We examine how to induce selfish heterogeneous users in a multicommodity network to reach an equilibrium that minimizes the social cost. In the absence of centralized coordination  we use the classical method of imposing appropriate taxes (tolls) on the edges of the network. We significantly generalize previous work (Yang and Huang in Transp. Res. Part B 38:1–15  [,stavros kolliopoulos,Not available,2009.0,10.1007/s00453-008-9181-3,Algorithmica,George2009,False,,Springer,Not available,Edge Pricing of Multicommodity Networks for Selfish Users with Elastic Demands,2f8d57f929337aab3a1e744abf3fc6a1,http://dx.doi.org/10.1007/s00453-008-9181-3
420,Strong Nash equilibria and Pareto-optimal Nash equilibria are natural and important strengthenings of the Nash equilibrium concept. We study these stronger notions of equilibrium in congestion games  focusing on the relationships between the price of anarchy for these equilibria and that for standard Nash equilibria (which is well understood). For ,steve chien,Not available,2009.0,10.1007/978-3-642-02927-1_24,Automata  Languages and Programming,Steve2009,False,,Springer,Not available,Strong and Pareto Price of Anarchy in Congestion Games,5d83d0abf58a7e6014f9746d93767b8d,http://dx.doi.org/10.1007/978-3-642-02927-1_24
421,Strong Nash equilibria and Pareto-optimal Nash equilibria are natural and important strengthenings of the Nash equilibrium concept. We study these stronger notions of equilibrium in congestion games  focusing on the relationships between the price of anarchy for these equilibria and that for standard Nash equilibria (which is well understood). For ,alistair sinclair,Not available,2009.0,10.1007/978-3-642-02927-1_24,Automata  Languages and Programming,Steve2009,False,,Springer,Not available,Strong and Pareto Price of Anarchy in Congestion Games,5d83d0abf58a7e6014f9746d93767b8d,http://dx.doi.org/10.1007/978-3-642-02927-1_24
422,We study Nash equilibria in the context of flows over time. Many results on ,ronald koch,Not available,2009.0,10.1007/978-3-642-04645-2_29,Algorithmic Game Theory,Ronald2009,False,,Springer,Not available,Nash Equilibria and the Price of Anarchy for Flows over Time,830648e2c8cf6565bcf544a56eba896e,http://dx.doi.org/10.1007/978-3-642-04645-2_29
423,Due to the lack of coordination  it is unlikely that the selfish players of a strategic game reach a socially good state. Using Stackelberg strategies is a popular way to improve the system’s performance. Stackelberg strategies consist of controlling the action of a fraction ,jerome monnot,Not available,2011.0,10.1007/978-3-642-24829-0_9,Algorithmic Game Theory,Bruno2011,False,,Springer,Not available,The Price of Optimum in a Matching Game,4a4ffd5f6795ff456a16886aef9e7f1e,http://dx.doi.org/10.1007/978-3-642-24829-0_9
424,We study Nash equilibria in the context of flows over time. Many results on ,martin skutella,Not available,2009.0,10.1007/978-3-642-04645-2_29,Algorithmic Game Theory,Ronald2009,False,,Springer,Not available,Nash Equilibria and the Price of Anarchy for Flows over Time,830648e2c8cf6565bcf544a56eba896e,http://dx.doi.org/10.1007/978-3-642-04645-2_29
425,We study the survivable version of the game theoretic network formation model known as the Connection Game  originally introduced in [4]. In this model  players attempt to connect to a common source node in a network by purchasing edges  and sharing their costs with other players. We introduce the ,elliot anshelevich,Not available,2009.0,10.1007/978-3-642-04645-2_19,Algorithmic Game Theory,Elliot2009,False,,Springer,Not available,Price of Stability in Survivable Network Design,753668edeca5e3642046ac843fc9435a,http://dx.doi.org/10.1007/978-3-642-04645-2_19
426,We study the survivable version of the game theoretic network formation model known as the Connection Game  originally introduced in [4]. In this model  players attempt to connect to a common source node in a network by purchasing edges  and sharing their costs with other players. We introduce the ,bugra caskurlu,Not available,2009.0,10.1007/978-3-642-04645-2_19,Algorithmic Game Theory,Elliot2009,False,,Springer,Not available,Price of Stability in Survivable Network Design,753668edeca5e3642046ac843fc9435a,http://dx.doi.org/10.1007/978-3-642-04645-2_19
427,Due to a lack of incentives  Internet peerings are a notorious bandwidth bottleneck. Through the use of direct interconnection and content delivery networks  content providers are able to provide better services to their customers. These technologies have a profound impact on the business models of internet service providers. Instead of competing for consumers and keeping uplink connection costs low  ISPs face a two-sided market in which they compete for EUs and generate revenues on the CP side of the market. This work presents a formal model for the providers’ pricing decision towards content providers and discusses consequences for the Internet.,thorsten hau,Not available,2009.0,10.1007/978-3-642-01796-4_7,Network Economics for Next Generation Networks,Thorsten2009,False,,Springer,Not available,Price Setting in Two-Sided Markets for Internet Connectivity,59d70619d37d1a70c960ee5b6775ad0e,http://dx.doi.org/10.1007/978-3-642-01796-4_7
428,Due to a lack of incentives  Internet peerings are a notorious bandwidth bottleneck. Through the use of direct interconnection and content delivery networks  content providers are able to provide better services to their customers. These technologies have a profound impact on the business models of internet service providers. Instead of competing for consumers and keeping uplink connection costs low  ISPs face a two-sided market in which they compete for EUs and generate revenues on the CP side of the market. This work presents a formal model for the providers’ pricing decision towards content providers and discusses consequences for the Internet.,walter brenner,Not available,2009.0,10.1007/978-3-642-01796-4_7,Network Economics for Next Generation Networks,Thorsten2009,False,,Springer,Not available,Price Setting in Two-Sided Markets for Internet Connectivity,59d70619d37d1a70c960ee5b6775ad0e,http://dx.doi.org/10.1007/978-3-642-01796-4_7
429,We compute the ,herve moulin,Not available,2008.0,10.1007/s00199-007-0275-y,Economic Theory,Hervé2008,False,,Springer,Not available,The price of anarchy of serial  average and incremental cost sharing,69ad78dbc40b338ff6af4416b62ea54c,http://dx.doi.org/10.1007/s00199-007-0275-y
430,"
We propose a simple and intuitive ",marios mavronicolas,Not available,2008.0,10.1007/s00453-007-9108-4,Algorithmica,Marios2008,False,,Springer,Not available,Cost Sharing Mechanisms for Fair Pricing of Resource Usage,961cfe6305f01ac95e0ce64c2456bbb2,http://dx.doi.org/10.1007/s00453-007-9108-4
431,"
We propose a simple and intuitive ",panagiota panagopoulou,Not available,2008.0,10.1007/s00453-007-9108-4,Algorithmica,Marios2008,False,,Springer,Not available,Cost Sharing Mechanisms for Fair Pricing of Resource Usage,961cfe6305f01ac95e0ce64c2456bbb2,http://dx.doi.org/10.1007/s00453-007-9108-4
432,"
We propose a simple and intuitive ",paul spirakis,Not available,2008.0,10.1007/s00453-007-9108-4,Algorithmica,Marios2008,False,,Springer,Not available,Cost Sharing Mechanisms for Fair Pricing of Resource Usage,961cfe6305f01ac95e0ce64c2456bbb2,http://dx.doi.org/10.1007/s00453-007-9108-4
433,,george christodoulou,Not available,2008.0,10.1007/978-0-387-30162-4_299,Encyclopedia of Algorithms,George2008,False,,Springer,Not available,Price of Anarchy,6e0c9b584b7c4311236567538640cf1c,http://dx.doi.org/10.1007/978-0-387-30162-4_299
434,We consider a model of next-hop routing by self-interested agents. In this model  nodes in a graph (representing ISPs  Autonomous Systems  etc.) make pricing decisions of how much to charge for forwarding traffic from each of their upstream neighbors  and routing decisions of which downstream neighbors to forward traffic to (i.e.  choosing the next hop). Traffic originates at a subset of these nodes that derive a utility when the traffic is routed to its destination node; the traffic demand is elastic and the utility derived from it can be different for different source nodes. Our next-hop routing and pricing model is in sharp contrast with the more common source routing and pricing models  in which the source of traffic determines the entire route from source to destination. For our model  we begin by showing sufficient conditions for prices to result in a Nash equilibrium  and in fact give an efficient algorithm to compute a Nash equilibrium which is as good as the centralized optimum  thus proving that the price of stability is 1. When only a single source node exists  then the price of anarchy is 1 as well  as long as some minor assumptions on player behavior is made. The above results hold for arbitrary convex pricing functions  but with the assumption that the utilities derived from getting traffic to its destination are linear. When utilities can be non-linear functions  we show that Nash equilibrium may not exist  even with simple discrete pricing models.,elliot anshelevich,Not available,2011.0,10.1007/978-3-642-24829-0_25,Algorithmic Game Theory,Elliot2011,False,,Springer,Not available,Strategic Pricing in Next-Hop Routing with Elastic Demands,5b7e979ed8e72b57b0eff1b77d536b88,http://dx.doi.org/10.1007/978-3-642-24829-0_25
435,,artur czumaj,Not available,2008.0,10.1007/978-0-387-30162-4_300,Encyclopedia of Algorithms,Artur2008,False,,Springer,Not available,Price of Anarchy for Machines Models,045aa9bec53a1112131dd0374b893444,http://dx.doi.org/10.1007/978-0-387-30162-4_300
436,,berthold vocking,Not available,2008.0,10.1007/978-0-387-30162-4_300,Encyclopedia of Algorithms,Artur2008,False,,Springer,Not available,Price of Anarchy for Machines Models,045aa9bec53a1112131dd0374b893444,http://dx.doi.org/10.1007/978-0-387-30162-4_300
437,,artur czumaj,Not available,2008.0,10.1007/978-3-642-27848-8_300-2,Encyclopedia of Algorithms,Artur2008,False,,Springer,Not available,Price of Anarchy for Machines Models,045aa9bec53a1112131dd0374b893444,http://dx.doi.org/10.1007/978-3-642-27848-8_300-2
438,,berthold vocking,Not available,2008.0,10.1007/978-3-642-27848-8_300-2,Encyclopedia of Algorithms,Artur2008,False,,Springer,Not available,Price of Anarchy for Machines Models,045aa9bec53a1112131dd0374b893444,http://dx.doi.org/10.1007/978-3-642-27848-8_300-2
439,Cournot oligopoly is typically inefficient in maximizing social welfare which is total surplus of consumer and producer. This paper quantifies the inefficiency of Cournot oligopoly with the term “price of anarchy”  i.e. the worst-case ratio of the maximum possible social welfare to the social welfare at equilibrium. With a parameterization of the equilibrium market share distribution  the inefficiency bounds are dependent on equilibrium market shares as well as market demand and number of firms. Equilibrium market share parameters are practically observable and analytically manageable. As a result  the price of anarchy of Cournot oligopoly established in this paper is applicable to both practical estimation and theoretical analysis.,xiaolei guo,Not available,2005.0,10.1007/11600930_24,Internet and Network Economics,Xiaolei2005,False,,Springer,Not available,The Price of Anarchy of Cournot Oligopoly,1f37991ad4b9958cfb8f12b133a4147b,http://dx.doi.org/10.1007/11600930_24
440,Cournot oligopoly is typically inefficient in maximizing social welfare which is total surplus of consumer and producer. This paper quantifies the inefficiency of Cournot oligopoly with the term “price of anarchy”  i.e. the worst-case ratio of the maximum possible social welfare to the social welfare at equilibrium. With a parameterization of the equilibrium market share distribution  the inefficiency bounds are dependent on equilibrium market shares as well as market demand and number of firms. Equilibrium market share parameters are practically observable and analytically manageable. As a result  the price of anarchy of Cournot oligopoly established in this paper is applicable to both practical estimation and theoretical analysis.,hai yang,Not available,2005.0,10.1007/11600930_24,Internet and Network Economics,Xiaolei2005,False,,Springer,Not available,The Price of Anarchy of Cournot Oligopoly,1f37991ad4b9958cfb8f12b133a4147b,http://dx.doi.org/10.1007/11600930_24
441,In this paper  we define a network service provider game. We show that the price of anarchy of the defined game can be bounded by analyzing a local search heuristic for a related facility location problem called the ,nikhil devanur,Not available,2005.0,10.1007/11600930_105,Internet and Network Economics,Nikhil2005,False,,Springer,Not available,Price of Anarchy  Locality Gap  and a Network Service Provider Game,62cb75c4042df24c45b784e9766d2fd1,http://dx.doi.org/10.1007/11600930_105
442,In this paper  we define a network service provider game. We show that the price of anarchy of the defined game can be bounded by analyzing a local search heuristic for a related facility location problem called the ,naveen garg,Not available,2005.0,10.1007/11600930_105,Internet and Network Economics,Nikhil2005,False,,Springer,Not available,Price of Anarchy  Locality Gap  and a Network Service Provider Game,62cb75c4042df24c45b784e9766d2fd1,http://dx.doi.org/10.1007/11600930_105
443,In this paper  we define a network service provider game. We show that the price of anarchy of the defined game can be bounded by analyzing a local search heuristic for a related facility location problem called the ,rohit khandekar,Not available,2005.0,10.1007/11600930_105,Internet and Network Economics,Nikhil2005,False,,Springer,Not available,Price of Anarchy  Locality Gap  and a Network Service Provider Game,62cb75c4042df24c45b784e9766d2fd1,http://dx.doi.org/10.1007/11600930_105
444,In this paper  we define a network service provider game. We show that the price of anarchy of the defined game can be bounded by analyzing a local search heuristic for a related facility location problem called the ,vinayaka pandit,Not available,2005.0,10.1007/11600930_105,Internet and Network Economics,Nikhil2005,False,,Springer,Not available,Price of Anarchy  Locality Gap  and a Network Service Provider Game,62cb75c4042df24c45b784e9766d2fd1,http://dx.doi.org/10.1007/11600930_105
445,As defined by Aumann in 1959  a strong equilibrium is a Nash equilibrium that is resilient to deviations by coalitions. We give tight bounds on the strong price of anarchy for load balancing on related machines. We also give tight bounds for ,meital levy,Not available,2007.0,10.1007/978-3-540-73420-8_51,Automata  Languages and Programming,Amos2007,False,,Springer,Not available,Strong Price of Anarchy for Machine Load Balancing,e62a88eac6ef598fa8bf2eb73a687dae,http://dx.doi.org/10.1007/978-3-540-73420-8_51
446,We consider a model of next-hop routing by self-interested agents. In this model  nodes in a graph (representing ISPs  Autonomous Systems  etc.) make pricing decisions of how much to charge for forwarding traffic from each of their upstream neighbors  and routing decisions of which downstream neighbors to forward traffic to (i.e.  choosing the next hop). Traffic originates at a subset of these nodes that derive a utility when the traffic is routed to its destination node; the traffic demand is elastic and the utility derived from it can be different for different source nodes. Our next-hop routing and pricing model is in sharp contrast with the more common source routing and pricing models  in which the source of traffic determines the entire route from source to destination. For our model  we begin by showing sufficient conditions for prices to result in a Nash equilibrium  and in fact give an efficient algorithm to compute a Nash equilibrium which is as good as the centralized optimum  thus proving that the price of stability is 1. When only a single source node exists  then the price of anarchy is 1 as well  as long as some minor assumptions on player behavior is made. The above results hold for arbitrary convex pricing functions  but with the assumption that the utilities derived from getting traffic to its destination are linear. When utilities can be non-linear functions  we show that Nash equilibrium may not exist  even with simple discrete pricing models.,ameya hate,Not available,2011.0,10.1007/978-3-642-24829-0_25,Algorithmic Game Theory,Elliot2011,False,,Springer,Not available,Strategic Pricing in Next-Hop Routing with Elastic Demands,5b7e979ed8e72b57b0eff1b77d536b88,http://dx.doi.org/10.1007/978-3-642-24829-0_25
447,In this paper  we define a network service provider game. We show that the price of anarchy of the defined game can be bounded by analyzing a local search heuristic for a related facility location problem called the ,amin saberi,Not available,2005.0,10.1007/11600930_105,Internet and Network Economics,Nikhil2005,False,,Springer,Not available,Price of Anarchy  Locality Gap  and a Network Service Provider Game,62cb75c4042df24c45b784e9766d2fd1,http://dx.doi.org/10.1007/11600930_105
448,In this paper  we define a network service provider game. We show that the price of anarchy of the defined game can be bounded by analyzing a local search heuristic for a related facility location problem called the ,vijay vazirani,Not available,2005.0,10.1007/11600930_105,Internet and Network Economics,Nikhil2005,False,,Springer,Not available,Price of Anarchy  Locality Gap  and a Network Service Provider Game,62cb75c4042df24c45b784e9766d2fd1,http://dx.doi.org/10.1007/11600930_105
449,We consider a class of networks where ,dinesh garg,Not available,2005.0,10.1007/11600930_107,Internet and Network Economics,Dinesh2005,False,,Springer,Not available,Price of Anarchy of Network Routing Games with Incomplete Information,9919c7246ac2792091a7841ca659e8be,http://dx.doi.org/10.1007/11600930_107
450,We consider a class of networks where ,yadati narahari,Not available,2005.0,10.1007/11600930_107,Internet and Network Economics,Dinesh2005,False,,Springer,Not available,Price of Anarchy of Network Routing Games with Incomplete Information,9919c7246ac2792091a7841ca659e8be,http://dx.doi.org/10.1007/11600930_107
451,"
                        ",martin gairing,Not available,2005.0,10.1007/11523468_5,Automata  Languages and Programming,Martin2005,False,,Springer,Not available,Nash Equilibria  the Price of Anarchy and the Fully Mixed Nash Equilibrium Conjecture,60b5d47d11657ab25d694d5cc345aa0c,http://dx.doi.org/10.1007/11523468_5
452,"
                        ",thomas lucking,Not available,2005.0,10.1007/11523468_5,Automata  Languages and Programming,Martin2005,False,,Springer,Not available,Nash Equilibria  the Price of Anarchy and the Fully Mixed Nash Equilibrium Conjecture,60b5d47d11657ab25d694d5cc345aa0c,http://dx.doi.org/10.1007/11523468_5
453,"
                        ",burkhard monien,Not available,2005.0,10.1007/11523468_5,Automata  Languages and Programming,Martin2005,False,,Springer,Not available,Nash Equilibria  the Price of Anarchy and the Fully Mixed Nash Equilibrium Conjecture,60b5d47d11657ab25d694d5cc345aa0c,http://dx.doi.org/10.1007/11523468_5
454,"
                        ",karsten tiemann,Not available,2005.0,10.1007/11523468_5,Automata  Languages and Programming,Martin2005,False,,Springer,Not available,Nash Equilibria  the Price of Anarchy and the Fully Mixed Nash Equilibrium Conjecture,60b5d47d11657ab25d694d5cc345aa0c,http://dx.doi.org/10.1007/11523468_5
455,We propose a simple and intuitive ,marios mavronicolas,Not available,2005.0,10.1007/11600930_21,Internet and Network Economics,Marios2005,False,,Springer,Not available,A Cost Mechanism for Fair Pricing of Resource Usage,8ccc386151d5b9aea00ee79dc2f302c8,http://dx.doi.org/10.1007/11600930_21
456,We propose a simple and intuitive ,panagiota panagopoulou,Not available,2005.0,10.1007/11600930_21,Internet and Network Economics,Marios2005,False,,Springer,Not available,A Cost Mechanism for Fair Pricing of Resource Usage,8ccc386151d5b9aea00ee79dc2f302c8,http://dx.doi.org/10.1007/11600930_21
457,We consider a model of next-hop routing by self-interested agents. In this model  nodes in a graph (representing ISPs  Autonomous Systems  etc.) make pricing decisions of how much to charge for forwarding traffic from each of their upstream neighbors  and routing decisions of which downstream neighbors to forward traffic to (i.e.  choosing the next hop). Traffic originates at a subset of these nodes that derive a utility when the traffic is routed to its destination node; the traffic demand is elastic and the utility derived from it can be different for different source nodes. Our next-hop routing and pricing model is in sharp contrast with the more common source routing and pricing models  in which the source of traffic determines the entire route from source to destination. For our model  we begin by showing sufficient conditions for prices to result in a Nash equilibrium  and in fact give an efficient algorithm to compute a Nash equilibrium which is as good as the centralized optimum  thus proving that the price of stability is 1. When only a single source node exists  then the price of anarchy is 1 as well  as long as some minor assumptions on player behavior is made. The above results hold for arbitrary convex pricing functions  but with the assumption that the utilities derived from getting traffic to its destination are linear. When utilities can be non-linear functions  we show that Nash equilibrium may not exist  even with simple discrete pricing models.,koushik kar,Not available,2011.0,10.1007/978-3-642-24829-0_25,Algorithmic Game Theory,Elliot2011,False,,Springer,Not available,Strategic Pricing in Next-Hop Routing with Elastic Demands,5b7e979ed8e72b57b0eff1b77d536b88,http://dx.doi.org/10.1007/978-3-642-24829-0_25
458,We propose a simple and intuitive ,paul spirakis,Not available,2005.0,10.1007/11600930_21,Internet and Network Economics,Marios2005,False,,Springer,Not available,A Cost Mechanism for Fair Pricing of Resource Usage,8ccc386151d5b9aea00ee79dc2f302c8,http://dx.doi.org/10.1007/11600930_21
459,Imagine a set of self-interested clients  each of whom must choose a server from a permissible set. A server’s latency is inversely proportional to its speed  but it grows linearly with (or  more generally  as the ,anshul kothari,Not available,2005.0,10.1007/11527954_3,Combinatorial and Algorithmic Aspects of Networking,Anshul2005,False,,Springer,Not available,Congestion Games  Load Balancing  and Price of Anarchy,cd96ed18d1f856196ad5638ef42783ae,http://dx.doi.org/10.1007/11527954_3
460,Imagine a set of self-interested clients  each of whom must choose a server from a permissible set. A server’s latency is inversely proportional to its speed  but it grows linearly with (or  more generally  as the ,subhash suri,Not available,2005.0,10.1007/11527954_3,Combinatorial and Algorithmic Aspects of Networking,Anshul2005,False,,Springer,Not available,Congestion Games  Load Balancing  and Price of Anarchy,cd96ed18d1f856196ad5638ef42783ae,http://dx.doi.org/10.1007/11527954_3
461,Imagine a set of self-interested clients  each of whom must choose a server from a permissible set. A server’s latency is inversely proportional to its speed  but it grows linearly with (or  more generally  as the ,csaba toth,Not available,2005.0,10.1007/11527954_3,Combinatorial and Algorithmic Aspects of Networking,Anshul2005,False,,Springer,Not available,Congestion Games  Load Balancing  and Price of Anarchy,cd96ed18d1f856196ad5638ef42783ae,http://dx.doi.org/10.1007/11527954_3
462,Imagine a set of self-interested clients  each of whom must choose a server from a permissible set. A server’s latency is inversely proportional to its speed  but it grows linearly with (or  more generally  as the ,yunhong zhou,Not available,2005.0,10.1007/11527954_3,Combinatorial and Algorithmic Aspects of Networking,Anshul2005,False,,Springer,Not available,Congestion Games  Load Balancing  and Price of Anarchy,cd96ed18d1f856196ad5638ef42783ae,http://dx.doi.org/10.1007/11527954_3
463,This paper uses John Rawls' theory of justice to defend the patent system against charges that it has an unfair effect on access to medications  from the perspective of national and international justice. The paper argues that the patent system is fair in a national context because it respects intellectual property rights and it benefits the least advantaged members of society by providing incentives for inventors  investors  and entrepreneurs. The paper also argues that the patent system is fair in an international context  provided that developed nations take steps to help disease-stricken countries secure internal justice. Fairness in a national or international context also requires that the patent system should include emergency exceptions to deal with short-term inequities.,david resnik,Not available,2004.0,10.1023/B:HCAN.0000041185.52817.8c,Health Care Analysis,B.2004,False,,Springer,Not available,Fair Drug Prices and the Patent System,36b8b8833aa04708c809d13c82c164f1,http://dx.doi.org/10.1023/B:HCAN.0000041185.52817.8c
464,We study the problem of minimizing the maximum latency of flows in networks with congestion. We show that this problem is NP-hard  even when all arc latency functions are linear and there is a single source and sink. Still  one can prove that an optimal flow and an equilibrium flow share a desirable property in this situation: all flow-carrying paths have the same length; i.e.  these solutions are “fair ” which is in general not true for the optimal flow in networks with nonlinear latency functions. In addition  the maximum latency of the Nash equilibrium  which can be computed efficiently  is within a constant factor of that of an optimal solution. That is  the so-called price of anarchy is bounded. In contrast  we present a family of instances that shows that the price of anarchy is unbounded for instances with multiple sources and a single sink  even in networks with linear latencies. Finally  we show that an ,jose correa,Not available,2004.0,10.1007/978-3-540-25960-2_5,Integer Programming and Combinatorial Optimization,R.2004,False,,Springer,Not available,Computational Complexity  Fairness  and the Price of Anarchy of the Maximum Latency Problem,9cf7b266e3cc7819037ee1439de5c415,http://dx.doi.org/10.1007/978-3-540-25960-2_5
465,We study the problem of minimizing the maximum latency of flows in networks with congestion. We show that this problem is NP-hard  even when all arc latency functions are linear and there is a single source and sink. Still  one can prove that an optimal flow and an equilibrium flow share a desirable property in this situation: all flow-carrying paths have the same length; i.e.  these solutions are “fair ” which is in general not true for the optimal flow in networks with nonlinear latency functions. In addition  the maximum latency of the Nash equilibrium  which can be computed efficiently  is within a constant factor of that of an optimal solution. That is  the so-called price of anarchy is bounded. In contrast  we present a family of instances that shows that the price of anarchy is unbounded for instances with multiple sources and a single sink  even in networks with linear latencies. Finally  we show that an ,andreas schulz,Not available,2004.0,10.1007/978-3-540-25960-2_5,Integer Programming and Combinatorial Optimization,R.2004,False,,Springer,Not available,Computational Complexity  Fairness  and the Price of Anarchy of the Maximum Latency Problem,9cf7b266e3cc7819037ee1439de5c415,http://dx.doi.org/10.1007/978-3-540-25960-2_5
466,We study the problem of minimizing the maximum latency of flows in networks with congestion. We show that this problem is NP-hard  even when all arc latency functions are linear and there is a single source and sink. Still  one can prove that an optimal flow and an equilibrium flow share a desirable property in this situation: all flow-carrying paths have the same length; i.e.  these solutions are “fair ” which is in general not true for the optimal flow in networks with nonlinear latency functions. In addition  the maximum latency of the Nash equilibrium  which can be computed efficiently  is within a constant factor of that of an optimal solution. That is  the so-called price of anarchy is bounded. In contrast  we present a family of instances that shows that the price of anarchy is unbounded for instances with multiple sources and a single sink  even in networks with linear latencies. Finally  we show that an ,moses stier,Not available,2004.0,10.1007/978-3-540-25960-2_5,Integer Programming and Combinatorial Optimization,R.2004,False,,Springer,Not available,Computational Complexity  Fairness  and the Price of Anarchy of the Maximum Latency Problem,9cf7b266e3cc7819037ee1439de5c415,http://dx.doi.org/10.1007/978-3-540-25960-2_5
467,In this paper we characterize the “price of anarchy”  i.e.  the inefficiency between user and system optimal solutions  when costs are non-separable  asymmetric and nonlinear  generalizing earlier work that has addressed “the price of anarchy” under separable costs. This generalization models traffic equilibria  competitive multi-period pricing and competitive supply chains. The bounds established in this paper are tight and explicitly account for the degree of asymmetry and nonlinearity of the cost function. We introduce an alternate proof method for providing bounds that uses ideas from semidefinite optimization. Finally  in the context of multi-period pricing our analysis establishes that user and system optimal solutions coincide.,g. perakis,Not available,2004.0,10.1007/978-3-540-25960-2_4,Integer Programming and Combinatorial Optimization,G.2004,False,,Springer,Not available,The Price of Anarchy when Costs Are Non-separable and Asymmetric,4c6dd54b590e6cc300e83bf2ee728f11,http://dx.doi.org/10.1007/978-3-540-25960-2_4
468,Our main goal is to abstract existing repeated sponsored search ad auction mechanisms which includes budgets  and study their equilibrium and dynamics. Our abstraction has multiple agents biding repeatedly for multiple identical items (such as impressions in an ad auction). The agents are budget limited and have a value for per item. We abstract the repeated interaction as a one-shot game  which we call ,asaph arnon,Not available,2011.0,10.1007/978-3-642-24829-0_3,Algorithmic Game Theory,Asaph2011,False,,Springer,Not available,Repeated Budgeted Second Price Ad Auction,223fe9d91518d4841d1763e57d6c8416,http://dx.doi.org/10.1007/978-3-642-24829-0_3
469,In this work  we consider an interesting variant of the well-studied ,martin gairing,Not available,2004.0,10.1007/978-3-540-28629-5_44,Mathematical Foundations of Computer Science 2004,Martin2004,False,,Springer,Not available,The Price of Anarchy for Polynomial Social Cost,35a5639d01ce505828197cb0c6f14442,http://dx.doi.org/10.1007/978-3-540-28629-5_44
470,In this work  we consider an interesting variant of the well-studied ,thomas lucking,Not available,2004.0,10.1007/978-3-540-28629-5_44,Mathematical Foundations of Computer Science 2004,Martin2004,False,,Springer,Not available,The Price of Anarchy for Polynomial Social Cost,35a5639d01ce505828197cb0c6f14442,http://dx.doi.org/10.1007/978-3-540-28629-5_44
471,In this work  we consider an interesting variant of the well-studied ,marios mavronicolas,Not available,2004.0,10.1007/978-3-540-28629-5_44,Mathematical Foundations of Computer Science 2004,Martin2004,False,,Springer,Not available,The Price of Anarchy for Polynomial Social Cost,35a5639d01ce505828197cb0c6f14442,http://dx.doi.org/10.1007/978-3-540-28629-5_44
472,In this work  we consider an interesting variant of the well-studied ,burkhard monien,Not available,2004.0,10.1007/978-3-540-28629-5_44,Mathematical Foundations of Computer Science 2004,Martin2004,False,,Springer,Not available,The Price of Anarchy for Polynomial Social Cost,35a5639d01ce505828197cb0c6f14442,http://dx.doi.org/10.1007/978-3-540-28629-5_44
473,,artur czumaj,Not available,2008.0,10.1007/978-3-642-27848-8_300-2,Encyclopedia of Algorithms,Artur2008,False,,Springer,Not available,Price of Anarchy for Machines Models,045aa9bec53a1112131dd0374b893444,http://dx.doi.org/10.1007/978-3-642-27848-8_300-2
474,,berthold vocking,Not available,2008.0,10.1007/978-3-642-27848-8_300-2,Encyclopedia of Algorithms,Artur2008,False,,Springer,Not available,Price of Anarchy for Machines Models,045aa9bec53a1112131dd0374b893444,http://dx.doi.org/10.1007/978-3-642-27848-8_300-2
475,We consider congestion games with linear latency functions in which each player is aware only of a subset of all the other players. This is modeled by means of a social knowledge graph ,vittorio bilo,Not available,2008.0,10.1007/978-3-540-92185-1_16,Internet and Network Economics,Vittorio2008,False,,Springer,Not available,Graphical Congestion Games,c146b528b98ba8dd6339b91b3869a3b4,http://dx.doi.org/10.1007/978-3-540-92185-1_16
476,We consider congestion games with linear latency functions in which each player is aware only of a subset of all the other players. This is modeled by means of a social knowledge graph ,angelo fanelli,Not available,2008.0,10.1007/978-3-540-92185-1_16,Internet and Network Economics,Vittorio2008,False,,Springer,Not available,Graphical Congestion Games,c146b528b98ba8dd6339b91b3869a3b4,http://dx.doi.org/10.1007/978-3-540-92185-1_16
477,We consider congestion games with linear latency functions in which each player is aware only of a subset of all the other players. This is modeled by means of a social knowledge graph ,michele flammini,Not available,2008.0,10.1007/978-3-540-92185-1_16,Internet and Network Economics,Vittorio2008,False,,Springer,Not available,Graphical Congestion Games,c146b528b98ba8dd6339b91b3869a3b4,http://dx.doi.org/10.1007/978-3-540-92185-1_16
478,We consider congestion games with linear latency functions in which each player is aware only of a subset of all the other players. This is modeled by means of a social knowledge graph ,luca moscardelli,Not available,2008.0,10.1007/978-3-540-92185-1_16,Internet and Network Economics,Vittorio2008,False,,Springer,Not available,Graphical Congestion Games,c146b528b98ba8dd6339b91b3869a3b4,http://dx.doi.org/10.1007/978-3-540-92185-1_16
479,Our main goal is to abstract existing repeated sponsored search ad auction mechanisms which includes budgets  and study their equilibrium and dynamics. Our abstraction has multiple agents biding repeatedly for multiple identical items (such as impressions in an ad auction). The agents are budget limited and have a value for per item. We abstract the repeated interaction as a one-shot game  which we call ,yishay mansour,Not available,2011.0,10.1007/978-3-642-24829-0_3,Algorithmic Game Theory,Asaph2011,False,,Springer,Not available,Repeated Budgeted Second Price Ad Auction,223fe9d91518d4841d1763e57d6c8416,http://dx.doi.org/10.1007/978-3-642-24829-0_3
480,We study path multicoloring games that describe situations in which selfish entities possess communication requests in a multifiber all-optical network. Each player is charged according to the maximum fiber multiplicity that her color (wavelength) choice incurs and the social cost is the maximum player cost. We investigate the price of anarchy of such games and provide two different upper bounds for general graphs—namely the number of wavelengths and the minimum length of a path of maximum disutility  over all worst-case Nash Equilibria—as well as matching lower bounds which hold even for trees; as a corollary we obtain that the price of anarchy in stars is exactly 2. We also prove constant bounds for the price of anarchy in chains and rings in which the number of wavelengths is relatively small compared to the load of the network; in the opposite case we show that the price of anarchy is unbounded.,evangelos bampas,Not available,2008.0,10.1007/978-3-540-92182-0_17,Algorithms and Computation,Evangelos2008,False,,Springer,Not available,On a Non-cooperative Model for Wavelength Assignment in Multifiber Optical Networks ,bfde5951560f6c014279b79c857bd417,http://dx.doi.org/10.1007/978-3-540-92182-0_17
481,We study path multicoloring games that describe situations in which selfish entities possess communication requests in a multifiber all-optical network. Each player is charged according to the maximum fiber multiplicity that her color (wavelength) choice incurs and the social cost is the maximum player cost. We investigate the price of anarchy of such games and provide two different upper bounds for general graphs—namely the number of wavelengths and the minimum length of a path of maximum disutility  over all worst-case Nash Equilibria—as well as matching lower bounds which hold even for trees; as a corollary we obtain that the price of anarchy in stars is exactly 2. We also prove constant bounds for the price of anarchy in chains and rings in which the number of wavelengths is relatively small compared to the load of the network; in the opposite case we show that the price of anarchy is unbounded.,aris pagourtzis,Not available,2008.0,10.1007/978-3-540-92182-0_17,Algorithms and Computation,Evangelos2008,False,,Springer,Not available,On a Non-cooperative Model for Wavelength Assignment in Multifiber Optical Networks ,bfde5951560f6c014279b79c857bd417,http://dx.doi.org/10.1007/978-3-540-92182-0_17
482,We study path multicoloring games that describe situations in which selfish entities possess communication requests in a multifiber all-optical network. Each player is charged according to the maximum fiber multiplicity that her color (wavelength) choice incurs and the social cost is the maximum player cost. We investigate the price of anarchy of such games and provide two different upper bounds for general graphs—namely the number of wavelengths and the minimum length of a path of maximum disutility  over all worst-case Nash Equilibria—as well as matching lower bounds which hold even for trees; as a corollary we obtain that the price of anarchy in stars is exactly 2. We also prove constant bounds for the price of anarchy in chains and rings in which the number of wavelengths is relatively small compared to the load of the network; in the opposite case we show that the price of anarchy is unbounded.,george pierrakos,Not available,2008.0,10.1007/978-3-540-92182-0_17,Algorithms and Computation,Evangelos2008,False,,Springer,Not available,On a Non-cooperative Model for Wavelength Assignment in Multifiber Optical Networks ,bfde5951560f6c014279b79c857bd417,http://dx.doi.org/10.1007/978-3-540-92182-0_17
483,We study path multicoloring games that describe situations in which selfish entities possess communication requests in a multifiber all-optical network. Each player is charged according to the maximum fiber multiplicity that her color (wavelength) choice incurs and the social cost is the maximum player cost. We investigate the price of anarchy of such games and provide two different upper bounds for general graphs—namely the number of wavelengths and the minimum length of a path of maximum disutility  over all worst-case Nash Equilibria—as well as matching lower bounds which hold even for trees; as a corollary we obtain that the price of anarchy in stars is exactly 2. We also prove constant bounds for the price of anarchy in chains and rings in which the number of wavelengths is relatively small compared to the load of the network; in the opposite case we show that the price of anarchy is unbounded.,katerina potika,Not available,2008.0,10.1007/978-3-540-92182-0_17,Algorithms and Computation,Evangelos2008,False,,Springer,Not available,On a Non-cooperative Model for Wavelength Assignment in Multifiber Optical Networks ,bfde5951560f6c014279b79c857bd417,http://dx.doi.org/10.1007/978-3-540-92182-0_17
484,This paper initiates a study of connections between local and global properties of graphical games. Specifically  we introduce a concept of local price of anarchy that quantifies how well subsets of agents respond to their environments. We then show several methods of bounding the global price of anarchy of a game in terms of the local price of anarchy. All our bounds are essentially tight.,oren ben-zwi,Not available,2008.0,10.1007/978-3-540-79309-0_23,Algorithmic Game Theory,Oren2008,False,,Springer,Not available,The Local and Global Price of Anarchy of Graphical Games,3fe9a68dd37a9a3fdd5a2f4bffefb455,http://dx.doi.org/10.1007/978-3-540-79309-0_23
485,This paper initiates a study of connections between local and global properties of graphical games. Specifically  we introduce a concept of local price of anarchy that quantifies how well subsets of agents respond to their environments. We then show several methods of bounding the global price of anarchy of a game in terms of the local price of anarchy. All our bounds are essentially tight.,amir ronen,Not available,2008.0,10.1007/978-3-540-79309-0_23,Algorithmic Game Theory,Oren2008,False,,Springer,Not available,The Local and Global Price of Anarchy of Graphical Games,3fe9a68dd37a9a3fdd5a2f4bffefb455,http://dx.doi.org/10.1007/978-3-540-79309-0_23
486,A good is produced with increasing marginal cost. A group of agents want at most one unit of that good. The two classic methods that solve this problem are average cost and random priority. In the first method users request a unit ex ante and every agent who gets a unit pay average cost of the number of produced units. Under random priority users are ordered without bias and the mechanism successively offers the units at price equal to marginal cost. We compare these mechanisms by the worst absolute surplus loss and find that random priority unambiguously performs better than average cost for any cost function and any number of agents. Fixing the cost function  we show that the ratio of worst absolute surplus losses will be bounded by positive constants for any number of agents  hence the above advantage of random priority is not very large.,ruben juarez,Not available,2008.0,10.1007/s00199-006-0165-8,Economic Theory,Ruben2008,False,,Springer,Not available,The worst absolute surplus loss in the problem of commons: random priority versus average cost,db5b0b335ce8c563925ed9395c57226c,http://dx.doi.org/10.1007/s00199-006-0165-8
487,,leah epstein,Not available,2008.0,10.1007/978-3-642-27848-8_494-1,Encyclopedia of Algorithms,Leah2008,False,,Springer,Not available,Selfish Bin Packing Problems,9d3649c6b6cb6f57197217a56b48e449,http://dx.doi.org/10.1007/978-3-642-27848-8_494-1
488,Given a graph ,hiro ito,Not available,2008.0,10.1007/978-3-540-77891-2_16,WALCOM: Algorithms and Computation,Hiro2008,False,,Springer,Not available,Multi-commodity Source Location Problems and Price of Greed,4cb58ba91ae82fc0716c03eb5afd16e5,http://dx.doi.org/10.1007/978-3-540-77891-2_16
489,Given a graph ,mike paterson,Not available,2008.0,10.1007/978-3-540-77891-2_16,WALCOM: Algorithms and Computation,Hiro2008,False,,Springer,Not available,Multi-commodity Source Location Problems and Price of Greed,4cb58ba91ae82fc0716c03eb5afd16e5,http://dx.doi.org/10.1007/978-3-540-77891-2_16
490,We consider a job scheduling game with two uniformly related parallel machines (or links). Jobs are atomic players  and the delay of a job is the completion time of the machine running it. The private goal of each job is to minimize its own delay and the social goal is to minimize the maximum delay of any job  that is  to minimize the makespan. We consider the well known ,leah epstein,Not available,2010.0,10.1007/s00236-010-0124-5,Acta Informatica,Leah2010,False,,Springer,Not available,Equilibria for two parallel links: the strong price of anarchy versus the price of anarchy,b0ad04cd56b3dee54131b430b99202a9,http://dx.doi.org/10.1007/s00236-010-0124-5
491,Given a graph ,kenya sugihara,Not available,2008.0,10.1007/978-3-540-77891-2_16,WALCOM: Algorithms and Computation,Hiro2008,False,,Springer,Not available,Multi-commodity Source Location Problems and Price of Greed,4cb58ba91ae82fc0716c03eb5afd16e5,http://dx.doi.org/10.1007/978-3-540-77891-2_16
492,We study a bin packing game in which any item to be packed is handled by a selfish agent. Each agent aims at minimizing his sharing cost with the other items staying in the same bin  where the social cost is the number of bins used. We first show that computing a pure Nash equilibrium can be done in polynomial time. We then prove that the price of anarchy for the game is in between 1.6416 and 1.6575  improving the previous bounds.,guosong yu,Not available,2008.0,10.1007/978-3-540-92185-1_50,Internet and Network Economics,Guosong2008,False,,Springer,Not available,Bin Packing of Selfish Items,2c753a52cd6bc4e575fffc3edb41047e,http://dx.doi.org/10.1007/978-3-540-92185-1_50
493,We study a bin packing game in which any item to be packed is handled by a selfish agent. Each agent aims at minimizing his sharing cost with the other items staying in the same bin  where the social cost is the number of bins used. We first show that computing a pure Nash equilibrium can be done in polynomial time. We then prove that the price of anarchy for the game is in between 1.6416 and 1.6575  improving the previous bounds.,guochuan zhang,Not available,2008.0,10.1007/978-3-540-92185-1_50,Internet and Network Economics,Guosong2008,False,,Springer,Not available,Bin Packing of Selfish Items,2c753a52cd6bc4e575fffc3edb41047e,http://dx.doi.org/10.1007/978-3-540-92185-1_50
494,The success of the Internet is remarkable in light of the decentralized manner in which it is designed and operated. Unlike small scale networks  the Internet is built and controlled by a large number of disparate service providers who are not interested in any global optimization. Instead  providers simply seek to maximize their own profit by charging users for access to their service. Users themselves also behave selfishly  optimizing over price and quality of service. Game theory provides a natural framework for the study of such a situation. However  recent work in this area tends to focus on either the service providers or the network users  but not both. This paper introduces a new model for exploring the interaction of these two elements  in which network managers compete for users via prices and the quality of service provided. We study the extent to which competition between service providers hurts the overall social utility of the system.,ara hayrapetyan,Not available,2007.0,10.1007/s00446-006-0020-y,Distributed Computing,Ara2007,False,,Springer,Not available,A network pricing game for selfish traffic,1e6ace55d7fedd0e4eeed19012c6755b,http://dx.doi.org/10.1007/s00446-006-0020-y
495,The success of the Internet is remarkable in light of the decentralized manner in which it is designed and operated. Unlike small scale networks  the Internet is built and controlled by a large number of disparate service providers who are not interested in any global optimization. Instead  providers simply seek to maximize their own profit by charging users for access to their service. Users themselves also behave selfishly  optimizing over price and quality of service. Game theory provides a natural framework for the study of such a situation. However  recent work in this area tends to focus on either the service providers or the network users  but not both. This paper introduces a new model for exploring the interaction of these two elements  in which network managers compete for users via prices and the quality of service provided. We study the extent to which competition between service providers hurts the overall social utility of the system.,eva tardos,Not available,2007.0,10.1007/s00446-006-0020-y,Distributed Computing,Ara2007,False,,Springer,Not available,A network pricing game for selfish traffic,1e6ace55d7fedd0e4eeed19012c6755b,http://dx.doi.org/10.1007/s00446-006-0020-y
496,The success of the Internet is remarkable in light of the decentralized manner in which it is designed and operated. Unlike small scale networks  the Internet is built and controlled by a large number of disparate service providers who are not interested in any global optimization. Instead  providers simply seek to maximize their own profit by charging users for access to their service. Users themselves also behave selfishly  optimizing over price and quality of service. Game theory provides a natural framework for the study of such a situation. However  recent work in this area tends to focus on either the service providers or the network users  but not both. This paper introduces a new model for exploring the interaction of these two elements  in which network managers compete for users via prices and the quality of service provided. We study the extent to which competition between service providers hurts the overall social utility of the system.,tom wexler,Not available,2007.0,10.1007/s00446-006-0020-y,Distributed Computing,Ara2007,False,,Springer,Not available,A network pricing game for selfish traffic,1e6ace55d7fedd0e4eeed19012c6755b,http://dx.doi.org/10.1007/s00446-006-0020-y
497,We introduce and study a congestion game having ,aristotelis giannakos,Not available,2007.0,10.1007/978-3-540-77105-0_22,Internet and Network Economics,Aristotelis2007,False,,Springer,Not available,On the Performance of Congestion Games for Optimum Satisfiability Problems,b992ef1b01acdc00fac9ba0201adfc70,http://dx.doi.org/10.1007/978-3-540-77105-0_22
498,We introduce and study a congestion game having ,laurent gourves,Not available,2007.0,10.1007/978-3-540-77105-0_22,Internet and Network Economics,Aristotelis2007,False,,Springer,Not available,On the Performance of Congestion Games for Optimum Satisfiability Problems,b992ef1b01acdc00fac9ba0201adfc70,http://dx.doi.org/10.1007/978-3-540-77105-0_22
499,We introduce and study a congestion game having ,jerome monnot,Not available,2007.0,10.1007/978-3-540-77105-0_22,Internet and Network Economics,Aristotelis2007,False,,Springer,Not available,On the Performance of Congestion Games for Optimum Satisfiability Problems,b992ef1b01acdc00fac9ba0201adfc70,http://dx.doi.org/10.1007/978-3-540-77105-0_22
500,We introduce and study a congestion game having ,vangelis paschos,Not available,2007.0,10.1007/978-3-540-77105-0_22,Internet and Network Economics,Aristotelis2007,False,,Springer,Not available,On the Performance of Congestion Games for Optimum Satisfiability Problems,b992ef1b01acdc00fac9ba0201adfc70,http://dx.doi.org/10.1007/978-3-540-77105-0_22
501,"We investigate the effect of linear independence in the strategies of congestion games on the convergence time of best improvement sequences and on the pure Price of Anarchy. In particular  we consider symmetric congestion games on extension-parallel networks  an interesting class of networks with linearly independent paths  and establish two remarkable properties previously known only for parallel-link games. We show that for arbitrary (non-negative and non-decreasing) latency functions  any best improvement sequence reaches a pure Nash equilibrium in at most as many steps as the number of players  and that for latency functions in class 
",dimitris fotakis,Not available,2010.0,10.1007/s00224-009-9205-7,Theory of Computing Systems,Dimitris2010,False,,Springer,Not available,Congestion Games with Linearly Independent Paths: Convergence Time and Price of Anarchy,7e5fabb61d1cd2e3b5b3c69ee2a382b1,http://dx.doi.org/10.1007/s00224-009-9205-7
502,We revisit the inefficiency of the uniform price auction  one of the standard multi-unit auction formats  for allocating multiple units of a single good. In the uniform price auction  each bidder submits a sequence of non-increasing marginal bids  for each additional unit  i.e.  a submodular curve. The per unit price is then set to be the highest losing bid. We focus on the pure Nash equilibria of such auctions  for bidders with submodular valuation functions. Our result is a tight upper and lower bound on the inefficiency of equilibria  showing that the Price of Anarchy is bounded by 2.1885. This resolves one of the open questions posed in previous works on multi-unit auctions. We also discuss implications of our bounds for an alternative  more practical form of the auction  employing a “,georgios birmpas,Not available,2018.0,10.1007/s00224-018-9889-7,Theory of Computing Systems,Georgios2018,False,,Springer,Not available,Tight Welfare Guarantees for Pure Nash Equilibria of the Uniform Price Auction,d27f4068ca5946de9c034380783dad07,http://dx.doi.org/10.1007/s00224-018-9889-7
503,We revisit the inefficiency of the uniform price auction  one of the standard multi-unit auction formats  for allocating multiple units of a single good. In the uniform price auction  each bidder submits a sequence of non-increasing marginal bids  for each additional unit  i.e.  a submodular curve. The per unit price is then set to be the highest losing bid. We focus on the pure Nash equilibria of such auctions  for bidders with submodular valuation functions. Our result is a tight upper and lower bound on the inefficiency of equilibria  showing that the Price of Anarchy is bounded by 2.1885. This resolves one of the open questions posed in previous works on multi-unit auctions. We also discuss implications of our bounds for an alternative  more practical form of the auction  employing a “,evangelos markakis,Not available,2018.0,10.1007/s00224-018-9889-7,Theory of Computing Systems,Georgios2018,False,,Springer,Not available,Tight Welfare Guarantees for Pure Nash Equilibria of the Uniform Price Auction,d27f4068ca5946de9c034380783dad07,http://dx.doi.org/10.1007/s00224-018-9889-7
504,We revisit the inefficiency of the uniform price auction  one of the standard multi-unit auction formats  for allocating multiple units of a single good. In the uniform price auction  each bidder submits a sequence of non-increasing marginal bids  for each additional unit  i.e.  a submodular curve. The per unit price is then set to be the highest losing bid. We focus on the pure Nash equilibria of such auctions  for bidders with submodular valuation functions. Our result is a tight upper and lower bound on the inefficiency of equilibria  showing that the Price of Anarchy is bounded by 2.1885. This resolves one of the open questions posed in previous works on multi-unit auctions. We also discuss implications of our bounds for an alternative  more practical form of the auction  employing a “,orestis telelis,Not available,2018.0,10.1007/s00224-018-9889-7,Theory of Computing Systems,Georgios2018,False,,Springer,Not available,Tight Welfare Guarantees for Pure Nash Equilibria of the Uniform Price Auction,d27f4068ca5946de9c034380783dad07,http://dx.doi.org/10.1007/s00224-018-9889-7
505,We revisit the inefficiency of the uniform price auction  one of the standard multi-unit auction formats  for allocating multiple units of a single good. In the uniform price auction  each bidder submits a sequence of non-increasing marginal bids  for each additional unit  i.e.  a submodular curve. The per unit price is then set to be the highest losing bid. We focus on the pure Nash equilibria of such auctions  for bidders with submodular valuation functions. Our result is a tight upper and lower bound on the inefficiency of equilibria  showing that the Price of Anarchy is bounded by 2.1885. This resolves one of the open questions posed in previous works on multi-unit auctions. We also discuss implications of our bounds for an alternative  more practical form of the auction  employing a “,artem tsikiridis,Not available,2018.0,10.1007/s00224-018-9889-7,Theory of Computing Systems,Georgios2018,False,,Springer,Not available,Tight Welfare Guarantees for Pure Nash Equilibria of the Uniform Price Auction,d27f4068ca5946de9c034380783dad07,http://dx.doi.org/10.1007/s00224-018-9889-7
506,Logit-response dynamics (Alós-Ferrer and Netzer in Games Econ Behav 68(2):413–427  ,paolo penna,Not available,2018.0,10.1007/s00182-017-0601-y,International Journal of Game Theory,Paolo2018,False,,Springer,Not available,The price of anarchy and stability in general noisy best-response dynamics,5958133331408ff3f7c34d76145dc17c,http://dx.doi.org/10.1007/s00182-017-0601-y
507,Market makers choose and design market rules to serve certain objectives  such as to maximize revenue from the sales in the case of a single seller and multiple buyers. Given such rules  market participants play against each other to maximize their utility function values on goods acquired  possibly by hiding or misrepresenting their information needed in the implementation of market rules. Today’s Internet economy has changed the information collection process and may make some of the assumptions of market rule implementation obsolete. Here we make a fresh review of works on this challenge on the Internet where new economic systems operate.,yukun cheng,Not available,2018.0,10.1007/s10288-018-0385-3,4OR,Yukun2018,False,,Springer,Not available,Recent studies of agent incentives in internet resource allocation and pricing,3324bd385574f387627973e2fc471bd2,http://dx.doi.org/10.1007/s10288-018-0385-3
508,Market makers choose and design market rules to serve certain objectives  such as to maximize revenue from the sales in the case of a single seller and multiple buyers. Given such rules  market participants play against each other to maximize their utility function values on goods acquired  possibly by hiding or misrepresenting their information needed in the implementation of market rules. Today’s Internet economy has changed the information collection process and may make some of the assumptions of market rule implementation obsolete. Here we make a fresh review of works on this challenge on the Internet where new economic systems operate.,xiaotie deng,Not available,2018.0,10.1007/s10288-018-0385-3,4OR,Yukun2018,False,,Springer,Not available,Recent studies of agent incentives in internet resource allocation and pricing,3324bd385574f387627973e2fc471bd2,http://dx.doi.org/10.1007/s10288-018-0385-3
509,Market makers choose and design market rules to serve certain objectives  such as to maximize revenue from the sales in the case of a single seller and multiple buyers. Given such rules  market participants play against each other to maximize their utility function values on goods acquired  possibly by hiding or misrepresenting their information needed in the implementation of market rules. Today’s Internet economy has changed the information collection process and may make some of the assumptions of market rule implementation obsolete. Here we make a fresh review of works on this challenge on the Internet where new economic systems operate.,dominik scheder,Not available,2018.0,10.1007/s10288-018-0385-3,4OR,Yukun2018,False,,Springer,Not available,Recent studies of agent incentives in internet resource allocation and pricing,3324bd385574f387627973e2fc471bd2,http://dx.doi.org/10.1007/s10288-018-0385-3
510,Network pricing serves as an instrument for congestion management  however  agencies and planners often encounter problems of estimating appropriate toll prices. Tolls are commonly estimated for a single-point deterministic travel demand  which may lead to imperfect policy decisions due to inherent uncertainties in future travel demand. Previous research has addressed the issue of demand uncertainty in the pricing context  but the elastic nature of demand along with its uncertainty has not been explicitly considered. Similarly  interactions between elasticity and uncertainty of demand have not been characterized. This study addresses these gaps and proposes a framework to estimate nearest optimal first-best tolls under long-term stochasticity in elastic demand. We show first that the optimal tolls under the deterministic-elastic and stochastic-elastic demand cases coincide when cost and demand functions are linear  and the set of equilibrium paths is constant. These assumptions are restrictive  so three larger networks are considered numerically  and the subsequent pricing decisions are assessed. The results of the numerical experiments suggest that in many cases  optimal pricing decisions under the combined stochastic-elastic demand scenario resemble those when demand is known exactly. The applications in this study thus suggest that inclusion of demand elasticity offsets the need of considering future demand uncertainties for first-best congestion pricing frameworks.,prateek bansal,Not available,2018.0,10.1007/s11116-017-9769-z,Transportation,Prateek2018,False,,Springer,Not available,Robust network pricing and system optimization under combined long-term stochasticity and elasticity of travel demand,f12f32214f2afa837c37367daf091817,http://dx.doi.org/10.1007/s11116-017-9769-z
511,Network pricing serves as an instrument for congestion management  however  agencies and planners often encounter problems of estimating appropriate toll prices. Tolls are commonly estimated for a single-point deterministic travel demand  which may lead to imperfect policy decisions due to inherent uncertainties in future travel demand. Previous research has addressed the issue of demand uncertainty in the pricing context  but the elastic nature of demand along with its uncertainty has not been explicitly considered. Similarly  interactions between elasticity and uncertainty of demand have not been characterized. This study addresses these gaps and proposes a framework to estimate nearest optimal first-best tolls under long-term stochasticity in elastic demand. We show first that the optimal tolls under the deterministic-elastic and stochastic-elastic demand cases coincide when cost and demand functions are linear  and the set of equilibrium paths is constant. These assumptions are restrictive  so three larger networks are considered numerically  and the subsequent pricing decisions are assessed. The results of the numerical experiments suggest that in many cases  optimal pricing decisions under the combined stochastic-elastic demand scenario resemble those when demand is known exactly. The applications in this study thus suggest that inclusion of demand elasticity offsets the need of considering future demand uncertainties for first-best congestion pricing frameworks.,rohan shah,Not available,2018.0,10.1007/s11116-017-9769-z,Transportation,Prateek2018,False,,Springer,Not available,Robust network pricing and system optimization under combined long-term stochasticity and elasticity of travel demand,f12f32214f2afa837c37367daf091817,http://dx.doi.org/10.1007/s11116-017-9769-z
512,We consider a multi-agent planning problem as a set of activities that has to be planned by several autonomous agents. In general  due to the possible dependencies between the agents’ activities or interactions during execution of those activities  allowing agents to plan individually may lead to a very inefficient or even infeasible solution to the multi-agent planning problem. This is exactly where ,adriaan mors,Not available,2010.0,10.1007/s10458-009-9086-9,Autonomous Agents and Multi-Agent Systems,Adriaan2010,True,,Springer,Not available,Coordination by design and the price of autonomy,f713f0c33e68effd115a15688a8987e8,http://dx.doi.org/10.1007/s10458-009-9086-9
513,Network pricing serves as an instrument for congestion management  however  agencies and planners often encounter problems of estimating appropriate toll prices. Tolls are commonly estimated for a single-point deterministic travel demand  which may lead to imperfect policy decisions due to inherent uncertainties in future travel demand. Previous research has addressed the issue of demand uncertainty in the pricing context  but the elastic nature of demand along with its uncertainty has not been explicitly considered. Similarly  interactions between elasticity and uncertainty of demand have not been characterized. This study addresses these gaps and proposes a framework to estimate nearest optimal first-best tolls under long-term stochasticity in elastic demand. We show first that the optimal tolls under the deterministic-elastic and stochastic-elastic demand cases coincide when cost and demand functions are linear  and the set of equilibrium paths is constant. These assumptions are restrictive  so three larger networks are considered numerically  and the subsequent pricing decisions are assessed. The results of the numerical experiments suggest that in many cases  optimal pricing decisions under the combined stochastic-elastic demand scenario resemble those when demand is known exactly. The applications in this study thus suggest that inclusion of demand elasticity offsets the need of considering future demand uncertainties for first-best congestion pricing frameworks.,stephen boyles,Not available,2018.0,10.1007/s11116-017-9769-z,Transportation,Prateek2018,False,,Springer,Not available,Robust network pricing and system optimization under combined long-term stochasticity and elasticity of travel demand,f12f32214f2afa837c37367daf091817,http://dx.doi.org/10.1007/s11116-017-9769-z
514,How will bounded rationality influence telecommunication network fluctuations? Recently  there has been an increased research interest in telecommunication network pricing  which leads to many proposals for new pricing schemes motivated by different objectives namely: to maximize service provider’s revenue  to guarantee fairness among users and to satisfy quality of service (QoS) requirements for differentiated network services. In the present paper  we consider a system with N rational service providers (SPs) that offer homogeneous telecommunication services to bounded rational costumers. All SPs offer the same services and seek to persuade more customers in the same system  we model this conflict as a noncooperative game. On the one hand  each SP decide his policies of price and QoS in order to maximize his profit. One the other hand  we assume that the customers are boundedly rational and make their subscription decisions probabilistically  according to Luce choice probabilities. Furthermore  the customers decide to which SP to subscribe  each one may migrate to another SP or alternatively switch to “no subscription state” depending on the observed price/QoS. In this work  we have proved through a detailed analysis the existence and uniqueness of Nash equilibrium. We evaluate the impact of user’s bounded rationality on the equilibrium of game. Using the price of anarchy  we examine the performance and efficiency of equilibrium. We have shown that the ,omar ait,Not available,2018.0,10.1007/s00607-018-0642-5,Computing,Driss2018,False,,Springer,Not available,On understanding price-QoS war for competitive market and confused consumers,ff7e6cf6b4049172d72141d95501b79a,http://dx.doi.org/10.1007/s00607-018-0642-5
515,How will bounded rationality influence telecommunication network fluctuations? Recently  there has been an increased research interest in telecommunication network pricing  which leads to many proposals for new pricing schemes motivated by different objectives namely: to maximize service provider’s revenue  to guarantee fairness among users and to satisfy quality of service (QoS) requirements for differentiated network services. In the present paper  we consider a system with N rational service providers (SPs) that offer homogeneous telecommunication services to bounded rational costumers. All SPs offer the same services and seek to persuade more customers in the same system  we model this conflict as a noncooperative game. On the one hand  each SP decide his policies of price and QoS in order to maximize his profit. One the other hand  we assume that the customers are boundedly rational and make their subscription decisions probabilistically  according to Luce choice probabilities. Furthermore  the customers decide to which SP to subscribe  each one may migrate to another SP or alternatively switch to “no subscription state” depending on the observed price/QoS. In this work  we have proved through a detailed analysis the existence and uniqueness of Nash equilibrium. We evaluate the impact of user’s bounded rationality on the equilibrium of game. Using the price of anarchy  we examine the performance and efficiency of equilibrium. We have shown that the ,m'hamed outanoute,Not available,2018.0,10.1007/s00607-018-0642-5,Computing,Driss2018,False,,Springer,Not available,On understanding price-QoS war for competitive market and confused consumers,ff7e6cf6b4049172d72141d95501b79a,http://dx.doi.org/10.1007/s00607-018-0642-5
516,How will bounded rationality influence telecommunication network fluctuations? Recently  there has been an increased research interest in telecommunication network pricing  which leads to many proposals for new pricing schemes motivated by different objectives namely: to maximize service provider’s revenue  to guarantee fairness among users and to satisfy quality of service (QoS) requirements for differentiated network services. In the present paper  we consider a system with N rational service providers (SPs) that offer homogeneous telecommunication services to bounded rational costumers. All SPs offer the same services and seek to persuade more customers in the same system  we model this conflict as a noncooperative game. On the one hand  each SP decide his policies of price and QoS in order to maximize his profit. One the other hand  we assume that the customers are boundedly rational and make their subscription decisions probabilistically  according to Luce choice probabilities. Furthermore  the customers decide to which SP to subscribe  each one may migrate to another SP or alternatively switch to “no subscription state” depending on the observed price/QoS. In this work  we have proved through a detailed analysis the existence and uniqueness of Nash equilibrium. We evaluate the impact of user’s bounded rationality on the equilibrium of game. Using the price of anarchy  we examine the performance and efficiency of equilibrium. We have shown that the ,mohamed baslam,Not available,2018.0,10.1007/s00607-018-0642-5,Computing,Driss2018,False,,Springer,Not available,On understanding price-QoS war for competitive market and confused consumers,ff7e6cf6b4049172d72141d95501b79a,http://dx.doi.org/10.1007/s00607-018-0642-5
517,How will bounded rationality influence telecommunication network fluctuations? Recently  there has been an increased research interest in telecommunication network pricing  which leads to many proposals for new pricing schemes motivated by different objectives namely: to maximize service provider’s revenue  to guarantee fairness among users and to satisfy quality of service (QoS) requirements for differentiated network services. In the present paper  we consider a system with N rational service providers (SPs) that offer homogeneous telecommunication services to bounded rational costumers. All SPs offer the same services and seek to persuade more customers in the same system  we model this conflict as a noncooperative game. On the one hand  each SP decide his policies of price and QoS in order to maximize his profit. One the other hand  we assume that the customers are boundedly rational and make their subscription decisions probabilistically  according to Luce choice probabilities. Furthermore  the customers decide to which SP to subscribe  each one may migrate to another SP or alternatively switch to “no subscription state” depending on the observed price/QoS. In this work  we have proved through a detailed analysis the existence and uniqueness of Nash equilibrium. We evaluate the impact of user’s bounded rationality on the equilibrium of game. Using the price of anarchy  we examine the performance and efficiency of equilibrium. We have shown that the ,mohamed fakir,Not available,2018.0,10.1007/s00607-018-0642-5,Computing,Driss2018,False,,Springer,Not available,On understanding price-QoS war for competitive market and confused consumers,ff7e6cf6b4049172d72141d95501b79a,http://dx.doi.org/10.1007/s00607-018-0642-5
518,How will bounded rationality influence telecommunication network fluctuations? Recently  there has been an increased research interest in telecommunication network pricing  which leads to many proposals for new pricing schemes motivated by different objectives namely: to maximize service provider’s revenue  to guarantee fairness among users and to satisfy quality of service (QoS) requirements for differentiated network services. In the present paper  we consider a system with N rational service providers (SPs) that offer homogeneous telecommunication services to bounded rational costumers. All SPs offer the same services and seek to persuade more customers in the same system  we model this conflict as a noncooperative game. On the one hand  each SP decide his policies of price and QoS in order to maximize his profit. One the other hand  we assume that the customers are boundedly rational and make their subscription decisions probabilistically  according to Luce choice probabilities. Furthermore  the customers decide to which SP to subscribe  each one may migrate to another SP or alternatively switch to “no subscription state” depending on the observed price/QoS. In this work  we have proved through a detailed analysis the existence and uniqueness of Nash equilibrium. We evaluate the impact of user’s bounded rationality on the equilibrium of game. Using the price of anarchy  we examine the performance and efficiency of equilibrium. We have shown that the ,belaid bouikhalene,Not available,2018.0,10.1007/s00607-018-0642-5,Computing,Driss2018,False,,Springer,Not available,On understanding price-QoS war for competitive market and confused consumers,ff7e6cf6b4049172d72141d95501b79a,http://dx.doi.org/10.1007/s00607-018-0642-5
519,We study several machine scheduling games  each involving ,long zhang,Not available,2018.0,10.1007/s11590-018-1285-3,Optimization Letters,Long2018,False,,Springer,Not available,Improved price of anarchy for machine scheduling games with coordination mechanisms,cf94e9507d039f70188025ee80788530,http://dx.doi.org/10.1007/s11590-018-1285-3
520,We study several machine scheduling games  each involving ,yuzhong zhang,Not available,2018.0,10.1007/s11590-018-1285-3,Optimization Letters,Long2018,False,,Springer,Not available,Improved price of anarchy for machine scheduling games with coordination mechanisms,cf94e9507d039f70188025ee80788530,http://dx.doi.org/10.1007/s11590-018-1285-3
521,We study several machine scheduling games  each involving ,donglei du,Not available,2018.0,10.1007/s11590-018-1285-3,Optimization Letters,Long2018,False,,Springer,Not available,Improved price of anarchy for machine scheduling games with coordination mechanisms,cf94e9507d039f70188025ee80788530,http://dx.doi.org/10.1007/s11590-018-1285-3
522,We study several machine scheduling games  each involving ,qingguo bai,Not available,2018.0,10.1007/s11590-018-1285-3,Optimization Letters,Long2018,False,,Springer,Not available,Improved price of anarchy for machine scheduling games with coordination mechanisms,cf94e9507d039f70188025ee80788530,http://dx.doi.org/10.1007/s11590-018-1285-3
523,We consider a multi-agent planning problem as a set of activities that has to be planned by several autonomous agents. In general  due to the possible dependencies between the agents’ activities or interactions during execution of those activities  allowing agents to plan individually may lead to a very inefficient or even infeasible solution to the multi-agent planning problem. This is exactly where ,chetan yadati,Not available,2010.0,10.1007/s10458-009-9086-9,Autonomous Agents and Multi-Agent Systems,Adriaan2010,True,,Springer,Not available,Coordination by design and the price of autonomy,f713f0c33e68effd115a15688a8987e8,http://dx.doi.org/10.1007/s10458-009-9086-9
524,We consider the bin packing problem in the non-cooperative game setting. In the game there are a set of items with sizes between 0 and 1 and a number of bins each with a capacity of 1. Each item seeks to be packed in one of the bins so as to minimize its cost (payoff). The social cost is the number of bins used in the packing. Existing research has focused on three bin packing games with selfish items  namely the Unit game  the Proportional game  and the General Weight game  each of which uses a unique payoff rule. In this paper we propose a new bin packing game in which the payoff of an item is a function of its own size and the size of the maximum item in the same bin. We find that the new payoff rule induces the items to reach a better Nash equilibrium. We show that the price of anarchy of the new bin packing game is ,q. nong,Not available,2018.0,10.1007/s10878-017-0201-6,Journal of Combinatorial Optimization,Q.2018,False,,Springer,Not available,Bin packing game with a price of anarchy of ,28065c382f0bd8af770924056bfea4a6,http://dx.doi.org/10.1007/s10878-017-0201-6
525,We consider the bin packing problem in the non-cooperative game setting. In the game there are a set of items with sizes between 0 and 1 and a number of bins each with a capacity of 1. Each item seeks to be packed in one of the bins so as to minimize its cost (payoff). The social cost is the number of bins used in the packing. Existing research has focused on three bin packing games with selfish items  namely the Unit game  the Proportional game  and the General Weight game  each of which uses a unique payoff rule. In this paper we propose a new bin packing game in which the payoff of an item is a function of its own size and the size of the maximum item in the same bin. We find that the new payoff rule induces the items to reach a better Nash equilibrium. We show that the price of anarchy of the new bin packing game is ,t. sun,Not available,2018.0,10.1007/s10878-017-0201-6,Journal of Combinatorial Optimization,Q.2018,False,,Springer,Not available,Bin packing game with a price of anarchy of ,28065c382f0bd8af770924056bfea4a6,http://dx.doi.org/10.1007/s10878-017-0201-6
526,We consider the bin packing problem in the non-cooperative game setting. In the game there are a set of items with sizes between 0 and 1 and a number of bins each with a capacity of 1. Each item seeks to be packed in one of the bins so as to minimize its cost (payoff). The social cost is the number of bins used in the packing. Existing research has focused on three bin packing games with selfish items  namely the Unit game  the Proportional game  and the General Weight game  each of which uses a unique payoff rule. In this paper we propose a new bin packing game in which the payoff of an item is a function of its own size and the size of the maximum item in the same bin. We find that the new payoff rule induces the items to reach a better Nash equilibrium. We show that the price of anarchy of the new bin packing game is ,t. cheng,Not available,2018.0,10.1007/s10878-017-0201-6,Journal of Combinatorial Optimization,Q.2018,False,,Springer,Not available,Bin packing game with a price of anarchy of ,28065c382f0bd8af770924056bfea4a6,http://dx.doi.org/10.1007/s10878-017-0201-6
527,We consider the bin packing problem in the non-cooperative game setting. In the game there are a set of items with sizes between 0 and 1 and a number of bins each with a capacity of 1. Each item seeks to be packed in one of the bins so as to minimize its cost (payoff). The social cost is the number of bins used in the packing. Existing research has focused on three bin packing games with selfish items  namely the Unit game  the Proportional game  and the General Weight game  each of which uses a unique payoff rule. In this paper we propose a new bin packing game in which the payoff of an item is a function of its own size and the size of the maximum item in the same bin. We find that the new payoff rule induces the items to reach a better Nash equilibrium. We show that the price of anarchy of the new bin packing game is ,q. fang,Not available,2018.0,10.1007/s10878-017-0201-6,Journal of Combinatorial Optimization,Q.2018,False,,Springer,Not available,Bin packing game with a price of anarchy of ,28065c382f0bd8af770924056bfea4a6,http://dx.doi.org/10.1007/s10878-017-0201-6
528,Pricing plays a central rule to a company’s profitability  and therefore has been extensively studied in the literature of economics. When designing a pricing mechanism/ model  an important principle to consider is “price discrimination”  which refers to selling the same resources with different prices according to different values of buyers. To meet the “price discrimination” principle  especially when the number of buyers is large  computational methods  which act in a more accurate and principled way  are usually needed to determine the optimal allocation of sellers’ resources (,fei tian,Not available,2018.0,10.1007/s11704-017-6005-0,Frontiers of Computer Science,Fei2018,False,,Springer,Not available,Computational pricing in Internet era,d76995e376a077d380108ee6ce23c027,http://dx.doi.org/10.1007/s11704-017-6005-0
529,Pricing plays a central rule to a company’s profitability  and therefore has been extensively studied in the literature of economics. When designing a pricing mechanism/ model  an important principle to consider is “price discrimination”  which refers to selling the same resources with different prices according to different values of buyers. To meet the “price discrimination” principle  especially when the number of buyers is large  computational methods  which act in a more accurate and principled way  are usually needed to determine the optimal allocation of sellers’ resources (,tao qin,Not available,2018.0,10.1007/s11704-017-6005-0,Frontiers of Computer Science,Fei2018,False,,Springer,Not available,Computational pricing in Internet era,d76995e376a077d380108ee6ce23c027,http://dx.doi.org/10.1007/s11704-017-6005-0
530,Pricing plays a central rule to a company’s profitability  and therefore has been extensively studied in the literature of economics. When designing a pricing mechanism/ model  an important principle to consider is “price discrimination”  which refers to selling the same resources with different prices according to different values of buyers. To meet the “price discrimination” principle  especially when the number of buyers is large  computational methods  which act in a more accurate and principled way  are usually needed to determine the optimal allocation of sellers’ resources (,tie-yan liu,Not available,2018.0,10.1007/s11704-017-6005-0,Frontiers of Computer Science,Fei2018,False,,Springer,Not available,Computational pricing in Internet era,d76995e376a077d380108ee6ce23c027,http://dx.doi.org/10.1007/s11704-017-6005-0
531,We consider nonatomic routing games with one source and one destination connected by multiple parallel edges. We examine the asymptotic behavior of the price of anarchy as the inflow increases. In accordance with some empirical observations  we prove that under suitable conditions on the costs the price of anarchy is asymptotic to one. We show with some counterexamples that this is not always the case  and that these counterexamples already occur in simple networks with only 2 parallel links.,riccardo colini-baldeschi,Not available,2018.0,10.1007/s00224-017-9834-1,Theory of Computing Systems,Riccardo2018,False,,Springer,Not available,Price of Anarchy for Highly Congested Routing Games in Parallel Networks,4616b27e20dd04e8e2a90385909df9e4,http://dx.doi.org/10.1007/s00224-017-9834-1
532,We consider nonatomic routing games with one source and one destination connected by multiple parallel edges. We examine the asymptotic behavior of the price of anarchy as the inflow increases. In accordance with some empirical observations  we prove that under suitable conditions on the costs the price of anarchy is asymptotic to one. We show with some counterexamples that this is not always the case  and that these counterexamples already occur in simple networks with only 2 parallel links.,roberto cominetti,Not available,2018.0,10.1007/s00224-017-9834-1,Theory of Computing Systems,Riccardo2018,False,,Springer,Not available,Price of Anarchy for Highly Congested Routing Games in Parallel Networks,4616b27e20dd04e8e2a90385909df9e4,http://dx.doi.org/10.1007/s00224-017-9834-1
533,We consider nonatomic routing games with one source and one destination connected by multiple parallel edges. We examine the asymptotic behavior of the price of anarchy as the inflow increases. In accordance with some empirical observations  we prove that under suitable conditions on the costs the price of anarchy is asymptotic to one. We show with some counterexamples that this is not always the case  and that these counterexamples already occur in simple networks with only 2 parallel links.,marco scarsini,Not available,2018.0,10.1007/s00224-017-9834-1,Theory of Computing Systems,Riccardo2018,False,,Springer,Not available,Price of Anarchy for Highly Congested Routing Games in Parallel Networks,4616b27e20dd04e8e2a90385909df9e4,http://dx.doi.org/10.1007/s00224-017-9834-1
534,We consider a multi-agent planning problem as a set of activities that has to be planned by several autonomous agents. In general  due to the possible dependencies between the agents’ activities or interactions during execution of those activities  allowing agents to plan individually may lead to a very inefficient or even infeasible solution to the multi-agent planning problem. This is exactly where ,cees witteveen,Not available,2010.0,10.1007/s10458-009-9086-9,Autonomous Agents and Multi-Agent Systems,Adriaan2010,True,,Springer,Not available,Coordination by design and the price of autonomy,f713f0c33e68effd115a15688a8987e8,http://dx.doi.org/10.1007/s10458-009-9086-9
535,We consider the atomic version of congestion games with affine cost functions  and analyze the quality of worst case Nash equilibria when the strategy spaces of the players are the set of bases of a ,jasper jong,Not available,2018.0,10.1007/978-3-319-89441-6_23,Approximation and Online Algorithms,Jasper2018,False,,Springer,Not available,The Asymptotic Price of Anarchy for ,00618f82c04fd214aaeab77c1c407304,http://dx.doi.org/10.1007/978-3-319-89441-6_23
536,We consider the atomic version of congestion games with affine cost functions  and analyze the quality of worst case Nash equilibria when the strategy spaces of the players are the set of bases of a ,walter kern,Not available,2018.0,10.1007/978-3-319-89441-6_23,Approximation and Online Algorithms,Jasper2018,False,,Springer,Not available,The Asymptotic Price of Anarchy for ,00618f82c04fd214aaeab77c1c407304,http://dx.doi.org/10.1007/978-3-319-89441-6_23
537,We consider the atomic version of congestion games with affine cost functions  and analyze the quality of worst case Nash equilibria when the strategy spaces of the players are the set of bases of a ,berend steenhuisen,Not available,2018.0,10.1007/978-3-319-89441-6_23,Approximation and Online Algorithms,Jasper2018,False,,Springer,Not available,The Asymptotic Price of Anarchy for ,00618f82c04fd214aaeab77c1c407304,http://dx.doi.org/10.1007/978-3-319-89441-6_23
538,We consider the atomic version of congestion games with affine cost functions  and analyze the quality of worst case Nash equilibria when the strategy spaces of the players are the set of bases of a ,marc uetz,Not available,2018.0,10.1007/978-3-319-89441-6_23,Approximation and Online Algorithms,Jasper2018,False,,Springer,Not available,The Asymptotic Price of Anarchy for ,00618f82c04fd214aaeab77c1c407304,http://dx.doi.org/10.1007/978-3-319-89441-6_23
539,The Price of Anarchy in congestion games has attracted a lot of research over the last decade. This resulted in a thorough understanding of this concept. In contrast the Price of Stability  which is an equally interesting concept  is much less understood.In this paper  we consider congestion games with polynomial cost functions with nonnegative coefficients and maximum degree ,george christodoulou,Not available,2013.0,10.1007/978-3-642-39212-2_44,Automata  Languages  and Programming,George2013,False,,Springer,Not available,Price of Stability in Polynomial Congestion Games,25fe27d8ddc48e48066c2cb0f7072c58,http://dx.doi.org/10.1007/978-3-642-39212-2_44
540,The Price of Anarchy in congestion games has attracted a lot of research over the last decade. This resulted in a thorough understanding of this concept. In contrast the Price of Stability  which is an equally interesting concept  is much less understood.In this paper  we consider congestion games with polynomial cost functions with nonnegative coefficients and maximum degree ,martin gairing,Not available,2013.0,10.1007/978-3-642-39212-2_44,Automata  Languages  and Programming,George2013,False,,Springer,Not available,Price of Stability in Polynomial Congestion Games,25fe27d8ddc48e48066c2cb0f7072c58,http://dx.doi.org/10.1007/978-3-642-39212-2_44
541,We consider the proportional allocation mechanism first studied by Kelly (1997) in the context of congestion control algorithms for communication networks. A single infinitely divisible resource is to be allocated efficiently to competing players whose individual utility functions are unknown to the resource manager. If players anticipate the effect of their bids on the price of the resource and their utility functions are concave  strictly increasing and continuously differentiable  Johari and Tsitsiklis (2004) proved that the price of anarchy is 4/3. The question was raised whether there is a relationship between this result and that of Roughgarden and Tardos (2002)  who had earlier shown exactly the same bound for nonatomic selfish routing with affine-linear congestion functions. We establish such a relationship and show  in particular  that the efficiency loss can be characterized by precisely the same geometric quantity. We also present a new variational inequality characterization of Nash equilibria in this setting  which enables us to extend the price-of-anarchy analysis to important classes of utility functions that are not necessarily concave.,jose correa,Not available,2013.0,10.1007/978-3-642-45046-4_10,Web and Internet Economics,R.2013,False,,Springer,Not available,The Price of Anarchy of the Proportional Allocation Mechanism Revisited,8de5069506ca7abf3ba0f8d56cde9585,http://dx.doi.org/10.1007/978-3-642-45046-4_10
542,We consider the proportional allocation mechanism first studied by Kelly (1997) in the context of congestion control algorithms for communication networks. A single infinitely divisible resource is to be allocated efficiently to competing players whose individual utility functions are unknown to the resource manager. If players anticipate the effect of their bids on the price of the resource and their utility functions are concave  strictly increasing and continuously differentiable  Johari and Tsitsiklis (2004) proved that the price of anarchy is 4/3. The question was raised whether there is a relationship between this result and that of Roughgarden and Tardos (2002)  who had earlier shown exactly the same bound for nonatomic selfish routing with affine-linear congestion functions. We establish such a relationship and show  in particular  that the efficiency loss can be characterized by precisely the same geometric quantity. We also present a new variational inequality characterization of Nash equilibria in this setting  which enables us to extend the price-of-anarchy analysis to important classes of utility functions that are not necessarily concave.,andreas schulz,Not available,2013.0,10.1007/978-3-642-45046-4_10,Web and Internet Economics,R.2013,False,,Springer,Not available,The Price of Anarchy of the Proportional Allocation Mechanism Revisited,8de5069506ca7abf3ba0f8d56cde9585,http://dx.doi.org/10.1007/978-3-642-45046-4_10
543,We consider the proportional allocation mechanism first studied by Kelly (1997) in the context of congestion control algorithms for communication networks. A single infinitely divisible resource is to be allocated efficiently to competing players whose individual utility functions are unknown to the resource manager. If players anticipate the effect of their bids on the price of the resource and their utility functions are concave  strictly increasing and continuously differentiable  Johari and Tsitsiklis (2004) proved that the price of anarchy is 4/3. The question was raised whether there is a relationship between this result and that of Roughgarden and Tardos (2002)  who had earlier shown exactly the same bound for nonatomic selfish routing with affine-linear congestion functions. We establish such a relationship and show  in particular  that the efficiency loss can be characterized by precisely the same geometric quantity. We also present a new variational inequality characterization of Nash equilibria in this setting  which enables us to extend the price-of-anarchy analysis to important classes of utility functions that are not necessarily concave.,nicolas stier-moses,Not available,2013.0,10.1007/978-3-642-45046-4_10,Web and Internet Economics,R.2013,False,,Springer,Not available,The Price of Anarchy of the Proportional Allocation Mechanism Revisited,8de5069506ca7abf3ba0f8d56cde9585,http://dx.doi.org/10.1007/978-3-642-45046-4_10
544,We study the Price of Anarchy (PoA) of the competitive cascade game following the framework proposed by Goyal and Kearns in [11]. Our main insight is that a reduction to a Linear Threshold Model in a time-expanded graph establishes the submodularity of the social utility function. From this observation  we deduce that the game is a valid utility game  which in turn implies an upper bound of 2 on the (coarse) PoA. This cleaner understanding of the model yields a simpler proof of a much more general result than that established by Goyal and Kearns: for the ,xinran he,Not available,2013.0,10.1007/978-3-642-45046-4_20,Web and Internet Economics,Xinran2013,False,,Springer,Not available,Price of Anarchy for the ,a424a10c12b175f7eec2a2d2ecdc92b7,http://dx.doi.org/10.1007/978-3-642-45046-4_20
545,We consider a multi-agent planning problem as a set of activities that has to be planned by several autonomous agents. In general  due to the possible dependencies between the agents’ activities or interactions during execution of those activities  allowing agents to plan individually may lead to a very inefficient or even infeasible solution to the multi-agent planning problem. This is exactly where ,yingqian zhang,Not available,2010.0,10.1007/s10458-009-9086-9,Autonomous Agents and Multi-Agent Systems,Adriaan2010,True,,Springer,Not available,Coordination by design and the price of autonomy,f713f0c33e68effd115a15688a8987e8,http://dx.doi.org/10.1007/s10458-009-9086-9
546,We study the Price of Anarchy (PoA) of the competitive cascade game following the framework proposed by Goyal and Kearns in [11]. Our main insight is that a reduction to a Linear Threshold Model in a time-expanded graph establishes the submodularity of the social utility function. From this observation  we deduce that the game is a valid utility game  which in turn implies an upper bound of 2 on the (coarse) PoA. This cleaner understanding of the model yields a simpler proof of a much more general result than that established by Goyal and Kearns: for the ,david kempe,Not available,2013.0,10.1007/978-3-642-45046-4_20,Web and Internet Economics,Xinran2013,False,,Springer,Not available,Price of Anarchy for the ,a424a10c12b175f7eec2a2d2ecdc92b7,http://dx.doi.org/10.1007/978-3-642-45046-4_20
547,We study the performance of Subgame Perfect Equilibria  a solution concept which better captures the players’ rationality in sequential games with respect to the classical myopic dynamics based on the notions of improving deviations and Nash Equilibria  in the context of sequential isolation games. In particular  for two important classes of sequential isolation games  we show upper and lower bounds on the Sequential Price of Anarchy  that is the worst-case ratio between the social performance of an optimal solution and that of a Subgame Perfect Equilibrium  under the two classical social functions mostly investigated in the scientific literature  namely  the minimum utility per player and the sum of the players’ utilities.,anna angelucci,Not available,2013.0,10.1007/978-3-642-38768-5_4,Computing and Combinatorics,Anna2013,False,,Springer,Not available,On the Sequential Price of Anarchy of Isolation Games,806792f212667c3ba558f3c159102734,http://dx.doi.org/10.1007/978-3-642-38768-5_4
548,We study the performance of Subgame Perfect Equilibria  a solution concept which better captures the players’ rationality in sequential games with respect to the classical myopic dynamics based on the notions of improving deviations and Nash Equilibria  in the context of sequential isolation games. In particular  for two important classes of sequential isolation games  we show upper and lower bounds on the Sequential Price of Anarchy  that is the worst-case ratio between the social performance of an optimal solution and that of a Subgame Perfect Equilibrium  under the two classical social functions mostly investigated in the scientific literature  namely  the minimum utility per player and the sum of the players’ utilities.,vittorio bilo,Not available,2013.0,10.1007/978-3-642-38768-5_4,Computing and Combinatorics,Anna2013,False,,Springer,Not available,On the Sequential Price of Anarchy of Isolation Games,806792f212667c3ba558f3c159102734,http://dx.doi.org/10.1007/978-3-642-38768-5_4
549,We study the performance of Subgame Perfect Equilibria  a solution concept which better captures the players’ rationality in sequential games with respect to the classical myopic dynamics based on the notions of improving deviations and Nash Equilibria  in the context of sequential isolation games. In particular  for two important classes of sequential isolation games  we show upper and lower bounds on the Sequential Price of Anarchy  that is the worst-case ratio between the social performance of an optimal solution and that of a Subgame Perfect Equilibrium  under the two classical social functions mostly investigated in the scientific literature  namely  the minimum utility per player and the sum of the players’ utilities.,michele flammini,Not available,2013.0,10.1007/978-3-642-38768-5_4,Computing and Combinatorics,Anna2013,False,,Springer,Not available,On the Sequential Price of Anarchy of Isolation Games,806792f212667c3ba558f3c159102734,http://dx.doi.org/10.1007/978-3-642-38768-5_4
550,We study the performance of Subgame Perfect Equilibria  a solution concept which better captures the players’ rationality in sequential games with respect to the classical myopic dynamics based on the notions of improving deviations and Nash Equilibria  in the context of sequential isolation games. In particular  for two important classes of sequential isolation games  we show upper and lower bounds on the Sequential Price of Anarchy  that is the worst-case ratio between the social performance of an optimal solution and that of a Subgame Perfect Equilibrium  under the two classical social functions mostly investigated in the scientific literature  namely  the minimum utility per player and the sum of the players’ utilities.,luca moscardelli,Not available,2013.0,10.1007/978-3-642-38768-5_4,Computing and Combinatorics,Anna2013,False,,Springer,Not available,On the Sequential Price of Anarchy of Isolation Games,806792f212667c3ba558f3c159102734,http://dx.doi.org/10.1007/978-3-642-38768-5_4
551,In this paper we show that the price of stability of Shapley network design games on undirected graphs with ,yann disser,Not available,2013.0,10.1007/978-3-642-38233-8_14,Algorithms and Complexity,Yann2013,False,,Springer,Not available,Improving the ,0e4d0d3699d5f568fde88f6a68005b45,http://dx.doi.org/10.1007/978-3-642-38233-8_14
552,In this paper we show that the price of stability of Shapley network design games on undirected graphs with ,andreas feldmann,Not available,2013.0,10.1007/978-3-642-38233-8_14,Algorithms and Complexity,Yann2013,False,,Springer,Not available,Improving the ,0e4d0d3699d5f568fde88f6a68005b45,http://dx.doi.org/10.1007/978-3-642-38233-8_14
553,In this paper we show that the price of stability of Shapley network design games on undirected graphs with ,max klimm,Not available,2013.0,10.1007/978-3-642-38233-8_14,Algorithms and Complexity,Yann2013,False,,Springer,Not available,Improving the ,0e4d0d3699d5f568fde88f6a68005b45,http://dx.doi.org/10.1007/978-3-642-38233-8_14
554,In this paper we show that the price of stability of Shapley network design games on undirected graphs with ,matus mihalak,Not available,2013.0,10.1007/978-3-642-38233-8_14,Algorithms and Complexity,Yann2013,False,,Springer,Not available,Improving the ,0e4d0d3699d5f568fde88f6a68005b45,http://dx.doi.org/10.1007/978-3-642-38233-8_14
555,This paper studies a two-stage game with a manufacturer and a subcontractor who are faced by a production scheduling problem. The manufacturer has a set of jobs to process  a subset of which can be subcontracted to the subcontractor to reduce the tardiness cost. In the game  the subcontractor makes the first decision to ask for a unit price of his machine time to be used by the manufacturer  and then the manufacturer follows to decide which jobs to be subcontracted to process and how the production scheduling is made. We analyze the game and derive how the subcontractor can optimize the unit price to maximize his profit. We then investigate the performance of such a simple contract from the viewpoint of coordination  and propose two other contracts that can achieve coordination between the two players.,xiangtong qi,Not available,2012.0,10.1007/s10951-012-0273-1,Journal of Scheduling,Xiangtong2012,False,,Springer,Not available,Production scheduling with subcontracting: the subcontractor’s pricing game,25dcec3a107fca1ef8b79a5024c7437c,http://dx.doi.org/10.1007/s10951-012-0273-1
556,As defined by Aumann in 1959  a strong equilibrium is a Nash equilibrium that is resilient to deviations by coalitions. We give tight bounds on the strong price of anarchy for load balancing on related machines. We also give tight bounds for ,svetlana olonetsky,Not available,2007.0,10.1007/978-3-540-73420-8_51,Automata  Languages and Programming,Amos2007,False,,Springer,Not available,Strong Price of Anarchy for Machine Load Balancing,e62a88eac6ef598fa8bf2eb73a687dae,http://dx.doi.org/10.1007/978-3-540-73420-8_51
557,We study selfish routing in ring networks with respect to minimizing the maximum latency. Our main result is an establishment of constant bounds on the price of stability (PoS) for routing unsplittable flows with linear latency. We show that the PoS is at most 6.83  which reduces to 4.57 when the linear latency functions are homogeneous. We also show the existence of a (54 1)-approximate Nash equilibrium. Additionally we address some algorithmic issues for computing an approximate Nash equilibrium.,bo chen,Not available,2010.0,10.1007/s10878-008-9171-z,Journal of Combinatorial Optimization,Bo2010,False,,Springer,Not available,The price of atomic selfish ring routing,4ba89cca52e9517e1a6e09a4ad435035,http://dx.doi.org/10.1007/s10878-008-9171-z
558,In this paper  we use the variational method to study the efficiency loss of user equilibrium for the multi-class  multi-criterion traffic equilibrium with general tolls and a discrete set of value of time. By introducing three important parameters ters ,kedong chen,Not available,2012.0,10.1007/s11518-011-5175-9,Journal of Systems Science and Systems Engineering,Kedong2012,False,,Springer,Not available,The bound of price of anarchy for multi-class and multi-criteria traffic equilibrium problem,7b2d7e23997f29aa5c367cc7bf253b2d,http://dx.doi.org/10.1007/s11518-011-5175-9
559,In this paper  we use the variational method to study the efficiency loss of user equilibrium for the multi-class  multi-criterion traffic equilibrium with general tolls and a discrete set of value of time. By introducing three important parameters ters ,daoli zhu,Not available,2012.0,10.1007/s11518-011-5175-9,Journal of Systems Science and Systems Engineering,Kedong2012,False,,Springer,Not available,The bound of price of anarchy for multi-class and multi-criteria traffic equilibrium problem,7b2d7e23997f29aa5c367cc7bf253b2d,http://dx.doi.org/10.1007/s11518-011-5175-9
560,In this paper  we use the variational method to study the efficiency loss of user equilibrium for the multi-class  multi-criterion traffic equilibrium with general tolls and a discrete set of value of time. By introducing three important parameters ters ,yihong hu,Not available,2012.0,10.1007/s11518-011-5175-9,Journal of Systems Science and Systems Engineering,Kedong2012,False,,Springer,Not available,The bound of price of anarchy for multi-class and multi-criteria traffic equilibrium problem,7b2d7e23997f29aa5c367cc7bf253b2d,http://dx.doi.org/10.1007/s11518-011-5175-9
561,In this paper  we use the variational method to study the efficiency loss of user equilibrium for the multi-class  multi-criterion traffic equilibrium with general tolls and a discrete set of value of time. By introducing three important parameters ters ,jianlin liu,Not available,2012.0,10.1007/s11518-011-5175-9,Journal of Systems Science and Systems Engineering,Kedong2012,False,,Springer,Not available,The bound of price of anarchy for multi-class and multi-criteria traffic equilibrium problem,7b2d7e23997f29aa5c367cc7bf253b2d,http://dx.doi.org/10.1007/s11518-011-5175-9
562,We study the design of price mechanisms for communication network problems in which a user’s utility depends on the amount of flow she sends through the network  and the congestion on each link depends on the total traffic flows over it. The price mechanisms are characterized by a set of axioms that have been adopted in the cost-sharing games  and we search for the price mechanisms that provide the minimum price of anarchy. We show that  given the non-decreasing and concave utilities of users and the convex quadratic congestion costs in each link  if the price mechanism cannot depend on utility functions  the best achievable price of anarchy is ,ying-ju chen,Not available,2012.0,10.1007/s10107-010-0379-1,Mathematical Programming,Ying-Ju2012,True,,Springer,Not available,Design of price mechanisms for network resource allocation via price of anarchy,ddf9aef29651f3494905b9f14d3eefd1,http://dx.doi.org/10.1007/s10107-010-0379-1
563,We study the design of price mechanisms for communication network problems in which a user’s utility depends on the amount of flow she sends through the network  and the congestion on each link depends on the total traffic flows over it. The price mechanisms are characterized by a set of axioms that have been adopted in the cost-sharing games  and we search for the price mechanisms that provide the minimum price of anarchy. We show that  given the non-decreasing and concave utilities of users and the convex quadratic congestion costs in each link  if the price mechanism cannot depend on utility functions  the best achievable price of anarchy is ,jiawei zhang,Not available,2012.0,10.1007/s10107-010-0379-1,Mathematical Programming,Ying-Ju2012,True,,Springer,Not available,Design of price mechanisms for network resource allocation via price of anarchy,ddf9aef29651f3494905b9f14d3eefd1,http://dx.doi.org/10.1007/s10107-010-0379-1
564,We introduce ,rajgopal kannan,Not available,2012.0,10.1007/978-3-642-30373-9_22,Game Theory for Networks,Rajgopal2012,False,,Springer,Not available,Optimal Price of Anarchy of Polynomial and Super-Polynomial Bottleneck Congestion Games,fa69c22f9054b6e8daae9c7ffa34a9d5,http://dx.doi.org/10.1007/978-3-642-30373-9_22
565,We introduce ,costas busch,Not available,2012.0,10.1007/978-3-642-30373-9_22,Game Theory for Networks,Rajgopal2012,False,,Springer,Not available,Optimal Price of Anarchy of Polynomial and Super-Polynomial Bottleneck Congestion Games,fa69c22f9054b6e8daae9c7ffa34a9d5,http://dx.doi.org/10.1007/978-3-642-30373-9_22
566,We introduce ,athanasios vasilakos,Not available,2012.0,10.1007/978-3-642-30373-9_22,Game Theory for Networks,Rajgopal2012,False,,Springer,Not available,Optimal Price of Anarchy of Polynomial and Super-Polynomial Bottleneck Congestion Games,fa69c22f9054b6e8daae9c7ffa34a9d5,http://dx.doi.org/10.1007/978-3-642-30373-9_22
567,We design a new class of vertex and set cover games  where the price of anarchy bounds match the best known constant factor approximation guarantees for the centralized optimization problems for linear and also for submodular costs. This is in contrast to all previously studied covering games  where the price of anarchy grows linearly with the size of the game. Both the game design and the price of anarchy results are based on structural properties of the linear programming relaxations. For linear costs we also exhibit simple best-response dynamics that converge to Nash equilibria in linear time.,georgios piliouras,Not available,2012.0,10.1007/978-3-642-35311-6_14,Internet and Network Economics,Georgios2012,False,,Springer,Not available,LP-Based Covering Games with Low Price of Anarchy,99247187da72b287a1b1393c8707615c,http://dx.doi.org/10.1007/978-3-642-35311-6_14
568,We study selfish routing in ring networks with respect to minimizing the maximum latency. Our main result is an establishment of constant bounds on the price of stability (PoS) for routing unsplittable flows with linear latency. We show that the PoS is at most 6.83  which reduces to 4.57 when the linear latency functions are homogeneous. We also show the existence of a (54 1)-approximate Nash equilibrium. Additionally we address some algorithmic issues for computing an approximate Nash equilibrium.,xujin chen,Not available,2010.0,10.1007/s10878-008-9171-z,Journal of Combinatorial Optimization,Bo2010,False,,Springer,Not available,The price of atomic selfish ring routing,4ba89cca52e9517e1a6e09a4ad435035,http://dx.doi.org/10.1007/s10878-008-9171-z
569,We design a new class of vertex and set cover games  where the price of anarchy bounds match the best known constant factor approximation guarantees for the centralized optimization problems for linear and also for submodular costs. This is in contrast to all previously studied covering games  where the price of anarchy grows linearly with the size of the game. Both the game design and the price of anarchy results are based on structural properties of the linear programming relaxations. For linear costs we also exhibit simple best-response dynamics that converge to Nash equilibria in linear time.,tomas valla,Not available,2012.0,10.1007/978-3-642-35311-6_14,Internet and Network Economics,Georgios2012,False,,Springer,Not available,LP-Based Covering Games with Low Price of Anarchy,99247187da72b287a1b1393c8707615c,http://dx.doi.org/10.1007/978-3-642-35311-6_14
570,We design a new class of vertex and set cover games  where the price of anarchy bounds match the best known constant factor approximation guarantees for the centralized optimization problems for linear and also for submodular costs. This is in contrast to all previously studied covering games  where the price of anarchy grows linearly with the size of the game. Both the game design and the price of anarchy results are based on structural properties of the linear programming relaxations. For linear costs we also exhibit simple best-response dynamics that converge to Nash equilibria in linear time.,laszlo vegh,Not available,2012.0,10.1007/978-3-642-35311-6_14,Internet and Network Economics,Georgios2012,False,,Springer,Not available,LP-Based Covering Games with Low Price of Anarchy,99247187da72b287a1b1393c8707615c,http://dx.doi.org/10.1007/978-3-642-35311-6_14
571,We examine how to induce selfish heterogeneous users in a multicommodity network to reach an equilibrium that minimizes the social cost. In the absence of centralized coordination  we use the classical method of imposing appropriate taxes (tolls) on the edges of the network. We significantly generalize previous work (Yang and Huang in Transp. Res. Part B 38:1–15  [,george karakostas,Not available,2009.0,10.1007/s00453-008-9181-3,Algorithmica,George2009,False,,Springer,Not available,Edge Pricing of Multicommodity Networks for Selfish Users with Elastic Demands,2f8d57f929337aab3a1e744abf3fc6a1,http://dx.doi.org/10.1007/s00453-008-9181-3
572,We examine how to induce selfish heterogeneous users in a multicommodity network to reach an equilibrium that minimizes the social cost. In the absence of centralized coordination  we use the classical method of imposing appropriate taxes (tolls) on the edges of the network. We significantly generalize previous work (Yang and Huang in Transp. Res. Part B 38:1–15  [,stavros kolliopoulos,Not available,2009.0,10.1007/s00453-008-9181-3,Algorithmica,George2009,False,,Springer,Not available,Edge Pricing of Multicommodity Networks for Selfish Users with Elastic Demands,2f8d57f929337aab3a1e744abf3fc6a1,http://dx.doi.org/10.1007/s00453-008-9181-3
573,"
A natural generalization of the selfish routing setting arises when some of the users obey a central coordinating authority  while the rest act selfishly. Such behavior can be modeled by dividing the users into an ",george karakostas,Not available,2009.0,10.1007/s00453-007-9018-5,Algorithmica,George2009,False,,Springer,Not available,Stackelberg Strategies for Selfish Routing in General Multicommodity Networks,af02b35ee57d11cca8f944d14d8caf21,http://dx.doi.org/10.1007/s00453-007-9018-5
574,"
A natural generalization of the selfish routing setting arises when some of the users obey a central coordinating authority  while the rest act selfishly. Such behavior can be modeled by dividing the users into an ",stavros kolliopoulos,Not available,2009.0,10.1007/s00453-007-9018-5,Algorithmica,George2009,False,,Springer,Not available,Stackelberg Strategies for Selfish Routing in General Multicommodity Networks,af02b35ee57d11cca8f944d14d8caf21,http://dx.doi.org/10.1007/s00453-007-9018-5
575,We give an overview of important results for non-atomic congestion games in their traditional form along with self-contained and short proofs and then present new results and challenges for an extended model  which we call ,lasse kliemann,Not available,2009.0,10.1007/978-3-642-02094-0_14,Algorithmics of Large and Complex Networks,Lasse2009,False,,Springer,Not available,Models of Non-atomic Congestion Games – From Unicast to Multicast Routing,b0336fa02e4c182ec7ed6d80ba92f49d,http://dx.doi.org/10.1007/978-3-642-02094-0_14
576,We give an overview of important results for non-atomic congestion games in their traditional form along with self-contained and short proofs and then present new results and challenges for an extended model  which we call ,anand srivastav,Not available,2009.0,10.1007/978-3-642-02094-0_14,Algorithmics of Large and Complex Networks,Lasse2009,False,,Springer,Not available,Models of Non-atomic Congestion Games – From Unicast to Multicast Routing,b0336fa02e4c182ec7ed6d80ba92f49d,http://dx.doi.org/10.1007/978-3-642-02094-0_14
577,"
In this paper we consider the ",martin hoefer,Not available,2009.0,10.1007/s00453-007-9014-9,Algorithmica,Martin2009,False,,Springer,Not available,Non-Cooperative Tree Creation,40f9a4536d543c2057bf27a213aec95c,http://dx.doi.org/10.1007/s00453-007-9014-9
578,Previous works on the inefficiency of selfish routing have focused on the Wardropian traffic equilibria with an infinite number of infinitesimal players  each controlling a negligible fraction of the overall traffic  but only very limited pseudo-approximation results have been obtained for the atomic selfish routing game with a finite number of players. In this note we examine the price of anarchy of selfish routing with atomic Cournot–Nash players  each controlling a strictly positive splittable amount of flow. We obtain an upper bound of the inefficiency of equilibria with polynomial cost functions  and show that the bound is 1 or there is no efficiency loss when there is only one player  and the bound reduces to the result established in the literature when there are an infinite number of infinitesimal players.,hai yang,Not available,2008.0,10.1007/s11067-007-9017-8,Networks and Spatial Economics,Hai2008,False,,Springer,Not available,Efficiency of Atomic Splittable Selfish Routing with Polynomial Cost Functions,0b33982d72615b09038623aadc2957aa,http://dx.doi.org/10.1007/s11067-007-9017-8
579,We study selfish routing in ring networks with respect to minimizing the maximum latency. Our main result is an establishment of constant bounds on the price of stability (PoS) for routing unsplittable flows with linear latency. We show that the PoS is at most 6.83  which reduces to 4.57 when the linear latency functions are homogeneous. We also show the existence of a (54 1)-approximate Nash equilibrium. Additionally we address some algorithmic issues for computing an approximate Nash equilibrium.,xiaodong hu,Not available,2010.0,10.1007/s10878-008-9171-z,Journal of Combinatorial Optimization,Bo2010,False,,Springer,Not available,The price of atomic selfish ring routing,4ba89cca52e9517e1a6e09a4ad435035,http://dx.doi.org/10.1007/s10878-008-9171-z
580,Previous works on the inefficiency of selfish routing have focused on the Wardropian traffic equilibria with an infinite number of infinitesimal players  each controlling a negligible fraction of the overall traffic  but only very limited pseudo-approximation results have been obtained for the atomic selfish routing game with a finite number of players. In this note we examine the price of anarchy of selfish routing with atomic Cournot–Nash players  each controlling a strictly positive splittable amount of flow. We obtain an upper bound of the inefficiency of equilibria with polynomial cost functions  and show that the bound is 1 or there is no efficiency loss when there is only one player  and the bound reduces to the result established in the literature when there are an infinite number of infinitesimal players.,deren han,Not available,2008.0,10.1007/s11067-007-9017-8,Networks and Spatial Economics,Hai2008,False,,Springer,Not available,Efficiency of Atomic Splittable Selfish Routing with Polynomial Cost Functions,0b33982d72615b09038623aadc2957aa,http://dx.doi.org/10.1007/s11067-007-9017-8
581,Previous works on the inefficiency of selfish routing have focused on the Wardropian traffic equilibria with an infinite number of infinitesimal players  each controlling a negligible fraction of the overall traffic  but only very limited pseudo-approximation results have been obtained for the atomic selfish routing game with a finite number of players. In this note we examine the price of anarchy of selfish routing with atomic Cournot–Nash players  each controlling a strictly positive splittable amount of flow. We obtain an upper bound of the inefficiency of equilibria with polynomial cost functions  and show that the bound is 1 or there is no efficiency loss when there is only one player  and the bound reduces to the result established in the literature when there are an infinite number of infinitesimal players.,hong lo,Not available,2008.0,10.1007/s11067-007-9017-8,Networks and Spatial Economics,Hai2008,False,,Springer,Not available,Efficiency of Atomic Splittable Selfish Routing with Polynomial Cost Functions,0b33982d72615b09038623aadc2957aa,http://dx.doi.org/10.1007/s11067-007-9017-8
582,We consider the packet routing problem in store-and-forward networks whose topologies are either paths  trees  or rings. We are interested by the quality of the solution produced  with respect to a global optimal solution  if each link uses a (fixed) local policy to schedule the packets which go through it. The quality of the derived solutions is measured using the worst case analysis for two global optimality criteria  namely the maximum arrival date of a packet at its destination (or makespan) and the average arrival date of the packets at their destinations.We consider the setting where ,eric angel,Not available,2008.0,10.1007/s10951-008-0069-5,Journal of Scheduling,Eric2008,False,,Springer,Not available,The impact of local policies on the quality of packet routing in paths  trees  and rings,45888f86ae16e209bc6a85e4d876baf2,http://dx.doi.org/10.1007/s10951-008-0069-5
583,We consider the packet routing problem in store-and-forward networks whose topologies are either paths  trees  or rings. We are interested by the quality of the solution produced  with respect to a global optimal solution  if each link uses a (fixed) local policy to schedule the packets which go through it. The quality of the derived solutions is measured using the worst case analysis for two global optimality criteria  namely the maximum arrival date of a packet at its destination (or makespan) and the average arrival date of the packets at their destinations.We consider the setting where ,evripidis bampis,Not available,2008.0,10.1007/s10951-008-0069-5,Journal of Scheduling,Eric2008,False,,Springer,Not available,The impact of local policies on the quality of packet routing in paths  trees  and rings,45888f86ae16e209bc6a85e4d876baf2,http://dx.doi.org/10.1007/s10951-008-0069-5
584,We consider the packet routing problem in store-and-forward networks whose topologies are either paths  trees  or rings. We are interested by the quality of the solution produced  with respect to a global optimal solution  if each link uses a (fixed) local policy to schedule the packets which go through it. The quality of the derived solutions is measured using the worst case analysis for two global optimality criteria  namely the maximum arrival date of a packet at its destination (or makespan) and the average arrival date of the packets at their destinations.We consider the setting where ,fanny pascual,Not available,2008.0,10.1007/s10951-008-0069-5,Journal of Scheduling,Eric2008,False,,Springer,Not available,The impact of local policies on the quality of packet routing in paths  trees  and rings,45888f86ae16e209bc6a85e4d876baf2,http://dx.doi.org/10.1007/s10951-008-0069-5
585,"
We propose a simple and intuitive ",marios mavronicolas,Not available,2008.0,10.1007/s00453-007-9108-4,Algorithmica,Marios2008,False,,Springer,Not available,Cost Sharing Mechanisms for Fair Pricing of Resource Usage,961cfe6305f01ac95e0ce64c2456bbb2,http://dx.doi.org/10.1007/s00453-007-9108-4
586,"
We propose a simple and intuitive ",panagiota panagopoulou,Not available,2008.0,10.1007/s00453-007-9108-4,Algorithmica,Marios2008,False,,Springer,Not available,Cost Sharing Mechanisms for Fair Pricing of Resource Usage,961cfe6305f01ac95e0ce64c2456bbb2,http://dx.doi.org/10.1007/s00453-007-9108-4
587,"
We propose a simple and intuitive ",paul spirakis,Not available,2008.0,10.1007/s00453-007-9108-4,Algorithmica,Marios2008,False,,Springer,Not available,Cost Sharing Mechanisms for Fair Pricing of Resource Usage,961cfe6305f01ac95e0ce64c2456bbb2,http://dx.doi.org/10.1007/s00453-007-9108-4
588,We compute the ,herve moulin,Not available,2008.0,10.1007/s00199-007-0275-y,Economic Theory,Hervé2008,False,,Springer,Not available,The price of anarchy of serial  average and incremental cost sharing,69ad78dbc40b338ff6af4416b62ea54c,http://dx.doi.org/10.1007/s00199-007-0275-y
589,We consider a model of game-theoretic network design initially studied by Anshelevich et al. (Proceedings of the 45th Annual Symposium on Foundations of Computer Science (FOCS)  pp. 295–304  ,ho-lin chen,Not available,2008.0,10.1007/s00224-008-9128-8,Theory of Computing Systems,Ho-Lin2008,False,,Springer,Not available,Network Design with Weighted Players,5fa79c4ded99caef1ab5a5c965f76cfa,http://dx.doi.org/10.1007/s00224-008-9128-8
590,We characterize the price of anarchy in weighted congestion games  as a function of the allowable resource cost functions. Our results provide as thorough an understanding of this quantity as is already known for nonatomic and unweighted congestion games  and take the form of universal (cost function-independent) worst-case examples. One noteworthy byproduct of our proofs is the fact that weighted congestion games are “tight”  which implies that the worst-case price of anarchy with respect to pure Nash  mixed Nash  correlated  and coarse correlated equilibria are always equal (under mild conditions on the allowable cost functions). Another is the fact that  like nonatomic but unlike atomic (unweighted) congestion games  weighted congestion games with trivial structure already realize the worst-case POA  at least for polynomial cost functions.We also prove a new result about unweighted congestion games: the worst-case price of anarchy in symmetric games is  as the number of players goes to infinity  as large as in their more general asymmetric counterparts.,kshipra bhawalkar,Not available,2010.0,10.1007/978-3-642-15781-3_2,Algorithms – ESA 2010,Kshipra2010,False,,Springer,Not available,Weighted Congestion Games: Price of Anarchy  Universal Worst-Case Examples  and Tightness,9f11838e22b41e35927993ad2276bbcc,http://dx.doi.org/10.1007/978-3-642-15781-3_2
591,We consider a model of game-theoretic network design initially studied by Anshelevich et al. (Proceedings of the 45th Annual Symposium on Foundations of Computer Science (FOCS)  pp. 295–304  ,tim roughgarden,Not available,2008.0,10.1007/s00224-008-9128-8,Theory of Computing Systems,Ho-Lin2008,False,,Springer,Not available,Network Design with Weighted Players,5fa79c4ded99caef1ab5a5c965f76cfa,http://dx.doi.org/10.1007/s00224-008-9128-8
592,We study a multicast game in ad-hoc wireless networks in which a source sends the same message or service to a set of receiving stations via multi-hop communications and the overall transmission cost is divided among the receivers according to given cost sharing methods. We assume that each receiver gets a certain utility from the transmission and enjoys a benefit equal to the difference between his utility and the shared cost he is asked to pay. Assuming a selfish and rational behavior  each user is willing to receive the transmission if and only if his shared cost does not exceed his utility. Moreover  given the strategies of the other users  he wants to select a strategy of minimum shared cost. A Nash equilibrium is a solution in which no user can increase his benefit by choosing to adopt a different strategy. We consider the following reasonable cost sharing methods: egalitarian  semi-egalitarian next-hop-proportional  path-proportional  egalitarian-path-proportional and Shapley value. We prove that  while the first five cost sharing methods in general do not admit a Nash equilibrium  the Shapley value yields games always converging to a Nash equilibrium. We then turn our attention to the special case in which the receivers’ set ,vittorio bilo,Not available,2008.0,10.1007/s11276-006-8817-y,Wireless Networks,Vittorio2008,False,,Springer,Not available,On Nash equilibria for multicast transmissions in ad-hoc wireless networks,ccc84d355f04366615aa5cefbce25d9d,http://dx.doi.org/10.1007/s11276-006-8817-y
593,We study a multicast game in ad-hoc wireless networks in which a source sends the same message or service to a set of receiving stations via multi-hop communications and the overall transmission cost is divided among the receivers according to given cost sharing methods. We assume that each receiver gets a certain utility from the transmission and enjoys a benefit equal to the difference between his utility and the shared cost he is asked to pay. Assuming a selfish and rational behavior  each user is willing to receive the transmission if and only if his shared cost does not exceed his utility. Moreover  given the strategies of the other users  he wants to select a strategy of minimum shared cost. A Nash equilibrium is a solution in which no user can increase his benefit by choosing to adopt a different strategy. We consider the following reasonable cost sharing methods: egalitarian  semi-egalitarian next-hop-proportional  path-proportional  egalitarian-path-proportional and Shapley value. We prove that  while the first five cost sharing methods in general do not admit a Nash equilibrium  the Shapley value yields games always converging to a Nash equilibrium. We then turn our attention to the special case in which the receivers’ set ,michele flammini,Not available,2008.0,10.1007/s11276-006-8817-y,Wireless Networks,Vittorio2008,False,,Springer,Not available,On Nash equilibria for multicast transmissions in ad-hoc wireless networks,ccc84d355f04366615aa5cefbce25d9d,http://dx.doi.org/10.1007/s11276-006-8817-y
594,We study a multicast game in ad-hoc wireless networks in which a source sends the same message or service to a set of receiving stations via multi-hop communications and the overall transmission cost is divided among the receivers according to given cost sharing methods. We assume that each receiver gets a certain utility from the transmission and enjoys a benefit equal to the difference between his utility and the shared cost he is asked to pay. Assuming a selfish and rational behavior  each user is willing to receive the transmission if and only if his shared cost does not exceed his utility. Moreover  given the strategies of the other users  he wants to select a strategy of minimum shared cost. A Nash equilibrium is a solution in which no user can increase his benefit by choosing to adopt a different strategy. We consider the following reasonable cost sharing methods: egalitarian  semi-egalitarian next-hop-proportional  path-proportional  egalitarian-path-proportional and Shapley value. We prove that  while the first five cost sharing methods in general do not admit a Nash equilibrium  the Shapley value yields games always converging to a Nash equilibrium. We then turn our attention to the special case in which the receivers’ set ,giovanna melideo,Not available,2008.0,10.1007/s11276-006-8817-y,Wireless Networks,Vittorio2008,False,,Springer,Not available,On Nash equilibria for multicast transmissions in ad-hoc wireless networks,ccc84d355f04366615aa5cefbce25d9d,http://dx.doi.org/10.1007/s11276-006-8817-y
595,We study a multicast game in ad-hoc wireless networks in which a source sends the same message or service to a set of receiving stations via multi-hop communications and the overall transmission cost is divided among the receivers according to given cost sharing methods. We assume that each receiver gets a certain utility from the transmission and enjoys a benefit equal to the difference between his utility and the shared cost he is asked to pay. Assuming a selfish and rational behavior  each user is willing to receive the transmission if and only if his shared cost does not exceed his utility. Moreover  given the strategies of the other users  he wants to select a strategy of minimum shared cost. A Nash equilibrium is a solution in which no user can increase his benefit by choosing to adopt a different strategy. We consider the following reasonable cost sharing methods: egalitarian  semi-egalitarian next-hop-proportional  path-proportional  egalitarian-path-proportional and Shapley value. We prove that  while the first five cost sharing methods in general do not admit a Nash equilibrium  the Shapley value yields games always converging to a Nash equilibrium. We then turn our attention to the special case in which the receivers’ set ,luca moscardelli,Not available,2008.0,10.1007/s11276-006-8817-y,Wireless Networks,Vittorio2008,False,,Springer,Not available,On Nash equilibria for multicast transmissions in ad-hoc wireless networks,ccc84d355f04366615aa5cefbce25d9d,http://dx.doi.org/10.1007/s11276-006-8817-y
596,We study ,rajgopal kannan,Not available,2010.0,10.1007/978-3-642-16170-4_20,Algorithmic Game Theory,Rajgopal2010,False,,Springer,Not available,Bottleneck Congestion Games with Logarithmic Price of Anarchy,c7219530a5103e564a0e617a84a7cf87,http://dx.doi.org/10.1007/978-3-642-16170-4_20
597,We study ,costas busch,Not available,2010.0,10.1007/978-3-642-16170-4_20,Algorithmic Game Theory,Rajgopal2010,False,,Springer,Not available,Bottleneck Congestion Games with Logarithmic Price of Anarchy,c7219530a5103e564a0e617a84a7cf87,http://dx.doi.org/10.1007/978-3-642-16170-4_20
598,We show a formal duality between certain equilibrium concepts  including the correlated and coarse correlated equilibrium  and analysis frameworks for proving bounds on the price of anarchy for such concepts. Our first application of this duality is a characterization of the set of distributions over game outcomes to which “smoothness bounds” always apply. This set is a natural and strict generalization of the coarse correlated equilibria of the game. Second  we derive a refined definition of smoothness that is specifically tailored for coarse correlated equilibria and can be used to give improved POA bounds for such equilibria.,uri nadav,Not available,2010.0,10.1007/978-3-642-17572-5_26,Internet and Network Economics,Uri2010,False,,Springer,Not available,The Limits of Smoothness: A Primal-Dual Framework for Price of Anarchy Bounds,8973d69a5cbcbc37f3dfa53a40a264b6,http://dx.doi.org/10.1007/978-3-642-17572-5_26
599,We show a formal duality between certain equilibrium concepts  including the correlated and coarse correlated equilibrium  and analysis frameworks for proving bounds on the price of anarchy for such concepts. Our first application of this duality is a characterization of the set of distributions over game outcomes to which “smoothness bounds” always apply. This set is a natural and strict generalization of the coarse correlated equilibria of the game. Second  we derive a refined definition of smoothness that is specifically tailored for coarse correlated equilibria and can be used to give improved POA bounds for such equilibria.,tim roughgarden,Not available,2010.0,10.1007/978-3-642-17572-5_26,Internet and Network Economics,Uri2010,False,,Springer,Not available,The Limits of Smoothness: A Primal-Dual Framework for Price of Anarchy Bounds,8973d69a5cbcbc37f3dfa53a40a264b6,http://dx.doi.org/10.1007/978-3-642-17572-5_26
600,Network creation games have been studied in many different settings recently. These games are motivated by social networks in which selfish agents want to construct a connection graph among themselves. Each node wants to minimize its average or maximum distance to the others  without paying much to construct the network. Many generalizations have been considered  including non-uniform interests between nodes  general graphs of allowable edges  bounded budget agents  etc. In all of these settings  there is no known constant bound on the price of anarchy. In fact  in many cases  the price of anarchy can be very large  namely  a constant power of the number of agents. This means that we have no control on the behavior of network when agents act selfishly. On the other hand  the price of stability in all these models is constant  which means that there is chance that agents act selfishly and we end up with a reasonable social cost.In this paper  we show how to use an advertising campaign (as introduced in SODA 2009 [2]) to find such efficient equilibria. More formally  we present advertising strategies such that  if an ,erik demaine,Not available,2010.0,10.1007/978-3-642-18009-5_12,Algorithms and Models for the Web-Graph,D.2010,False,,Springer,Not available,Constant Price of Anarchy in Network Creation Games via Public Service Advertising,4ed6429c04f27f429fc8c82aebd74961,http://dx.doi.org/10.1007/978-3-642-18009-5_12
601,We characterize the price of anarchy in weighted congestion games  as a function of the allowable resource cost functions. Our results provide as thorough an understanding of this quantity as is already known for nonatomic and unweighted congestion games  and take the form of universal (cost function-independent) worst-case examples. One noteworthy byproduct of our proofs is the fact that weighted congestion games are “tight”  which implies that the worst-case price of anarchy with respect to pure Nash  mixed Nash  correlated  and coarse correlated equilibria are always equal (under mild conditions on the allowable cost functions). Another is the fact that  like nonatomic but unlike atomic (unweighted) congestion games  weighted congestion games with trivial structure already realize the worst-case POA  at least for polynomial cost functions.We also prove a new result about unweighted congestion games: the worst-case price of anarchy in symmetric games is  as the number of players goes to infinity  as large as in their more general asymmetric counterparts.,martin gairing,Not available,2010.0,10.1007/978-3-642-15781-3_2,Algorithms – ESA 2010,Kshipra2010,False,,Springer,Not available,Weighted Congestion Games: Price of Anarchy  Universal Worst-Case Examples  and Tightness,9f11838e22b41e35927993ad2276bbcc,http://dx.doi.org/10.1007/978-3-642-15781-3_2
602,Network creation games have been studied in many different settings recently. These games are motivated by social networks in which selfish agents want to construct a connection graph among themselves. Each node wants to minimize its average or maximum distance to the others  without paying much to construct the network. Many generalizations have been considered  including non-uniform interests between nodes  general graphs of allowable edges  bounded budget agents  etc. In all of these settings  there is no known constant bound on the price of anarchy. In fact  in many cases  the price of anarchy can be very large  namely  a constant power of the number of agents. This means that we have no control on the behavior of network when agents act selfishly. On the other hand  the price of stability in all these models is constant  which means that there is chance that agents act selfishly and we end up with a reasonable social cost.In this paper  we show how to use an advertising campaign (as introduced in SODA 2009 [2]) to find such efficient equilibria. More formally  we present advertising strategies such that  if an ,morteza zadimoghaddam,Not available,2010.0,10.1007/978-3-642-18009-5_12,Algorithms and Models for the Web-Graph,D.2010,False,,Springer,Not available,Constant Price of Anarchy in Network Creation Games via Public Service Advertising,4ed6429c04f27f429fc8c82aebd74961,http://dx.doi.org/10.1007/978-3-642-18009-5_12
603,We study the quality of equilibrium in atomic splittable routing games. We show that in single-source single-sink games on series-parallel graphs  the ,umang bhaskar,Not available,2010.0,10.1007/978-3-642-13036-6_24,Integer Programming and Combinatorial Optimization,Umang2010,False,,Springer,Not available,The Price of Collusion in Series-Parallel Networks,220d99d65fbba70b24b74a5c353322d2,http://dx.doi.org/10.1007/978-3-642-13036-6_24
604,We study the quality of equilibrium in atomic splittable routing games. We show that in single-source single-sink games on series-parallel graphs  the ,lisa fleischer,Not available,2010.0,10.1007/978-3-642-13036-6_24,Integer Programming and Combinatorial Optimization,Umang2010,False,,Springer,Not available,The Price of Collusion in Series-Parallel Networks,220d99d65fbba70b24b74a5c353322d2,http://dx.doi.org/10.1007/978-3-642-13036-6_24
605,We study the quality of equilibrium in atomic splittable routing games. We show that in single-source single-sink games on series-parallel graphs  the ,chien-chung huang,Not available,2010.0,10.1007/978-3-642-13036-6_24,Integer Programming and Combinatorial Optimization,Umang2010,False,,Springer,Not available,The Price of Collusion in Series-Parallel Networks,220d99d65fbba70b24b74a5c353322d2,http://dx.doi.org/10.1007/978-3-642-13036-6_24
606,Non-cooperative game theory purports that economic agents behave with little regard towards the negative externalities they impose on each other. Such behaviors generally lead to inefficient outcomes where the social welfare is bounded away from its optimal value. However  in practice  self-interested individuals explore the possibility of circumventing such negative externalities by forming coalitions. What sort of coalitions should we expect to arise? How do they affect the social welfare?We study these questions in the setting of Cournot markets  one of the most prevalent models of firm competition. Our model of coalition formation has two dynamic aspects. First  agents choose strategically how to update the current coalition partition. Furthermore  coalitions compete repeatedly between themselves trying to minimize their long-term regret. We prove tight bounds on the social welfare  which are significantly higher than that of the Nash equilibria of the original game. Furthermore  this improvement in performance is robust across different supply-demand curves and depends only on the size of the market.,nicole immorlica,Not available,2010.0,10.1007/978-3-642-17572-5_22,Internet and Network Economics,Nicole2010,False,,Springer,Not available,Coalition Formation and Price of Anarchy in Cournot Oligopolies,8c5bc0b618cd4d6f3702408b87742946,http://dx.doi.org/10.1007/978-3-642-17572-5_22
607,Non-cooperative game theory purports that economic agents behave with little regard towards the negative externalities they impose on each other. Such behaviors generally lead to inefficient outcomes where the social welfare is bounded away from its optimal value. However  in practice  self-interested individuals explore the possibility of circumventing such negative externalities by forming coalitions. What sort of coalitions should we expect to arise? How do they affect the social welfare?We study these questions in the setting of Cournot markets  one of the most prevalent models of firm competition. Our model of coalition formation has two dynamic aspects. First  agents choose strategically how to update the current coalition partition. Furthermore  coalitions compete repeatedly between themselves trying to minimize their long-term regret. We prove tight bounds on the social welfare  which are significantly higher than that of the Nash equilibria of the original game. Furthermore  this improvement in performance is robust across different supply-demand curves and depends only on the size of the market.,evangelos markakis,Not available,2010.0,10.1007/978-3-642-17572-5_22,Internet and Network Economics,Nicole2010,False,,Springer,Not available,Coalition Formation and Price of Anarchy in Cournot Oligopolies,8c5bc0b618cd4d6f3702408b87742946,http://dx.doi.org/10.1007/978-3-642-17572-5_22
608,Non-cooperative game theory purports that economic agents behave with little regard towards the negative externalities they impose on each other. Such behaviors generally lead to inefficient outcomes where the social welfare is bounded away from its optimal value. However  in practice  self-interested individuals explore the possibility of circumventing such negative externalities by forming coalitions. What sort of coalitions should we expect to arise? How do they affect the social welfare?We study these questions in the setting of Cournot markets  one of the most prevalent models of firm competition. Our model of coalition formation has two dynamic aspects. First  agents choose strategically how to update the current coalition partition. Furthermore  coalitions compete repeatedly between themselves trying to minimize their long-term regret. We prove tight bounds on the social welfare  which are significantly higher than that of the Nash equilibria of the original game. Furthermore  this improvement in performance is robust across different supply-demand curves and depends only on the size of the market.,georgios piliouras,Not available,2010.0,10.1007/978-3-642-17572-5_22,Internet and Network Economics,Nicole2010,False,,Springer,Not available,Coalition Formation and Price of Anarchy in Cournot Oligopolies,8c5bc0b618cd4d6f3702408b87742946,http://dx.doi.org/10.1007/978-3-642-17572-5_22
609,We continue the study of the effects of selfish behavior in the network design problem. We provide new bounds for the price of stability for network design with fair cost allocation for undirected graphs. We consider the most general case  for which the best known upper bound is the Harmonic number ,george christodoulou,Not available,2010.0,10.1007/978-3-642-12450-1_8,Approximation and Online Algorithms,George2010,False,,Springer,Not available,On the Price of Stability for Undirected Network Design,7e8a70fa0c9693eeb89328784454c103,http://dx.doi.org/10.1007/978-3-642-12450-1_8
610,We continue the study of the effects of selfish behavior in the network design problem. We provide new bounds for the price of stability for network design with fair cost allocation for undirected graphs. We consider the most general case  for which the best known upper bound is the Harmonic number ,christine chung,Not available,2010.0,10.1007/978-3-642-12450-1_8,Approximation and Online Algorithms,George2010,False,,Springer,Not available,On the Price of Stability for Undirected Network Design,7e8a70fa0c9693eeb89328784454c103,http://dx.doi.org/10.1007/978-3-642-12450-1_8
611,We continue the study of the effects of selfish behavior in the network design problem. We provide new bounds for the price of stability for network design with fair cost allocation for undirected graphs. We consider the most general case  for which the best known upper bound is the Harmonic number ,katrina ligett,Not available,2010.0,10.1007/978-3-642-12450-1_8,Approximation and Online Algorithms,George2010,False,,Springer,Not available,On the Price of Stability for Undirected Network Design,7e8a70fa0c9693eeb89328784454c103,http://dx.doi.org/10.1007/978-3-642-12450-1_8
612,We characterize the price of anarchy in weighted congestion games  as a function of the allowable resource cost functions. Our results provide as thorough an understanding of this quantity as is already known for nonatomic and unweighted congestion games  and take the form of universal (cost function-independent) worst-case examples. One noteworthy byproduct of our proofs is the fact that weighted congestion games are “tight”  which implies that the worst-case price of anarchy with respect to pure Nash  mixed Nash  correlated  and coarse correlated equilibria are always equal (under mild conditions on the allowable cost functions). Another is the fact that  like nonatomic but unlike atomic (unweighted) congestion games  weighted congestion games with trivial structure already realize the worst-case POA  at least for polynomial cost functions.We also prove a new result about unweighted congestion games: the worst-case price of anarchy in symmetric games is  as the number of players goes to infinity  as large as in their more general asymmetric counterparts.,tim roughgarden,Not available,2010.0,10.1007/978-3-642-15781-3_2,Algorithms – ESA 2010,Kshipra2010,False,,Springer,Not available,Weighted Congestion Games: Price of Anarchy  Universal Worst-Case Examples  and Tightness,9f11838e22b41e35927993ad2276bbcc,http://dx.doi.org/10.1007/978-3-642-15781-3_2
613,We continue the study of the effects of selfish behavior in the network design problem. We provide new bounds for the price of stability for network design with fair cost allocation for undirected graphs. We consider the most general case  for which the best known upper bound is the Harmonic number ,evangelia pyrga,Not available,2010.0,10.1007/978-3-642-12450-1_8,Approximation and Online Algorithms,George2010,False,,Springer,Not available,On the Price of Stability for Undirected Network Design,7e8a70fa0c9693eeb89328784454c103,http://dx.doi.org/10.1007/978-3-642-12450-1_8
614,We continue the study of the effects of selfish behavior in the network design problem. We provide new bounds for the price of stability for network design with fair cost allocation for undirected graphs. We consider the most general case  for which the best known upper bound is the Harmonic number ,rob stee,Not available,2010.0,10.1007/978-3-642-12450-1_8,Approximation and Online Algorithms,George2010,False,,Springer,Not available,On the Price of Stability for Undirected Network Design,7e8a70fa0c9693eeb89328784454c103,http://dx.doi.org/10.1007/978-3-642-12450-1_8
615,Bounding the price of stability of undirected network design games with fair cost allocation is a challenging open problem in the Algorithmic Game Theory research agenda. Even though the generalization of such games in directed networks is well understood in terms of the price of stability (it is exactly ,vittorio bilo,Not available,2010.0,10.1007/978-3-642-16170-4_9,Algorithmic Game Theory,Vittorio2010,False,,Springer,Not available,Improved Lower Bounds on the Price of Stability of Undirected Network Design Games,13d3fdd637c2eec181cf44596be3c643,http://dx.doi.org/10.1007/978-3-642-16170-4_9
616,Bounding the price of stability of undirected network design games with fair cost allocation is a challenging open problem in the Algorithmic Game Theory research agenda. Even though the generalization of such games in directed networks is well understood in terms of the price of stability (it is exactly ,ioannis caragiannis,Not available,2010.0,10.1007/978-3-642-16170-4_9,Algorithmic Game Theory,Vittorio2010,False,,Springer,Not available,Improved Lower Bounds on the Price of Stability of Undirected Network Design Games,13d3fdd637c2eec181cf44596be3c643,http://dx.doi.org/10.1007/978-3-642-16170-4_9
617,Bounding the price of stability of undirected network design games with fair cost allocation is a challenging open problem in the Algorithmic Game Theory research agenda. Even though the generalization of such games in directed networks is well understood in terms of the price of stability (it is exactly ,angelo fanelli,Not available,2010.0,10.1007/978-3-642-16170-4_9,Algorithmic Game Theory,Vittorio2010,False,,Springer,Not available,Improved Lower Bounds on the Price of Stability of Undirected Network Design Games,13d3fdd637c2eec181cf44596be3c643,http://dx.doi.org/10.1007/978-3-642-16170-4_9
618,Bounding the price of stability of undirected network design games with fair cost allocation is a challenging open problem in the Algorithmic Game Theory research agenda. Even though the generalization of such games in directed networks is well understood in terms of the price of stability (it is exactly ,gianpiero monaco,Not available,2010.0,10.1007/978-3-642-16170-4_9,Algorithmic Game Theory,Vittorio2010,False,,Springer,Not available,Improved Lower Bounds on the Price of Stability of Undirected Network Design Games,13d3fdd637c2eec181cf44596be3c643,http://dx.doi.org/10.1007/978-3-642-16170-4_9
619,In the realm of information security  lack of information about other users' incentives in a network can lead to inefficient security choices and reductions in individuals' payoffs. We propose  contrast and compare three metrics for measuring the ,jens grossklags,Not available,2010.0,10.1007/978-1-4419-6967-5_2,Economics of Information Security and Privacy,Jens2010,False,,Springer,Not available,The Price of Uncertainty in Security Games,e35e82dbbb9d9c318fbfd58899ea5f11,http://dx.doi.org/10.1007/978-1-4419-6967-5_2
620,In the realm of information security  lack of information about other users' incentives in a network can lead to inefficient security choices and reductions in individuals' payoffs. We propose  contrast and compare three metrics for measuring the ,benjamin johnson,Not available,2010.0,10.1007/978-1-4419-6967-5_2,Economics of Information Security and Privacy,Jens2010,False,,Springer,Not available,The Price of Uncertainty in Security Games,e35e82dbbb9d9c318fbfd58899ea5f11,http://dx.doi.org/10.1007/978-1-4419-6967-5_2
621,In the realm of information security  lack of information about other users' incentives in a network can lead to inefficient security choices and reductions in individuals' payoffs. We propose  contrast and compare three metrics for measuring the ,nicolas christin,Not available,2010.0,10.1007/978-1-4419-6967-5_2,Economics of Information Security and Privacy,Jens2010,False,,Springer,Not available,The Price of Uncertainty in Security Games,e35e82dbbb9d9c318fbfd58899ea5f11,http://dx.doi.org/10.1007/978-1-4419-6967-5_2
622,This article provides an in-depth review of the state-of-the-art and describes methodological advances in the design and evaluation of road network pricing schemes. A number of paradigm shifts from the two polar cases of the marginal social cost pricing of road traffic congestion and revenue-maximizing road toll pricing are analyzed  as induced by the need to address realistic design complexities and constraints. The crucial role of the joint consideration of pricing strategies with optimal capacity provision and several network management measures is manifested and an integrated evaluation framework is suggested to incorporate a wide range of road pricing impacts into the scheme design process.,theodore tsekeris,Not available,2009.0,10.1007/s11066-008-9024-z,NETNOMICS: Economic Research and Electronic Networking,Theodore2009,False,,Springer,Not available,Design and evaluation of road pricing: state-of-the-art and methodological advances,26231300faf219f2a623f5db28e0d593,http://dx.doi.org/10.1007/s11066-008-9024-z
623,We study the price of anarchy and the structure of equilibria in network creation games. A network creation game (first defined and studied by Fabrikant et al. [4]) is played by ,matus mihalak,Not available,2010.0,10.1007/978-3-642-16170-4_24,Algorithmic Game Theory,Matúš2010,False,,Springer,Not available,The Price of Anarchy in Network Creation Games Is (Mostly) Constant,b90e80a44ae5428829fe3f8c2300c6e6,http://dx.doi.org/10.1007/978-3-642-16170-4_24
624,This article provides an in-depth review of the state-of-the-art and describes methodological advances in the design and evaluation of road network pricing schemes. A number of paradigm shifts from the two polar cases of the marginal social cost pricing of road traffic congestion and revenue-maximizing road toll pricing are analyzed  as induced by the need to address realistic design complexities and constraints. The crucial role of the joint consideration of pricing strategies with optimal capacity provision and several network management measures is manifested and an integrated evaluation framework is suggested to incorporate a wide range of road pricing impacts into the scheme design process.,stefan voss,Not available,2009.0,10.1007/s11066-008-9024-z,NETNOMICS: Economic Research and Electronic Networking,Theodore2009,False,,Springer,Not available,Design and evaluation of road pricing: state-of-the-art and methodological advances,26231300faf219f2a623f5db28e0d593,http://dx.doi.org/10.1007/s11066-008-9024-z
625,Israeli society has changed its attitude to the sacrifice of life in war  a change that is reflected in the bereavement discourse. Attitudes have shifted from the unquestioned justification of military losses prior to the First Lebanon War (1982) to the emergence of an antiwar bereavement discourse after the war and during the South Lebanon war of attrition that followed it. More recently  following the Al-Aqsa Intifada and the Second Lebanon War (2006)  a discourse that accepts losses has emerged. While the retreat from the hegemonic discourse prior to the First Lebanon War is explained by the changing attitudes to military sacrifice among the social elites  the latter shift took place in parallel with the alteration of the social composition of the Israeli Defence Force. It is argued that the social composition of the military affects the level of sensitivity to losses. While secular upper-middle class groups tend to show a high level of sensitivity to war losses  which they then translate into a subversive bereavement discourse  religious and peripheral groups with a hawkish agenda are more tolerant of military losses  or  alternatively  may seek to avoid excessive casualties by improving the military’s performance or the quality of the political directives.,yagil levy,Not available,2009.0,10.1007/s10767-009-9048-x,International Journal of Politics  Culture  and Society,Yagil2009,False,,Springer,Not available,An Unbearable Price: War Casualties and Warring Democracies,e299351853acee11f1bd6d9a13269495,http://dx.doi.org/10.1007/s10767-009-9048-x
626,Strategic users in a wireless network cannot be assumed to follow the network algorithms blindly. Moreover  some of these users aim to use their knowledge about network algorithms to maliciously gain more resources and also to create interference to other users. We consider a general model of Multiple Access Channel (MAC) without successive interference cancellation (SIC) under Quality of Service (QoS) requirement of each user where malicious behavior exists. We model the heterogeneous behavior of users  which ranges from altruistic to selfish and then to malicious  within the analytical framework of game theory. To ensure the QoS requirements with efficient resource allocation  the noncooperative game in normal form is formulated and the Nash Equilibrium (NE) power allocation is derived in closed form. The effects of malicious behavior in network resource allocation mechanisms such as auctions and pricing schemes are studied. We consider firstly the problem of net utility maximization and then individual user QoS requirement satisfaction. We show that the well-known Vicrey-Clarke-Groves (VCG) mechanism loses its efficiency property in the presence of malicious users  which motivates the need to quantify the effect of malicious behavior. Then  the ,fei shen,Not available,2016.0,10.1007/978-3-319-22440-4_13,Communications in Interference Limited Networks,Fei2016,False,,Springer,Not available,Resource Allocation and Pricing in Non-cooperative Interference Networks with Malicious Users,08e196478165de4fdbdd31c517f04114,http://dx.doi.org/10.1007/978-3-319-22440-4_13
627,Strategic users in a wireless network cannot be assumed to follow the network algorithms blindly. Moreover  some of these users aim to use their knowledge about network algorithms to maliciously gain more resources and also to create interference to other users. We consider a general model of Multiple Access Channel (MAC) without successive interference cancellation (SIC) under Quality of Service (QoS) requirement of each user where malicious behavior exists. We model the heterogeneous behavior of users  which ranges from altruistic to selfish and then to malicious  within the analytical framework of game theory. To ensure the QoS requirements with efficient resource allocation  the noncooperative game in normal form is formulated and the Nash Equilibrium (NE) power allocation is derived in closed form. The effects of malicious behavior in network resource allocation mechanisms such as auctions and pricing schemes are studied. We consider firstly the problem of net utility maximization and then individual user QoS requirement satisfaction. We show that the well-known Vicrey-Clarke-Groves (VCG) mechanism loses its efficiency property in the presence of malicious users  which motivates the need to quantify the effect of malicious behavior. Then  the ,anil chorppath,Not available,2016.0,10.1007/978-3-319-22440-4_13,Communications in Interference Limited Networks,Fei2016,False,,Springer,Not available,Resource Allocation and Pricing in Non-cooperative Interference Networks with Malicious Users,08e196478165de4fdbdd31c517f04114,http://dx.doi.org/10.1007/978-3-319-22440-4_13
628,Strategic users in a wireless network cannot be assumed to follow the network algorithms blindly. Moreover  some of these users aim to use their knowledge about network algorithms to maliciously gain more resources and also to create interference to other users. We consider a general model of Multiple Access Channel (MAC) without successive interference cancellation (SIC) under Quality of Service (QoS) requirement of each user where malicious behavior exists. We model the heterogeneous behavior of users  which ranges from altruistic to selfish and then to malicious  within the analytical framework of game theory. To ensure the QoS requirements with efficient resource allocation  the noncooperative game in normal form is formulated and the Nash Equilibrium (NE) power allocation is derived in closed form. The effects of malicious behavior in network resource allocation mechanisms such as auctions and pricing schemes are studied. We consider firstly the problem of net utility maximization and then individual user QoS requirement satisfaction. We show that the well-known Vicrey-Clarke-Groves (VCG) mechanism loses its efficiency property in the presence of malicious users  which motivates the need to quantify the effect of malicious behavior. Then  the ,eduard jorswieck,Not available,2016.0,10.1007/978-3-319-22440-4_13,Communications in Interference Limited Networks,Fei2016,False,,Springer,Not available,Resource Allocation and Pricing in Non-cooperative Interference Networks with Malicious Users,08e196478165de4fdbdd31c517f04114,http://dx.doi.org/10.1007/978-3-319-22440-4_13
629,Strategic users in a wireless network cannot be assumed to follow the network algorithms blindly. Moreover  some of these users aim to use their knowledge about network algorithms to maliciously gain more resources and also to create interference to other users. We consider a general model of Multiple Access Channel (MAC) without successive interference cancellation (SIC) under Quality of Service (QoS) requirement of each user where malicious behavior exists. We model the heterogeneous behavior of users  which ranges from altruistic to selfish and then to malicious  within the analytical framework of game theory. To ensure the QoS requirements with efficient resource allocation  the noncooperative game in normal form is formulated and the Nash Equilibrium (NE) power allocation is derived in closed form. The effects of malicious behavior in network resource allocation mechanisms such as auctions and pricing schemes are studied. We consider firstly the problem of net utility maximization and then individual user QoS requirement satisfaction. We show that the well-known Vicrey-Clarke-Groves (VCG) mechanism loses its efficiency property in the presence of malicious users  which motivates the need to quantify the effect of malicious behavior. Then  the ,holger boche,Not available,2016.0,10.1007/978-3-319-22440-4_13,Communications in Interference Limited Networks,Fei2016,False,,Springer,Not available,Resource Allocation and Pricing in Non-cooperative Interference Networks with Malicious Users,08e196478165de4fdbdd31c517f04114,http://dx.doi.org/10.1007/978-3-319-22440-4_13
630,By rights  Leonor of Navarre (d. 1479) should never have become a queen  as the youngest child of Blanca I of Navarre and her consort  Juan of Aragon. However  as a widower  Juan would disinherit their son and elder daughter when they refused to support his retaining the crown and settled the succession on Leonor. Chroniclers have blamed unrest and civil war on Leonor’s unseemly ambition and support of her father as his lieutenant in Navarre  while her reputation suffered further damage in the popular nineteenth-century novels by Francisco Villoslado  which romanticized the fate of Leonor’s older sister who died imprisoned in one of Leonor’s castles. Woodacre assesses both Leonor’s image as a scheming villainess in contemporary and modern works and her actions as a ruler in order to ascertain whether her reputation can be rehabilitated.,elena woodacre,Not available,2016.0,10.1007/978-3-319-31283-5_8,Queenship  Gender  and Reputation in the Medieval and Early Modern West  1060-1600,Elena2016,False,,Springer,Not available,Leonor of Navarre: The Price of Ambition,d0b41cb4042c1f07af6ef0e239bf74bc,http://dx.doi.org/10.1007/978-3-319-31283-5_8
631,,li-sha huang,Not available,2016.0,10.1007/978-1-4939-2864-4_94,Encyclopedia of Algorithms,Li-Sha2016,False,,Springer,Not available,CPU Time Pricing,06bd009f62fbc4945d9c10a069893080,http://dx.doi.org/10.1007/978-1-4939-2864-4_94
632,In this paper  we studied the coordination of the supply chain consisting of one retailer and one supplier  where the market demand is uncertain. The combination of the Wholesale Price Contract and Option Contract is used to solve the problem that market risk is borne independently by the supplier. The theoretical analysis shows that the strategy can share the risk between members of the supply chain  i.e.  the supplier’s risk reduced  and the supply chain system profit can be rationally distributed  the supply chain can be coordinated and a win-win situation can be achieved by choosing appropriate option price. Finally  the numerical examples were given to verify this conclusion.,tian-yuan liu,Not available,2016.0,10.2991/978-94-6239-180-2_44,Proceedings of the 22nd International Conference on Industrial Engineering and Engineering Management 2015,Tian-yuan2016,False,,Springer,Not available,On the Coordination of Supply Chain with Demand Uncertainty Under the Combination of the Wholesale Price Contract and Option Contract,936c899bbf8299a2c71b526aa95d847b,http://dx.doi.org/10.2991/978-94-6239-180-2_44
633,In this paper  we studied the coordination of the supply chain consisting of one retailer and one supplier  where the market demand is uncertain. The combination of the Wholesale Price Contract and Option Contract is used to solve the problem that market risk is borne independently by the supplier. The theoretical analysis shows that the strategy can share the risk between members of the supply chain  i.e.  the supplier’s risk reduced  and the supply chain system profit can be rationally distributed  the supply chain can be coordinated and a win-win situation can be achieved by choosing appropriate option price. Finally  the numerical examples were given to verify this conclusion.,jiang-tao mo,Not available,2016.0,10.2991/978-94-6239-180-2_44,Proceedings of the 22nd International Conference on Industrial Engineering and Engineering Management 2015,Tian-yuan2016,False,,Springer,Not available,On the Coordination of Supply Chain with Demand Uncertainty Under the Combination of the Wholesale Price Contract and Option Contract,936c899bbf8299a2c71b526aa95d847b,http://dx.doi.org/10.2991/978-94-6239-180-2_44
634,We study the price of anarchy and the structure of equilibria in network creation games. A network creation game (first defined and studied by Fabrikant et al. [4]) is played by ,jan schlegel,Not available,2010.0,10.1007/978-3-642-16170-4_24,Algorithmic Game Theory,Matúš2010,False,,Springer,Not available,The Price of Anarchy in Network Creation Games Is (Mostly) Constant,b90e80a44ae5428829fe3f8c2300c6e6,http://dx.doi.org/10.1007/978-3-642-16170-4_24
635,In this paper  we studied the coordination of the supply chain consisting of one retailer and one supplier  where the market demand is uncertain. The combination of the Wholesale Price Contract and Option Contract is used to solve the problem that market risk is borne independently by the supplier. The theoretical analysis shows that the strategy can share the risk between members of the supply chain  i.e.  the supplier’s risk reduced  and the supply chain system profit can be rationally distributed  the supply chain can be coordinated and a win-win situation can be achieved by choosing appropriate option price. Finally  the numerical examples were given to verify this conclusion.,si-yao tang,Not available,2016.0,10.2991/978-94-6239-180-2_44,Proceedings of the 22nd International Conference on Industrial Engineering and Engineering Management 2015,Tian-yuan2016,False,,Springer,Not available,On the Coordination of Supply Chain with Demand Uncertainty Under the Combination of the Wholesale Price Contract and Option Contract,936c899bbf8299a2c71b526aa95d847b,http://dx.doi.org/10.2991/978-94-6239-180-2_44
636,"Recent spikes in international food prices and the occurrence of food riots in the period 2007–2008 have led many researchers to investigate more closely the links between rising food prices and conflict or political instability. However  this emerging literature suffers from a number of shortcomings. The objective of this article is to analyze these shortcomings further  highlight their theoretical and empirical implications  and offer ways of addressing them. I focus on three main issues. First  I look at the recurring lack of precision in the use of concepts such as political instability and conflict  and in particular the food riot concept itself. Second  I examine the often uncritical data gathering based on framing by media sources without a closer analysis of the events that took place on the ground. And third  I focus on the issue of presupposed and understudied economic as well as political causal mechanisms.,Récemment  la hausse des prix mondiaux des denrées alimentaires et les émeutes de la faim en 2007–2008 ont amené de nombreux chercheurs à étudier de plus près les liens entre la hausse des prix des denrées alimentaires et le conflit ou l’instabilité politique. Cependant  ce corps émergent d’ouvrages sur le sujet souffre de plusieurs lacunes. L’objectif de cet article est d’aller plus loin dans l’analyse de ces lacunes  de mettre en avant leurs implications théoriques et empiriques  et d’offrir des solutions pour les combler. Je me focalise sur trois problèmes principaux: tout d’abord  un manque de précision récurrent dans l’utilisation de concepts tels que l’instabilité politique ou le conflit  et en particulier pour le concept d’émeute de la faim lui-même. Ensuite  les données collectées par les média en fonction de leur agenda  souvent manquant de sens critique et d’analyse approfondie des évènements qui ont lieux sur place. Enfin  la problématique des mécanismes de cause à effet politiques et économiques  qui restent insuffisamment étudiés et basés sur des suppositions.",leila demarest,Not available,2015.0,10.1057/ejdr.2014.52,The European Journal of Development Research,Leila2015,False,,Springer,Not available,Food Price Rises and Political Instability: Problematizing a Complex Relationship,77da6232e8f95e7ad391a1282106a46e,http://dx.doi.org/10.1057/ejdr.2014.52
637,We study the Uniform Price Auction  one of the standard sealed-bid multi-unit auction formats in Auction Theory  for selling multiple identical units of a single good to multi-demand bidders. Contrary to the truthful and efficient multi-unit Vickrey auction  the Uniform Price Auction encourages strategic bidding and is generally inefficient  due to a “Demand Reduction” effect; bidders tend to bid for fewer (identical) units  so as to receive them at a lower uniform price. All the same  the uniform pricing rule is popular by its appeal to the anticipation that identical items should be identically priced. Its applications include  among others  sales of U.S. Treasury notes to investors and trade exchanges over the Internet facilitated by popular online brokers. In this work  we characterize pure undominated bidding strategies and give an algorithm for computing pure Nash equilibria in such strategies. Subsequently we show that their Price of Anarchy is ,evangelos markakis,Not available,2015.0,10.1007/s00224-014-9537-9,Theory of Computing Systems,Evangelos2015,False,,Springer,Not available,Uniform Price Auctions: Equilibria and Efficiency,eb3c05f68d391d2253a037224d3141d4,http://dx.doi.org/10.1007/s00224-014-9537-9
638,We study the Uniform Price Auction  one of the standard sealed-bid multi-unit auction formats in Auction Theory  for selling multiple identical units of a single good to multi-demand bidders. Contrary to the truthful and efficient multi-unit Vickrey auction  the Uniform Price Auction encourages strategic bidding and is generally inefficient  due to a “Demand Reduction” effect; bidders tend to bid for fewer (identical) units  so as to receive them at a lower uniform price. All the same  the uniform pricing rule is popular by its appeal to the anticipation that identical items should be identically priced. Its applications include  among others  sales of U.S. Treasury notes to investors and trade exchanges over the Internet facilitated by popular online brokers. In this work  we characterize pure undominated bidding strategies and give an algorithm for computing pure Nash equilibria in such strategies. Subsequently we show that their Price of Anarchy is ,orestis telelis,Not available,2015.0,10.1007/s00224-014-9537-9,Theory of Computing Systems,Evangelos2015,False,,Springer,Not available,Uniform Price Auctions: Equilibria and Efficiency,eb3c05f68d391d2253a037224d3141d4,http://dx.doi.org/10.1007/s00224-014-9537-9
639,This paper considers the machine load balancing game with uniformly related machines. Players choose machines of different speeds to run their jobs striving to minimize job’s delay  i.e.  the job completion time on a chosen machine. The social cost is the maximum delay over all machines. In the general case and the special case of 3 machines  we obtain upper estimates for the price of anarchy (PoA) and demonstrate when they coincide with the exact values. Moreover  sufficient conditions for PoA increase are established under new machine inclusion into the system. And finally  we propose a computing algorithm of the exact PoA value in the three-machine model.,yu. chirkova,Not available,2015.0,10.1134/S0005117915100124,Automation and Remote Control,V.2015,False,,Springer,Not available,Price of anarchy in machine load balancing game,7863ee0f28672a57ad337dab732d7779,http://dx.doi.org/10.1134/S0005117915100124
640,This article argues that the price obtainable in an open market provides the best standard for determining the justice or injustice of the price of a product. The article argues that this standard  which is closely related to positions which have been held for hundreds of years  is superior to several alternative conceptions of the just price that have been put forward in recent years and is not subject to fundamental criticisms which can be addressed to them. The article also shows how this standard is grounded in more fundamental principles of justice such as desert and equality.,juan elegido,Not available,2015.0,10.1007/s10551-014-2240-6,Journal of Business Ethics,M.2015,False,,Springer,Not available,The Just Price as the Price Obtainable in an Open Market,4b27270eed3175511e742bfbf8e51123,http://dx.doi.org/10.1007/s10551-014-2240-6
641,We study the inefficiency of equilibrium outcomes in ,bart keijzer,Not available,2015.0,10.1007/s00224-014-9598-9,Theory of Computing Systems,de2015,False,,Springer,Not available,The Strong Price of Anarchy of Linear Bottleneck Congestion Games,21cac123ce887c1a76175059bfe7861d,http://dx.doi.org/10.1007/s00224-014-9598-9
642,We study the inefficiency of equilibrium outcomes in ,guido schafer,Not available,2015.0,10.1007/s00224-014-9598-9,Theory of Computing Systems,de2015,False,,Springer,Not available,The Strong Price of Anarchy of Linear Bottleneck Congestion Games,21cac123ce887c1a76175059bfe7861d,http://dx.doi.org/10.1007/s00224-014-9598-9
643,We study the inefficiency of equilibrium outcomes in ,orestis telelis,Not available,2015.0,10.1007/s00224-014-9598-9,Theory of Computing Systems,de2015,False,,Springer,Not available,The Strong Price of Anarchy of Linear Bottleneck Congestion Games,21cac123ce887c1a76175059bfe7861d,http://dx.doi.org/10.1007/s00224-014-9598-9
644,We design a new class of vertex and set cover games  where the price of anarchy bounds match the best known constant factor approximation guarantees for the centralized optimization problems for linear and also for submodular costs. This is in contrast to all previously studied covering games  where the price of anarchy grows linearly with the size of the game. Both the game design and the price of anarchy results are based on structural properties of the linear programming relaxations. For linear costs we also exhibit simple best response dynamics that converge to Nash equilibria in linear time.,georgios piliouras,Not available,2015.0,10.1007/s00224-014-9587-z,Theory of Computing Systems,Georgios2015,False,,Springer,Not available,LP-Based Covering Games with Low Price of Anarchy,947517ac299f93abfdd6ffa322e3ff0b,http://dx.doi.org/10.1007/s00224-014-9587-z
645,We analyze the network congestion game with atomic players  asymmetric strategies  and the maximum latency among all players as social cost. This important social cost function is much less understood than the average latency. We show that the price of anarchy is at most two  when the network is a ring and the link latencies are linear. Our bound is tight. This is the first sharp bound for the maximum latency objective.,xujin chen,Not available,2012.0,10.1007/978-3-642-35311-6_31,Internet and Network Economics,Xujin2012,False,,Springer,Not available,The Price of Anarchy for Selfish Ring Routing Is Two,01390471650cbf8095dd2ef654e55ce0,http://dx.doi.org/10.1007/978-3-642-35311-6_31
646,We design a new class of vertex and set cover games  where the price of anarchy bounds match the best known constant factor approximation guarantees for the centralized optimization problems for linear and also for submodular costs. This is in contrast to all previously studied covering games  where the price of anarchy grows linearly with the size of the game. Both the game design and the price of anarchy results are based on structural properties of the linear programming relaxations. For linear costs we also exhibit simple best response dynamics that converge to Nash equilibria in linear time.,tomas valla,Not available,2015.0,10.1007/s00224-014-9587-z,Theory of Computing Systems,Georgios2015,False,,Springer,Not available,LP-Based Covering Games with Low Price of Anarchy,947517ac299f93abfdd6ffa322e3ff0b,http://dx.doi.org/10.1007/s00224-014-9587-z
647,We design a new class of vertex and set cover games  where the price of anarchy bounds match the best known constant factor approximation guarantees for the centralized optimization problems for linear and also for submodular costs. This is in contrast to all previously studied covering games  where the price of anarchy grows linearly with the size of the game. Both the game design and the price of anarchy results are based on structural properties of the linear programming relaxations. For linear costs we also exhibit simple best response dynamics that converge to Nash equilibria in linear time.,laszlo vegh,Not available,2015.0,10.1007/s00224-014-9587-z,Theory of Computing Systems,Georgios2015,False,,Springer,Not available,LP-Based Covering Games with Low Price of Anarchy,947517ac299f93abfdd6ffa322e3ff0b,http://dx.doi.org/10.1007/s00224-014-9587-z
648,We study the computation of approximate pure Nash equilibria in Shapley value (SV) weighted congestion games  introduced in [,matthias feldotto,Not available,2017.0,10.1007/978-3-319-71924-5_14,Web and Internet Economics,Matthias2017,False,,Springer,Not available,Computing Approximate Pure Nash Equilibria in Shapley Value Weighted Congestion Games,e52f5acc8662f74402f3b93d7b70441b,http://dx.doi.org/10.1007/978-3-319-71924-5_14
649,We study the computation of approximate pure Nash equilibria in Shapley value (SV) weighted congestion games  introduced in [,martin gairing,Not available,2017.0,10.1007/978-3-319-71924-5_14,Web and Internet Economics,Matthias2017,False,,Springer,Not available,Computing Approximate Pure Nash Equilibria in Shapley Value Weighted Congestion Games,e52f5acc8662f74402f3b93d7b70441b,http://dx.doi.org/10.1007/978-3-319-71924-5_14
650,We study the computation of approximate pure Nash equilibria in Shapley value (SV) weighted congestion games  introduced in [,grammateia kotsialou,Not available,2017.0,10.1007/978-3-319-71924-5_14,Web and Internet Economics,Matthias2017,False,,Springer,Not available,Computing Approximate Pure Nash Equilibria in Shapley Value Weighted Congestion Games,e52f5acc8662f74402f3b93d7b70441b,http://dx.doi.org/10.1007/978-3-319-71924-5_14
651,We study the computation of approximate pure Nash equilibria in Shapley value (SV) weighted congestion games  introduced in [,alexander skopalik,Not available,2017.0,10.1007/978-3-319-71924-5_14,Web and Internet Economics,Matthias2017,False,,Springer,Not available,Computing Approximate Pure Nash Equilibria in Shapley Value Weighted Congestion Games,e52f5acc8662f74402f3b93d7b70441b,http://dx.doi.org/10.1007/978-3-319-71924-5_14
652,Best response (BR) dynamics is a natural method by which players proceed toward a pure Nash equilibrium via a local search method. The quality of the equilibrium reached may depend heavily on the order by which players are chosen to perform their best response moves. A ,michal feldman,Not available,2017.0,10.1007/978-3-319-66700-3_15,Algorithmic Game Theory,Michal2017,False,,Springer,Not available,The Efficiency of Best-Response Dynamics,1763b372b0c2200004cf0249287e1a6a,http://dx.doi.org/10.1007/978-3-319-66700-3_15
653,Best response (BR) dynamics is a natural method by which players proceed toward a pure Nash equilibrium via a local search method. The quality of the equilibrium reached may depend heavily on the order by which players are chosen to perform their best response moves. A ,yuval snappir,Not available,2017.0,10.1007/978-3-319-66700-3_15,Algorithmic Game Theory,Michal2017,False,,Springer,Not available,The Efficiency of Best-Response Dynamics,1763b372b0c2200004cf0249287e1a6a,http://dx.doi.org/10.1007/978-3-319-66700-3_15
654,Best response (BR) dynamics is a natural method by which players proceed toward a pure Nash equilibrium via a local search method. The quality of the equilibrium reached may depend heavily on the order by which players are chosen to perform their best response moves. A ,tami tamir,Not available,2017.0,10.1007/978-3-319-66700-3_15,Algorithmic Game Theory,Michal2017,False,,Springer,Not available,The Efficiency of Best-Response Dynamics,1763b372b0c2200004cf0249287e1a6a,http://dx.doi.org/10.1007/978-3-319-66700-3_15
655,We study atomic routing games where every agent travels both along its decided edges and through time. The agents arriving on an edge are first lined up in a ,anisse ismaili,Not available,2017.0,10.1007/978-3-319-71924-5_19,Web and Internet Economics,Anisse2017,False,,Springer,Not available,Routing Games over Time with FIFO Policy,bb368b9a90372f1e0d46c79e985d12c5,http://dx.doi.org/10.1007/978-3-319-71924-5_19
656,We analyze the network congestion game with atomic players  asymmetric strategies  and the maximum latency among all players as social cost. This important social cost function is much less understood than the average latency. We show that the price of anarchy is at most two  when the network is a ring and the link latencies are linear. Our bound is tight. This is the first sharp bound for the maximum latency objective.,benjamin doerr,Not available,2012.0,10.1007/978-3-642-35311-6_31,Internet and Network Economics,Xujin2012,False,,Springer,Not available,The Price of Anarchy for Selfish Ring Routing Is Two,01390471650cbf8095dd2ef654e55ce0,http://dx.doi.org/10.1007/978-3-642-35311-6_31
657,In this paper  we tackle the problem of a sequential routing game where multiple users coexist and competitively send their traffic to a destination over a line. The users arrive at time epoch with a given capacity. Then  they ship their demands over time on a shared resource. The state of players evolve according to whether they decide to transmit or not. The decision of each user is thus spatio-temporal control. We provide an explicit expression of the equilibrium of such systems and compare it to the global optimum case. In particular  we determine the expression of price of anarchy of such scheme and identify a Braess-type paradox in the context of sequential routing game.,abdelillah karouit,Not available,2017.0,10.1007/978-3-319-68179-5_2,Ubiquitous Networking,Abdelillah2017,False,,Springer,Not available,Routing Game on the Line: The Case of Multi-players,951a06f9db1fec44dab94e54f7dcf141,http://dx.doi.org/10.1007/978-3-319-68179-5_2
658,In this paper  we tackle the problem of a sequential routing game where multiple users coexist and competitively send their traffic to a destination over a line. The users arrive at time epoch with a given capacity. Then  they ship their demands over time on a shared resource. The state of players evolve according to whether they decide to transmit or not. The decision of each user is thus spatio-temporal control. We provide an explicit expression of the equilibrium of such systems and compare it to the global optimum case. In particular  we determine the expression of price of anarchy of such scheme and identify a Braess-type paradox in the context of sequential routing game.,majed haddad,Not available,2017.0,10.1007/978-3-319-68179-5_2,Ubiquitous Networking,Abdelillah2017,False,,Springer,Not available,Routing Game on the Line: The Case of Multi-players,951a06f9db1fec44dab94e54f7dcf141,http://dx.doi.org/10.1007/978-3-319-68179-5_2
659,In this paper  we tackle the problem of a sequential routing game where multiple users coexist and competitively send their traffic to a destination over a line. The users arrive at time epoch with a given capacity. Then  they ship their demands over time on a shared resource. The state of players evolve according to whether they decide to transmit or not. The decision of each user is thus spatio-temporal control. We provide an explicit expression of the equilibrium of such systems and compare it to the global optimum case. In particular  we determine the expression of price of anarchy of such scheme and identify a Braess-type paradox in the context of sequential routing game.,eitan altman,Not available,2017.0,10.1007/978-3-319-68179-5_2,Ubiquitous Networking,Abdelillah2017,False,,Springer,Not available,Routing Game on the Line: The Case of Multi-players,951a06f9db1fec44dab94e54f7dcf141,http://dx.doi.org/10.1007/978-3-319-68179-5_2
660,In this paper  we tackle the problem of a sequential routing game where multiple users coexist and competitively send their traffic to a destination over a line. The users arrive at time epoch with a given capacity. Then  they ship their demands over time on a shared resource. The state of players evolve according to whether they decide to transmit or not. The decision of each user is thus spatio-temporal control. We provide an explicit expression of the equilibrium of such systems and compare it to the global optimum case. In particular  we determine the expression of price of anarchy of such scheme and identify a Braess-type paradox in the context of sequential routing game.,moulay lmater,Not available,2017.0,10.1007/978-3-319-68179-5_2,Ubiquitous Networking,Abdelillah2017,False,,Springer,Not available,Routing Game on the Line: The Case of Multi-players,951a06f9db1fec44dab94e54f7dcf141,http://dx.doi.org/10.1007/978-3-319-68179-5_2
661,Recently  there has been an increased research interest in telecommunication network pricing  which leads to many proposals for new pricing schemes motivated by different objectives namely: to maximize service provider’s revenue  to guarantee fairness among users and to satisfy QoS requirements for differentiated network services.In present paper  we consider a Bertrand model with ,omar ait,Not available,2017.0,10.1007/978-3-319-59647-1_33,Networked Systems,Driss2017,False,,Springer,Not available,Joint Price and QoS Competition with Bounded Rational Customers,a5e86c9aa2e048137a40f11663f50628,http://dx.doi.org/10.1007/978-3-319-59647-1_33
662,Recently  there has been an increased research interest in telecommunication network pricing  which leads to many proposals for new pricing schemes motivated by different objectives namely: to maximize service provider’s revenue  to guarantee fairness among users and to satisfy QoS requirements for differentiated network services.In present paper  we consider a Bertrand model with ,m'hamed outanoute,Not available,2017.0,10.1007/978-3-319-59647-1_33,Networked Systems,Driss2017,False,,Springer,Not available,Joint Price and QoS Competition with Bounded Rational Customers,a5e86c9aa2e048137a40f11663f50628,http://dx.doi.org/10.1007/978-3-319-59647-1_33
663,Recently  there has been an increased research interest in telecommunication network pricing  which leads to many proposals for new pricing schemes motivated by different objectives namely: to maximize service provider’s revenue  to guarantee fairness among users and to satisfy QoS requirements for differentiated network services.In present paper  we consider a Bertrand model with ,mohamed baslam,Not available,2017.0,10.1007/978-3-319-59647-1_33,Networked Systems,Driss2017,False,,Springer,Not available,Joint Price and QoS Competition with Bounded Rational Customers,a5e86c9aa2e048137a40f11663f50628,http://dx.doi.org/10.1007/978-3-319-59647-1_33
664,Recently  there has been an increased research interest in telecommunication network pricing  which leads to many proposals for new pricing schemes motivated by different objectives namely: to maximize service provider’s revenue  to guarantee fairness among users and to satisfy QoS requirements for differentiated network services.In present paper  we consider a Bertrand model with ,mohamed fakir,Not available,2017.0,10.1007/978-3-319-59647-1_33,Networked Systems,Driss2017,False,,Springer,Not available,Joint Price and QoS Competition with Bounded Rational Customers,a5e86c9aa2e048137a40f11663f50628,http://dx.doi.org/10.1007/978-3-319-59647-1_33
665,Recently  there has been an increased research interest in telecommunication network pricing  which leads to many proposals for new pricing schemes motivated by different objectives namely: to maximize service provider’s revenue  to guarantee fairness among users and to satisfy QoS requirements for differentiated network services.In present paper  we consider a Bertrand model with ,belaid bouikhalne,Not available,2017.0,10.1007/978-3-319-59647-1_33,Networked Systems,Driss2017,False,,Springer,Not available,Joint Price and QoS Competition with Bounded Rational Customers,a5e86c9aa2e048137a40f11663f50628,http://dx.doi.org/10.1007/978-3-319-59647-1_33
666,We study a natural strategic situation arising from the selection of shared means of transportation. Some clients (the players) are located on different nodes of a given graph and they want to be transported from their location to a common destination point (,dimitris fotakis,Not available,2017.0,10.1007/978-3-319-51963-0_14,SOFSEM 2017: Theory and Practice of Computer Science,Dimitris2017,False,,Springer,Not available,Selfish Transportation Games,28b7f8195c13a95ab2e1699711efb31e,http://dx.doi.org/10.1007/978-3-319-51963-0_14
667,We consider the problem of sharing the cost of multicast transmissions in non-cooperative undirected networks with non-negative edge costs. In such a setting  there is a set of receivers ,vittorio bilo,Not available,2007.0,10.1007/978-3-540-77120-3_35,Algorithms and Computation,Vittorio2007,False,,Springer,Not available,The Price of Nash Equilibria in Multicast Transmissions Games,a5c98274106e3a31ba18eee78c2cb017,http://dx.doi.org/10.1007/978-3-540-77120-3_35
668,We analyze the network congestion game with atomic players  asymmetric strategies  and the maximum latency among all players as social cost. This important social cost function is much less understood than the average latency. We show that the price of anarchy is at most two  when the network is a ring and the link latencies are linear. Our bound is tight. This is the first sharp bound for the maximum latency objective.,xiaodong hu,Not available,2012.0,10.1007/978-3-642-35311-6_31,Internet and Network Economics,Xujin2012,False,,Springer,Not available,The Price of Anarchy for Selfish Ring Routing Is Two,01390471650cbf8095dd2ef654e55ce0,http://dx.doi.org/10.1007/978-3-642-35311-6_31
669,We study a natural strategic situation arising from the selection of shared means of transportation. Some clients (the players) are located on different nodes of a given graph and they want to be transported from their location to a common destination point (,laurent gourves,Not available,2017.0,10.1007/978-3-319-51963-0_14,SOFSEM 2017: Theory and Practice of Computer Science,Dimitris2017,False,,Springer,Not available,Selfish Transportation Games,28b7f8195c13a95ab2e1699711efb31e,http://dx.doi.org/10.1007/978-3-319-51963-0_14
670,We study a natural strategic situation arising from the selection of shared means of transportation. Some clients (the players) are located on different nodes of a given graph and they want to be transported from their location to a common destination point (,jerome monnot,Not available,2017.0,10.1007/978-3-319-51963-0_14,SOFSEM 2017: Theory and Practice of Computer Science,Dimitris2017,False,,Springer,Not available,Selfish Transportation Games,28b7f8195c13a95ab2e1699711efb31e,http://dx.doi.org/10.1007/978-3-319-51963-0_14
671,This chapter presents a game theoretic framework for studying Stackelberg routing games on parallel transportation networks. A new class of latency functions is introduced to model congestion due to the formation of physical queues  inspired from the fundamental diagram of traffic. For this new class  some results from the classical congestion games literature (in which latency is assumed to be a nondecreasing function of the flow) do not hold. A characterization of Nash equilibria is given  and it is shown  in particular  that there may exist multiple equilibria that have different total costs. A simple polynomial-time algorithm is provided  for computing the ,walid krichene,Not available,2017.0,10.1007/978-3-319-27335-8_26-1,Handbook of Dynamic Game Theory,Walid2017,False,,Springer,Not available,Stackelberg Routing on Parallel Transportation Networks,34c1aee38e7dca7728566e08d9ae0c88,http://dx.doi.org/10.1007/978-3-319-27335-8_26-1
672,This chapter presents a game theoretic framework for studying Stackelberg routing games on parallel transportation networks. A new class of latency functions is introduced to model congestion due to the formation of physical queues  inspired from the fundamental diagram of traffic. For this new class  some results from the classical congestion games literature (in which latency is assumed to be a nondecreasing function of the flow) do not hold. A characterization of Nash equilibria is given  and it is shown  in particular  that there may exist multiple equilibria that have different total costs. A simple polynomial-time algorithm is provided  for computing the ,jack reilly,Not available,2017.0,10.1007/978-3-319-27335-8_26-1,Handbook of Dynamic Game Theory,Walid2017,False,,Springer,Not available,Stackelberg Routing on Parallel Transportation Networks,34c1aee38e7dca7728566e08d9ae0c88,http://dx.doi.org/10.1007/978-3-319-27335-8_26-1
673,This chapter presents a game theoretic framework for studying Stackelberg routing games on parallel transportation networks. A new class of latency functions is introduced to model congestion due to the formation of physical queues  inspired from the fundamental diagram of traffic. For this new class  some results from the classical congestion games literature (in which latency is assumed to be a nondecreasing function of the flow) do not hold. A characterization of Nash equilibria is given  and it is shown  in particular  that there may exist multiple equilibria that have different total costs. A simple polynomial-time algorithm is provided  for computing the ,saurabh amin,Not available,2017.0,10.1007/978-3-319-27335-8_26-1,Handbook of Dynamic Game Theory,Walid2017,False,,Springer,Not available,Stackelberg Routing on Parallel Transportation Networks,34c1aee38e7dca7728566e08d9ae0c88,http://dx.doi.org/10.1007/978-3-319-27335-8_26-1
674,This chapter presents a game theoretic framework for studying Stackelberg routing games on parallel transportation networks. A new class of latency functions is introduced to model congestion due to the formation of physical queues  inspired from the fundamental diagram of traffic. For this new class  some results from the classical congestion games literature (in which latency is assumed to be a nondecreasing function of the flow) do not hold. A characterization of Nash equilibria is given  and it is shown  in particular  that there may exist multiple equilibria that have different total costs. A simple polynomial-time algorithm is provided  for computing the ,alexandre bayen,Not available,2017.0,10.1007/978-3-319-27335-8_26-1,Handbook of Dynamic Game Theory,Walid2017,False,,Springer,Not available,Stackelberg Routing on Parallel Transportation Networks,34c1aee38e7dca7728566e08d9ae0c88,http://dx.doi.org/10.1007/978-3-319-27335-8_26-1
675,Selfish bin packing can be viewed as the non-cooperative version of bin packing problem  where every item is a selfish agent and want to minimize his sharing cost with the other items packing in the same bin. In this paper  we focus on designing a new mechanism (a payoff rule) for selfish bin packing  called modified Dutch treatment mechanism. We first show that the pure Nash equilibrium exists and it can be obtained in polynomial time. We then prove that under the new mechanism  the price of anarchy (PoA) is between 1.47407 and 1.4748  improving the known results.,xin chen,Not available,2017.0,10.1007/978-3-319-71147-8_17,Combinatorial Optimization and Applications,Xin2017,False,,Springer,Not available,An Improved Mechanism for Selfish Bin Packing,4d998257344f7f1b328650a1267f607b,http://dx.doi.org/10.1007/978-3-319-71147-8_17
676,Selfish bin packing can be viewed as the non-cooperative version of bin packing problem  where every item is a selfish agent and want to minimize his sharing cost with the other items packing in the same bin. In this paper  we focus on designing a new mechanism (a payoff rule) for selfish bin packing  called modified Dutch treatment mechanism. We first show that the pure Nash equilibrium exists and it can be obtained in polynomial time. We then prove that under the new mechanism  the price of anarchy (PoA) is between 1.47407 and 1.4748  improving the known results.,qingqin nong,Not available,2017.0,10.1007/978-3-319-71147-8_17,Combinatorial Optimization and Applications,Xin2017,False,,Springer,Not available,An Improved Mechanism for Selfish Bin Packing,4d998257344f7f1b328650a1267f607b,http://dx.doi.org/10.1007/978-3-319-71147-8_17
677,Selfish bin packing can be viewed as the non-cooperative version of bin packing problem  where every item is a selfish agent and want to minimize his sharing cost with the other items packing in the same bin. In this paper  we focus on designing a new mechanism (a payoff rule) for selfish bin packing  called modified Dutch treatment mechanism. We first show that the pure Nash equilibrium exists and it can be obtained in polynomial time. We then prove that under the new mechanism  the price of anarchy (PoA) is between 1.47407 and 1.4748  improving the known results.,qizhi fang,Not available,2017.0,10.1007/978-3-319-71147-8_17,Combinatorial Optimization and Applications,Xin2017,False,,Springer,Not available,An Improved Mechanism for Selfish Bin Packing,4d998257344f7f1b328650a1267f607b,http://dx.doi.org/10.1007/978-3-319-71147-8_17
678,This article summarizes the methodology and economics of Karl Marx. After a brief account of his life  it deals with his historical materialism  and then his labour theory of value  his theories of rent  money  surplus value  and crises  his account of the laws of motion of the capitalism mode of production  and his and Engels’s conception of the economy of post-capitalist societies.,ernest mandel,Not available,2017.0,10.1057/978-1-349-95121-5_1019-2,The New Palgrave Dictionary of Economics,Ernest2017,False,,Springer,Not available,Marx  Karl Heinrich (1818–1883),8b910d292bc5a94412a4a98c6b705274,http://dx.doi.org/10.1057/978-1-349-95121-5_1019-2
679,We analyze the network congestion game with atomic players  asymmetric strategies  and the maximum latency among all players as social cost. This important social cost function is much less understood than the average latency. We show that the price of anarchy is at most two  when the network is a ring and the link latencies are linear. Our bound is tight. This is the first sharp bound for the maximum latency objective.,weidong ma,Not available,2012.0,10.1007/978-3-642-35311-6_31,Internet and Network Economics,Xujin2012,False,,Springer,Not available,The Price of Anarchy for Selfish Ring Routing Is Two,01390471650cbf8095dd2ef654e55ce0,http://dx.doi.org/10.1007/978-3-642-35311-6_31
680,Media increasingly accuse firms of exploiting suppliers  and these allegations often result in lurid headlines that threaten the reputations and therefore business successes of these firms. Neither has the phenomenon of supplier exploitation been investigated from a rigorous  ethical standpoint  nor have answers been provided regarding why some firms pursue exploitative approaches. By systemically contrasting economic liberalism and just prices as two divergent perspectives on supplier exploitation  we introduce a distinction of common business practice and unethical supplier exploitation. Since supplier exploitation is based on power  we elucidate several levels of power as antecedents and investigate the role of ethical climate as a moderator. This study extends Victor and Cullen’s (,martin schleper,Not available,2017.0,10.1007/s10551-015-2681-6,Journal of Business Ethics,C.2017,False,,Springer,Not available,The Dark Side of Buyer Power: Supplier Exploitation and the Role of Ethical Climates,1f02f612ecd9b82321285fbf5554ef49,http://dx.doi.org/10.1007/s10551-015-2681-6
681,Media increasingly accuse firms of exploiting suppliers  and these allegations often result in lurid headlines that threaten the reputations and therefore business successes of these firms. Neither has the phenomenon of supplier exploitation been investigated from a rigorous  ethical standpoint  nor have answers been provided regarding why some firms pursue exploitative approaches. By systemically contrasting economic liberalism and just prices as two divergent perspectives on supplier exploitation  we introduce a distinction of common business practice and unethical supplier exploitation. Since supplier exploitation is based on power  we elucidate several levels of power as antecedents and investigate the role of ethical climate as a moderator. This study extends Victor and Cullen’s (,constantin blome,Not available,2017.0,10.1007/s10551-015-2681-6,Journal of Business Ethics,C.2017,False,,Springer,Not available,The Dark Side of Buyer Power: Supplier Exploitation and the Role of Ethical Climates,1f02f612ecd9b82321285fbf5554ef49,http://dx.doi.org/10.1007/s10551-015-2681-6
682,Media increasingly accuse firms of exploiting suppliers  and these allegations often result in lurid headlines that threaten the reputations and therefore business successes of these firms. Neither has the phenomenon of supplier exploitation been investigated from a rigorous  ethical standpoint  nor have answers been provided regarding why some firms pursue exploitative approaches. By systemically contrasting economic liberalism and just prices as two divergent perspectives on supplier exploitation  we introduce a distinction of common business practice and unethical supplier exploitation. Since supplier exploitation is based on power  we elucidate several levels of power as antecedents and investigate the role of ethical climate as a moderator. This study extends Victor and Cullen’s (,david wuttke,Not available,2017.0,10.1007/s10551-015-2681-6,Journal of Business Ethics,C.2017,False,,Springer,Not available,The Dark Side of Buyer Power: Supplier Exploitation and the Role of Ethical Climates,1f02f612ecd9b82321285fbf5554ef49,http://dx.doi.org/10.1007/s10551-015-2681-6
683,Our main goal is to abstract existing repeated sponsored search ad auction mechanisms which incorporate budgets  and study their equilibrium and dynamics. Our abstraction has multiple agents bidding repeatedly for multiple identical items (such as impressions in an ad auction). The agents are budget limited and have a value per item. We abstract this repeated interaction as a one-shot game  which we call ,asaph arnon,Not available,2014.0,10.1007/s00224-013-9472-1,Theory of Computing Systems,Asaph2014,False,,Springer,Not available,Repeated Budgeted Second Price Ad Auction,0ed98b5128a774a891e40933e89c5eed,http://dx.doi.org/10.1007/s00224-013-9472-1
684,Our main goal is to abstract existing repeated sponsored search ad auction mechanisms which incorporate budgets  and study their equilibrium and dynamics. Our abstraction has multiple agents bidding repeatedly for multiple identical items (such as impressions in an ad auction). The agents are budget limited and have a value per item. We abstract this repeated interaction as a one-shot game  which we call ,yishay mansour,Not available,2014.0,10.1007/s00224-013-9472-1,Theory of Computing Systems,Asaph2014,False,,Springer,Not available,Repeated Budgeted Second Price Ad Auction,0ed98b5128a774a891e40933e89c5eed,http://dx.doi.org/10.1007/s00224-013-9472-1
685,,george christodoulou,Not available,2014.0,10.1007/978-3-642-27848-8_299-2,Encyclopedia of Algorithms,George2014,False,,Springer,Not available,Price of Anarchy,66db23292444db36f03e95d9c6e6945a,http://dx.doi.org/10.1007/978-3-642-27848-8_299-2
686,We introduce a framework for studying the effect of cooperation on the quality of outcomes in utility games. Our framework is a coalitional analog of the smoothness framework of non-cooperative games. Coalitional smoothness implies bounds on the strong price of anarchy  the loss of quality of coalitionally stable outcomes. Our coalitional smoothness framework captures existing results bounding the strong price of anarchy of network design games. Moreover  we give novel strong price of anarchy results for any monotone utility-maximization game  showing that if each player’s utility is at least his marginal contribution to the welfare  then the strong price of anarchy is at most 2. This captures a broad class of games  including games that have a price of anarchy as high as the number of players. Additionally  we show that in potential games the strong price of anarchy is close to the price of stability  the quality of the best Nash equilibrium.We also initiate the study of the quality of coalitional out-of-equilibrium outcomes in games. To this end  we define a coalitional version of myopic best-response dynamics  and show that the bound on the strong price of anarchy implied by coalitional smoothness  also extends with small degradation to the average quality of outcomes of the given dynamic.,yoram bachrach,Not available,2014.0,10.1007/978-3-662-44803-8_19,Algorithmic Game Theory,Yoram2014,False,,Springer,Not available,Strong Price of Anarchy  Utility Games and Coalitional Dynamics,c20dae0d8b35efe369ff6969ef6f66db,http://dx.doi.org/10.1007/978-3-662-44803-8_19
687,We introduce a framework for studying the effect of cooperation on the quality of outcomes in utility games. Our framework is a coalitional analog of the smoothness framework of non-cooperative games. Coalitional smoothness implies bounds on the strong price of anarchy  the loss of quality of coalitionally stable outcomes. Our coalitional smoothness framework captures existing results bounding the strong price of anarchy of network design games. Moreover  we give novel strong price of anarchy results for any monotone utility-maximization game  showing that if each player’s utility is at least his marginal contribution to the welfare  then the strong price of anarchy is at most 2. This captures a broad class of games  including games that have a price of anarchy as high as the number of players. Additionally  we show that in potential games the strong price of anarchy is close to the price of stability  the quality of the best Nash equilibrium.We also initiate the study of the quality of coalitional out-of-equilibrium outcomes in games. To this end  we define a coalitional version of myopic best-response dynamics  and show that the bound on the strong price of anarchy implied by coalitional smoothness  also extends with small degradation to the average quality of outcomes of the given dynamic.,vasilis syrgkanis,Not available,2014.0,10.1007/978-3-662-44803-8_19,Algorithmic Game Theory,Yoram2014,False,,Springer,Not available,Strong Price of Anarchy  Utility Games and Coalitional Dynamics,c20dae0d8b35efe369ff6969ef6f66db,http://dx.doi.org/10.1007/978-3-662-44803-8_19
688,We introduce a framework for studying the effect of cooperation on the quality of outcomes in utility games. Our framework is a coalitional analog of the smoothness framework of non-cooperative games. Coalitional smoothness implies bounds on the strong price of anarchy  the loss of quality of coalitionally stable outcomes. Our coalitional smoothness framework captures existing results bounding the strong price of anarchy of network design games. Moreover  we give novel strong price of anarchy results for any monotone utility-maximization game  showing that if each player’s utility is at least his marginal contribution to the welfare  then the strong price of anarchy is at most 2. This captures a broad class of games  including games that have a price of anarchy as high as the number of players. Additionally  we show that in potential games the strong price of anarchy is close to the price of stability  the quality of the best Nash equilibrium.We also initiate the study of the quality of coalitional out-of-equilibrium outcomes in games. To this end  we define a coalitional version of myopic best-response dynamics  and show that the bound on the strong price of anarchy implied by coalitional smoothness  also extends with small degradation to the average quality of outcomes of the given dynamic.,eva tardos,Not available,2014.0,10.1007/978-3-662-44803-8_19,Algorithmic Game Theory,Yoram2014,False,,Springer,Not available,Strong Price of Anarchy  Utility Games and Coalitional Dynamics,c20dae0d8b35efe369ff6969ef6f66db,http://dx.doi.org/10.1007/978-3-662-44803-8_19
689,We introduce a framework for studying the effect of cooperation on the quality of outcomes in utility games. Our framework is a coalitional analog of the smoothness framework of non-cooperative games. Coalitional smoothness implies bounds on the strong price of anarchy  the loss of quality of coalitionally stable outcomes. Our coalitional smoothness framework captures existing results bounding the strong price of anarchy of network design games. Moreover  we give novel strong price of anarchy results for any monotone utility-maximization game  showing that if each player’s utility is at least his marginal contribution to the welfare  then the strong price of anarchy is at most 2. This captures a broad class of games  including games that have a price of anarchy as high as the number of players. Additionally  we show that in potential games the strong price of anarchy is close to the price of stability  the quality of the best Nash equilibrium.We also initiate the study of the quality of coalitional out-of-equilibrium outcomes in games. To this end  we define a coalitional version of myopic best-response dynamics  and show that the bound on the strong price of anarchy implied by coalitional smoothness  also extends with small degradation to the average quality of outcomes of the given dynamic.,milan vojnovic,Not available,2014.0,10.1007/978-3-662-44803-8_19,Algorithmic Game Theory,Yoram2014,False,,Springer,Not available,Strong Price of Anarchy  Utility Games and Coalitional Dynamics,c20dae0d8b35efe369ff6969ef6f66db,http://dx.doi.org/10.1007/978-3-662-44803-8_19
690,We analyze the network congestion game with atomic players  asymmetric strategies  and the maximum latency among all players as social cost. This important social cost function is much less understood than the average latency. We show that the price of anarchy is at most two  when the network is a ring and the link latencies are linear. Our bound is tight. This is the first sharp bound for the maximum latency objective.,rob stee,Not available,2012.0,10.1007/978-3-642-35311-6_31,Internet and Network Economics,Xujin2012,False,,Springer,Not available,The Price of Anarchy for Selfish Ring Routing Is Two,01390471650cbf8095dd2ef654e55ce0,http://dx.doi.org/10.1007/978-3-642-35311-6_31
691,In situations without central coordination  the price of anarchy relates the quality of any Nash equilibrium to the quality of a global optimum. Instead of assuming that all players choose their actions simultaneously  we consider games where players choose their actions sequentially. The sequential price of anarchy  recently introduced by Paes Leme  Syrgkanis  and Tardos [13]  relates the quality of any subgame perfect equilibrium to the quality of a global optimum. The effect of sequential decision making on the quality of equilibria  depends on the specific game under consideration. We analyze the sequential price of anarchy for atomic congestion games with affine cost functions. We derive several lower and upper bounds  showing that sequential decisions mitigate the worst case outcomes known for the classical price of anarchy [2 5]. Next to tight bounds on the sequential price of anarchy  a methodological contribution of our work is  among other things  a “factor revealing” linear programming approach we use to solve the case of three players.,jasper jong,Not available,2014.0,10.1007/978-3-319-13129-0_35,Web and Internet Economics,Jasper2014,False,,Springer,Not available,The Sequential Price of Anarchy for Atomic Congestion Games,b4115bba65b3ce206c832a80a2787480,http://dx.doi.org/10.1007/978-3-319-13129-0_35
692,In situations without central coordination  the price of anarchy relates the quality of any Nash equilibrium to the quality of a global optimum. Instead of assuming that all players choose their actions simultaneously  we consider games where players choose their actions sequentially. The sequential price of anarchy  recently introduced by Paes Leme  Syrgkanis  and Tardos [13]  relates the quality of any subgame perfect equilibrium to the quality of a global optimum. The effect of sequential decision making on the quality of equilibria  depends on the specific game under consideration. We analyze the sequential price of anarchy for atomic congestion games with affine cost functions. We derive several lower and upper bounds  showing that sequential decisions mitigate the worst case outcomes known for the classical price of anarchy [2 5]. Next to tight bounds on the sequential price of anarchy  a methodological contribution of our work is  among other things  a “factor revealing” linear programming approach we use to solve the case of three players.,marc uetz,Not available,2014.0,10.1007/978-3-319-13129-0_35,Web and Internet Economics,Jasper2014,False,,Springer,Not available,The Sequential Price of Anarchy for Atomic Congestion Games,b4115bba65b3ce206c832a80a2787480,http://dx.doi.org/10.1007/978-3-319-13129-0_35
693,The price of anarchy (POA) in a congestion network refers to the ratio of the individually optimal total cost to the socially optimal total cost. An extensive literature on this subject has focussed mostly on deriving upper bounds on the POA that are independent of the topology of the network and (to a lesser extent) the form of the cost functions at the facilities of the network. This paper considers congestion networks in which the cost functions at the facilities display qualitative characteristics found in the waiting-time function for queue with an infinite waiting room. For a network of parallel ,shaler stidham,Not available,2014.0,10.1007/978-1-4614-9056-2_5,Essays in Production  Project Planning and Scheduling,Shaler2014,False,,Springer,Not available,The Price of Anarchy for a Network of Queues in Heavy Traffic,40c0e8a509074029a9b658d3899b44c2,http://dx.doi.org/10.1007/978-1-4614-9056-2_5
694,,alexis kaporis,Not available,2014.0,10.1007/978-3-642-27848-8_398-2,Encyclopedia of Algorithms,Alexis2014,False,,Springer,Not available,Stackelberg Games: The Price of Optimum,6c46af94485f58573e0e9359e32df7e4,http://dx.doi.org/10.1007/978-3-642-27848-8_398-2
695,,paul spirakis,Not available,2014.0,10.1007/978-3-642-27848-8_398-2,Encyclopedia of Algorithms,Alexis2014,False,,Springer,Not available,Stackelberg Games: The Price of Optimum,6c46af94485f58573e0e9359e32df7e4,http://dx.doi.org/10.1007/978-3-642-27848-8_398-2
696,The paper considers a dynamic game with a single manufacturer who supplies two retailers. The manufacturer determines his production rate of a specific product  the rate of quality improvement efforts as well as the rate of advertising for the product. Each retailer controls her purchasing rate and the consumer sales price. Payments from a retailer to the manufacturer are determined by a wholesale price or a revenue-sharing scheme. The retailers operate in the same consumer market in which they compete in prices for the consumer demand. Nash equilibrium conditions are derived and numerical methods are employed to characterize equilibrium behavior of the players in a differential game of fixed and finite duration.,fouad ouardighi,Not available,2013.0,10.1007/s00291-012-0300-9,OR Spectrum,El2013,False,,Springer,Not available,A dynamic game with monopolist manufacturer and price-competing duopolist retailers,b0c055a8d82c1ba83130020f7e4ddc2f,http://dx.doi.org/10.1007/s00291-012-0300-9
697,The paper considers a dynamic game with a single manufacturer who supplies two retailers. The manufacturer determines his production rate of a specific product  the rate of quality improvement efforts as well as the rate of advertising for the product. Each retailer controls her purchasing rate and the consumer sales price. Payments from a retailer to the manufacturer are determined by a wholesale price or a revenue-sharing scheme. The retailers operate in the same consumer market in which they compete in prices for the consumer demand. Nash equilibrium conditions are derived and numerical methods are employed to characterize equilibrium behavior of the players in a differential game of fixed and finite duration.,steffen jorgensen,Not available,2013.0,10.1007/s00291-012-0300-9,OR Spectrum,El2013,False,,Springer,Not available,A dynamic game with monopolist manufacturer and price-competing duopolist retailers,b0c055a8d82c1ba83130020f7e4ddc2f,http://dx.doi.org/10.1007/s00291-012-0300-9
698,The paper considers a dynamic game with a single manufacturer who supplies two retailers. The manufacturer determines his production rate of a specific product  the rate of quality improvement efforts as well as the rate of advertising for the product. Each retailer controls her purchasing rate and the consumer sales price. Payments from a retailer to the manufacturer are determined by a wholesale price or a revenue-sharing scheme. The retailers operate in the same consumer market in which they compete in prices for the consumer demand. Nash equilibrium conditions are derived and numerical methods are employed to characterize equilibrium behavior of the players in a differential game of fixed and finite duration.,federico pasin,Not available,2013.0,10.1007/s00291-012-0300-9,OR Spectrum,El2013,False,,Springer,Not available,A dynamic game with monopolist manufacturer and price-competing duopolist retailers,b0c055a8d82c1ba83130020f7e4ddc2f,http://dx.doi.org/10.1007/s00291-012-0300-9
699,The purpose of this paper is to investigate the direct link between firm fundamentals and stock prices in a set of emerging Asian stock markets using firm-level panel data. In doing so  we explore the relationship between firm-specific variations in stock returns and firm fundamentals in the context of a simple present value framework. We find that alternative proxies of variation in firm fundamentals—albeit at differing degrees—explain a significant part of firm-specific return variation in a majority of emerging markets in Asia. Findings are robust to the influence of other factors known to affect stock return volatility (e.g. firm size  stock turnover  and leverage). Overall results suggest that stock prices in a majority of the Asian emerging markets contain a significant amount of firm-specific fundamental information and are  therefore  not as murky as commonly thought.,m. rahman,Not available,2013.0,10.1007/s11156-012-0316-x,Review of Quantitative Finance and Accounting,Arifur2013,False,,Springer,Not available,Firm fundamentals and stock prices in emerging Asian stock markets: some panel data evidence,f2943b2ada14f70713a8f68728cf225f,http://dx.doi.org/10.1007/s11156-012-0316-x
700,The purpose of this paper is to investigate the direct link between firm fundamentals and stock prices in a set of emerging Asian stock markets using firm-level panel data. In doing so  we explore the relationship between firm-specific variations in stock returns and firm fundamentals in the context of a simple present value framework. We find that alternative proxies of variation in firm fundamentals—albeit at differing degrees—explain a significant part of firm-specific return variation in a majority of emerging markets in Asia. Findings are robust to the influence of other factors known to affect stock return volatility (e.g. firm size  stock turnover  and leverage). Overall results suggest that stock prices in a majority of the Asian emerging markets contain a significant amount of firm-specific fundamental information and are  therefore  not as murky as commonly thought.,m. hassan,Not available,2013.0,10.1007/s11156-012-0316-x,Review of Quantitative Finance and Accounting,Arifur2013,False,,Springer,Not available,Firm fundamentals and stock prices in emerging Asian stock markets: some panel data evidence,f2943b2ada14f70713a8f68728cf225f,http://dx.doi.org/10.1007/s11156-012-0316-x
701,We analyze the network congestion game with atomic players  asymmetric strategies  and the maximum latency among all players as social cost. This important social cost function is much less understood than the average latency. We show that the price of anarchy is at most two  when the network is a ring and the link latencies are linear. Our bound is tight. This is the first sharp bound for the maximum latency objective.,carola winzen,Not available,2012.0,10.1007/978-3-642-35311-6_31,Internet and Network Economics,Xujin2012,False,,Springer,Not available,The Price of Anarchy for Selfish Ring Routing Is Two,01390471650cbf8095dd2ef654e55ce0,http://dx.doi.org/10.1007/978-3-642-35311-6_31
702,We study the price of anarchy and the structure of equilibria in network creation games. A network creation game is played by ,matus mihalak,Not available,2013.0,10.1007/s00224-013-9459-y,Theory of Computing Systems,Matúš2013,False,,Springer,Not available,The Price of Anarchy in Network Creation Games Is (Mostly) Constant,9e3a187ca11096845834402342b63d20,http://dx.doi.org/10.1007/s00224-013-9459-y
703,We study the price of anarchy and the structure of equilibria in network creation games. A network creation game is played by ,jan schlegel,Not available,2013.0,10.1007/s00224-013-9459-y,Theory of Computing Systems,Matúš2013,False,,Springer,Not available,The Price of Anarchy in Network Creation Games Is (Mostly) Constant,9e3a187ca11096845834402342b63d20,http://dx.doi.org/10.1007/s00224-013-9459-y
704,Bounding the price of stability of undirected network design games with fair cost allocation is a challenging open problem in the Algorithmic Game Theory research agenda. Even though the generalization of such games in directed networks is well understood in terms of the price of stability (it is exactly ,vittorio bilo,Not available,2013.0,10.1007/s00224-012-9411-6,Theory of Computing Systems,Vittorio2013,False,,Springer,Not available,Improved Lower Bounds on the Price of Stability of Undirected Network Design Games,511d9787e09b554098f9011bc0de5e9b,http://dx.doi.org/10.1007/s00224-012-9411-6
705,Bounding the price of stability of undirected network design games with fair cost allocation is a challenging open problem in the Algorithmic Game Theory research agenda. Even though the generalization of such games in directed networks is well understood in terms of the price of stability (it is exactly ,ioannis caragiannis,Not available,2013.0,10.1007/s00224-012-9411-6,Theory of Computing Systems,Vittorio2013,False,,Springer,Not available,Improved Lower Bounds on the Price of Stability of Undirected Network Design Games,511d9787e09b554098f9011bc0de5e9b,http://dx.doi.org/10.1007/s00224-012-9411-6
706,Bounding the price of stability of undirected network design games with fair cost allocation is a challenging open problem in the Algorithmic Game Theory research agenda. Even though the generalization of such games in directed networks is well understood in terms of the price of stability (it is exactly ,angelo fanelli,Not available,2013.0,10.1007/s00224-012-9411-6,Theory of Computing Systems,Vittorio2013,False,,Springer,Not available,Improved Lower Bounds on the Price of Stability of Undirected Network Design Games,511d9787e09b554098f9011bc0de5e9b,http://dx.doi.org/10.1007/s00224-012-9411-6
707,Bounding the price of stability of undirected network design games with fair cost allocation is a challenging open problem in the Algorithmic Game Theory research agenda. Even though the generalization of such games in directed networks is well understood in terms of the price of stability (it is exactly ,gianpiero monaco,Not available,2013.0,10.1007/s00224-012-9411-6,Theory of Computing Systems,Vittorio2013,False,,Springer,Not available,Improved Lower Bounds on the Price of Stability of Undirected Network Design Games,511d9787e09b554098f9011bc0de5e9b,http://dx.doi.org/10.1007/s00224-012-9411-6
708,Globally operating suppliers face the rising challenge of wholesale pricing under scarce data about retail demand  in contrast to better informed  locally operating retailers. At the same time  as local businesses proliferate  markets congest and retail competition increases. To capture these strategic considerations  we employ the classic Cournot model and extend it to a two-stage supply chain with an upstream supplier who operates under demand uncertainty and multiple downstream retailers who compete over quantity. The supplier’s belief about retail demand is modeled via a continuous probability distribution function ,costis melolidakis,Not available,2018.0,10.1007/978-3-319-99383-6_21,Belief Functions: Theory and Applications,Costis2018,False,,Springer,Not available,Measuring Market Performance with Stochastic Demand: Price of Anarchy and Price of Uncertainty,22c259144d733592b1bdbb752fbd0c16,http://dx.doi.org/10.1007/978-3-319-99383-6_21
709,Globally operating suppliers face the rising challenge of wholesale pricing under scarce data about retail demand  in contrast to better informed  locally operating retailers. At the same time  as local businesses proliferate  markets congest and retail competition increases. To capture these strategic considerations  we employ the classic Cournot model and extend it to a two-stage supply chain with an upstream supplier who operates under demand uncertainty and multiple downstream retailers who compete over quantity. The supplier’s belief about retail demand is modeled via a continuous probability distribution function ,stefanos leonardos,Not available,2018.0,10.1007/978-3-319-99383-6_21,Belief Functions: Theory and Applications,Costis2018,False,,Springer,Not available,Measuring Market Performance with Stochastic Demand: Price of Anarchy and Price of Uncertainty,22c259144d733592b1bdbb752fbd0c16,http://dx.doi.org/10.1007/978-3-319-99383-6_21
710,Globally operating suppliers face the rising challenge of wholesale pricing under scarce data about retail demand  in contrast to better informed  locally operating retailers. At the same time  as local businesses proliferate  markets congest and retail competition increases. To capture these strategic considerations  we employ the classic Cournot model and extend it to a two-stage supply chain with an upstream supplier who operates under demand uncertainty and multiple downstream retailers who compete over quantity. The supplier’s belief about retail demand is modeled via a continuous probability distribution function ,constandina koki,Not available,2018.0,10.1007/978-3-319-99383-6_21,Belief Functions: Theory and Applications,Costis2018,False,,Springer,Not available,Measuring Market Performance with Stochastic Demand: Price of Anarchy and Price of Uncertainty,22c259144d733592b1bdbb752fbd0c16,http://dx.doi.org/10.1007/978-3-319-99383-6_21
711,This chapter considers three fundamental problems in the general area of communication networks and their relationship to game theory. These problems are (i) allocation of shared bandwidth resources  (ii) routing across shared links  and (iii) scheduling across shared spectrum. Each problem inherently involves agents that experience negative externalities under which the presence of one degrades the utility perceived by others. Two approaches to solving such problems are (i) to find a globally optimal allocation and simply implement it in a fait accompli fashion  and (ii) request information from the competing agents (traffic flows) and construct a mechanism to allocate resources. Often  only the second option is viable  since a centralized solution using complete information might be impractical (or impossible) with many millions of competing flows  each one having private information about the application that it corresponds to. Hence  a game theoretical analysis of these problems is natural. In what follows  we will present results on each problem and characterize the efficiency loss that results from the mechanism employed.,srinivas shakkottai,Not available,2018.0,10.1007/978-3-319-44374-4_29,Handbook of Dynamic Game Theory,Srinivas2018,False,,Springer,Not available,Communication Networks: Pricing  Congestion Control  Routing  and Scheduling,43abe857420eb52b5d6690a7d2f856b2,http://dx.doi.org/10.1007/978-3-319-44374-4_29
712,We address the classical uniformly related machine scheduling problem with minsum objective. The problem is solvable in polynomial time by the algorithm of Horowitz and Sahni. In that solution  each machine sequences its jobs shortest first. However when jobs may choose the machine on which they are processed  while keeping the same sequencing rule per machine  the resulting Nash equilibria are in general not optimal. The price of anarchy measures this optimality gap. By means of a new characterization of the optimal solution  we show that the price of anarchy in this setting is bounded from above by 2. We also give a lower bound of ,ruben hoeksma,Not available,2012.0,10.1007/978-3-642-29116-6_22,Approximation and Online Algorithms,Ruben2012,False,,Springer,Not available,The Price of Anarchy for Minsum Related Machine Scheduling,8e2dc52cc1d243c4b68701fa0cd0b4e8,http://dx.doi.org/10.1007/978-3-642-29116-6_22
713,This chapter considers three fundamental problems in the general area of communication networks and their relationship to game theory. These problems are (i) allocation of shared bandwidth resources  (ii) routing across shared links  and (iii) scheduling across shared spectrum. Each problem inherently involves agents that experience negative externalities under which the presence of one degrades the utility perceived by others. Two approaches to solving such problems are (i) to find a globally optimal allocation and simply implement it in a fait accompli fashion  and (ii) request information from the competing agents (traffic flows) and construct a mechanism to allocate resources. Often  only the second option is viable  since a centralized solution using complete information might be impractical (or impossible) with many millions of competing flows  each one having private information about the application that it corresponds to. Hence  a game theoretical analysis of these problems is natural. In what follows  we will present results on each problem and characterize the efficiency loss that results from the mechanism employed.,r. srikant,Not available,2018.0,10.1007/978-3-319-44374-4_29,Handbook of Dynamic Game Theory,Srinivas2018,False,,Springer,Not available,Communication Networks: Pricing  Congestion Control  Routing  and Scheduling,43abe857420eb52b5d6690a7d2f856b2,http://dx.doi.org/10.1007/978-3-319-44374-4_29
714,We prove a tight lower bound on the asymptotic performance ratio ,yoshiharu kohayakawa,Not available,2018.0,10.1007/978-3-319-77404-6_51,LATIN 2018: Theoretical Informatics,Yoshiharu2018,False,,Springer,Not available,A Tight Lower Bound for an Online Hypercube Packing Problem and Bounds for Prices of Anarchy of a Related Game,dc7dac690c4fde60b99bc748937362b0,http://dx.doi.org/10.1007/978-3-319-77404-6_51
715,We prove a tight lower bound on the asymptotic performance ratio ,flavio miyazawa,Not available,2018.0,10.1007/978-3-319-77404-6_51,LATIN 2018: Theoretical Informatics,Yoshiharu2018,False,,Springer,Not available,A Tight Lower Bound for an Online Hypercube Packing Problem and Bounds for Prices of Anarchy of a Related Game,dc7dac690c4fde60b99bc748937362b0,http://dx.doi.org/10.1007/978-3-319-77404-6_51
716,We prove a tight lower bound on the asymptotic performance ratio ,yoshiko wakabayashi,Not available,2018.0,10.1007/978-3-319-77404-6_51,LATIN 2018: Theoretical Informatics,Yoshiharu2018,False,,Springer,Not available,A Tight Lower Bound for an Online Hypercube Packing Problem and Bounds for Prices of Anarchy of a Related Game,dc7dac690c4fde60b99bc748937362b0,http://dx.doi.org/10.1007/978-3-319-77404-6_51
717,We consider social distance games  where a group of utility maximizing players  connected over a network representing social proximity  wish to form coalitions (or clusters) so that they are grouped together with players that are at close distance. Given a cluster  the utility of each player depends on its distance to the other players inside the cluster and on the cluster size  and a player will deviate to another cluster if this leads to higher utility. We are interested in Nash equilibria of such games  where no player has an incentive to unilaterally deviate to another cluster  and we present bounds on the price of stability both for the normal utility function and for a slightly modified one.,christos kaklamanis,Not available,2018.0,10.1007/978-3-319-99660-8_12,Algorithmic Game Theory,Christos2018,False,,Springer,Not available,On the Price of Stability of Social Distance Games,c96125b465ffe683c182fe71b42e39af,http://dx.doi.org/10.1007/978-3-319-99660-8_12
718,We consider social distance games  where a group of utility maximizing players  connected over a network representing social proximity  wish to form coalitions (or clusters) so that they are grouped together with players that are at close distance. Given a cluster  the utility of each player depends on its distance to the other players inside the cluster and on the cluster size  and a player will deviate to another cluster if this leads to higher utility. We are interested in Nash equilibria of such games  where no player has an incentive to unilaterally deviate to another cluster  and we present bounds on the price of stability both for the normal utility function and for a slightly modified one.,panagiotis kanellopoulos,Not available,2018.0,10.1007/978-3-319-99660-8_12,Algorithmic Game Theory,Christos2018,False,,Springer,Not available,On the Price of Stability of Social Distance Games,c96125b465ffe683c182fe71b42e39af,http://dx.doi.org/10.1007/978-3-319-99660-8_12
719,We consider social distance games  where a group of utility maximizing players  connected over a network representing social proximity  wish to form coalitions (or clusters) so that they are grouped together with players that are at close distance. Given a cluster  the utility of each player depends on its distance to the other players inside the cluster and on the cluster size  and a player will deviate to another cluster if this leads to higher utility. We are interested in Nash equilibria of such games  where no player has an incentive to unilaterally deviate to another cluster  and we present bounds on the price of stability both for the normal utility function and for a slightly modified one.,dimitris patouchas,Not available,2018.0,10.1007/978-3-319-99660-8_12,Algorithmic Game Theory,Christos2018,False,,Springer,Not available,On the Price of Stability of Social Distance Games,c96125b465ffe683c182fe71b42e39af,http://dx.doi.org/10.1007/978-3-319-99660-8_12
720,In supply chain management  it is prevalent to design contract for coordination or proper risk-sharing in the supply chain. However  when a supply chain contract is developed based on the concept of expectation (e.g.  expected profit)  there is uncertainty risk with respect to the contract value which arises from various uncertainties inherent in the supply chain  such as demand uncertainty  price uncertainty  etc. We call such uncertainty risk associated with the contract ,yingxue zhao,Not available,2017.0,10.1007/s10479-014-1689-0,Annals of Operations Research,Yingxue2017,False,,Springer,Not available,Mean-risk analysis of wholesale price contracts with stochastic price-dependent demand,48d49678d02b7ea37e82251cbad06152,http://dx.doi.org/10.1007/s10479-014-1689-0
721,In supply chain management  it is prevalent to design contract for coordination or proper risk-sharing in the supply chain. However  when a supply chain contract is developed based on the concept of expectation (e.g.  expected profit)  there is uncertainty risk with respect to the contract value which arises from various uncertainties inherent in the supply chain  such as demand uncertainty  price uncertainty  etc. We call such uncertainty risk associated with the contract ,tsan-ming choi,Not available,2017.0,10.1007/s10479-014-1689-0,Annals of Operations Research,Yingxue2017,False,,Springer,Not available,Mean-risk analysis of wholesale price contracts with stochastic price-dependent demand,48d49678d02b7ea37e82251cbad06152,http://dx.doi.org/10.1007/s10479-014-1689-0
722,In supply chain management  it is prevalent to design contract for coordination or proper risk-sharing in the supply chain. However  when a supply chain contract is developed based on the concept of expectation (e.g.  expected profit)  there is uncertainty risk with respect to the contract value which arises from various uncertainties inherent in the supply chain  such as demand uncertainty  price uncertainty  etc. We call such uncertainty risk associated with the contract ,t. cheng,Not available,2017.0,10.1007/s10479-014-1689-0,Annals of Operations Research,Yingxue2017,False,,Springer,Not available,Mean-risk analysis of wholesale price contracts with stochastic price-dependent demand,48d49678d02b7ea37e82251cbad06152,http://dx.doi.org/10.1007/s10479-014-1689-0
723,We address the classical uniformly related machine scheduling problem with minsum objective. The problem is solvable in polynomial time by the algorithm of Horowitz and Sahni. In that solution  each machine sequences its jobs shortest first. However when jobs may choose the machine on which they are processed  while keeping the same sequencing rule per machine  the resulting Nash equilibria are in general not optimal. The price of anarchy measures this optimality gap. By means of a new characterization of the optimal solution  we show that the price of anarchy in this setting is bounded from above by 2. We also give a lower bound of ,marc uetz,Not available,2012.0,10.1007/978-3-642-29116-6_22,Approximation and Online Algorithms,Ruben2012,False,,Springer,Not available,The Price of Anarchy for Minsum Related Machine Scheduling,8e2dc52cc1d243c4b68701fa0cd0b4e8,http://dx.doi.org/10.1007/978-3-642-29116-6_22
724,In supply chain management  it is prevalent to design contract for coordination or proper risk-sharing in the supply chain. However  when a supply chain contract is developed based on the concept of expectation (e.g.  expected profit)  there is uncertainty risk with respect to the contract value which arises from various uncertainties inherent in the supply chain  such as demand uncertainty  price uncertainty  etc. We call such uncertainty risk associated with the contract ,shouyang wang,Not available,2017.0,10.1007/s10479-014-1689-0,Annals of Operations Research,Yingxue2017,False,,Springer,Not available,Mean-risk analysis of wholesale price contracts with stochastic price-dependent demand,48d49678d02b7ea37e82251cbad06152,http://dx.doi.org/10.1007/s10479-014-1689-0
725,Let ,daniel li,Not available,2017.0,10.1007/s10878-016-0099-4,Journal of Combinatorial Optimization,Li2017,False,,Springer,Not available,Cost sharing on prices for games on graphs,58849e03f4c51bf0742c189218799cd5,http://dx.doi.org/10.1007/s10878-016-0099-4
726,Let ,erfang shan,Not available,2017.0,10.1007/s10878-016-0099-4,Journal of Combinatorial Optimization,Li2017,False,,Springer,Not available,Cost sharing on prices for games on graphs,58849e03f4c51bf0742c189218799cd5,http://dx.doi.org/10.1007/s10878-016-0099-4
727,Hospital throughput is often studied and optimised in isolation  ignoring the interactions between hospitals. In this paper  critical care unit (CCU) interaction is placed within a game theoretic framework. The methodology involves the use of a normal form game underpinned by a two-dimensional continuous Markov chain. A theorem is given that proves that a Nash Equilibrium exists in pure strategies for the games considered. In the United Kingdom  a variety of utilisation targets are often discussed: aiming to ensure that wards/hospitals operate at a given utilisation value. The effect of these target policies is investigated justifying their use to align the interests of individual hospitals and social welfare. In particular  we identify the lowest value of a utilisation target that aligns these.,vincent knight,Not available,2017.0,10.1057/s41274-016-0100-8,Journal of the Operational Research Society,Vincent2017,True,,Springer,Not available,Measuring the price of anarchy in critical care unit interactions,c30e64213c711bb789654f2fbc57820f,http://dx.doi.org/10.1057/s41274-016-0100-8
728,Hospital throughput is often studied and optimised in isolation  ignoring the interactions between hospitals. In this paper  critical care unit (CCU) interaction is placed within a game theoretic framework. The methodology involves the use of a normal form game underpinned by a two-dimensional continuous Markov chain. A theorem is given that proves that a Nash Equilibrium exists in pure strategies for the games considered. In the United Kingdom  a variety of utilisation targets are often discussed: aiming to ensure that wards/hospitals operate at a given utilisation value. The effect of these target policies is investigated justifying their use to align the interests of individual hospitals and social welfare. In particular  we identify the lowest value of a utilisation target that aligns these.,izabela komenda,Not available,2017.0,10.1057/s41274-016-0100-8,Journal of the Operational Research Society,Vincent2017,True,,Springer,Not available,Measuring the price of anarchy in critical care unit interactions,c30e64213c711bb789654f2fbc57820f,http://dx.doi.org/10.1057/s41274-016-0100-8
729,Hospital throughput is often studied and optimised in isolation  ignoring the interactions between hospitals. In this paper  critical care unit (CCU) interaction is placed within a game theoretic framework. The methodology involves the use of a normal form game underpinned by a two-dimensional continuous Markov chain. A theorem is given that proves that a Nash Equilibrium exists in pure strategies for the games considered. In the United Kingdom  a variety of utilisation targets are often discussed: aiming to ensure that wards/hospitals operate at a given utilisation value. The effect of these target policies is investigated justifying their use to align the interests of individual hospitals and social welfare. In particular  we identify the lowest value of a utilisation target that aligns these.,jeff griffiths,Not available,2017.0,10.1057/s41274-016-0100-8,Journal of the Operational Research Society,Vincent2017,True,,Springer,Not available,Measuring the price of anarchy in critical care unit interactions,c30e64213c711bb789654f2fbc57820f,http://dx.doi.org/10.1057/s41274-016-0100-8
730,This paper evaluates industry-wide economic incentives arising from changes in product prices in an industry exploiting a common renewable resource (tropical tunas) that is regulated via output limits. Changes in prices alter economic incentives by affecting revenues  profits  conservation  and nonmarket public benefits. Economic incentives in industries exploiting common resources have been examined from multiple angles. However  industry level variation in market prices arising from changes in public regulation has not been explored. We analyse the impact on economic incentives due to changes in output limits and market prices through estimation of ex-vessel price and scale flexibilities for imported skipjack and yellowfin in Thailand’s cannery market. The unitary scale flexibility  estimated from the General Synthetic Inverse Demand Systems  indicates no loss in revenue and even potential profit increases resulting from lower harvest levels that could arise from lower catch limits. However  for a revenue neutral or positive outcome to be achieved  the three inter-governmental tuna Regional Fisheries Management Organizations  which manage the majority of the yellowfin and skipjack tuna in the Pacific and Indian Oceans  would have to coordinate multilaterally to set the catch limits for both species.,chin-hwa sun,Not available,2017.0,10.1007/s10640-015-9971-4,Environmental and Resource Economics,Jenny2017,False,,Springer,Not available,Fewer Fish for Higher Profits? Price Response and Economic Incentives in Global Tuna Fisheries Management,139488d30a93c313542609023fbd3597,http://dx.doi.org/10.1007/s10640-015-9971-4
731,This paper evaluates industry-wide economic incentives arising from changes in product prices in an industry exploiting a common renewable resource (tropical tunas) that is regulated via output limits. Changes in prices alter economic incentives by affecting revenues  profits  conservation  and nonmarket public benefits. Economic incentives in industries exploiting common resources have been examined from multiple angles. However  industry level variation in market prices arising from changes in public regulation has not been explored. We analyse the impact on economic incentives due to changes in output limits and market prices through estimation of ex-vessel price and scale flexibilities for imported skipjack and yellowfin in Thailand’s cannery market. The unitary scale flexibility  estimated from the General Synthetic Inverse Demand Systems  indicates no loss in revenue and even potential profit increases resulting from lower harvest levels that could arise from lower catch limits. However  for a revenue neutral or positive outcome to be achieved  the three inter-governmental tuna Regional Fisheries Management Organizations  which manage the majority of the yellowfin and skipjack tuna in the Pacific and Indian Oceans  would have to coordinate multilaterally to set the catch limits for both species.,fu-sung chiang,Not available,2017.0,10.1007/s10640-015-9971-4,Environmental and Resource Economics,Jenny2017,False,,Springer,Not available,Fewer Fish for Higher Profits? Price Response and Economic Incentives in Global Tuna Fisheries Management,139488d30a93c313542609023fbd3597,http://dx.doi.org/10.1007/s10640-015-9971-4
732,This paper evaluates industry-wide economic incentives arising from changes in product prices in an industry exploiting a common renewable resource (tropical tunas) that is regulated via output limits. Changes in prices alter economic incentives by affecting revenues  profits  conservation  and nonmarket public benefits. Economic incentives in industries exploiting common resources have been examined from multiple angles. However  industry level variation in market prices arising from changes in public regulation has not been explored. We analyse the impact on economic incentives due to changes in output limits and market prices through estimation of ex-vessel price and scale flexibilities for imported skipjack and yellowfin in Thailand’s cannery market. The unitary scale flexibility  estimated from the General Synthetic Inverse Demand Systems  indicates no loss in revenue and even potential profit increases resulting from lower harvest levels that could arise from lower catch limits. However  for a revenue neutral or positive outcome to be achieved  the three inter-governmental tuna Regional Fisheries Management Organizations  which manage the majority of the yellowfin and skipjack tuna in the Pacific and Indian Oceans  would have to coordinate multilaterally to set the catch limits for both species.,patrice guillotreau,Not available,2017.0,10.1007/s10640-015-9971-4,Environmental and Resource Economics,Jenny2017,False,,Springer,Not available,Fewer Fish for Higher Profits? Price Response and Economic Incentives in Global Tuna Fisheries Management,139488d30a93c313542609023fbd3597,http://dx.doi.org/10.1007/s10640-015-9971-4
733,This paper evaluates industry-wide economic incentives arising from changes in product prices in an industry exploiting a common renewable resource (tropical tunas) that is regulated via output limits. Changes in prices alter economic incentives by affecting revenues  profits  conservation  and nonmarket public benefits. Economic incentives in industries exploiting common resources have been examined from multiple angles. However  industry level variation in market prices arising from changes in public regulation has not been explored. We analyse the impact on economic incentives due to changes in output limits and market prices through estimation of ex-vessel price and scale flexibilities for imported skipjack and yellowfin in Thailand’s cannery market. The unitary scale flexibility  estimated from the General Synthetic Inverse Demand Systems  indicates no loss in revenue and even potential profit increases resulting from lower harvest levels that could arise from lower catch limits. However  for a revenue neutral or positive outcome to be achieved  the three inter-governmental tuna Regional Fisheries Management Organizations  which manage the majority of the yellowfin and skipjack tuna in the Pacific and Indian Oceans  would have to coordinate multilaterally to set the catch limits for both species.,dale squires,Not available,2017.0,10.1007/s10640-015-9971-4,Environmental and Resource Economics,Jenny2017,False,,Springer,Not available,Fewer Fish for Higher Profits? Price Response and Economic Incentives in Global Tuna Fisheries Management,139488d30a93c313542609023fbd3597,http://dx.doi.org/10.1007/s10640-015-9971-4
734,We study the price of anarchy of a trading mechanism for divisible goods in markets containing both producers and consumers (i.e. in two-sided markets). Each producer is asked to submit a linear pricing function (or  equivalently  a linear supply function) that specifies a per-unit price ,volodymyr kuleshov,Not available,2012.0,10.1007/978-3-642-35311-6_21,Internet and Network Economics,Volodymyr2012,False,,Springer,Not available,On the Efficiency of the Simplest Pricing Mechanisms in Two-Sided Markets,1329d6fdccd7fefa1d7898669316e42d,http://dx.doi.org/10.1007/978-3-642-35311-6_21
735,This paper evaluates industry-wide economic incentives arising from changes in product prices in an industry exploiting a common renewable resource (tropical tunas) that is regulated via output limits. Changes in prices alter economic incentives by affecting revenues  profits  conservation  and nonmarket public benefits. Economic incentives in industries exploiting common resources have been examined from multiple angles. However  industry level variation in market prices arising from changes in public regulation has not been explored. We analyse the impact on economic incentives due to changes in output limits and market prices through estimation of ex-vessel price and scale flexibilities for imported skipjack and yellowfin in Thailand’s cannery market. The unitary scale flexibility  estimated from the General Synthetic Inverse Demand Systems  indicates no loss in revenue and even potential profit increases resulting from lower harvest levels that could arise from lower catch limits. However  for a revenue neutral or positive outcome to be achieved  the three inter-governmental tuna Regional Fisheries Management Organizations  which manage the majority of the yellowfin and skipjack tuna in the Pacific and Indian Oceans  would have to coordinate multilaterally to set the catch limits for both species.,d. webster,Not available,2017.0,10.1007/s10640-015-9971-4,Environmental and Resource Economics,Jenny2017,False,,Springer,Not available,Fewer Fish for Higher Profits? Price Response and Economic Incentives in Global Tuna Fisheries Management,139488d30a93c313542609023fbd3597,http://dx.doi.org/10.1007/s10640-015-9971-4
736,This paper evaluates industry-wide economic incentives arising from changes in product prices in an industry exploiting a common renewable resource (tropical tunas) that is regulated via output limits. Changes in prices alter economic incentives by affecting revenues  profits  conservation  and nonmarket public benefits. Economic incentives in industries exploiting common resources have been examined from multiple angles. However  industry level variation in market prices arising from changes in public regulation has not been explored. We analyse the impact on economic incentives due to changes in output limits and market prices through estimation of ex-vessel price and scale flexibilities for imported skipjack and yellowfin in Thailand’s cannery market. The unitary scale flexibility  estimated from the General Synthetic Inverse Demand Systems  indicates no loss in revenue and even potential profit increases resulting from lower harvest levels that could arise from lower catch limits. However  for a revenue neutral or positive outcome to be achieved  the three inter-governmental tuna Regional Fisheries Management Organizations  which manage the majority of the yellowfin and skipjack tuna in the Pacific and Indian Oceans  would have to coordinate multilaterally to set the catch limits for both species.,matt owens,Not available,2017.0,10.1007/s10640-015-9971-4,Environmental and Resource Economics,Jenny2017,False,,Springer,Not available,Fewer Fish for Higher Profits? Price Response and Economic Incentives in Global Tuna Fisheries Management,139488d30a93c313542609023fbd3597,http://dx.doi.org/10.1007/s10640-015-9971-4
737,We study the bilateral version of the adversary network formation game introduced by the author in 2010. In bilateral network formation  a link is formed only if both endpoints agree on it and then both have to pay the link cost ,lasse kliemann,Not available,2017.0,10.1007/s00453-016-0120-4,Algorithmica,Lasse2017,False,,Springer,Not available,The Price of Anarchy in Bilateral Network Formation in an Adversary Model,bcb1da0435cbf1b3c2d3327909bc5a18,http://dx.doi.org/10.1007/s00453-016-0120-4
738,This paper deals with a matching game in which the nodes of a simple graph are independent agents who try to form pairs. If we let the agents make their decision without any central control then a possible outcome is a Nash equilibrium  that is a situation in which no unmatched player can change his strategy and find a partner. However  there can be a big difference between two possible outcomes of the same instance  in terms of number of matched nodes. A possible solution is to force all the nodes to follow a centrally computed maximum matching but it can be difficult to implement this approach. This article proposes a tradeoff between the total absence and the full presence of a central control. Concretely  we study the optimization problem where the action of a ,bruno escoffier,Not available,2017.0,10.1007/s00453-015-0108-5,Algorithmica,Bruno2017,False,,Springer,Not available,The Price of Optimum: Complexity and Approximation for a Matching Game,ec3502323307798f30e098f0564fccb6,http://dx.doi.org/10.1007/s00453-015-0108-5
739,This paper deals with a matching game in which the nodes of a simple graph are independent agents who try to form pairs. If we let the agents make their decision without any central control then a possible outcome is a Nash equilibrium  that is a situation in which no unmatched player can change his strategy and find a partner. However  there can be a big difference between two possible outcomes of the same instance  in terms of number of matched nodes. A possible solution is to force all the nodes to follow a centrally computed maximum matching but it can be difficult to implement this approach. This article proposes a tradeoff between the total absence and the full presence of a central control. Concretely  we study the optimization problem where the action of a ,laurent gourves,Not available,2017.0,10.1007/s00453-015-0108-5,Algorithmica,Bruno2017,False,,Springer,Not available,The Price of Optimum: Complexity and Approximation for a Matching Game,ec3502323307798f30e098f0564fccb6,http://dx.doi.org/10.1007/s00453-015-0108-5
740,This paper deals with a matching game in which the nodes of a simple graph are independent agents who try to form pairs. If we let the agents make their decision without any central control then a possible outcome is a Nash equilibrium  that is a situation in which no unmatched player can change his strategy and find a partner. However  there can be a big difference between two possible outcomes of the same instance  in terms of number of matched nodes. A possible solution is to force all the nodes to follow a centrally computed maximum matching but it can be difficult to implement this approach. This article proposes a tradeoff between the total absence and the full presence of a central control. Concretely  we study the optimization problem where the action of a ,jerome monnot,Not available,2017.0,10.1007/s00453-015-0108-5,Algorithmica,Bruno2017,False,,Springer,Not available,The Price of Optimum: Complexity and Approximation for a Matching Game,ec3502323307798f30e098f0564fccb6,http://dx.doi.org/10.1007/s00453-015-0108-5
741,All justice ethics aim at finding balance between liberty and equality  between individual autonomy and the common good. However  each raises objections that demonstrate their own limitations. Three paradigms in which the theories fit will be presented  as well as four models that illustrate how the theories apply to bioethical problems. Moreover  the theoretical perception of justice has set the foundations for a multiplicity of responses given to the most prominent ethical questionings.,michel renaud,Not available,2016.0,10.1007/978-3-319-09483-0_260,Encyclopedia of Global Bioethics,Michel2016,False,,Springer,Not available,Justice: Theories of,10c1d18af22b810f037c1c9f157a0329,http://dx.doi.org/10.1007/978-3-319-09483-0_260
742,All justice ethics aim at finding balance between liberty and equality  between individual autonomy and the common good. However  each raises objections that demonstrate their own limitations. Three paradigms in which the theories fit will be presented  as well as four models that illustrate how the theories apply to bioethical problems. Moreover  the theoretical perception of justice has set the foundations for a multiplicity of responses given to the most prominent ethical questionings.,cintia aguas,Not available,2016.0,10.1007/978-3-319-09483-0_260,Encyclopedia of Global Bioethics,Michel2016,False,,Springer,Not available,Justice: Theories of,10c1d18af22b810f037c1c9f157a0329,http://dx.doi.org/10.1007/978-3-319-09483-0_260
743,In this paper  we studied the coordination of the supply chain consisting of one retailer and one supplier  where the market demand is uncertain. The combination of the Wholesale Price Contract and Option Contract is used to solve the problem that market risk is borne independently by the supplier. The theoretical analysis shows that the strategy can share the risk between members of the supply chain  i.e.  the supplier’s risk reduced  and the supply chain system profit can be rationally distributed  the supply chain can be coordinated and a win-win situation can be achieved by choosing appropriate option price. Finally  the numerical examples were given to verify this conclusion.,tian-yuan liu,Not available,2016.0,10.2991/978-94-6239-180-2_44,Proceedings of the 22nd International Conference on Industrial Engineering and Engineering Management 2015,Tian-yuan2016,False,,Springer,Not available,On the Coordination of Supply Chain with Demand Uncertainty Under the Combination of the Wholesale Price Contract and Option Contract,936c899bbf8299a2c71b526aa95d847b,http://dx.doi.org/10.2991/978-94-6239-180-2_44
744,In this paper  we studied the coordination of the supply chain consisting of one retailer and one supplier  where the market demand is uncertain. The combination of the Wholesale Price Contract and Option Contract is used to solve the problem that market risk is borne independently by the supplier. The theoretical analysis shows that the strategy can share the risk between members of the supply chain  i.e.  the supplier’s risk reduced  and the supply chain system profit can be rationally distributed  the supply chain can be coordinated and a win-win situation can be achieved by choosing appropriate option price. Finally  the numerical examples were given to verify this conclusion.,jiang-tao mo,Not available,2016.0,10.2991/978-94-6239-180-2_44,Proceedings of the 22nd International Conference on Industrial Engineering and Engineering Management 2015,Tian-yuan2016,False,,Springer,Not available,On the Coordination of Supply Chain with Demand Uncertainty Under the Combination of the Wholesale Price Contract and Option Contract,936c899bbf8299a2c71b526aa95d847b,http://dx.doi.org/10.2991/978-94-6239-180-2_44
745,We study the price of anarchy of a trading mechanism for divisible goods in markets containing both producers and consumers (i.e. in two-sided markets). Each producer is asked to submit a linear pricing function (or  equivalently  a linear supply function) that specifies a per-unit price ,gordon wilfong,Not available,2012.0,10.1007/978-3-642-35311-6_21,Internet and Network Economics,Volodymyr2012,False,,Springer,Not available,On the Efficiency of the Simplest Pricing Mechanisms in Two-Sided Markets,1329d6fdccd7fefa1d7898669316e42d,http://dx.doi.org/10.1007/978-3-642-35311-6_21
746,In this paper  we studied the coordination of the supply chain consisting of one retailer and one supplier  where the market demand is uncertain. The combination of the Wholesale Price Contract and Option Contract is used to solve the problem that market risk is borne independently by the supplier. The theoretical analysis shows that the strategy can share the risk between members of the supply chain  i.e.  the supplier’s risk reduced  and the supply chain system profit can be rationally distributed  the supply chain can be coordinated and a win-win situation can be achieved by choosing appropriate option price. Finally  the numerical examples were given to verify this conclusion.,si-yao tang,Not available,2016.0,10.2991/978-94-6239-180-2_44,Proceedings of the 22nd International Conference on Industrial Engineering and Engineering Management 2015,Tian-yuan2016,False,,Springer,Not available,On the Coordination of Supply Chain with Demand Uncertainty Under the Combination of the Wholesale Price Contract and Option Contract,936c899bbf8299a2c71b526aa95d847b,http://dx.doi.org/10.2991/978-94-6239-180-2_44
747,"Recent spikes in international food prices and the occurrence of food riots in the period 2007–2008 have led many researchers to investigate more closely the links between rising food prices and conflict or political instability. However  this emerging literature suffers from a number of shortcomings. The objective of this article is to analyze these shortcomings further  highlight their theoretical and empirical implications  and offer ways of addressing them. I focus on three main issues. First  I look at the recurring lack of precision in the use of concepts such as political instability and conflict  and in particular the food riot concept itself. Second  I examine the often uncritical data gathering based on framing by media sources without a closer analysis of the events that took place on the ground. And third  I focus on the issue of presupposed and understudied economic as well as political causal mechanisms.,Récemment  la hausse des prix mondiaux des denrées alimentaires et les émeutes de la faim en 2007–2008 ont amené de nombreux chercheurs à étudier de plus près les liens entre la hausse des prix des denrées alimentaires et le conflit ou l’instabilité politique. Cependant  ce corps émergent d’ouvrages sur le sujet souffre de plusieurs lacunes. L’objectif de cet article est d’aller plus loin dans l’analyse de ces lacunes  de mettre en avant leurs implications théoriques et empiriques  et d’offrir des solutions pour les combler. Je me focalise sur trois problèmes principaux: tout d’abord  un manque de précision récurrent dans l’utilisation de concepts tels que l’instabilité politique ou le conflit  et en particulier pour le concept d’émeute de la faim lui-même. Ensuite  les données collectées par les média en fonction de leur agenda  souvent manquant de sens critique et d’analyse approfondie des évènements qui ont lieux sur place. Enfin  la problématique des mécanismes de cause à effet politiques et économiques  qui restent insuffisamment étudiés et basés sur des suppositions.",leila demarest,Not available,2015.0,10.1057/ejdr.2014.52,The European Journal of Development Research,Leila2015,False,,Springer,Not available,Food Price Rises and Political Instability: Problematizing a Complex Relationship,77da6232e8f95e7ad391a1282106a46e,http://dx.doi.org/10.1057/ejdr.2014.52
748,We study the Uniform Price Auction  one of the standard sealed-bid multi-unit auction formats in Auction Theory  for selling multiple identical units of a single good to multi-demand bidders. Contrary to the truthful and efficient multi-unit Vickrey auction  the Uniform Price Auction encourages strategic bidding and is generally inefficient  due to a “Demand Reduction” effect; bidders tend to bid for fewer (identical) units  so as to receive them at a lower uniform price. All the same  the uniform pricing rule is popular by its appeal to the anticipation that identical items should be identically priced. Its applications include  among others  sales of U.S. Treasury notes to investors and trade exchanges over the Internet facilitated by popular online brokers. In this work  we characterize pure undominated bidding strategies and give an algorithm for computing pure Nash equilibria in such strategies. Subsequently we show that their Price of Anarchy is ,evangelos markakis,Not available,2015.0,10.1007/s00224-014-9537-9,Theory of Computing Systems,Evangelos2015,False,,Springer,Not available,Uniform Price Auctions: Equilibria and Efficiency,eb3c05f68d391d2253a037224d3141d4,http://dx.doi.org/10.1007/s00224-014-9537-9
749,We study the Uniform Price Auction  one of the standard sealed-bid multi-unit auction formats in Auction Theory  for selling multiple identical units of a single good to multi-demand bidders. Contrary to the truthful and efficient multi-unit Vickrey auction  the Uniform Price Auction encourages strategic bidding and is generally inefficient  due to a “Demand Reduction” effect; bidders tend to bid for fewer (identical) units  so as to receive them at a lower uniform price. All the same  the uniform pricing rule is popular by its appeal to the anticipation that identical items should be identically priced. Its applications include  among others  sales of U.S. Treasury notes to investors and trade exchanges over the Internet facilitated by popular online brokers. In this work  we characterize pure undominated bidding strategies and give an algorithm for computing pure Nash equilibria in such strategies. Subsequently we show that their Price of Anarchy is ,orestis telelis,Not available,2015.0,10.1007/s00224-014-9537-9,Theory of Computing Systems,Evangelos2015,False,,Springer,Not available,Uniform Price Auctions: Equilibria and Efficiency,eb3c05f68d391d2253a037224d3141d4,http://dx.doi.org/10.1007/s00224-014-9537-9
750,We study a ,michal feldman,Not available,2015.0,10.1007/s00224-014-9540-1,Theory of Computing Systems,Michal2015,False,,Springer,Not available,Capacitated Network Design Games,2fcd7edd054db457698e8a92d36b7575,http://dx.doi.org/10.1007/s00224-014-9540-1
751,We study a ,tom ron,Not available,2015.0,10.1007/s00224-014-9540-1,Theory of Computing Systems,Michal2015,False,,Springer,Not available,Capacitated Network Design Games,2fcd7edd054db457698e8a92d36b7575,http://dx.doi.org/10.1007/s00224-014-9540-1
752,How and why people form ties is a critical issue for understanding the fabric of social networks. In contrast to most existing work  we are interested in settings where agents are neither so myopic as to consider only the benefit they derive from their immediate neighbors  nor do they consider the effects on the entire network when forming connections. Instead  we consider games on networks where a node tries to maximize its utility taking into account the benefit it gets from the nodes it is directly connected to (called ,elliot anshelevich,Not available,2015.0,10.1007/s00224-014-9582-4,Theory of Computing Systems,Elliot2015,False,,Springer,Not available,Friend of My Friend: Network Formation with Two-Hop Benefit,3df99eea1953ed82588c796ca1f9b89f,http://dx.doi.org/10.1007/s00224-014-9582-4
753,How and why people form ties is a critical issue for understanding the fabric of social networks. In contrast to most existing work  we are interested in settings where agents are neither so myopic as to consider only the benefit they derive from their immediate neighbors  nor do they consider the effects on the entire network when forming connections. Instead  we consider games on networks where a node tries to maximize its utility taking into account the benefit it gets from the nodes it is directly connected to (called ,onkar bhardwaj,Not available,2015.0,10.1007/s00224-014-9582-4,Theory of Computing Systems,Elliot2015,False,,Springer,Not available,Friend of My Friend: Network Formation with Two-Hop Benefit,3df99eea1953ed82588c796ca1f9b89f,http://dx.doi.org/10.1007/s00224-014-9582-4
754,How and why people form ties is a critical issue for understanding the fabric of social networks. In contrast to most existing work  we are interested in settings where agents are neither so myopic as to consider only the benefit they derive from their immediate neighbors  nor do they consider the effects on the entire network when forming connections. Instead  we consider games on networks where a node tries to maximize its utility taking into account the benefit it gets from the nodes it is directly connected to (called ,michael usher,Not available,2015.0,10.1007/s00224-014-9582-4,Theory of Computing Systems,Elliot2015,False,,Springer,Not available,Friend of My Friend: Network Formation with Two-Hop Benefit,3df99eea1953ed82588c796ca1f9b89f,http://dx.doi.org/10.1007/s00224-014-9582-4
755,Many are worried that the global food system is entering a period of intense volatility driven by a combination of climate change and population growth. One way to address this problem is for governments and the international community to store more food as a buffer against crisis. The purpose of this paper is to explore the role of food storage as a component of a robust food security strategy in the twenty-first century. We do this by first drawing on historical examples from ancient Rome and China  where preindustrial government designed extensive systems that ensured adequate food storage to keep food systems stable. Next  we review the links between food storage and price volatility in the last 20 years and demonstrate that the size of food stores (and in particular grain reserves) directly relates to price volatility. Third  we explore three different types of policies designed to promote grain reserves  the US’s “ever-normal granary” policy  the EU’s Common Agricultural Policy  and the Strategic Grain Reserve in Africa. In this third section  we show how there has been a decline from state-owned strategic grain reserves in favor of a more market-oriented approach that is dominated by a handful of powerful corporations who maintain sophisticated supply chains. Because data on the amount of food supply these corporations hold in storage are proprietary secrets  it is impossible to assess how resilient or vulnerable this makes our food system. Finally  we conclude that over time  food storage has fallen in and out of favor  criticized for being expensive yet often shown to play an important role in protecting poor consumers in times of food crisis. Given the lack of data on current levels of supply chain and household storage  more research is needed to evaluate the scale at which food storage systems should be implemented to ensure food system resilience as well as the most effective mechanisms to govern and manage them.,evan fraser,Not available,2015.0,10.1007/s13412-015-0276-2,Journal of Environmental Studies and Sciences,G.2015,False,,Springer,Not available,Food stocks and grain reserves: evaluating whether storing food creates resilient food systems,83b2a0e39262b6679a4f74ebe94b96ee,http://dx.doi.org/10.1007/s13412-015-0276-2
756,We present our results on Uniform Price Auctions  one of the standard sealed-bid multi-unit auction formats  for selling multiple identical units of a single good to multi-demand bidders. Contrary to the truthful and economically efficient multi-unit Vickrey auction  the Uniform Price Auction encourages strategic bidding and is socially inefficient in general  partly due to a ”Demand Reduction” effect; bidders tend to bid for fewer (identical) units  so as to receive them at a lower uniform price. Despite its inefficiency  the uniform pricing rule is widely popular by its appeal to the natural anticipation  that identical items should be identically priced. Application domains of its variants include sales of U.S. Treasury bonds to investors  trade exchanges over the internet facilitated by popular online brokers  allocation of radio spectrum licenses etc. In this work we study equilibria of the Uniform Price Auction in undominated strategies. We characterize a class of undominated pure Nash equilibria and quantify the social inefficiency of pure and (mixed) Bayes-Nash equilibria by means of bounds on the Price of Anarchy.,evangelos markakis,Not available,2012.0,10.1007/978-3-642-33996-7_20,Algorithmic Game Theory,Evangelos2012,False,,Springer,Not available,Uniform Price Auctions: Equilibria and Efficiency,b11d0a076e78797908baa3e9cbe37e67,http://dx.doi.org/10.1007/978-3-642-33996-7_20
757,Many are worried that the global food system is entering a period of intense volatility driven by a combination of climate change and population growth. One way to address this problem is for governments and the international community to store more food as a buffer against crisis. The purpose of this paper is to explore the role of food storage as a component of a robust food security strategy in the twenty-first century. We do this by first drawing on historical examples from ancient Rome and China  where preindustrial government designed extensive systems that ensured adequate food storage to keep food systems stable. Next  we review the links between food storage and price volatility in the last 20 years and demonstrate that the size of food stores (and in particular grain reserves) directly relates to price volatility. Third  we explore three different types of policies designed to promote grain reserves  the US’s “ever-normal granary” policy  the EU’s Common Agricultural Policy  and the Strategic Grain Reserve in Africa. In this third section  we show how there has been a decline from state-owned strategic grain reserves in favor of a more market-oriented approach that is dominated by a handful of powerful corporations who maintain sophisticated supply chains. Because data on the amount of food supply these corporations hold in storage are proprietary secrets  it is impossible to assess how resilient or vulnerable this makes our food system. Finally  we conclude that over time  food storage has fallen in and out of favor  criticized for being expensive yet often shown to play an important role in protecting poor consumers in times of food crisis. Given the lack of data on current levels of supply chain and household storage  more research is needed to evaluate the scale at which food storage systems should be implemented to ensure food system resilience as well as the most effective mechanisms to govern and manage them.,alexander legwegoh,Not available,2015.0,10.1007/s13412-015-0276-2,Journal of Environmental Studies and Sciences,G.2015,False,,Springer,Not available,Food stocks and grain reserves: evaluating whether storing food creates resilient food systems,83b2a0e39262b6679a4f74ebe94b96ee,http://dx.doi.org/10.1007/s13412-015-0276-2
758,Many are worried that the global food system is entering a period of intense volatility driven by a combination of climate change and population growth. One way to address this problem is for governments and the international community to store more food as a buffer against crisis. The purpose of this paper is to explore the role of food storage as a component of a robust food security strategy in the twenty-first century. We do this by first drawing on historical examples from ancient Rome and China  where preindustrial government designed extensive systems that ensured adequate food storage to keep food systems stable. Next  we review the links between food storage and price volatility in the last 20 years and demonstrate that the size of food stores (and in particular grain reserves) directly relates to price volatility. Third  we explore three different types of policies designed to promote grain reserves  the US’s “ever-normal granary” policy  the EU’s Common Agricultural Policy  and the Strategic Grain Reserve in Africa. In this third section  we show how there has been a decline from state-owned strategic grain reserves in favor of a more market-oriented approach that is dominated by a handful of powerful corporations who maintain sophisticated supply chains. Because data on the amount of food supply these corporations hold in storage are proprietary secrets  it is impossible to assess how resilient or vulnerable this makes our food system. Finally  we conclude that over time  food storage has fallen in and out of favor  criticized for being expensive yet often shown to play an important role in protecting poor consumers in times of food crisis. Given the lack of data on current levels of supply chain and household storage  more research is needed to evaluate the scale at which food storage systems should be implemented to ensure food system resilience as well as the most effective mechanisms to govern and manage them.,krishna kc,Not available,2015.0,10.1007/s13412-015-0276-2,Journal of Environmental Studies and Sciences,G.2015,False,,Springer,Not available,Food stocks and grain reserves: evaluating whether storing food creates resilient food systems,83b2a0e39262b6679a4f74ebe94b96ee,http://dx.doi.org/10.1007/s13412-015-0276-2
759,This article argues that the price obtainable in an open market provides the best standard for determining the justice or injustice of the price of a product. The article argues that this standard  which is closely related to positions which have been held for hundreds of years  is superior to several alternative conceptions of the just price that have been put forward in recent years and is not subject to fundamental criticisms which can be addressed to them. The article also shows how this standard is grounded in more fundamental principles of justice such as desert and equality.,juan elegido,Not available,2015.0,10.1007/s10551-014-2240-6,Journal of Business Ethics,M.2015,False,,Springer,Not available,The Just Price as the Price Obtainable in an Open Market,4b27270eed3175511e742bfbf8e51123,http://dx.doi.org/10.1007/s10551-014-2240-6
760,We study the inefficiency of equilibrium outcomes in ,bart keijzer,Not available,2015.0,10.1007/s00224-014-9598-9,Theory of Computing Systems,de2015,False,,Springer,Not available,The Strong Price of Anarchy of Linear Bottleneck Congestion Games,21cac123ce887c1a76175059bfe7861d,http://dx.doi.org/10.1007/s00224-014-9598-9
761,We study the inefficiency of equilibrium outcomes in ,guido schafer,Not available,2015.0,10.1007/s00224-014-9598-9,Theory of Computing Systems,de2015,False,,Springer,Not available,The Strong Price of Anarchy of Linear Bottleneck Congestion Games,21cac123ce887c1a76175059bfe7861d,http://dx.doi.org/10.1007/s00224-014-9598-9
762,We study the inefficiency of equilibrium outcomes in ,orestis telelis,Not available,2015.0,10.1007/s00224-014-9598-9,Theory of Computing Systems,de2015,False,,Springer,Not available,The Strong Price of Anarchy of Linear Bottleneck Congestion Games,21cac123ce887c1a76175059bfe7861d,http://dx.doi.org/10.1007/s00224-014-9598-9
763,The paper investigates the extent to which capacity investment considerations interact with the double marginalization effect in a simple supply chain governed by a wholesale price contract. To do so  a non-cooperative differential game model is formulated to study the pricing and capacity investment decisions in a supply chain  which consists of a supplier and a manufacturer. In such a game  there are different decision rules—open-loop  closed-loop  feedback—that are available to the supply chain participants  depending on the observability of the current state of the supply chain. While closed-loop and feedback equilibrium strategies involve the observability of other chain member’s production capacity  open-loop equilibrium strategies do not have such requirement. We examine how the supplier and the manufacturer determine  with the different decision rules  their production capacities and pricing policies to maximize their profits over an infinite planning horizon  and determine how the observability of other supply chain’s members’ production capacity affects the magnitude of the double marginalization effect. Our study suggests that the observability of other chain member’s current production capacity entails a lower production efficiency that results in a greater double marginalization effect. This allows us to conclude that observability of other chain member’s current production capacity is associated with a greater double marginalization effect.,fouad ouardighi,Not available,2015.0,10.1057/jors.2014.99,Journal of the Operational Research Society,El2015,False,,Springer,Not available,Production capacity buildup and double marginalization mitigation in a dynamic supply chain,c0056dba5069720955f98607abddbc0c,http://dx.doi.org/10.1057/jors.2014.99
764,The paper investigates the extent to which capacity investment considerations interact with the double marginalization effect in a simple supply chain governed by a wholesale price contract. To do so  a non-cooperative differential game model is formulated to study the pricing and capacity investment decisions in a supply chain  which consists of a supplier and a manufacturer. In such a game  there are different decision rules—open-loop  closed-loop  feedback—that are available to the supply chain participants  depending on the observability of the current state of the supply chain. While closed-loop and feedback equilibrium strategies involve the observability of other chain member’s production capacity  open-loop equilibrium strategies do not have such requirement. We examine how the supplier and the manufacturer determine  with the different decision rules  their production capacities and pricing policies to maximize their profits over an infinite planning horizon  and determine how the observability of other supply chain’s members’ production capacity affects the magnitude of the double marginalization effect. Our study suggests that the observability of other chain member’s current production capacity entails a lower production efficiency that results in a greater double marginalization effect. This allows us to conclude that observability of other chain member’s current production capacity is associated with a greater double marginalization effect.,gary erickson,Not available,2015.0,10.1057/jors.2014.99,Journal of the Operational Research Society,El2015,False,,Springer,Not available,Production capacity buildup and double marginalization mitigation in a dynamic supply chain,c0056dba5069720955f98607abddbc0c,http://dx.doi.org/10.1057/jors.2014.99
765,We present our results on Uniform Price Auctions  one of the standard sealed-bid multi-unit auction formats  for selling multiple identical units of a single good to multi-demand bidders. Contrary to the truthful and economically efficient multi-unit Vickrey auction  the Uniform Price Auction encourages strategic bidding and is socially inefficient in general  partly due to a ”Demand Reduction” effect; bidders tend to bid for fewer (identical) units  so as to receive them at a lower uniform price. Despite its inefficiency  the uniform pricing rule is widely popular by its appeal to the natural anticipation  that identical items should be identically priced. Application domains of its variants include sales of U.S. Treasury bonds to investors  trade exchanges over the internet facilitated by popular online brokers  allocation of radio spectrum licenses etc. In this work we study equilibria of the Uniform Price Auction in undominated strategies. We characterize a class of undominated pure Nash equilibria and quantify the social inefficiency of pure and (mixed) Bayes-Nash equilibria by means of bounds on the Price of Anarchy.,orestis telelis,Not available,2012.0,10.1007/978-3-642-33996-7_20,Algorithmic Game Theory,Evangelos2012,False,,Springer,Not available,Uniform Price Auctions: Equilibria and Efficiency,b11d0a076e78797908baa3e9cbe37e67,http://dx.doi.org/10.1007/978-3-642-33996-7_20
766,In this paper  we study continuous opinion formation games with aggregation aspects. In many domains  expressed opinions of people are not only affected by local interaction and personal beliefs  but also by influences that stem from global properties of the opinions present in the society. To capture the interplay of such global and local effects  we propose a model of opinion formation games with aggregation  where we concentrate on the ,markos epitropou,Not available,2018.0,10.1007/s00224-018-9891-0,Theory of Computing Systems,Markos2018,False,,Springer,Not available,Opinion Formation Games with Aggregation and Negative Influence,c915ccade32c37429e9f6a861c6c13ce,http://dx.doi.org/10.1007/s00224-018-9891-0
767,In this paper  we study continuous opinion formation games with aggregation aspects. In many domains  expressed opinions of people are not only affected by local interaction and personal beliefs  but also by influences that stem from global properties of the opinions present in the society. To capture the interplay of such global and local effects  we propose a model of opinion formation games with aggregation  where we concentrate on the ,dimitris fotakis,Not available,2018.0,10.1007/s00224-018-9891-0,Theory of Computing Systems,Markos2018,False,,Springer,Not available,Opinion Formation Games with Aggregation and Negative Influence,c915ccade32c37429e9f6a861c6c13ce,http://dx.doi.org/10.1007/s00224-018-9891-0
768,In this paper  we study continuous opinion formation games with aggregation aspects. In many domains  expressed opinions of people are not only affected by local interaction and personal beliefs  but also by influences that stem from global properties of the opinions present in the society. To capture the interplay of such global and local effects  we propose a model of opinion formation games with aggregation  where we concentrate on the ,martin hoefer,Not available,2018.0,10.1007/s00224-018-9891-0,Theory of Computing Systems,Markos2018,False,,Springer,Not available,Opinion Formation Games with Aggregation and Negative Influence,c915ccade32c37429e9f6a861c6c13ce,http://dx.doi.org/10.1007/s00224-018-9891-0
769,In this paper  we study continuous opinion formation games with aggregation aspects. In many domains  expressed opinions of people are not only affected by local interaction and personal beliefs  but also by influences that stem from global properties of the opinions present in the society. To capture the interplay of such global and local effects  we propose a model of opinion formation games with aggregation  where we concentrate on the ,stratis skoulakis,Not available,2018.0,10.1007/s00224-018-9891-0,Theory of Computing Systems,Markos2018,False,,Springer,Not available,Opinion Formation Games with Aggregation and Negative Influence,c915ccade32c37429e9f6a861c6c13ce,http://dx.doi.org/10.1007/s00224-018-9891-0
770,The bin packing problem deals with packing items of sizes no larger than 1 into unit capacity bins. Here  we analyze a class of bin packing games where the cost of an item is 1 over the total number of items packed into its bin  which is a bin packing congestion game. We study strong equilibria and find the tight values of the ,gyorgy dosa,Not available,2018.0,10.1007/s10951-018-0587-8,Journal of Scheduling,György2018,False,,Springer,Not available,Quality of strong equilibria for selfish bin packing with uniform cost sharing,295688278bedf81e4db6436b744b7fe5,http://dx.doi.org/10.1007/s10951-018-0587-8
771,The bin packing problem deals with packing items of sizes no larger than 1 into unit capacity bins. Here  we analyze a class of bin packing games where the cost of an item is 1 over the total number of items packed into its bin  which is a bin packing congestion game. We study strong equilibria and find the tight values of the ,leah epstein,Not available,2018.0,10.1007/s10951-018-0587-8,Journal of Scheduling,György2018,False,,Springer,Not available,Quality of strong equilibria for selfish bin packing with uniform cost sharing,295688278bedf81e4db6436b744b7fe5,http://dx.doi.org/10.1007/s10951-018-0587-8
772,When a group of Mobile Users (MUs) equipped with multi-mode or multi-home terminals  like passengers on board a bus or a train or a car  moves from one wireless network (WN) to another WN within a heterogeneous wireless network (HWN) environment  request vertical handoffs simultaneously  a group vertical handoff (GVHO) occurs. In literature  the prevailing research work is mainly concerned for forced GVHO with network aspects like signal strength and bandwidth etc. while in reality the user initiated GVHO with the user aspects like price  power consumption and velocity etc. along with their respective user preferences is more important for performing vertical handoffs in HWNs. In user initiated GVHO  selection of the mutually best WN-MU pair which can maximise network revenue of constituent WN as well as user satisfaction of MU in a group while minimising the simultaneous selection of a WN by multiple MU of the group is a challenging problem. This paper proposes a GVHO decision model based on non-cooperative game which utilizes multiple handoff decision attributes and their respective user preferences calculated dynamically on real-time basis as the game strategies to select the best available WNs by group MUs at NASH equilibrium for vertical handoffs. The performance of the proposed model is evaluated in terms of number of GVHOs  price of anarchy and price of stability for both group of MUs and WNs. The simulation results show that the proposed model results in minimum number of GVHOs as compared to existing GVHO models and maximisation of user satisfaction and network revenue.,pramod goyal,Not available,2018.0,10.1007/s11276-018-1826-9,Wireless Networks,Pramod2018,False,,Springer,Not available,Dynamic user preference based group vertical handoffs in heterogeneous wireless networks: a non-cooperative game approach,9983e169586bf8821adeb4f2ffc7bf89,http://dx.doi.org/10.1007/s11276-018-1826-9
773,When a group of Mobile Users (MUs) equipped with multi-mode or multi-home terminals  like passengers on board a bus or a train or a car  moves from one wireless network (WN) to another WN within a heterogeneous wireless network (HWN) environment  request vertical handoffs simultaneously  a group vertical handoff (GVHO) occurs. In literature  the prevailing research work is mainly concerned for forced GVHO with network aspects like signal strength and bandwidth etc. while in reality the user initiated GVHO with the user aspects like price  power consumption and velocity etc. along with their respective user preferences is more important for performing vertical handoffs in HWNs. In user initiated GVHO  selection of the mutually best WN-MU pair which can maximise network revenue of constituent WN as well as user satisfaction of MU in a group while minimising the simultaneous selection of a WN by multiple MU of the group is a challenging problem. This paper proposes a GVHO decision model based on non-cooperative game which utilizes multiple handoff decision attributes and their respective user preferences calculated dynamically on real-time basis as the game strategies to select the best available WNs by group MUs at NASH equilibrium for vertical handoffs. The performance of the proposed model is evaluated in terms of number of GVHOs  price of anarchy and price of stability for both group of MUs and WNs. The simulation results show that the proposed model results in minimum number of GVHOs as compared to existing GVHO models and maximisation of user satisfaction and network revenue.,d. lobiyal,Not available,2018.0,10.1007/s11276-018-1826-9,Wireless Networks,Pramod2018,False,,Springer,Not available,Dynamic user preference based group vertical handoffs in heterogeneous wireless networks: a non-cooperative game approach,9983e169586bf8821adeb4f2ffc7bf89,http://dx.doi.org/10.1007/s11276-018-1826-9
774,When a group of Mobile Users (MUs) equipped with multi-mode or multi-home terminals  like passengers on board a bus or a train or a car  moves from one wireless network (WN) to another WN within a heterogeneous wireless network (HWN) environment  request vertical handoffs simultaneously  a group vertical handoff (GVHO) occurs. In literature  the prevailing research work is mainly concerned for forced GVHO with network aspects like signal strength and bandwidth etc. while in reality the user initiated GVHO with the user aspects like price  power consumption and velocity etc. along with their respective user preferences is more important for performing vertical handoffs in HWNs. In user initiated GVHO  selection of the mutually best WN-MU pair which can maximise network revenue of constituent WN as well as user satisfaction of MU in a group while minimising the simultaneous selection of a WN by multiple MU of the group is a challenging problem. This paper proposes a GVHO decision model based on non-cooperative game which utilizes multiple handoff decision attributes and their respective user preferences calculated dynamically on real-time basis as the game strategies to select the best available WNs by group MUs at NASH equilibrium for vertical handoffs. The performance of the proposed model is evaluated in terms of number of GVHOs  price of anarchy and price of stability for both group of MUs and WNs. The simulation results show that the proposed model results in minimum number of GVHOs as compared to existing GVHO models and maximisation of user satisfaction and network revenue.,c. katti,Not available,2018.0,10.1007/s11276-018-1826-9,Wireless Networks,Pramod2018,False,,Springer,Not available,Dynamic user preference based group vertical handoffs in heterogeneous wireless networks: a non-cooperative game approach,9983e169586bf8821adeb4f2ffc7bf89,http://dx.doi.org/10.1007/s11276-018-1826-9
775,Network pricing serves as an instrument for congestion management  however  agencies and planners often encounter problems of estimating appropriate toll prices. Tolls are commonly estimated for a single-point deterministic travel demand  which may lead to imperfect policy decisions due to inherent uncertainties in future travel demand. Previous research has addressed the issue of demand uncertainty in the pricing context  but the elastic nature of demand along with its uncertainty has not been explicitly considered. Similarly  interactions between elasticity and uncertainty of demand have not been characterized. This study addresses these gaps and proposes a framework to estimate nearest optimal first-best tolls under long-term stochasticity in elastic demand. We show first that the optimal tolls under the deterministic-elastic and stochastic-elastic demand cases coincide when cost and demand functions are linear  and the set of equilibrium paths is constant. These assumptions are restrictive  so three larger networks are considered numerically  and the subsequent pricing decisions are assessed. The results of the numerical experiments suggest that in many cases  optimal pricing decisions under the combined stochastic-elastic demand scenario resemble those when demand is known exactly. The applications in this study thus suggest that inclusion of demand elasticity offsets the need of considering future demand uncertainties for first-best congestion pricing frameworks.,prateek bansal,Not available,2018.0,10.1007/s11116-017-9769-z,Transportation,Prateek2018,False,,Springer,Not available,Robust network pricing and system optimization under combined long-term stochasticity and elasticity of travel demand,f12f32214f2afa837c37367daf091817,http://dx.doi.org/10.1007/s11116-017-9769-z
776,Contrary to early expectations  recent studies have shown near-perfect adherence to HIV antiretrovirals in sub-Saharan Africa We conducted qualitative interviews with patients purchasing low-cost  generic antiretroviral therapy to better understand the social dynamics underlying these findings. We found that concerns for family well-being motivate adherence  yet  the financial sacrifices necessary to secure therapy may paradoxically undermine family welfare. We suggest that missed doses may be more due to a failure to ,j. crane,Not available,2006.0,10.1007/s10461-006-9080-z,AIDS and Behavior,T.2006,False,,Springer,Not available,The Price of Adherence: Qualitative Findings From HIV Positive Individuals Purchasing Fixed-Dose Combination Generic HIV Antiretroviral Therapy in Kampala  Uganda,3546dd01c0a6376828bbafaaa37b87c7,http://dx.doi.org/10.1007/s10461-006-9080-z
777,We study Nash equilibria in the context of flows over time. Many results on ,ronald koch,Not available,2011.0,10.1007/s00224-010-9299-y,Theory of Computing Systems,Ronald2011,False,,Springer,Not available,Nash Equilibria and the Price of Anarchy for Flows over Time,06b8b7674203c381c500a0183c727511,http://dx.doi.org/10.1007/s00224-010-9299-y
778,Network pricing serves as an instrument for congestion management  however  agencies and planners often encounter problems of estimating appropriate toll prices. Tolls are commonly estimated for a single-point deterministic travel demand  which may lead to imperfect policy decisions due to inherent uncertainties in future travel demand. Previous research has addressed the issue of demand uncertainty in the pricing context  but the elastic nature of demand along with its uncertainty has not been explicitly considered. Similarly  interactions between elasticity and uncertainty of demand have not been characterized. This study addresses these gaps and proposes a framework to estimate nearest optimal first-best tolls under long-term stochasticity in elastic demand. We show first that the optimal tolls under the deterministic-elastic and stochastic-elastic demand cases coincide when cost and demand functions are linear  and the set of equilibrium paths is constant. These assumptions are restrictive  so three larger networks are considered numerically  and the subsequent pricing decisions are assessed. The results of the numerical experiments suggest that in many cases  optimal pricing decisions under the combined stochastic-elastic demand scenario resemble those when demand is known exactly. The applications in this study thus suggest that inclusion of demand elasticity offsets the need of considering future demand uncertainties for first-best congestion pricing frameworks.,rohan shah,Not available,2018.0,10.1007/s11116-017-9769-z,Transportation,Prateek2018,False,,Springer,Not available,Robust network pricing and system optimization under combined long-term stochasticity and elasticity of travel demand,f12f32214f2afa837c37367daf091817,http://dx.doi.org/10.1007/s11116-017-9769-z
779,Network pricing serves as an instrument for congestion management  however  agencies and planners often encounter problems of estimating appropriate toll prices. Tolls are commonly estimated for a single-point deterministic travel demand  which may lead to imperfect policy decisions due to inherent uncertainties in future travel demand. Previous research has addressed the issue of demand uncertainty in the pricing context  but the elastic nature of demand along with its uncertainty has not been explicitly considered. Similarly  interactions between elasticity and uncertainty of demand have not been characterized. This study addresses these gaps and proposes a framework to estimate nearest optimal first-best tolls under long-term stochasticity in elastic demand. We show first that the optimal tolls under the deterministic-elastic and stochastic-elastic demand cases coincide when cost and demand functions are linear  and the set of equilibrium paths is constant. These assumptions are restrictive  so three larger networks are considered numerically  and the subsequent pricing decisions are assessed. The results of the numerical experiments suggest that in many cases  optimal pricing decisions under the combined stochastic-elastic demand scenario resemble those when demand is known exactly. The applications in this study thus suggest that inclusion of demand elasticity offsets the need of considering future demand uncertainties for first-best congestion pricing frameworks.,stephen boyles,Not available,2018.0,10.1007/s11116-017-9769-z,Transportation,Prateek2018,False,,Springer,Not available,Robust network pricing and system optimization under combined long-term stochasticity and elasticity of travel demand,f12f32214f2afa837c37367daf091817,http://dx.doi.org/10.1007/s11116-017-9769-z
780,This paper deals with decentralized decision-making situations in which firms outsource production orders to multiple identical suppliers. Each firm aims to minimize the sum of its completion times. We study whether a central authority can install a mechanism such that strategic interaction leads to a socially optimal schedule. For the case of single demand the shortest-first mechanism implements optimal schedules in Nash equilibrium. We show that for the general case there exists no anonymous mechanism that implements optimal schedules in correlated equilibrium.,herbert hamers,Not available,2018.0,10.1007/s00186-018-0645-1,Mathematical Methods of Operations Research,Herbert2018,False,,Springer,Not available,Implementation of optimal schedules in outsourcing with identical suppliers,3adf215b0f5f337f805a1ae53a0f3f07,http://dx.doi.org/10.1007/s00186-018-0645-1
781,This paper deals with decentralized decision-making situations in which firms outsource production orders to multiple identical suppliers. Each firm aims to minimize the sum of its completion times. We study whether a central authority can install a mechanism such that strategic interaction leads to a socially optimal schedule. For the case of single demand the shortest-first mechanism implements optimal schedules in Nash equilibrium. We show that for the general case there exists no anonymous mechanism that implements optimal schedules in correlated equilibrium.,flip klijn,Not available,2018.0,10.1007/s00186-018-0645-1,Mathematical Methods of Operations Research,Herbert2018,False,,Springer,Not available,Implementation of optimal schedules in outsourcing with identical suppliers,3adf215b0f5f337f805a1ae53a0f3f07,http://dx.doi.org/10.1007/s00186-018-0645-1
782,This paper deals with decentralized decision-making situations in which firms outsource production orders to multiple identical suppliers. Each firm aims to minimize the sum of its completion times. We study whether a central authority can install a mechanism such that strategic interaction leads to a socially optimal schedule. For the case of single demand the shortest-first mechanism implements optimal schedules in Nash equilibrium. We show that for the general case there exists no anonymous mechanism that implements optimal schedules in correlated equilibrium.,marco slikker,Not available,2018.0,10.1007/s00186-018-0645-1,Mathematical Methods of Operations Research,Herbert2018,False,,Springer,Not available,Implementation of optimal schedules in outsourcing with identical suppliers,3adf215b0f5f337f805a1ae53a0f3f07,http://dx.doi.org/10.1007/s00186-018-0645-1
783,We present a general technique  based on a primal-dual formulation  for analyzing the quality of self-emerging solutions in weighted congestion games. With respect to traditional combinatorial approaches  the primal-dual schema has at least three advantages: first  it provides an analytic tool which can always be used to prove tight upper bounds for all the cases in which we are able to characterize exactly the polyhedron of the solutions under analysis; secondly  in each such a case  the complementary slackness conditions give us a hint on how to construct matching lower bounding instances; thirdly  proofs become simpler and easy to check. For the sake of exposition  we first apply our technique to the problems of bounding the price of anarchy and stability of exact and approximate pure Nash equilibria  as well as the approximation ratio of the strategy profiles achieved after a one-round walk starting from the empty state  in the case of affine latency functions and we show how all the known upper bounds for these measures (and some of their generalizations) can be easily reobtained under a unified approach. Then  we use the technique to attack the more challenging setting of polynomial latency functions. In particular  we obtain the first known upper bounds on the price of stability of pure Nash equilibria and on the approximation ratio of the strategy profiles achieved after a one-round walk starting from the empty state for unweighted players in the cases of quadratic and cubic latency functions.,vittorio bilo,Not available,2018.0,10.1007/s00224-017-9826-1,Theory of Computing Systems,Vittorio2018,False,,Springer,Not available,A Unifying Tool for Bounding the Quality of Non-Cooperative Solutions in Weighted Congestion Games,7ced81f78a801ff16c1676cb3704d24f,http://dx.doi.org/10.1007/s00224-017-9826-1
784,How will bounded rationality influence telecommunication network fluctuations? Recently  there has been an increased research interest in telecommunication network pricing  which leads to many proposals for new pricing schemes motivated by different objectives namely: to maximize service provider’s revenue  to guarantee fairness among users and to satisfy quality of service (QoS) requirements for differentiated network services. In the present paper  we consider a system with N rational service providers (SPs) that offer homogeneous telecommunication services to bounded rational costumers. All SPs offer the same services and seek to persuade more customers in the same system  we model this conflict as a noncooperative game. On the one hand  each SP decide his policies of price and QoS in order to maximize his profit. One the other hand  we assume that the customers are boundedly rational and make their subscription decisions probabilistically  according to Luce choice probabilities. Furthermore  the customers decide to which SP to subscribe  each one may migrate to another SP or alternatively switch to “no subscription state” depending on the observed price/QoS. In this work  we have proved through a detailed analysis the existence and uniqueness of Nash equilibrium. We evaluate the impact of user’s bounded rationality on the equilibrium of game. Using the price of anarchy  we examine the performance and efficiency of equilibrium. We have shown that the ,omar ait,Not available,2018.0,10.1007/s00607-018-0642-5,Computing,Driss2018,False,,Springer,Not available,On understanding price-QoS war for competitive market and confused consumers,ff7e6cf6b4049172d72141d95501b79a,http://dx.doi.org/10.1007/s00607-018-0642-5
785,How will bounded rationality influence telecommunication network fluctuations? Recently  there has been an increased research interest in telecommunication network pricing  which leads to many proposals for new pricing schemes motivated by different objectives namely: to maximize service provider’s revenue  to guarantee fairness among users and to satisfy quality of service (QoS) requirements for differentiated network services. In the present paper  we consider a system with N rational service providers (SPs) that offer homogeneous telecommunication services to bounded rational costumers. All SPs offer the same services and seek to persuade more customers in the same system  we model this conflict as a noncooperative game. On the one hand  each SP decide his policies of price and QoS in order to maximize his profit. One the other hand  we assume that the customers are boundedly rational and make their subscription decisions probabilistically  according to Luce choice probabilities. Furthermore  the customers decide to which SP to subscribe  each one may migrate to another SP or alternatively switch to “no subscription state” depending on the observed price/QoS. In this work  we have proved through a detailed analysis the existence and uniqueness of Nash equilibrium. We evaluate the impact of user’s bounded rationality on the equilibrium of game. Using the price of anarchy  we examine the performance and efficiency of equilibrium. We have shown that the ,m'hamed outanoute,Not available,2018.0,10.1007/s00607-018-0642-5,Computing,Driss2018,False,,Springer,Not available,On understanding price-QoS war for competitive market and confused consumers,ff7e6cf6b4049172d72141d95501b79a,http://dx.doi.org/10.1007/s00607-018-0642-5
786,How will bounded rationality influence telecommunication network fluctuations? Recently  there has been an increased research interest in telecommunication network pricing  which leads to many proposals for new pricing schemes motivated by different objectives namely: to maximize service provider’s revenue  to guarantee fairness among users and to satisfy quality of service (QoS) requirements for differentiated network services. In the present paper  we consider a system with N rational service providers (SPs) that offer homogeneous telecommunication services to bounded rational costumers. All SPs offer the same services and seek to persuade more customers in the same system  we model this conflict as a noncooperative game. On the one hand  each SP decide his policies of price and QoS in order to maximize his profit. One the other hand  we assume that the customers are boundedly rational and make their subscription decisions probabilistically  according to Luce choice probabilities. Furthermore  the customers decide to which SP to subscribe  each one may migrate to another SP or alternatively switch to “no subscription state” depending on the observed price/QoS. In this work  we have proved through a detailed analysis the existence and uniqueness of Nash equilibrium. We evaluate the impact of user’s bounded rationality on the equilibrium of game. Using the price of anarchy  we examine the performance and efficiency of equilibrium. We have shown that the ,mohamed baslam,Not available,2018.0,10.1007/s00607-018-0642-5,Computing,Driss2018,False,,Springer,Not available,On understanding price-QoS war for competitive market and confused consumers,ff7e6cf6b4049172d72141d95501b79a,http://dx.doi.org/10.1007/s00607-018-0642-5
787,How will bounded rationality influence telecommunication network fluctuations? Recently  there has been an increased research interest in telecommunication network pricing  which leads to many proposals for new pricing schemes motivated by different objectives namely: to maximize service provider’s revenue  to guarantee fairness among users and to satisfy quality of service (QoS) requirements for differentiated network services. In the present paper  we consider a system with N rational service providers (SPs) that offer homogeneous telecommunication services to bounded rational costumers. All SPs offer the same services and seek to persuade more customers in the same system  we model this conflict as a noncooperative game. On the one hand  each SP decide his policies of price and QoS in order to maximize his profit. One the other hand  we assume that the customers are boundedly rational and make their subscription decisions probabilistically  according to Luce choice probabilities. Furthermore  the customers decide to which SP to subscribe  each one may migrate to another SP or alternatively switch to “no subscription state” depending on the observed price/QoS. In this work  we have proved through a detailed analysis the existence and uniqueness of Nash equilibrium. We evaluate the impact of user’s bounded rationality on the equilibrium of game. Using the price of anarchy  we examine the performance and efficiency of equilibrium. We have shown that the ,mohamed fakir,Not available,2018.0,10.1007/s00607-018-0642-5,Computing,Driss2018,False,,Springer,Not available,On understanding price-QoS war for competitive market and confused consumers,ff7e6cf6b4049172d72141d95501b79a,http://dx.doi.org/10.1007/s00607-018-0642-5
788,We study Nash equilibria in the context of flows over time. Many results on ,martin skutella,Not available,2011.0,10.1007/s00224-010-9299-y,Theory of Computing Systems,Ronald2011,False,,Springer,Not available,Nash Equilibria and the Price of Anarchy for Flows over Time,06b8b7674203c381c500a0183c727511,http://dx.doi.org/10.1007/s00224-010-9299-y
789,How will bounded rationality influence telecommunication network fluctuations? Recently  there has been an increased research interest in telecommunication network pricing  which leads to many proposals for new pricing schemes motivated by different objectives namely: to maximize service provider’s revenue  to guarantee fairness among users and to satisfy quality of service (QoS) requirements for differentiated network services. In the present paper  we consider a system with N rational service providers (SPs) that offer homogeneous telecommunication services to bounded rational costumers. All SPs offer the same services and seek to persuade more customers in the same system  we model this conflict as a noncooperative game. On the one hand  each SP decide his policies of price and QoS in order to maximize his profit. One the other hand  we assume that the customers are boundedly rational and make their subscription decisions probabilistically  according to Luce choice probabilities. Furthermore  the customers decide to which SP to subscribe  each one may migrate to another SP or alternatively switch to “no subscription state” depending on the observed price/QoS. In this work  we have proved through a detailed analysis the existence and uniqueness of Nash equilibrium. We evaluate the impact of user’s bounded rationality on the equilibrium of game. Using the price of anarchy  we examine the performance and efficiency of equilibrium. We have shown that the ,belaid bouikhalene,Not available,2018.0,10.1007/s00607-018-0642-5,Computing,Driss2018,False,,Springer,Not available,On understanding price-QoS war for competitive market and confused consumers,ff7e6cf6b4049172d72141d95501b79a,http://dx.doi.org/10.1007/s00607-018-0642-5
790,We study several machine scheduling games  each involving ,long zhang,Not available,2018.0,10.1007/s11590-018-1285-3,Optimization Letters,Long2018,False,,Springer,Not available,Improved price of anarchy for machine scheduling games with coordination mechanisms,cf94e9507d039f70188025ee80788530,http://dx.doi.org/10.1007/s11590-018-1285-3
791,We study several machine scheduling games  each involving ,yuzhong zhang,Not available,2018.0,10.1007/s11590-018-1285-3,Optimization Letters,Long2018,False,,Springer,Not available,Improved price of anarchy for machine scheduling games with coordination mechanisms,cf94e9507d039f70188025ee80788530,http://dx.doi.org/10.1007/s11590-018-1285-3
792,We study several machine scheduling games  each involving ,donglei du,Not available,2018.0,10.1007/s11590-018-1285-3,Optimization Letters,Long2018,False,,Springer,Not available,Improved price of anarchy for machine scheduling games with coordination mechanisms,cf94e9507d039f70188025ee80788530,http://dx.doi.org/10.1007/s11590-018-1285-3
793,We study several machine scheduling games  each involving ,qingguo bai,Not available,2018.0,10.1007/s11590-018-1285-3,Optimization Letters,Long2018,False,,Springer,Not available,Improved price of anarchy for machine scheduling games with coordination mechanisms,cf94e9507d039f70188025ee80788530,http://dx.doi.org/10.1007/s11590-018-1285-3
794,We study a game theoretical model of multistage interval scheduling problems in which each job consists of exactly one task (interval) for each of ,arne herzel,Not available,2018.0,10.1007/s10951-018-0568-y,Journal of Scheduling,Arne2018,False,,Springer,Not available,Multistage interval scheduling games,3366854ba662eecbf7895ad4a08bbc8f,http://dx.doi.org/10.1007/s10951-018-0568-y
795,We study a game theoretical model of multistage interval scheduling problems in which each job consists of exactly one task (interval) for each of ,michael hopf,Not available,2018.0,10.1007/s10951-018-0568-y,Journal of Scheduling,Arne2018,False,,Springer,Not available,Multistage interval scheduling games,3366854ba662eecbf7895ad4a08bbc8f,http://dx.doi.org/10.1007/s10951-018-0568-y
796,We study a game theoretical model of multistage interval scheduling problems in which each job consists of exactly one task (interval) for each of ,clemens thielen,Not available,2018.0,10.1007/s10951-018-0568-y,Journal of Scheduling,Arne2018,False,,Springer,Not available,Multistage interval scheduling games,3366854ba662eecbf7895ad4a08bbc8f,http://dx.doi.org/10.1007/s10951-018-0568-y
797,We study the load balancing problem in the context of a set of clients each wishing to run a job on a server selected among a subset of permissible servers for the particular client. We consider two different scenarios. In ,ioannis caragiannis,Not available,2011.0,10.1007/s00453-010-9427-8,Algorithmica,Ioannis2011,False,,Springer,Not available,Tight Bounds for Selfish and Greedy Load Balancing,0639a8842c95de1ebcfa0df10cebb52d,http://dx.doi.org/10.1007/s00453-010-9427-8
798,We study the load balancing problem in the context of a set of clients each wishing to run a job on a server selected among a subset of permissible servers for the particular client. We consider two different scenarios. In ,michele flammini,Not available,2011.0,10.1007/s00453-010-9427-8,Algorithmica,Ioannis2011,False,,Springer,Not available,Tight Bounds for Selfish and Greedy Load Balancing,0639a8842c95de1ebcfa0df10cebb52d,http://dx.doi.org/10.1007/s00453-010-9427-8
799,We study the survivable version of the game theoretic network formation model known as the Connection Game  originally introduced in Anshelevich et al. (Proc. 35th ACM Symposium on Theory of Computing  ,elliot anshelevich,Not available,2011.0,10.1007/s00224-011-9317-8,Theory of Computing Systems,Elliot2011,False,,Springer,Not available,Price of Stability in Survivable Network Design,1f9cefcd85f0a64234eb1002ab008f3d,http://dx.doi.org/10.1007/s00224-011-9317-8
800,We study the load balancing problem in the context of a set of clients each wishing to run a job on a server selected among a subset of permissible servers for the particular client. We consider two different scenarios. In ,christos kaklamanis,Not available,2011.0,10.1007/s00453-010-9427-8,Algorithmica,Ioannis2011,False,,Springer,Not available,Tight Bounds for Selfish and Greedy Load Balancing,0639a8842c95de1ebcfa0df10cebb52d,http://dx.doi.org/10.1007/s00453-010-9427-8
801,We study the load balancing problem in the context of a set of clients each wishing to run a job on a server selected among a subset of permissible servers for the particular client. We consider two different scenarios. In ,panagiotis kanellopoulos,Not available,2011.0,10.1007/s00453-010-9427-8,Algorithmica,Ioannis2011,False,,Springer,Not available,Tight Bounds for Selfish and Greedy Load Balancing,0639a8842c95de1ebcfa0df10cebb52d,http://dx.doi.org/10.1007/s00453-010-9427-8
802,We study the load balancing problem in the context of a set of clients each wishing to run a job on a server selected among a subset of permissible servers for the particular client. We consider two different scenarios. In ,luca moscardelli,Not available,2011.0,10.1007/s00453-010-9427-8,Algorithmica,Ioannis2011,False,,Springer,Not available,Tight Bounds for Selfish and Greedy Load Balancing,0639a8842c95de1ebcfa0df10cebb52d,http://dx.doi.org/10.1007/s00453-010-9427-8
803,The bin packing problem  a classical problem in combinatorial optimization  has recently been studied from the viewpoint of algorithmic game theory. In this bin packing game each item is controlled by a selfish player minimizing its personal cost  which in this context is defined as the relative contribution of the size of the item to the total load in the bin.We introduce a related game  the so-called bin coloring game  in which players control colored items and each player aims at packing its item into a bin with as few different colors as possible.We establish existence of Nash and strong as well as weakly and strictly Pareto optimal equilibria in these games in the cases of capacitated and uncapacitated bins. For both kinds of games we determine the prices of anarchy and stability concerning those four equilibrium concepts. Furthermore  we show that extreme Nash equilibria  representatives of the set of Nash equilibria with minimal or maximal number of colors in a bin  can be found in time polynomial in the number of items for the uncapacitated case.,leah epstein,Not available,2011.0,10.1007/s10878-010-9302-1,Journal of Combinatorial Optimization,Leah2011,False,,Springer,Not available,Selfish bin coloring,9107482fd364c25c3c11ee44dac8ad2c,http://dx.doi.org/10.1007/s10878-010-9302-1
804,The bin packing problem  a classical problem in combinatorial optimization  has recently been studied from the viewpoint of algorithmic game theory. In this bin packing game each item is controlled by a selfish player minimizing its personal cost  which in this context is defined as the relative contribution of the size of the item to the total load in the bin.We introduce a related game  the so-called bin coloring game  in which players control colored items and each player aims at packing its item into a bin with as few different colors as possible.We establish existence of Nash and strong as well as weakly and strictly Pareto optimal equilibria in these games in the cases of capacitated and uncapacitated bins. For both kinds of games we determine the prices of anarchy and stability concerning those four equilibrium concepts. Furthermore  we show that extreme Nash equilibria  representatives of the set of Nash equilibria with minimal or maximal number of colors in a bin  can be found in time polynomial in the number of items for the uncapacitated case.,sven krumke,Not available,2011.0,10.1007/s10878-010-9302-1,Journal of Combinatorial Optimization,Leah2011,False,,Springer,Not available,Selfish bin coloring,9107482fd364c25c3c11ee44dac8ad2c,http://dx.doi.org/10.1007/s10878-010-9302-1
805,The bin packing problem  a classical problem in combinatorial optimization  has recently been studied from the viewpoint of algorithmic game theory. In this bin packing game each item is controlled by a selfish player minimizing its personal cost  which in this context is defined as the relative contribution of the size of the item to the total load in the bin.We introduce a related game  the so-called bin coloring game  in which players control colored items and each player aims at packing its item into a bin with as few different colors as possible.We establish existence of Nash and strong as well as weakly and strictly Pareto optimal equilibria in these games in the cases of capacitated and uncapacitated bins. For both kinds of games we determine the prices of anarchy and stability concerning those four equilibrium concepts. Furthermore  we show that extreme Nash equilibria  representatives of the set of Nash equilibria with minimal or maximal number of colors in a bin  can be found in time polynomial in the number of items for the uncapacitated case.,asaf levin,Not available,2011.0,10.1007/s10878-010-9302-1,Journal of Combinatorial Optimization,Leah2011,False,,Springer,Not available,Selfish bin coloring,9107482fd364c25c3c11ee44dac8ad2c,http://dx.doi.org/10.1007/s10878-010-9302-1
806,The bin packing problem  a classical problem in combinatorial optimization  has recently been studied from the viewpoint of algorithmic game theory. In this bin packing game each item is controlled by a selfish player minimizing its personal cost  which in this context is defined as the relative contribution of the size of the item to the total load in the bin.We introduce a related game  the so-called bin coloring game  in which players control colored items and each player aims at packing its item into a bin with as few different colors as possible.We establish existence of Nash and strong as well as weakly and strictly Pareto optimal equilibria in these games in the cases of capacitated and uncapacitated bins. For both kinds of games we determine the prices of anarchy and stability concerning those four equilibrium concepts. Furthermore  we show that extreme Nash equilibria  representatives of the set of Nash equilibria with minimal or maximal number of colors in a bin  can be found in time polynomial in the number of items for the uncapacitated case.,heike sperber,Not available,2011.0,10.1007/s10878-010-9302-1,Journal of Combinatorial Optimization,Leah2011,False,,Springer,Not available,Selfish bin coloring,9107482fd364c25c3c11ee44dac8ad2c,http://dx.doi.org/10.1007/s10878-010-9302-1
807,We consider congestion games with linear latency functions in which each player is aware only of a subset of all the other players. This is modeled by means of a social knowledge graph ,vittorio bilo,Not available,2011.0,10.1007/s00453-010-9417-x,Algorithmica,Vittorio2011,False,,Springer,Not available,Graphical Congestion Games,bfd47b8289a2905988101f20d64c808b,http://dx.doi.org/10.1007/s00453-010-9417-x
808,We consider congestion games with linear latency functions in which each player is aware only of a subset of all the other players. This is modeled by means of a social knowledge graph ,angelo fanelli,Not available,2011.0,10.1007/s00453-010-9417-x,Algorithmica,Vittorio2011,False,,Springer,Not available,Graphical Congestion Games,bfd47b8289a2905988101f20d64c808b,http://dx.doi.org/10.1007/s00453-010-9417-x
809,We consider congestion games with linear latency functions in which each player is aware only of a subset of all the other players. This is modeled by means of a social knowledge graph ,michele flammini,Not available,2011.0,10.1007/s00453-010-9417-x,Algorithmica,Vittorio2011,False,,Springer,Not available,Graphical Congestion Games,bfd47b8289a2905988101f20d64c808b,http://dx.doi.org/10.1007/s00453-010-9417-x
810,We study the survivable version of the game theoretic network formation model known as the Connection Game  originally introduced in Anshelevich et al. (Proc. 35th ACM Symposium on Theory of Computing  ,bugra caskurlu,Not available,2011.0,10.1007/s00224-011-9317-8,Theory of Computing Systems,Elliot2011,False,,Springer,Not available,Price of Stability in Survivable Network Design,1f9cefcd85f0a64234eb1002ab008f3d,http://dx.doi.org/10.1007/s00224-011-9317-8
811,We consider congestion games with linear latency functions in which each player is aware only of a subset of all the other players. This is modeled by means of a social knowledge graph ,luca moscardelli,Not available,2011.0,10.1007/s00453-010-9417-x,Algorithmica,Vittorio2011,False,,Springer,Not available,Graphical Congestion Games,bfd47b8289a2905988101f20d64c808b,http://dx.doi.org/10.1007/s00453-010-9417-x
812,Current peer-to-peer (P2P) systems often suffer from a large fraction of freeriders not contributing any resources to the network. Various mechanisms have been designed to overcome this problem. However  the selfish behavior of peers has aspects which go beyond resource sharing. This paper studies the effects on the topology of a P2P network if peers selfishly select the peers to connect to. In our model  a peer exploits locality properties in order to minimize the latency (or response times) of its lookup operations. At the same time  the peer aims at not having to maintain links to too many other peers in the system. By giving tight bounds on the price of anarchy  we show that the resulting topologies can be much worse than if peers collaborated. Moreover  the network may never stabilize  even in the absence of churn. Finally  we establish the complexity of Nash equilibria in our game theoretic model of P2P networks. Specifically  we prove that it is NP-hard to decide whether our game has a Nash equilibrium and can stabilize.,thomas moscibroda,Not available,2011.0,10.1007/s00453-010-9398-9,Algorithmica,Thomas2011,False,,Springer,Not available,Topological Implications of Selfish Neighbor Selection in Unstructured Peer-to-Peer Networks,fcd6e86ba0b781583b7da06c996065cf,http://dx.doi.org/10.1007/s00453-010-9398-9
813,Current peer-to-peer (P2P) systems often suffer from a large fraction of freeriders not contributing any resources to the network. Various mechanisms have been designed to overcome this problem. However  the selfish behavior of peers has aspects which go beyond resource sharing. This paper studies the effects on the topology of a P2P network if peers selfishly select the peers to connect to. In our model  a peer exploits locality properties in order to minimize the latency (or response times) of its lookup operations. At the same time  the peer aims at not having to maintain links to too many other peers in the system. By giving tight bounds on the price of anarchy  we show that the resulting topologies can be much worse than if peers collaborated. Moreover  the network may never stabilize  even in the absence of churn. Finally  we establish the complexity of Nash equilibria in our game theoretic model of P2P networks. Specifically  we prove that it is NP-hard to decide whether our game has a Nash equilibrium and can stabilize.,stefan schmid,Not available,2011.0,10.1007/s00453-010-9398-9,Algorithmica,Thomas2011,False,,Springer,Not available,Topological Implications of Selfish Neighbor Selection in Unstructured Peer-to-Peer Networks,fcd6e86ba0b781583b7da06c996065cf,http://dx.doi.org/10.1007/s00453-010-9398-9
814,Current peer-to-peer (P2P) systems often suffer from a large fraction of freeriders not contributing any resources to the network. Various mechanisms have been designed to overcome this problem. However  the selfish behavior of peers has aspects which go beyond resource sharing. This paper studies the effects on the topology of a P2P network if peers selfishly select the peers to connect to. In our model  a peer exploits locality properties in order to minimize the latency (or response times) of its lookup operations. At the same time  the peer aims at not having to maintain links to too many other peers in the system. By giving tight bounds on the price of anarchy  we show that the resulting topologies can be much worse than if peers collaborated. Moreover  the network may never stabilize  even in the absence of churn. Finally  we establish the complexity of Nash equilibria in our game theoretic model of P2P networks. Specifically  we prove that it is NP-hard to decide whether our game has a Nash equilibrium and can stabilize.,roger wattenhofer,Not available,2011.0,10.1007/s00453-010-9398-9,Algorithmica,Thomas2011,False,,Springer,Not available,Topological Implications of Selfish Neighbor Selection in Unstructured Peer-to-Peer Networks,fcd6e86ba0b781583b7da06c996065cf,http://dx.doi.org/10.1007/s00453-010-9398-9
815,We study the performances of Nash equilibria in isolation games  a class of competitive location games recently introduced in Zhao et al. (Proc. of the 19th International Symposium on Algorithms and Computation (ISAAC)  pp. 148–159  ,vittorio bilo,Not available,2011.0,10.1007/s10878-010-9300-3,Journal of Combinatorial Optimization,Vittorio2011,False,,Springer,Not available,On the performances of Nash equilibria in isolation games,8ec90719d42c1533641eb7fcfd6fc9fe,http://dx.doi.org/10.1007/s10878-010-9300-3
816,We study the performances of Nash equilibria in isolation games  a class of competitive location games recently introduced in Zhao et al. (Proc. of the 19th International Symposium on Algorithms and Computation (ISAAC)  pp. 148–159  ,michele flammini,Not available,2011.0,10.1007/s10878-010-9300-3,Journal of Combinatorial Optimization,Vittorio2011,False,,Springer,Not available,On the performances of Nash equilibria in isolation games,8ec90719d42c1533641eb7fcfd6fc9fe,http://dx.doi.org/10.1007/s10878-010-9300-3
817,We study the performances of Nash equilibria in isolation games  a class of competitive location games recently introduced in Zhao et al. (Proc. of the 19th International Symposium on Algorithms and Computation (ISAAC)  pp. 148–159  ,gianpiero monaco,Not available,2011.0,10.1007/s10878-010-9300-3,Journal of Combinatorial Optimization,Vittorio2011,False,,Springer,Not available,On the performances of Nash equilibria in isolation games,8ec90719d42c1533641eb7fcfd6fc9fe,http://dx.doi.org/10.1007/s10878-010-9300-3
818,We study the performances of Nash equilibria in isolation games  a class of competitive location games recently introduced in Zhao et al. (Proc. of the 19th International Symposium on Algorithms and Computation (ISAAC)  pp. 148–159  ,luca moscardelli,Not available,2011.0,10.1007/s10878-010-9300-3,Journal of Combinatorial Optimization,Vittorio2011,False,,Springer,Not available,On the performances of Nash equilibria in isolation games,8ec90719d42c1533641eb7fcfd6fc9fe,http://dx.doi.org/10.1007/s10878-010-9300-3
819,We study the performance of approximate Nash equilibria for congestion games with polynomial latency functions. We consider how much the price of anarchy worsens and how much the price of stability improves as a function of the approximation factor ,george christodoulou,Not available,2011.0,10.1007/s00453-010-9449-2,Algorithmica,George2011,False,,Springer,Not available,On the Performance of Approximate Equilibria in Congestion Games,20a5e39b35a1162c769a65e7ed694985,http://dx.doi.org/10.1007/s00453-010-9449-2
820,We study the performance of approximate Nash equilibria for congestion games with polynomial latency functions. We consider how much the price of anarchy worsens and how much the price of stability improves as a function of the approximation factor ,elias koutsoupias,Not available,2011.0,10.1007/s00453-010-9449-2,Algorithmica,George2011,False,,Springer,Not available,On the Performance of Approximate Equilibria in Congestion Games,20a5e39b35a1162c769a65e7ed694985,http://dx.doi.org/10.1007/s00453-010-9449-2
821,The relation between the Faustmann model and “a forestry of prices” as a concept of thought was examined. At first  the meaning of the Faustmann model in economic sciences is the explanation of allocation and distribution by prices. The rotation age determination plays a secondary role only. Secondly  “a forestry of prices” as an application of the “free to choose” way of thinking is explained. The concept allows us to understand how individuals of anonymous groups achieve forest sustainability and provide forest environmental goods. Thirdly  the relation between the Faustmann model and “a forestry of prices” is discussed. For this purpose  the Faustmann model is described as a scientific laboratory. It helps us to observe how equilibrium arises as a non-intended result of individual welfare maximization in anonymous interactions. And conversely with the help of “a forestry of prices”  we understand also that the individual maximization approach of the Faustmann model re-enacts the unintended interaction situations in anonymous group. With help of the Faustmann model  we can understand deep aspects of “a forestry of prices”. Vice versa  “a forestry of prices” shows the meaning of the formal solutions of the Faustmann model.,peter deegen,Not available,2011.0,10.1007/s10342-009-0336-9,European Journal of Forest Research,Peter2011,False,,Springer,Not available,The Faustmann model as a model for a forestry of prices,45ef13615a3430e244e8b142fd1a3350,http://dx.doi.org/10.1007/s10342-009-0336-9
822,We study the performance of approximate Nash equilibria for congestion games with polynomial latency functions. We consider how much the price of anarchy worsens and how much the price of stability improves as a function of the approximation factor ,paul spirakis,Not available,2011.0,10.1007/s00453-010-9449-2,Algorithmica,George2011,False,,Springer,Not available,On the Performance of Approximate Equilibria in Congestion Games,20a5e39b35a1162c769a65e7ed694985,http://dx.doi.org/10.1007/s00453-010-9449-2
823,We analyze the performance of protocols for load balancing in distributed systems based on no-regret algorithms from online learning theory. These protocols treat load balancing as a repeated game and apply algorithms whose average performance over time is guaranteed to match or exceed the average performance of the best strategy in hindsight. Our approach captures two major aspects of distributed systems. First  in our setting of atomic load balancing  every single process can have a significant impact on the performance and behavior of the system. Furthermore  although in distributed systems participants can query the current state of the system they cannot reliably predict the effect of their actions on it. We address this issue by considering load balancing games in the bulletin board model  where players can find out the delay on all machines  but do not have information on what their experienced delay would have been if they had selected another machine. We show that under these more realistic assumptions  if all players use the well-known multiplicative weights algorithm  then the quality of the resulting solution is exponentially better than the worst correlated equilibrium  and almost as good as that of the worst Nash. These tighter bounds are derived from analyzing the dynamics of a multi-agent learning system.,robert kleinberg,Not available,2011.0,10.1007/s00446-011-0129-5,Distributed Computing,Robert2011,False,,Springer,Not available,Load balancing without regret in the bulletin board model,3a1a17f778a74d7f9cc56671962ac993,http://dx.doi.org/10.1007/s00446-011-0129-5
824,We analyze the performance of protocols for load balancing in distributed systems based on no-regret algorithms from online learning theory. These protocols treat load balancing as a repeated game and apply algorithms whose average performance over time is guaranteed to match or exceed the average performance of the best strategy in hindsight. Our approach captures two major aspects of distributed systems. First  in our setting of atomic load balancing  every single process can have a significant impact on the performance and behavior of the system. Furthermore  although in distributed systems participants can query the current state of the system they cannot reliably predict the effect of their actions on it. We address this issue by considering load balancing games in the bulletin board model  where players can find out the delay on all machines  but do not have information on what their experienced delay would have been if they had selected another machine. We show that under these more realistic assumptions  if all players use the well-known multiplicative weights algorithm  then the quality of the resulting solution is exponentially better than the worst correlated equilibrium  and almost as good as that of the worst Nash. These tighter bounds are derived from analyzing the dynamics of a multi-agent learning system.,georgios piliouras,Not available,2011.0,10.1007/s00446-011-0129-5,Distributed Computing,Robert2011,False,,Springer,Not available,Load balancing without regret in the bulletin board model,3a1a17f778a74d7f9cc56671962ac993,http://dx.doi.org/10.1007/s00446-011-0129-5
825,We analyze the performance of protocols for load balancing in distributed systems based on no-regret algorithms from online learning theory. These protocols treat load balancing as a repeated game and apply algorithms whose average performance over time is guaranteed to match or exceed the average performance of the best strategy in hindsight. Our approach captures two major aspects of distributed systems. First  in our setting of atomic load balancing  every single process can have a significant impact on the performance and behavior of the system. Furthermore  although in distributed systems participants can query the current state of the system they cannot reliably predict the effect of their actions on it. We address this issue by considering load balancing games in the bulletin board model  where players can find out the delay on all machines  but do not have information on what their experienced delay would have been if they had selected another machine. We show that under these more realistic assumptions  if all players use the well-known multiplicative weights algorithm  then the quality of the resulting solution is exponentially better than the worst correlated equilibrium  and almost as good as that of the worst Nash. These tighter bounds are derived from analyzing the dynamics of a multi-agent learning system.,eva tardos,Not available,2011.0,10.1007/s00446-011-0129-5,Distributed Computing,Robert2011,False,,Springer,Not available,Load balancing without regret in the bulletin board model,3a1a17f778a74d7f9cc56671962ac993,http://dx.doi.org/10.1007/s00446-011-0129-5
826,We consider a general class of non-cooperative ,martin hoefer,Not available,2011.0,10.1007/s00453-009-9367-3,Algorithmica,Martin2011,False,,Springer,Not available,Competitive Cost Sharing with Economies of Scale,3e8596f207fb2447652d31983bd7a24e,http://dx.doi.org/10.1007/s00453-009-9367-3
827,We study the survivable version of the game theoretic network formation model known as the Connection Game  originally introduced in Anshelevich et al. (Proc. 35th ACM Symposium on Theory of Computing  ,elliot anshelevich,Not available,2011.0,10.1007/s00224-011-9317-8,Theory of Computing Systems,Elliot2011,False,,Springer,Not available,Price of Stability in Survivable Network Design,1f9cefcd85f0a64234eb1002ab008f3d,http://dx.doi.org/10.1007/s00224-011-9317-8
828,We study the survivable version of the game theoretic network formation model known as the Connection Game  originally introduced in Anshelevich et al. (Proc. 35th ACM Symposium on Theory of Computing  ,bugra caskurlu,Not available,2011.0,10.1007/s00224-011-9317-8,Theory of Computing Systems,Elliot2011,False,,Springer,Not available,Price of Stability in Survivable Network Design,1f9cefcd85f0a64234eb1002ab008f3d,http://dx.doi.org/10.1007/s00224-011-9317-8
829,We investigate optimal load balancing strategies for a multi-class multi-server processor-sharing system with a Poisson input stream  heterogeneous service rates  and a server-dependent holding cost per unit time. Specifically  we study (i) the centralized setting in which a dispatcher routes incoming jobs based on their service time requirements so as to minimize the weighted mean sojourn time in the system; and (ii) the decentralized  distributed non-cooperative setting in which each job  aware of its service time  selects a server with the objective of minimizing its weighted mean sojourn time in the system. For the decentralized setting we show the existence of a potential function  which allows us to transform the non-cooperative game into a standard convex optimization problem.For the two aforementioned settings  we characterize the set of optimal routing policies and obtain a closed form expression for the load on each server under any such policy. Furthermore  we show the existence of an optimal policy that routes a job independently of its service time requirement. We also show that the set of servers used in the decentralized setting is a subset of set of servers used in the centralized setting. Finally  we compare the performance perceived by jobs in the two settings by studying the so-called Price of Anarchy (PoA)  that is  the ratio between the decentralized and the optimal centralized solutions. When the holding cost per unit time is the same for all servers  it is known that the PoA is upper bounded by the number of servers in the system. Interestingly  we show that the PoA for our system can be unbounded. In particular this indicates that in our system  the performance of selfish routing can be extremely inefficient.,e. altman,Not available,2011.0,10.1007/s11235-010-9300-8,Telecommunication Systems,E.2011,False,,Springer,Not available,Load balancing in processor sharing systems,37397e5775fe7656b8c5896d9f775a7b,http://dx.doi.org/10.1007/s11235-010-9300-8
830,We investigate optimal load balancing strategies for a multi-class multi-server processor-sharing system with a Poisson input stream  heterogeneous service rates  and a server-dependent holding cost per unit time. Specifically  we study (i) the centralized setting in which a dispatcher routes incoming jobs based on their service time requirements so as to minimize the weighted mean sojourn time in the system; and (ii) the decentralized  distributed non-cooperative setting in which each job  aware of its service time  selects a server with the objective of minimizing its weighted mean sojourn time in the system. For the decentralized setting we show the existence of a potential function  which allows us to transform the non-cooperative game into a standard convex optimization problem.For the two aforementioned settings  we characterize the set of optimal routing policies and obtain a closed form expression for the load on each server under any such policy. Furthermore  we show the existence of an optimal policy that routes a job independently of its service time requirement. We also show that the set of servers used in the decentralized setting is a subset of set of servers used in the centralized setting. Finally  we compare the performance perceived by jobs in the two settings by studying the so-called Price of Anarchy (PoA)  that is  the ratio between the decentralized and the optimal centralized solutions. When the holding cost per unit time is the same for all servers  it is known that the PoA is upper bounded by the number of servers in the system. Interestingly  we show that the PoA for our system can be unbounded. In particular this indicates that in our system  the performance of selfish routing can be extremely inefficient.,u. ayesta,Not available,2011.0,10.1007/s11235-010-9300-8,Telecommunication Systems,E.2011,False,,Springer,Not available,Load balancing in processor sharing systems,37397e5775fe7656b8c5896d9f775a7b,http://dx.doi.org/10.1007/s11235-010-9300-8
831,We investigate optimal load balancing strategies for a multi-class multi-server processor-sharing system with a Poisson input stream  heterogeneous service rates  and a server-dependent holding cost per unit time. Specifically  we study (i) the centralized setting in which a dispatcher routes incoming jobs based on their service time requirements so as to minimize the weighted mean sojourn time in the system; and (ii) the decentralized  distributed non-cooperative setting in which each job  aware of its service time  selects a server with the objective of minimizing its weighted mean sojourn time in the system. For the decentralized setting we show the existence of a potential function  which allows us to transform the non-cooperative game into a standard convex optimization problem.For the two aforementioned settings  we characterize the set of optimal routing policies and obtain a closed form expression for the load on each server under any such policy. Furthermore  we show the existence of an optimal policy that routes a job independently of its service time requirement. We also show that the set of servers used in the decentralized setting is a subset of set of servers used in the centralized setting. Finally  we compare the performance perceived by jobs in the two settings by studying the so-called Price of Anarchy (PoA)  that is  the ratio between the decentralized and the optimal centralized solutions. When the holding cost per unit time is the same for all servers  it is known that the PoA is upper bounded by the number of servers in the system. Interestingly  we show that the PoA for our system can be unbounded. In particular this indicates that in our system  the performance of selfish routing can be extremely inefficient.,b. prabhu,Not available,2011.0,10.1007/s11235-010-9300-8,Telecommunication Systems,E.2011,False,,Springer,Not available,Load balancing in processor sharing systems,37397e5775fe7656b8c5896d9f775a7b,http://dx.doi.org/10.1007/s11235-010-9300-8
832,The relation between the Faustmann model and “a forestry of prices” as a concept of thought was examined. At first  the meaning of the Faustmann model in economic sciences is the explanation of allocation and distribution by prices. The rotation age determination plays a secondary role only. Secondly  “a forestry of prices” as an application of the “free to choose” way of thinking is explained. The concept allows us to understand how individuals of anonymous groups achieve forest sustainability and provide forest environmental goods. Thirdly  the relation between the Faustmann model and “a forestry of prices” is discussed. For this purpose  the Faustmann model is described as a scientific laboratory. It helps us to observe how equilibrium arises as a non-intended result of individual welfare maximization in anonymous interactions. And conversely with the help of “a forestry of prices”  we understand also that the individual maximization approach of the Faustmann model re-enacts the unintended interaction situations in anonymous group. With help of the Faustmann model  we can understand deep aspects of “a forestry of prices”. Vice versa  “a forestry of prices” shows the meaning of the formal solutions of the Faustmann model.,martin hostettler,Not available,2011.0,10.1007/s10342-009-0336-9,European Journal of Forest Research,Peter2011,False,,Springer,Not available,The Faustmann model as a model for a forestry of prices,45ef13615a3430e244e8b142fd1a3350,http://dx.doi.org/10.1007/s10342-009-0336-9
833,We study a game that models a market in which heterogeneous producers of perfect substitutes make pricing decisions in a first stage  followed by consumers that select a producer that sells at lowest price. As opposed to Cournot or Bertrand competition  producers select prices using a ,jose correa,Not available,2014.0,10.1007/s10107-013-0682-8,Mathematical Programming,R.2014,False,,Springer,Not available,Pricing with markups in industries with increasing marginal costs,a03a68420b7252a468207e6f535595ca,http://dx.doi.org/10.1007/s10107-013-0682-8
834,We study a game that models a market in which heterogeneous producers of perfect substitutes make pricing decisions in a first stage  followed by consumers that select a producer that sells at lowest price. As opposed to Cournot or Bertrand competition  producers select prices using a ,nicolas figueroa,Not available,2014.0,10.1007/s10107-013-0682-8,Mathematical Programming,R.2014,False,,Springer,Not available,Pricing with markups in industries with increasing marginal costs,a03a68420b7252a468207e6f535595ca,http://dx.doi.org/10.1007/s10107-013-0682-8
835,We study a game that models a market in which heterogeneous producers of perfect substitutes make pricing decisions in a first stage  followed by consumers that select a producer that sells at lowest price. As opposed to Cournot or Bertrand competition  producers select prices using a ,roger lederman,Not available,2014.0,10.1007/s10107-013-0682-8,Mathematical Programming,R.2014,False,,Springer,Not available,Pricing with markups in industries with increasing marginal costs,a03a68420b7252a468207e6f535595ca,http://dx.doi.org/10.1007/s10107-013-0682-8
836,We study a game that models a market in which heterogeneous producers of perfect substitutes make pricing decisions in a first stage  followed by consumers that select a producer that sells at lowest price. As opposed to Cournot or Bertrand competition  producers select prices using a ,nicolas stier-moses,Not available,2014.0,10.1007/s10107-013-0682-8,Mathematical Programming,R.2014,False,,Springer,Not available,Pricing with markups in industries with increasing marginal costs,a03a68420b7252a468207e6f535595ca,http://dx.doi.org/10.1007/s10107-013-0682-8
837,We reconsider the well-studied Selfish Routing game with affine latency functions. The Price of Anarchy for this class of games takes maximum value 4/3; this maximum is attained already for a simple network of two parallel links  known as Pigou’s network. We improve upon the value 4/3 by means of Coordination Mechanisms.We increase the latency functions of the edges in the network  i.e.  if ,giorgos christodoulou,Not available,2014.0,10.1007/s00453-013-9753-8,Algorithmica,Giorgos2014,False,,Springer,Not available,Improving the Price of Anarchy for Selfish Routing via Coordination Mechanisms,84d043946de74a546a65147685ae0130,http://dx.doi.org/10.1007/s00453-013-9753-8
838,We reconsider the well-studied Selfish Routing game with affine latency functions. The Price of Anarchy for this class of games takes maximum value 4/3; this maximum is attained already for a simple network of two parallel links  known as Pigou’s network. We improve upon the value 4/3 by means of Coordination Mechanisms.We increase the latency functions of the edges in the network  i.e.  if ,kurt mehlhorn,Not available,2014.0,10.1007/s00453-013-9753-8,Algorithmica,Giorgos2014,False,,Springer,Not available,Improving the Price of Anarchy for Selfish Routing via Coordination Mechanisms,84d043946de74a546a65147685ae0130,http://dx.doi.org/10.1007/s00453-013-9753-8
839,We reconsider the well-studied Selfish Routing game with affine latency functions. The Price of Anarchy for this class of games takes maximum value 4/3; this maximum is attained already for a simple network of two parallel links  known as Pigou’s network. We improve upon the value 4/3 by means of Coordination Mechanisms.We increase the latency functions of the edges in the network  i.e.  if ,evangelia pyrga,Not available,2014.0,10.1007/s00453-013-9753-8,Algorithmica,Giorgos2014,False,,Springer,Not available,Improving the Price of Anarchy for Selfish Routing via Coordination Mechanisms,84d043946de74a546a65147685ae0130,http://dx.doi.org/10.1007/s00453-013-9753-8
840,We study asymmetric atomic selfish routing in ring networks  which has diverse practical applications in network design and analysis. We are concerned with minimizing the maximum latency of source-destination node-pairs over links with linear latencies. We show that there exists an optimal solution that is a 9-approximate Nash equilibrium  significantly improving the existing upper bound of 54 on the instability factor. We present fast implementation of the best response dynamics for computing a Nash equilibrium. Furthermore  we perform empirical study on the price of stability  narrowing the gap between the lower and upper bounds to 0.7436.,bo chen,Not available,2014.0,10.1007/s10114-014-3055-1,Acta Mathematica Sinica  English Series,Bo2014,False,,Springer,Not available,Stability vs. optimality in selfish ring routing,b9d0946ff173f4c8c7d3869ad818e58e,http://dx.doi.org/10.1007/s10114-014-3055-1
841,We study asymmetric atomic selfish routing in ring networks  which has diverse practical applications in network design and analysis. We are concerned with minimizing the maximum latency of source-destination node-pairs over links with linear latencies. We show that there exists an optimal solution that is a 9-approximate Nash equilibrium  significantly improving the existing upper bound of 54 on the instability factor. We present fast implementation of the best response dynamics for computing a Nash equilibrium. Furthermore  we perform empirical study on the price of stability  narrowing the gap between the lower and upper bounds to 0.7436.,xujin chen,Not available,2014.0,10.1007/s10114-014-3055-1,Acta Mathematica Sinica  English Series,Bo2014,False,,Springer,Not available,Stability vs. optimality in selfish ring routing,b9d0946ff173f4c8c7d3869ad818e58e,http://dx.doi.org/10.1007/s10114-014-3055-1
842,We study asymmetric atomic selfish routing in ring networks  which has diverse practical applications in network design and analysis. We are concerned with minimizing the maximum latency of source-destination node-pairs over links with linear latencies. We show that there exists an optimal solution that is a 9-approximate Nash equilibrium  significantly improving the existing upper bound of 54 on the instability factor. We present fast implementation of the best response dynamics for computing a Nash equilibrium. Furthermore  we perform empirical study on the price of stability  narrowing the gap between the lower and upper bounds to 0.7436.,jie hu,Not available,2014.0,10.1007/s10114-014-3055-1,Acta Mathematica Sinica  English Series,Bo2014,False,,Springer,Not available,Stability vs. optimality in selfish ring routing,b9d0946ff173f4c8c7d3869ad818e58e,http://dx.doi.org/10.1007/s10114-014-3055-1
843,The relation between the Faustmann model and “a forestry of prices” as a concept of thought was examined. At first  the meaning of the Faustmann model in economic sciences is the explanation of allocation and distribution by prices. The rotation age determination plays a secondary role only. Secondly  “a forestry of prices” as an application of the “free to choose” way of thinking is explained. The concept allows us to understand how individuals of anonymous groups achieve forest sustainability and provide forest environmental goods. Thirdly  the relation between the Faustmann model and “a forestry of prices” is discussed. For this purpose  the Faustmann model is described as a scientific laboratory. It helps us to observe how equilibrium arises as a non-intended result of individual welfare maximization in anonymous interactions. And conversely with the help of “a forestry of prices”  we understand also that the individual maximization approach of the Faustmann model re-enacts the unintended interaction situations in anonymous group. With help of the Faustmann model  we can understand deep aspects of “a forestry of prices”. Vice versa  “a forestry of prices” shows the meaning of the formal solutions of the Faustmann model.,guillermo navarro,Not available,2011.0,10.1007/s10342-009-0336-9,European Journal of Forest Research,Peter2011,False,,Springer,Not available,The Faustmann model as a model for a forestry of prices,45ef13615a3430e244e8b142fd1a3350,http://dx.doi.org/10.1007/s10342-009-0336-9
844,Consider the following scheduling game. A set of jobs  each controlled by a selfish agent  are to be assigned to ,leah epstein,Not available,2014.0,10.1007/s10878-012-9555-y,Journal of Combinatorial Optimization,Leah2014,False,,Springer,Not available,The cost of selfishness for maximizing the minimum load on uniformly related machines,5b98bf11cb39a799b3c61143b34389cd,http://dx.doi.org/10.1007/s10878-012-9555-y
845,Consider the following scheduling game. A set of jobs  each controlled by a selfish agent  are to be assigned to ,elena kleiman,Not available,2014.0,10.1007/s10878-012-9555-y,Journal of Combinatorial Optimization,Leah2014,False,,Springer,Not available,The cost of selfishness for maximizing the minimum load on uniformly related machines,5b98bf11cb39a799b3c61143b34389cd,http://dx.doi.org/10.1007/s10878-012-9555-y
846,Consider the following scheduling game. A set of jobs  each controlled by a selfish agent  are to be assigned to ,rob stee,Not available,2014.0,10.1007/s10878-012-9555-y,Journal of Combinatorial Optimization,Leah2014,False,,Springer,Not available,The cost of selfishness for maximizing the minimum load on uniformly related machines,5b98bf11cb39a799b3c61143b34389cd,http://dx.doi.org/10.1007/s10878-012-9555-y
847,This paper studies a spatial economic model under network externalities  assuming a quadratic transport cost function. A classical circular model is applied where the consumers  each with a fixed demand  are uniformly distributed along the circumference of a circle. Assuming symmetric locations of profit-maximizing suppliers  a unique symmetric price equilibrium is derived under both positive and negative network externalities. The price equilibrium is obtained using the tridiagonality property of the demand system. The equilibrium price is higher with negative network externalities than the price without externalities whereas the converse is true with positive network externalities. The efficiency loss of the free entry equilibrium is studied in terms of the price of anarchy. Numerical experiments suggest that the price of anarchy is robust to weak externalities but can be significant under strong network externalities.,t. heikkinen,Not available,2014.0,10.1007/s12351-013-0136-3,Operational Research,T.2014,False,,Springer,Not available,A spatial economic model under network externalities: symmetric equilibrium and efficiency,eb1779a944ff620af7471e7f00d24be4,http://dx.doi.org/10.1007/s12351-013-0136-3
848,We consider a model of next-hop routing by self-interested agents. In this model  nodes in a graph (representing ISPs  Autonomous Systems  etc.) make pricing decisions of how much to charge for forwarding traffic from each of their upstream neighbors  and routing decisions of which downstream neighbors to forward traffic to (i.e.  choosing the next hop). Traffic originates at a subset of these nodes that derive a utility when the traffic is routed to its destination node; the traffic demand is elastic and the utility derived from it can be different for different source nodes. Our next-hop routing and pricing model is in sharp contrast with the more common source routing and pricing models  in which the source of traffic determines the entire route from source to destination. For our model  we begin by showing sufficient conditions for prices to result in a Nash equilibrium  and in fact give an efficient algorithm to compute a Nash equilibrium which is as good as the centralized optimum  thus proving that the price of stability is 1. When only a single source node exists  then the price of anarchy is 1 as well  as long as some minor assumptions on player behavior is made. The above results hold for arbitrary convex pricing functions  but with the assumption that the utilities derived from getting traffic to its destination are linear. When utilities can be non-linear functions  we show that Nash equilibrium may not exist  even with simple discrete pricing models.,elliot anshelevich,Not available,2014.0,10.1007/s00224-012-9435-y,Theory of Computing Systems,Elliot2014,False,,Springer,Not available,Strategic Pricing in Next-Hop Routing with Elastic Demands,0f921513b90b6c8b8b550ca12a19d19e,http://dx.doi.org/10.1007/s00224-012-9435-y
849,We consider a model of next-hop routing by self-interested agents. In this model  nodes in a graph (representing ISPs  Autonomous Systems  etc.) make pricing decisions of how much to charge for forwarding traffic from each of their upstream neighbors  and routing decisions of which downstream neighbors to forward traffic to (i.e.  choosing the next hop). Traffic originates at a subset of these nodes that derive a utility when the traffic is routed to its destination node; the traffic demand is elastic and the utility derived from it can be different for different source nodes. Our next-hop routing and pricing model is in sharp contrast with the more common source routing and pricing models  in which the source of traffic determines the entire route from source to destination. For our model  we begin by showing sufficient conditions for prices to result in a Nash equilibrium  and in fact give an efficient algorithm to compute a Nash equilibrium which is as good as the centralized optimum  thus proving that the price of stability is 1. When only a single source node exists  then the price of anarchy is 1 as well  as long as some minor assumptions on player behavior is made. The above results hold for arbitrary convex pricing functions  but with the assumption that the utilities derived from getting traffic to its destination are linear. When utilities can be non-linear functions  we show that Nash equilibrium may not exist  even with simple discrete pricing models.,ameya hate,Not available,2014.0,10.1007/s00224-012-9435-y,Theory of Computing Systems,Elliot2014,False,,Springer,Not available,Strategic Pricing in Next-Hop Routing with Elastic Demands,0f921513b90b6c8b8b550ca12a19d19e,http://dx.doi.org/10.1007/s00224-012-9435-y
850,We consider a model of next-hop routing by self-interested agents. In this model  nodes in a graph (representing ISPs  Autonomous Systems  etc.) make pricing decisions of how much to charge for forwarding traffic from each of their upstream neighbors  and routing decisions of which downstream neighbors to forward traffic to (i.e.  choosing the next hop). Traffic originates at a subset of these nodes that derive a utility when the traffic is routed to its destination node; the traffic demand is elastic and the utility derived from it can be different for different source nodes. Our next-hop routing and pricing model is in sharp contrast with the more common source routing and pricing models  in which the source of traffic determines the entire route from source to destination. For our model  we begin by showing sufficient conditions for prices to result in a Nash equilibrium  and in fact give an efficient algorithm to compute a Nash equilibrium which is as good as the centralized optimum  thus proving that the price of stability is 1. When only a single source node exists  then the price of anarchy is 1 as well  as long as some minor assumptions on player behavior is made. The above results hold for arbitrary convex pricing functions  but with the assumption that the utilities derived from getting traffic to its destination are linear. When utilities can be non-linear functions  we show that Nash equilibrium may not exist  even with simple discrete pricing models.,koushik kar,Not available,2014.0,10.1007/s00224-012-9435-y,Theory of Computing Systems,Elliot2014,False,,Springer,Not available,Strategic Pricing in Next-Hop Routing with Elastic Demands,0f921513b90b6c8b8b550ca12a19d19e,http://dx.doi.org/10.1007/s00224-012-9435-y
851,,george christodoulou,Not available,2014.0,10.1007/978-3-642-27848-8_299-2,Encyclopedia of Algorithms,George2014,False,,Springer,Not available,Price of Anarchy,66db23292444db36f03e95d9c6e6945a,http://dx.doi.org/10.1007/978-3-642-27848-8_299-2
852,,erik demaine,Not available,2014.0,10.1007/978-3-642-27848-8_752-1,Encyclopedia of Algorithms,D.2014,False,,Springer,Not available,Network Creation Games,f530c1f7098c9e3a7a7acf1bdfbb42e7,http://dx.doi.org/10.1007/978-3-642-27848-8_752-1
853,,mohammadtaghi hajiaghayi,Not available,2014.0,10.1007/978-3-642-27848-8_752-1,Encyclopedia of Algorithms,D.2014,False,,Springer,Not available,Network Creation Games,f530c1f7098c9e3a7a7acf1bdfbb42e7,http://dx.doi.org/10.1007/978-3-642-27848-8_752-1
854,The ,tamer basar,Not available,2011.0,10.1007/s13235-010-0002-3,Dynamic Games and Applications,Tamer2011,False,,Springer,Not available,Prices of Anarchy  Information  and Cooperation in Differential Games,72c6ce9e54dade443eecbab9da430e09,http://dx.doi.org/10.1007/s13235-010-0002-3
855,,hamid mahini,Not available,2014.0,10.1007/978-3-642-27848-8_752-1,Encyclopedia of Algorithms,D.2014,False,,Springer,Not available,Network Creation Games,f530c1f7098c9e3a7a7acf1bdfbb42e7,http://dx.doi.org/10.1007/978-3-642-27848-8_752-1
856,,morteza zadimoghaddam,Not available,2014.0,10.1007/978-3-642-27848-8_752-1,Encyclopedia of Algorithms,D.2014,False,,Springer,Not available,Network Creation Games,f530c1f7098c9e3a7a7acf1bdfbb42e7,http://dx.doi.org/10.1007/978-3-642-27848-8_752-1
857,Network creation games model the autonomous formation of an interconnected system of selfish users. In particular  when the network will serve as a digital communication infrastructure  each user is identified by a node of the network  and contributes to the build-up process by strategically balancing between her ,davide bilo,Not available,2014.0,10.1007/978-3-319-09620-9_17,Structural Information and Communication Complexity,Davide2014,False,,Springer,Not available,Network Creation Games with Traceroute-Based Strategies,80b32c9f9d9b4136b4901a5707d32393,http://dx.doi.org/10.1007/978-3-319-09620-9_17
858,Network creation games model the autonomous formation of an interconnected system of selfish users. In particular  when the network will serve as a digital communication infrastructure  each user is identified by a node of the network  and contributes to the build-up process by strategically balancing between her ,luciano guala,Not available,2014.0,10.1007/978-3-319-09620-9_17,Structural Information and Communication Complexity,Davide2014,False,,Springer,Not available,Network Creation Games with Traceroute-Based Strategies,80b32c9f9d9b4136b4901a5707d32393,http://dx.doi.org/10.1007/978-3-319-09620-9_17
859,Network creation games model the autonomous formation of an interconnected system of selfish users. In particular  when the network will serve as a digital communication infrastructure  each user is identified by a node of the network  and contributes to the build-up process by strategically balancing between her ,stefano leucci,Not available,2014.0,10.1007/978-3-319-09620-9_17,Structural Information and Communication Complexity,Davide2014,False,,Springer,Not available,Network Creation Games with Traceroute-Based Strategies,80b32c9f9d9b4136b4901a5707d32393,http://dx.doi.org/10.1007/978-3-319-09620-9_17
860,Network creation games model the autonomous formation of an interconnected system of selfish users. In particular  when the network will serve as a digital communication infrastructure  each user is identified by a node of the network  and contributes to the build-up process by strategically balancing between her ,guido proietti,Not available,2014.0,10.1007/978-3-319-09620-9_17,Structural Information and Communication Complexity,Davide2014,False,,Springer,Not available,Network Creation Games with Traceroute-Based Strategies,80b32c9f9d9b4136b4901a5707d32393,http://dx.doi.org/10.1007/978-3-319-09620-9_17
861,The Firefighter Problem was proposed in 1995 [,carme alvarez,Not available,2014.0,10.1007/978-3-319-13123-8_9,Algorithms and Models for the Web Graph,Carme2014,False,,Springer,Not available,Firefighting as a Game,d8df5dc0d10e2c5b71f02e602e8575a5,http://dx.doi.org/10.1007/978-3-319-13123-8_9
862,The Firefighter Problem was proposed in 1995 [,maria blesa,Not available,2014.0,10.1007/978-3-319-13123-8_9,Algorithms and Models for the Web Graph,Carme2014,False,,Springer,Not available,Firefighting as a Game,d8df5dc0d10e2c5b71f02e602e8575a5,http://dx.doi.org/10.1007/978-3-319-13123-8_9
863,The Firefighter Problem was proposed in 1995 [,hendrik molter,Not available,2014.0,10.1007/978-3-319-13123-8_9,Algorithms and Models for the Web Graph,Carme2014,False,,Springer,Not available,Firefighting as a Game,d8df5dc0d10e2c5b71f02e602e8575a5,http://dx.doi.org/10.1007/978-3-319-13123-8_9
864,We consider wireless networks that can be modeled by multiple access channels in which all the terminals are equipped with multiple antennas. The propagation model used to account for the effects of transmit and receive antenna correlations is the unitary-invariant-unitary model  which is one of the most general models available in the literature. In this context  we introduce and analyze two resource allocation games. In both games  the mobile stations selfishly choose their power allocation policies in order to maximize their individual uplink transmission rates; in particular they can ignore some specified centralized policies. In the first game considered  the base station implements successive interference cancellation (SIC) and each mobile station chooses his best space-time power allocation scheme; here  a coordination mechanism is used to indicate to the users the order in which the receiver applies SIC. In the second framework  the base station is assumed to implement single-user decoding. For these two games a thorough analysis of the Nash equilibrium is provided: the existence and uniqueness issues are addressed; the corresponding power allocation policies are determined by exploiting random matrix theory; the sum-rate efficiency of the equilibrium is studied analytically in the low and high signal-to-noise ratio regimes and by simulations in more typical scenarios. Simulations show that  in particular  the sum-rate efficiency is high for the type of systems investigated and the performance loss due to the use of the proposed suboptimum coordination mechanism is very small.,elena-veronica belmega,Not available,2011.0,10.1007/s11235-010-9305-3,Telecommunication Systems,Elena-Veronica2011,False,,Springer,Not available,Power allocation games in wireless networks of multi-antenna terminals,c86b31b1aa63e311d18a47e529e771f8,http://dx.doi.org/10.1007/s11235-010-9305-3
865,The ,quanyan zhu,Not available,2011.0,10.1007/s13235-010-0002-3,Dynamic Games and Applications,Tamer2011,False,,Springer,Not available,Prices of Anarchy  Information  and Cooperation in Differential Games,72c6ce9e54dade443eecbab9da430e09,http://dx.doi.org/10.1007/s13235-010-0002-3
866,We consider wireless networks that can be modeled by multiple access channels in which all the terminals are equipped with multiple antennas. The propagation model used to account for the effects of transmit and receive antenna correlations is the unitary-invariant-unitary model  which is one of the most general models available in the literature. In this context  we introduce and analyze two resource allocation games. In both games  the mobile stations selfishly choose their power allocation policies in order to maximize their individual uplink transmission rates; in particular they can ignore some specified centralized policies. In the first game considered  the base station implements successive interference cancellation (SIC) and each mobile station chooses his best space-time power allocation scheme; here  a coordination mechanism is used to indicate to the users the order in which the receiver applies SIC. In the second framework  the base station is assumed to implement single-user decoding. For these two games a thorough analysis of the Nash equilibrium is provided: the existence and uniqueness issues are addressed; the corresponding power allocation policies are determined by exploiting random matrix theory; the sum-rate efficiency of the equilibrium is studied analytically in the low and high signal-to-noise ratio regimes and by simulations in more typical scenarios. Simulations show that  in particular  the sum-rate efficiency is high for the type of systems investigated and the performance loss due to the use of the proposed suboptimum coordination mechanism is very small.,samson lasaulce,Not available,2011.0,10.1007/s11235-010-9305-3,Telecommunication Systems,Elena-Veronica2011,False,,Springer,Not available,Power allocation games in wireless networks of multi-antenna terminals,c86b31b1aa63e311d18a47e529e771f8,http://dx.doi.org/10.1007/s11235-010-9305-3
867,We consider wireless networks that can be modeled by multiple access channels in which all the terminals are equipped with multiple antennas. The propagation model used to account for the effects of transmit and receive antenna correlations is the unitary-invariant-unitary model  which is one of the most general models available in the literature. In this context  we introduce and analyze two resource allocation games. In both games  the mobile stations selfishly choose their power allocation policies in order to maximize their individual uplink transmission rates; in particular they can ignore some specified centralized policies. In the first game considered  the base station implements successive interference cancellation (SIC) and each mobile station chooses his best space-time power allocation scheme; here  a coordination mechanism is used to indicate to the users the order in which the receiver applies SIC. In the second framework  the base station is assumed to implement single-user decoding. For these two games a thorough analysis of the Nash equilibrium is provided: the existence and uniqueness issues are addressed; the corresponding power allocation policies are determined by exploiting random matrix theory; the sum-rate efficiency of the equilibrium is studied analytically in the low and high signal-to-noise ratio regimes and by simulations in more typical scenarios. Simulations show that  in particular  the sum-rate efficiency is high for the type of systems investigated and the performance loss due to the use of the proposed suboptimum coordination mechanism is very small.,merouane debbah,Not available,2011.0,10.1007/s11235-010-9305-3,Telecommunication Systems,Elena-Veronica2011,False,,Springer,Not available,Power allocation games in wireless networks of multi-antenna terminals,c86b31b1aa63e311d18a47e529e771f8,http://dx.doi.org/10.1007/s11235-010-9305-3
868,We consider wireless networks that can be modeled by multiple access channels in which all the terminals are equipped with multiple antennas. The propagation model used to account for the effects of transmit and receive antenna correlations is the unitary-invariant-unitary model  which is one of the most general models available in the literature. In this context  we introduce and analyze two resource allocation games. In both games  the mobile stations selfishly choose their power allocation policies in order to maximize their individual uplink transmission rates; in particular they can ignore some specified centralized policies. In the first game considered  the base station implements successive interference cancellation (SIC) and each mobile station chooses his best space-time power allocation scheme; here  a coordination mechanism is used to indicate to the users the order in which the receiver applies SIC. In the second framework  the base station is assumed to implement single-user decoding. For these two games a thorough analysis of the Nash equilibrium is provided: the existence and uniqueness issues are addressed; the corresponding power allocation policies are determined by exploiting random matrix theory; the sum-rate efficiency of the equilibrium is studied analytically in the low and high signal-to-noise ratio regimes and by simulations in more typical scenarios. Simulations show that  in particular  the sum-rate efficiency is high for the type of systems investigated and the performance loss due to the use of the proposed suboptimum coordination mechanism is very small.,marc jungers,Not available,2011.0,10.1007/s11235-010-9305-3,Telecommunication Systems,Elena-Veronica2011,False,,Springer,Not available,Power allocation games in wireless networks of multi-antenna terminals,c86b31b1aa63e311d18a47e529e771f8,http://dx.doi.org/10.1007/s11235-010-9305-3
869,We consider wireless networks that can be modeled by multiple access channels in which all the terminals are equipped with multiple antennas. The propagation model used to account for the effects of transmit and receive antenna correlations is the unitary-invariant-unitary model  which is one of the most general models available in the literature. In this context  we introduce and analyze two resource allocation games. In both games  the mobile stations selfishly choose their power allocation policies in order to maximize their individual uplink transmission rates; in particular they can ignore some specified centralized policies. In the first game considered  the base station implements successive interference cancellation (SIC) and each mobile station chooses his best space-time power allocation scheme; here  a coordination mechanism is used to indicate to the users the order in which the receiver applies SIC. In the second framework  the base station is assumed to implement single-user decoding. For these two games a thorough analysis of the Nash equilibrium is provided: the existence and uniqueness issues are addressed; the corresponding power allocation policies are determined by exploiting random matrix theory; the sum-rate efficiency of the equilibrium is studied analytically in the low and high signal-to-noise ratio regimes and by simulations in more typical scenarios. Simulations show that  in particular  the sum-rate efficiency is high for the type of systems investigated and the performance loss due to the use of the proposed suboptimum coordination mechanism is very small.,julien dumont,Not available,2011.0,10.1007/s11235-010-9305-3,Telecommunication Systems,Elena-Veronica2011,False,,Springer,Not available,Power allocation games in wireless networks of multi-antenna terminals,c86b31b1aa63e311d18a47e529e771f8,http://dx.doi.org/10.1007/s11235-010-9305-3
870,We study the impact of collusion in network games with splittable flow and focus on the well established price of anarchy as a measure of this impact. We first investigate symmetric load balancing games and show that the price of anarchy is at most ,tobias harks,Not available,2011.0,10.1007/s00224-010-9269-4,Theory of Computing Systems,Tobias2011,False,,Springer,Not available,Stackelberg Strategies and Collusion in Network Games with Splittable Flow,23d1df27693f2093dbf6bc48447887aa,http://dx.doi.org/10.1007/s00224-010-9269-4
871,The ,tamer basar,Not available,2011.0,10.1007/s13235-010-0002-3,Dynamic Games and Applications,Tamer2011,False,,Springer,Not available,Prices of Anarchy  Information  and Cooperation in Differential Games,72c6ce9e54dade443eecbab9da430e09,http://dx.doi.org/10.1007/s13235-010-0002-3
872,The ,quanyan zhu,Not available,2011.0,10.1007/s13235-010-0002-3,Dynamic Games and Applications,Tamer2011,False,,Springer,Not available,Prices of Anarchy  Information  and Cooperation in Differential Games,72c6ce9e54dade443eecbab9da430e09,http://dx.doi.org/10.1007/s13235-010-0002-3
873,We introduce the concert (or cafeteria) queueing problem: A finite but large number of customers arrive into a queueing system that starts service at a specified opening time. Each customer is free to choose her arrival time (before or after opening time)  and is interested in early service completion with minimal wait. These goals are captured by a cost function which is additive and linear in the waiting time and service completion time  with coefficients that may be class dependent. We consider a fluid model of this system  which is motivated as the fluid-scale limit of the stochastic system. In the fluid setting  we explicitly identify the unique Nash-equilibrium arrival profile for each class of customers. Our structural results imply that  in equilibrium  the arrival rate is increasing up until the closing time where all customers are served. Furthermore  the waiting queue is maximal at the opening time  and monotonically decreases thereafter. In the simple single class setting  we show that the price of anarchy (PoA  the efficiency loss relative to the socially optimal solution) is exactly two  while in the multi-class setting we develop tight upper and lower bounds on the PoA. In addition  we consider several mechanisms that may be used to reduce the PoA. The proposed model may explain queueing phenomena in diverse settings that involve a pre-assigned opening time.,rahul jain,Not available,2011.0,10.1007/s10626-010-0097-0,Discrete Event Dynamic Systems,Rahul2011,False,,Springer,Not available,The concert queueing game: to wait or to be late,79f8bf4e2b3d91ea9b819dfd960852e2,http://dx.doi.org/10.1007/s10626-010-0097-0
874,We introduce the concert (or cafeteria) queueing problem: A finite but large number of customers arrive into a queueing system that starts service at a specified opening time. Each customer is free to choose her arrival time (before or after opening time)  and is interested in early service completion with minimal wait. These goals are captured by a cost function which is additive and linear in the waiting time and service completion time  with coefficients that may be class dependent. We consider a fluid model of this system  which is motivated as the fluid-scale limit of the stochastic system. In the fluid setting  we explicitly identify the unique Nash-equilibrium arrival profile for each class of customers. Our structural results imply that  in equilibrium  the arrival rate is increasing up until the closing time where all customers are served. Furthermore  the waiting queue is maximal at the opening time  and monotonically decreases thereafter. In the simple single class setting  we show that the price of anarchy (PoA  the efficiency loss relative to the socially optimal solution) is exactly two  while in the multi-class setting we develop tight upper and lower bounds on the PoA. In addition  we consider several mechanisms that may be used to reduce the PoA. The proposed model may explain queueing phenomena in diverse settings that involve a pre-assigned opening time.,sandeep juneja,Not available,2011.0,10.1007/s10626-010-0097-0,Discrete Event Dynamic Systems,Rahul2011,False,,Springer,Not available,The concert queueing game: to wait or to be late,79f8bf4e2b3d91ea9b819dfd960852e2,http://dx.doi.org/10.1007/s10626-010-0097-0
875,We introduce the concert (or cafeteria) queueing problem: A finite but large number of customers arrive into a queueing system that starts service at a specified opening time. Each customer is free to choose her arrival time (before or after opening time)  and is interested in early service completion with minimal wait. These goals are captured by a cost function which is additive and linear in the waiting time and service completion time  with coefficients that may be class dependent. We consider a fluid model of this system  which is motivated as the fluid-scale limit of the stochastic system. In the fluid setting  we explicitly identify the unique Nash-equilibrium arrival profile for each class of customers. Our structural results imply that  in equilibrium  the arrival rate is increasing up until the closing time where all customers are served. Furthermore  the waiting queue is maximal at the opening time  and monotonically decreases thereafter. In the simple single class setting  we show that the price of anarchy (PoA  the efficiency loss relative to the socially optimal solution) is exactly two  while in the multi-class setting we develop tight upper and lower bounds on the PoA. In addition  we consider several mechanisms that may be used to reduce the PoA. The proposed model may explain queueing phenomena in diverse settings that involve a pre-assigned opening time.,nahum shimkin,Not available,2011.0,10.1007/s10626-010-0097-0,Discrete Event Dynamic Systems,Rahul2011,False,,Springer,Not available,The concert queueing game: to wait or to be late,79f8bf4e2b3d91ea9b819dfd960852e2,http://dx.doi.org/10.1007/s10626-010-0097-0
876,We reconsider the well-studied Selfish Routing game with affine latency functions. The Price of Anarchy for this class of games takes maximum value 4/3; this maximum is attained already for a simple network of two parallel links  known as Pigou’s network. We improve upon the value 4/3 by means of Coordination Mechanisms.We increase the latency functions of the edges in the network  i.e.  if ℓ,george christodoulou,Not available,2011.0,10.1007/978-3-642-23719-5_11,Algorithms – ESA 2011,George2011,False,,Springer,Not available,Improving the Price of Anarchy for Selfish Routing via Coordination Mechanisms,7b1b2db85da0cab514891f5b471cba20,http://dx.doi.org/10.1007/978-3-642-23719-5_11
877,Pope Benedict XVI’s 2009 Encyclical-Letter “,james murphy,Not available,2011.0,10.1007/s10551-012-1229-2,Journal of Business Ethics,Bernard2011,False,,Springer,Not available,The Morality of Bargaining: Insights from “,de246ea50cc7e7cb14930fb5079b51d0,http://dx.doi.org/10.1007/s10551-012-1229-2
878,This paper considers a selfish routing based network improvement problem  in which the authors would like to find a modified latency function that results in a new Nash equilibrium flow satisfying all traffic demands subject to the target capacity  while the total modification cost on edge latency is minimized. By using the reduction from the 3-Satisfiability (3-SAT) problem to our problem  the authors show that this problem is strongly NP-hard  even for the single commodity network.,binwu zhang,Not available,2011.0,10.1007/s11424-011-8156-7,Journal of Systems Science and Complexity,Binwu2011,False,,Springer,Not available,A selfish routing based network improvement problem,43dc5d2dbccc31300738e45590f30150,http://dx.doi.org/10.1007/s11424-011-8156-7
879,This paper considers a selfish routing based network improvement problem  in which the authors would like to find a modified latency function that results in a new Nash equilibrium flow satisfying all traffic demands subject to the target capacity  while the total modification cost on edge latency is minimized. By using the reduction from the 3-Satisfiability (3-SAT) problem to our problem  the authors show that this problem is strongly NP-hard  even for the single commodity network.,shu-cherng fang,Not available,2011.0,10.1007/s11424-011-8156-7,Journal of Systems Science and Complexity,Binwu2011,False,,Springer,Not available,A selfish routing based network improvement problem,43dc5d2dbccc31300738e45590f30150,http://dx.doi.org/10.1007/s11424-011-8156-7
880,We consider a model of next-hop routing by self-interested agents. In this model  nodes in a graph (representing ISPs  Autonomous Systems  etc.) make pricing decisions of how much to charge for forwarding traffic from each of their upstream neighbors  and routing decisions of which downstream neighbors to forward traffic to (i.e.  choosing the next hop). Traffic originates at a subset of these nodes that derive a utility when the traffic is routed to its destination node; the traffic demand is elastic and the utility derived from it can be different for different source nodes. Our next-hop routing and pricing model is in sharp contrast with the more common source routing and pricing models  in which the source of traffic determines the entire route from source to destination. For our model  we begin by showing sufficient conditions for prices to result in a Nash equilibrium  and in fact give an efficient algorithm to compute a Nash equilibrium which is as good as the centralized optimum  thus proving that the price of stability is 1. When only a single source node exists  then the price of anarchy is 1 as well  as long as some minor assumptions on player behavior is made. The above results hold for arbitrary convex pricing functions  but with the assumption that the utilities derived from getting traffic to its destination are linear. When utilities can be non-linear functions  we show that Nash equilibrium may not exist  even with simple discrete pricing models.,elliot anshelevich,Not available,2011.0,10.1007/978-3-642-24829-0_25,Algorithmic Game Theory,Elliot2011,False,,Springer,Not available,Strategic Pricing in Next-Hop Routing with Elastic Demands,5b7e979ed8e72b57b0eff1b77d536b88,http://dx.doi.org/10.1007/978-3-642-24829-0_25
881,We consider a model of next-hop routing by self-interested agents. In this model  nodes in a graph (representing ISPs  Autonomous Systems  etc.) make pricing decisions of how much to charge for forwarding traffic from each of their upstream neighbors  and routing decisions of which downstream neighbors to forward traffic to (i.e.  choosing the next hop). Traffic originates at a subset of these nodes that derive a utility when the traffic is routed to its destination node; the traffic demand is elastic and the utility derived from it can be different for different source nodes. Our next-hop routing and pricing model is in sharp contrast with the more common source routing and pricing models  in which the source of traffic determines the entire route from source to destination. For our model  we begin by showing sufficient conditions for prices to result in a Nash equilibrium  and in fact give an efficient algorithm to compute a Nash equilibrium which is as good as the centralized optimum  thus proving that the price of stability is 1. When only a single source node exists  then the price of anarchy is 1 as well  as long as some minor assumptions on player behavior is made. The above results hold for arbitrary convex pricing functions  but with the assumption that the utilities derived from getting traffic to its destination are linear. When utilities can be non-linear functions  we show that Nash equilibrium may not exist  even with simple discrete pricing models.,ameya hate,Not available,2011.0,10.1007/978-3-642-24829-0_25,Algorithmic Game Theory,Elliot2011,False,,Springer,Not available,Strategic Pricing in Next-Hop Routing with Elastic Demands,5b7e979ed8e72b57b0eff1b77d536b88,http://dx.doi.org/10.1007/978-3-642-24829-0_25
882,We consider a model of next-hop routing by self-interested agents. In this model  nodes in a graph (representing ISPs  Autonomous Systems  etc.) make pricing decisions of how much to charge for forwarding traffic from each of their upstream neighbors  and routing decisions of which downstream neighbors to forward traffic to (i.e.  choosing the next hop). Traffic originates at a subset of these nodes that derive a utility when the traffic is routed to its destination node; the traffic demand is elastic and the utility derived from it can be different for different source nodes. Our next-hop routing and pricing model is in sharp contrast with the more common source routing and pricing models  in which the source of traffic determines the entire route from source to destination. For our model  we begin by showing sufficient conditions for prices to result in a Nash equilibrium  and in fact give an efficient algorithm to compute a Nash equilibrium which is as good as the centralized optimum  thus proving that the price of stability is 1. When only a single source node exists  then the price of anarchy is 1 as well  as long as some minor assumptions on player behavior is made. The above results hold for arbitrary convex pricing functions  but with the assumption that the utilities derived from getting traffic to its destination are linear. When utilities can be non-linear functions  we show that Nash equilibrium may not exist  even with simple discrete pricing models.,koushik kar,Not available,2011.0,10.1007/978-3-642-24829-0_25,Algorithmic Game Theory,Elliot2011,False,,Springer,Not available,Strategic Pricing in Next-Hop Routing with Elastic Demands,5b7e979ed8e72b57b0eff1b77d536b88,http://dx.doi.org/10.1007/978-3-642-24829-0_25
883,"We investigate the effect of linear independence in the strategies of congestion games on the convergence time of best improvement sequences and on the pure Price of Anarchy. In particular  we consider symmetric congestion games on extension-parallel networks  an interesting class of networks with linearly independent paths  and establish two remarkable properties previously known only for parallel-link games. We show that for arbitrary (non-negative and non-decreasing) latency functions  any best improvement sequence reaches a pure Nash equilibrium in at most as many steps as the number of players  and that for latency functions in class 
",dimitris fotakis,Not available,2010.0,10.1007/s00224-009-9205-7,Theory of Computing Systems,Dimitris2010,False,,Springer,Not available,Congestion Games with Linearly Independent Paths: Convergence Time and Price of Anarchy,7e5fabb61d1cd2e3b5b3c69ee2a382b1,http://dx.doi.org/10.1007/s00224-009-9205-7
884,We investigate the effectiveness of Stackelberg strategies for atomic congestion games with unsplittable demands. In our setting  only a fraction of the players are selfish  while the rest are willing to follow a predetermined strategy. A ,dimitris fotakis,Not available,2010.0,10.1007/s00224-008-9152-8,Theory of Computing Systems,Dimitris2010,False,,Springer,Not available,Stackelberg Strategies for Atomic Congestion Games,102853add00c8a2c5d59f403a0bd57cf,http://dx.doi.org/10.1007/s00224-008-9152-8
885,We consider a cost sharing system where users are selfish and act according to their own interest. There is a set of facilities and each facility provides services to a subset of the users. Each user is interested in purchasing a service  and will buy it from the facility offering it at the lowest cost. The overall system performance is defined to be the total cost of the facilities chosen by the users. A central authority can encourage the purchase of services by offering subsidies that reduce their price  in order to improve the system performance. The subsidies are financed by taxes collected from the users.Specifically  we investigate a non-cooperative game  where users join the system  and act according to their ,niv buchbinder,Not available,2010.0,10.1007/s00224-009-9197-3,Theory of Computing Systems,Niv2010,False,,Springer,Not available,Non-Cooperative Cost Sharing Games via Subsidies,d74f9d2157c94e75fc1f9c6f3d701745,http://dx.doi.org/10.1007/s00224-009-9197-3
886,We consider a cost sharing system where users are selfish and act according to their own interest. There is a set of facilities and each facility provides services to a subset of the users. Each user is interested in purchasing a service  and will buy it from the facility offering it at the lowest cost. The overall system performance is defined to be the total cost of the facilities chosen by the users. A central authority can encourage the purchase of services by offering subsidies that reduce their price  in order to improve the system performance. The subsidies are financed by taxes collected from the users.Specifically  we investigate a non-cooperative game  where users join the system  and act according to their ,liane lewin-eytan,Not available,2010.0,10.1007/s00224-009-9197-3,Theory of Computing Systems,Niv2010,False,,Springer,Not available,Non-Cooperative Cost Sharing Games via Subsidies,d74f9d2157c94e75fc1f9c6f3d701745,http://dx.doi.org/10.1007/s00224-009-9197-3
887,Contrary to early expectations  recent studies have shown near-perfect adherence to HIV antiretrovirals in sub-Saharan Africa We conducted qualitative interviews with patients purchasing low-cost  generic antiretroviral therapy to better understand the social dynamics underlying these findings. We found that concerns for family well-being motivate adherence  yet  the financial sacrifices necessary to secure therapy may paradoxically undermine family welfare. We suggest that missed doses may be more due to a failure to ,a. kawuma,Not available,2006.0,10.1007/s10461-006-9080-z,AIDS and Behavior,T.2006,False,,Springer,Not available,The Price of Adherence: Qualitative Findings From HIV Positive Individuals Purchasing Fixed-Dose Combination Generic HIV Antiretroviral Therapy in Kampala  Uganda,3546dd01c0a6376828bbafaaa37b87c7,http://dx.doi.org/10.1007/s10461-006-9080-z
888,We reconsider the well-studied Selfish Routing game with affine latency functions. The Price of Anarchy for this class of games takes maximum value 4/3; this maximum is attained already for a simple network of two parallel links  known as Pigou’s network. We improve upon the value 4/3 by means of Coordination Mechanisms.We increase the latency functions of the edges in the network  i.e.  if ℓ,kurt mehlhorn,Not available,2011.0,10.1007/978-3-642-23719-5_11,Algorithms – ESA 2011,George2011,False,,Springer,Not available,Improving the Price of Anarchy for Selfish Routing via Coordination Mechanisms,7b1b2db85da0cab514891f5b471cba20,http://dx.doi.org/10.1007/978-3-642-23719-5_11
889,We consider a cost sharing system where users are selfish and act according to their own interest. There is a set of facilities and each facility provides services to a subset of the users. Each user is interested in purchasing a service  and will buy it from the facility offering it at the lowest cost. The overall system performance is defined to be the total cost of the facilities chosen by the users. A central authority can encourage the purchase of services by offering subsidies that reduce their price  in order to improve the system performance. The subsidies are financed by taxes collected from the users.Specifically  we investigate a non-cooperative game  where users join the system  and act according to their ,joseph naor,Not available,2010.0,10.1007/s00224-009-9197-3,Theory of Computing Systems,Niv2010,False,,Springer,Not available,Non-Cooperative Cost Sharing Games via Subsidies,d74f9d2157c94e75fc1f9c6f3d701745,http://dx.doi.org/10.1007/s00224-009-9197-3
890,We consider a cost sharing system where users are selfish and act according to their own interest. There is a set of facilities and each facility provides services to a subset of the users. Each user is interested in purchasing a service  and will buy it from the facility offering it at the lowest cost. The overall system performance is defined to be the total cost of the facilities chosen by the users. A central authority can encourage the purchase of services by offering subsidies that reduce their price  in order to improve the system performance. The subsidies are financed by taxes collected from the users.Specifically  we investigate a non-cooperative game  where users join the system  and act according to their ,ariel orda,Not available,2010.0,10.1007/s00224-009-9197-3,Theory of Computing Systems,Niv2010,False,,Springer,Not available,Non-Cooperative Cost Sharing Games via Subsidies,d74f9d2157c94e75fc1f9c6f3d701745,http://dx.doi.org/10.1007/s00224-009-9197-3
891,Work at the intersection of computer science and game theory is briefly surveyed  with a focus on the work in computer science. In particular  the following topics are considered: various roles of computational complexity in game theory  including modelling bounded rationality  its role in mechanism design  and the problem of computing Nash equilibria; the ,joseph halpern,Not available,2018.0,10.1057/978-1-349-95189-5_2133,The New Palgrave Dictionary of Economics,Y.2018,False,,Springer,Not available,Computer Science and Game Theory,485c95acf22129f003266a20664cca53,http://dx.doi.org/10.1057/978-1-349-95189-5_2133
892,Heterogeneous wireless network (HWN) is an overlay structure of different wireless networks (WN). The WNs may differ in terms of coverage  capacity  underlying technology  service types  and network operators. In such a HWN environment  a mobile user (MU) equipped with multi-mode or multi-home terminal always wish to maintain connectivity with a wireless network which can provide best quality of experience (QoE). Similarly  the WN may allow the connectivity only to a MU which can provide highest revenue. This may leads to an event  called vertical handoff  where the MU leaves current WN and connect to another different WN. The conflicting goals of maximizing QoE and revenue simultaneously while performing a VHO necessitates the selection of mutually best MU and WN. Game theory is an efficient mathematical tool to model such situations where specific actions of decision makers lead to mutually conflicting consequences to each other. This paper  using a tutorial style  presented the game theory concepts and its application for VHO  type of games  and game solutions. It proposes  in specific  the noncooperative game formulations for three different VHO situations and their solutions using NASH for HWNs.,pramod goyal,Not available,2018.0,10.1007/978-981-10-8240-5_47,Advanced Computational and Communication Paradigms,Pramod2018,False,,Springer,Not available,Game Theory for Vertical Handoff Decisions in Heterogeneous Wireless Networks: A Tutorial,8828fa82aee39882b33cacd3e9458392,http://dx.doi.org/10.1007/978-981-10-8240-5_47
893,Heterogeneous wireless network (HWN) is an overlay structure of different wireless networks (WN). The WNs may differ in terms of coverage  capacity  underlying technology  service types  and network operators. In such a HWN environment  a mobile user (MU) equipped with multi-mode or multi-home terminal always wish to maintain connectivity with a wireless network which can provide best quality of experience (QoE). Similarly  the WN may allow the connectivity only to a MU which can provide highest revenue. This may leads to an event  called vertical handoff  where the MU leaves current WN and connect to another different WN. The conflicting goals of maximizing QoE and revenue simultaneously while performing a VHO necessitates the selection of mutually best MU and WN. Game theory is an efficient mathematical tool to model such situations where specific actions of decision makers lead to mutually conflicting consequences to each other. This paper  using a tutorial style  presented the game theory concepts and its application for VHO  type of games  and game solutions. It proposes  in specific  the noncooperative game formulations for three different VHO situations and their solutions using NASH for HWNs.,d. lobiyal,Not available,2018.0,10.1007/978-981-10-8240-5_47,Advanced Computational and Communication Paradigms,Pramod2018,False,,Springer,Not available,Game Theory for Vertical Handoff Decisions in Heterogeneous Wireless Networks: A Tutorial,8828fa82aee39882b33cacd3e9458392,http://dx.doi.org/10.1007/978-981-10-8240-5_47
894,Heterogeneous wireless network (HWN) is an overlay structure of different wireless networks (WN). The WNs may differ in terms of coverage  capacity  underlying technology  service types  and network operators. In such a HWN environment  a mobile user (MU) equipped with multi-mode or multi-home terminal always wish to maintain connectivity with a wireless network which can provide best quality of experience (QoE). Similarly  the WN may allow the connectivity only to a MU which can provide highest revenue. This may leads to an event  called vertical handoff  where the MU leaves current WN and connect to another different WN. The conflicting goals of maximizing QoE and revenue simultaneously while performing a VHO necessitates the selection of mutually best MU and WN. Game theory is an efficient mathematical tool to model such situations where specific actions of decision makers lead to mutually conflicting consequences to each other. This paper  using a tutorial style  presented the game theory concepts and its application for VHO  type of games  and game solutions. It proposes  in specific  the noncooperative game formulations for three different VHO situations and their solutions using NASH for HWNs.,c. katti,Not available,2018.0,10.1007/978-981-10-8240-5_47,Advanced Computational and Communication Paradigms,Pramod2018,False,,Springer,Not available,Game Theory for Vertical Handoff Decisions in Heterogeneous Wireless Networks: A Tutorial,8828fa82aee39882b33cacd3e9458392,http://dx.doi.org/10.1007/978-981-10-8240-5_47
895,This chapter presents a game theoretic framework for studying Stackelberg routing games on parallel transportation networks. A new class of latency functions is introduced to model congestion due to the formation of physical queues  inspired from the fundamental diagram of traffic. For this new class  some results from the classical congestion games literature (in which latency is assumed to be a nondecreasing function of the flow) do not hold. A characterization of Nash equilibria is given  and it is shown  in particular  that there may exist multiple equilibria that have different total costs. A simple polynomial-time algorithm is provided  for computing the ,walid krichene,Not available,2018.0,10.1007/978-3-319-44374-4_26,Handbook of Dynamic Game Theory,Walid2018,False,,Springer,Not available,Stackelberg Routing on Parallel Transportation Networks,495f64c47b83e55fa8fd4db699963316,http://dx.doi.org/10.1007/978-3-319-44374-4_26
896,This chapter presents a game theoretic framework for studying Stackelberg routing games on parallel transportation networks. A new class of latency functions is introduced to model congestion due to the formation of physical queues  inspired from the fundamental diagram of traffic. For this new class  some results from the classical congestion games literature (in which latency is assumed to be a nondecreasing function of the flow) do not hold. A characterization of Nash equilibria is given  and it is shown  in particular  that there may exist multiple equilibria that have different total costs. A simple polynomial-time algorithm is provided  for computing the ,jack reilly,Not available,2018.0,10.1007/978-3-319-44374-4_26,Handbook of Dynamic Game Theory,Walid2018,False,,Springer,Not available,Stackelberg Routing on Parallel Transportation Networks,495f64c47b83e55fa8fd4db699963316,http://dx.doi.org/10.1007/978-3-319-44374-4_26
897,This chapter presents a game theoretic framework for studying Stackelberg routing games on parallel transportation networks. A new class of latency functions is introduced to model congestion due to the formation of physical queues  inspired from the fundamental diagram of traffic. For this new class  some results from the classical congestion games literature (in which latency is assumed to be a nondecreasing function of the flow) do not hold. A characterization of Nash equilibria is given  and it is shown  in particular  that there may exist multiple equilibria that have different total costs. A simple polynomial-time algorithm is provided  for computing the ,saurabh amin,Not available,2018.0,10.1007/978-3-319-44374-4_26,Handbook of Dynamic Game Theory,Walid2018,False,,Springer,Not available,Stackelberg Routing on Parallel Transportation Networks,495f64c47b83e55fa8fd4db699963316,http://dx.doi.org/10.1007/978-3-319-44374-4_26
898,This chapter presents a game theoretic framework for studying Stackelberg routing games on parallel transportation networks. A new class of latency functions is introduced to model congestion due to the formation of physical queues  inspired from the fundamental diagram of traffic. For this new class  some results from the classical congestion games literature (in which latency is assumed to be a nondecreasing function of the flow) do not hold. A characterization of Nash equilibria is given  and it is shown  in particular  that there may exist multiple equilibria that have different total costs. A simple polynomial-time algorithm is provided  for computing the ,alexandre bayen,Not available,2018.0,10.1007/978-3-319-44374-4_26,Handbook of Dynamic Game Theory,Walid2018,False,,Springer,Not available,Stackelberg Routing on Parallel Transportation Networks,495f64c47b83e55fa8fd4db699963316,http://dx.doi.org/10.1007/978-3-319-44374-4_26
899,We reconsider the well-studied Selfish Routing game with affine latency functions. The Price of Anarchy for this class of games takes maximum value 4/3; this maximum is attained already for a simple network of two parallel links  known as Pigou’s network. We improve upon the value 4/3 by means of Coordination Mechanisms.We increase the latency functions of the edges in the network  i.e.  if ℓ,evangelia pyrga,Not available,2011.0,10.1007/978-3-642-23719-5_11,Algorithms – ESA 2011,George2011,False,,Springer,Not available,Improving the Price of Anarchy for Selfish Routing via Coordination Mechanisms,7b1b2db85da0cab514891f5b471cba20,http://dx.doi.org/10.1007/978-3-642-23719-5_11
900,This article summarizes the methodology and economics of Karl Marx. After a brief account of his life  it deals with his historical materialism  and then his labour theory of value  his theories of rent  money  surplus value  and crises  his account of the laws of motion of the capitalism mode of production  and his and Engels’s conception of the economy of post-capitalist societies.,ernest mandel,Not available,2018.0,10.1057/978-1-349-95189-5_1019,The New Palgrave Dictionary of Economics,Ernest2018,False,,Springer,Not available,Marx  Karl Heinrich (1818–1883),0a138258e5effd5f680f0277f7aa7d16,http://dx.doi.org/10.1057/978-1-349-95189-5_1019
901,The British economy in wartime had been planned and some in the 1930s and 1940s also admired the Soviet model. Many authors  including Hayek  Robbins Durbin and Franks  had written about the future of top-down control. Meade’s proposal was a mix. There was no case for an imperative plan. Prices and quantities should be determined by supply and demand. Since  however  information and coordination are always problematic where decisions are decentralised  there is a need in a market economy for an indicative plan that would reduce wasteful duplication and minimise supply-chain inconsistency. Although control is undesirable  grants and concessions would provide a useful nudge.,david reisman,Not available,2018.0,10.1007/978-3-319-69281-4_11,James Edward Meade,David2018,False,,Springer,Not available,Economic Planning,a23c7b4fd6bed4fe84d1168702444a41,http://dx.doi.org/10.1007/978-3-319-69281-4_11
902,We introduce a unifying model to study the impact of worst-case latency deviations in non-atomic selfish routing games. In our model  latencies are subject to (bounded) deviations which are taken into account by the players. The quality deterioration caused by such deviations is assessed by the ,pieter kleer,Not available,2017.0,10.1007/s00224-017-9829-y,Theory of Computing Systems,Pieter2017,False,,Springer,Not available,The Impact of Worst-Case Deviations in Non-Atomic Network Routing Games,cb47c631b9fcd7fd050fad4d4c69534c,http://dx.doi.org/10.1007/s00224-017-9829-y
903,We introduce a unifying model to study the impact of worst-case latency deviations in non-atomic selfish routing games. In our model  latencies are subject to (bounded) deviations which are taken into account by the players. The quality deterioration caused by such deviations is assessed by the ,guido schafer,Not available,2017.0,10.1007/s00224-017-9829-y,Theory of Computing Systems,Pieter2017,False,,Springer,Not available,The Impact of Worst-Case Deviations in Non-Atomic Network Routing Games,cb47c631b9fcd7fd050fad4d4c69534c,http://dx.doi.org/10.1007/s00224-017-9829-y
904,We study the design of cost-sharing protocols for two fundamental resource allocation problems  the ,george christodoulou,Not available,2017.0,10.1007/s00224-017-9832-3,Theory of Computing Systems,George2017,True,,Springer,Not available,Designing Cost-Sharing Methods for Bayesian Games,d6da5046dc1d5df74b9472736e2b4fb7,http://dx.doi.org/10.1007/s00224-017-9832-3
905,We study the design of cost-sharing protocols for two fundamental resource allocation problems  the ,stefano leonardi,Not available,2017.0,10.1007/s00224-017-9832-3,Theory of Computing Systems,George2017,True,,Springer,Not available,Designing Cost-Sharing Methods for Bayesian Games,d6da5046dc1d5df74b9472736e2b4fb7,http://dx.doi.org/10.1007/s00224-017-9832-3
906,We study the design of cost-sharing protocols for two fundamental resource allocation problems  the ,alkmini sgouritsa,Not available,2017.0,10.1007/s00224-017-9832-3,Theory of Computing Systems,George2017,True,,Springer,Not available,Designing Cost-Sharing Methods for Bayesian Games,d6da5046dc1d5df74b9472736e2b4fb7,http://dx.doi.org/10.1007/s00224-017-9832-3
907,"Purpose of Review,The relationship between climate change and violent conflict has been the subject of intense academic as well as policy debate over the past few decades. Adverse economic conditions constitute an important channel linking the two phenomena. Here  I review the theoretical arguments and recent empirical evidence connecting climate-driven adverse economic conditions to conflict.,Recent Findings,Climate-induced adverse economic conditions could lead to conflict by lowering the opportunity cost of violence  weakening state capacity  and exacerbating political and economic inequalities/grievances. The empirical literature does not provide robust evidence for a “direct” climate-economy-conflict relationship.,Summary,Recent empirical research offers considerable suggestive evidence that climate-driven economic downturns lead to conflict in agriculture-dependent regions and in combination and interaction with other socioeconomic and political factors. Future research should further examine the context(s) in which climate-induced adverse economic conditions led to conflict  and also identify and test the precise empirical implications of the theoretical mechanisms through which these adverse economic conditions lead to conflict using disaggregated data and appropriate estimation procedures.",vally koubi,Not available,2017.0,10.1007/s40641-017-0074-x,Current Climate Change Reports,Vally2017,False,,Springer,Not available,Climate Change  the Economy  and Conflict,fb8fa2024518d573c80313db36ee8bf6,http://dx.doi.org/10.1007/s40641-017-0074-x
908,In the network design game with ,akaki mamageishvili,Not available,2017.0,10.1007/s00182-017-0600-z,International Journal of Game Theory,Akaki2017,False,,Springer,Not available,Improved bounds on equilibria solutions in the network design game,99666e86f7c56c9e0cc8385b7824e78f,http://dx.doi.org/10.1007/s00182-017-0600-z
909,In the network design game with ,matus mihalak,Not available,2017.0,10.1007/s00182-017-0600-z,International Journal of Game Theory,Akaki2017,False,,Springer,Not available,Improved bounds on equilibria solutions in the network design game,99666e86f7c56c9e0cc8385b7824e78f,http://dx.doi.org/10.1007/s00182-017-0600-z
910,We study the inefficiency of equilibria for several classes of games when players are (partially) altruistic. We model altruistic behavior by assuming that player ,po-an chen,Not available,2011.0,10.1007/978-3-642-25510-6_33,Internet and Network Economics,Po-An2011,False,,Springer,Not available,The Robust Price of Anarchy of Altruistic Games,8d046e9acfd6d12f203e7186cc22cec9,http://dx.doi.org/10.1007/978-3-642-25510-6_33
911,In the network design game with ,simone montemezzani,Not available,2017.0,10.1007/s00182-017-0600-z,International Journal of Game Theory,Akaki2017,False,,Springer,Not available,Improved bounds on equilibria solutions in the network design game,99666e86f7c56c9e0cc8385b7824e78f,http://dx.doi.org/10.1007/s00182-017-0600-z
912,In supply chain management  it is prevalent to design contract for coordination or proper risk-sharing in the supply chain. However  when a supply chain contract is developed based on the concept of expectation (e.g.  expected profit)  there is uncertainty risk with respect to the contract value which arises from various uncertainties inherent in the supply chain  such as demand uncertainty  price uncertainty  etc. We call such uncertainty risk associated with the contract ,yingxue zhao,Not available,2017.0,10.1007/s10479-014-1689-0,Annals of Operations Research,Yingxue2017,False,,Springer,Not available,Mean-risk analysis of wholesale price contracts with stochastic price-dependent demand,48d49678d02b7ea37e82251cbad06152,http://dx.doi.org/10.1007/s10479-014-1689-0
913,In supply chain management  it is prevalent to design contract for coordination or proper risk-sharing in the supply chain. However  when a supply chain contract is developed based on the concept of expectation (e.g.  expected profit)  there is uncertainty risk with respect to the contract value which arises from various uncertainties inherent in the supply chain  such as demand uncertainty  price uncertainty  etc. We call such uncertainty risk associated with the contract ,tsan-ming choi,Not available,2017.0,10.1007/s10479-014-1689-0,Annals of Operations Research,Yingxue2017,False,,Springer,Not available,Mean-risk analysis of wholesale price contracts with stochastic price-dependent demand,48d49678d02b7ea37e82251cbad06152,http://dx.doi.org/10.1007/s10479-014-1689-0
914,In supply chain management  it is prevalent to design contract for coordination or proper risk-sharing in the supply chain. However  when a supply chain contract is developed based on the concept of expectation (e.g.  expected profit)  there is uncertainty risk with respect to the contract value which arises from various uncertainties inherent in the supply chain  such as demand uncertainty  price uncertainty  etc. We call such uncertainty risk associated with the contract ,t. cheng,Not available,2017.0,10.1007/s10479-014-1689-0,Annals of Operations Research,Yingxue2017,False,,Springer,Not available,Mean-risk analysis of wholesale price contracts with stochastic price-dependent demand,48d49678d02b7ea37e82251cbad06152,http://dx.doi.org/10.1007/s10479-014-1689-0
915,In supply chain management  it is prevalent to design contract for coordination or proper risk-sharing in the supply chain. However  when a supply chain contract is developed based on the concept of expectation (e.g.  expected profit)  there is uncertainty risk with respect to the contract value which arises from various uncertainties inherent in the supply chain  such as demand uncertainty  price uncertainty  etc. We call such uncertainty risk associated with the contract ,shouyang wang,Not available,2017.0,10.1007/s10479-014-1689-0,Annals of Operations Research,Yingxue2017,False,,Springer,Not available,Mean-risk analysis of wholesale price contracts with stochastic price-dependent demand,48d49678d02b7ea37e82251cbad06152,http://dx.doi.org/10.1007/s10479-014-1689-0
916,We study the inefficiency of equilibria for several classes of games when players are (partially) altruistic. We model altruistic behavior by assuming that player ,bart keijzer,Not available,2011.0,10.1007/978-3-642-25510-6_33,Internet and Network Economics,Po-An2011,False,,Springer,Not available,The Robust Price of Anarchy of Altruistic Games,8d046e9acfd6d12f203e7186cc22cec9,http://dx.doi.org/10.1007/978-3-642-25510-6_33
917,We study the inefficiency of equilibria for several classes of games when players are (partially) altruistic. We model altruistic behavior by assuming that player ,david kempe,Not available,2011.0,10.1007/978-3-642-25510-6_33,Internet and Network Economics,Po-An2011,False,,Springer,Not available,The Robust Price of Anarchy of Altruistic Games,8d046e9acfd6d12f203e7186cc22cec9,http://dx.doi.org/10.1007/978-3-642-25510-6_33
918,We study the inefficiency of equilibria for several classes of games when players are (partially) altruistic. We model altruistic behavior by assuming that player ,guido schafer,Not available,2011.0,10.1007/978-3-642-25510-6_33,Internet and Network Economics,Po-An2011,False,,Springer,Not available,The Robust Price of Anarchy of Altruistic Games,8d046e9acfd6d12f203e7186cc22cec9,http://dx.doi.org/10.1007/978-3-642-25510-6_33
919,This paper deals with a scheduling problem with parallel-batching machines from a game theoretic perspective. There are ,qing-qin nong,Not available,2016.0,10.1007/s40305-016-0134-2,Journal of the Operations Research Society of China,Qing-Qin2016,False,,Springer,Not available,The Shortest First Coordination Mechanism for a Scheduling Game with Parallel-Batching Machines,74b39375671a9169566a0741e12d848e,http://dx.doi.org/10.1007/s40305-016-0134-2
920,This paper deals with a scheduling problem with parallel-batching machines from a game theoretic perspective. There are ,sai-jun guo,Not available,2016.0,10.1007/s40305-016-0134-2,Journal of the Operations Research Society of China,Qing-Qin2016,False,,Springer,Not available,The Shortest First Coordination Mechanism for a Scheduling Game with Parallel-Batching Machines,74b39375671a9169566a0741e12d848e,http://dx.doi.org/10.1007/s40305-016-0134-2
921,This paper deals with a scheduling problem with parallel-batching machines from a game theoretic perspective. There are ,li-hui miao,Not available,2016.0,10.1007/s40305-016-0134-2,Journal of the Operations Research Society of China,Qing-Qin2016,False,,Springer,Not available,The Shortest First Coordination Mechanism for a Scheduling Game with Parallel-Batching Machines,74b39375671a9169566a0741e12d848e,http://dx.doi.org/10.1007/s40305-016-0134-2
922,According to the proportional allocation mechanism from the network optimization literature  users compete for a divisible resource – such as bandwidth – by submitting bids. The mechanism allocates to each user a fraction of the resource that is proportional to her bid and collects an amount equal to her bid as payment. Since users act as utility-maximizers  this naturally defines a proportional allocation game. Syrgkanis and Tardos (STOC 2013) quantified the inefficiency of equilibria in this game with respect to the social welfare and presented a lower bound of 26.8 ,ioannis caragiannis,Not available,2016.0,10.1007/s00224-016-9674-4,Theory of Computing Systems,Ioannis2016,False,,Springer,Not available,Welfare Guarantees for Proportional Allocations,1d8ae082a051688dbd93e495f0ef4f8e,http://dx.doi.org/10.1007/s00224-016-9674-4
923,"
Based on large-scale human mobility data collected in San Francisco and Boston, the morning peak urban rail transit (URT) ODs (origin-destination matrix) were estimated and the most vulnerable URT segments, those capable of causing the largest service interruptions, were identified. In both URT networks, a few highly vulnerable segments were observed. For this small group of vital segments, the impact of failure must be carefully evaluated. A bipartite URT usage network was developed and used to determine the inherent connections between urban rail transits and their passengers' travel demands. Although passengers' origins and destinations were easy to locate for a large number of URT segments, a few show very complicated spatial distributions. Based on the bipartite URT usage network, a new layer of the understanding of a URT segment's vulnerability can be achieved by taking the difficulty of addressing the failure of a given segment into account. Two proof-of-concept cases are described here: Possible transfer of passenger flow to the road network is here predicted in the cases of failures of two representative URT segments in San Francisco.
",junjie wang,Not available,2013.0,10.1371/journal.pone.0080178,PLoS ONE,Wang2013,Not available,,PLOS,10,Vulnerability Analysis and Passenger Source Prediction in Urban Rail Transit Networks,9a21f1886b7083a9c6e058ae4ca3f299,https://doi.org/10.1371/journal.pone.0080178
924,"
Based on large-scale human mobility data collected in San Francisco and Boston, the morning peak urban rail transit (URT) ODs (origin-destination matrix) were estimated and the most vulnerable URT segments, those capable of causing the largest service interruptions, were identified. In both URT networks, a few highly vulnerable segments were observed. For this small group of vital segments, the impact of failure must be carefully evaluated. A bipartite URT usage network was developed and used to determine the inherent connections between urban rail transits and their passengers' travel demands. Although passengers' origins and destinations were easy to locate for a large number of URT segments, a few show very complicated spatial distributions. Based on the bipartite URT usage network, a new layer of the understanding of a URT segment's vulnerability can be achieved by taking the difficulty of addressing the failure of a given segment into account. Two proof-of-concept cases are described here: Possible transfer of passenger flow to the road network is here predicted in the cases of failures of two representative URT segments in San Francisco.
",yishuai li,Not available,2013.0,10.1371/journal.pone.0080178,PLoS ONE,Wang2013,Not available,,PLOS,10,Vulnerability Analysis and Passenger Source Prediction in Urban Rail Transit Networks,9a21f1886b7083a9c6e058ae4ca3f299,https://doi.org/10.1371/journal.pone.0080178
925,"
We study a class of games which models the competition among agents to access some service provided by distributed service units and which exhibits congestion and frustration phenomena when service units have limited capacity. We propose a technique, based on the cavity method of statistical physics, to characterize the full spectrum of Nash equilibria of the game. The analysis reveals a large variety of equilibria, with very different statistical properties. Natural selfish dynamics, such as best-response, usually tend to large-utility equilibria, even though those of smaller utility are exponentially more numerous. Interestingly, the latter actually can be reached by selecting the initial conditions of the best-response dynamics close to the saturation limit of the service unit capacities. We also study a more realistic stochastic variant of the game by means of a simple and effective approximation of the average over the random parameters, showing that the properties of the average-case Nash equilibria are qualitatively similar to the deterministic ones.
",fabrizio altarelli,Not available,2015.0,10.1371/journal.pone.0119286,PLOS ONE,Altarelli2015,Not available,,PLOS,18,Statics and Dynamics of Selfish Interactions in Distributed Service Systems,5c19d86ea52e6c05bddbb080529b4282,https://doi.org/10.1371/journal.pone.0119286
926,"
We study a class of games which models the competition among agents to access some service provided by distributed service units and which exhibits congestion and frustration phenomena when service units have limited capacity. We propose a technique, based on the cavity method of statistical physics, to characterize the full spectrum of Nash equilibria of the game. The analysis reveals a large variety of equilibria, with very different statistical properties. Natural selfish dynamics, such as best-response, usually tend to large-utility equilibria, even though those of smaller utility are exponentially more numerous. Interestingly, the latter actually can be reached by selecting the initial conditions of the best-response dynamics close to the saturation limit of the service unit capacities. We also study a more realistic stochastic variant of the game by means of a simple and effective approximation of the average over the random parameters, showing that the properties of the average-case Nash equilibria are qualitatively similar to the deterministic ones.
",alfredo braunstein,Not available,2015.0,10.1371/journal.pone.0119286,PLOS ONE,Altarelli2015,Not available,,PLOS,18,Statics and Dynamics of Selfish Interactions in Distributed Service Systems,5c19d86ea52e6c05bddbb080529b4282,https://doi.org/10.1371/journal.pone.0119286
927,"
We study a class of games which models the competition among agents to access some service provided by distributed service units and which exhibits congestion and frustration phenomena when service units have limited capacity. We propose a technique, based on the cavity method of statistical physics, to characterize the full spectrum of Nash equilibria of the game. The analysis reveals a large variety of equilibria, with very different statistical properties. Natural selfish dynamics, such as best-response, usually tend to large-utility equilibria, even though those of smaller utility are exponentially more numerous. Interestingly, the latter actually can be reached by selecting the initial conditions of the best-response dynamics close to the saturation limit of the service unit capacities. We also study a more realistic stochastic variant of the game by means of a simple and effective approximation of the average over the random parameters, showing that the properties of the average-case Nash equilibria are qualitatively similar to the deterministic ones.
",luca dall'asta,Not available,2015.0,10.1371/journal.pone.0119286,PLOS ONE,Altarelli2015,Not available,,PLOS,18,Statics and Dynamics of Selfish Interactions in Distributed Service Systems,5c19d86ea52e6c05bddbb080529b4282,https://doi.org/10.1371/journal.pone.0119286
928,"
Using an evolutionary game, we show that patients and physicians can interact with predator-prey relationships. Litigious patients who seek compensation are the ‘predators’ and physicians are their ‘prey’. Physicians can adapt to the risk of being sued by performing defensive medicine. We find that improvements in clinical safety can increase the share of litigious patients and leave unchanged the share of physicians who perform defensive medicine. This paradoxical result is consistent with increasing trends in malpractice claims in spite of safety improvements, observed for example in empirical studies on anesthesiologists. Perfect cooperation with neither defensive nor litigious behaviors can be the Pareto-optimal solution when it is not a Nash equilibrium, so maximizing social welfare may require government intervention.
",angelo antoci,Not available,2016.0,10.1371/journal.pone.0150523,PLOS ONE,Antoci2016,Not available,,PLOS,17,The Ecology of Defensive Medicine and Malpractice Litigation,2886f46ee4b93d9787ff952301d1b26a,https://doi.org/10.1371/journal.pone.0150523
929,"
Using an evolutionary game, we show that patients and physicians can interact with predator-prey relationships. Litigious patients who seek compensation are the ‘predators’ and physicians are their ‘prey’. Physicians can adapt to the risk of being sued by performing defensive medicine. We find that improvements in clinical safety can increase the share of litigious patients and leave unchanged the share of physicians who perform defensive medicine. This paradoxical result is consistent with increasing trends in malpractice claims in spite of safety improvements, observed for example in empirical studies on anesthesiologists. Perfect cooperation with neither defensive nor litigious behaviors can be the Pareto-optimal solution when it is not a Nash equilibrium, so maximizing social welfare may require government intervention.
",alessandro maccioni,Not available,2016.0,10.1371/journal.pone.0150523,PLOS ONE,Antoci2016,Not available,,PLOS,17,The Ecology of Defensive Medicine and Malpractice Litigation,2886f46ee4b93d9787ff952301d1b26a,https://doi.org/10.1371/journal.pone.0150523
930,"
Using an evolutionary game, we show that patients and physicians can interact with predator-prey relationships. Litigious patients who seek compensation are the ‘predators’ and physicians are their ‘prey’. Physicians can adapt to the risk of being sued by performing defensive medicine. We find that improvements in clinical safety can increase the share of litigious patients and leave unchanged the share of physicians who perform defensive medicine. This paradoxical result is consistent with increasing trends in malpractice claims in spite of safety improvements, observed for example in empirical studies on anesthesiologists. Perfect cooperation with neither defensive nor litigious behaviors can be the Pareto-optimal solution when it is not a Nash equilibrium, so maximizing social welfare may require government intervention.
",paolo russu,Not available,2016.0,10.1371/journal.pone.0150523,PLOS ONE,Antoci2016,Not available,,PLOS,17,The Ecology of Defensive Medicine and Malpractice Litigation,2886f46ee4b93d9787ff952301d1b26a,https://doi.org/10.1371/journal.pone.0150523
931,"
Cities around the world are inundated by cars and suffer traffic congestion that results in excess delays, reduced safety and environmental pollution. The interplay between road infrastructure and travel choices defines the level and the spatio-temporal extent of congestion. Given the existing infrastructure, understanding how the route choice decisions are made and how travellers interact with each other is a crucial first step in mitigating traffic congestion. This is a problem with fundamental importance, as it has implications for other limited supply systems where agents compete for resources and reach an equilibrium. Here, we observe the route choice decisions and the traffic conditions through an extensive data set of GPS trajectories. We compare the actual paths followed by travellers to those implied by equilibrium conditions (i) at a microscopic scale, where we focus on individual path similarities, and (ii) at a macroscopic scale, where we perform network-level comparison of the traffic loads. We present that non-cooperative or selfish equilibrium replicates the actual traffic (to a certain extent) at the macroscopic scale, while the majority of individual decisions cannot be reproduced by neither selfish nor cooperative equilibrium models.
",mehmet yildirimoglu,Not available,2018.0,10.1371/journal.pone.0196997,PLOS ONE,Yildirimoglu2018,Not available,,PLOS,15,Searching for empirical evidence on traffic equilibrium,c91207730c2d2b1a4545368f85cf337b,https://doi.org/10.1371/journal.pone.0196997
932,"
Cities around the world are inundated by cars and suffer traffic congestion that results in excess delays, reduced safety and environmental pollution. The interplay between road infrastructure and travel choices defines the level and the spatio-temporal extent of congestion. Given the existing infrastructure, understanding how the route choice decisions are made and how travellers interact with each other is a crucial first step in mitigating traffic congestion. This is a problem with fundamental importance, as it has implications for other limited supply systems where agents compete for resources and reach an equilibrium. Here, we observe the route choice decisions and the traffic conditions through an extensive data set of GPS trajectories. We compare the actual paths followed by travellers to those implied by equilibrium conditions (i) at a microscopic scale, where we focus on individual path similarities, and (ii) at a macroscopic scale, where we perform network-level comparison of the traffic loads. We present that non-cooperative or selfish equilibrium replicates the actual traffic (to a certain extent) at the macroscopic scale, while the majority of individual decisions cannot be reproduced by neither selfish nor cooperative equilibrium models.
",osman kahraman,Not available,2018.0,10.1371/journal.pone.0196997,PLOS ONE,Yildirimoglu2018,Not available,,PLOS,15,Searching for empirical evidence on traffic equilibrium,c91207730c2d2b1a4545368f85cf337b,https://doi.org/10.1371/journal.pone.0196997
933,"
Collaboration may be understood as the execution of coordinated tasks (in the most general sense) by groups of users, who cooperate for achieving a common goal. Collaboration is a fundamental assumption and requirement for the correct operation of many communication systems. The main challenge when creating collaborative systems in a decentralized manner is dealing with the fact that users may behave in selfish ways, trying to obtain the benefits of the tasks but without participating in their execution. In this context, Game Theory has been instrumental to model collaborative systems and the task allocation problem, and to design mechanisms for optimal allocation of tasks. In this paper, we revise the classical assumptions of these models and propose a new approach to this problem. First, we establish a system model based on heterogenous nodes (users, players), and propose a basic distributed mechanism so that, when a new task appears, it is assigned to the most suitable node. The classical technique for compensating a node that executes a task is the use of payments (which in most networks are hard or impossible to implement). Instead, we propose a distributed mechanism for the optimal allocation of tasks without payments. We prove this mechanism to be robust evenevent in the presence of independent selfish or rationally limited players. Additionally, our model is based on very weak assumptions, which makes the proposed mechanisms susceptible to be implemented in networked systems (e.g., the Internet).
",agustin santos,Not available,2013.0,10.1371/journal.pone.0066575,PLoS ONE,Santos2013,Not available,,PLOS,15,Quid Pro Quo: A Mechanism for Fair Collaboration in Networked Systems,4c92b5db64bc4c1c53016b36da4845eb,https://doi.org/10.1371/journal.pone.0066575
934,"
Collaboration may be understood as the execution of coordinated tasks (in the most general sense) by groups of users, who cooperate for achieving a common goal. Collaboration is a fundamental assumption and requirement for the correct operation of many communication systems. The main challenge when creating collaborative systems in a decentralized manner is dealing with the fact that users may behave in selfish ways, trying to obtain the benefits of the tasks but without participating in their execution. In this context, Game Theory has been instrumental to model collaborative systems and the task allocation problem, and to design mechanisms for optimal allocation of tasks. In this paper, we revise the classical assumptions of these models and propose a new approach to this problem. First, we establish a system model based on heterogenous nodes (users, players), and propose a basic distributed mechanism so that, when a new task appears, it is assigned to the most suitable node. The classical technique for compensating a node that executes a task is the use of payments (which in most networks are hard or impossible to implement). Instead, we propose a distributed mechanism for the optimal allocation of tasks without payments. We prove this mechanism to be robust evenevent in the presence of independent selfish or rationally limited players. Additionally, our model is based on very weak assumptions, which makes the proposed mechanisms susceptible to be implemented in networked systems (e.g., the Internet).
",antonio anta,Not available,2013.0,10.1371/journal.pone.0066575,PLoS ONE,Santos2013,Not available,,PLOS,15,Quid Pro Quo: A Mechanism for Fair Collaboration in Networked Systems,4c92b5db64bc4c1c53016b36da4845eb,https://doi.org/10.1371/journal.pone.0066575
935,"
Based on large-scale human mobility data collected in San Francisco and Boston, the morning peak urban rail transit (URT) ODs (origin-destination matrix) were estimated and the most vulnerable URT segments, those capable of causing the largest service interruptions, were identified. In both URT networks, a few highly vulnerable segments were observed. For this small group of vital segments, the impact of failure must be carefully evaluated. A bipartite URT usage network was developed and used to determine the inherent connections between urban rail transits and their passengers' travel demands. Although passengers' origins and destinations were easy to locate for a large number of URT segments, a few show very complicated spatial distributions. Based on the bipartite URT usage network, a new layer of the understanding of a URT segment's vulnerability can be achieved by taking the difficulty of addressing the failure of a given segment into account. Two proof-of-concept cases are described here: Possible transfer of passenger flow to the road network is here predicted in the cases of failures of two representative URT segments in San Francisco.
",jingyu liu,Not available,2013.0,10.1371/journal.pone.0080178,PLoS ONE,Wang2013,Not available,,PLOS,10,Vulnerability Analysis and Passenger Source Prediction in Urban Rail Transit Networks,9a21f1886b7083a9c6e058ae4ca3f299,https://doi.org/10.1371/journal.pone.0080178
936,"
Collaboration may be understood as the execution of coordinated tasks (in the most general sense) by groups of users, who cooperate for achieving a common goal. Collaboration is a fundamental assumption and requirement for the correct operation of many communication systems. The main challenge when creating collaborative systems in a decentralized manner is dealing with the fact that users may behave in selfish ways, trying to obtain the benefits of the tasks but without participating in their execution. In this context, Game Theory has been instrumental to model collaborative systems and the task allocation problem, and to design mechanisms for optimal allocation of tasks. In this paper, we revise the classical assumptions of these models and propose a new approach to this problem. First, we establish a system model based on heterogenous nodes (users, players), and propose a basic distributed mechanism so that, when a new task appears, it is assigned to the most suitable node. The classical technique for compensating a node that executes a task is the use of payments (which in most networks are hard or impossible to implement). Instead, we propose a distributed mechanism for the optimal allocation of tasks without payments. We prove this mechanism to be robust evenevent in the presence of independent selfish or rationally limited players. Additionally, our model is based on very weak assumptions, which makes the proposed mechanisms susceptible to be implemented in networked systems (e.g., the Internet).
",luis fernandez,Not available,2013.0,10.1371/journal.pone.0066575,PLoS ONE,Santos2013,Not available,,PLOS,15,Quid Pro Quo: A Mechanism for Fair Collaboration in Networked Systems,4c92b5db64bc4c1c53016b36da4845eb,https://doi.org/10.1371/journal.pone.0066575
937,"
        The spread of infectious diseases at the global scale is mediated by long-range human travel. Our ability to predict the impact of an outbreak on human health requires understanding the spatiotemporal signature of early-time spreading from a specific location. Here, we show that network topology, geography, traffic structure and individual mobility patterns are all essential for accurate predictions of disease spreading. Specifically, we study contagion dynamics through the air transportation network by means of a stochastic agent-tracking model that accounts for the spatial distribution of airports, detailed air traffic and the correlated nature of mobility patterns and waiting-time distributions of individual agents. From the simulation results and the empirical air-travel data, we formulate a metric of influential spreading––the geographic spreading centrality––which accounts for spatial organization and the hierarchical structure of the network traffic, and provides an accurate measure of the early-time spreading power of individual nodes.
      ",christos nicolaides,Not available,2012.0,10.1371/journal.pone.0040961,PLoS ONE,Nicolaides2012,Not available,,PLOS,14,A Metric of Influential Spreading during Contagion Dynamics through the Air Transportation Network,e5e3ee6056383848933f43456869a92d,https://doi.org/10.1371/journal.pone.0040961
938,"
        The spread of infectious diseases at the global scale is mediated by long-range human travel. Our ability to predict the impact of an outbreak on human health requires understanding the spatiotemporal signature of early-time spreading from a specific location. Here, we show that network topology, geography, traffic structure and individual mobility patterns are all essential for accurate predictions of disease spreading. Specifically, we study contagion dynamics through the air transportation network by means of a stochastic agent-tracking model that accounts for the spatial distribution of airports, detailed air traffic and the correlated nature of mobility patterns and waiting-time distributions of individual agents. From the simulation results and the empirical air-travel data, we formulate a metric of influential spreading––the geographic spreading centrality––which accounts for spatial organization and the hierarchical structure of the network traffic, and provides an accurate measure of the early-time spreading power of individual nodes.
      ",luis cueto-felgueroso,Not available,2012.0,10.1371/journal.pone.0040961,PLoS ONE,Nicolaides2012,Not available,,PLOS,14,A Metric of Influential Spreading during Contagion Dynamics through the Air Transportation Network,e5e3ee6056383848933f43456869a92d,https://doi.org/10.1371/journal.pone.0040961
939,"
        The spread of infectious diseases at the global scale is mediated by long-range human travel. Our ability to predict the impact of an outbreak on human health requires understanding the spatiotemporal signature of early-time spreading from a specific location. Here, we show that network topology, geography, traffic structure and individual mobility patterns are all essential for accurate predictions of disease spreading. Specifically, we study contagion dynamics through the air transportation network by means of a stochastic agent-tracking model that accounts for the spatial distribution of airports, detailed air traffic and the correlated nature of mobility patterns and waiting-time distributions of individual agents. From the simulation results and the empirical air-travel data, we formulate a metric of influential spreading––the geographic spreading centrality––which accounts for spatial organization and the hierarchical structure of the network traffic, and provides an accurate measure of the early-time spreading power of individual nodes.
      ",marta gonzalez,Not available,2012.0,10.1371/journal.pone.0040961,PLoS ONE,Nicolaides2012,Not available,,PLOS,14,A Metric of Influential Spreading during Contagion Dynamics through the Air Transportation Network,e5e3ee6056383848933f43456869a92d,https://doi.org/10.1371/journal.pone.0040961
940,"
        The spread of infectious diseases at the global scale is mediated by long-range human travel. Our ability to predict the impact of an outbreak on human health requires understanding the spatiotemporal signature of early-time spreading from a specific location. Here, we show that network topology, geography, traffic structure and individual mobility patterns are all essential for accurate predictions of disease spreading. Specifically, we study contagion dynamics through the air transportation network by means of a stochastic agent-tracking model that accounts for the spatial distribution of airports, detailed air traffic and the correlated nature of mobility patterns and waiting-time distributions of individual agents. From the simulation results and the empirical air-travel data, we formulate a metric of influential spreading––the geographic spreading centrality––which accounts for spatial organization and the hierarchical structure of the network traffic, and provides an accurate measure of the early-time spreading power of individual nodes.
      ",ruben juanes,Not available,2012.0,10.1371/journal.pone.0040961,PLoS ONE,Nicolaides2012,Not available,,PLOS,14,A Metric of Influential Spreading during Contagion Dynamics through the Air Transportation Network,e5e3ee6056383848933f43456869a92d,https://doi.org/10.1371/journal.pone.0040961
941,"
Player tracking data represents a revolutionary new data source for basketball analysis, in which essentially every aspect of a player’s performance is tracked and can be analyzed numerically. We suggest a way by which this data set, when coupled with a network-style model of the offense that relates players’ skills to the team’s success at running different plays, can be used to automatically learn players’ skills and predict the performance of untested 5-man lineups in a way that accounts for the interaction between players’ respective skill sets. After developing a general analysis procedure, we present as an example a specific implementation of our method using a simplified network model. While player tracking data is not yet available in the public domain, we evaluate our model using simulated data and show that player skills can be accurately inferred by a simple statistical inference scheme. Finally, we use the model to analyze games from the 2011 playoff series between the Memphis Grizzlies and the Oklahoma City Thunder and we show that, even with a very limited data set, the model can consistently describe a player’s interactions with a given lineup based only on his performance with a different lineup.
",brian skinner,Not available,2015.0,10.1371/journal.pone.0136393,PLOS ONE,Skinner2015,Not available,,PLOS,14,A Method for Using Player Tracking Data in Basketball to Learn Player Skills and Predict Team Performance,f6affe1d1bdc6bd6a9bdf5b708f3de30,https://doi.org/10.1371/journal.pone.0136393
942,"
Player tracking data represents a revolutionary new data source for basketball analysis, in which essentially every aspect of a player’s performance is tracked and can be analyzed numerically. We suggest a way by which this data set, when coupled with a network-style model of the offense that relates players’ skills to the team’s success at running different plays, can be used to automatically learn players’ skills and predict the performance of untested 5-man lineups in a way that accounts for the interaction between players’ respective skill sets. After developing a general analysis procedure, we present as an example a specific implementation of our method using a simplified network model. While player tracking data is not yet available in the public domain, we evaluate our model using simulated data and show that player skills can be accurately inferred by a simple statistical inference scheme. Finally, we use the model to analyze games from the 2011 playoff series between the Memphis Grizzlies and the Oklahoma City Thunder and we show that, even with a very limited data set, the model can consistently describe a player’s interactions with a given lineup based only on his performance with a different lineup.
",stephen guy,Not available,2015.0,10.1371/journal.pone.0136393,PLOS ONE,Skinner2015,Not available,,PLOS,14,A Method for Using Player Tracking Data in Basketball to Learn Player Skills and Predict Team Performance,f6affe1d1bdc6bd6a9bdf5b708f3de30,https://doi.org/10.1371/journal.pone.0136393
943,"
        We asked how team dynamics can be captured in relation to function by considering games in the first round of the NBA 2010 play-offs as networks. Defining players as nodes and ball movements as links, we analyzed the network properties of degree centrality, clustering, entropy and flow centrality across teams and positions, to characterize the game from a network perspective and to determine whether we can assess differences in team offensive strategy by their network properties. The compiled network structure across teams reflected a fundamental attribute of basketball strategy. They primarily showed a centralized ball distribution pattern with the point guard in a leadership role. However, individual play-off teams showed variation in their relative involvement of other players/positions in ball distribution, reflected quantitatively by differences in clustering and degree centrality. We also characterized two potential alternate offensive strategies by associated variation in network structure: (1) whether teams consistently moved the ball towards their shooting specialists, measured as “uphill/downhill” flux, and (2) whether they distributed the ball in a way that reduced predictability, measured as team entropy. These network metrics quantified different aspects of team strategy, with no single metric wholly predictive of success. However, in the context of the 2010 play-offs, the values of clustering (connectedness across players) and network entropy (unpredictability of ball movement) had the most consistent association with team advancement. Our analyses demonstrate the utility of network approaches in quantifying team strategy and show that testable hypotheses can be evaluated using this approach. These analyses also highlight the richness of basketball networks as a dataset for exploring the relationships between network structure and dynamics with team organization and effectiveness.
      ",jennifer fewell,Not available,2012.0,10.1371/journal.pone.0047445,PLoS ONE,Fewell2012,Not available,,PLOS,14,Basketball Teams as Strategic Networks,52b1639610d35cf71d5cc300e5b7190e,https://doi.org/10.1371/journal.pone.0047445
944,"
        We asked how team dynamics can be captured in relation to function by considering games in the first round of the NBA 2010 play-offs as networks. Defining players as nodes and ball movements as links, we analyzed the network properties of degree centrality, clustering, entropy and flow centrality across teams and positions, to characterize the game from a network perspective and to determine whether we can assess differences in team offensive strategy by their network properties. The compiled network structure across teams reflected a fundamental attribute of basketball strategy. They primarily showed a centralized ball distribution pattern with the point guard in a leadership role. However, individual play-off teams showed variation in their relative involvement of other players/positions in ball distribution, reflected quantitatively by differences in clustering and degree centrality. We also characterized two potential alternate offensive strategies by associated variation in network structure: (1) whether teams consistently moved the ball towards their shooting specialists, measured as “uphill/downhill” flux, and (2) whether they distributed the ball in a way that reduced predictability, measured as team entropy. These network metrics quantified different aspects of team strategy, with no single metric wholly predictive of success. However, in the context of the 2010 play-offs, the values of clustering (connectedness across players) and network entropy (unpredictability of ball movement) had the most consistent association with team advancement. Our analyses demonstrate the utility of network approaches in quantifying team strategy and show that testable hypotheses can be evaluated using this approach. These analyses also highlight the richness of basketball networks as a dataset for exploring the relationships between network structure and dynamics with team organization and effectiveness.
      ",dieter armbruster,Not available,2012.0,10.1371/journal.pone.0047445,PLoS ONE,Fewell2012,Not available,,PLOS,14,Basketball Teams as Strategic Networks,52b1639610d35cf71d5cc300e5b7190e,https://doi.org/10.1371/journal.pone.0047445
945,"
        We asked how team dynamics can be captured in relation to function by considering games in the first round of the NBA 2010 play-offs as networks. Defining players as nodes and ball movements as links, we analyzed the network properties of degree centrality, clustering, entropy and flow centrality across teams and positions, to characterize the game from a network perspective and to determine whether we can assess differences in team offensive strategy by their network properties. The compiled network structure across teams reflected a fundamental attribute of basketball strategy. They primarily showed a centralized ball distribution pattern with the point guard in a leadership role. However, individual play-off teams showed variation in their relative involvement of other players/positions in ball distribution, reflected quantitatively by differences in clustering and degree centrality. We also characterized two potential alternate offensive strategies by associated variation in network structure: (1) whether teams consistently moved the ball towards their shooting specialists, measured as “uphill/downhill” flux, and (2) whether they distributed the ball in a way that reduced predictability, measured as team entropy. These network metrics quantified different aspects of team strategy, with no single metric wholly predictive of success. However, in the context of the 2010 play-offs, the values of clustering (connectedness across players) and network entropy (unpredictability of ball movement) had the most consistent association with team advancement. Our analyses demonstrate the utility of network approaches in quantifying team strategy and show that testable hypotheses can be evaluated using this approach. These analyses also highlight the richness of basketball networks as a dataset for exploring the relationships between network structure and dynamics with team organization and effectiveness.
      ",john ingraham,Not available,2012.0,10.1371/journal.pone.0047445,PLoS ONE,Fewell2012,Not available,,PLOS,14,Basketball Teams as Strategic Networks,52b1639610d35cf71d5cc300e5b7190e,https://doi.org/10.1371/journal.pone.0047445
946,"
Based on large-scale human mobility data collected in San Francisco and Boston, the morning peak urban rail transit (URT) ODs (origin-destination matrix) were estimated and the most vulnerable URT segments, those capable of causing the largest service interruptions, were identified. In both URT networks, a few highly vulnerable segments were observed. For this small group of vital segments, the impact of failure must be carefully evaluated. A bipartite URT usage network was developed and used to determine the inherent connections between urban rail transits and their passengers' travel demands. Although passengers' origins and destinations were easy to locate for a large number of URT segments, a few show very complicated spatial distributions. Based on the bipartite URT usage network, a new layer of the understanding of a URT segment's vulnerability can be achieved by taking the difficulty of addressing the failure of a given segment into account. Two proof-of-concept cases are described here: Possible transfer of passenger flow to the road network is here predicted in the cases of failures of two representative URT segments in San Francisco.
",kun he,Not available,2013.0,10.1371/journal.pone.0080178,PLoS ONE,Wang2013,Not available,,PLOS,10,Vulnerability Analysis and Passenger Source Prediction in Urban Rail Transit Networks,9a21f1886b7083a9c6e058ae4ca3f299,https://doi.org/10.1371/journal.pone.0080178
947,"
        We asked how team dynamics can be captured in relation to function by considering games in the first round of the NBA 2010 play-offs as networks. Defining players as nodes and ball movements as links, we analyzed the network properties of degree centrality, clustering, entropy and flow centrality across teams and positions, to characterize the game from a network perspective and to determine whether we can assess differences in team offensive strategy by their network properties. The compiled network structure across teams reflected a fundamental attribute of basketball strategy. They primarily showed a centralized ball distribution pattern with the point guard in a leadership role. However, individual play-off teams showed variation in their relative involvement of other players/positions in ball distribution, reflected quantitatively by differences in clustering and degree centrality. We also characterized two potential alternate offensive strategies by associated variation in network structure: (1) whether teams consistently moved the ball towards their shooting specialists, measured as “uphill/downhill” flux, and (2) whether they distributed the ball in a way that reduced predictability, measured as team entropy. These network metrics quantified different aspects of team strategy, with no single metric wholly predictive of success. However, in the context of the 2010 play-offs, the values of clustering (connectedness across players) and network entropy (unpredictability of ball movement) had the most consistent association with team advancement. Our analyses demonstrate the utility of network approaches in quantifying team strategy and show that testable hypotheses can be evaluated using this approach. These analyses also highlight the richness of basketball networks as a dataset for exploring the relationships between network structure and dynamics with team organization and effectiveness.
      ",alexander petersen,Not available,2012.0,10.1371/journal.pone.0047445,PLoS ONE,Fewell2012,Not available,,PLOS,14,Basketball Teams as Strategic Networks,52b1639610d35cf71d5cc300e5b7190e,https://doi.org/10.1371/journal.pone.0047445
948,"
        We asked how team dynamics can be captured in relation to function by considering games in the first round of the NBA 2010 play-offs as networks. Defining players as nodes and ball movements as links, we analyzed the network properties of degree centrality, clustering, entropy and flow centrality across teams and positions, to characterize the game from a network perspective and to determine whether we can assess differences in team offensive strategy by their network properties. The compiled network structure across teams reflected a fundamental attribute of basketball strategy. They primarily showed a centralized ball distribution pattern with the point guard in a leadership role. However, individual play-off teams showed variation in their relative involvement of other players/positions in ball distribution, reflected quantitatively by differences in clustering and degree centrality. We also characterized two potential alternate offensive strategies by associated variation in network structure: (1) whether teams consistently moved the ball towards their shooting specialists, measured as “uphill/downhill” flux, and (2) whether they distributed the ball in a way that reduced predictability, measured as team entropy. These network metrics quantified different aspects of team strategy, with no single metric wholly predictive of success. However, in the context of the 2010 play-offs, the values of clustering (connectedness across players) and network entropy (unpredictability of ball movement) had the most consistent association with team advancement. Our analyses demonstrate the utility of network approaches in quantifying team strategy and show that testable hypotheses can be evaluated using this approach. These analyses also highlight the richness of basketball networks as a dataset for exploring the relationships between network structure and dynamics with team organization and effectiveness.
      ",james waters,Not available,2012.0,10.1371/journal.pone.0047445,PLoS ONE,Fewell2012,Not available,,PLOS,14,Basketball Teams as Strategic Networks,52b1639610d35cf71d5cc300e5b7190e,https://doi.org/10.1371/journal.pone.0047445
949,"
        We considered all matches played by professional tennis players between 1968 and2010, and, on the basis of this data set, constructed a directed and weighted network of contacts. The resulting graph showed complex features, typical of many real networked systems studied in literature. We developed a diffusion algorithm and applied it to the tennis contact network in order to rank professional players. Jimmy Connors was identified as the best player in the history of tennis according to our ranking procedure. We performed a complete analysis by determining the best players on specific playing surfaces as well as the best ones in each of the years covered by the data set. The results of our technique were compared to those of two other well established methods. In general, we observed that our ranking method performed better: it had a higher predictive power and did not require the arbitrary introduction of external criteria for the correct assessment of the quality of players. The present work provides novel evidence of the utility of tools and methods of network theory in real applications.
      ",filippo radicchi,Not available,2011.0,10.1371/journal.pone.0017249,PLoS ONE,Radicchi2011,Not available,,PLOS,11,Who Is the Best Player Ever? A Complex Network Analysis of the History of Professional Tennis,2fd4a27b796311feb802bf5d5f5d8b3e,https://doi.org/10.1371/journal.pone.0017249
950,"
        In basketball, every time the offense produces a shot opportunity the player with the ball must decide whether the shot is worth taking. In this article, I explore the question of when a team should shoot and when they should pass up the shot by considering a simple theoretical model of the shot selection process, in which the quality of shot opportunities generated by the offense is assumed to fall randomly within a uniform distribution. Within this model I derive an answer to the question “how likely must the shot be to go in before the player should take it?” and I show that this lower cutoff for shot quality  depends crucially on the number  of shot opportunities remaining (say, before the shot clock expires), with larger  demanding that only higher-quality shots should be taken. The function  is also derived in the presence of a finite turnover rate and used to predict the shooting rate of an optimal-shooting team as a function of time. The theoretical prediction for the optimal shooting rate is compared to data from the National Basketball Association (NBA). The comparison highlights some limitations of the theoretical model, while also suggesting that NBA teams may be overly reluctant to shoot the ball early in the shot clock.
      ",brian skinner,Not available,2012.0,10.1371/journal.pone.0030776,PLoS ONE,Skinner2012,Not available,,PLOS,11,The Problem of Shot Selection in Basketball,666e52a8c5426d895beb81ef1bd8b052,https://doi.org/10.1371/journal.pone.0030776
951,"
In operant learning, behaviors are reinforced or inhibited in response to the consequences of similar actions taken in the past. However, because in natural environments the “same” situation never recurs, it is essential for the learner to decide what “similar” is so that he can generalize from experience in one state of the world to future actions in different states of the world. The computational principles underlying this generalization are poorly understood, in particular because natural environments are typically too complex to study quantitatively. In this paper we study the principles underlying generalization in operant learning of professional basketball players. In particular, we utilize detailed information about the spatial organization of shot locations to study how players adapt their attacking strategy in real time according to recent events in the game. To quantify this learning, we study how a make \ miss from one location in the court affects the probabilities of shooting from different locations. We show that generalization is not a spatially-local process, nor is governed by the difficulty of the shot. Rather, to a first approximation, players use a simplified binary representation of the court into 2 pt and 3 pt zones. This result indicates that rather than using low-level features, generalization is determined by high-level cognitive processes that incorporate the abstract rules of the game.
Author Summary: According to the law of effect, formulated a century ago by Edward Thorndike, actions which are rewarded in a particular situation are more likely to be executed when that same situation recurs. However, in natural settings the same situation never recurs and therefore, generalization from one state of the world to other states is an essential part of the process of learning. In this paper we utilize basketball statistics to study the computational principles underlying generalization in operant learning of professional basketball players. We show that players are more likely to attempt a field goal from the vicinity of a previously made shot than they are from the vicinity of a missed shot, as expected from the law of effect. However, the outcome of a shot can also affect the likelihood of attempting another shot at a different location. Using hierarchical clustering we characterize the spatial pattern of generalization and show that generalization is primarily determined by the type of shot, 3 pt vs. 2 pt. This result indicates that rather than using low-level features, generalization is determined by high-level cognitive processes that incorporate the abstract rules of the game. ",tal neiman,Not available,2014.0,10.1371/journal.pcbi.1003623,PLoS Computational Biology,Neiman2014,Not available,,PLOS,10,Spatial Generalization in Operant Learning: Lessons from Professional Basketball,c925cf312ba5c3f890e49fdfa50a7e54,https://doi.org/10.1371/journal.pcbi.1003623
952,"
In operant learning, behaviors are reinforced or inhibited in response to the consequences of similar actions taken in the past. However, because in natural environments the “same” situation never recurs, it is essential for the learner to decide what “similar” is so that he can generalize from experience in one state of the world to future actions in different states of the world. The computational principles underlying this generalization are poorly understood, in particular because natural environments are typically too complex to study quantitatively. In this paper we study the principles underlying generalization in operant learning of professional basketball players. In particular, we utilize detailed information about the spatial organization of shot locations to study how players adapt their attacking strategy in real time according to recent events in the game. To quantify this learning, we study how a make \ miss from one location in the court affects the probabilities of shooting from different locations. We show that generalization is not a spatially-local process, nor is governed by the difficulty of the shot. Rather, to a first approximation, players use a simplified binary representation of the court into 2 pt and 3 pt zones. This result indicates that rather than using low-level features, generalization is determined by high-level cognitive processes that incorporate the abstract rules of the game.
Author Summary: According to the law of effect, formulated a century ago by Edward Thorndike, actions which are rewarded in a particular situation are more likely to be executed when that same situation recurs. However, in natural settings the same situation never recurs and therefore, generalization from one state of the world to other states is an essential part of the process of learning. In this paper we utilize basketball statistics to study the computational principles underlying generalization in operant learning of professional basketball players. We show that players are more likely to attempt a field goal from the vicinity of a previously made shot than they are from the vicinity of a missed shot, as expected from the law of effect. However, the outcome of a shot can also affect the likelihood of attempting another shot at a different location. Using hierarchical clustering we characterize the spatial pattern of generalization and show that generalization is primarily determined by the type of shot, 3 pt vs. 2 pt. This result indicates that rather than using low-level features, generalization is determined by high-level cognitive processes that incorporate the abstract rules of the game. ",yonatan loewenstein,Not available,2014.0,10.1371/journal.pcbi.1003623,PLoS Computational Biology,Neiman2014,Not available,,PLOS,10,Spatial Generalization in Operant Learning: Lessons from Professional Basketball,c925cf312ba5c3f890e49fdfa50a7e54,https://doi.org/10.1371/journal.pcbi.1003623
953,"
Based on large-scale human mobility data collected in San Francisco and Boston, the morning peak urban rail transit (URT) ODs (origin-destination matrix) were estimated and the most vulnerable URT segments, those capable of causing the largest service interruptions, were identified. In both URT networks, a few highly vulnerable segments were observed. For this small group of vital segments, the impact of failure must be carefully evaluated. A bipartite URT usage network was developed and used to determine the inherent connections between urban rail transits and their passengers' travel demands. Although passengers' origins and destinations were easy to locate for a large number of URT segments, a few show very complicated spatial distributions. Based on the bipartite URT usage network, a new layer of the understanding of a URT segment's vulnerability can be achieved by taking the difficulty of addressing the failure of a given segment into account. Two proof-of-concept cases are described here: Possible transfer of passenger flow to the road network is here predicted in the cases of failures of two representative URT segments in San Francisco.
",pu wang,Not available,2013.0,10.1371/journal.pone.0080178,PLoS ONE,Wang2013,Not available,,PLOS,10,Vulnerability Analysis and Passenger Source Prediction in Urban Rail Transit Networks,9a21f1886b7083a9c6e058ae4ca3f299,https://doi.org/10.1371/journal.pone.0080178
954,"
We set up a game theoretic framework to analyze a wide range of situations from team sports. A fundamental idea is the concept of potential; the probability of the offense scoring the next goal minus the probability that the next goal is made by the defense. We develop categorical as well as continuous models, and obtain optimal strategies for both offense and defense. A main result is that the optimal defensive strategy is to minimize the maximum potential of all offensive strategies.
",jan lennartsson,Not available,2015.0,10.1371/journal.pone.0125453,PLOS ONE,Lennartsson2015,Not available,,PLOS,9,Game Intelligence in Team Sports,faf9f6204f0bc51545ab707d45b6e263,https://doi.org/10.1371/journal.pone.0125453
955,"
We set up a game theoretic framework to analyze a wide range of situations from team sports. A fundamental idea is the concept of potential; the probability of the offense scoring the next goal minus the probability that the next goal is made by the defense. We develop categorical as well as continuous models, and obtain optimal strategies for both offense and defense. A main result is that the optimal defensive strategy is to minimize the maximum potential of all offensive strategies.
",nicklas lidstrom,Not available,2015.0,10.1371/journal.pone.0125453,PLOS ONE,Lennartsson2015,Not available,,PLOS,9,Game Intelligence in Team Sports,faf9f6204f0bc51545ab707d45b6e263,https://doi.org/10.1371/journal.pone.0125453
956,"
We set up a game theoretic framework to analyze a wide range of situations from team sports. A fundamental idea is the concept of potential; the probability of the offense scoring the next goal minus the probability that the next goal is made by the defense. We develop categorical as well as continuous models, and obtain optimal strategies for both offense and defense. A main result is that the optimal defensive strategy is to minimize the maximum potential of all offensive strategies.
",carl lindberg,Not available,2015.0,10.1371/journal.pone.0125453,PLOS ONE,Lennartsson2015,Not available,,PLOS,9,Game Intelligence in Team Sports,faf9f6204f0bc51545ab707d45b6e263,https://doi.org/10.1371/journal.pone.0125453
957,"
Best investment in the road infrastructure or the network design is perceived as a fundamental and benchmark problem in transportation. Given a set of candidate road projects with associated costs, finding the best subset with respect to a limited budget is known as a bilevel Discrete Network Design Problem (DNDP) of NP-hard computationally complexity. We engage with the complexity with a hybrid exact-heuristic methodology based on a two-stage relaxation as follows: (i) the bilevel feature is relaxed to a single-level problem by taking the network performance function of the upper level into the user equilibrium traffic assignment problem (UE-TAP) in the lower level as a constraint. It results in a mixed-integer nonlinear programming (MINLP) problem which is then solved using the Outer Approximation (OA) algorithm (ii) we further relax the multi-commodity UE-TAP to a single-commodity MILP problem, that is, the multiple OD pairs are aggregated to a single OD pair. This methodology has two main advantages: (i) the method is proven to be highly efficient to solve the DNDP for a large-sized network of Winnipeg, Canada. The results suggest that within a limited number of iterations (as termination criterion), global optimum solutions are quickly reached in most of the cases; otherwise, good solutions (close to global optimum solutions) are found in early iterations. Comparative analysis of the networks of Gao and Sioux-Falls shows that for such a non-exact method the global optimum solutions are found in fewer iterations than those found in some analytically exact algorithms in the literature. (ii) Integration of the objective function among the constraints provides a commensurate capability to tackle the multi-objective (or multi-criteria) DNDP as well.
",saeed bagloee,Not available,2018.0,10.1371/journal.pone.0192454,PLOS ONE,Bagloee2018,Not available,,PLOS,7,An outer approximation method for the road network design problem,f87b0f49104ec8917e47e5d6d6b5523b,https://doi.org/10.1371/journal.pone.0192454
958,"
Best investment in the road infrastructure or the network design is perceived as a fundamental and benchmark problem in transportation. Given a set of candidate road projects with associated costs, finding the best subset with respect to a limited budget is known as a bilevel Discrete Network Design Problem (DNDP) of NP-hard computationally complexity. We engage with the complexity with a hybrid exact-heuristic methodology based on a two-stage relaxation as follows: (i) the bilevel feature is relaxed to a single-level problem by taking the network performance function of the upper level into the user equilibrium traffic assignment problem (UE-TAP) in the lower level as a constraint. It results in a mixed-integer nonlinear programming (MINLP) problem which is then solved using the Outer Approximation (OA) algorithm (ii) we further relax the multi-commodity UE-TAP to a single-commodity MILP problem, that is, the multiple OD pairs are aggregated to a single OD pair. This methodology has two main advantages: (i) the method is proven to be highly efficient to solve the DNDP for a large-sized network of Winnipeg, Canada. The results suggest that within a limited number of iterations (as termination criterion), global optimum solutions are quickly reached in most of the cases; otherwise, good solutions (close to global optimum solutions) are found in early iterations. Comparative analysis of the networks of Gao and Sioux-Falls shows that for such a non-exact method the global optimum solutions are found in fewer iterations than those found in some analytically exact algorithms in the literature. (ii) Integration of the objective function among the constraints provides a commensurate capability to tackle the multi-objective (or multi-criteria) DNDP as well.
",majid sarvi,Not available,2018.0,10.1371/journal.pone.0192454,PLOS ONE,Bagloee2018,Not available,,PLOS,7,An outer approximation method for the road network design problem,f87b0f49104ec8917e47e5d6d6b5523b,https://doi.org/10.1371/journal.pone.0192454
959,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
960,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
961,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
962,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
963,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
964,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",sanjiv kapoor,Routing,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
965,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",sanjiv kapoor,Delays,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
966,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",sanjiv kapoor,Global Positioning System,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
967,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",sanjiv kapoor,Nash equilibrium,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
968,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",sanjiv kapoor,Processor scheduling,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
969,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",sanjiv kapoor,Servers,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
970,"Transforming conventional passive customers into active participants who interact with the utility in real time is the key idea of demand response (DR) in smart grid. However, an effective and efficient DR scheme relies on precise prediction and modeling of the uncertainties, i.e., renewable generations and load demands. In this paper, we first present a series of linear prediction models for the load prediction purpose, such as standard autoregressive (AR) process and time-varying AR (TVAR) process, according to different assumptions on the stationarity of customer load profile: piecewise stationarity, local stationarity, and cyclostationarity. Two important issues in AR/TVAR models are addressed: determining the order of AR/TVAR models and calculating the AR/TVAR coefficients. The partial autocorrelation function is analyzed to determine the model order, and the minimum mean squared error estimator is adopted to derive the AR/TVAR coefficients, which leads to the Yule-Walker type of equations. With the load prediction problem addressed, we further design a DR scheduling scheme based on utility cost minimization with different customer clustering sizes. The optimal DR load profiles are given in forms of both 1-D and 2-D water-filling solutions. A tradeoff strategy, which attempts to balance the competing objectives (centralized and distributed), is also provided based on the price-of-anarchy analysis. Simulation results of both the load prediction models and the DR schemes are presented and analyzed.",ding li,Demand response (DR),2017.0,10.1109/JSYST.2014.2369451,IEEE Systems Journal,Li2017,False,,IEEE,Not available,Uncertainty Modeling and Price-Based Demand Response Scheme Design in Smart Grid,53f1ee3785bc69c7aff8eb474d03c147,https://ieeexplore.ieee.org/document/6982225/
971,"Transforming conventional passive customers into active participants who interact with the utility in real time is the key idea of demand response (DR) in smart grid. However, an effective and efficient DR scheme relies on precise prediction and modeling of the uncertainties, i.e., renewable generations and load demands. In this paper, we first present a series of linear prediction models for the load prediction purpose, such as standard autoregressive (AR) process and time-varying AR (TVAR) process, according to different assumptions on the stationarity of customer load profile: piecewise stationarity, local stationarity, and cyclostationarity. Two important issues in AR/TVAR models are addressed: determining the order of AR/TVAR models and calculating the AR/TVAR coefficients. The partial autocorrelation function is analyzed to determine the model order, and the minimum mean squared error estimator is adopted to derive the AR/TVAR coefficients, which leads to the Yule-Walker type of equations. With the load prediction problem addressed, we further design a DR scheduling scheme based on utility cost minimization with different customer clustering sizes. The optimal DR load profiles are given in forms of both 1-D and 2-D water-filling solutions. A tradeoff strategy, which attempts to balance the competing objectives (centralized and distributed), is also provided based on the price-of-anarchy analysis. Simulation results of both the load prediction models and the DR schemes are presented and analyzed.",ding li,load prediction,2017.0,10.1109/JSYST.2014.2369451,IEEE Systems Journal,Li2017,False,,IEEE,Not available,Uncertainty Modeling and Price-Based Demand Response Scheme Design in Smart Grid,53f1ee3785bc69c7aff8eb474d03c147,https://ieeexplore.ieee.org/document/6982225/
972,"Transforming conventional passive customers into active participants who interact with the utility in real time is the key idea of demand response (DR) in smart grid. However, an effective and efficient DR scheme relies on precise prediction and modeling of the uncertainties, i.e., renewable generations and load demands. In this paper, we first present a series of linear prediction models for the load prediction purpose, such as standard autoregressive (AR) process and time-varying AR (TVAR) process, according to different assumptions on the stationarity of customer load profile: piecewise stationarity, local stationarity, and cyclostationarity. Two important issues in AR/TVAR models are addressed: determining the order of AR/TVAR models and calculating the AR/TVAR coefficients. The partial autocorrelation function is analyzed to determine the model order, and the minimum mean squared error estimator is adopted to derive the AR/TVAR coefficients, which leads to the Yule-Walker type of equations. With the load prediction problem addressed, we further design a DR scheduling scheme based on utility cost minimization with different customer clustering sizes. The optimal DR load profiles are given in forms of both 1-D and 2-D water-filling solutions. A tradeoff strategy, which attempts to balance the competing objectives (centralized and distributed), is also provided based on the price-of-anarchy analysis. Simulation results of both the load prediction models and the DR schemes are presented and analyzed.",ding li,partial autocorrelation function (PACF),2017.0,10.1109/JSYST.2014.2369451,IEEE Systems Journal,Li2017,False,,IEEE,Not available,Uncertainty Modeling and Price-Based Demand Response Scheme Design in Smart Grid,53f1ee3785bc69c7aff8eb474d03c147,https://ieeexplore.ieee.org/document/6982225/
973,"Transforming conventional passive customers into active participants who interact with the utility in real time is the key idea of demand response (DR) in smart grid. However, an effective and efficient DR scheme relies on precise prediction and modeling of the uncertainties, i.e., renewable generations and load demands. In this paper, we first present a series of linear prediction models for the load prediction purpose, such as standard autoregressive (AR) process and time-varying AR (TVAR) process, according to different assumptions on the stationarity of customer load profile: piecewise stationarity, local stationarity, and cyclostationarity. Two important issues in AR/TVAR models are addressed: determining the order of AR/TVAR models and calculating the AR/TVAR coefficients. The partial autocorrelation function is analyzed to determine the model order, and the minimum mean squared error estimator is adopted to derive the AR/TVAR coefficients, which leads to the Yule-Walker type of equations. With the load prediction problem addressed, we further design a DR scheduling scheme based on utility cost minimization with different customer clustering sizes. The optimal DR load profiles are given in forms of both 1-D and 2-D water-filling solutions. A tradeoff strategy, which attempts to balance the competing objectives (centralized and distributed), is also provided based on the price-of-anarchy analysis. Simulation results of both the load prediction models and the DR schemes are presented and analyzed.",ding li,price of anarchy (POA),2017.0,10.1109/JSYST.2014.2369451,IEEE Systems Journal,Li2017,False,,IEEE,Not available,Uncertainty Modeling and Price-Based Demand Response Scheme Design in Smart Grid,53f1ee3785bc69c7aff8eb474d03c147,https://ieeexplore.ieee.org/document/6982225/
974,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
975,"Transforming conventional passive customers into active participants who interact with the utility in real time is the key idea of demand response (DR) in smart grid. However, an effective and efficient DR scheme relies on precise prediction and modeling of the uncertainties, i.e., renewable generations and load demands. In this paper, we first present a series of linear prediction models for the load prediction purpose, such as standard autoregressive (AR) process and time-varying AR (TVAR) process, according to different assumptions on the stationarity of customer load profile: piecewise stationarity, local stationarity, and cyclostationarity. Two important issues in AR/TVAR models are addressed: determining the order of AR/TVAR models and calculating the AR/TVAR coefficients. The partial autocorrelation function is analyzed to determine the model order, and the minimum mean squared error estimator is adopted to derive the AR/TVAR coefficients, which leads to the Yule-Walker type of equations. With the load prediction problem addressed, we further design a DR scheduling scheme based on utility cost minimization with different customer clustering sizes. The optimal DR load profiles are given in forms of both 1-D and 2-D water-filling solutions. A tradeoff strategy, which attempts to balance the competing objectives (centralized and distributed), is also provided based on the price-of-anarchy analysis. Simulation results of both the load prediction models and the DR schemes are presented and analyzed.",ding li,time-varying autoregressive (TVAR) process,2017.0,10.1109/JSYST.2014.2369451,IEEE Systems Journal,Li2017,False,,IEEE,Not available,Uncertainty Modeling and Price-Based Demand Response Scheme Design in Smart Grid,53f1ee3785bc69c7aff8eb474d03c147,https://ieeexplore.ieee.org/document/6982225/
976,"Transforming conventional passive customers into active participants who interact with the utility in real time is the key idea of demand response (DR) in smart grid. However, an effective and efficient DR scheme relies on precise prediction and modeling of the uncertainties, i.e., renewable generations and load demands. In this paper, we first present a series of linear prediction models for the load prediction purpose, such as standard autoregressive (AR) process and time-varying AR (TVAR) process, according to different assumptions on the stationarity of customer load profile: piecewise stationarity, local stationarity, and cyclostationarity. Two important issues in AR/TVAR models are addressed: determining the order of AR/TVAR models and calculating the AR/TVAR coefficients. The partial autocorrelation function is analyzed to determine the model order, and the minimum mean squared error estimator is adopted to derive the AR/TVAR coefficients, which leads to the Yule-Walker type of equations. With the load prediction problem addressed, we further design a DR scheduling scheme based on utility cost minimization with different customer clustering sizes. The optimal DR load profiles are given in forms of both 1-D and 2-D water-filling solutions. A tradeoff strategy, which attempts to balance the competing objectives (centralized and distributed), is also provided based on the price-of-anarchy analysis. Simulation results of both the load prediction models and the DR schemes are presented and analyzed.",ding li,2-D water filling,2017.0,10.1109/JSYST.2014.2369451,IEEE Systems Journal,Li2017,False,,IEEE,Not available,Uncertainty Modeling and Price-Based Demand Response Scheme Design in Smart Grid,53f1ee3785bc69c7aff8eb474d03c147,https://ieeexplore.ieee.org/document/6982225/
977,"Transforming conventional passive customers into active participants who interact with the utility in real time is the key idea of demand response (DR) in smart grid. However, an effective and efficient DR scheme relies on precise prediction and modeling of the uncertainties, i.e., renewable generations and load demands. In this paper, we first present a series of linear prediction models for the load prediction purpose, such as standard autoregressive (AR) process and time-varying AR (TVAR) process, according to different assumptions on the stationarity of customer load profile: piecewise stationarity, local stationarity, and cyclostationarity. Two important issues in AR/TVAR models are addressed: determining the order of AR/TVAR models and calculating the AR/TVAR coefficients. The partial autocorrelation function is analyzed to determine the model order, and the minimum mean squared error estimator is adopted to derive the AR/TVAR coefficients, which leads to the Yule-Walker type of equations. With the load prediction problem addressed, we further design a DR scheduling scheme based on utility cost minimization with different customer clustering sizes. The optimal DR load profiles are given in forms of both 1-D and 2-D water-filling solutions. A tradeoff strategy, which attempts to balance the competing objectives (centralized and distributed), is also provided based on the price-of-anarchy analysis. Simulation results of both the load prediction models and the DR schemes are presented and analyzed.",sudharman jayaweera,Demand response (DR),2017.0,10.1109/JSYST.2014.2369451,IEEE Systems Journal,Li2017,False,,IEEE,Not available,Uncertainty Modeling and Price-Based Demand Response Scheme Design in Smart Grid,53f1ee3785bc69c7aff8eb474d03c147,https://ieeexplore.ieee.org/document/6982225/
978,"Transforming conventional passive customers into active participants who interact with the utility in real time is the key idea of demand response (DR) in smart grid. However, an effective and efficient DR scheme relies on precise prediction and modeling of the uncertainties, i.e., renewable generations and load demands. In this paper, we first present a series of linear prediction models for the load prediction purpose, such as standard autoregressive (AR) process and time-varying AR (TVAR) process, according to different assumptions on the stationarity of customer load profile: piecewise stationarity, local stationarity, and cyclostationarity. Two important issues in AR/TVAR models are addressed: determining the order of AR/TVAR models and calculating the AR/TVAR coefficients. The partial autocorrelation function is analyzed to determine the model order, and the minimum mean squared error estimator is adopted to derive the AR/TVAR coefficients, which leads to the Yule-Walker type of equations. With the load prediction problem addressed, we further design a DR scheduling scheme based on utility cost minimization with different customer clustering sizes. The optimal DR load profiles are given in forms of both 1-D and 2-D water-filling solutions. A tradeoff strategy, which attempts to balance the competing objectives (centralized and distributed), is also provided based on the price-of-anarchy analysis. Simulation results of both the load prediction models and the DR schemes are presented and analyzed.",sudharman jayaweera,load prediction,2017.0,10.1109/JSYST.2014.2369451,IEEE Systems Journal,Li2017,False,,IEEE,Not available,Uncertainty Modeling and Price-Based Demand Response Scheme Design in Smart Grid,53f1ee3785bc69c7aff8eb474d03c147,https://ieeexplore.ieee.org/document/6982225/
979,"Transforming conventional passive customers into active participants who interact with the utility in real time is the key idea of demand response (DR) in smart grid. However, an effective and efficient DR scheme relies on precise prediction and modeling of the uncertainties, i.e., renewable generations and load demands. In this paper, we first present a series of linear prediction models for the load prediction purpose, such as standard autoregressive (AR) process and time-varying AR (TVAR) process, according to different assumptions on the stationarity of customer load profile: piecewise stationarity, local stationarity, and cyclostationarity. Two important issues in AR/TVAR models are addressed: determining the order of AR/TVAR models and calculating the AR/TVAR coefficients. The partial autocorrelation function is analyzed to determine the model order, and the minimum mean squared error estimator is adopted to derive the AR/TVAR coefficients, which leads to the Yule-Walker type of equations. With the load prediction problem addressed, we further design a DR scheduling scheme based on utility cost minimization with different customer clustering sizes. The optimal DR load profiles are given in forms of both 1-D and 2-D water-filling solutions. A tradeoff strategy, which attempts to balance the competing objectives (centralized and distributed), is also provided based on the price-of-anarchy analysis. Simulation results of both the load prediction models and the DR schemes are presented and analyzed.",sudharman jayaweera,partial autocorrelation function (PACF),2017.0,10.1109/JSYST.2014.2369451,IEEE Systems Journal,Li2017,False,,IEEE,Not available,Uncertainty Modeling and Price-Based Demand Response Scheme Design in Smart Grid,53f1ee3785bc69c7aff8eb474d03c147,https://ieeexplore.ieee.org/document/6982225/
980,"Transforming conventional passive customers into active participants who interact with the utility in real time is the key idea of demand response (DR) in smart grid. However, an effective and efficient DR scheme relies on precise prediction and modeling of the uncertainties, i.e., renewable generations and load demands. In this paper, we first present a series of linear prediction models for the load prediction purpose, such as standard autoregressive (AR) process and time-varying AR (TVAR) process, according to different assumptions on the stationarity of customer load profile: piecewise stationarity, local stationarity, and cyclostationarity. Two important issues in AR/TVAR models are addressed: determining the order of AR/TVAR models and calculating the AR/TVAR coefficients. The partial autocorrelation function is analyzed to determine the model order, and the minimum mean squared error estimator is adopted to derive the AR/TVAR coefficients, which leads to the Yule-Walker type of equations. With the load prediction problem addressed, we further design a DR scheduling scheme based on utility cost minimization with different customer clustering sizes. The optimal DR load profiles are given in forms of both 1-D and 2-D water-filling solutions. A tradeoff strategy, which attempts to balance the competing objectives (centralized and distributed), is also provided based on the price-of-anarchy analysis. Simulation results of both the load prediction models and the DR schemes are presented and analyzed.",sudharman jayaweera,price of anarchy (POA),2017.0,10.1109/JSYST.2014.2369451,IEEE Systems Journal,Li2017,False,,IEEE,Not available,Uncertainty Modeling and Price-Based Demand Response Scheme Design in Smart Grid,53f1ee3785bc69c7aff8eb474d03c147,https://ieeexplore.ieee.org/document/6982225/
981,"Transforming conventional passive customers into active participants who interact with the utility in real time is the key idea of demand response (DR) in smart grid. However, an effective and efficient DR scheme relies on precise prediction and modeling of the uncertainties, i.e., renewable generations and load demands. In this paper, we first present a series of linear prediction models for the load prediction purpose, such as standard autoregressive (AR) process and time-varying AR (TVAR) process, according to different assumptions on the stationarity of customer load profile: piecewise stationarity, local stationarity, and cyclostationarity. Two important issues in AR/TVAR models are addressed: determining the order of AR/TVAR models and calculating the AR/TVAR coefficients. The partial autocorrelation function is analyzed to determine the model order, and the minimum mean squared error estimator is adopted to derive the AR/TVAR coefficients, which leads to the Yule-Walker type of equations. With the load prediction problem addressed, we further design a DR scheduling scheme based on utility cost minimization with different customer clustering sizes. The optimal DR load profiles are given in forms of both 1-D and 2-D water-filling solutions. A tradeoff strategy, which attempts to balance the competing objectives (centralized and distributed), is also provided based on the price-of-anarchy analysis. Simulation results of both the load prediction models and the DR schemes are presented and analyzed.",sudharman jayaweera,time-varying autoregressive (TVAR) process,2017.0,10.1109/JSYST.2014.2369451,IEEE Systems Journal,Li2017,False,,IEEE,Not available,Uncertainty Modeling and Price-Based Demand Response Scheme Design in Smart Grid,53f1ee3785bc69c7aff8eb474d03c147,https://ieeexplore.ieee.org/document/6982225/
982,"Transforming conventional passive customers into active participants who interact with the utility in real time is the key idea of demand response (DR) in smart grid. However, an effective and efficient DR scheme relies on precise prediction and modeling of the uncertainties, i.e., renewable generations and load demands. In this paper, we first present a series of linear prediction models for the load prediction purpose, such as standard autoregressive (AR) process and time-varying AR (TVAR) process, according to different assumptions on the stationarity of customer load profile: piecewise stationarity, local stationarity, and cyclostationarity. Two important issues in AR/TVAR models are addressed: determining the order of AR/TVAR models and calculating the AR/TVAR coefficients. The partial autocorrelation function is analyzed to determine the model order, and the minimum mean squared error estimator is adopted to derive the AR/TVAR coefficients, which leads to the Yule-Walker type of equations. With the load prediction problem addressed, we further design a DR scheduling scheme based on utility cost minimization with different customer clustering sizes. The optimal DR load profiles are given in forms of both 1-D and 2-D water-filling solutions. A tradeoff strategy, which attempts to balance the competing objectives (centralized and distributed), is also provided based on the price-of-anarchy analysis. Simulation results of both the load prediction models and the DR schemes are presented and analyzed.",sudharman jayaweera,2-D water filling,2017.0,10.1109/JSYST.2014.2369451,IEEE Systems Journal,Li2017,False,,IEEE,Not available,Uncertainty Modeling and Price-Based Demand Response Scheme Design in Smart Grid,53f1ee3785bc69c7aff8eb474d03c147,https://ieeexplore.ieee.org/document/6982225/
983,"In this work, we employ stochastic queueing models to design charging fees for a network of public electric vehicle charging stations operated by a Charging Network Operator (CNO). We assume that the CNO has access to statistics of electric vehicle (EV) users' mobility patterns that determine the demand for charging stations. We model geographically distributed charging stations as a network of unobservable queues with heterogeneous operational costs due to their geographical location and variations in the locational marginal price of electricity. Individual EV users are modeled as selfish agents that minimize their own expected cost of traveling and charging. To eliminate the inefficiencies of selfish routing in the queueing network and reduce aggregate electricity costs, the CNO designs charging fees to control the equilibrium travel and charging patterns on the charging station network. We consider the socially optimal solution to this charging fee design problem and analyze its performance. We also provide bounds on the Price of Anarchy in the charging network (including congestion and electricity costs).",philip wong,Charging stations,2017.0,10.1109/ALLERTON.2017.8262816,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Wong2017,False,,IEEE,Not available,Congestion control and pricing in a network of electric vehicle public charging stations,0b957456c4a9d86277ceb5592e20db54,https://ieeexplore.ieee.org/document/8262816/
984,"In this work, we employ stochastic queueing models to design charging fees for a network of public electric vehicle charging stations operated by a Charging Network Operator (CNO). We assume that the CNO has access to statistics of electric vehicle (EV) users' mobility patterns that determine the demand for charging stations. We model geographically distributed charging stations as a network of unobservable queues with heterogeneous operational costs due to their geographical location and variations in the locational marginal price of electricity. Individual EV users are modeled as selfish agents that minimize their own expected cost of traveling and charging. To eliminate the inefficiencies of selfish routing in the queueing network and reduce aggregate electricity costs, the CNO designs charging fees to control the equilibrium travel and charging patterns on the charging station network. We consider the socially optimal solution to this charging fee design problem and analyze its performance. We also provide bounds on the Price of Anarchy in the charging network (including congestion and electricity costs).",philip wong,Roads,2017.0,10.1109/ALLERTON.2017.8262816,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Wong2017,False,,IEEE,Not available,Congestion control and pricing in a network of electric vehicle public charging stations,0b957456c4a9d86277ceb5592e20db54,https://ieeexplore.ieee.org/document/8262816/
985,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
986,"In this work, we employ stochastic queueing models to design charging fees for a network of public electric vehicle charging stations operated by a Charging Network Operator (CNO). We assume that the CNO has access to statistics of electric vehicle (EV) users' mobility patterns that determine the demand for charging stations. We model geographically distributed charging stations as a network of unobservable queues with heterogeneous operational costs due to their geographical location and variations in the locational marginal price of electricity. Individual EV users are modeled as selfish agents that minimize their own expected cost of traveling and charging. To eliminate the inefficiencies of selfish routing in the queueing network and reduce aggregate electricity costs, the CNO designs charging fees to control the equilibrium travel and charging patterns on the charging station network. We consider the socially optimal solution to this charging fee design problem and analyze its performance. We also provide bounds on the Price of Anarchy in the charging network (including congestion and electricity costs).",philip wong,Pricing,2017.0,10.1109/ALLERTON.2017.8262816,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Wong2017,False,,IEEE,Not available,Congestion control and pricing in a network of electric vehicle public charging stations,0b957456c4a9d86277ceb5592e20db54,https://ieeexplore.ieee.org/document/8262816/
987,"In this work, we employ stochastic queueing models to design charging fees for a network of public electric vehicle charging stations operated by a Charging Network Operator (CNO). We assume that the CNO has access to statistics of electric vehicle (EV) users' mobility patterns that determine the demand for charging stations. We model geographically distributed charging stations as a network of unobservable queues with heterogeneous operational costs due to their geographical location and variations in the locational marginal price of electricity. Individual EV users are modeled as selfish agents that minimize their own expected cost of traveling and charging. To eliminate the inefficiencies of selfish routing in the queueing network and reduce aggregate electricity costs, the CNO designs charging fees to control the equilibrium travel and charging patterns on the charging station network. We consider the socially optimal solution to this charging fee design problem and analyze its performance. We also provide bounds on the Price of Anarchy in the charging network (including congestion and electricity costs).",philip wong,Random variables,2017.0,10.1109/ALLERTON.2017.8262816,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Wong2017,False,,IEEE,Not available,Congestion control and pricing in a network of electric vehicle public charging stations,0b957456c4a9d86277ceb5592e20db54,https://ieeexplore.ieee.org/document/8262816/
988,"In this work, we employ stochastic queueing models to design charging fees for a network of public electric vehicle charging stations operated by a Charging Network Operator (CNO). We assume that the CNO has access to statistics of electric vehicle (EV) users' mobility patterns that determine the demand for charging stations. We model geographically distributed charging stations as a network of unobservable queues with heterogeneous operational costs due to their geographical location and variations in the locational marginal price of electricity. Individual EV users are modeled as selfish agents that minimize their own expected cost of traveling and charging. To eliminate the inefficiencies of selfish routing in the queueing network and reduce aggregate electricity costs, the CNO designs charging fees to control the equilibrium travel and charging patterns on the charging station network. We consider the socially optimal solution to this charging fee design problem and analyze its performance. We also provide bounds on the Price of Anarchy in the charging network (including congestion and electricity costs).",mahnoosh alizadeh,Charging stations,2017.0,10.1109/ALLERTON.2017.8262816,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Wong2017,False,,IEEE,Not available,Congestion control and pricing in a network of electric vehicle public charging stations,0b957456c4a9d86277ceb5592e20db54,https://ieeexplore.ieee.org/document/8262816/
989,"In this work, we employ stochastic queueing models to design charging fees for a network of public electric vehicle charging stations operated by a Charging Network Operator (CNO). We assume that the CNO has access to statistics of electric vehicle (EV) users' mobility patterns that determine the demand for charging stations. We model geographically distributed charging stations as a network of unobservable queues with heterogeneous operational costs due to their geographical location and variations in the locational marginal price of electricity. Individual EV users are modeled as selfish agents that minimize their own expected cost of traveling and charging. To eliminate the inefficiencies of selfish routing in the queueing network and reduce aggregate electricity costs, the CNO designs charging fees to control the equilibrium travel and charging patterns on the charging station network. We consider the socially optimal solution to this charging fee design problem and analyze its performance. We also provide bounds on the Price of Anarchy in the charging network (including congestion and electricity costs).",mahnoosh alizadeh,Roads,2017.0,10.1109/ALLERTON.2017.8262816,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Wong2017,False,,IEEE,Not available,Congestion control and pricing in a network of electric vehicle public charging stations,0b957456c4a9d86277ceb5592e20db54,https://ieeexplore.ieee.org/document/8262816/
990,"In this work, we employ stochastic queueing models to design charging fees for a network of public electric vehicle charging stations operated by a Charging Network Operator (CNO). We assume that the CNO has access to statistics of electric vehicle (EV) users' mobility patterns that determine the demand for charging stations. We model geographically distributed charging stations as a network of unobservable queues with heterogeneous operational costs due to their geographical location and variations in the locational marginal price of electricity. Individual EV users are modeled as selfish agents that minimize their own expected cost of traveling and charging. To eliminate the inefficiencies of selfish routing in the queueing network and reduce aggregate electricity costs, the CNO designs charging fees to control the equilibrium travel and charging patterns on the charging station network. We consider the socially optimal solution to this charging fee design problem and analyze its performance. We also provide bounds on the Price of Anarchy in the charging network (including congestion and electricity costs).",mahnoosh alizadeh,Pricing,2017.0,10.1109/ALLERTON.2017.8262816,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Wong2017,False,,IEEE,Not available,Congestion control and pricing in a network of electric vehicle public charging stations,0b957456c4a9d86277ceb5592e20db54,https://ieeexplore.ieee.org/document/8262816/
991,"In this work, we employ stochastic queueing models to design charging fees for a network of public electric vehicle charging stations operated by a Charging Network Operator (CNO). We assume that the CNO has access to statistics of electric vehicle (EV) users' mobility patterns that determine the demand for charging stations. We model geographically distributed charging stations as a network of unobservable queues with heterogeneous operational costs due to their geographical location and variations in the locational marginal price of electricity. Individual EV users are modeled as selfish agents that minimize their own expected cost of traveling and charging. To eliminate the inefficiencies of selfish routing in the queueing network and reduce aggregate electricity costs, the CNO designs charging fees to control the equilibrium travel and charging patterns on the charging station network. We consider the socially optimal solution to this charging fee design problem and analyze its performance. We also provide bounds on the Price of Anarchy in the charging network (including congestion and electricity costs).",mahnoosh alizadeh,Random variables,2017.0,10.1109/ALLERTON.2017.8262816,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Wong2017,False,,IEEE,Not available,Congestion control and pricing in a network of electric vehicle public charging stations,0b957456c4a9d86277ceb5592e20db54,https://ieeexplore.ieee.org/document/8262816/
992,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",y. xi,Pricing,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
993,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",y. xi,Routing,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
994,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",y. xi,Spread spectrum communication,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
995,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",y. xi,Relays,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
996,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
997,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",y. xi,Peer to peer computing,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
998,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",y. xi,Telecommunication traffic,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
999,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",y. xi,Cost function,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
1000,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",y. xi,Network topology,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
1001,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",y. xi,Communications Society,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
1002,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",y. xi,USA Councils,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
1003,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",e. yeh,Pricing,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
1004,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",e. yeh,Routing,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
1005,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",e. yeh,Spread spectrum communication,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
1006,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",e. yeh,Relays,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
1007,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
1008,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",e. yeh,Peer to peer computing,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
1009,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",e. yeh,Telecommunication traffic,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
1010,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",e. yeh,Cost function,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
1011,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",e. yeh,Network topology,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
1012,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",e. yeh,Communications Society,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
1013,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",e. yeh,USA Councils,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
1014,"We investigate the behavior of a large number of selfish users that are able to switch dynamically between multiple wireless access-points (possibly belonging to different standards) by introducing an iterated non-cooperative game. Users start out completely uneducated and naive but, by using a fixed set of strategies to process a broadcasted training signal, they quickly evolve and converge to an evolutionarily stable equilibrium. Then, in order to measure efficiency in this steady state, we adapt the notion of the price of anarchy to our setting and we obtain an explicit analytic estimate for it by using methods from statistical physics (namely the theory of replicas). Surprisingly, we find that the price of anarchy does not depend on the specifics of the wireless nodes (e.g., spectral efficiency) but only on the number of strategies per user and a particular combination of the number of nodes, the number of users and the size of the training signal. Finally, we map this game to the well-studied minority game, generalizing its analysis to an arbitrary number of choices.",panayotis mertikopoulos,Wireless networks,2008.0,10.1109/JSAC.2008.080913,IEEE Journal on Selected Areas in Communications,Mertikopoulos2008,False,,IEEE,Not available,Correlated Anarchy in Overlapping Wireless Networks,540321518afa99c49e61ed19b69c5f19,https://ieeexplore.ieee.org/document/4604741/
1015,"We investigate the behavior of a large number of selfish users that are able to switch dynamically between multiple wireless access-points (possibly belonging to different standards) by introducing an iterated non-cooperative game. Users start out completely uneducated and naive but, by using a fixed set of strategies to process a broadcasted training signal, they quickly evolve and converge to an evolutionarily stable equilibrium. Then, in order to measure efficiency in this steady state, we adapt the notion of the price of anarchy to our setting and we obtain an explicit analytic estimate for it by using methods from statistical physics (namely the theory of replicas). Surprisingly, we find that the price of anarchy does not depend on the specifics of the wireless nodes (e.g., spectral efficiency) but only on the number of strategies per user and a particular combination of the number of nodes, the number of users and the size of the training signal. Finally, we map this game to the well-studied minority game, generalizing its analysis to an arbitrary number of choices.",panayotis mertikopoulos,Nash equilibrium,2008.0,10.1109/JSAC.2008.080913,IEEE Journal on Selected Areas in Communications,Mertikopoulos2008,False,,IEEE,Not available,Correlated Anarchy in Overlapping Wireless Networks,540321518afa99c49e61ed19b69c5f19,https://ieeexplore.ieee.org/document/4604741/
1016,"We investigate the behavior of a large number of selfish users that are able to switch dynamically between multiple wireless access-points (possibly belonging to different standards) by introducing an iterated non-cooperative game. Users start out completely uneducated and naive but, by using a fixed set of strategies to process a broadcasted training signal, they quickly evolve and converge to an evolutionarily stable equilibrium. Then, in order to measure efficiency in this steady state, we adapt the notion of the price of anarchy to our setting and we obtain an explicit analytic estimate for it by using methods from statistical physics (namely the theory of replicas). Surprisingly, we find that the price of anarchy does not depend on the specifics of the wireless nodes (e.g., spectral efficiency) but only on the number of strategies per user and a particular combination of the number of nodes, the number of users and the size of the training signal. Finally, we map this game to the well-studied minority game, generalizing its analysis to an arbitrary number of choices.",panayotis mertikopoulos,correlated equilibrium,2008.0,10.1109/JSAC.2008.080913,IEEE Journal on Selected Areas in Communications,Mertikopoulos2008,False,,IEEE,Not available,Correlated Anarchy in Overlapping Wireless Networks,540321518afa99c49e61ed19b69c5f19,https://ieeexplore.ieee.org/document/4604741/
1017,"We investigate the behavior of a large number of selfish users that are able to switch dynamically between multiple wireless access-points (possibly belonging to different standards) by introducing an iterated non-cooperative game. Users start out completely uneducated and naive but, by using a fixed set of strategies to process a broadcasted training signal, they quickly evolve and converge to an evolutionarily stable equilibrium. Then, in order to measure efficiency in this steady state, we adapt the notion of the price of anarchy to our setting and we obtain an explicit analytic estimate for it by using methods from statistical physics (namely the theory of replicas). Surprisingly, we find that the price of anarchy does not depend on the specifics of the wireless nodes (e.g., spectral efficiency) but only on the number of strategies per user and a particular combination of the number of nodes, the number of users and the size of the training signal. Finally, we map this game to the well-studied minority game, generalizing its analysis to an arbitrary number of choices.",panayotis mertikopoulos,price of anarchy,2008.0,10.1109/JSAC.2008.080913,IEEE Journal on Selected Areas in Communications,Mertikopoulos2008,False,,IEEE,Not available,Correlated Anarchy in Overlapping Wireless Networks,540321518afa99c49e61ed19b69c5f19,https://ieeexplore.ieee.org/document/4604741/
1018,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
1019,"We investigate the behavior of a large number of selfish users that are able to switch dynamically between multiple wireless access-points (possibly belonging to different standards) by introducing an iterated non-cooperative game. Users start out completely uneducated and naive but, by using a fixed set of strategies to process a broadcasted training signal, they quickly evolve and converge to an evolutionarily stable equilibrium. Then, in order to measure efficiency in this steady state, we adapt the notion of the price of anarchy to our setting and we obtain an explicit analytic estimate for it by using methods from statistical physics (namely the theory of replicas). Surprisingly, we find that the price of anarchy does not depend on the specifics of the wireless nodes (e.g., spectral efficiency) but only on the number of strategies per user and a particular combination of the number of nodes, the number of users and the size of the training signal. Finally, we map this game to the well-studied minority game, generalizing its analysis to an arbitrary number of choices.",panayotis mertikopoulos,evolutionary games,2008.0,10.1109/JSAC.2008.080913,IEEE Journal on Selected Areas in Communications,Mertikopoulos2008,False,,IEEE,Not available,Correlated Anarchy in Overlapping Wireless Networks,540321518afa99c49e61ed19b69c5f19,https://ieeexplore.ieee.org/document/4604741/
1020,"We investigate the behavior of a large number of selfish users that are able to switch dynamically between multiple wireless access-points (possibly belonging to different standards) by introducing an iterated non-cooperative game. Users start out completely uneducated and naive but, by using a fixed set of strategies to process a broadcasted training signal, they quickly evolve and converge to an evolutionarily stable equilibrium. Then, in order to measure efficiency in this steady state, we adapt the notion of the price of anarchy to our setting and we obtain an explicit analytic estimate for it by using methods from statistical physics (namely the theory of replicas). Surprisingly, we find that the price of anarchy does not depend on the specifics of the wireless nodes (e.g., spectral efficiency) but only on the number of strategies per user and a particular combination of the number of nodes, the number of users and the size of the training signal. Finally, we map this game to the well-studied minority game, generalizing its analysis to an arbitrary number of choices.",panayotis mertikopoulos,replicas,2008.0,10.1109/JSAC.2008.080913,IEEE Journal on Selected Areas in Communications,Mertikopoulos2008,False,,IEEE,Not available,Correlated Anarchy in Overlapping Wireless Networks,540321518afa99c49e61ed19b69c5f19,https://ieeexplore.ieee.org/document/4604741/
1021,"We investigate the behavior of a large number of selfish users that are able to switch dynamically between multiple wireless access-points (possibly belonging to different standards) by introducing an iterated non-cooperative game. Users start out completely uneducated and naive but, by using a fixed set of strategies to process a broadcasted training signal, they quickly evolve and converge to an evolutionarily stable equilibrium. Then, in order to measure efficiency in this steady state, we adapt the notion of the price of anarchy to our setting and we obtain an explicit analytic estimate for it by using methods from statistical physics (namely the theory of replicas). Surprisingly, we find that the price of anarchy does not depend on the specifics of the wireless nodes (e.g., spectral efficiency) but only on the number of strategies per user and a particular combination of the number of nodes, the number of users and the size of the training signal. Finally, we map this game to the well-studied minority game, generalizing its analysis to an arbitrary number of choices.",aris moustakas,Wireless networks,2008.0,10.1109/JSAC.2008.080913,IEEE Journal on Selected Areas in Communications,Mertikopoulos2008,False,,IEEE,Not available,Correlated Anarchy in Overlapping Wireless Networks,540321518afa99c49e61ed19b69c5f19,https://ieeexplore.ieee.org/document/4604741/
1022,"We investigate the behavior of a large number of selfish users that are able to switch dynamically between multiple wireless access-points (possibly belonging to different standards) by introducing an iterated non-cooperative game. Users start out completely uneducated and naive but, by using a fixed set of strategies to process a broadcasted training signal, they quickly evolve and converge to an evolutionarily stable equilibrium. Then, in order to measure efficiency in this steady state, we adapt the notion of the price of anarchy to our setting and we obtain an explicit analytic estimate for it by using methods from statistical physics (namely the theory of replicas). Surprisingly, we find that the price of anarchy does not depend on the specifics of the wireless nodes (e.g., spectral efficiency) but only on the number of strategies per user and a particular combination of the number of nodes, the number of users and the size of the training signal. Finally, we map this game to the well-studied minority game, generalizing its analysis to an arbitrary number of choices.",aris moustakas,Nash equilibrium,2008.0,10.1109/JSAC.2008.080913,IEEE Journal on Selected Areas in Communications,Mertikopoulos2008,False,,IEEE,Not available,Correlated Anarchy in Overlapping Wireless Networks,540321518afa99c49e61ed19b69c5f19,https://ieeexplore.ieee.org/document/4604741/
1023,"We investigate the behavior of a large number of selfish users that are able to switch dynamically between multiple wireless access-points (possibly belonging to different standards) by introducing an iterated non-cooperative game. Users start out completely uneducated and naive but, by using a fixed set of strategies to process a broadcasted training signal, they quickly evolve and converge to an evolutionarily stable equilibrium. Then, in order to measure efficiency in this steady state, we adapt the notion of the price of anarchy to our setting and we obtain an explicit analytic estimate for it by using methods from statistical physics (namely the theory of replicas). Surprisingly, we find that the price of anarchy does not depend on the specifics of the wireless nodes (e.g., spectral efficiency) but only on the number of strategies per user and a particular combination of the number of nodes, the number of users and the size of the training signal. Finally, we map this game to the well-studied minority game, generalizing its analysis to an arbitrary number of choices.",aris moustakas,correlated equilibrium,2008.0,10.1109/JSAC.2008.080913,IEEE Journal on Selected Areas in Communications,Mertikopoulos2008,False,,IEEE,Not available,Correlated Anarchy in Overlapping Wireless Networks,540321518afa99c49e61ed19b69c5f19,https://ieeexplore.ieee.org/document/4604741/
1024,"We investigate the behavior of a large number of selfish users that are able to switch dynamically between multiple wireless access-points (possibly belonging to different standards) by introducing an iterated non-cooperative game. Users start out completely uneducated and naive but, by using a fixed set of strategies to process a broadcasted training signal, they quickly evolve and converge to an evolutionarily stable equilibrium. Then, in order to measure efficiency in this steady state, we adapt the notion of the price of anarchy to our setting and we obtain an explicit analytic estimate for it by using methods from statistical physics (namely the theory of replicas). Surprisingly, we find that the price of anarchy does not depend on the specifics of the wireless nodes (e.g., spectral efficiency) but only on the number of strategies per user and a particular combination of the number of nodes, the number of users and the size of the training signal. Finally, we map this game to the well-studied minority game, generalizing its analysis to an arbitrary number of choices.",aris moustakas,price of anarchy,2008.0,10.1109/JSAC.2008.080913,IEEE Journal on Selected Areas in Communications,Mertikopoulos2008,False,,IEEE,Not available,Correlated Anarchy in Overlapping Wireless Networks,540321518afa99c49e61ed19b69c5f19,https://ieeexplore.ieee.org/document/4604741/
1025,"We investigate the behavior of a large number of selfish users that are able to switch dynamically between multiple wireless access-points (possibly belonging to different standards) by introducing an iterated non-cooperative game. Users start out completely uneducated and naive but, by using a fixed set of strategies to process a broadcasted training signal, they quickly evolve and converge to an evolutionarily stable equilibrium. Then, in order to measure efficiency in this steady state, we adapt the notion of the price of anarchy to our setting and we obtain an explicit analytic estimate for it by using methods from statistical physics (namely the theory of replicas). Surprisingly, we find that the price of anarchy does not depend on the specifics of the wireless nodes (e.g., spectral efficiency) but only on the number of strategies per user and a particular combination of the number of nodes, the number of users and the size of the training signal. Finally, we map this game to the well-studied minority game, generalizing its analysis to an arbitrary number of choices.",aris moustakas,evolutionary games,2008.0,10.1109/JSAC.2008.080913,IEEE Journal on Selected Areas in Communications,Mertikopoulos2008,False,,IEEE,Not available,Correlated Anarchy in Overlapping Wireless Networks,540321518afa99c49e61ed19b69c5f19,https://ieeexplore.ieee.org/document/4604741/
1026,"We investigate the behavior of a large number of selfish users that are able to switch dynamically between multiple wireless access-points (possibly belonging to different standards) by introducing an iterated non-cooperative game. Users start out completely uneducated and naive but, by using a fixed set of strategies to process a broadcasted training signal, they quickly evolve and converge to an evolutionarily stable equilibrium. Then, in order to measure efficiency in this steady state, we adapt the notion of the price of anarchy to our setting and we obtain an explicit analytic estimate for it by using methods from statistical physics (namely the theory of replicas). Surprisingly, we find that the price of anarchy does not depend on the specifics of the wireless nodes (e.g., spectral efficiency) but only on the number of strategies per user and a particular combination of the number of nodes, the number of users and the size of the training signal. Finally, we map this game to the well-studied minority game, generalizing its analysis to an arbitrary number of choices.",aris moustakas,replicas,2008.0,10.1109/JSAC.2008.080913,IEEE Journal on Selected Areas in Communications,Mertikopoulos2008,False,,IEEE,Not available,Correlated Anarchy in Overlapping Wireless Networks,540321518afa99c49e61ed19b69c5f19,https://ieeexplore.ieee.org/document/4604741/
1027,"Many studies on Internet Service Provider (ISP) interconnection make simplifying assumptions on the implementation of the service provision. Our work explicitly models the ISP service that is provided to users that run peer-to-peer applications and it analyses the behavior of competing ISPs. The ISPs have agreed to peer each other and each ISP has purchased transit service from one Internet Backbone Provider. The quality of service, the equilibrium prices and the market shares that the competition game yields are computed by means of our model. Our work assesses the strategy of an ISP which provisions its transit link against a competing ISP in terms of competitive advantage and social welfare. And it assesses the effect of the entrance of more competing ISPs.",luis guijarro,Competition,2011.0,10.1109/CCNC.2011.5766356,2011 IEEE Consumer Communications and Networking Conference (CCNC),Guijarro2011,False,,IEEE,Not available,Analysis of price competition under peering and transit agreements in Internet Service provision to peer-to-peer users,b3e4f9b865e8f395bd4d0ae371eb9ca8,https://ieeexplore.ieee.org/document/5766356/
1028,"Many studies on Internet Service Provider (ISP) interconnection make simplifying assumptions on the implementation of the service provision. Our work explicitly models the ISP service that is provided to users that run peer-to-peer applications and it analyses the behavior of competing ISPs. The ISPs have agreed to peer each other and each ISP has purchased transit service from one Internet Backbone Provider. The quality of service, the equilibrium prices and the market shares that the competition game yields are computed by means of our model. Our work assesses the strategy of an ISP which provisions its transit link against a competing ISP in terms of competitive advantage and social welfare. And it assesses the effect of the entrance of more competing ISPs.",luis guijarro,game theory,2011.0,10.1109/CCNC.2011.5766356,2011 IEEE Consumer Communications and Networking Conference (CCNC),Guijarro2011,False,,IEEE,Not available,Analysis of price competition under peering and transit agreements in Internet Service provision to peer-to-peer users,b3e4f9b865e8f395bd4d0ae371eb9ca8,https://ieeexplore.ieee.org/document/5766356/
1029,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
1030,"Many studies on Internet Service Provider (ISP) interconnection make simplifying assumptions on the implementation of the service provision. Our work explicitly models the ISP service that is provided to users that run peer-to-peer applications and it analyses the behavior of competing ISPs. The ISPs have agreed to peer each other and each ISP has purchased transit service from one Internet Backbone Provider. The quality of service, the equilibrium prices and the market shares that the competition game yields are computed by means of our model. Our work assesses the strategy of an ISP which provisions its transit link against a competing ISP in terms of competitive advantage and social welfare. And it assesses the effect of the entrance of more competing ISPs.",luis guijarro,peering agreement,2011.0,10.1109/CCNC.2011.5766356,2011 IEEE Consumer Communications and Networking Conference (CCNC),Guijarro2011,False,,IEEE,Not available,Analysis of price competition under peering and transit agreements in Internet Service provision to peer-to-peer users,b3e4f9b865e8f395bd4d0ae371eb9ca8,https://ieeexplore.ieee.org/document/5766356/
1031,"Many studies on Internet Service Provider (ISP) interconnection make simplifying assumptions on the implementation of the service provision. Our work explicitly models the ISP service that is provided to users that run peer-to-peer applications and it analyses the behavior of competing ISPs. The ISPs have agreed to peer each other and each ISP has purchased transit service from one Internet Backbone Provider. The quality of service, the equilibrium prices and the market shares that the competition game yields are computed by means of our model. Our work assesses the strategy of an ISP which provisions its transit link against a competing ISP in terms of competitive advantage and social welfare. And it assesses the effect of the entrance of more competing ISPs.",luis guijarro,peer-to-peer,2011.0,10.1109/CCNC.2011.5766356,2011 IEEE Consumer Communications and Networking Conference (CCNC),Guijarro2011,False,,IEEE,Not available,Analysis of price competition under peering and transit agreements in Internet Service provision to peer-to-peer users,b3e4f9b865e8f395bd4d0ae371eb9ca8,https://ieeexplore.ieee.org/document/5766356/
1032,"Many studies on Internet Service Provider (ISP) interconnection make simplifying assumptions on the implementation of the service provision. Our work explicitly models the ISP service that is provided to users that run peer-to-peer applications and it analyses the behavior of competing ISPs. The ISPs have agreed to peer each other and each ISP has purchased transit service from one Internet Backbone Provider. The quality of service, the equilibrium prices and the market shares that the competition game yields are computed by means of our model. Our work assesses the strategy of an ISP which provisions its transit link against a competing ISP in terms of competitive advantage and social welfare. And it assesses the effect of the entrance of more competing ISPs.",luis guijarro,price of anarchy,2011.0,10.1109/CCNC.2011.5766356,2011 IEEE Consumer Communications and Networking Conference (CCNC),Guijarro2011,False,,IEEE,Not available,Analysis of price competition under peering and transit agreements in Internet Service provision to peer-to-peer users,b3e4f9b865e8f395bd4d0ae371eb9ca8,https://ieeexplore.ieee.org/document/5766356/
1033,"Many studies on Internet Service Provider (ISP) interconnection make simplifying assumptions on the implementation of the service provision. Our work explicitly models the ISP service that is provided to users that run peer-to-peer applications and it analyses the behavior of competing ISPs. The ISPs have agreed to peer each other and each ISP has purchased transit service from one Internet Backbone Provider. The quality of service, the equilibrium prices and the market shares that the competition game yields are computed by means of our model. Our work assesses the strategy of an ISP which provisions its transit link against a competing ISP in terms of competitive advantage and social welfare. And it assesses the effect of the entrance of more competing ISPs.",luis guijarro,quality of service,2011.0,10.1109/CCNC.2011.5766356,2011 IEEE Consumer Communications and Networking Conference (CCNC),Guijarro2011,False,,IEEE,Not available,Analysis of price competition under peering and transit agreements in Internet Service provision to peer-to-peer users,b3e4f9b865e8f395bd4d0ae371eb9ca8,https://ieeexplore.ieee.org/document/5766356/
1034,"Many studies on Internet Service Provider (ISP) interconnection make simplifying assumptions on the implementation of the service provision. Our work explicitly models the ISP service that is provided to users that run peer-to-peer applications and it analyses the behavior of competing ISPs. The ISPs have agreed to peer each other and each ISP has purchased transit service from one Internet Backbone Provider. The quality of service, the equilibrium prices and the market shares that the competition game yields are computed by means of our model. Our work assesses the strategy of an ISP which provisions its transit link against a competing ISP in terms of competitive advantage and social welfare. And it assesses the effect of the entrance of more competing ISPs.",vicent pla,Competition,2011.0,10.1109/CCNC.2011.5766356,2011 IEEE Consumer Communications and Networking Conference (CCNC),Guijarro2011,False,,IEEE,Not available,Analysis of price competition under peering and transit agreements in Internet Service provision to peer-to-peer users,b3e4f9b865e8f395bd4d0ae371eb9ca8,https://ieeexplore.ieee.org/document/5766356/
1035,"Many studies on Internet Service Provider (ISP) interconnection make simplifying assumptions on the implementation of the service provision. Our work explicitly models the ISP service that is provided to users that run peer-to-peer applications and it analyses the behavior of competing ISPs. The ISPs have agreed to peer each other and each ISP has purchased transit service from one Internet Backbone Provider. The quality of service, the equilibrium prices and the market shares that the competition game yields are computed by means of our model. Our work assesses the strategy of an ISP which provisions its transit link against a competing ISP in terms of competitive advantage and social welfare. And it assesses the effect of the entrance of more competing ISPs.",vicent pla,game theory,2011.0,10.1109/CCNC.2011.5766356,2011 IEEE Consumer Communications and Networking Conference (CCNC),Guijarro2011,False,,IEEE,Not available,Analysis of price competition under peering and transit agreements in Internet Service provision to peer-to-peer users,b3e4f9b865e8f395bd4d0ae371eb9ca8,https://ieeexplore.ieee.org/document/5766356/
1036,"Many studies on Internet Service Provider (ISP) interconnection make simplifying assumptions on the implementation of the service provision. Our work explicitly models the ISP service that is provided to users that run peer-to-peer applications and it analyses the behavior of competing ISPs. The ISPs have agreed to peer each other and each ISP has purchased transit service from one Internet Backbone Provider. The quality of service, the equilibrium prices and the market shares that the competition game yields are computed by means of our model. Our work assesses the strategy of an ISP which provisions its transit link against a competing ISP in terms of competitive advantage and social welfare. And it assesses the effect of the entrance of more competing ISPs.",vicent pla,peering agreement,2011.0,10.1109/CCNC.2011.5766356,2011 IEEE Consumer Communications and Networking Conference (CCNC),Guijarro2011,False,,IEEE,Not available,Analysis of price competition under peering and transit agreements in Internet Service provision to peer-to-peer users,b3e4f9b865e8f395bd4d0ae371eb9ca8,https://ieeexplore.ieee.org/document/5766356/
1037,"Many studies on Internet Service Provider (ISP) interconnection make simplifying assumptions on the implementation of the service provision. Our work explicitly models the ISP service that is provided to users that run peer-to-peer applications and it analyses the behavior of competing ISPs. The ISPs have agreed to peer each other and each ISP has purchased transit service from one Internet Backbone Provider. The quality of service, the equilibrium prices and the market shares that the competition game yields are computed by means of our model. Our work assesses the strategy of an ISP which provisions its transit link against a competing ISP in terms of competitive advantage and social welfare. And it assesses the effect of the entrance of more competing ISPs.",vicent pla,peer-to-peer,2011.0,10.1109/CCNC.2011.5766356,2011 IEEE Consumer Communications and Networking Conference (CCNC),Guijarro2011,False,,IEEE,Not available,Analysis of price competition under peering and transit agreements in Internet Service provision to peer-to-peer users,b3e4f9b865e8f395bd4d0ae371eb9ca8,https://ieeexplore.ieee.org/document/5766356/
1038,"Many studies on Internet Service Provider (ISP) interconnection make simplifying assumptions on the implementation of the service provision. Our work explicitly models the ISP service that is provided to users that run peer-to-peer applications and it analyses the behavior of competing ISPs. The ISPs have agreed to peer each other and each ISP has purchased transit service from one Internet Backbone Provider. The quality of service, the equilibrium prices and the market shares that the competition game yields are computed by means of our model. Our work assesses the strategy of an ISP which provisions its transit link against a competing ISP in terms of competitive advantage and social welfare. And it assesses the effect of the entrance of more competing ISPs.",vicent pla,price of anarchy,2011.0,10.1109/CCNC.2011.5766356,2011 IEEE Consumer Communications and Networking Conference (CCNC),Guijarro2011,False,,IEEE,Not available,Analysis of price competition under peering and transit agreements in Internet Service provision to peer-to-peer users,b3e4f9b865e8f395bd4d0ae371eb9ca8,https://ieeexplore.ieee.org/document/5766356/
1039,"Many studies on Internet Service Provider (ISP) interconnection make simplifying assumptions on the implementation of the service provision. Our work explicitly models the ISP service that is provided to users that run peer-to-peer applications and it analyses the behavior of competing ISPs. The ISPs have agreed to peer each other and each ISP has purchased transit service from one Internet Backbone Provider. The quality of service, the equilibrium prices and the market shares that the competition game yields are computed by means of our model. Our work assesses the strategy of an ISP which provisions its transit link against a competing ISP in terms of competitive advantage and social welfare. And it assesses the effect of the entrance of more competing ISPs.",vicent pla,quality of service,2011.0,10.1109/CCNC.2011.5766356,2011 IEEE Consumer Communications and Networking Conference (CCNC),Guijarro2011,False,,IEEE,Not available,Analysis of price competition under peering and transit agreements in Internet Service provision to peer-to-peer users,b3e4f9b865e8f395bd4d0ae371eb9ca8,https://ieeexplore.ieee.org/document/5766356/
1040,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
1041,"Many studies on Internet Service Provider (ISP) interconnection make simplifying assumptions on the implementation of the service provision. Our work explicitly models the ISP service that is provided to users that run peer-to-peer applications and it analyses the behavior of competing ISPs. The ISPs have agreed to peer each other and each ISP has purchased transit service from one Internet Backbone Provider. The quality of service, the equilibrium prices and the market shares that the competition game yields are computed by means of our model. Our work assesses the strategy of an ISP which provisions its transit link against a competing ISP in terms of competitive advantage and social welfare. And it assesses the effect of the entrance of more competing ISPs.",jose vidal,Competition,2011.0,10.1109/CCNC.2011.5766356,2011 IEEE Consumer Communications and Networking Conference (CCNC),Guijarro2011,False,,IEEE,Not available,Analysis of price competition under peering and transit agreements in Internet Service provision to peer-to-peer users,b3e4f9b865e8f395bd4d0ae371eb9ca8,https://ieeexplore.ieee.org/document/5766356/
1042,"Many studies on Internet Service Provider (ISP) interconnection make simplifying assumptions on the implementation of the service provision. Our work explicitly models the ISP service that is provided to users that run peer-to-peer applications and it analyses the behavior of competing ISPs. The ISPs have agreed to peer each other and each ISP has purchased transit service from one Internet Backbone Provider. The quality of service, the equilibrium prices and the market shares that the competition game yields are computed by means of our model. Our work assesses the strategy of an ISP which provisions its transit link against a competing ISP in terms of competitive advantage and social welfare. And it assesses the effect of the entrance of more competing ISPs.",jose vidal,game theory,2011.0,10.1109/CCNC.2011.5766356,2011 IEEE Consumer Communications and Networking Conference (CCNC),Guijarro2011,False,,IEEE,Not available,Analysis of price competition under peering and transit agreements in Internet Service provision to peer-to-peer users,b3e4f9b865e8f395bd4d0ae371eb9ca8,https://ieeexplore.ieee.org/document/5766356/
1043,"Many studies on Internet Service Provider (ISP) interconnection make simplifying assumptions on the implementation of the service provision. Our work explicitly models the ISP service that is provided to users that run peer-to-peer applications and it analyses the behavior of competing ISPs. The ISPs have agreed to peer each other and each ISP has purchased transit service from one Internet Backbone Provider. The quality of service, the equilibrium prices and the market shares that the competition game yields are computed by means of our model. Our work assesses the strategy of an ISP which provisions its transit link against a competing ISP in terms of competitive advantage and social welfare. And it assesses the effect of the entrance of more competing ISPs.",jose vidal,peering agreement,2011.0,10.1109/CCNC.2011.5766356,2011 IEEE Consumer Communications and Networking Conference (CCNC),Guijarro2011,False,,IEEE,Not available,Analysis of price competition under peering and transit agreements in Internet Service provision to peer-to-peer users,b3e4f9b865e8f395bd4d0ae371eb9ca8,https://ieeexplore.ieee.org/document/5766356/
1044,"Many studies on Internet Service Provider (ISP) interconnection make simplifying assumptions on the implementation of the service provision. Our work explicitly models the ISP service that is provided to users that run peer-to-peer applications and it analyses the behavior of competing ISPs. The ISPs have agreed to peer each other and each ISP has purchased transit service from one Internet Backbone Provider. The quality of service, the equilibrium prices and the market shares that the competition game yields are computed by means of our model. Our work assesses the strategy of an ISP which provisions its transit link against a competing ISP in terms of competitive advantage and social welfare. And it assesses the effect of the entrance of more competing ISPs.",jose vidal,peer-to-peer,2011.0,10.1109/CCNC.2011.5766356,2011 IEEE Consumer Communications and Networking Conference (CCNC),Guijarro2011,False,,IEEE,Not available,Analysis of price competition under peering and transit agreements in Internet Service provision to peer-to-peer users,b3e4f9b865e8f395bd4d0ae371eb9ca8,https://ieeexplore.ieee.org/document/5766356/
1045,"Many studies on Internet Service Provider (ISP) interconnection make simplifying assumptions on the implementation of the service provision. Our work explicitly models the ISP service that is provided to users that run peer-to-peer applications and it analyses the behavior of competing ISPs. The ISPs have agreed to peer each other and each ISP has purchased transit service from one Internet Backbone Provider. The quality of service, the equilibrium prices and the market shares that the competition game yields are computed by means of our model. Our work assesses the strategy of an ISP which provisions its transit link against a competing ISP in terms of competitive advantage and social welfare. And it assesses the effect of the entrance of more competing ISPs.",jose vidal,price of anarchy,2011.0,10.1109/CCNC.2011.5766356,2011 IEEE Consumer Communications and Networking Conference (CCNC),Guijarro2011,False,,IEEE,Not available,Analysis of price competition under peering and transit agreements in Internet Service provision to peer-to-peer users,b3e4f9b865e8f395bd4d0ae371eb9ca8,https://ieeexplore.ieee.org/document/5766356/
1046,"Many studies on Internet Service Provider (ISP) interconnection make simplifying assumptions on the implementation of the service provision. Our work explicitly models the ISP service that is provided to users that run peer-to-peer applications and it analyses the behavior of competing ISPs. The ISPs have agreed to peer each other and each ISP has purchased transit service from one Internet Backbone Provider. The quality of service, the equilibrium prices and the market shares that the competition game yields are computed by means of our model. Our work assesses the strategy of an ISP which provisions its transit link against a competing ISP in terms of competitive advantage and social welfare. And it assesses the effect of the entrance of more competing ISPs.",jose vidal,quality of service,2011.0,10.1109/CCNC.2011.5766356,2011 IEEE Consumer Communications and Networking Conference (CCNC),Guijarro2011,False,,IEEE,Not available,Analysis of price competition under peering and transit agreements in Internet Service provision to peer-to-peer users,b3e4f9b865e8f395bd4d0ae371eb9ca8,https://ieeexplore.ieee.org/document/5766356/
1047,"Many studies on Internet Service Provider (ISP) interconnection make simplifying assumptions on the implementation of the service provision. Our work explicitly models the ISP service that is provided to users that run peer-to-peer applications and it analyses the behavior of competing ISPs. The ISPs have agreed to peer each other and each ISP has purchased transit service from one Internet Backbone Provider. The quality of service, the equilibrium prices and the market shares that the competition game yields are computed by means of our model. Our work assesses the strategy of an ISP which provisions its transit link against a competing ISP in terms of competitive advantage and social welfare. And it assesses the effect of the entrance of more competing ISPs.",jorge martinez-bauset,Competition,2011.0,10.1109/CCNC.2011.5766356,2011 IEEE Consumer Communications and Networking Conference (CCNC),Guijarro2011,False,,IEEE,Not available,Analysis of price competition under peering and transit agreements in Internet Service provision to peer-to-peer users,b3e4f9b865e8f395bd4d0ae371eb9ca8,https://ieeexplore.ieee.org/document/5766356/
1048,"Many studies on Internet Service Provider (ISP) interconnection make simplifying assumptions on the implementation of the service provision. Our work explicitly models the ISP service that is provided to users that run peer-to-peer applications and it analyses the behavior of competing ISPs. The ISPs have agreed to peer each other and each ISP has purchased transit service from one Internet Backbone Provider. The quality of service, the equilibrium prices and the market shares that the competition game yields are computed by means of our model. Our work assesses the strategy of an ISP which provisions its transit link against a competing ISP in terms of competitive advantage and social welfare. And it assesses the effect of the entrance of more competing ISPs.",jorge martinez-bauset,game theory,2011.0,10.1109/CCNC.2011.5766356,2011 IEEE Consumer Communications and Networking Conference (CCNC),Guijarro2011,False,,IEEE,Not available,Analysis of price competition under peering and transit agreements in Internet Service provision to peer-to-peer users,b3e4f9b865e8f395bd4d0ae371eb9ca8,https://ieeexplore.ieee.org/document/5766356/
1049,"Many studies on Internet Service Provider (ISP) interconnection make simplifying assumptions on the implementation of the service provision. Our work explicitly models the ISP service that is provided to users that run peer-to-peer applications and it analyses the behavior of competing ISPs. The ISPs have agreed to peer each other and each ISP has purchased transit service from one Internet Backbone Provider. The quality of service, the equilibrium prices and the market shares that the competition game yields are computed by means of our model. Our work assesses the strategy of an ISP which provisions its transit link against a competing ISP in terms of competitive advantage and social welfare. And it assesses the effect of the entrance of more competing ISPs.",jorge martinez-bauset,peering agreement,2011.0,10.1109/CCNC.2011.5766356,2011 IEEE Consumer Communications and Networking Conference (CCNC),Guijarro2011,False,,IEEE,Not available,Analysis of price competition under peering and transit agreements in Internet Service provision to peer-to-peer users,b3e4f9b865e8f395bd4d0ae371eb9ca8,https://ieeexplore.ieee.org/document/5766356/
1050,"Many studies on Internet Service Provider (ISP) interconnection make simplifying assumptions on the implementation of the service provision. Our work explicitly models the ISP service that is provided to users that run peer-to-peer applications and it analyses the behavior of competing ISPs. The ISPs have agreed to peer each other and each ISP has purchased transit service from one Internet Backbone Provider. The quality of service, the equilibrium prices and the market shares that the competition game yields are computed by means of our model. Our work assesses the strategy of an ISP which provisions its transit link against a competing ISP in terms of competitive advantage and social welfare. And it assesses the effect of the entrance of more competing ISPs.",jorge martinez-bauset,peer-to-peer,2011.0,10.1109/CCNC.2011.5766356,2011 IEEE Consumer Communications and Networking Conference (CCNC),Guijarro2011,False,,IEEE,Not available,Analysis of price competition under peering and transit agreements in Internet Service provision to peer-to-peer users,b3e4f9b865e8f395bd4d0ae371eb9ca8,https://ieeexplore.ieee.org/document/5766356/
1051,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
1052,"Many studies on Internet Service Provider (ISP) interconnection make simplifying assumptions on the implementation of the service provision. Our work explicitly models the ISP service that is provided to users that run peer-to-peer applications and it analyses the behavior of competing ISPs. The ISPs have agreed to peer each other and each ISP has purchased transit service from one Internet Backbone Provider. The quality of service, the equilibrium prices and the market shares that the competition game yields are computed by means of our model. Our work assesses the strategy of an ISP which provisions its transit link against a competing ISP in terms of competitive advantage and social welfare. And it assesses the effect of the entrance of more competing ISPs.",jorge martinez-bauset,price of anarchy,2011.0,10.1109/CCNC.2011.5766356,2011 IEEE Consumer Communications and Networking Conference (CCNC),Guijarro2011,False,,IEEE,Not available,Analysis of price competition under peering and transit agreements in Internet Service provision to peer-to-peer users,b3e4f9b865e8f395bd4d0ae371eb9ca8,https://ieeexplore.ieee.org/document/5766356/
1053,"Many studies on Internet Service Provider (ISP) interconnection make simplifying assumptions on the implementation of the service provision. Our work explicitly models the ISP service that is provided to users that run peer-to-peer applications and it analyses the behavior of competing ISPs. The ISPs have agreed to peer each other and each ISP has purchased transit service from one Internet Backbone Provider. The quality of service, the equilibrium prices and the market shares that the competition game yields are computed by means of our model. Our work assesses the strategy of an ISP which provisions its transit link against a competing ISP in terms of competitive advantage and social welfare. And it assesses the effect of the entrance of more competing ISPs.",jorge martinez-bauset,quality of service,2011.0,10.1109/CCNC.2011.5766356,2011 IEEE Consumer Communications and Networking Conference (CCNC),Guijarro2011,False,,IEEE,Not available,Analysis of price competition under peering and transit agreements in Internet Service provision to peer-to-peer users,b3e4f9b865e8f395bd4d0ae371eb9ca8,https://ieeexplore.ieee.org/document/5766356/
1054,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Pricing,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
1055,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Routing,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
1056,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Spread spectrum communication,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
1057,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Relays,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
1058,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Telecommunication traffic,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
1059,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Oligopoly,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
1060,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Network topology,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
1061,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Costs,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
1062,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
1063,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Conferences,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
1064,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Computer networks,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
1065,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Pricing,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
1066,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Routing,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
1067,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Spread spectrum communication,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
1068,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Relays,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
1069,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Telecommunication traffic,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
1070,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Oligopoly,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
1071,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Network topology,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
1072,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Costs,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
1073,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
1074,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
1075,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Conferences,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
1076,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Computer networks,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
1077,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",paulin jacquot,Smart Grids,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
1078,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",paulin jacquot,Demand Response,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
1079,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",paulin jacquot,Dynamic Pricing,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
1080,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",paulin jacquot,Game Theory,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
1081,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",paulin jacquot,Equilibrium,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
1082,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",paulin jacquot,Price of Anarchy,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
1083,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",paulin jacquot,Fairness,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
1084,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",olivier beaude,Smart Grids,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
1085,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
1086,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",olivier beaude,Demand Response,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
1087,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",olivier beaude,Dynamic Pricing,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
1088,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",olivier beaude,Game Theory,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
1089,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",olivier beaude,Equilibrium,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
1090,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",olivier beaude,Price of Anarchy,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
1091,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",olivier beaude,Fairness,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
1092,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",stephane gaubert,Smart Grids,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
1093,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",stephane gaubert,Demand Response,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
1094,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",stephane gaubert,Dynamic Pricing,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
1095,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",stephane gaubert,Game Theory,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
1096,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
1097,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",stephane gaubert,Equilibrium,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
1098,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",stephane gaubert,Price of Anarchy,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
1099,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",stephane gaubert,Fairness,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
1100,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",nadia oudjane,Smart Grids,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
1101,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",nadia oudjane,Demand Response,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
1102,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",nadia oudjane,Dynamic Pricing,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
1103,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",nadia oudjane,Game Theory,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
1104,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",nadia oudjane,Equilibrium,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
1105,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",nadia oudjane,Price of Anarchy,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
1106,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",nadia oudjane,Fairness,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
1107,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
1108,"Investments in security technologies by strategic users is typically modeled as a public good problem, known as the Interdependent Security (IDS) game. The equilibria for such games are often inefficient, as selfish users free-ride on positive externalities of others' contributions. We present a mechanism that implements the socially optimal equilibrium in an IDS game through a message exchange process; this mechanism does not need to monitor or audit users. However, it does not necessarily guarantee voluntary participation, often a trivial condition to satisfy in many resource allocation problems, but made much harder due to the incentive to stay out and free-ride on others' investments. We discuss the role of cyber insurance in this setting.",parinaz naghizadeh,Security,2014.0,10.1109/ITA.2014.6804216,2014 Information Theory and Applications Workshop (ITA),Naghizadeh2014,False,,IEEE,Not available,Closing the price of anarchy gap in the interdependent security game,92d4d6c85c3bf830b63aad30635033a7,https://ieeexplore.ieee.org/document/6804216/
1109,"Investments in security technologies by strategic users is typically modeled as a public good problem, known as the Interdependent Security (IDS) game. The equilibria for such games are often inefficient, as selfish users free-ride on positive externalities of others' contributions. We present a mechanism that implements the socially optimal equilibrium in an IDS game through a message exchange process; this mechanism does not need to monitor or audit users. However, it does not necessarily guarantee voluntary participation, often a trivial condition to satisfy in many resource allocation problems, but made much harder due to the incentive to stay out and free-ride on others' investments. We discuss the role of cyber insurance in this setting.",parinaz naghizadeh,Investment,2014.0,10.1109/ITA.2014.6804216,2014 Information Theory and Applications Workshop (ITA),Naghizadeh2014,False,,IEEE,Not available,Closing the price of anarchy gap in the interdependent security game,92d4d6c85c3bf830b63aad30635033a7,https://ieeexplore.ieee.org/document/6804216/
1110,"Investments in security technologies by strategic users is typically modeled as a public good problem, known as the Interdependent Security (IDS) game. The equilibria for such games are often inefficient, as selfish users free-ride on positive externalities of others' contributions. We present a mechanism that implements the socially optimal equilibrium in an IDS game through a message exchange process; this mechanism does not need to monitor or audit users. However, it does not necessarily guarantee voluntary participation, often a trivial condition to satisfy in many resource allocation problems, but made much harder due to the incentive to stay out and free-ride on others' investments. We discuss the role of cyber insurance in this setting.",parinaz naghizadeh,Games,2014.0,10.1109/ITA.2014.6804216,2014 Information Theory and Applications Workshop (ITA),Naghizadeh2014,False,,IEEE,Not available,Closing the price of anarchy gap in the interdependent security game,92d4d6c85c3bf830b63aad30635033a7,https://ieeexplore.ieee.org/document/6804216/
1111,"Investments in security technologies by strategic users is typically modeled as a public good problem, known as the Interdependent Security (IDS) game. The equilibria for such games are often inefficient, as selfish users free-ride on positive externalities of others' contributions. We present a mechanism that implements the socially optimal equilibrium in an IDS game through a message exchange process; this mechanism does not need to monitor or audit users. However, it does not necessarily guarantee voluntary participation, often a trivial condition to satisfy in many resource allocation problems, but made much harder due to the incentive to stay out and free-ride on others' investments. We discuss the role of cyber insurance in this setting.",parinaz naghizadeh,Nash equilibrium,2014.0,10.1109/ITA.2014.6804216,2014 Information Theory and Applications Workshop (ITA),Naghizadeh2014,False,,IEEE,Not available,Closing the price of anarchy gap in the interdependent security game,92d4d6c85c3bf830b63aad30635033a7,https://ieeexplore.ieee.org/document/6804216/
1112,"Investments in security technologies by strategic users is typically modeled as a public good problem, known as the Interdependent Security (IDS) game. The equilibria for such games are often inefficient, as selfish users free-ride on positive externalities of others' contributions. We present a mechanism that implements the socially optimal equilibrium in an IDS game through a message exchange process; this mechanism does not need to monitor or audit users. However, it does not necessarily guarantee voluntary participation, often a trivial condition to satisfy in many resource allocation problems, but made much harder due to the incentive to stay out and free-ride on others' investments. We discuss the role of cyber insurance in this setting.",parinaz naghizadeh,Vectors,2014.0,10.1109/ITA.2014.6804216,2014 Information Theory and Applications Workshop (ITA),Naghizadeh2014,False,,IEEE,Not available,Closing the price of anarchy gap in the interdependent security game,92d4d6c85c3bf830b63aad30635033a7,https://ieeexplore.ieee.org/document/6804216/
1113,"Investments in security technologies by strategic users is typically modeled as a public good problem, known as the Interdependent Security (IDS) game. The equilibria for such games are often inefficient, as selfish users free-ride on positive externalities of others' contributions. We present a mechanism that implements the socially optimal equilibrium in an IDS game through a message exchange process; this mechanism does not need to monitor or audit users. However, it does not necessarily guarantee voluntary participation, often a trivial condition to satisfy in many resource allocation problems, but made much harder due to the incentive to stay out and free-ride on others' investments. We discuss the role of cyber insurance in this setting.",parinaz naghizadeh,Proposals,2014.0,10.1109/ITA.2014.6804216,2014 Information Theory and Applications Workshop (ITA),Naghizadeh2014,False,,IEEE,Not available,Closing the price of anarchy gap in the interdependent security game,92d4d6c85c3bf830b63aad30635033a7,https://ieeexplore.ieee.org/document/6804216/
1114,"Investments in security technologies by strategic users is typically modeled as a public good problem, known as the Interdependent Security (IDS) game. The equilibria for such games are often inefficient, as selfish users free-ride on positive externalities of others' contributions. We present a mechanism that implements the socially optimal equilibrium in an IDS game through a message exchange process; this mechanism does not need to monitor or audit users. However, it does not necessarily guarantee voluntary participation, often a trivial condition to satisfy in many resource allocation problems, but made much harder due to the incentive to stay out and free-ride on others' investments. We discuss the role of cyber insurance in this setting.",parinaz naghizadeh,Monitoring,2014.0,10.1109/ITA.2014.6804216,2014 Information Theory and Applications Workshop (ITA),Naghizadeh2014,False,,IEEE,Not available,Closing the price of anarchy gap in the interdependent security game,92d4d6c85c3bf830b63aad30635033a7,https://ieeexplore.ieee.org/document/6804216/
1115,"Investments in security technologies by strategic users is typically modeled as a public good problem, known as the Interdependent Security (IDS) game. The equilibria for such games are often inefficient, as selfish users free-ride on positive externalities of others' contributions. We present a mechanism that implements the socially optimal equilibrium in an IDS game through a message exchange process; this mechanism does not need to monitor or audit users. However, it does not necessarily guarantee voluntary participation, often a trivial condition to satisfy in many resource allocation problems, but made much harder due to the incentive to stay out and free-ride on others' investments. We discuss the role of cyber insurance in this setting.",mingyan liu,Security,2014.0,10.1109/ITA.2014.6804216,2014 Information Theory and Applications Workshop (ITA),Naghizadeh2014,False,,IEEE,Not available,Closing the price of anarchy gap in the interdependent security game,92d4d6c85c3bf830b63aad30635033a7,https://ieeexplore.ieee.org/document/6804216/
1116,"Investments in security technologies by strategic users is typically modeled as a public good problem, known as the Interdependent Security (IDS) game. The equilibria for such games are often inefficient, as selfish users free-ride on positive externalities of others' contributions. We present a mechanism that implements the socially optimal equilibrium in an IDS game through a message exchange process; this mechanism does not need to monitor or audit users. However, it does not necessarily guarantee voluntary participation, often a trivial condition to satisfy in many resource allocation problems, but made much harder due to the incentive to stay out and free-ride on others' investments. We discuss the role of cyber insurance in this setting.",mingyan liu,Investment,2014.0,10.1109/ITA.2014.6804216,2014 Information Theory and Applications Workshop (ITA),Naghizadeh2014,False,,IEEE,Not available,Closing the price of anarchy gap in the interdependent security game,92d4d6c85c3bf830b63aad30635033a7,https://ieeexplore.ieee.org/document/6804216/
1117,"Investments in security technologies by strategic users is typically modeled as a public good problem, known as the Interdependent Security (IDS) game. The equilibria for such games are often inefficient, as selfish users free-ride on positive externalities of others' contributions. We present a mechanism that implements the socially optimal equilibrium in an IDS game through a message exchange process; this mechanism does not need to monitor or audit users. However, it does not necessarily guarantee voluntary participation, often a trivial condition to satisfy in many resource allocation problems, but made much harder due to the incentive to stay out and free-ride on others' investments. We discuss the role of cyber insurance in this setting.",mingyan liu,Games,2014.0,10.1109/ITA.2014.6804216,2014 Information Theory and Applications Workshop (ITA),Naghizadeh2014,False,,IEEE,Not available,Closing the price of anarchy gap in the interdependent security game,92d4d6c85c3bf830b63aad30635033a7,https://ieeexplore.ieee.org/document/6804216/
1118,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
1119,"Investments in security technologies by strategic users is typically modeled as a public good problem, known as the Interdependent Security (IDS) game. The equilibria for such games are often inefficient, as selfish users free-ride on positive externalities of others' contributions. We present a mechanism that implements the socially optimal equilibrium in an IDS game through a message exchange process; this mechanism does not need to monitor or audit users. However, it does not necessarily guarantee voluntary participation, often a trivial condition to satisfy in many resource allocation problems, but made much harder due to the incentive to stay out and free-ride on others' investments. We discuss the role of cyber insurance in this setting.",mingyan liu,Nash equilibrium,2014.0,10.1109/ITA.2014.6804216,2014 Information Theory and Applications Workshop (ITA),Naghizadeh2014,False,,IEEE,Not available,Closing the price of anarchy gap in the interdependent security game,92d4d6c85c3bf830b63aad30635033a7,https://ieeexplore.ieee.org/document/6804216/
1120,"Investments in security technologies by strategic users is typically modeled as a public good problem, known as the Interdependent Security (IDS) game. The equilibria for such games are often inefficient, as selfish users free-ride on positive externalities of others' contributions. We present a mechanism that implements the socially optimal equilibrium in an IDS game through a message exchange process; this mechanism does not need to monitor or audit users. However, it does not necessarily guarantee voluntary participation, often a trivial condition to satisfy in many resource allocation problems, but made much harder due to the incentive to stay out and free-ride on others' investments. We discuss the role of cyber insurance in this setting.",mingyan liu,Vectors,2014.0,10.1109/ITA.2014.6804216,2014 Information Theory and Applications Workshop (ITA),Naghizadeh2014,False,,IEEE,Not available,Closing the price of anarchy gap in the interdependent security game,92d4d6c85c3bf830b63aad30635033a7,https://ieeexplore.ieee.org/document/6804216/
1121,"Investments in security technologies by strategic users is typically modeled as a public good problem, known as the Interdependent Security (IDS) game. The equilibria for such games are often inefficient, as selfish users free-ride on positive externalities of others' contributions. We present a mechanism that implements the socially optimal equilibrium in an IDS game through a message exchange process; this mechanism does not need to monitor or audit users. However, it does not necessarily guarantee voluntary participation, often a trivial condition to satisfy in many resource allocation problems, but made much harder due to the incentive to stay out and free-ride on others' investments. We discuss the role of cyber insurance in this setting.",mingyan liu,Proposals,2014.0,10.1109/ITA.2014.6804216,2014 Information Theory and Applications Workshop (ITA),Naghizadeh2014,False,,IEEE,Not available,Closing the price of anarchy gap in the interdependent security game,92d4d6c85c3bf830b63aad30635033a7,https://ieeexplore.ieee.org/document/6804216/
1122,"Investments in security technologies by strategic users is typically modeled as a public good problem, known as the Interdependent Security (IDS) game. The equilibria for such games are often inefficient, as selfish users free-ride on positive externalities of others' contributions. We present a mechanism that implements the socially optimal equilibrium in an IDS game through a message exchange process; this mechanism does not need to monitor or audit users. However, it does not necessarily guarantee voluntary participation, often a trivial condition to satisfy in many resource allocation problems, but made much harder due to the incentive to stay out and free-ride on others' investments. We discuss the role of cyber insurance in this setting.",mingyan liu,Monitoring,2014.0,10.1109/ITA.2014.6804216,2014 Information Theory and Applications Workshop (ITA),Naghizadeh2014,False,,IEEE,Not available,Closing the price of anarchy gap in the interdependent security game,92d4d6c85c3bf830b63aad30635033a7,https://ieeexplore.ieee.org/document/6804216/
1123,"Allowing selfish agents to acquire and exploit system information has both positive and negative effects on the overall performance of resource allocation systems. The positive effect results from reduction in the uncertainty inherently present in large-scale systems. The negative effect, which can be mitigated through congestion pricing, is due to agent selfishness. However, current research, concentrated around the notion of “Price of Anarchy”, is mostly concerned with the negative effect. This paper evaluates systemic risks/benefits of selfish agent ability to acquire and exploit dynamic system information in a specific case of selfish routing in a large-scale, random, loss network. Our analysis indicates that the beneficial effect of this ability dominates in a case of high system uncertainty - low load, while the negative effect dominates in a case of low system uncertainty - high load. In the intermediate cases while the beneficial effect still dominates in the “normal” operating mode, the negative effect manifests itself in a risk of cascading overload driving the system to an emergent metastable, i.e., persistent, congested mode. Future research should consider resource allocation models with elastic selfish users and evaluate effect of the congestion pricing.",v. marbukh,selfish agents,2012.0,10.1109/NOMS.2012.6211986,2012 IEEE Network Operations and Management Symposium,Marbukh2012,False,,IEEE,Not available,Systemic risks/benefits of selfish network operations & management in dynamic environment,40489152c1d5cdc0c00098a85c1cae3c,https://ieeexplore.ieee.org/document/6211986/
1124,"Allowing selfish agents to acquire and exploit system information has both positive and negative effects on the overall performance of resource allocation systems. The positive effect results from reduction in the uncertainty inherently present in large-scale systems. The negative effect, which can be mitigated through congestion pricing, is due to agent selfishness. However, current research, concentrated around the notion of “Price of Anarchy”, is mostly concerned with the negative effect. This paper evaluates systemic risks/benefits of selfish agent ability to acquire and exploit dynamic system information in a specific case of selfish routing in a large-scale, random, loss network. Our analysis indicates that the beneficial effect of this ability dominates in a case of high system uncertainty - low load, while the negative effect dominates in a case of low system uncertainty - high load. In the intermediate cases while the beneficial effect still dominates in the “normal” operating mode, the negative effect manifests itself in a risk of cascading overload driving the system to an emergent metastable, i.e., persistent, congested mode. Future research should consider resource allocation models with elastic selfish users and evaluate effect of the congestion pricing.",v. marbukh,information availability,2012.0,10.1109/NOMS.2012.6211986,2012 IEEE Network Operations and Management Symposium,Marbukh2012,False,,IEEE,Not available,Systemic risks/benefits of selfish network operations & management in dynamic environment,40489152c1d5cdc0c00098a85c1cae3c,https://ieeexplore.ieee.org/document/6211986/
1125,"Allowing selfish agents to acquire and exploit system information has both positive and negative effects on the overall performance of resource allocation systems. The positive effect results from reduction in the uncertainty inherently present in large-scale systems. The negative effect, which can be mitigated through congestion pricing, is due to agent selfishness. However, current research, concentrated around the notion of “Price of Anarchy”, is mostly concerned with the negative effect. This paper evaluates systemic risks/benefits of selfish agent ability to acquire and exploit dynamic system information in a specific case of selfish routing in a large-scale, random, loss network. Our analysis indicates that the beneficial effect of this ability dominates in a case of high system uncertainty - low load, while the negative effect dominates in a case of low system uncertainty - high load. In the intermediate cases while the beneficial effect still dominates in the “normal” operating mode, the negative effect manifests itself in a risk of cascading overload driving the system to an emergent metastable, i.e., persistent, congested mode. Future research should consider resource allocation models with elastic selfish users and evaluate effect of the congestion pricing.",v. marbukh,systemic risk,2012.0,10.1109/NOMS.2012.6211986,2012 IEEE Network Operations and Management Symposium,Marbukh2012,False,,IEEE,Not available,Systemic risks/benefits of selfish network operations & management in dynamic environment,40489152c1d5cdc0c00098a85c1cae3c,https://ieeexplore.ieee.org/document/6211986/
1126,"We combine queueing theory and game theory to evaluate the performance of a queueing system with multiple strategic candidate servers. The intent is to model a transmission system where packets can be sent via multiple options, each incurring a cost and controlled by a distributed management. Our purpose is to analyze the effects of the presence or the lack of both cooperation and communication between servers. The mathematical characterization of the uncertainty about the characteristics of the transmission alternatives available is captured through a Bayesian game formulation. In this setup, we compute both the Price of Anarchy, quantifying the inherent inefficiency arising from selfish management of each server, and the Price of Stability, which is the loss due to distributed system management, under different conditions of signaling exchange among the servers.",anna guglielmi,Queueing analysis,2015.0,10.1109/CAMAD.2015.7390486,2015 IEEE 20th International Workshop on Computer Aided Modelling and Design of Communication Links and Networks (CAMAD),Guglielmi2015,False,,IEEE,Not available,Bayesian game analysis of a queueing system with multiple candidate servers,603463c4e0930af0157ab3c10da065b2,https://ieeexplore.ieee.org/document/7390486/
1127,"We combine queueing theory and game theory to evaluate the performance of a queueing system with multiple strategic candidate servers. The intent is to model a transmission system where packets can be sent via multiple options, each incurring a cost and controlled by a distributed management. Our purpose is to analyze the effects of the presence or the lack of both cooperation and communication between servers. The mathematical characterization of the uncertainty about the characteristics of the transmission alternatives available is captured through a Bayesian game formulation. In this setup, we compute both the Price of Anarchy, quantifying the inherent inefficiency arising from selfish management of each server, and the Price of Stability, which is the loss due to distributed system management, under different conditions of signaling exchange among the servers.",anna guglielmi,telecommunication networks,2015.0,10.1109/CAMAD.2015.7390486,2015 IEEE 20th International Workshop on Computer Aided Modelling and Design of Communication Links and Networks (CAMAD),Guglielmi2015,False,,IEEE,Not available,Bayesian game analysis of a queueing system with multiple candidate servers,603463c4e0930af0157ab3c10da065b2,https://ieeexplore.ieee.org/document/7390486/
1128,"We combine queueing theory and game theory to evaluate the performance of a queueing system with multiple strategic candidate servers. The intent is to model a transmission system where packets can be sent via multiple options, each incurring a cost and controlled by a distributed management. Our purpose is to analyze the effects of the presence or the lack of both cooperation and communication between servers. The mathematical characterization of the uncertainty about the characteristics of the transmission alternatives available is captured through a Bayesian game formulation. In this setup, we compute both the Price of Anarchy, quantifying the inherent inefficiency arising from selfish management of each server, and the Price of Stability, which is the loss due to distributed system management, under different conditions of signaling exchange among the servers.",anna guglielmi,game theory,2015.0,10.1109/CAMAD.2015.7390486,2015 IEEE 20th International Workshop on Computer Aided Modelling and Design of Communication Links and Networks (CAMAD),Guglielmi2015,False,,IEEE,Not available,Bayesian game analysis of a queueing system with multiple candidate servers,603463c4e0930af0157ab3c10da065b2,https://ieeexplore.ieee.org/document/7390486/
1129,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
1130,"We combine queueing theory and game theory to evaluate the performance of a queueing system with multiple strategic candidate servers. The intent is to model a transmission system where packets can be sent via multiple options, each incurring a cost and controlled by a distributed management. Our purpose is to analyze the effects of the presence or the lack of both cooperation and communication between servers. The mathematical characterization of the uncertainty about the characteristics of the transmission alternatives available is captured through a Bayesian game formulation. In this setup, we compute both the Price of Anarchy, quantifying the inherent inefficiency arising from selfish management of each server, and the Price of Stability, which is the loss due to distributed system management, under different conditions of signaling exchange among the servers.",anna guglielmi,Bayesian games,2015.0,10.1109/CAMAD.2015.7390486,2015 IEEE 20th International Workshop on Computer Aided Modelling and Design of Communication Links and Networks (CAMAD),Guglielmi2015,False,,IEEE,Not available,Bayesian game analysis of a queueing system with multiple candidate servers,603463c4e0930af0157ab3c10da065b2,https://ieeexplore.ieee.org/document/7390486/
1131,"We combine queueing theory and game theory to evaluate the performance of a queueing system with multiple strategic candidate servers. The intent is to model a transmission system where packets can be sent via multiple options, each incurring a cost and controlled by a distributed management. Our purpose is to analyze the effects of the presence or the lack of both cooperation and communication between servers. The mathematical characterization of the uncertainty about the characteristics of the transmission alternatives available is captured through a Bayesian game formulation. In this setup, we compute both the Price of Anarchy, quantifying the inherent inefficiency arising from selfish management of each server, and the Price of Stability, which is the loss due to distributed system management, under different conditions of signaling exchange among the servers.",anna guglielmi,Price of Anarchy,2015.0,10.1109/CAMAD.2015.7390486,2015 IEEE 20th International Workshop on Computer Aided Modelling and Design of Communication Links and Networks (CAMAD),Guglielmi2015,False,,IEEE,Not available,Bayesian game analysis of a queueing system with multiple candidate servers,603463c4e0930af0157ab3c10da065b2,https://ieeexplore.ieee.org/document/7390486/
1132,"We combine queueing theory and game theory to evaluate the performance of a queueing system with multiple strategic candidate servers. The intent is to model a transmission system where packets can be sent via multiple options, each incurring a cost and controlled by a distributed management. Our purpose is to analyze the effects of the presence or the lack of both cooperation and communication between servers. The mathematical characterization of the uncertainty about the characteristics of the transmission alternatives available is captured through a Bayesian game formulation. In this setup, we compute both the Price of Anarchy, quantifying the inherent inefficiency arising from selfish management of each server, and the Price of Stability, which is the loss due to distributed system management, under different conditions of signaling exchange among the servers.",leonardo badia,Queueing analysis,2015.0,10.1109/CAMAD.2015.7390486,2015 IEEE 20th International Workshop on Computer Aided Modelling and Design of Communication Links and Networks (CAMAD),Guglielmi2015,False,,IEEE,Not available,Bayesian game analysis of a queueing system with multiple candidate servers,603463c4e0930af0157ab3c10da065b2,https://ieeexplore.ieee.org/document/7390486/
1133,"We combine queueing theory and game theory to evaluate the performance of a queueing system with multiple strategic candidate servers. The intent is to model a transmission system where packets can be sent via multiple options, each incurring a cost and controlled by a distributed management. Our purpose is to analyze the effects of the presence or the lack of both cooperation and communication between servers. The mathematical characterization of the uncertainty about the characteristics of the transmission alternatives available is captured through a Bayesian game formulation. In this setup, we compute both the Price of Anarchy, quantifying the inherent inefficiency arising from selfish management of each server, and the Price of Stability, which is the loss due to distributed system management, under different conditions of signaling exchange among the servers.",leonardo badia,telecommunication networks,2015.0,10.1109/CAMAD.2015.7390486,2015 IEEE 20th International Workshop on Computer Aided Modelling and Design of Communication Links and Networks (CAMAD),Guglielmi2015,False,,IEEE,Not available,Bayesian game analysis of a queueing system with multiple candidate servers,603463c4e0930af0157ab3c10da065b2,https://ieeexplore.ieee.org/document/7390486/
1134,"We combine queueing theory and game theory to evaluate the performance of a queueing system with multiple strategic candidate servers. The intent is to model a transmission system where packets can be sent via multiple options, each incurring a cost and controlled by a distributed management. Our purpose is to analyze the effects of the presence or the lack of both cooperation and communication between servers. The mathematical characterization of the uncertainty about the characteristics of the transmission alternatives available is captured through a Bayesian game formulation. In this setup, we compute both the Price of Anarchy, quantifying the inherent inefficiency arising from selfish management of each server, and the Price of Stability, which is the loss due to distributed system management, under different conditions of signaling exchange among the servers.",leonardo badia,game theory,2015.0,10.1109/CAMAD.2015.7390486,2015 IEEE 20th International Workshop on Computer Aided Modelling and Design of Communication Links and Networks (CAMAD),Guglielmi2015,False,,IEEE,Not available,Bayesian game analysis of a queueing system with multiple candidate servers,603463c4e0930af0157ab3c10da065b2,https://ieeexplore.ieee.org/document/7390486/
1135,"We combine queueing theory and game theory to evaluate the performance of a queueing system with multiple strategic candidate servers. The intent is to model a transmission system where packets can be sent via multiple options, each incurring a cost and controlled by a distributed management. Our purpose is to analyze the effects of the presence or the lack of both cooperation and communication between servers. The mathematical characterization of the uncertainty about the characteristics of the transmission alternatives available is captured through a Bayesian game formulation. In this setup, we compute both the Price of Anarchy, quantifying the inherent inefficiency arising from selfish management of each server, and the Price of Stability, which is the loss due to distributed system management, under different conditions of signaling exchange among the servers.",leonardo badia,Bayesian games,2015.0,10.1109/CAMAD.2015.7390486,2015 IEEE 20th International Workshop on Computer Aided Modelling and Design of Communication Links and Networks (CAMAD),Guglielmi2015,False,,IEEE,Not available,Bayesian game analysis of a queueing system with multiple candidate servers,603463c4e0930af0157ab3c10da065b2,https://ieeexplore.ieee.org/document/7390486/
1136,"We combine queueing theory and game theory to evaluate the performance of a queueing system with multiple strategic candidate servers. The intent is to model a transmission system where packets can be sent via multiple options, each incurring a cost and controlled by a distributed management. Our purpose is to analyze the effects of the presence or the lack of both cooperation and communication between servers. The mathematical characterization of the uncertainty about the characteristics of the transmission alternatives available is captured through a Bayesian game formulation. In this setup, we compute both the Price of Anarchy, quantifying the inherent inefficiency arising from selfish management of each server, and the Price of Stability, which is the loss due to distributed system management, under different conditions of signaling exchange among the servers.",leonardo badia,Price of Anarchy,2015.0,10.1109/CAMAD.2015.7390486,2015 IEEE 20th International Workshop on Computer Aided Modelling and Design of Communication Links and Networks (CAMAD),Guglielmi2015,False,,IEEE,Not available,Bayesian game analysis of a queueing system with multiple candidate servers,603463c4e0930af0157ab3c10da065b2,https://ieeexplore.ieee.org/document/7390486/
1137,"This paper explains when and how communication and computational lower bounds for algorithms for an optimization problem translate to lower bounds on the worst-case quality of equilibria in games derived from the problem. We give three families of lower bounds on the quality of equilibria, each motivated by a different set of problems: congestion, scheduling, and distributed welfare games, welfare-maximization in combinatorial auctions with ""black-box"" bidder valuations, and welfare-maximization in combinatorial auctions with succinctly described valuations. The most straightforward use of our lower bound framework is to harness an existing computational or communication lower bound to derive a lower bound on the worst-case price of anarchy (POA) in a class of games. This is a new approach to POA lower bounds, which relies on reductions in lieu of explicit constructions. More generally, the POA lower bounds implied by our framework apply to all classes of games that share the same underlying optimization problem, independent of the details of players' utility functions. For this reason, our lower bounds are particularly significant for problems of game design -- ranging from the design of simple combinatorial auctions to the computation of tolls for routing networks -- where the goal is to design a game that has only near-optimal equilibria. For example, our results imply that the simultaneous first-price auction format is optimal among all ""simple combinatorial auctions"" in several settings.",tim roughgarden,price of anarchy,2014.0,10.1109/FOCS.2014.16,2014 IEEE 55th Annual Symposium on Foundations of Computer Science,Roughgarden2014,False,,IEEE,Not available,Barriers to Near-Optimal Equilibria,4c4f4ab60e53a1f1df03162eff4e269f,https://ieeexplore.ieee.org/document/6978991/
1138,"This paper explains when and how communication and computational lower bounds for algorithms for an optimization problem translate to lower bounds on the worst-case quality of equilibria in games derived from the problem. We give three families of lower bounds on the quality of equilibria, each motivated by a different set of problems: congestion, scheduling, and distributed welfare games, welfare-maximization in combinatorial auctions with ""black-box"" bidder valuations, and welfare-maximization in combinatorial auctions with succinctly described valuations. The most straightforward use of our lower bound framework is to harness an existing computational or communication lower bound to derive a lower bound on the worst-case price of anarchy (POA) in a class of games. This is a new approach to POA lower bounds, which relies on reductions in lieu of explicit constructions. More generally, the POA lower bounds implied by our framework apply to all classes of games that share the same underlying optimization problem, independent of the details of players' utility functions. For this reason, our lower bounds are particularly significant for problems of game design -- ranging from the design of simple combinatorial auctions to the computation of tolls for routing networks -- where the goal is to design a game that has only near-optimal equilibria. For example, our results imply that the simultaneous first-price auction format is optimal among all ""simple combinatorial auctions"" in several settings.",tim roughgarden,mechanism design,2014.0,10.1109/FOCS.2014.16,2014 IEEE 55th Annual Symposium on Foundations of Computer Science,Roughgarden2014,False,,IEEE,Not available,Barriers to Near-Optimal Equilibria,4c4f4ab60e53a1f1df03162eff4e269f,https://ieeexplore.ieee.org/document/6978991/
1139,"This paper explains when and how communication and computational lower bounds for algorithms for an optimization problem translate to lower bounds on the worst-case quality of equilibria in games derived from the problem. We give three families of lower bounds on the quality of equilibria, each motivated by a different set of problems: congestion, scheduling, and distributed welfare games, welfare-maximization in combinatorial auctions with ""black-box"" bidder valuations, and welfare-maximization in combinatorial auctions with succinctly described valuations. The most straightforward use of our lower bound framework is to harness an existing computational or communication lower bound to derive a lower bound on the worst-case price of anarchy (POA) in a class of games. This is a new approach to POA lower bounds, which relies on reductions in lieu of explicit constructions. More generally, the POA lower bounds implied by our framework apply to all classes of games that share the same underlying optimization problem, independent of the details of players' utility functions. For this reason, our lower bounds are particularly significant for problems of game design -- ranging from the design of simple combinatorial auctions to the computation of tolls for routing networks -- where the goal is to design a game that has only near-optimal equilibria. For example, our results imply that the simultaneous first-price auction format is optimal among all ""simple combinatorial auctions"" in several settings.",tim roughgarden,complexity of equilbria,2014.0,10.1109/FOCS.2014.16,2014 IEEE 55th Annual Symposium on Foundations of Computer Science,Roughgarden2014,False,,IEEE,Not available,Barriers to Near-Optimal Equilibria,4c4f4ab60e53a1f1df03162eff4e269f,https://ieeexplore.ieee.org/document/6978991/
1140,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
1141,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The degradation in performance due to the lack of regulation is measured by the Price of Anarchy (POA), which is defined as the ratio between the cost of the worst possible Wardrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Toward establishing this result, we first characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. Next, we show that the Wardrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA >; 1 and determine near-tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy.",aditya ramamoorthy,Distributed source coding,2012.0,10.1109/TIT.2012.2184660,IEEE Transactions on Information Theory,Ramamoorthy2012,False,,IEEE,Not available,Selfish Distributed Compression Over Networks: Correlation Induces Anarchy,047e59363aaf2dc243cdd1e6c38419be,https://ieeexplore.ieee.org/document/6142086/
1142,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The degradation in performance due to the lack of regulation is measured by the Price of Anarchy (POA), which is defined as the ratio between the cost of the worst possible Wardrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Toward establishing this result, we first characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. Next, we show that the Wardrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA >; 1 and determine near-tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy.",aditya ramamoorthy,game theory,2012.0,10.1109/TIT.2012.2184660,IEEE Transactions on Information Theory,Ramamoorthy2012,False,,IEEE,Not available,Selfish Distributed Compression Over Networks: Correlation Induces Anarchy,047e59363aaf2dc243cdd1e6c38419be,https://ieeexplore.ieee.org/document/6142086/
1143,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The degradation in performance due to the lack of regulation is measured by the Price of Anarchy (POA), which is defined as the ratio between the cost of the worst possible Wardrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Toward establishing this result, we first characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. Next, we show that the Wardrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA >; 1 and determine near-tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy.",aditya ramamoorthy,multicast,2012.0,10.1109/TIT.2012.2184660,IEEE Transactions on Information Theory,Ramamoorthy2012,False,,IEEE,Not available,Selfish Distributed Compression Over Networks: Correlation Induces Anarchy,047e59363aaf2dc243cdd1e6c38419be,https://ieeexplore.ieee.org/document/6142086/
1144,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The degradation in performance due to the lack of regulation is measured by the Price of Anarchy (POA), which is defined as the ratio between the cost of the worst possible Wardrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Toward establishing this result, we first characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. Next, we show that the Wardrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA >; 1 and determine near-tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy.",aditya ramamoorthy,network coding,2012.0,10.1109/TIT.2012.2184660,IEEE Transactions on Information Theory,Ramamoorthy2012,False,,IEEE,Not available,Selfish Distributed Compression Over Networks: Correlation Induces Anarchy,047e59363aaf2dc243cdd1e6c38419be,https://ieeexplore.ieee.org/document/6142086/
1145,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The degradation in performance due to the lack of regulation is measured by the Price of Anarchy (POA), which is defined as the ratio between the cost of the worst possible Wardrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Toward establishing this result, we first characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. Next, we show that the Wardrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA >; 1 and determine near-tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy.",aditya ramamoorthy,selfish behavior,2012.0,10.1109/TIT.2012.2184660,IEEE Transactions on Information Theory,Ramamoorthy2012,False,,IEEE,Not available,Selfish Distributed Compression Over Networks: Correlation Induces Anarchy,047e59363aaf2dc243cdd1e6c38419be,https://ieeexplore.ieee.org/document/6142086/
1146,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The degradation in performance due to the lack of regulation is measured by the Price of Anarchy (POA), which is defined as the ratio between the cost of the worst possible Wardrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Toward establishing this result, we first characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. Next, we show that the Wardrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA >; 1 and determine near-tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy.",vwani roychowdhury,Distributed source coding,2012.0,10.1109/TIT.2012.2184660,IEEE Transactions on Information Theory,Ramamoorthy2012,False,,IEEE,Not available,Selfish Distributed Compression Over Networks: Correlation Induces Anarchy,047e59363aaf2dc243cdd1e6c38419be,https://ieeexplore.ieee.org/document/6142086/
1147,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The degradation in performance due to the lack of regulation is measured by the Price of Anarchy (POA), which is defined as the ratio between the cost of the worst possible Wardrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Toward establishing this result, we first characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. Next, we show that the Wardrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA >; 1 and determine near-tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy.",vwani roychowdhury,game theory,2012.0,10.1109/TIT.2012.2184660,IEEE Transactions on Information Theory,Ramamoorthy2012,False,,IEEE,Not available,Selfish Distributed Compression Over Networks: Correlation Induces Anarchy,047e59363aaf2dc243cdd1e6c38419be,https://ieeexplore.ieee.org/document/6142086/
1148,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The degradation in performance due to the lack of regulation is measured by the Price of Anarchy (POA), which is defined as the ratio between the cost of the worst possible Wardrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Toward establishing this result, we first characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. Next, we show that the Wardrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA >; 1 and determine near-tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy.",vwani roychowdhury,multicast,2012.0,10.1109/TIT.2012.2184660,IEEE Transactions on Information Theory,Ramamoorthy2012,False,,IEEE,Not available,Selfish Distributed Compression Over Networks: Correlation Induces Anarchy,047e59363aaf2dc243cdd1e6c38419be,https://ieeexplore.ieee.org/document/6142086/
1149,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The degradation in performance due to the lack of regulation is measured by the Price of Anarchy (POA), which is defined as the ratio between the cost of the worst possible Wardrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Toward establishing this result, we first characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. Next, we show that the Wardrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA >; 1 and determine near-tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy.",vwani roychowdhury,network coding,2012.0,10.1109/TIT.2012.2184660,IEEE Transactions on Information Theory,Ramamoorthy2012,False,,IEEE,Not available,Selfish Distributed Compression Over Networks: Correlation Induces Anarchy,047e59363aaf2dc243cdd1e6c38419be,https://ieeexplore.ieee.org/document/6142086/
1150,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The degradation in performance due to the lack of regulation is measured by the Price of Anarchy (POA), which is defined as the ratio between the cost of the worst possible Wardrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Toward establishing this result, we first characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. Next, we show that the Wardrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA >; 1 and determine near-tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy.",vwani roychowdhury,selfish behavior,2012.0,10.1109/TIT.2012.2184660,IEEE Transactions on Information Theory,Ramamoorthy2012,False,,IEEE,Not available,Selfish Distributed Compression Over Networks: Correlation Induces Anarchy,047e59363aaf2dc243cdd1e6c38419be,https://ieeexplore.ieee.org/document/6142086/
1151,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
1152,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The degradation in performance due to the lack of regulation is measured by the Price of Anarchy (POA), which is defined as the ratio between the cost of the worst possible Wardrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Toward establishing this result, we first characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. Next, we show that the Wardrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA >; 1 and determine near-tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy.",sudhir singh,Distributed source coding,2012.0,10.1109/TIT.2012.2184660,IEEE Transactions on Information Theory,Ramamoorthy2012,False,,IEEE,Not available,Selfish Distributed Compression Over Networks: Correlation Induces Anarchy,047e59363aaf2dc243cdd1e6c38419be,https://ieeexplore.ieee.org/document/6142086/
1153,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The degradation in performance due to the lack of regulation is measured by the Price of Anarchy (POA), which is defined as the ratio between the cost of the worst possible Wardrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Toward establishing this result, we first characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. Next, we show that the Wardrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA >; 1 and determine near-tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy.",sudhir singh,game theory,2012.0,10.1109/TIT.2012.2184660,IEEE Transactions on Information Theory,Ramamoorthy2012,False,,IEEE,Not available,Selfish Distributed Compression Over Networks: Correlation Induces Anarchy,047e59363aaf2dc243cdd1e6c38419be,https://ieeexplore.ieee.org/document/6142086/
1154,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The degradation in performance due to the lack of regulation is measured by the Price of Anarchy (POA), which is defined as the ratio between the cost of the worst possible Wardrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Toward establishing this result, we first characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. Next, we show that the Wardrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA >; 1 and determine near-tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy.",sudhir singh,multicast,2012.0,10.1109/TIT.2012.2184660,IEEE Transactions on Information Theory,Ramamoorthy2012,False,,IEEE,Not available,Selfish Distributed Compression Over Networks: Correlation Induces Anarchy,047e59363aaf2dc243cdd1e6c38419be,https://ieeexplore.ieee.org/document/6142086/
1155,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The degradation in performance due to the lack of regulation is measured by the Price of Anarchy (POA), which is defined as the ratio between the cost of the worst possible Wardrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Toward establishing this result, we first characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. Next, we show that the Wardrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA >; 1 and determine near-tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy.",sudhir singh,network coding,2012.0,10.1109/TIT.2012.2184660,IEEE Transactions on Information Theory,Ramamoorthy2012,False,,IEEE,Not available,Selfish Distributed Compression Over Networks: Correlation Induces Anarchy,047e59363aaf2dc243cdd1e6c38419be,https://ieeexplore.ieee.org/document/6142086/
1156,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The degradation in performance due to the lack of regulation is measured by the Price of Anarchy (POA), which is defined as the ratio between the cost of the worst possible Wardrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Toward establishing this result, we first characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. Next, we show that the Wardrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA >; 1 and determine near-tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy.",sudhir singh,selfish behavior,2012.0,10.1109/TIT.2012.2184660,IEEE Transactions on Information Theory,Ramamoorthy2012,False,,IEEE,Not available,Selfish Distributed Compression Over Networks: Correlation Induces Anarchy,047e59363aaf2dc243cdd1e6c38419be,https://ieeexplore.ieee.org/document/6142086/
1157,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",chi chau,Routing,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
1158,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",chi chau,Monopoly,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
1159,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",chi chau,Pricing,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
1160,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",chi chau,Multiprotocol label switching,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
1161,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",chi chau,IP networks,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
1162,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
1163,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",chi chau,Delay,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
1164,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",chi chau,Web and internet services,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
1165,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",chi chau,Control systems,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
1166,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",chi chau,Communication system traffic control,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
1167,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",chi chau,Upper bound,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
1168,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",kwang sim,Routing,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
1169,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",kwang sim,Monopoly,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
1170,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",kwang sim,Pricing,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
1171,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",kwang sim,Multiprotocol label switching,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
1172,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",kwang sim,IP networks,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
1173,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
1174,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",kwang sim,Delay,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
1175,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",kwang sim,Web and internet services,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
1176,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",kwang sim,Control systems,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
1177,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",kwang sim,Communication system traffic control,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
1178,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",kwang sim,Upper bound,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
1179,"We investigate cascades in networks consisting of strategic agents with interdependent security. We assume that the strategic agents have choices between (i) investing in protecting themselves, (ii) purchasing insurance to transfer (some) risks, and (iii) taking no actions. Using a population game model, we study how various system parameters, such as node degrees, infection propagation rate, and the probability with which infected nodes transmit infection to neighbors, affect nodes' choices at Nash equilibria and the resultant price of anarchy/stability. In addition, we examine how the probability that a single infected node can spread the infection to a significant portion of the entire network, called cascade probability, behaves with respect to system parameters. In particular, we demonstrate that, at least for some parameter regimes, the cascade probability increases with the average degree of nodes.",richard la,Cascade,2016.0,10.1109/TNET.2015.2408598,IEEE/ACM Transactions on Networking,La2016,False,,IEEE,Not available,Interdependent Security With Strategic Agents and Cascades of Infection,61cf886f0b42047e446f31bd8c9959af,https://ieeexplore.ieee.org/document/7065333/
1180,"We investigate cascades in networks consisting of strategic agents with interdependent security. We assume that the strategic agents have choices between (i) investing in protecting themselves, (ii) purchasing insurance to transfer (some) risks, and (iii) taking no actions. Using a population game model, we study how various system parameters, such as node degrees, infection propagation rate, and the probability with which infected nodes transmit infection to neighbors, affect nodes' choices at Nash equilibria and the resultant price of anarchy/stability. In addition, we examine how the probability that a single infected node can spread the infection to a significant portion of the entire network, called cascade probability, behaves with respect to system parameters. In particular, we demonstrate that, at least for some parameter regimes, the cascade probability increases with the average degree of nodes.",richard la,contagion,2016.0,10.1109/TNET.2015.2408598,IEEE/ACM Transactions on Networking,La2016,False,,IEEE,Not available,Interdependent Security With Strategic Agents and Cascades of Infection,61cf886f0b42047e446f31bd8c9959af,https://ieeexplore.ieee.org/document/7065333/
1181,"We investigate cascades in networks consisting of strategic agents with interdependent security. We assume that the strategic agents have choices between (i) investing in protecting themselves, (ii) purchasing insurance to transfer (some) risks, and (iii) taking no actions. Using a population game model, we study how various system parameters, such as node degrees, infection propagation rate, and the probability with which infected nodes transmit infection to neighbors, affect nodes' choices at Nash equilibria and the resultant price of anarchy/stability. In addition, we examine how the probability that a single infected node can spread the infection to a significant portion of the entire network, called cascade probability, behaves with respect to system parameters. In particular, we demonstrate that, at least for some parameter regimes, the cascade probability increases with the average degree of nodes.",richard la,interdependent security,2016.0,10.1109/TNET.2015.2408598,IEEE/ACM Transactions on Networking,La2016,False,,IEEE,Not available,Interdependent Security With Strategic Agents and Cascades of Infection,61cf886f0b42047e446f31bd8c9959af,https://ieeexplore.ieee.org/document/7065333/
1182,"We investigate cascades in networks consisting of strategic agents with interdependent security. We assume that the strategic agents have choices between (i) investing in protecting themselves, (ii) purchasing insurance to transfer (some) risks, and (iii) taking no actions. Using a population game model, we study how various system parameters, such as node degrees, infection propagation rate, and the probability with which infected nodes transmit infection to neighbors, affect nodes' choices at Nash equilibria and the resultant price of anarchy/stability. In addition, we examine how the probability that a single infected node can spread the infection to a significant portion of the entire network, called cascade probability, behaves with respect to system parameters. In particular, we demonstrate that, at least for some parameter regimes, the cascade probability increases with the average degree of nodes.",richard la,population game,2016.0,10.1109/TNET.2015.2408598,IEEE/ACM Transactions on Networking,La2016,False,,IEEE,Not available,Interdependent Security With Strategic Agents and Cascades of Infection,61cf886f0b42047e446f31bd8c9959af,https://ieeexplore.ieee.org/document/7065333/
1183,"We investigate cascades in networks consisting of strategic agents with interdependent security. We assume that the strategic agents have choices between (i) investing in protecting themselves, (ii) purchasing insurance to transfer (some) risks, and (iii) taking no actions. Using a population game model, we study how various system parameters, such as node degrees, infection propagation rate, and the probability with which infected nodes transmit infection to neighbors, affect nodes' choices at Nash equilibria and the resultant price of anarchy/stability. In addition, we examine how the probability that a single infected node can spread the infection to a significant portion of the entire network, called cascade probability, behaves with respect to system parameters. In particular, we demonstrate that, at least for some parameter regimes, the cascade probability increases with the average degree of nodes.",richard la,price of anarchy,2016.0,10.1109/TNET.2015.2408598,IEEE/ACM Transactions on Networking,La2016,False,,IEEE,Not available,Interdependent Security With Strategic Agents and Cascades of Infection,61cf886f0b42047e446f31bd8c9959af,https://ieeexplore.ieee.org/document/7065333/
1184,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
1185,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
1186,"Cognitive radio networks provide the capability to share the wireless channel with licensed (primary) users in an opportunistic manner. Primary users have a license to operate in a certain spectrum band; their access can only be controlled by the Primary Operator and is not affected by any other unlicensed (secondary) user. On the other hand, secondary users (SUs) have no spectrum license, and they attempt to exploit the spectral gaps left free by primary users. This work studies the spectrum access problem in cognitive radio networks from a game theoretical perspective. The problem is modeled as a non-cooperative spectrum access game where secondary users access simultaneously multiple spectrum bands left available by primary users, optimizing their objective function which takes into account the congestion level observed on the available spectrum bands. As a key innovative feature with respect to existing works, we model accurately the interference between SUs, capturing the effect of spatial reuse. We demonstrate the existence of the Nash equilibrium, and derive equilibrium flow settings. Finally, we provide numerical results of the proposed spectrum access game in several cognitive radio scenarios, and study the impact of the interference between SUs on the game efficiency. Our results indicate that the congestion cost functions we propose in this paper lead to small gaps between Nash equilibria and optimal solutions in all the considered network scenarios, thus representing a starting point for designing pricing mechanisms so as to obtain a socially optimal use of the network.",jocelyne elias,Cognitive Radio Networks,2010.0,,"8th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Elias2010,False,,IEEE,Not available,Competitive interference-aware spectrum access in cognitive radio networks,c33f127f150625858296fb853f6525df,https://ieeexplore.ieee.org/document/5519538/
1187,"Cognitive radio networks provide the capability to share the wireless channel with licensed (primary) users in an opportunistic manner. Primary users have a license to operate in a certain spectrum band; their access can only be controlled by the Primary Operator and is not affected by any other unlicensed (secondary) user. On the other hand, secondary users (SUs) have no spectrum license, and they attempt to exploit the spectral gaps left free by primary users. This work studies the spectrum access problem in cognitive radio networks from a game theoretical perspective. The problem is modeled as a non-cooperative spectrum access game where secondary users access simultaneously multiple spectrum bands left available by primary users, optimizing their objective function which takes into account the congestion level observed on the available spectrum bands. As a key innovative feature with respect to existing works, we model accurately the interference between SUs, capturing the effect of spatial reuse. We demonstrate the existence of the Nash equilibrium, and derive equilibrium flow settings. Finally, we provide numerical results of the proposed spectrum access game in several cognitive radio scenarios, and study the impact of the interference between SUs on the game efficiency. Our results indicate that the congestion cost functions we propose in this paper lead to small gaps between Nash equilibria and optimal solutions in all the considered network scenarios, thus representing a starting point for designing pricing mechanisms so as to obtain a socially optimal use of the network.",jocelyne elias,Spectrum access,2010.0,,"8th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Elias2010,False,,IEEE,Not available,Competitive interference-aware spectrum access in cognitive radio networks,c33f127f150625858296fb853f6525df,https://ieeexplore.ieee.org/document/5519538/
1188,"Cognitive radio networks provide the capability to share the wireless channel with licensed (primary) users in an opportunistic manner. Primary users have a license to operate in a certain spectrum band; their access can only be controlled by the Primary Operator and is not affected by any other unlicensed (secondary) user. On the other hand, secondary users (SUs) have no spectrum license, and they attempt to exploit the spectral gaps left free by primary users. This work studies the spectrum access problem in cognitive radio networks from a game theoretical perspective. The problem is modeled as a non-cooperative spectrum access game where secondary users access simultaneously multiple spectrum bands left available by primary users, optimizing their objective function which takes into account the congestion level observed on the available spectrum bands. As a key innovative feature with respect to existing works, we model accurately the interference between SUs, capturing the effect of spatial reuse. We demonstrate the existence of the Nash equilibrium, and derive equilibrium flow settings. Finally, we provide numerical results of the proposed spectrum access game in several cognitive radio scenarios, and study the impact of the interference between SUs on the game efficiency. Our results indicate that the congestion cost functions we propose in this paper lead to small gaps between Nash equilibria and optimal solutions in all the considered network scenarios, thus representing a starting point for designing pricing mechanisms so as to obtain a socially optimal use of the network.",jocelyne elias,Game Theory,2010.0,,"8th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Elias2010,False,,IEEE,Not available,Competitive interference-aware spectrum access in cognitive radio networks,c33f127f150625858296fb853f6525df,https://ieeexplore.ieee.org/document/5519538/
1189,"Cognitive radio networks provide the capability to share the wireless channel with licensed (primary) users in an opportunistic manner. Primary users have a license to operate in a certain spectrum band; their access can only be controlled by the Primary Operator and is not affected by any other unlicensed (secondary) user. On the other hand, secondary users (SUs) have no spectrum license, and they attempt to exploit the spectral gaps left free by primary users. This work studies the spectrum access problem in cognitive radio networks from a game theoretical perspective. The problem is modeled as a non-cooperative spectrum access game where secondary users access simultaneously multiple spectrum bands left available by primary users, optimizing their objective function which takes into account the congestion level observed on the available spectrum bands. As a key innovative feature with respect to existing works, we model accurately the interference between SUs, capturing the effect of spatial reuse. We demonstrate the existence of the Nash equilibrium, and derive equilibrium flow settings. Finally, we provide numerical results of the proposed spectrum access game in several cognitive radio scenarios, and study the impact of the interference between SUs on the game efficiency. Our results indicate that the congestion cost functions we propose in this paper lead to small gaps between Nash equilibria and optimal solutions in all the considered network scenarios, thus representing a starting point for designing pricing mechanisms so as to obtain a socially optimal use of the network.",jocelyne elias,Price of Anarchy,2010.0,,"8th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Elias2010,False,,IEEE,Not available,Competitive interference-aware spectrum access in cognitive radio networks,c33f127f150625858296fb853f6525df,https://ieeexplore.ieee.org/document/5519538/
1190,"Cognitive radio networks provide the capability to share the wireless channel with licensed (primary) users in an opportunistic manner. Primary users have a license to operate in a certain spectrum band; their access can only be controlled by the Primary Operator and is not affected by any other unlicensed (secondary) user. On the other hand, secondary users (SUs) have no spectrum license, and they attempt to exploit the spectral gaps left free by primary users. This work studies the spectrum access problem in cognitive radio networks from a game theoretical perspective. The problem is modeled as a non-cooperative spectrum access game where secondary users access simultaneously multiple spectrum bands left available by primary users, optimizing their objective function which takes into account the congestion level observed on the available spectrum bands. As a key innovative feature with respect to existing works, we model accurately the interference between SUs, capturing the effect of spatial reuse. We demonstrate the existence of the Nash equilibrium, and derive equilibrium flow settings. Finally, we provide numerical results of the proposed spectrum access game in several cognitive radio scenarios, and study the impact of the interference between SUs on the game efficiency. Our results indicate that the congestion cost functions we propose in this paper lead to small gaps between Nash equilibria and optimal solutions in all the considered network scenarios, thus representing a starting point for designing pricing mechanisms so as to obtain a socially optimal use of the network.",fabio martignon,Cognitive Radio Networks,2010.0,,"8th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Elias2010,False,,IEEE,Not available,Competitive interference-aware spectrum access in cognitive radio networks,c33f127f150625858296fb853f6525df,https://ieeexplore.ieee.org/document/5519538/
1191,"Cognitive radio networks provide the capability to share the wireless channel with licensed (primary) users in an opportunistic manner. Primary users have a license to operate in a certain spectrum band; their access can only be controlled by the Primary Operator and is not affected by any other unlicensed (secondary) user. On the other hand, secondary users (SUs) have no spectrum license, and they attempt to exploit the spectral gaps left free by primary users. This work studies the spectrum access problem in cognitive radio networks from a game theoretical perspective. The problem is modeled as a non-cooperative spectrum access game where secondary users access simultaneously multiple spectrum bands left available by primary users, optimizing their objective function which takes into account the congestion level observed on the available spectrum bands. As a key innovative feature with respect to existing works, we model accurately the interference between SUs, capturing the effect of spatial reuse. We demonstrate the existence of the Nash equilibrium, and derive equilibrium flow settings. Finally, we provide numerical results of the proposed spectrum access game in several cognitive radio scenarios, and study the impact of the interference between SUs on the game efficiency. Our results indicate that the congestion cost functions we propose in this paper lead to small gaps between Nash equilibria and optimal solutions in all the considered network scenarios, thus representing a starting point for designing pricing mechanisms so as to obtain a socially optimal use of the network.",fabio martignon,Spectrum access,2010.0,,"8th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Elias2010,False,,IEEE,Not available,Competitive interference-aware spectrum access in cognitive radio networks,c33f127f150625858296fb853f6525df,https://ieeexplore.ieee.org/document/5519538/
1192,"Cognitive radio networks provide the capability to share the wireless channel with licensed (primary) users in an opportunistic manner. Primary users have a license to operate in a certain spectrum band; their access can only be controlled by the Primary Operator and is not affected by any other unlicensed (secondary) user. On the other hand, secondary users (SUs) have no spectrum license, and they attempt to exploit the spectral gaps left free by primary users. This work studies the spectrum access problem in cognitive radio networks from a game theoretical perspective. The problem is modeled as a non-cooperative spectrum access game where secondary users access simultaneously multiple spectrum bands left available by primary users, optimizing their objective function which takes into account the congestion level observed on the available spectrum bands. As a key innovative feature with respect to existing works, we model accurately the interference between SUs, capturing the effect of spatial reuse. We demonstrate the existence of the Nash equilibrium, and derive equilibrium flow settings. Finally, we provide numerical results of the proposed spectrum access game in several cognitive radio scenarios, and study the impact of the interference between SUs on the game efficiency. Our results indicate that the congestion cost functions we propose in this paper lead to small gaps between Nash equilibria and optimal solutions in all the considered network scenarios, thus representing a starting point for designing pricing mechanisms so as to obtain a socially optimal use of the network.",fabio martignon,Game Theory,2010.0,,"8th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Elias2010,False,,IEEE,Not available,Competitive interference-aware spectrum access in cognitive radio networks,c33f127f150625858296fb853f6525df,https://ieeexplore.ieee.org/document/5519538/
1193,"Cognitive radio networks provide the capability to share the wireless channel with licensed (primary) users in an opportunistic manner. Primary users have a license to operate in a certain spectrum band; their access can only be controlled by the Primary Operator and is not affected by any other unlicensed (secondary) user. On the other hand, secondary users (SUs) have no spectrum license, and they attempt to exploit the spectral gaps left free by primary users. This work studies the spectrum access problem in cognitive radio networks from a game theoretical perspective. The problem is modeled as a non-cooperative spectrum access game where secondary users access simultaneously multiple spectrum bands left available by primary users, optimizing their objective function which takes into account the congestion level observed on the available spectrum bands. As a key innovative feature with respect to existing works, we model accurately the interference between SUs, capturing the effect of spatial reuse. We demonstrate the existence of the Nash equilibrium, and derive equilibrium flow settings. Finally, we provide numerical results of the proposed spectrum access game in several cognitive radio scenarios, and study the impact of the interference between SUs on the game efficiency. Our results indicate that the congestion cost functions we propose in this paper lead to small gaps between Nash equilibria and optimal solutions in all the considered network scenarios, thus representing a starting point for designing pricing mechanisms so as to obtain a socially optimal use of the network.",fabio martignon,Price of Anarchy,2010.0,,"8th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Elias2010,False,,IEEE,Not available,Competitive interference-aware spectrum access in cognitive radio networks,c33f127f150625858296fb853f6525df,https://ieeexplore.ieee.org/document/5519538/
1194,"Cognitive radio networks provide the capability to share the wireless channel with licensed (primary) users in an opportunistic manner. Primary users have a license to operate in a certain spectrum band; their access can only be controlled by the Primary Operator and is not affected by any other unlicensed (secondary) user. On the other hand, secondary users (SUs) have no spectrum license, and they attempt to exploit the spectral gaps left free by primary users. This work studies the spectrum access problem in cognitive radio networks from a game theoretical perspective. The problem is modeled as a non-cooperative spectrum access game where secondary users access simultaneously multiple spectrum bands left available by primary users, optimizing their objective function which takes into account the congestion level observed on the available spectrum bands. As a key innovative feature with respect to existing works, we model accurately the interference between SUs, capturing the effect of spatial reuse. We demonstrate the existence of the Nash equilibrium, and derive equilibrium flow settings. Finally, we provide numerical results of the proposed spectrum access game in several cognitive radio scenarios, and study the impact of the interference between SUs on the game efficiency. Our results indicate that the congestion cost functions we propose in this paper lead to small gaps between Nash equilibria and optimal solutions in all the considered network scenarios, thus representing a starting point for designing pricing mechanisms so as to obtain a socially optimal use of the network.",antonio capone,Cognitive Radio Networks,2010.0,,"8th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Elias2010,False,,IEEE,Not available,Competitive interference-aware spectrum access in cognitive radio networks,c33f127f150625858296fb853f6525df,https://ieeexplore.ieee.org/document/5519538/
1195,"Cognitive radio networks provide the capability to share the wireless channel with licensed (primary) users in an opportunistic manner. Primary users have a license to operate in a certain spectrum band; their access can only be controlled by the Primary Operator and is not affected by any other unlicensed (secondary) user. On the other hand, secondary users (SUs) have no spectrum license, and they attempt to exploit the spectral gaps left free by primary users. This work studies the spectrum access problem in cognitive radio networks from a game theoretical perspective. The problem is modeled as a non-cooperative spectrum access game where secondary users access simultaneously multiple spectrum bands left available by primary users, optimizing their objective function which takes into account the congestion level observed on the available spectrum bands. As a key innovative feature with respect to existing works, we model accurately the interference between SUs, capturing the effect of spatial reuse. We demonstrate the existence of the Nash equilibrium, and derive equilibrium flow settings. Finally, we provide numerical results of the proposed spectrum access game in several cognitive radio scenarios, and study the impact of the interference between SUs on the game efficiency. Our results indicate that the congestion cost functions we propose in this paper lead to small gaps between Nash equilibria and optimal solutions in all the considered network scenarios, thus representing a starting point for designing pricing mechanisms so as to obtain a socially optimal use of the network.",antonio capone,Spectrum access,2010.0,,"8th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Elias2010,False,,IEEE,Not available,Competitive interference-aware spectrum access in cognitive radio networks,c33f127f150625858296fb853f6525df,https://ieeexplore.ieee.org/document/5519538/
1196,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
1197,"Cognitive radio networks provide the capability to share the wireless channel with licensed (primary) users in an opportunistic manner. Primary users have a license to operate in a certain spectrum band; their access can only be controlled by the Primary Operator and is not affected by any other unlicensed (secondary) user. On the other hand, secondary users (SUs) have no spectrum license, and they attempt to exploit the spectral gaps left free by primary users. This work studies the spectrum access problem in cognitive radio networks from a game theoretical perspective. The problem is modeled as a non-cooperative spectrum access game where secondary users access simultaneously multiple spectrum bands left available by primary users, optimizing their objective function which takes into account the congestion level observed on the available spectrum bands. As a key innovative feature with respect to existing works, we model accurately the interference between SUs, capturing the effect of spatial reuse. We demonstrate the existence of the Nash equilibrium, and derive equilibrium flow settings. Finally, we provide numerical results of the proposed spectrum access game in several cognitive radio scenarios, and study the impact of the interference between SUs on the game efficiency. Our results indicate that the congestion cost functions we propose in this paper lead to small gaps between Nash equilibria and optimal solutions in all the considered network scenarios, thus representing a starting point for designing pricing mechanisms so as to obtain a socially optimal use of the network.",antonio capone,Game Theory,2010.0,,"8th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Elias2010,False,,IEEE,Not available,Competitive interference-aware spectrum access in cognitive radio networks,c33f127f150625858296fb853f6525df,https://ieeexplore.ieee.org/document/5519538/
1198,"Cognitive radio networks provide the capability to share the wireless channel with licensed (primary) users in an opportunistic manner. Primary users have a license to operate in a certain spectrum band; their access can only be controlled by the Primary Operator and is not affected by any other unlicensed (secondary) user. On the other hand, secondary users (SUs) have no spectrum license, and they attempt to exploit the spectral gaps left free by primary users. This work studies the spectrum access problem in cognitive radio networks from a game theoretical perspective. The problem is modeled as a non-cooperative spectrum access game where secondary users access simultaneously multiple spectrum bands left available by primary users, optimizing their objective function which takes into account the congestion level observed on the available spectrum bands. As a key innovative feature with respect to existing works, we model accurately the interference between SUs, capturing the effect of spatial reuse. We demonstrate the existence of the Nash equilibrium, and derive equilibrium flow settings. Finally, we provide numerical results of the proposed spectrum access game in several cognitive radio scenarios, and study the impact of the interference between SUs on the game efficiency. Our results indicate that the congestion cost functions we propose in this paper lead to small gaps between Nash equilibria and optimal solutions in all the considered network scenarios, thus representing a starting point for designing pricing mechanisms so as to obtain a socially optimal use of the network.",antonio capone,Price of Anarchy,2010.0,,"8th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Elias2010,False,,IEEE,Not available,Competitive interference-aware spectrum access in cognitive radio networks,c33f127f150625858296fb853f6525df,https://ieeexplore.ieee.org/document/5519538/
1199,"Cognitive radio networks provide the capability to share the wireless channel with licensed (primary) users in an opportunistic manner. Primary users have a license to operate in a certain spectrum band; their access can only be controlled by the Primary Operator and is not affected by any other unlicensed (secondary) user. On the other hand, secondary users (SUs) have no spectrum license, and they attempt to exploit the spectral gaps left free by primary users. This work studies the spectrum access problem in cognitive radio networks from a game theoretical perspective. The problem is modeled as a non-cooperative spectrum access game where secondary users access simultaneously multiple spectrum bands left available by primary users, optimizing their objective function which takes into account the congestion level observed on the available spectrum bands. As a key innovative feature with respect to existing works, we model accurately the interference between SUs, capturing the effect of spatial reuse. We demonstrate the existence of the Nash equilibrium, and derive equilibrium flow settings. Finally, we provide numerical results of the proposed spectrum access game in several cognitive radio scenarios, and study the impact of the interference between SUs on the game efficiency. Our results indicate that the congestion cost functions we propose in this paper lead to small gaps between Nash equilibria and optimal solutions in all the considered network scenarios, thus representing a starting point for designing pricing mechanisms so as to obtain a socially optimal use of the network.",eitan altman,Cognitive Radio Networks,2010.0,,"8th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Elias2010,False,,IEEE,Not available,Competitive interference-aware spectrum access in cognitive radio networks,c33f127f150625858296fb853f6525df,https://ieeexplore.ieee.org/document/5519538/
1200,"Cognitive radio networks provide the capability to share the wireless channel with licensed (primary) users in an opportunistic manner. Primary users have a license to operate in a certain spectrum band; their access can only be controlled by the Primary Operator and is not affected by any other unlicensed (secondary) user. On the other hand, secondary users (SUs) have no spectrum license, and they attempt to exploit the spectral gaps left free by primary users. This work studies the spectrum access problem in cognitive radio networks from a game theoretical perspective. The problem is modeled as a non-cooperative spectrum access game where secondary users access simultaneously multiple spectrum bands left available by primary users, optimizing their objective function which takes into account the congestion level observed on the available spectrum bands. As a key innovative feature with respect to existing works, we model accurately the interference between SUs, capturing the effect of spatial reuse. We demonstrate the existence of the Nash equilibrium, and derive equilibrium flow settings. Finally, we provide numerical results of the proposed spectrum access game in several cognitive radio scenarios, and study the impact of the interference between SUs on the game efficiency. Our results indicate that the congestion cost functions we propose in this paper lead to small gaps between Nash equilibria and optimal solutions in all the considered network scenarios, thus representing a starting point for designing pricing mechanisms so as to obtain a socially optimal use of the network.",eitan altman,Spectrum access,2010.0,,"8th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Elias2010,False,,IEEE,Not available,Competitive interference-aware spectrum access in cognitive radio networks,c33f127f150625858296fb853f6525df,https://ieeexplore.ieee.org/document/5519538/
1201,"Cognitive radio networks provide the capability to share the wireless channel with licensed (primary) users in an opportunistic manner. Primary users have a license to operate in a certain spectrum band; their access can only be controlled by the Primary Operator and is not affected by any other unlicensed (secondary) user. On the other hand, secondary users (SUs) have no spectrum license, and they attempt to exploit the spectral gaps left free by primary users. This work studies the spectrum access problem in cognitive radio networks from a game theoretical perspective. The problem is modeled as a non-cooperative spectrum access game where secondary users access simultaneously multiple spectrum bands left available by primary users, optimizing their objective function which takes into account the congestion level observed on the available spectrum bands. As a key innovative feature with respect to existing works, we model accurately the interference between SUs, capturing the effect of spatial reuse. We demonstrate the existence of the Nash equilibrium, and derive equilibrium flow settings. Finally, we provide numerical results of the proposed spectrum access game in several cognitive radio scenarios, and study the impact of the interference between SUs on the game efficiency. Our results indicate that the congestion cost functions we propose in this paper lead to small gaps between Nash equilibria and optimal solutions in all the considered network scenarios, thus representing a starting point for designing pricing mechanisms so as to obtain a socially optimal use of the network.",eitan altman,Game Theory,2010.0,,"8th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Elias2010,False,,IEEE,Not available,Competitive interference-aware spectrum access in cognitive radio networks,c33f127f150625858296fb853f6525df,https://ieeexplore.ieee.org/document/5519538/
1202,"Cognitive radio networks provide the capability to share the wireless channel with licensed (primary) users in an opportunistic manner. Primary users have a license to operate in a certain spectrum band; their access can only be controlled by the Primary Operator and is not affected by any other unlicensed (secondary) user. On the other hand, secondary users (SUs) have no spectrum license, and they attempt to exploit the spectral gaps left free by primary users. This work studies the spectrum access problem in cognitive radio networks from a game theoretical perspective. The problem is modeled as a non-cooperative spectrum access game where secondary users access simultaneously multiple spectrum bands left available by primary users, optimizing their objective function which takes into account the congestion level observed on the available spectrum bands. As a key innovative feature with respect to existing works, we model accurately the interference between SUs, capturing the effect of spatial reuse. We demonstrate the existence of the Nash equilibrium, and derive equilibrium flow settings. Finally, we provide numerical results of the proposed spectrum access game in several cognitive radio scenarios, and study the impact of the interference between SUs on the game efficiency. Our results indicate that the congestion cost functions we propose in this paper lead to small gaps between Nash equilibria and optimal solutions in all the considered network scenarios, thus representing a starting point for designing pricing mechanisms so as to obtain a socially optimal use of the network.",eitan altman,Price of Anarchy,2010.0,,"8th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Elias2010,False,,IEEE,Not available,Competitive interference-aware spectrum access in cognitive radio networks,c33f127f150625858296fb853f6525df,https://ieeexplore.ieee.org/document/5519538/
1203,"We study a network security game where strategic players choose their investments in security. Since a player's investment can reduce the propagation of computer viruses, a key feature of the game is the positive externality exerted by the investment. With selfish players, unfortunately, the overall network security can be far from optimum. The contributions of this paper are as follows. 1) We first characterize the price of anarchy (POA) in the strategic-form game under an “Effective-investment” model and a “Bad-traffic” model, and give insight on how the POA depends on individual players' cost functions and their mutual influence. We also introduce the concept of “weighted POA” to bound the region of payoff vectors. 2) In a repeated game, players have more incentive to cooperate for their long term interests. We consider the socially best outcome that can be supported by the repeated game, as compared to the social optimum. 3) Next, we compare the benefits of improving security technology and improving incentives, and show that improving technology alone may not offset the price of anarchy. 4) Finally, we characterize the performance of correlated equilibrium (CE). Although the paper focuses on network security, many results are generally applicable to games with positive externalities .",libin jiang,Correlated equilibrium (CE),2011.0,10.1109/TNET.2010.2071397,IEEE/ACM Transactions on Networking,Jiang2011,False,,IEEE,Not available,How Bad Are Selfish Investments in Network Security?,b998a0b4a2948c4632b037e584709110,https://ieeexplore.ieee.org/document/5575384/
1204,"We study a network security game where strategic players choose their investments in security. Since a player's investment can reduce the propagation of computer viruses, a key feature of the game is the positive externality exerted by the investment. With selfish players, unfortunately, the overall network security can be far from optimum. The contributions of this paper are as follows. 1) We first characterize the price of anarchy (POA) in the strategic-form game under an “Effective-investment” model and a “Bad-traffic” model, and give insight on how the POA depends on individual players' cost functions and their mutual influence. We also introduce the concept of “weighted POA” to bound the region of payoff vectors. 2) In a repeated game, players have more incentive to cooperate for their long term interests. We consider the socially best outcome that can be supported by the repeated game, as compared to the social optimum. 3) Next, we compare the benefits of improving security technology and improving incentives, and show that improving technology alone may not offset the price of anarchy. 4) Finally, we characterize the performance of correlated equilibrium (CE). Although the paper focuses on network security, many results are generally applicable to games with positive externalities .",libin jiang,game theory,2011.0,10.1109/TNET.2010.2071397,IEEE/ACM Transactions on Networking,Jiang2011,False,,IEEE,Not available,How Bad Are Selfish Investments in Network Security?,b998a0b4a2948c4632b037e584709110,https://ieeexplore.ieee.org/document/5575384/
1205,"We study a network security game where strategic players choose their investments in security. Since a player's investment can reduce the propagation of computer viruses, a key feature of the game is the positive externality exerted by the investment. With selfish players, unfortunately, the overall network security can be far from optimum. The contributions of this paper are as follows. 1) We first characterize the price of anarchy (POA) in the strategic-form game under an “Effective-investment” model and a “Bad-traffic” model, and give insight on how the POA depends on individual players' cost functions and their mutual influence. We also introduce the concept of “weighted POA” to bound the region of payoff vectors. 2) In a repeated game, players have more incentive to cooperate for their long term interests. We consider the socially best outcome that can be supported by the repeated game, as compared to the social optimum. 3) Next, we compare the benefits of improving security technology and improving incentives, and show that improving technology alone may not offset the price of anarchy. 4) Finally, we characterize the performance of correlated equilibrium (CE). Although the paper focuses on network security, many results are generally applicable to games with positive externalities .",libin jiang,network security,2011.0,10.1109/TNET.2010.2071397,IEEE/ACM Transactions on Networking,Jiang2011,False,,IEEE,Not available,How Bad Are Selfish Investments in Network Security?,b998a0b4a2948c4632b037e584709110,https://ieeexplore.ieee.org/document/5575384/
1206,"We study a network security game where strategic players choose their investments in security. Since a player's investment can reduce the propagation of computer viruses, a key feature of the game is the positive externality exerted by the investment. With selfish players, unfortunately, the overall network security can be far from optimum. The contributions of this paper are as follows. 1) We first characterize the price of anarchy (POA) in the strategic-form game under an “Effective-investment” model and a “Bad-traffic” model, and give insight on how the POA depends on individual players' cost functions and their mutual influence. We also introduce the concept of “weighted POA” to bound the region of payoff vectors. 2) In a repeated game, players have more incentive to cooperate for their long term interests. We consider the socially best outcome that can be supported by the repeated game, as compared to the social optimum. 3) Next, we compare the benefits of improving security technology and improving incentives, and show that improving technology alone may not offset the price of anarchy. 4) Finally, we characterize the performance of correlated equilibrium (CE). Although the paper focuses on network security, many results are generally applicable to games with positive externalities .",libin jiang,positive externality,2011.0,10.1109/TNET.2010.2071397,IEEE/ACM Transactions on Networking,Jiang2011,False,,IEEE,Not available,How Bad Are Selfish Investments in Network Security?,b998a0b4a2948c4632b037e584709110,https://ieeexplore.ieee.org/document/5575384/
1207,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
1208,"We study a network security game where strategic players choose their investments in security. Since a player's investment can reduce the propagation of computer viruses, a key feature of the game is the positive externality exerted by the investment. With selfish players, unfortunately, the overall network security can be far from optimum. The contributions of this paper are as follows. 1) We first characterize the price of anarchy (POA) in the strategic-form game under an “Effective-investment” model and a “Bad-traffic” model, and give insight on how the POA depends on individual players' cost functions and their mutual influence. We also introduce the concept of “weighted POA” to bound the region of payoff vectors. 2) In a repeated game, players have more incentive to cooperate for their long term interests. We consider the socially best outcome that can be supported by the repeated game, as compared to the social optimum. 3) Next, we compare the benefits of improving security technology and improving incentives, and show that improving technology alone may not offset the price of anarchy. 4) Finally, we characterize the performance of correlated equilibrium (CE). Although the paper focuses on network security, many results are generally applicable to games with positive externalities .",libin jiang,price of anarchy (POA),2011.0,10.1109/TNET.2010.2071397,IEEE/ACM Transactions on Networking,Jiang2011,False,,IEEE,Not available,How Bad Are Selfish Investments in Network Security?,b998a0b4a2948c4632b037e584709110,https://ieeexplore.ieee.org/document/5575384/
1209,"We study a network security game where strategic players choose their investments in security. Since a player's investment can reduce the propagation of computer viruses, a key feature of the game is the positive externality exerted by the investment. With selfish players, unfortunately, the overall network security can be far from optimum. The contributions of this paper are as follows. 1) We first characterize the price of anarchy (POA) in the strategic-form game under an “Effective-investment” model and a “Bad-traffic” model, and give insight on how the POA depends on individual players' cost functions and their mutual influence. We also introduce the concept of “weighted POA” to bound the region of payoff vectors. 2) In a repeated game, players have more incentive to cooperate for their long term interests. We consider the socially best outcome that can be supported by the repeated game, as compared to the social optimum. 3) Next, we compare the benefits of improving security technology and improving incentives, and show that improving technology alone may not offset the price of anarchy. 4) Finally, we characterize the performance of correlated equilibrium (CE). Although the paper focuses on network security, many results are generally applicable to games with positive externalities .",libin jiang,repeated game,2011.0,10.1109/TNET.2010.2071397,IEEE/ACM Transactions on Networking,Jiang2011,False,,IEEE,Not available,How Bad Are Selfish Investments in Network Security?,b998a0b4a2948c4632b037e584709110,https://ieeexplore.ieee.org/document/5575384/
1210,"We study a network security game where strategic players choose their investments in security. Since a player's investment can reduce the propagation of computer viruses, a key feature of the game is the positive externality exerted by the investment. With selfish players, unfortunately, the overall network security can be far from optimum. The contributions of this paper are as follows. 1) We first characterize the price of anarchy (POA) in the strategic-form game under an “Effective-investment” model and a “Bad-traffic” model, and give insight on how the POA depends on individual players' cost functions and their mutual influence. We also introduce the concept of “weighted POA” to bound the region of payoff vectors. 2) In a repeated game, players have more incentive to cooperate for their long term interests. We consider the socially best outcome that can be supported by the repeated game, as compared to the social optimum. 3) Next, we compare the benefits of improving security technology and improving incentives, and show that improving technology alone may not offset the price of anarchy. 4) Finally, we characterize the performance of correlated equilibrium (CE). Although the paper focuses on network security, many results are generally applicable to games with positive externalities .",venkat anantharam,Correlated equilibrium (CE),2011.0,10.1109/TNET.2010.2071397,IEEE/ACM Transactions on Networking,Jiang2011,False,,IEEE,Not available,How Bad Are Selfish Investments in Network Security?,b998a0b4a2948c4632b037e584709110,https://ieeexplore.ieee.org/document/5575384/
1211,"We study a network security game where strategic players choose their investments in security. Since a player's investment can reduce the propagation of computer viruses, a key feature of the game is the positive externality exerted by the investment. With selfish players, unfortunately, the overall network security can be far from optimum. The contributions of this paper are as follows. 1) We first characterize the price of anarchy (POA) in the strategic-form game under an “Effective-investment” model and a “Bad-traffic” model, and give insight on how the POA depends on individual players' cost functions and their mutual influence. We also introduce the concept of “weighted POA” to bound the region of payoff vectors. 2) In a repeated game, players have more incentive to cooperate for their long term interests. We consider the socially best outcome that can be supported by the repeated game, as compared to the social optimum. 3) Next, we compare the benefits of improving security technology and improving incentives, and show that improving technology alone may not offset the price of anarchy. 4) Finally, we characterize the performance of correlated equilibrium (CE). Although the paper focuses on network security, many results are generally applicable to games with positive externalities .",venkat anantharam,game theory,2011.0,10.1109/TNET.2010.2071397,IEEE/ACM Transactions on Networking,Jiang2011,False,,IEEE,Not available,How Bad Are Selfish Investments in Network Security?,b998a0b4a2948c4632b037e584709110,https://ieeexplore.ieee.org/document/5575384/
1212,"We study a network security game where strategic players choose their investments in security. Since a player's investment can reduce the propagation of computer viruses, a key feature of the game is the positive externality exerted by the investment. With selfish players, unfortunately, the overall network security can be far from optimum. The contributions of this paper are as follows. 1) We first characterize the price of anarchy (POA) in the strategic-form game under an “Effective-investment” model and a “Bad-traffic” model, and give insight on how the POA depends on individual players' cost functions and their mutual influence. We also introduce the concept of “weighted POA” to bound the region of payoff vectors. 2) In a repeated game, players have more incentive to cooperate for their long term interests. We consider the socially best outcome that can be supported by the repeated game, as compared to the social optimum. 3) Next, we compare the benefits of improving security technology and improving incentives, and show that improving technology alone may not offset the price of anarchy. 4) Finally, we characterize the performance of correlated equilibrium (CE). Although the paper focuses on network security, many results are generally applicable to games with positive externalities .",venkat anantharam,network security,2011.0,10.1109/TNET.2010.2071397,IEEE/ACM Transactions on Networking,Jiang2011,False,,IEEE,Not available,How Bad Are Selfish Investments in Network Security?,b998a0b4a2948c4632b037e584709110,https://ieeexplore.ieee.org/document/5575384/
1213,"We study a network security game where strategic players choose their investments in security. Since a player's investment can reduce the propagation of computer viruses, a key feature of the game is the positive externality exerted by the investment. With selfish players, unfortunately, the overall network security can be far from optimum. The contributions of this paper are as follows. 1) We first characterize the price of anarchy (POA) in the strategic-form game under an “Effective-investment” model and a “Bad-traffic” model, and give insight on how the POA depends on individual players' cost functions and their mutual influence. We also introduce the concept of “weighted POA” to bound the region of payoff vectors. 2) In a repeated game, players have more incentive to cooperate for their long term interests. We consider the socially best outcome that can be supported by the repeated game, as compared to the social optimum. 3) Next, we compare the benefits of improving security technology and improving incentives, and show that improving technology alone may not offset the price of anarchy. 4) Finally, we characterize the performance of correlated equilibrium (CE). Although the paper focuses on network security, many results are generally applicable to games with positive externalities .",venkat anantharam,positive externality,2011.0,10.1109/TNET.2010.2071397,IEEE/ACM Transactions on Networking,Jiang2011,False,,IEEE,Not available,How Bad Are Selfish Investments in Network Security?,b998a0b4a2948c4632b037e584709110,https://ieeexplore.ieee.org/document/5575384/
1214,"We study a network security game where strategic players choose their investments in security. Since a player's investment can reduce the propagation of computer viruses, a key feature of the game is the positive externality exerted by the investment. With selfish players, unfortunately, the overall network security can be far from optimum. The contributions of this paper are as follows. 1) We first characterize the price of anarchy (POA) in the strategic-form game under an “Effective-investment” model and a “Bad-traffic” model, and give insight on how the POA depends on individual players' cost functions and their mutual influence. We also introduce the concept of “weighted POA” to bound the region of payoff vectors. 2) In a repeated game, players have more incentive to cooperate for their long term interests. We consider the socially best outcome that can be supported by the repeated game, as compared to the social optimum. 3) Next, we compare the benefits of improving security technology and improving incentives, and show that improving technology alone may not offset the price of anarchy. 4) Finally, we characterize the performance of correlated equilibrium (CE). Although the paper focuses on network security, many results are generally applicable to games with positive externalities .",venkat anantharam,price of anarchy (POA),2011.0,10.1109/TNET.2010.2071397,IEEE/ACM Transactions on Networking,Jiang2011,False,,IEEE,Not available,How Bad Are Selfish Investments in Network Security?,b998a0b4a2948c4632b037e584709110,https://ieeexplore.ieee.org/document/5575384/
1215,"We study a network security game where strategic players choose their investments in security. Since a player's investment can reduce the propagation of computer viruses, a key feature of the game is the positive externality exerted by the investment. With selfish players, unfortunately, the overall network security can be far from optimum. The contributions of this paper are as follows. 1) We first characterize the price of anarchy (POA) in the strategic-form game under an “Effective-investment” model and a “Bad-traffic” model, and give insight on how the POA depends on individual players' cost functions and their mutual influence. We also introduce the concept of “weighted POA” to bound the region of payoff vectors. 2) In a repeated game, players have more incentive to cooperate for their long term interests. We consider the socially best outcome that can be supported by the repeated game, as compared to the social optimum. 3) Next, we compare the benefits of improving security technology and improving incentives, and show that improving technology alone may not offset the price of anarchy. 4) Finally, we characterize the performance of correlated equilibrium (CE). Although the paper focuses on network security, many results are generally applicable to games with positive externalities .",venkat anantharam,repeated game,2011.0,10.1109/TNET.2010.2071397,IEEE/ACM Transactions on Networking,Jiang2011,False,,IEEE,Not available,How Bad Are Selfish Investments in Network Security?,b998a0b4a2948c4632b037e584709110,https://ieeexplore.ieee.org/document/5575384/
1216,"We study a network security game where strategic players choose their investments in security. Since a player's investment can reduce the propagation of computer viruses, a key feature of the game is the positive externality exerted by the investment. With selfish players, unfortunately, the overall network security can be far from optimum. The contributions of this paper are as follows. 1) We first characterize the price of anarchy (POA) in the strategic-form game under an “Effective-investment” model and a “Bad-traffic” model, and give insight on how the POA depends on individual players' cost functions and their mutual influence. We also introduce the concept of “weighted POA” to bound the region of payoff vectors. 2) In a repeated game, players have more incentive to cooperate for their long term interests. We consider the socially best outcome that can be supported by the repeated game, as compared to the social optimum. 3) Next, we compare the benefits of improving security technology and improving incentives, and show that improving technology alone may not offset the price of anarchy. 4) Finally, we characterize the performance of correlated equilibrium (CE). Although the paper focuses on network security, many results are generally applicable to games with positive externalities .",jean walrand,Correlated equilibrium (CE),2011.0,10.1109/TNET.2010.2071397,IEEE/ACM Transactions on Networking,Jiang2011,False,,IEEE,Not available,How Bad Are Selfish Investments in Network Security?,b998a0b4a2948c4632b037e584709110,https://ieeexplore.ieee.org/document/5575384/
1217,"We study a network security game where strategic players choose their investments in security. Since a player's investment can reduce the propagation of computer viruses, a key feature of the game is the positive externality exerted by the investment. With selfish players, unfortunately, the overall network security can be far from optimum. The contributions of this paper are as follows. 1) We first characterize the price of anarchy (POA) in the strategic-form game under an “Effective-investment” model and a “Bad-traffic” model, and give insight on how the POA depends on individual players' cost functions and their mutual influence. We also introduce the concept of “weighted POA” to bound the region of payoff vectors. 2) In a repeated game, players have more incentive to cooperate for their long term interests. We consider the socially best outcome that can be supported by the repeated game, as compared to the social optimum. 3) Next, we compare the benefits of improving security technology and improving incentives, and show that improving technology alone may not offset the price of anarchy. 4) Finally, we characterize the performance of correlated equilibrium (CE). Although the paper focuses on network security, many results are generally applicable to games with positive externalities .",jean walrand,game theory,2011.0,10.1109/TNET.2010.2071397,IEEE/ACM Transactions on Networking,Jiang2011,False,,IEEE,Not available,How Bad Are Selfish Investments in Network Security?,b998a0b4a2948c4632b037e584709110,https://ieeexplore.ieee.org/document/5575384/
1218,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
1219,"We study a network security game where strategic players choose their investments in security. Since a player's investment can reduce the propagation of computer viruses, a key feature of the game is the positive externality exerted by the investment. With selfish players, unfortunately, the overall network security can be far from optimum. The contributions of this paper are as follows. 1) We first characterize the price of anarchy (POA) in the strategic-form game under an “Effective-investment” model and a “Bad-traffic” model, and give insight on how the POA depends on individual players' cost functions and their mutual influence. We also introduce the concept of “weighted POA” to bound the region of payoff vectors. 2) In a repeated game, players have more incentive to cooperate for their long term interests. We consider the socially best outcome that can be supported by the repeated game, as compared to the social optimum. 3) Next, we compare the benefits of improving security technology and improving incentives, and show that improving technology alone may not offset the price of anarchy. 4) Finally, we characterize the performance of correlated equilibrium (CE). Although the paper focuses on network security, many results are generally applicable to games with positive externalities .",jean walrand,network security,2011.0,10.1109/TNET.2010.2071397,IEEE/ACM Transactions on Networking,Jiang2011,False,,IEEE,Not available,How Bad Are Selfish Investments in Network Security?,b998a0b4a2948c4632b037e584709110,https://ieeexplore.ieee.org/document/5575384/
1220,"We study a network security game where strategic players choose their investments in security. Since a player's investment can reduce the propagation of computer viruses, a key feature of the game is the positive externality exerted by the investment. With selfish players, unfortunately, the overall network security can be far from optimum. The contributions of this paper are as follows. 1) We first characterize the price of anarchy (POA) in the strategic-form game under an “Effective-investment” model and a “Bad-traffic” model, and give insight on how the POA depends on individual players' cost functions and their mutual influence. We also introduce the concept of “weighted POA” to bound the region of payoff vectors. 2) In a repeated game, players have more incentive to cooperate for their long term interests. We consider the socially best outcome that can be supported by the repeated game, as compared to the social optimum. 3) Next, we compare the benefits of improving security technology and improving incentives, and show that improving technology alone may not offset the price of anarchy. 4) Finally, we characterize the performance of correlated equilibrium (CE). Although the paper focuses on network security, many results are generally applicable to games with positive externalities .",jean walrand,positive externality,2011.0,10.1109/TNET.2010.2071397,IEEE/ACM Transactions on Networking,Jiang2011,False,,IEEE,Not available,How Bad Are Selfish Investments in Network Security?,b998a0b4a2948c4632b037e584709110,https://ieeexplore.ieee.org/document/5575384/
1221,"We study a network security game where strategic players choose their investments in security. Since a player's investment can reduce the propagation of computer viruses, a key feature of the game is the positive externality exerted by the investment. With selfish players, unfortunately, the overall network security can be far from optimum. The contributions of this paper are as follows. 1) We first characterize the price of anarchy (POA) in the strategic-form game under an “Effective-investment” model and a “Bad-traffic” model, and give insight on how the POA depends on individual players' cost functions and their mutual influence. We also introduce the concept of “weighted POA” to bound the region of payoff vectors. 2) In a repeated game, players have more incentive to cooperate for their long term interests. We consider the socially best outcome that can be supported by the repeated game, as compared to the social optimum. 3) Next, we compare the benefits of improving security technology and improving incentives, and show that improving technology alone may not offset the price of anarchy. 4) Finally, we characterize the performance of correlated equilibrium (CE). Although the paper focuses on network security, many results are generally applicable to games with positive externalities .",jean walrand,price of anarchy (POA),2011.0,10.1109/TNET.2010.2071397,IEEE/ACM Transactions on Networking,Jiang2011,False,,IEEE,Not available,How Bad Are Selfish Investments in Network Security?,b998a0b4a2948c4632b037e584709110,https://ieeexplore.ieee.org/document/5575384/
1222,"We study a network security game where strategic players choose their investments in security. Since a player's investment can reduce the propagation of computer viruses, a key feature of the game is the positive externality exerted by the investment. With selfish players, unfortunately, the overall network security can be far from optimum. The contributions of this paper are as follows. 1) We first characterize the price of anarchy (POA) in the strategic-form game under an “Effective-investment” model and a “Bad-traffic” model, and give insight on how the POA depends on individual players' cost functions and their mutual influence. We also introduce the concept of “weighted POA” to bound the region of payoff vectors. 2) In a repeated game, players have more incentive to cooperate for their long term interests. We consider the socially best outcome that can be supported by the repeated game, as compared to the social optimum. 3) Next, we compare the benefits of improving security technology and improving incentives, and show that improving technology alone may not offset the price of anarchy. 4) Finally, we characterize the performance of correlated equilibrium (CE). Although the paper focuses on network security, many results are generally applicable to games with positive externalities .",jean walrand,repeated game,2011.0,10.1109/TNET.2010.2071397,IEEE/ACM Transactions on Networking,Jiang2011,False,,IEEE,Not available,How Bad Are Selfish Investments in Network Security?,b998a0b4a2948c4632b037e584709110,https://ieeexplore.ieee.org/document/5575384/
1223,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",joshua davis,social networks,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1224,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",joshua davis,game theory,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1225,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",joshua davis,price of anarchy,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1226,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",joshua davis,Nash equilibria,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1227,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",joshua davis,coordination games,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1228,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",zachary goldman,social networks,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1229,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
1230,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",zachary goldman,game theory,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1231,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",zachary goldman,price of anarchy,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1232,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",zachary goldman,Nash equilibria,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1233,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",zachary goldman,coordination games,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1234,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",jacob hilty,social networks,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1235,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",jacob hilty,game theory,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1236,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",jacob hilty,price of anarchy,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1237,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",jacob hilty,Nash equilibria,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1238,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",jacob hilty,coordination games,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1239,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",elizabeth koch,social networks,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1240,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
1241,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",elizabeth koch,game theory,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1242,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",elizabeth koch,price of anarchy,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1243,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",elizabeth koch,Nash equilibria,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1244,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",elizabeth koch,coordination games,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1245,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",david liben-nowell,social networks,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1246,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",david liben-nowell,game theory,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1247,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",david liben-nowell,price of anarchy,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1248,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",david liben-nowell,Nash equilibria,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1249,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",david liben-nowell,coordination games,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1250,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",alexa sharp,social networks,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1251,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
1252,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",alexa sharp,game theory,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1253,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",alexa sharp,price of anarchy,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1254,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",alexa sharp,Nash equilibria,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1255,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",alexa sharp,coordination games,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1256,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",tom wexler,social networks,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1257,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",tom wexler,game theory,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1258,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",tom wexler,price of anarchy,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1259,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",tom wexler,Nash equilibria,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1260,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",tom wexler,coordination games,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1261,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",emma zhou,social networks,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1262,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
1263,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",emma zhou,game theory,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1264,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",emma zhou,price of anarchy,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1265,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",emma zhou,Nash equilibria,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1266,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",emma zhou,coordination games,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
1267,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",baudelio baez,Optical Networks,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
1268,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",baudelio baez,Wavelength Converter Allocation,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
1269,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",baudelio baez,Cooperative Routing,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
1270,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",baudelio baez,Selfish Routing,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
1271,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",baudelio baez,Anarchy Price,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
1272,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",baudelio baez,Multi-objective Optimization,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
1273,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
1274,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",baudelio baez,Evolutionary Algorithms,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
1275,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",jose colbes,Optical Networks,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
1276,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",jose colbes,Wavelength Converter Allocation,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
1277,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",jose colbes,Cooperative Routing,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
1278,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",jose colbes,Selfish Routing,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
1279,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",jose colbes,Anarchy Price,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
1280,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",jose colbes,Multi-objective Optimization,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
1281,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",jose colbes,Evolutionary Algorithms,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
1282,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",diego pinto-roa,Optical Networks,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
1283,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",diego pinto-roa,Wavelength Converter Allocation,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
1284,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
1285,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",diego pinto-roa,Cooperative Routing,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
1286,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",diego pinto-roa,Selfish Routing,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
1287,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",diego pinto-roa,Anarchy Price,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
1288,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",diego pinto-roa,Multi-objective Optimization,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
1289,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",diego pinto-roa,Evolutionary Algorithms,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
1290,"This paper studies the performance of Mobile Ad hoc Networks (MANETs) when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We consider goodput and delay as the performance metric that each node is interested in optimizing taking into account the transmission energy costs. We introduce a pricing scheme based on the transmission energy requirements and compute the symmetric Nash equilibria of the game in closed form. It is shown that by appropriately pricing the nodes, the selfish behavior of the nodes can be used to achieve the social optimum at equilibrium. The price of anarchy is then analyzed for these games. For the game with delay based utility, we bound the price of anarchy and study the effect of the price factor. For the game with goodput based utility, it is shown that price of anarchy is infinite at the price factor that achieves the global optima.",m.k. hanawal,Game Theory,2012.0,10.1109/INFCOM.2012.6195554,2012 Proceedings IEEE INFOCOM,Hanawal2012,False,,IEEE,Not available,Stochastic geometry based medium access games,d91dc35b4e99845860d323b3bc42cb30,https://ieeexplore.ieee.org/document/6195554/
1291,"This paper studies the performance of Mobile Ad hoc Networks (MANETs) when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We consider goodput and delay as the performance metric that each node is interested in optimizing taking into account the transmission energy costs. We introduce a pricing scheme based on the transmission energy requirements and compute the symmetric Nash equilibria of the game in closed form. It is shown that by appropriately pricing the nodes, the selfish behavior of the nodes can be used to achieve the social optimum at equilibrium. The price of anarchy is then analyzed for these games. For the game with delay based utility, we bound the price of anarchy and study the effect of the price factor. For the game with goodput based utility, it is shown that price of anarchy is infinite at the price factor that achieves the global optima.",m.k. hanawal,Mobile Ad hoc Networks (MANETs),2012.0,10.1109/INFCOM.2012.6195554,2012 Proceedings IEEE INFOCOM,Hanawal2012,False,,IEEE,Not available,Stochastic geometry based medium access games,d91dc35b4e99845860d323b3bc42cb30,https://ieeexplore.ieee.org/document/6195554/
1292,"This paper studies the performance of Mobile Ad hoc Networks (MANETs) when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We consider goodput and delay as the performance metric that each node is interested in optimizing taking into account the transmission energy costs. We introduce a pricing scheme based on the transmission energy requirements and compute the symmetric Nash equilibria of the game in closed form. It is shown that by appropriately pricing the nodes, the selfish behavior of the nodes can be used to achieve the social optimum at equilibrium. The price of anarchy is then analyzed for these games. For the game with delay based utility, we bound the price of anarchy and study the effect of the price factor. For the game with goodput based utility, it is shown that price of anarchy is infinite at the price factor that achieves the global optima.",m.k. hanawal,Pricing,2012.0,10.1109/INFCOM.2012.6195554,2012 Proceedings IEEE INFOCOM,Hanawal2012,False,,IEEE,Not available,Stochastic geometry based medium access games,d91dc35b4e99845860d323b3bc42cb30,https://ieeexplore.ieee.org/document/6195554/
1293,"This paper studies the performance of Mobile Ad hoc Networks (MANETs) when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We consider goodput and delay as the performance metric that each node is interested in optimizing taking into account the transmission energy costs. We introduce a pricing scheme based on the transmission energy requirements and compute the symmetric Nash equilibria of the game in closed form. It is shown that by appropriately pricing the nodes, the selfish behavior of the nodes can be used to achieve the social optimum at equilibrium. The price of anarchy is then analyzed for these games. For the game with delay based utility, we bound the price of anarchy and study the effect of the price factor. For the game with goodput based utility, it is shown that price of anarchy is infinite at the price factor that achieves the global optima.",m.k. hanawal,Medium Access Control,2012.0,10.1109/INFCOM.2012.6195554,2012 Proceedings IEEE INFOCOM,Hanawal2012,False,,IEEE,Not available,Stochastic geometry based medium access games,d91dc35b4e99845860d323b3bc42cb30,https://ieeexplore.ieee.org/document/6195554/
1294,"This paper studies the performance of Mobile Ad hoc Networks (MANETs) when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We consider goodput and delay as the performance metric that each node is interested in optimizing taking into account the transmission energy costs. We introduce a pricing scheme based on the transmission energy requirements and compute the symmetric Nash equilibria of the game in closed form. It is shown that by appropriately pricing the nodes, the selfish behavior of the nodes can be used to achieve the social optimum at equilibrium. The price of anarchy is then analyzed for these games. For the game with delay based utility, we bound the price of anarchy and study the effect of the price factor. For the game with goodput based utility, it is shown that price of anarchy is infinite at the price factor that achieves the global optima.",m.k. hanawal,Stochastic Geometry,2012.0,10.1109/INFCOM.2012.6195554,2012 Proceedings IEEE INFOCOM,Hanawal2012,False,,IEEE,Not available,Stochastic geometry based medium access games,d91dc35b4e99845860d323b3bc42cb30,https://ieeexplore.ieee.org/document/6195554/
1295,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
1296,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA > 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
1297,"This paper studies the performance of Mobile Ad hoc Networks (MANETs) when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We consider goodput and delay as the performance metric that each node is interested in optimizing taking into account the transmission energy costs. We introduce a pricing scheme based on the transmission energy requirements and compute the symmetric Nash equilibria of the game in closed form. It is shown that by appropriately pricing the nodes, the selfish behavior of the nodes can be used to achieve the social optimum at equilibrium. The price of anarchy is then analyzed for these games. For the game with delay based utility, we bound the price of anarchy and study the effect of the price factor. For the game with goodput based utility, it is shown that price of anarchy is infinite at the price factor that achieves the global optima.",e. altman,Game Theory,2012.0,10.1109/INFCOM.2012.6195554,2012 Proceedings IEEE INFOCOM,Hanawal2012,False,,IEEE,Not available,Stochastic geometry based medium access games,d91dc35b4e99845860d323b3bc42cb30,https://ieeexplore.ieee.org/document/6195554/
1298,"This paper studies the performance of Mobile Ad hoc Networks (MANETs) when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We consider goodput and delay as the performance metric that each node is interested in optimizing taking into account the transmission energy costs. We introduce a pricing scheme based on the transmission energy requirements and compute the symmetric Nash equilibria of the game in closed form. It is shown that by appropriately pricing the nodes, the selfish behavior of the nodes can be used to achieve the social optimum at equilibrium. The price of anarchy is then analyzed for these games. For the game with delay based utility, we bound the price of anarchy and study the effect of the price factor. For the game with goodput based utility, it is shown that price of anarchy is infinite at the price factor that achieves the global optima.",e. altman,Mobile Ad hoc Networks (MANETs),2012.0,10.1109/INFCOM.2012.6195554,2012 Proceedings IEEE INFOCOM,Hanawal2012,False,,IEEE,Not available,Stochastic geometry based medium access games,d91dc35b4e99845860d323b3bc42cb30,https://ieeexplore.ieee.org/document/6195554/
1299,"This paper studies the performance of Mobile Ad hoc Networks (MANETs) when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We consider goodput and delay as the performance metric that each node is interested in optimizing taking into account the transmission energy costs. We introduce a pricing scheme based on the transmission energy requirements and compute the symmetric Nash equilibria of the game in closed form. It is shown that by appropriately pricing the nodes, the selfish behavior of the nodes can be used to achieve the social optimum at equilibrium. The price of anarchy is then analyzed for these games. For the game with delay based utility, we bound the price of anarchy and study the effect of the price factor. For the game with goodput based utility, it is shown that price of anarchy is infinite at the price factor that achieves the global optima.",e. altman,Pricing,2012.0,10.1109/INFCOM.2012.6195554,2012 Proceedings IEEE INFOCOM,Hanawal2012,False,,IEEE,Not available,Stochastic geometry based medium access games,d91dc35b4e99845860d323b3bc42cb30,https://ieeexplore.ieee.org/document/6195554/
1300,"This paper studies the performance of Mobile Ad hoc Networks (MANETs) when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We consider goodput and delay as the performance metric that each node is interested in optimizing taking into account the transmission energy costs. We introduce a pricing scheme based on the transmission energy requirements and compute the symmetric Nash equilibria of the game in closed form. It is shown that by appropriately pricing the nodes, the selfish behavior of the nodes can be used to achieve the social optimum at equilibrium. The price of anarchy is then analyzed for these games. For the game with delay based utility, we bound the price of anarchy and study the effect of the price factor. For the game with goodput based utility, it is shown that price of anarchy is infinite at the price factor that achieves the global optima.",e. altman,Medium Access Control,2012.0,10.1109/INFCOM.2012.6195554,2012 Proceedings IEEE INFOCOM,Hanawal2012,False,,IEEE,Not available,Stochastic geometry based medium access games,d91dc35b4e99845860d323b3bc42cb30,https://ieeexplore.ieee.org/document/6195554/
1301,"This paper studies the performance of Mobile Ad hoc Networks (MANETs) when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We consider goodput and delay as the performance metric that each node is interested in optimizing taking into account the transmission energy costs. We introduce a pricing scheme based on the transmission energy requirements and compute the symmetric Nash equilibria of the game in closed form. It is shown that by appropriately pricing the nodes, the selfish behavior of the nodes can be used to achieve the social optimum at equilibrium. The price of anarchy is then analyzed for these games. For the game with delay based utility, we bound the price of anarchy and study the effect of the price factor. For the game with goodput based utility, it is shown that price of anarchy is infinite at the price factor that achieves the global optima.",e. altman,Stochastic Geometry,2012.0,10.1109/INFCOM.2012.6195554,2012 Proceedings IEEE INFOCOM,Hanawal2012,False,,IEEE,Not available,Stochastic geometry based medium access games,d91dc35b4e99845860d323b3bc42cb30,https://ieeexplore.ieee.org/document/6195554/
1302,"This paper studies the performance of Mobile Ad hoc Networks (MANETs) when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We consider goodput and delay as the performance metric that each node is interested in optimizing taking into account the transmission energy costs. We introduce a pricing scheme based on the transmission energy requirements and compute the symmetric Nash equilibria of the game in closed form. It is shown that by appropriately pricing the nodes, the selfish behavior of the nodes can be used to achieve the social optimum at equilibrium. The price of anarchy is then analyzed for these games. For the game with delay based utility, we bound the price of anarchy and study the effect of the price factor. For the game with goodput based utility, it is shown that price of anarchy is infinite at the price factor that achieves the global optima.",f. baccelli,Game Theory,2012.0,10.1109/INFCOM.2012.6195554,2012 Proceedings IEEE INFOCOM,Hanawal2012,False,,IEEE,Not available,Stochastic geometry based medium access games,d91dc35b4e99845860d323b3bc42cb30,https://ieeexplore.ieee.org/document/6195554/
1303,"This paper studies the performance of Mobile Ad hoc Networks (MANETs) when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We consider goodput and delay as the performance metric that each node is interested in optimizing taking into account the transmission energy costs. We introduce a pricing scheme based on the transmission energy requirements and compute the symmetric Nash equilibria of the game in closed form. It is shown that by appropriately pricing the nodes, the selfish behavior of the nodes can be used to achieve the social optimum at equilibrium. The price of anarchy is then analyzed for these games. For the game with delay based utility, we bound the price of anarchy and study the effect of the price factor. For the game with goodput based utility, it is shown that price of anarchy is infinite at the price factor that achieves the global optima.",f. baccelli,Mobile Ad hoc Networks (MANETs),2012.0,10.1109/INFCOM.2012.6195554,2012 Proceedings IEEE INFOCOM,Hanawal2012,False,,IEEE,Not available,Stochastic geometry based medium access games,d91dc35b4e99845860d323b3bc42cb30,https://ieeexplore.ieee.org/document/6195554/
1304,"This paper studies the performance of Mobile Ad hoc Networks (MANETs) when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We consider goodput and delay as the performance metric that each node is interested in optimizing taking into account the transmission energy costs. We introduce a pricing scheme based on the transmission energy requirements and compute the symmetric Nash equilibria of the game in closed form. It is shown that by appropriately pricing the nodes, the selfish behavior of the nodes can be used to achieve the social optimum at equilibrium. The price of anarchy is then analyzed for these games. For the game with delay based utility, we bound the price of anarchy and study the effect of the price factor. For the game with goodput based utility, it is shown that price of anarchy is infinite at the price factor that achieves the global optima.",f. baccelli,Pricing,2012.0,10.1109/INFCOM.2012.6195554,2012 Proceedings IEEE INFOCOM,Hanawal2012,False,,IEEE,Not available,Stochastic geometry based medium access games,d91dc35b4e99845860d323b3bc42cb30,https://ieeexplore.ieee.org/document/6195554/
1305,"This paper studies the performance of Mobile Ad hoc Networks (MANETs) when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We consider goodput and delay as the performance metric that each node is interested in optimizing taking into account the transmission energy costs. We introduce a pricing scheme based on the transmission energy requirements and compute the symmetric Nash equilibria of the game in closed form. It is shown that by appropriately pricing the nodes, the selfish behavior of the nodes can be used to achieve the social optimum at equilibrium. The price of anarchy is then analyzed for these games. For the game with delay based utility, we bound the price of anarchy and study the effect of the price factor. For the game with goodput based utility, it is shown that price of anarchy is infinite at the price factor that achieves the global optima.",f. baccelli,Medium Access Control,2012.0,10.1109/INFCOM.2012.6195554,2012 Proceedings IEEE INFOCOM,Hanawal2012,False,,IEEE,Not available,Stochastic geometry based medium access games,d91dc35b4e99845860d323b3bc42cb30,https://ieeexplore.ieee.org/document/6195554/
1306,"This paper studies the performance of Mobile Ad hoc Networks (MANETs) when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We consider goodput and delay as the performance metric that each node is interested in optimizing taking into account the transmission energy costs. We introduce a pricing scheme based on the transmission energy requirements and compute the symmetric Nash equilibria of the game in closed form. It is shown that by appropriately pricing the nodes, the selfish behavior of the nodes can be used to achieve the social optimum at equilibrium. The price of anarchy is then analyzed for these games. For the game with delay based utility, we bound the price of anarchy and study the effect of the price factor. For the game with goodput based utility, it is shown that price of anarchy is infinite at the price factor that achieves the global optima.",f. baccelli,Stochastic Geometry,2012.0,10.1109/INFCOM.2012.6195554,2012 Proceedings IEEE INFOCOM,Hanawal2012,False,,IEEE,Not available,Stochastic geometry based medium access games,d91dc35b4e99845860d323b3bc42cb30,https://ieeexplore.ieee.org/document/6195554/
1307,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA > 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
1308,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",hamed mohsenian-rad,Inter-session network coding,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
1309,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",hamed mohsenian-rad,butterfly network,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
1310,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",hamed mohsenian-rad,game theory,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
1311,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",hamed mohsenian-rad,Nash equilibrium,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
1312,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",hamed mohsenian-rad,price-of-anarchy,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
1313,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",hamed mohsenian-rad,efficiency bound,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
1314,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",jianwei huang,Inter-session network coding,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
1315,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",jianwei huang,butterfly network,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
1316,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",jianwei huang,game theory,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
1317,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",jianwei huang,Nash equilibrium,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
1318,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA > 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
1319,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",jianwei huang,price-of-anarchy,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
1320,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",jianwei huang,efficiency bound,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
1321,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",vincent wong,Inter-session network coding,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
1322,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",vincent wong,butterfly network,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
1323,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",vincent wong,game theory,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
1324,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",vincent wong,Nash equilibrium,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
1325,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",vincent wong,price-of-anarchy,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
1326,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",vincent wong,efficiency bound,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
1327,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",sidharth jaggi,Inter-session network coding,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
1328,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",sidharth jaggi,butterfly network,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
1329,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA > 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
1330,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",sidharth jaggi,game theory,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
1331,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",sidharth jaggi,Nash equilibrium,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
1332,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",sidharth jaggi,price-of-anarchy,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
1333,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",sidharth jaggi,efficiency bound,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
1334,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",robert schober,Inter-session network coding,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
1335,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",robert schober,butterfly network,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
1336,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",robert schober,game theory,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
1337,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",robert schober,Nash equilibrium,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
1338,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",robert schober,price-of-anarchy,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
1339,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",robert schober,efficiency bound,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
1340,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA > 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
1341,"We address the parallel machines scheduling problems when selling to a selfish customer population with heterogeneous time utility functions. The manufacturer, owning parallel machines resource, has some independent objective. Because of customers' selfishness, anarchistic competition would worsen the manufacturer's performance, and then, cause “Price of Anarchy”. On the other hand, the optimization of the manufacturer's objective would also deteriorate some customers' waiting costs greatly (and then, will harm seller himself in long term). In this paper, noncooperative game is used to model above multi-person multi-objective problem in parallel machine environment. Price of Anarchy is analyzed. To balance each participant's performance, a coordination mechanism which could generate an efficient schedule is provided by choosing payment to motivate all selfish customers to act as the manufacturer wishes. Numerical experiments on proposed coordination mechanism are given at last.",changjun wang,parallel machine scheduling,2012.0,10.1109/ICSMC.2012.6378064,"2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC)",Wang2012,False,,IEEE,Not available,Parallel machines scheduling in the presence of heterogeneous selfish customers,8d5a830abada4b29bf7cbabe5e5517e5,https://ieeexplore.ieee.org/document/6378064/
1342,"We address the parallel machines scheduling problems when selling to a selfish customer population with heterogeneous time utility functions. The manufacturer, owning parallel machines resource, has some independent objective. Because of customers' selfishness, anarchistic competition would worsen the manufacturer's performance, and then, cause “Price of Anarchy”. On the other hand, the optimization of the manufacturer's objective would also deteriorate some customers' waiting costs greatly (and then, will harm seller himself in long term). In this paper, noncooperative game is used to model above multi-person multi-objective problem in parallel machine environment. Price of Anarchy is analyzed. To balance each participant's performance, a coordination mechanism which could generate an efficient schedule is provided by choosing payment to motivate all selfish customers to act as the manufacturer wishes. Numerical experiments on proposed coordination mechanism are given at last.",changjun wang,noncooperative game,2012.0,10.1109/ICSMC.2012.6378064,"2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC)",Wang2012,False,,IEEE,Not available,Parallel machines scheduling in the presence of heterogeneous selfish customers,8d5a830abada4b29bf7cbabe5e5517e5,https://ieeexplore.ieee.org/document/6378064/
1343,"We address the parallel machines scheduling problems when selling to a selfish customer population with heterogeneous time utility functions. The manufacturer, owning parallel machines resource, has some independent objective. Because of customers' selfishness, anarchistic competition would worsen the manufacturer's performance, and then, cause “Price of Anarchy”. On the other hand, the optimization of the manufacturer's objective would also deteriorate some customers' waiting costs greatly (and then, will harm seller himself in long term). In this paper, noncooperative game is used to model above multi-person multi-objective problem in parallel machine environment. Price of Anarchy is analyzed. To balance each participant's performance, a coordination mechanism which could generate an efficient schedule is provided by choosing payment to motivate all selfish customers to act as the manufacturer wishes. Numerical experiments on proposed coordination mechanism are given at last.",changjun wang,heterogeneous customers,2012.0,10.1109/ICSMC.2012.6378064,"2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC)",Wang2012,False,,IEEE,Not available,Parallel machines scheduling in the presence of heterogeneous selfish customers,8d5a830abada4b29bf7cbabe5e5517e5,https://ieeexplore.ieee.org/document/6378064/
1344,"We address the parallel machines scheduling problems when selling to a selfish customer population with heterogeneous time utility functions. The manufacturer, owning parallel machines resource, has some independent objective. Because of customers' selfishness, anarchistic competition would worsen the manufacturer's performance, and then, cause “Price of Anarchy”. On the other hand, the optimization of the manufacturer's objective would also deteriorate some customers' waiting costs greatly (and then, will harm seller himself in long term). In this paper, noncooperative game is used to model above multi-person multi-objective problem in parallel machine environment. Price of Anarchy is analyzed. To balance each participant's performance, a coordination mechanism which could generate an efficient schedule is provided by choosing payment to motivate all selfish customers to act as the manufacturer wishes. Numerical experiments on proposed coordination mechanism are given at last.",changjun wang,price of anachy,2012.0,10.1109/ICSMC.2012.6378064,"2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC)",Wang2012,False,,IEEE,Not available,Parallel machines scheduling in the presence of heterogeneous selfish customers,8d5a830abada4b29bf7cbabe5e5517e5,https://ieeexplore.ieee.org/document/6378064/
1345,"We address the parallel machines scheduling problems when selling to a selfish customer population with heterogeneous time utility functions. The manufacturer, owning parallel machines resource, has some independent objective. Because of customers' selfishness, anarchistic competition would worsen the manufacturer's performance, and then, cause “Price of Anarchy”. On the other hand, the optimization of the manufacturer's objective would also deteriorate some customers' waiting costs greatly (and then, will harm seller himself in long term). In this paper, noncooperative game is used to model above multi-person multi-objective problem in parallel machine environment. Price of Anarchy is analyzed. To balance each participant's performance, a coordination mechanism which could generate an efficient schedule is provided by choosing payment to motivate all selfish customers to act as the manufacturer wishes. Numerical experiments on proposed coordination mechanism are given at last.",dayang lei,parallel machine scheduling,2012.0,10.1109/ICSMC.2012.6378064,"2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC)",Wang2012,False,,IEEE,Not available,Parallel machines scheduling in the presence of heterogeneous selfish customers,8d5a830abada4b29bf7cbabe5e5517e5,https://ieeexplore.ieee.org/document/6378064/
1346,"We address the parallel machines scheduling problems when selling to a selfish customer population with heterogeneous time utility functions. The manufacturer, owning parallel machines resource, has some independent objective. Because of customers' selfishness, anarchistic competition would worsen the manufacturer's performance, and then, cause “Price of Anarchy”. On the other hand, the optimization of the manufacturer's objective would also deteriorate some customers' waiting costs greatly (and then, will harm seller himself in long term). In this paper, noncooperative game is used to model above multi-person multi-objective problem in parallel machine environment. Price of Anarchy is analyzed. To balance each participant's performance, a coordination mechanism which could generate an efficient schedule is provided by choosing payment to motivate all selfish customers to act as the manufacturer wishes. Numerical experiments on proposed coordination mechanism are given at last.",dayang lei,noncooperative game,2012.0,10.1109/ICSMC.2012.6378064,"2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC)",Wang2012,False,,IEEE,Not available,Parallel machines scheduling in the presence of heterogeneous selfish customers,8d5a830abada4b29bf7cbabe5e5517e5,https://ieeexplore.ieee.org/document/6378064/
1347,"We address the parallel machines scheduling problems when selling to a selfish customer population with heterogeneous time utility functions. The manufacturer, owning parallel machines resource, has some independent objective. Because of customers' selfishness, anarchistic competition would worsen the manufacturer's performance, and then, cause “Price of Anarchy”. On the other hand, the optimization of the manufacturer's objective would also deteriorate some customers' waiting costs greatly (and then, will harm seller himself in long term). In this paper, noncooperative game is used to model above multi-person multi-objective problem in parallel machine environment. Price of Anarchy is analyzed. To balance each participant's performance, a coordination mechanism which could generate an efficient schedule is provided by choosing payment to motivate all selfish customers to act as the manufacturer wishes. Numerical experiments on proposed coordination mechanism are given at last.",dayang lei,heterogeneous customers,2012.0,10.1109/ICSMC.2012.6378064,"2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC)",Wang2012,False,,IEEE,Not available,Parallel machines scheduling in the presence of heterogeneous selfish customers,8d5a830abada4b29bf7cbabe5e5517e5,https://ieeexplore.ieee.org/document/6378064/
1348,"We address the parallel machines scheduling problems when selling to a selfish customer population with heterogeneous time utility functions. The manufacturer, owning parallel machines resource, has some independent objective. Because of customers' selfishness, anarchistic competition would worsen the manufacturer's performance, and then, cause “Price of Anarchy”. On the other hand, the optimization of the manufacturer's objective would also deteriorate some customers' waiting costs greatly (and then, will harm seller himself in long term). In this paper, noncooperative game is used to model above multi-person multi-objective problem in parallel machine environment. Price of Anarchy is analyzed. To balance each participant's performance, a coordination mechanism which could generate an efficient schedule is provided by choosing payment to motivate all selfish customers to act as the manufacturer wishes. Numerical experiments on proposed coordination mechanism are given at last.",dayang lei,price of anachy,2012.0,10.1109/ICSMC.2012.6378064,"2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC)",Wang2012,False,,IEEE,Not available,Parallel machines scheduling in the presence of heterogeneous selfish customers,8d5a830abada4b29bf7cbabe5e5517e5,https://ieeexplore.ieee.org/document/6378064/
1349,"We address the parallel machines scheduling problems when selling to a selfish customer population with heterogeneous time utility functions. The manufacturer, owning parallel machines resource, has some independent objective. Because of customers' selfishness, anarchistic competition would worsen the manufacturer's performance, and then, cause “Price of Anarchy”. On the other hand, the optimization of the manufacturer's objective would also deteriorate some customers' waiting costs greatly (and then, will harm seller himself in long term). In this paper, noncooperative game is used to model above multi-person multi-objective problem in parallel machine environment. Price of Anarchy is analyzed. To balance each participant's performance, a coordination mechanism which could generate an efficient schedule is provided by choosing payment to motivate all selfish customers to act as the manufacturer wishes. Numerical experiments on proposed coordination mechanism are given at last.",yongji jia,parallel machine scheduling,2012.0,10.1109/ICSMC.2012.6378064,"2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC)",Wang2012,False,,IEEE,Not available,Parallel machines scheduling in the presence of heterogeneous selfish customers,8d5a830abada4b29bf7cbabe5e5517e5,https://ieeexplore.ieee.org/document/6378064/
1350,"We address the parallel machines scheduling problems when selling to a selfish customer population with heterogeneous time utility functions. The manufacturer, owning parallel machines resource, has some independent objective. Because of customers' selfishness, anarchistic competition would worsen the manufacturer's performance, and then, cause “Price of Anarchy”. On the other hand, the optimization of the manufacturer's objective would also deteriorate some customers' waiting costs greatly (and then, will harm seller himself in long term). In this paper, noncooperative game is used to model above multi-person multi-objective problem in parallel machine environment. Price of Anarchy is analyzed. To balance each participant's performance, a coordination mechanism which could generate an efficient schedule is provided by choosing payment to motivate all selfish customers to act as the manufacturer wishes. Numerical experiments on proposed coordination mechanism are given at last.",yongji jia,noncooperative game,2012.0,10.1109/ICSMC.2012.6378064,"2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC)",Wang2012,False,,IEEE,Not available,Parallel machines scheduling in the presence of heterogeneous selfish customers,8d5a830abada4b29bf7cbabe5e5517e5,https://ieeexplore.ieee.org/document/6378064/
1351,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA > 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
1352,"We address the parallel machines scheduling problems when selling to a selfish customer population with heterogeneous time utility functions. The manufacturer, owning parallel machines resource, has some independent objective. Because of customers' selfishness, anarchistic competition would worsen the manufacturer's performance, and then, cause “Price of Anarchy”. On the other hand, the optimization of the manufacturer's objective would also deteriorate some customers' waiting costs greatly (and then, will harm seller himself in long term). In this paper, noncooperative game is used to model above multi-person multi-objective problem in parallel machine environment. Price of Anarchy is analyzed. To balance each participant's performance, a coordination mechanism which could generate an efficient schedule is provided by choosing payment to motivate all selfish customers to act as the manufacturer wishes. Numerical experiments on proposed coordination mechanism are given at last.",yongji jia,heterogeneous customers,2012.0,10.1109/ICSMC.2012.6378064,"2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC)",Wang2012,False,,IEEE,Not available,Parallel machines scheduling in the presence of heterogeneous selfish customers,8d5a830abada4b29bf7cbabe5e5517e5,https://ieeexplore.ieee.org/document/6378064/
1353,"We address the parallel machines scheduling problems when selling to a selfish customer population with heterogeneous time utility functions. The manufacturer, owning parallel machines resource, has some independent objective. Because of customers' selfishness, anarchistic competition would worsen the manufacturer's performance, and then, cause “Price of Anarchy”. On the other hand, the optimization of the manufacturer's objective would also deteriorate some customers' waiting costs greatly (and then, will harm seller himself in long term). In this paper, noncooperative game is used to model above multi-person multi-objective problem in parallel machine environment. Price of Anarchy is analyzed. To balance each participant's performance, a coordination mechanism which could generate an efficient schedule is provided by choosing payment to motivate all selfish customers to act as the manufacturer wishes. Numerical experiments on proposed coordination mechanism are given at last.",yongji jia,price of anachy,2012.0,10.1109/ICSMC.2012.6378064,"2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC)",Wang2012,False,,IEEE,Not available,Parallel machines scheduling in the presence of heterogeneous selfish customers,8d5a830abada4b29bf7cbabe5e5517e5,https://ieeexplore.ieee.org/document/6378064/
1354,"In the foreseeable future, power grids will be managed largely with demand-side management (DSM) programs. With the growing population of electric vehicles (EVs) and the emergence of aggregators, DSM will surely introduce more intense competition to the markets. Since EV charging produces a large amount of time-flexible load in power systems, competition of its management could become a major game. This paper first formulates the game of EV charging management to describe this major form of the future DSM competition and then studies three challenges inherent in it: 1) inefficiency of Nash equilibria; 2) the game of chicken; and 3) cheating on private information. It is found that a central regulator is required to prevent these drawbacks. Solutions are proposed and a central governing procedure is also presented. The notion of the game of EV charging management is compatible with DSM programs that are able to schedule load flexibly over multiple time periods.",n. xu,Aggregator,2015.0,10.1109/TSG.2014.2373401,IEEE Transactions on Smart Grid,Xu2015,False,,IEEE,Not available,Challenges in Future Competition of Electric Vehicle Charging Management and Solutions,68cf1a3e6a55873549ac78feb6a702f4,https://ieeexplore.ieee.org/document/6990624/
1355,"In the foreseeable future, power grids will be managed largely with demand-side management (DSM) programs. With the growing population of electric vehicles (EVs) and the emergence of aggregators, DSM will surely introduce more intense competition to the markets. Since EV charging produces a large amount of time-flexible load in power systems, competition of its management could become a major game. This paper first formulates the game of EV charging management to describe this major form of the future DSM competition and then studies three challenges inherent in it: 1) inefficiency of Nash equilibria; 2) the game of chicken; and 3) cheating on private information. It is found that a central regulator is required to prevent these drawbacks. Solutions are proposed and a central governing procedure is also presented. The notion of the game of EV charging management is compatible with DSM programs that are able to schedule load flexibly over multiple time periods.",n. xu,correlated equilibrium,2015.0,10.1109/TSG.2014.2373401,IEEE Transactions on Smart Grid,Xu2015,False,,IEEE,Not available,Challenges in Future Competition of Electric Vehicle Charging Management and Solutions,68cf1a3e6a55873549ac78feb6a702f4,https://ieeexplore.ieee.org/document/6990624/
1356,"In the foreseeable future, power grids will be managed largely with demand-side management (DSM) programs. With the growing population of electric vehicles (EVs) and the emergence of aggregators, DSM will surely introduce more intense competition to the markets. Since EV charging produces a large amount of time-flexible load in power systems, competition of its management could become a major game. This paper first formulates the game of EV charging management to describe this major form of the future DSM competition and then studies three challenges inherent in it: 1) inefficiency of Nash equilibria; 2) the game of chicken; and 3) cheating on private information. It is found that a central regulator is required to prevent these drawbacks. Solutions are proposed and a central governing procedure is also presented. The notion of the game of EV charging management is compatible with DSM programs that are able to schedule load flexibly over multiple time periods.",n. xu,demand-side management (DSM),2015.0,10.1109/TSG.2014.2373401,IEEE Transactions on Smart Grid,Xu2015,False,,IEEE,Not available,Challenges in Future Competition of Electric Vehicle Charging Management and Solutions,68cf1a3e6a55873549ac78feb6a702f4,https://ieeexplore.ieee.org/document/6990624/
1357,"In the foreseeable future, power grids will be managed largely with demand-side management (DSM) programs. With the growing population of electric vehicles (EVs) and the emergence of aggregators, DSM will surely introduce more intense competition to the markets. Since EV charging produces a large amount of time-flexible load in power systems, competition of its management could become a major game. This paper first formulates the game of EV charging management to describe this major form of the future DSM competition and then studies three challenges inherent in it: 1) inefficiency of Nash equilibria; 2) the game of chicken; and 3) cheating on private information. It is found that a central regulator is required to prevent these drawbacks. Solutions are proposed and a central governing procedure is also presented. The notion of the game of EV charging management is compatible with DSM programs that are able to schedule load flexibly over multiple time periods.",n. xu,electric vehicle (EV) charging,2015.0,10.1109/TSG.2014.2373401,IEEE Transactions on Smart Grid,Xu2015,False,,IEEE,Not available,Challenges in Future Competition of Electric Vehicle Charging Management and Solutions,68cf1a3e6a55873549ac78feb6a702f4,https://ieeexplore.ieee.org/document/6990624/
1358,"In the foreseeable future, power grids will be managed largely with demand-side management (DSM) programs. With the growing population of electric vehicles (EVs) and the emergence of aggregators, DSM will surely introduce more intense competition to the markets. Since EV charging produces a large amount of time-flexible load in power systems, competition of its management could become a major game. This paper first formulates the game of EV charging management to describe this major form of the future DSM competition and then studies three challenges inherent in it: 1) inefficiency of Nash equilibria; 2) the game of chicken; and 3) cheating on private information. It is found that a central regulator is required to prevent these drawbacks. Solutions are proposed and a central governing procedure is also presented. The notion of the game of EV charging management is compatible with DSM programs that are able to schedule load flexibly over multiple time periods.",n. xu,mechanism design,2015.0,10.1109/TSG.2014.2373401,IEEE Transactions on Smart Grid,Xu2015,False,,IEEE,Not available,Challenges in Future Competition of Electric Vehicle Charging Management and Solutions,68cf1a3e6a55873549ac78feb6a702f4,https://ieeexplore.ieee.org/document/6990624/
1359,"In the foreseeable future, power grids will be managed largely with demand-side management (DSM) programs. With the growing population of electric vehicles (EVs) and the emergence of aggregators, DSM will surely introduce more intense competition to the markets. Since EV charging produces a large amount of time-flexible load in power systems, competition of its management could become a major game. This paper first formulates the game of EV charging management to describe this major form of the future DSM competition and then studies three challenges inherent in it: 1) inefficiency of Nash equilibria; 2) the game of chicken; and 3) cheating on private information. It is found that a central regulator is required to prevent these drawbacks. Solutions are proposed and a central governing procedure is also presented. The notion of the game of EV charging management is compatible with DSM programs that are able to schedule load flexibly over multiple time periods.",n. xu,Nash equilibrium,2015.0,10.1109/TSG.2014.2373401,IEEE Transactions on Smart Grid,Xu2015,False,,IEEE,Not available,Challenges in Future Competition of Electric Vehicle Charging Management and Solutions,68cf1a3e6a55873549ac78feb6a702f4,https://ieeexplore.ieee.org/document/6990624/
1360,"In the foreseeable future, power grids will be managed largely with demand-side management (DSM) programs. With the growing population of electric vehicles (EVs) and the emergence of aggregators, DSM will surely introduce more intense competition to the markets. Since EV charging produces a large amount of time-flexible load in power systems, competition of its management could become a major game. This paper first formulates the game of EV charging management to describe this major form of the future DSM competition and then studies three challenges inherent in it: 1) inefficiency of Nash equilibria; 2) the game of chicken; and 3) cheating on private information. It is found that a central regulator is required to prevent these drawbacks. Solutions are proposed and a central governing procedure is also presented. The notion of the game of EV charging management is compatible with DSM programs that are able to schedule load flexibly over multiple time periods.",n. xu,price of anarchy (PoA),2015.0,10.1109/TSG.2014.2373401,IEEE Transactions on Smart Grid,Xu2015,False,,IEEE,Not available,Challenges in Future Competition of Electric Vehicle Charging Management and Solutions,68cf1a3e6a55873549ac78feb6a702f4,https://ieeexplore.ieee.org/document/6990624/
1361,"In the foreseeable future, power grids will be managed largely with demand-side management (DSM) programs. With the growing population of electric vehicles (EVs) and the emergence of aggregators, DSM will surely introduce more intense competition to the markets. Since EV charging produces a large amount of time-flexible load in power systems, competition of its management could become a major game. This paper first formulates the game of EV charging management to describe this major form of the future DSM competition and then studies three challenges inherent in it: 1) inefficiency of Nash equilibria; 2) the game of chicken; and 3) cheating on private information. It is found that a central regulator is required to prevent these drawbacks. Solutions are proposed and a central governing procedure is also presented. The notion of the game of EV charging management is compatible with DSM programs that are able to schedule load flexibly over multiple time periods.",n. xu,Aggregator,2015.0,10.1109/TSG.2014.2373401,IEEE Transactions on Smart Grid,Xu2015,False,,IEEE,Not available,Challenges in Future Competition of Electric Vehicle Charging Management and Solutions,68cf1a3e6a55873549ac78feb6a702f4,https://ieeexplore.ieee.org/document/6990624/
1362,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA > 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
1363,"In the foreseeable future, power grids will be managed largely with demand-side management (DSM) programs. With the growing population of electric vehicles (EVs) and the emergence of aggregators, DSM will surely introduce more intense competition to the markets. Since EV charging produces a large amount of time-flexible load in power systems, competition of its management could become a major game. This paper first formulates the game of EV charging management to describe this major form of the future DSM competition and then studies three challenges inherent in it: 1) inefficiency of Nash equilibria; 2) the game of chicken; and 3) cheating on private information. It is found that a central regulator is required to prevent these drawbacks. Solutions are proposed and a central governing procedure is also presented. The notion of the game of EV charging management is compatible with DSM programs that are able to schedule load flexibly over multiple time periods.",n. xu,correlated equilibrium,2015.0,10.1109/TSG.2014.2373401,IEEE Transactions on Smart Grid,Xu2015,False,,IEEE,Not available,Challenges in Future Competition of Electric Vehicle Charging Management and Solutions,68cf1a3e6a55873549ac78feb6a702f4,https://ieeexplore.ieee.org/document/6990624/
1364,"In the foreseeable future, power grids will be managed largely with demand-side management (DSM) programs. With the growing population of electric vehicles (EVs) and the emergence of aggregators, DSM will surely introduce more intense competition to the markets. Since EV charging produces a large amount of time-flexible load in power systems, competition of its management could become a major game. This paper first formulates the game of EV charging management to describe this major form of the future DSM competition and then studies three challenges inherent in it: 1) inefficiency of Nash equilibria; 2) the game of chicken; and 3) cheating on private information. It is found that a central regulator is required to prevent these drawbacks. Solutions are proposed and a central governing procedure is also presented. The notion of the game of EV charging management is compatible with DSM programs that are able to schedule load flexibly over multiple time periods.",n. xu,demand-side management (DSM),2015.0,10.1109/TSG.2014.2373401,IEEE Transactions on Smart Grid,Xu2015,False,,IEEE,Not available,Challenges in Future Competition of Electric Vehicle Charging Management and Solutions,68cf1a3e6a55873549ac78feb6a702f4,https://ieeexplore.ieee.org/document/6990624/
1365,"In the foreseeable future, power grids will be managed largely with demand-side management (DSM) programs. With the growing population of electric vehicles (EVs) and the emergence of aggregators, DSM will surely introduce more intense competition to the markets. Since EV charging produces a large amount of time-flexible load in power systems, competition of its management could become a major game. This paper first formulates the game of EV charging management to describe this major form of the future DSM competition and then studies three challenges inherent in it: 1) inefficiency of Nash equilibria; 2) the game of chicken; and 3) cheating on private information. It is found that a central regulator is required to prevent these drawbacks. Solutions are proposed and a central governing procedure is also presented. The notion of the game of EV charging management is compatible with DSM programs that are able to schedule load flexibly over multiple time periods.",n. xu,electric vehicle (EV) charging,2015.0,10.1109/TSG.2014.2373401,IEEE Transactions on Smart Grid,Xu2015,False,,IEEE,Not available,Challenges in Future Competition of Electric Vehicle Charging Management and Solutions,68cf1a3e6a55873549ac78feb6a702f4,https://ieeexplore.ieee.org/document/6990624/
1366,"In the foreseeable future, power grids will be managed largely with demand-side management (DSM) programs. With the growing population of electric vehicles (EVs) and the emergence of aggregators, DSM will surely introduce more intense competition to the markets. Since EV charging produces a large amount of time-flexible load in power systems, competition of its management could become a major game. This paper first formulates the game of EV charging management to describe this major form of the future DSM competition and then studies three challenges inherent in it: 1) inefficiency of Nash equilibria; 2) the game of chicken; and 3) cheating on private information. It is found that a central regulator is required to prevent these drawbacks. Solutions are proposed and a central governing procedure is also presented. The notion of the game of EV charging management is compatible with DSM programs that are able to schedule load flexibly over multiple time periods.",n. xu,mechanism design,2015.0,10.1109/TSG.2014.2373401,IEEE Transactions on Smart Grid,Xu2015,False,,IEEE,Not available,Challenges in Future Competition of Electric Vehicle Charging Management and Solutions,68cf1a3e6a55873549ac78feb6a702f4,https://ieeexplore.ieee.org/document/6990624/
1367,"In the foreseeable future, power grids will be managed largely with demand-side management (DSM) programs. With the growing population of electric vehicles (EVs) and the emergence of aggregators, DSM will surely introduce more intense competition to the markets. Since EV charging produces a large amount of time-flexible load in power systems, competition of its management could become a major game. This paper first formulates the game of EV charging management to describe this major form of the future DSM competition and then studies three challenges inherent in it: 1) inefficiency of Nash equilibria; 2) the game of chicken; and 3) cheating on private information. It is found that a central regulator is required to prevent these drawbacks. Solutions are proposed and a central governing procedure is also presented. The notion of the game of EV charging management is compatible with DSM programs that are able to schedule load flexibly over multiple time periods.",n. xu,Nash equilibrium,2015.0,10.1109/TSG.2014.2373401,IEEE Transactions on Smart Grid,Xu2015,False,,IEEE,Not available,Challenges in Future Competition of Electric Vehicle Charging Management and Solutions,68cf1a3e6a55873549ac78feb6a702f4,https://ieeexplore.ieee.org/document/6990624/
1368,"In the foreseeable future, power grids will be managed largely with demand-side management (DSM) programs. With the growing population of electric vehicles (EVs) and the emergence of aggregators, DSM will surely introduce more intense competition to the markets. Since EV charging produces a large amount of time-flexible load in power systems, competition of its management could become a major game. This paper first formulates the game of EV charging management to describe this major form of the future DSM competition and then studies three challenges inherent in it: 1) inefficiency of Nash equilibria; 2) the game of chicken; and 3) cheating on private information. It is found that a central regulator is required to prevent these drawbacks. Solutions are proposed and a central governing procedure is also presented. The notion of the game of EV charging management is compatible with DSM programs that are able to schedule load flexibly over multiple time periods.",n. xu,price of anarchy (PoA),2015.0,10.1109/TSG.2014.2373401,IEEE Transactions on Smart Grid,Xu2015,False,,IEEE,Not available,Challenges in Future Competition of Electric Vehicle Charging Management and Solutions,68cf1a3e6a55873549ac78feb6a702f4,https://ieeexplore.ieee.org/document/6990624/
1369,"In the foreseeable future, power grids will be managed largely with demand-side management (DSM) programs. With the growing population of electric vehicles (EVs) and the emergence of aggregators, DSM will surely introduce more intense competition to the markets. Since EV charging produces a large amount of time-flexible load in power systems, competition of its management could become a major game. This paper first formulates the game of EV charging management to describe this major form of the future DSM competition and then studies three challenges inherent in it: 1) inefficiency of Nash equilibria; 2) the game of chicken; and 3) cheating on private information. It is found that a central regulator is required to prevent these drawbacks. Solutions are proposed and a central governing procedure is also presented. The notion of the game of EV charging management is compatible with DSM programs that are able to schedule load flexibly over multiple time periods.",c. chung,Aggregator,2015.0,10.1109/TSG.2014.2373401,IEEE Transactions on Smart Grid,Xu2015,False,,IEEE,Not available,Challenges in Future Competition of Electric Vehicle Charging Management and Solutions,68cf1a3e6a55873549ac78feb6a702f4,https://ieeexplore.ieee.org/document/6990624/
1370,"In the foreseeable future, power grids will be managed largely with demand-side management (DSM) programs. With the growing population of electric vehicles (EVs) and the emergence of aggregators, DSM will surely introduce more intense competition to the markets. Since EV charging produces a large amount of time-flexible load in power systems, competition of its management could become a major game. This paper first formulates the game of EV charging management to describe this major form of the future DSM competition and then studies three challenges inherent in it: 1) inefficiency of Nash equilibria; 2) the game of chicken; and 3) cheating on private information. It is found that a central regulator is required to prevent these drawbacks. Solutions are proposed and a central governing procedure is also presented. The notion of the game of EV charging management is compatible with DSM programs that are able to schedule load flexibly over multiple time periods.",c. chung,correlated equilibrium,2015.0,10.1109/TSG.2014.2373401,IEEE Transactions on Smart Grid,Xu2015,False,,IEEE,Not available,Challenges in Future Competition of Electric Vehicle Charging Management and Solutions,68cf1a3e6a55873549ac78feb6a702f4,https://ieeexplore.ieee.org/document/6990624/
1371,"In the foreseeable future, power grids will be managed largely with demand-side management (DSM) programs. With the growing population of electric vehicles (EVs) and the emergence of aggregators, DSM will surely introduce more intense competition to the markets. Since EV charging produces a large amount of time-flexible load in power systems, competition of its management could become a major game. This paper first formulates the game of EV charging management to describe this major form of the future DSM competition and then studies three challenges inherent in it: 1) inefficiency of Nash equilibria; 2) the game of chicken; and 3) cheating on private information. It is found that a central regulator is required to prevent these drawbacks. Solutions are proposed and a central governing procedure is also presented. The notion of the game of EV charging management is compatible with DSM programs that are able to schedule load flexibly over multiple time periods.",c. chung,demand-side management (DSM),2015.0,10.1109/TSG.2014.2373401,IEEE Transactions on Smart Grid,Xu2015,False,,IEEE,Not available,Challenges in Future Competition of Electric Vehicle Charging Management and Solutions,68cf1a3e6a55873549ac78feb6a702f4,https://ieeexplore.ieee.org/document/6990624/
1372,"In the foreseeable future, power grids will be managed largely with demand-side management (DSM) programs. With the growing population of electric vehicles (EVs) and the emergence of aggregators, DSM will surely introduce more intense competition to the markets. Since EV charging produces a large amount of time-flexible load in power systems, competition of its management could become a major game. This paper first formulates the game of EV charging management to describe this major form of the future DSM competition and then studies three challenges inherent in it: 1) inefficiency of Nash equilibria; 2) the game of chicken; and 3) cheating on private information. It is found that a central regulator is required to prevent these drawbacks. Solutions are proposed and a central governing procedure is also presented. The notion of the game of EV charging management is compatible with DSM programs that are able to schedule load flexibly over multiple time periods.",c. chung,electric vehicle (EV) charging,2015.0,10.1109/TSG.2014.2373401,IEEE Transactions on Smart Grid,Xu2015,False,,IEEE,Not available,Challenges in Future Competition of Electric Vehicle Charging Management and Solutions,68cf1a3e6a55873549ac78feb6a702f4,https://ieeexplore.ieee.org/document/6990624/
1373,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA > 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
1374,"In the foreseeable future, power grids will be managed largely with demand-side management (DSM) programs. With the growing population of electric vehicles (EVs) and the emergence of aggregators, DSM will surely introduce more intense competition to the markets. Since EV charging produces a large amount of time-flexible load in power systems, competition of its management could become a major game. This paper first formulates the game of EV charging management to describe this major form of the future DSM competition and then studies three challenges inherent in it: 1) inefficiency of Nash equilibria; 2) the game of chicken; and 3) cheating on private information. It is found that a central regulator is required to prevent these drawbacks. Solutions are proposed and a central governing procedure is also presented. The notion of the game of EV charging management is compatible with DSM programs that are able to schedule load flexibly over multiple time periods.",c. chung,mechanism design,2015.0,10.1109/TSG.2014.2373401,IEEE Transactions on Smart Grid,Xu2015,False,,IEEE,Not available,Challenges in Future Competition of Electric Vehicle Charging Management and Solutions,68cf1a3e6a55873549ac78feb6a702f4,https://ieeexplore.ieee.org/document/6990624/
1375,"In the foreseeable future, power grids will be managed largely with demand-side management (DSM) programs. With the growing population of electric vehicles (EVs) and the emergence of aggregators, DSM will surely introduce more intense competition to the markets. Since EV charging produces a large amount of time-flexible load in power systems, competition of its management could become a major game. This paper first formulates the game of EV charging management to describe this major form of the future DSM competition and then studies three challenges inherent in it: 1) inefficiency of Nash equilibria; 2) the game of chicken; and 3) cheating on private information. It is found that a central regulator is required to prevent these drawbacks. Solutions are proposed and a central governing procedure is also presented. The notion of the game of EV charging management is compatible with DSM programs that are able to schedule load flexibly over multiple time periods.",c. chung,Nash equilibrium,2015.0,10.1109/TSG.2014.2373401,IEEE Transactions on Smart Grid,Xu2015,False,,IEEE,Not available,Challenges in Future Competition of Electric Vehicle Charging Management and Solutions,68cf1a3e6a55873549ac78feb6a702f4,https://ieeexplore.ieee.org/document/6990624/
1376,"In the foreseeable future, power grids will be managed largely with demand-side management (DSM) programs. With the growing population of electric vehicles (EVs) and the emergence of aggregators, DSM will surely introduce more intense competition to the markets. Since EV charging produces a large amount of time-flexible load in power systems, competition of its management could become a major game. This paper first formulates the game of EV charging management to describe this major form of the future DSM competition and then studies three challenges inherent in it: 1) inefficiency of Nash equilibria; 2) the game of chicken; and 3) cheating on private information. It is found that a central regulator is required to prevent these drawbacks. Solutions are proposed and a central governing procedure is also presented. The notion of the game of EV charging management is compatible with DSM programs that are able to schedule load flexibly over multiple time periods.",c. chung,price of anarchy (PoA),2015.0,10.1109/TSG.2014.2373401,IEEE Transactions on Smart Grid,Xu2015,False,,IEEE,Not available,Challenges in Future Competition of Electric Vehicle Charging Management and Solutions,68cf1a3e6a55873549ac78feb6a702f4,https://ieeexplore.ieee.org/document/6990624/
1377,"In the foreseeable future, power grids will be managed largely with demand-side management (DSM) programs. With the growing population of electric vehicles (EVs) and the emergence of aggregators, DSM will surely introduce more intense competition to the markets. Since EV charging produces a large amount of time-flexible load in power systems, competition of its management could become a major game. This paper first formulates the game of EV charging management to describe this major form of the future DSM competition and then studies three challenges inherent in it: 1) inefficiency of Nash equilibria; 2) the game of chicken; and 3) cheating on private information. It is found that a central regulator is required to prevent these drawbacks. Solutions are proposed and a central governing procedure is also presented. The notion of the game of EV charging management is compatible with DSM programs that are able to schedule load flexibly over multiple time periods.",c. chung,Aggregator,2015.0,10.1109/TSG.2014.2373401,IEEE Transactions on Smart Grid,Xu2015,False,,IEEE,Not available,Challenges in Future Competition of Electric Vehicle Charging Management and Solutions,68cf1a3e6a55873549ac78feb6a702f4,https://ieeexplore.ieee.org/document/6990624/
1378,"In the foreseeable future, power grids will be managed largely with demand-side management (DSM) programs. With the growing population of electric vehicles (EVs) and the emergence of aggregators, DSM will surely introduce more intense competition to the markets. Since EV charging produces a large amount of time-flexible load in power systems, competition of its management could become a major game. This paper first formulates the game of EV charging management to describe this major form of the future DSM competition and then studies three challenges inherent in it: 1) inefficiency of Nash equilibria; 2) the game of chicken; and 3) cheating on private information. It is found that a central regulator is required to prevent these drawbacks. Solutions are proposed and a central governing procedure is also presented. The notion of the game of EV charging management is compatible with DSM programs that are able to schedule load flexibly over multiple time periods.",c. chung,correlated equilibrium,2015.0,10.1109/TSG.2014.2373401,IEEE Transactions on Smart Grid,Xu2015,False,,IEEE,Not available,Challenges in Future Competition of Electric Vehicle Charging Management and Solutions,68cf1a3e6a55873549ac78feb6a702f4,https://ieeexplore.ieee.org/document/6990624/
1379,"In the foreseeable future, power grids will be managed largely with demand-side management (DSM) programs. With the growing population of electric vehicles (EVs) and the emergence of aggregators, DSM will surely introduce more intense competition to the markets. Since EV charging produces a large amount of time-flexible load in power systems, competition of its management could become a major game. This paper first formulates the game of EV charging management to describe this major form of the future DSM competition and then studies three challenges inherent in it: 1) inefficiency of Nash equilibria; 2) the game of chicken; and 3) cheating on private information. It is found that a central regulator is required to prevent these drawbacks. Solutions are proposed and a central governing procedure is also presented. The notion of the game of EV charging management is compatible with DSM programs that are able to schedule load flexibly over multiple time periods.",c. chung,demand-side management (DSM),2015.0,10.1109/TSG.2014.2373401,IEEE Transactions on Smart Grid,Xu2015,False,,IEEE,Not available,Challenges in Future Competition of Electric Vehicle Charging Management and Solutions,68cf1a3e6a55873549ac78feb6a702f4,https://ieeexplore.ieee.org/document/6990624/
1380,"In the foreseeable future, power grids will be managed largely with demand-side management (DSM) programs. With the growing population of electric vehicles (EVs) and the emergence of aggregators, DSM will surely introduce more intense competition to the markets. Since EV charging produces a large amount of time-flexible load in power systems, competition of its management could become a major game. This paper first formulates the game of EV charging management to describe this major form of the future DSM competition and then studies three challenges inherent in it: 1) inefficiency of Nash equilibria; 2) the game of chicken; and 3) cheating on private information. It is found that a central regulator is required to prevent these drawbacks. Solutions are proposed and a central governing procedure is also presented. The notion of the game of EV charging management is compatible with DSM programs that are able to schedule load flexibly over multiple time periods.",c. chung,electric vehicle (EV) charging,2015.0,10.1109/TSG.2014.2373401,IEEE Transactions on Smart Grid,Xu2015,False,,IEEE,Not available,Challenges in Future Competition of Electric Vehicle Charging Management and Solutions,68cf1a3e6a55873549ac78feb6a702f4,https://ieeexplore.ieee.org/document/6990624/
1381,"In the foreseeable future, power grids will be managed largely with demand-side management (DSM) programs. With the growing population of electric vehicles (EVs) and the emergence of aggregators, DSM will surely introduce more intense competition to the markets. Since EV charging produces a large amount of time-flexible load in power systems, competition of its management could become a major game. This paper first formulates the game of EV charging management to describe this major form of the future DSM competition and then studies three challenges inherent in it: 1) inefficiency of Nash equilibria; 2) the game of chicken; and 3) cheating on private information. It is found that a central regulator is required to prevent these drawbacks. Solutions are proposed and a central governing procedure is also presented. The notion of the game of EV charging management is compatible with DSM programs that are able to schedule load flexibly over multiple time periods.",c. chung,mechanism design,2015.0,10.1109/TSG.2014.2373401,IEEE Transactions on Smart Grid,Xu2015,False,,IEEE,Not available,Challenges in Future Competition of Electric Vehicle Charging Management and Solutions,68cf1a3e6a55873549ac78feb6a702f4,https://ieeexplore.ieee.org/document/6990624/
1382,"In the foreseeable future, power grids will be managed largely with demand-side management (DSM) programs. With the growing population of electric vehicles (EVs) and the emergence of aggregators, DSM will surely introduce more intense competition to the markets. Since EV charging produces a large amount of time-flexible load in power systems, competition of its management could become a major game. This paper first formulates the game of EV charging management to describe this major form of the future DSM competition and then studies three challenges inherent in it: 1) inefficiency of Nash equilibria; 2) the game of chicken; and 3) cheating on private information. It is found that a central regulator is required to prevent these drawbacks. Solutions are proposed and a central governing procedure is also presented. The notion of the game of EV charging management is compatible with DSM programs that are able to schedule load flexibly over multiple time periods.",c. chung,Nash equilibrium,2015.0,10.1109/TSG.2014.2373401,IEEE Transactions on Smart Grid,Xu2015,False,,IEEE,Not available,Challenges in Future Competition of Electric Vehicle Charging Management and Solutions,68cf1a3e6a55873549ac78feb6a702f4,https://ieeexplore.ieee.org/document/6990624/
1383,"In the foreseeable future, power grids will be managed largely with demand-side management (DSM) programs. With the growing population of electric vehicles (EVs) and the emergence of aggregators, DSM will surely introduce more intense competition to the markets. Since EV charging produces a large amount of time-flexible load in power systems, competition of its management could become a major game. This paper first formulates the game of EV charging management to describe this major form of the future DSM competition and then studies three challenges inherent in it: 1) inefficiency of Nash equilibria; 2) the game of chicken; and 3) cheating on private information. It is found that a central regulator is required to prevent these drawbacks. Solutions are proposed and a central governing procedure is also presented. The notion of the game of EV charging management is compatible with DSM programs that are able to schedule load flexibly over multiple time periods.",c. chung,price of anarchy (PoA),2015.0,10.1109/TSG.2014.2373401,IEEE Transactions on Smart Grid,Xu2015,False,,IEEE,Not available,Challenges in Future Competition of Electric Vehicle Charging Management and Solutions,68cf1a3e6a55873549ac78feb6a702f4,https://ieeexplore.ieee.org/document/6990624/
1384,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA > 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
1385,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",paulin jacquot,Games,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
1386,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",paulin jacquot,Energy consumption,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
1387,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",paulin jacquot,Standards,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
1388,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",paulin jacquot,Smart grids,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
1389,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",paulin jacquot,Load management,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
1390,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",paulin jacquot,Noise measurement,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
1391,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",olivier beaude,Games,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
1392,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",olivier beaude,Energy consumption,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
1393,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",olivier beaude,Standards,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
1394,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",olivier beaude,Smart grids,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
1395,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
1396,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",olivier beaude,Load management,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
1397,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",olivier beaude,Noise measurement,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
1398,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",stephane gaubert,Games,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
1399,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",stephane gaubert,Energy consumption,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
1400,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",stephane gaubert,Standards,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
1401,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",stephane gaubert,Smart grids,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
1402,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",stephane gaubert,Load management,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
1403,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",stephane gaubert,Noise measurement,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
1404,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",nadia oudjane,Games,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
1405,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",nadia oudjane,Energy consumption,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
1406,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
1407,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
1408,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",nadia oudjane,Standards,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
1409,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",nadia oudjane,Smart grids,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
1410,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",nadia oudjane,Load management,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
1411,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",nadia oudjane,Noise measurement,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
1412,"This paper proposes to empower capacityand coverage-centric fiber-wireless (FiWi) enhanced 4G LongTerm Evolution Advanced (LTE-A) heterogeneous networks (HetNets) with computationand storage-centric mobile cloud computing to cope with the unprecedented growth of mobile data traffic. Minimizing energy consumption and maximizing revenue while offloading mobile data in such highly converged and hierarchical networks is not trivial, where multiple players (ίe., cloud service providers, macrocell and small cells, users) with multiple objectives coexist. This paper proposes a mobile data offloading framework using a noncooperative multi-level game-theoretic approach from an end-to-end perspective in the envisioned network. More specifically, we design three-level Stackelberg games, in which a single-leader multi-follower game, a multi-leader multi-follower game, and a single-leader multi-follower game are modeled in the introduced network such that individual players selfishly optimize their local payoff functions and collectively solve the large complex network-wide optimization problem. Further, we develop distributed mobile data offloading algorithms to reduce the complexity of the hierarchical games and to achieve a unique Nash equilibrium condition in each subgame. Simulation results show that by reaching the Nash equilibrium condition, the proposed solution helps minimize energy consumption, interference price, and processing cost, while maximizing revenues of the players in the envisioned network. In addition, the efficiency of the equilibria in terms of price of anarchy and price of stability is quantified for the best/worst case of the Nash equilibrium.",bhaskar rimai,Fiber-wireless (FiWi),2017.0,10.1364/JOCN.9.000601,IEEE/OSA Journal of Optical Communications and Networking,Rimai2017,False,,IEEE,Not available,Mobile data offloading in FiWi enhanced LTE-A heterogeneous networks,9e1d53a3b64be142024910ca68ac89e4,
1413,"This paper proposes to empower capacityand coverage-centric fiber-wireless (FiWi) enhanced 4G LongTerm Evolution Advanced (LTE-A) heterogeneous networks (HetNets) with computationand storage-centric mobile cloud computing to cope with the unprecedented growth of mobile data traffic. Minimizing energy consumption and maximizing revenue while offloading mobile data in such highly converged and hierarchical networks is not trivial, where multiple players (ίe., cloud service providers, macrocell and small cells, users) with multiple objectives coexist. This paper proposes a mobile data offloading framework using a noncooperative multi-level game-theoretic approach from an end-to-end perspective in the envisioned network. More specifically, we design three-level Stackelberg games, in which a single-leader multi-follower game, a multi-leader multi-follower game, and a single-leader multi-follower game are modeled in the introduced network such that individual players selfishly optimize their local payoff functions and collectively solve the large complex network-wide optimization problem. Further, we develop distributed mobile data offloading algorithms to reduce the complexity of the hierarchical games and to achieve a unique Nash equilibrium condition in each subgame. Simulation results show that by reaching the Nash equilibrium condition, the proposed solution helps minimize energy consumption, interference price, and processing cost, while maximizing revenues of the players in the envisioned network. In addition, the efficiency of the equilibria in terms of price of anarchy and price of stability is quantified for the best/worst case of the Nash equilibrium.",bhaskar rimai,Game theory,2017.0,10.1364/JOCN.9.000601,IEEE/OSA Journal of Optical Communications and Networking,Rimai2017,False,,IEEE,Not available,Mobile data offloading in FiWi enhanced LTE-A heterogeneous networks,9e1d53a3b64be142024910ca68ac89e4,
1414,"This paper proposes to empower capacityand coverage-centric fiber-wireless (FiWi) enhanced 4G LongTerm Evolution Advanced (LTE-A) heterogeneous networks (HetNets) with computationand storage-centric mobile cloud computing to cope with the unprecedented growth of mobile data traffic. Minimizing energy consumption and maximizing revenue while offloading mobile data in such highly converged and hierarchical networks is not trivial, where multiple players (ίe., cloud service providers, macrocell and small cells, users) with multiple objectives coexist. This paper proposes a mobile data offloading framework using a noncooperative multi-level game-theoretic approach from an end-to-end perspective in the envisioned network. More specifically, we design three-level Stackelberg games, in which a single-leader multi-follower game, a multi-leader multi-follower game, and a single-leader multi-follower game are modeled in the introduced network such that individual players selfishly optimize their local payoff functions and collectively solve the large complex network-wide optimization problem. Further, we develop distributed mobile data offloading algorithms to reduce the complexity of the hierarchical games and to achieve a unique Nash equilibrium condition in each subgame. Simulation results show that by reaching the Nash equilibrium condition, the proposed solution helps minimize energy consumption, interference price, and processing cost, while maximizing revenues of the players in the envisioned network. In addition, the efficiency of the equilibria in terms of price of anarchy and price of stability is quantified for the best/worst case of the Nash equilibrium.",bhaskar rimai,Heterogeneous networks,2017.0,10.1364/JOCN.9.000601,IEEE/OSA Journal of Optical Communications and Networking,Rimai2017,False,,IEEE,Not available,Mobile data offloading in FiWi enhanced LTE-A heterogeneous networks,9e1d53a3b64be142024910ca68ac89e4,
1415,"This paper proposes to empower capacityand coverage-centric fiber-wireless (FiWi) enhanced 4G LongTerm Evolution Advanced (LTE-A) heterogeneous networks (HetNets) with computationand storage-centric mobile cloud computing to cope with the unprecedented growth of mobile data traffic. Minimizing energy consumption and maximizing revenue while offloading mobile data in such highly converged and hierarchical networks is not trivial, where multiple players (ίe., cloud service providers, macrocell and small cells, users) with multiple objectives coexist. This paper proposes a mobile data offloading framework using a noncooperative multi-level game-theoretic approach from an end-to-end perspective in the envisioned network. More specifically, we design three-level Stackelberg games, in which a single-leader multi-follower game, a multi-leader multi-follower game, and a single-leader multi-follower game are modeled in the introduced network such that individual players selfishly optimize their local payoff functions and collectively solve the large complex network-wide optimization problem. Further, we develop distributed mobile data offloading algorithms to reduce the complexity of the hierarchical games and to achieve a unique Nash equilibrium condition in each subgame. Simulation results show that by reaching the Nash equilibrium condition, the proposed solution helps minimize energy consumption, interference price, and processing cost, while maximizing revenues of the players in the envisioned network. In addition, the efficiency of the equilibria in terms of price of anarchy and price of stability is quantified for the best/worst case of the Nash equilibrium.",bhaskar rimai,Mobile cloud computing (MCC),2017.0,10.1364/JOCN.9.000601,IEEE/OSA Journal of Optical Communications and Networking,Rimai2017,False,,IEEE,Not available,Mobile data offloading in FiWi enhanced LTE-A heterogeneous networks,9e1d53a3b64be142024910ca68ac89e4,
1416,"This paper proposes to empower capacityand coverage-centric fiber-wireless (FiWi) enhanced 4G LongTerm Evolution Advanced (LTE-A) heterogeneous networks (HetNets) with computationand storage-centric mobile cloud computing to cope with the unprecedented growth of mobile data traffic. Minimizing energy consumption and maximizing revenue while offloading mobile data in such highly converged and hierarchical networks is not trivial, where multiple players (ίe., cloud service providers, macrocell and small cells, users) with multiple objectives coexist. This paper proposes a mobile data offloading framework using a noncooperative multi-level game-theoretic approach from an end-to-end perspective in the envisioned network. More specifically, we design three-level Stackelberg games, in which a single-leader multi-follower game, a multi-leader multi-follower game, and a single-leader multi-follower game are modeled in the introduced network such that individual players selfishly optimize their local payoff functions and collectively solve the large complex network-wide optimization problem. Further, we develop distributed mobile data offloading algorithms to reduce the complexity of the hierarchical games and to achieve a unique Nash equilibrium condition in each subgame. Simulation results show that by reaching the Nash equilibrium condition, the proposed solution helps minimize energy consumption, interference price, and processing cost, while maximizing revenues of the players in the envisioned network. In addition, the efficiency of the equilibria in terms of price of anarchy and price of stability is quantified for the best/worst case of the Nash equilibrium.",bhaskar rimai,Mobile data offloading,2017.0,10.1364/JOCN.9.000601,IEEE/OSA Journal of Optical Communications and Networking,Rimai2017,False,,IEEE,Not available,Mobile data offloading in FiWi enhanced LTE-A heterogeneous networks,9e1d53a3b64be142024910ca68ac89e4,
1417,"This paper proposes to empower capacityand coverage-centric fiber-wireless (FiWi) enhanced 4G LongTerm Evolution Advanced (LTE-A) heterogeneous networks (HetNets) with computationand storage-centric mobile cloud computing to cope with the unprecedented growth of mobile data traffic. Minimizing energy consumption and maximizing revenue while offloading mobile data in such highly converged and hierarchical networks is not trivial, where multiple players (ίe., cloud service providers, macrocell and small cells, users) with multiple objectives coexist. This paper proposes a mobile data offloading framework using a noncooperative multi-level game-theoretic approach from an end-to-end perspective in the envisioned network. More specifically, we design three-level Stackelberg games, in which a single-leader multi-follower game, a multi-leader multi-follower game, and a single-leader multi-follower game are modeled in the introduced network such that individual players selfishly optimize their local payoff functions and collectively solve the large complex network-wide optimization problem. Further, we develop distributed mobile data offloading algorithms to reduce the complexity of the hierarchical games and to achieve a unique Nash equilibrium condition in each subgame. Simulation results show that by reaching the Nash equilibrium condition, the proposed solution helps minimize energy consumption, interference price, and processing cost, while maximizing revenues of the players in the envisioned network. In addition, the efficiency of the equilibria in terms of price of anarchy and price of stability is quantified for the best/worst case of the Nash equilibrium.",bhaskar rimai,Nash equilibrium,2017.0,10.1364/JOCN.9.000601,IEEE/OSA Journal of Optical Communications and Networking,Rimai2017,False,,IEEE,Not available,Mobile data offloading in FiWi enhanced LTE-A heterogeneous networks,9e1d53a3b64be142024910ca68ac89e4,
1418,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
1419,"This paper proposes to empower capacityand coverage-centric fiber-wireless (FiWi) enhanced 4G LongTerm Evolution Advanced (LTE-A) heterogeneous networks (HetNets) with computationand storage-centric mobile cloud computing to cope with the unprecedented growth of mobile data traffic. Minimizing energy consumption and maximizing revenue while offloading mobile data in such highly converged and hierarchical networks is not trivial, where multiple players (ίe., cloud service providers, macrocell and small cells, users) with multiple objectives coexist. This paper proposes a mobile data offloading framework using a noncooperative multi-level game-theoretic approach from an end-to-end perspective in the envisioned network. More specifically, we design three-level Stackelberg games, in which a single-leader multi-follower game, a multi-leader multi-follower game, and a single-leader multi-follower game are modeled in the introduced network such that individual players selfishly optimize their local payoff functions and collectively solve the large complex network-wide optimization problem. Further, we develop distributed mobile data offloading algorithms to reduce the complexity of the hierarchical games and to achieve a unique Nash equilibrium condition in each subgame. Simulation results show that by reaching the Nash equilibrium condition, the proposed solution helps minimize energy consumption, interference price, and processing cost, while maximizing revenues of the players in the envisioned network. In addition, the efficiency of the equilibria in terms of price of anarchy and price of stability is quantified for the best/worst case of the Nash equilibrium.",bhaskar rimai,Passive optical networks (PONs),2017.0,10.1364/JOCN.9.000601,IEEE/OSA Journal of Optical Communications and Networking,Rimai2017,False,,IEEE,Not available,Mobile data offloading in FiWi enhanced LTE-A heterogeneous networks,9e1d53a3b64be142024910ca68ac89e4,
1420,"This paper proposes to empower capacityand coverage-centric fiber-wireless (FiWi) enhanced 4G LongTerm Evolution Advanced (LTE-A) heterogeneous networks (HetNets) with computationand storage-centric mobile cloud computing to cope with the unprecedented growth of mobile data traffic. Minimizing energy consumption and maximizing revenue while offloading mobile data in such highly converged and hierarchical networks is not trivial, where multiple players (ίe., cloud service providers, macrocell and small cells, users) with multiple objectives coexist. This paper proposes a mobile data offloading framework using a noncooperative multi-level game-theoretic approach from an end-to-end perspective in the envisioned network. More specifically, we design three-level Stackelberg games, in which a single-leader multi-follower game, a multi-leader multi-follower game, and a single-leader multi-follower game are modeled in the introduced network such that individual players selfishly optimize their local payoff functions and collectively solve the large complex network-wide optimization problem. Further, we develop distributed mobile data offloading algorithms to reduce the complexity of the hierarchical games and to achieve a unique Nash equilibrium condition in each subgame. Simulation results show that by reaching the Nash equilibrium condition, the proposed solution helps minimize energy consumption, interference price, and processing cost, while maximizing revenues of the players in the envisioned network. In addition, the efficiency of the equilibria in terms of price of anarchy and price of stability is quantified for the best/worst case of the Nash equilibrium.",bhaskar rimai,Price of anarchy (PoA),2017.0,10.1364/JOCN.9.000601,IEEE/OSA Journal of Optical Communications and Networking,Rimai2017,False,,IEEE,Not available,Mobile data offloading in FiWi enhanced LTE-A heterogeneous networks,9e1d53a3b64be142024910ca68ac89e4,
1421,"This paper proposes to empower capacityand coverage-centric fiber-wireless (FiWi) enhanced 4G LongTerm Evolution Advanced (LTE-A) heterogeneous networks (HetNets) with computationand storage-centric mobile cloud computing to cope with the unprecedented growth of mobile data traffic. Minimizing energy consumption and maximizing revenue while offloading mobile data in such highly converged and hierarchical networks is not trivial, where multiple players (ίe., cloud service providers, macrocell and small cells, users) with multiple objectives coexist. This paper proposes a mobile data offloading framework using a noncooperative multi-level game-theoretic approach from an end-to-end perspective in the envisioned network. More specifically, we design three-level Stackelberg games, in which a single-leader multi-follower game, a multi-leader multi-follower game, and a single-leader multi-follower game are modeled in the introduced network such that individual players selfishly optimize their local payoff functions and collectively solve the large complex network-wide optimization problem. Further, we develop distributed mobile data offloading algorithms to reduce the complexity of the hierarchical games and to achieve a unique Nash equilibrium condition in each subgame. Simulation results show that by reaching the Nash equilibrium condition, the proposed solution helps minimize energy consumption, interference price, and processing cost, while maximizing revenues of the players in the envisioned network. In addition, the efficiency of the equilibria in terms of price of anarchy and price of stability is quantified for the best/worst case of the Nash equilibrium.",martin maier,Fiber-wireless (FiWi),2017.0,10.1364/JOCN.9.000601,IEEE/OSA Journal of Optical Communications and Networking,Rimai2017,False,,IEEE,Not available,Mobile data offloading in FiWi enhanced LTE-A heterogeneous networks,9e1d53a3b64be142024910ca68ac89e4,
1422,"This paper proposes to empower capacityand coverage-centric fiber-wireless (FiWi) enhanced 4G LongTerm Evolution Advanced (LTE-A) heterogeneous networks (HetNets) with computationand storage-centric mobile cloud computing to cope with the unprecedented growth of mobile data traffic. Minimizing energy consumption and maximizing revenue while offloading mobile data in such highly converged and hierarchical networks is not trivial, where multiple players (ίe., cloud service providers, macrocell and small cells, users) with multiple objectives coexist. This paper proposes a mobile data offloading framework using a noncooperative multi-level game-theoretic approach from an end-to-end perspective in the envisioned network. More specifically, we design three-level Stackelberg games, in which a single-leader multi-follower game, a multi-leader multi-follower game, and a single-leader multi-follower game are modeled in the introduced network such that individual players selfishly optimize their local payoff functions and collectively solve the large complex network-wide optimization problem. Further, we develop distributed mobile data offloading algorithms to reduce the complexity of the hierarchical games and to achieve a unique Nash equilibrium condition in each subgame. Simulation results show that by reaching the Nash equilibrium condition, the proposed solution helps minimize energy consumption, interference price, and processing cost, while maximizing revenues of the players in the envisioned network. In addition, the efficiency of the equilibria in terms of price of anarchy and price of stability is quantified for the best/worst case of the Nash equilibrium.",martin maier,Game theory,2017.0,10.1364/JOCN.9.000601,IEEE/OSA Journal of Optical Communications and Networking,Rimai2017,False,,IEEE,Not available,Mobile data offloading in FiWi enhanced LTE-A heterogeneous networks,9e1d53a3b64be142024910ca68ac89e4,
1423,"This paper proposes to empower capacityand coverage-centric fiber-wireless (FiWi) enhanced 4G LongTerm Evolution Advanced (LTE-A) heterogeneous networks (HetNets) with computationand storage-centric mobile cloud computing to cope with the unprecedented growth of mobile data traffic. Minimizing energy consumption and maximizing revenue while offloading mobile data in such highly converged and hierarchical networks is not trivial, where multiple players (ίe., cloud service providers, macrocell and small cells, users) with multiple objectives coexist. This paper proposes a mobile data offloading framework using a noncooperative multi-level game-theoretic approach from an end-to-end perspective in the envisioned network. More specifically, we design three-level Stackelberg games, in which a single-leader multi-follower game, a multi-leader multi-follower game, and a single-leader multi-follower game are modeled in the introduced network such that individual players selfishly optimize their local payoff functions and collectively solve the large complex network-wide optimization problem. Further, we develop distributed mobile data offloading algorithms to reduce the complexity of the hierarchical games and to achieve a unique Nash equilibrium condition in each subgame. Simulation results show that by reaching the Nash equilibrium condition, the proposed solution helps minimize energy consumption, interference price, and processing cost, while maximizing revenues of the players in the envisioned network. In addition, the efficiency of the equilibria in terms of price of anarchy and price of stability is quantified for the best/worst case of the Nash equilibrium.",martin maier,Heterogeneous networks,2017.0,10.1364/JOCN.9.000601,IEEE/OSA Journal of Optical Communications and Networking,Rimai2017,False,,IEEE,Not available,Mobile data offloading in FiWi enhanced LTE-A heterogeneous networks,9e1d53a3b64be142024910ca68ac89e4,
1424,"This paper proposes to empower capacityand coverage-centric fiber-wireless (FiWi) enhanced 4G LongTerm Evolution Advanced (LTE-A) heterogeneous networks (HetNets) with computationand storage-centric mobile cloud computing to cope with the unprecedented growth of mobile data traffic. Minimizing energy consumption and maximizing revenue while offloading mobile data in such highly converged and hierarchical networks is not trivial, where multiple players (ίe., cloud service providers, macrocell and small cells, users) with multiple objectives coexist. This paper proposes a mobile data offloading framework using a noncooperative multi-level game-theoretic approach from an end-to-end perspective in the envisioned network. More specifically, we design three-level Stackelberg games, in which a single-leader multi-follower game, a multi-leader multi-follower game, and a single-leader multi-follower game are modeled in the introduced network such that individual players selfishly optimize their local payoff functions and collectively solve the large complex network-wide optimization problem. Further, we develop distributed mobile data offloading algorithms to reduce the complexity of the hierarchical games and to achieve a unique Nash equilibrium condition in each subgame. Simulation results show that by reaching the Nash equilibrium condition, the proposed solution helps minimize energy consumption, interference price, and processing cost, while maximizing revenues of the players in the envisioned network. In addition, the efficiency of the equilibria in terms of price of anarchy and price of stability is quantified for the best/worst case of the Nash equilibrium.",martin maier,Mobile cloud computing (MCC),2017.0,10.1364/JOCN.9.000601,IEEE/OSA Journal of Optical Communications and Networking,Rimai2017,False,,IEEE,Not available,Mobile data offloading in FiWi enhanced LTE-A heterogeneous networks,9e1d53a3b64be142024910ca68ac89e4,
1425,"This paper proposes to empower capacityand coverage-centric fiber-wireless (FiWi) enhanced 4G LongTerm Evolution Advanced (LTE-A) heterogeneous networks (HetNets) with computationand storage-centric mobile cloud computing to cope with the unprecedented growth of mobile data traffic. Minimizing energy consumption and maximizing revenue while offloading mobile data in such highly converged and hierarchical networks is not trivial, where multiple players (ίe., cloud service providers, macrocell and small cells, users) with multiple objectives coexist. This paper proposes a mobile data offloading framework using a noncooperative multi-level game-theoretic approach from an end-to-end perspective in the envisioned network. More specifically, we design three-level Stackelberg games, in which a single-leader multi-follower game, a multi-leader multi-follower game, and a single-leader multi-follower game are modeled in the introduced network such that individual players selfishly optimize their local payoff functions and collectively solve the large complex network-wide optimization problem. Further, we develop distributed mobile data offloading algorithms to reduce the complexity of the hierarchical games and to achieve a unique Nash equilibrium condition in each subgame. Simulation results show that by reaching the Nash equilibrium condition, the proposed solution helps minimize energy consumption, interference price, and processing cost, while maximizing revenues of the players in the envisioned network. In addition, the efficiency of the equilibria in terms of price of anarchy and price of stability is quantified for the best/worst case of the Nash equilibrium.",martin maier,Mobile data offloading,2017.0,10.1364/JOCN.9.000601,IEEE/OSA Journal of Optical Communications and Networking,Rimai2017,False,,IEEE,Not available,Mobile data offloading in FiWi enhanced LTE-A heterogeneous networks,9e1d53a3b64be142024910ca68ac89e4,
1426,"This paper proposes to empower capacityand coverage-centric fiber-wireless (FiWi) enhanced 4G LongTerm Evolution Advanced (LTE-A) heterogeneous networks (HetNets) with computationand storage-centric mobile cloud computing to cope with the unprecedented growth of mobile data traffic. Minimizing energy consumption and maximizing revenue while offloading mobile data in such highly converged and hierarchical networks is not trivial, where multiple players (ίe., cloud service providers, macrocell and small cells, users) with multiple objectives coexist. This paper proposes a mobile data offloading framework using a noncooperative multi-level game-theoretic approach from an end-to-end perspective in the envisioned network. More specifically, we design three-level Stackelberg games, in which a single-leader multi-follower game, a multi-leader multi-follower game, and a single-leader multi-follower game are modeled in the introduced network such that individual players selfishly optimize their local payoff functions and collectively solve the large complex network-wide optimization problem. Further, we develop distributed mobile data offloading algorithms to reduce the complexity of the hierarchical games and to achieve a unique Nash equilibrium condition in each subgame. Simulation results show that by reaching the Nash equilibrium condition, the proposed solution helps minimize energy consumption, interference price, and processing cost, while maximizing revenues of the players in the envisioned network. In addition, the efficiency of the equilibria in terms of price of anarchy and price of stability is quantified for the best/worst case of the Nash equilibrium.",martin maier,Nash equilibrium,2017.0,10.1364/JOCN.9.000601,IEEE/OSA Journal of Optical Communications and Networking,Rimai2017,False,,IEEE,Not available,Mobile data offloading in FiWi enhanced LTE-A heterogeneous networks,9e1d53a3b64be142024910ca68ac89e4,
1427,"This paper proposes to empower capacityand coverage-centric fiber-wireless (FiWi) enhanced 4G LongTerm Evolution Advanced (LTE-A) heterogeneous networks (HetNets) with computationand storage-centric mobile cloud computing to cope with the unprecedented growth of mobile data traffic. Minimizing energy consumption and maximizing revenue while offloading mobile data in such highly converged and hierarchical networks is not trivial, where multiple players (ίe., cloud service providers, macrocell and small cells, users) with multiple objectives coexist. This paper proposes a mobile data offloading framework using a noncooperative multi-level game-theoretic approach from an end-to-end perspective in the envisioned network. More specifically, we design three-level Stackelberg games, in which a single-leader multi-follower game, a multi-leader multi-follower game, and a single-leader multi-follower game are modeled in the introduced network such that individual players selfishly optimize their local payoff functions and collectively solve the large complex network-wide optimization problem. Further, we develop distributed mobile data offloading algorithms to reduce the complexity of the hierarchical games and to achieve a unique Nash equilibrium condition in each subgame. Simulation results show that by reaching the Nash equilibrium condition, the proposed solution helps minimize energy consumption, interference price, and processing cost, while maximizing revenues of the players in the envisioned network. In addition, the efficiency of the equilibria in terms of price of anarchy and price of stability is quantified for the best/worst case of the Nash equilibrium.",martin maier,Passive optical networks (PONs),2017.0,10.1364/JOCN.9.000601,IEEE/OSA Journal of Optical Communications and Networking,Rimai2017,False,,IEEE,Not available,Mobile data offloading in FiWi enhanced LTE-A heterogeneous networks,9e1d53a3b64be142024910ca68ac89e4,
1428,"This paper proposes to empower capacityand coverage-centric fiber-wireless (FiWi) enhanced 4G LongTerm Evolution Advanced (LTE-A) heterogeneous networks (HetNets) with computationand storage-centric mobile cloud computing to cope with the unprecedented growth of mobile data traffic. Minimizing energy consumption and maximizing revenue while offloading mobile data in such highly converged and hierarchical networks is not trivial, where multiple players (ίe., cloud service providers, macrocell and small cells, users) with multiple objectives coexist. This paper proposes a mobile data offloading framework using a noncooperative multi-level game-theoretic approach from an end-to-end perspective in the envisioned network. More specifically, we design three-level Stackelberg games, in which a single-leader multi-follower game, a multi-leader multi-follower game, and a single-leader multi-follower game are modeled in the introduced network such that individual players selfishly optimize their local payoff functions and collectively solve the large complex network-wide optimization problem. Further, we develop distributed mobile data offloading algorithms to reduce the complexity of the hierarchical games and to achieve a unique Nash equilibrium condition in each subgame. Simulation results show that by reaching the Nash equilibrium condition, the proposed solution helps minimize energy consumption, interference price, and processing cost, while maximizing revenues of the players in the envisioned network. In addition, the efficiency of the equilibria in terms of price of anarchy and price of stability is quantified for the best/worst case of the Nash equilibrium.",martin maier,Price of anarchy (PoA),2017.0,10.1364/JOCN.9.000601,IEEE/OSA Journal of Optical Communications and Networking,Rimai2017,False,,IEEE,Not available,Mobile data offloading in FiWi enhanced LTE-A heterogeneous networks,9e1d53a3b64be142024910ca68ac89e4,
1429,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
1430,"This paper systematically explores the efficiency of uncoordinated parking space allocation in urban environments with two types of parking facilities. Drivers decide whether to go for inexpensive but limited on-street parking spots or for expensive yet overdimensioned parking lots, incurring an additional cruising cost when they decide for on-street parking spots but fail to actually acquire one. Their decisions are made under perfect knowledge of the total parking supply and costs and different levels of information about the parking demand, i.e., complete/probabilistic information and uncertainty. We take a game-theoretic approach and analyze the parking-space allocation process in each case as resource selection game instances. We derive their equilibria, compute the related price-of-anarchy (PoA) values, and study the impact of pricing on them. It is shown that, under typical pricing policies on the two types of parking facilities, drivers tend to overcompete for the on-street parking space, giving rise to redundant cruising cost. However, this inefficiency can be alleviated through systematic manipulation of the information that is announced to the drivers. In particular, counterintuitive less-is-more effects emerge regarding the way that information availability modulates the resulting efficiency of the process, which underpin general competitive service provision settings.",evangelia kokolaki,Intelligent transportation,2013.0,10.1109/TVT.2013.2269015,IEEE Transactions on Vehicular Technology,Kokolaki2013,False,,IEEE,Not available,Leveraging Information in Parking Assistance Systems,44a9a7938c886c516d9f166e35b8e133,https://ieeexplore.ieee.org/document/6542023/
1431,"This paper systematically explores the efficiency of uncoordinated parking space allocation in urban environments with two types of parking facilities. Drivers decide whether to go for inexpensive but limited on-street parking spots or for expensive yet overdimensioned parking lots, incurring an additional cruising cost when they decide for on-street parking spots but fail to actually acquire one. Their decisions are made under perfect knowledge of the total parking supply and costs and different levels of information about the parking demand, i.e., complete/probabilistic information and uncertainty. We take a game-theoretic approach and analyze the parking-space allocation process in each case as resource selection game instances. We derive their equilibria, compute the related price-of-anarchy (PoA) values, and study the impact of pricing on them. It is shown that, under typical pricing policies on the two types of parking facilities, drivers tend to overcompete for the on-street parking space, giving rise to redundant cruising cost. However, this inefficiency can be alleviated through systematic manipulation of the information that is announced to the drivers. In particular, counterintuitive less-is-more effects emerge regarding the way that information availability modulates the resulting efficiency of the process, which underpin general competitive service provision settings.",evangelia kokolaki,parking games,2013.0,10.1109/TVT.2013.2269015,IEEE Transactions on Vehicular Technology,Kokolaki2013,False,,IEEE,Not available,Leveraging Information in Parking Assistance Systems,44a9a7938c886c516d9f166e35b8e133,https://ieeexplore.ieee.org/document/6542023/
1432,"This paper systematically explores the efficiency of uncoordinated parking space allocation in urban environments with two types of parking facilities. Drivers decide whether to go for inexpensive but limited on-street parking spots or for expensive yet overdimensioned parking lots, incurring an additional cruising cost when they decide for on-street parking spots but fail to actually acquire one. Their decisions are made under perfect knowledge of the total parking supply and costs and different levels of information about the parking demand, i.e., complete/probabilistic information and uncertainty. We take a game-theoretic approach and analyze the parking-space allocation process in each case as resource selection game instances. We derive their equilibria, compute the related price-of-anarchy (PoA) values, and study the impact of pricing on them. It is shown that, under typical pricing policies on the two types of parking facilities, drivers tend to overcompete for the on-street parking space, giving rise to redundant cruising cost. However, this inefficiency can be alleviated through systematic manipulation of the information that is announced to the drivers. In particular, counterintuitive less-is-more effects emerge regarding the way that information availability modulates the resulting efficiency of the process, which underpin general competitive service provision settings.",evangelia kokolaki,uncertainty,2013.0,10.1109/TVT.2013.2269015,IEEE Transactions on Vehicular Technology,Kokolaki2013,False,,IEEE,Not available,Leveraging Information in Parking Assistance Systems,44a9a7938c886c516d9f166e35b8e133,https://ieeexplore.ieee.org/document/6542023/
1433,"This paper systematically explores the efficiency of uncoordinated parking space allocation in urban environments with two types of parking facilities. Drivers decide whether to go for inexpensive but limited on-street parking spots or for expensive yet overdimensioned parking lots, incurring an additional cruising cost when they decide for on-street parking spots but fail to actually acquire one. Their decisions are made under perfect knowledge of the total parking supply and costs and different levels of information about the parking demand, i.e., complete/probabilistic information and uncertainty. We take a game-theoretic approach and analyze the parking-space allocation process in each case as resource selection game instances. We derive their equilibria, compute the related price-of-anarchy (PoA) values, and study the impact of pricing on them. It is shown that, under typical pricing policies on the two types of parking facilities, drivers tend to overcompete for the on-street parking space, giving rise to redundant cruising cost. However, this inefficiency can be alleviated through systematic manipulation of the information that is announced to the drivers. In particular, counterintuitive less-is-more effects emerge regarding the way that information availability modulates the resulting efficiency of the process, which underpin general competitive service provision settings.",evangelia kokolaki,vehicular ad hoc networks (VANETs),2013.0,10.1109/TVT.2013.2269015,IEEE Transactions on Vehicular Technology,Kokolaki2013,False,,IEEE,Not available,Leveraging Information in Parking Assistance Systems,44a9a7938c886c516d9f166e35b8e133,https://ieeexplore.ieee.org/document/6542023/
1434,"This paper systematically explores the efficiency of uncoordinated parking space allocation in urban environments with two types of parking facilities. Drivers decide whether to go for inexpensive but limited on-street parking spots or for expensive yet overdimensioned parking lots, incurring an additional cruising cost when they decide for on-street parking spots but fail to actually acquire one. Their decisions are made under perfect knowledge of the total parking supply and costs and different levels of information about the parking demand, i.e., complete/probabilistic information and uncertainty. We take a game-theoretic approach and analyze the parking-space allocation process in each case as resource selection game instances. We derive their equilibria, compute the related price-of-anarchy (PoA) values, and study the impact of pricing on them. It is shown that, under typical pricing policies on the two types of parking facilities, drivers tend to overcompete for the on-street parking space, giving rise to redundant cruising cost. However, this inefficiency can be alleviated through systematic manipulation of the information that is announced to the drivers. In particular, counterintuitive less-is-more effects emerge regarding the way that information availability modulates the resulting efficiency of the process, which underpin general competitive service provision settings.",merkouris karaliopoulos,Intelligent transportation,2013.0,10.1109/TVT.2013.2269015,IEEE Transactions on Vehicular Technology,Kokolaki2013,False,,IEEE,Not available,Leveraging Information in Parking Assistance Systems,44a9a7938c886c516d9f166e35b8e133,https://ieeexplore.ieee.org/document/6542023/
1435,"This paper systematically explores the efficiency of uncoordinated parking space allocation in urban environments with two types of parking facilities. Drivers decide whether to go for inexpensive but limited on-street parking spots or for expensive yet overdimensioned parking lots, incurring an additional cruising cost when they decide for on-street parking spots but fail to actually acquire one. Their decisions are made under perfect knowledge of the total parking supply and costs and different levels of information about the parking demand, i.e., complete/probabilistic information and uncertainty. We take a game-theoretic approach and analyze the parking-space allocation process in each case as resource selection game instances. We derive their equilibria, compute the related price-of-anarchy (PoA) values, and study the impact of pricing on them. It is shown that, under typical pricing policies on the two types of parking facilities, drivers tend to overcompete for the on-street parking space, giving rise to redundant cruising cost. However, this inefficiency can be alleviated through systematic manipulation of the information that is announced to the drivers. In particular, counterintuitive less-is-more effects emerge regarding the way that information availability modulates the resulting efficiency of the process, which underpin general competitive service provision settings.",merkouris karaliopoulos,parking games,2013.0,10.1109/TVT.2013.2269015,IEEE Transactions on Vehicular Technology,Kokolaki2013,False,,IEEE,Not available,Leveraging Information in Parking Assistance Systems,44a9a7938c886c516d9f166e35b8e133,https://ieeexplore.ieee.org/document/6542023/
1436,"This paper systematically explores the efficiency of uncoordinated parking space allocation in urban environments with two types of parking facilities. Drivers decide whether to go for inexpensive but limited on-street parking spots or for expensive yet overdimensioned parking lots, incurring an additional cruising cost when they decide for on-street parking spots but fail to actually acquire one. Their decisions are made under perfect knowledge of the total parking supply and costs and different levels of information about the parking demand, i.e., complete/probabilistic information and uncertainty. We take a game-theoretic approach and analyze the parking-space allocation process in each case as resource selection game instances. We derive their equilibria, compute the related price-of-anarchy (PoA) values, and study the impact of pricing on them. It is shown that, under typical pricing policies on the two types of parking facilities, drivers tend to overcompete for the on-street parking space, giving rise to redundant cruising cost. However, this inefficiency can be alleviated through systematic manipulation of the information that is announced to the drivers. In particular, counterintuitive less-is-more effects emerge regarding the way that information availability modulates the resulting efficiency of the process, which underpin general competitive service provision settings.",merkouris karaliopoulos,uncertainty,2013.0,10.1109/TVT.2013.2269015,IEEE Transactions on Vehicular Technology,Kokolaki2013,False,,IEEE,Not available,Leveraging Information in Parking Assistance Systems,44a9a7938c886c516d9f166e35b8e133,https://ieeexplore.ieee.org/document/6542023/
1437,"This paper systematically explores the efficiency of uncoordinated parking space allocation in urban environments with two types of parking facilities. Drivers decide whether to go for inexpensive but limited on-street parking spots or for expensive yet overdimensioned parking lots, incurring an additional cruising cost when they decide for on-street parking spots but fail to actually acquire one. Their decisions are made under perfect knowledge of the total parking supply and costs and different levels of information about the parking demand, i.e., complete/probabilistic information and uncertainty. We take a game-theoretic approach and analyze the parking-space allocation process in each case as resource selection game instances. We derive their equilibria, compute the related price-of-anarchy (PoA) values, and study the impact of pricing on them. It is shown that, under typical pricing policies on the two types of parking facilities, drivers tend to overcompete for the on-street parking space, giving rise to redundant cruising cost. However, this inefficiency can be alleviated through systematic manipulation of the information that is announced to the drivers. In particular, counterintuitive less-is-more effects emerge regarding the way that information availability modulates the resulting efficiency of the process, which underpin general competitive service provision settings.",merkouris karaliopoulos,vehicular ad hoc networks (VANETs),2013.0,10.1109/TVT.2013.2269015,IEEE Transactions on Vehicular Technology,Kokolaki2013,False,,IEEE,Not available,Leveraging Information in Parking Assistance Systems,44a9a7938c886c516d9f166e35b8e133,https://ieeexplore.ieee.org/document/6542023/
1438,"This paper systematically explores the efficiency of uncoordinated parking space allocation in urban environments with two types of parking facilities. Drivers decide whether to go for inexpensive but limited on-street parking spots or for expensive yet overdimensioned parking lots, incurring an additional cruising cost when they decide for on-street parking spots but fail to actually acquire one. Their decisions are made under perfect knowledge of the total parking supply and costs and different levels of information about the parking demand, i.e., complete/probabilistic information and uncertainty. We take a game-theoretic approach and analyze the parking-space allocation process in each case as resource selection game instances. We derive their equilibria, compute the related price-of-anarchy (PoA) values, and study the impact of pricing on them. It is shown that, under typical pricing policies on the two types of parking facilities, drivers tend to overcompete for the on-street parking space, giving rise to redundant cruising cost. However, this inefficiency can be alleviated through systematic manipulation of the information that is announced to the drivers. In particular, counterintuitive less-is-more effects emerge regarding the way that information availability modulates the resulting efficiency of the process, which underpin general competitive service provision settings.",ioannis stavrakakis,Intelligent transportation,2013.0,10.1109/TVT.2013.2269015,IEEE Transactions on Vehicular Technology,Kokolaki2013,False,,IEEE,Not available,Leveraging Information in Parking Assistance Systems,44a9a7938c886c516d9f166e35b8e133,https://ieeexplore.ieee.org/document/6542023/
1439,"This paper systematically explores the efficiency of uncoordinated parking space allocation in urban environments with two types of parking facilities. Drivers decide whether to go for inexpensive but limited on-street parking spots or for expensive yet overdimensioned parking lots, incurring an additional cruising cost when they decide for on-street parking spots but fail to actually acquire one. Their decisions are made under perfect knowledge of the total parking supply and costs and different levels of information about the parking demand, i.e., complete/probabilistic information and uncertainty. We take a game-theoretic approach and analyze the parking-space allocation process in each case as resource selection game instances. We derive their equilibria, compute the related price-of-anarchy (PoA) values, and study the impact of pricing on them. It is shown that, under typical pricing policies on the two types of parking facilities, drivers tend to overcompete for the on-street parking space, giving rise to redundant cruising cost. However, this inefficiency can be alleviated through systematic manipulation of the information that is announced to the drivers. In particular, counterintuitive less-is-more effects emerge regarding the way that information availability modulates the resulting efficiency of the process, which underpin general competitive service provision settings.",ioannis stavrakakis,parking games,2013.0,10.1109/TVT.2013.2269015,IEEE Transactions on Vehicular Technology,Kokolaki2013,False,,IEEE,Not available,Leveraging Information in Parking Assistance Systems,44a9a7938c886c516d9f166e35b8e133,https://ieeexplore.ieee.org/document/6542023/
1440,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
1441,"This paper systematically explores the efficiency of uncoordinated parking space allocation in urban environments with two types of parking facilities. Drivers decide whether to go for inexpensive but limited on-street parking spots or for expensive yet overdimensioned parking lots, incurring an additional cruising cost when they decide for on-street parking spots but fail to actually acquire one. Their decisions are made under perfect knowledge of the total parking supply and costs and different levels of information about the parking demand, i.e., complete/probabilistic information and uncertainty. We take a game-theoretic approach and analyze the parking-space allocation process in each case as resource selection game instances. We derive their equilibria, compute the related price-of-anarchy (PoA) values, and study the impact of pricing on them. It is shown that, under typical pricing policies on the two types of parking facilities, drivers tend to overcompete for the on-street parking space, giving rise to redundant cruising cost. However, this inefficiency can be alleviated through systematic manipulation of the information that is announced to the drivers. In particular, counterintuitive less-is-more effects emerge regarding the way that information availability modulates the resulting efficiency of the process, which underpin general competitive service provision settings.",ioannis stavrakakis,uncertainty,2013.0,10.1109/TVT.2013.2269015,IEEE Transactions on Vehicular Technology,Kokolaki2013,False,,IEEE,Not available,Leveraging Information in Parking Assistance Systems,44a9a7938c886c516d9f166e35b8e133,https://ieeexplore.ieee.org/document/6542023/
1442,"This paper systematically explores the efficiency of uncoordinated parking space allocation in urban environments with two types of parking facilities. Drivers decide whether to go for inexpensive but limited on-street parking spots or for expensive yet overdimensioned parking lots, incurring an additional cruising cost when they decide for on-street parking spots but fail to actually acquire one. Their decisions are made under perfect knowledge of the total parking supply and costs and different levels of information about the parking demand, i.e., complete/probabilistic information and uncertainty. We take a game-theoretic approach and analyze the parking-space allocation process in each case as resource selection game instances. We derive their equilibria, compute the related price-of-anarchy (PoA) values, and study the impact of pricing on them. It is shown that, under typical pricing policies on the two types of parking facilities, drivers tend to overcompete for the on-street parking space, giving rise to redundant cruising cost. However, this inefficiency can be alleviated through systematic manipulation of the information that is announced to the drivers. In particular, counterintuitive less-is-more effects emerge regarding the way that information availability modulates the resulting efficiency of the process, which underpin general competitive service provision settings.",ioannis stavrakakis,vehicular ad hoc networks (VANETs),2013.0,10.1109/TVT.2013.2269015,IEEE Transactions on Vehicular Technology,Kokolaki2013,False,,IEEE,Not available,Leveraging Information in Parking Assistance Systems,44a9a7938c886c516d9f166e35b8e133,https://ieeexplore.ieee.org/document/6542023/
1443,"In this paper, a static non-cooperative game formulation of the problem of distributed charging in electrical vehicle (EV) networks is proposed. This formulation allows one to model the interaction between several EV which are connected to a common residential distribution transformer. Each EV aims at choosing the time at which it starts charging its battery in order to minimize an individual cost which is mainly related to the total power delivered by the transformer, the location of the time interval over which the charging operation is performed, and the charging duration needed for the considered EV to have its battery fully recharged. As individual cost functions are assumed to be memoryless, it is possible to show that the game of interest is always an ordinal potential game. More precisely, both an atomic and nonatomic versions of the charging game are considered. In both cases, equilibrium analysis is conducted. In particular, important issues such as equilibrium uniqueness and efficiency are tackled. Interestingly, both analytical and numerical results show that the efficiency loss due to decentralization (e.g., when cost functions such as distribution network Joule losses or life of residential distribution transformers when no thermal inertia is assumed) induced by charging is small and the corresponding “efficiency”, a notion close to the Price of Anarchy, tends to one when the number of EV increases.",olivier beaude,Charging games,2012.0,,"2012 6th International Conference on Network Games, Control and Optimization (NetGCooP)",Beaude2012,False,,IEEE,Not available,Charging games in networks of electrical vehicles,914d658c34542b3882aa11ffdb928190,
1444,"In this paper, a static non-cooperative game formulation of the problem of distributed charging in electrical vehicle (EV) networks is proposed. This formulation allows one to model the interaction between several EV which are connected to a common residential distribution transformer. Each EV aims at choosing the time at which it starts charging its battery in order to minimize an individual cost which is mainly related to the total power delivered by the transformer, the location of the time interval over which the charging operation is performed, and the charging duration needed for the considered EV to have its battery fully recharged. As individual cost functions are assumed to be memoryless, it is possible to show that the game of interest is always an ordinal potential game. More precisely, both an atomic and nonatomic versions of the charging game are considered. In both cases, equilibrium analysis is conducted. In particular, important issues such as equilibrium uniqueness and efficiency are tackled. Interestingly, both analytical and numerical results show that the efficiency loss due to decentralization (e.g., when cost functions such as distribution network Joule losses or life of residential distribution transformers when no thermal inertia is assumed) induced by charging is small and the corresponding “efficiency”, a notion close to the Price of Anarchy, tends to one when the number of EV increases.",olivier beaude,electrical vehicle,2012.0,,"2012 6th International Conference on Network Games, Control and Optimization (NetGCooP)",Beaude2012,False,,IEEE,Not available,Charging games in networks of electrical vehicles,914d658c34542b3882aa11ffdb928190,
1445,"In this paper, a static non-cooperative game formulation of the problem of distributed charging in electrical vehicle (EV) networks is proposed. This formulation allows one to model the interaction between several EV which are connected to a common residential distribution transformer. Each EV aims at choosing the time at which it starts charging its battery in order to minimize an individual cost which is mainly related to the total power delivered by the transformer, the location of the time interval over which the charging operation is performed, and the charging duration needed for the considered EV to have its battery fully recharged. As individual cost functions are assumed to be memoryless, it is possible to show that the game of interest is always an ordinal potential game. More precisely, both an atomic and nonatomic versions of the charging game are considered. In both cases, equilibrium analysis is conducted. In particular, important issues such as equilibrium uniqueness and efficiency are tackled. Interestingly, both analytical and numerical results show that the efficiency loss due to decentralization (e.g., when cost functions such as distribution network Joule losses or life of residential distribution transformers when no thermal inertia is assumed) induced by charging is small and the corresponding “efficiency”, a notion close to the Price of Anarchy, tends to one when the number of EV increases.",olivier beaude,distribution networks,2012.0,,"2012 6th International Conference on Network Games, Control and Optimization (NetGCooP)",Beaude2012,False,,IEEE,Not available,Charging games in networks of electrical vehicles,914d658c34542b3882aa11ffdb928190,
1446,"In this paper, a static non-cooperative game formulation of the problem of distributed charging in electrical vehicle (EV) networks is proposed. This formulation allows one to model the interaction between several EV which are connected to a common residential distribution transformer. Each EV aims at choosing the time at which it starts charging its battery in order to minimize an individual cost which is mainly related to the total power delivered by the transformer, the location of the time interval over which the charging operation is performed, and the charging duration needed for the considered EV to have its battery fully recharged. As individual cost functions are assumed to be memoryless, it is possible to show that the game of interest is always an ordinal potential game. More precisely, both an atomic and nonatomic versions of the charging game are considered. In both cases, equilibrium analysis is conducted. In particular, important issues such as equilibrium uniqueness and efficiency are tackled. Interestingly, both analytical and numerical results show that the efficiency loss due to decentralization (e.g., when cost functions such as distribution network Joule losses or life of residential distribution transformers when no thermal inertia is assumed) induced by charging is small and the corresponding “efficiency”, a notion close to the Price of Anarchy, tends to one when the number of EV increases.",olivier beaude,potential games,2012.0,,"2012 6th International Conference on Network Games, Control and Optimization (NetGCooP)",Beaude2012,False,,IEEE,Not available,Charging games in networks of electrical vehicles,914d658c34542b3882aa11ffdb928190,
1447,"In this paper, a static non-cooperative game formulation of the problem of distributed charging in electrical vehicle (EV) networks is proposed. This formulation allows one to model the interaction between several EV which are connected to a common residential distribution transformer. Each EV aims at choosing the time at which it starts charging its battery in order to minimize an individual cost which is mainly related to the total power delivered by the transformer, the location of the time interval over which the charging operation is performed, and the charging duration needed for the considered EV to have its battery fully recharged. As individual cost functions are assumed to be memoryless, it is possible to show that the game of interest is always an ordinal potential game. More precisely, both an atomic and nonatomic versions of the charging game are considered. In both cases, equilibrium analysis is conducted. In particular, important issues such as equilibrium uniqueness and efficiency are tackled. Interestingly, both analytical and numerical results show that the efficiency loss due to decentralization (e.g., when cost functions such as distribution network Joule losses or life of residential distribution transformers when no thermal inertia is assumed) induced by charging is small and the corresponding “efficiency”, a notion close to the Price of Anarchy, tends to one when the number of EV increases.",olivier beaude,Nash equilibrium,2012.0,,"2012 6th International Conference on Network Games, Control and Optimization (NetGCooP)",Beaude2012,False,,IEEE,Not available,Charging games in networks of electrical vehicles,914d658c34542b3882aa11ffdb928190,
1448,"In this paper, a static non-cooperative game formulation of the problem of distributed charging in electrical vehicle (EV) networks is proposed. This formulation allows one to model the interaction between several EV which are connected to a common residential distribution transformer. Each EV aims at choosing the time at which it starts charging its battery in order to minimize an individual cost which is mainly related to the total power delivered by the transformer, the location of the time interval over which the charging operation is performed, and the charging duration needed for the considered EV to have its battery fully recharged. As individual cost functions are assumed to be memoryless, it is possible to show that the game of interest is always an ordinal potential game. More precisely, both an atomic and nonatomic versions of the charging game are considered. In both cases, equilibrium analysis is conducted. In particular, important issues such as equilibrium uniqueness and efficiency are tackled. Interestingly, both analytical and numerical results show that the efficiency loss due to decentralization (e.g., when cost functions such as distribution network Joule losses or life of residential distribution transformers when no thermal inertia is assumed) induced by charging is small and the corresponding “efficiency”, a notion close to the Price of Anarchy, tends to one when the number of EV increases.",olivier beaude,price of anarchy,2012.0,,"2012 6th International Conference on Network Games, Control and Optimization (NetGCooP)",Beaude2012,False,,IEEE,Not available,Charging games in networks of electrical vehicles,914d658c34542b3882aa11ffdb928190,
1449,"In this paper, a static non-cooperative game formulation of the problem of distributed charging in electrical vehicle (EV) networks is proposed. This formulation allows one to model the interaction between several EV which are connected to a common residential distribution transformer. Each EV aims at choosing the time at which it starts charging its battery in order to minimize an individual cost which is mainly related to the total power delivered by the transformer, the location of the time interval over which the charging operation is performed, and the charging duration needed for the considered EV to have its battery fully recharged. As individual cost functions are assumed to be memoryless, it is possible to show that the game of interest is always an ordinal potential game. More precisely, both an atomic and nonatomic versions of the charging game are considered. In both cases, equilibrium analysis is conducted. In particular, important issues such as equilibrium uniqueness and efficiency are tackled. Interestingly, both analytical and numerical results show that the efficiency loss due to decentralization (e.g., when cost functions such as distribution network Joule losses or life of residential distribution transformers when no thermal inertia is assumed) induced by charging is small and the corresponding “efficiency”, a notion close to the Price of Anarchy, tends to one when the number of EV increases.",samson lasaulce,Charging games,2012.0,,"2012 6th International Conference on Network Games, Control and Optimization (NetGCooP)",Beaude2012,False,,IEEE,Not available,Charging games in networks of electrical vehicles,914d658c34542b3882aa11ffdb928190,
1450,"In this paper, a static non-cooperative game formulation of the problem of distributed charging in electrical vehicle (EV) networks is proposed. This formulation allows one to model the interaction between several EV which are connected to a common residential distribution transformer. Each EV aims at choosing the time at which it starts charging its battery in order to minimize an individual cost which is mainly related to the total power delivered by the transformer, the location of the time interval over which the charging operation is performed, and the charging duration needed for the considered EV to have its battery fully recharged. As individual cost functions are assumed to be memoryless, it is possible to show that the game of interest is always an ordinal potential game. More precisely, both an atomic and nonatomic versions of the charging game are considered. In both cases, equilibrium analysis is conducted. In particular, important issues such as equilibrium uniqueness and efficiency are tackled. Interestingly, both analytical and numerical results show that the efficiency loss due to decentralization (e.g., when cost functions such as distribution network Joule losses or life of residential distribution transformers when no thermal inertia is assumed) induced by charging is small and the corresponding “efficiency”, a notion close to the Price of Anarchy, tends to one when the number of EV increases.",samson lasaulce,electrical vehicle,2012.0,,"2012 6th International Conference on Network Games, Control and Optimization (NetGCooP)",Beaude2012,False,,IEEE,Not available,Charging games in networks of electrical vehicles,914d658c34542b3882aa11ffdb928190,
1451,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
1452,"In this paper, a static non-cooperative game formulation of the problem of distributed charging in electrical vehicle (EV) networks is proposed. This formulation allows one to model the interaction between several EV which are connected to a common residential distribution transformer. Each EV aims at choosing the time at which it starts charging its battery in order to minimize an individual cost which is mainly related to the total power delivered by the transformer, the location of the time interval over which the charging operation is performed, and the charging duration needed for the considered EV to have its battery fully recharged. As individual cost functions are assumed to be memoryless, it is possible to show that the game of interest is always an ordinal potential game. More precisely, both an atomic and nonatomic versions of the charging game are considered. In both cases, equilibrium analysis is conducted. In particular, important issues such as equilibrium uniqueness and efficiency are tackled. Interestingly, both analytical and numerical results show that the efficiency loss due to decentralization (e.g., when cost functions such as distribution network Joule losses or life of residential distribution transformers when no thermal inertia is assumed) induced by charging is small and the corresponding “efficiency”, a notion close to the Price of Anarchy, tends to one when the number of EV increases.",samson lasaulce,distribution networks,2012.0,,"2012 6th International Conference on Network Games, Control and Optimization (NetGCooP)",Beaude2012,False,,IEEE,Not available,Charging games in networks of electrical vehicles,914d658c34542b3882aa11ffdb928190,
1453,"In this paper, a static non-cooperative game formulation of the problem of distributed charging in electrical vehicle (EV) networks is proposed. This formulation allows one to model the interaction between several EV which are connected to a common residential distribution transformer. Each EV aims at choosing the time at which it starts charging its battery in order to minimize an individual cost which is mainly related to the total power delivered by the transformer, the location of the time interval over which the charging operation is performed, and the charging duration needed for the considered EV to have its battery fully recharged. As individual cost functions are assumed to be memoryless, it is possible to show that the game of interest is always an ordinal potential game. More precisely, both an atomic and nonatomic versions of the charging game are considered. In both cases, equilibrium analysis is conducted. In particular, important issues such as equilibrium uniqueness and efficiency are tackled. Interestingly, both analytical and numerical results show that the efficiency loss due to decentralization (e.g., when cost functions such as distribution network Joule losses or life of residential distribution transformers when no thermal inertia is assumed) induced by charging is small and the corresponding “efficiency”, a notion close to the Price of Anarchy, tends to one when the number of EV increases.",samson lasaulce,potential games,2012.0,,"2012 6th International Conference on Network Games, Control and Optimization (NetGCooP)",Beaude2012,False,,IEEE,Not available,Charging games in networks of electrical vehicles,914d658c34542b3882aa11ffdb928190,
1454,"In this paper, a static non-cooperative game formulation of the problem of distributed charging in electrical vehicle (EV) networks is proposed. This formulation allows one to model the interaction between several EV which are connected to a common residential distribution transformer. Each EV aims at choosing the time at which it starts charging its battery in order to minimize an individual cost which is mainly related to the total power delivered by the transformer, the location of the time interval over which the charging operation is performed, and the charging duration needed for the considered EV to have its battery fully recharged. As individual cost functions are assumed to be memoryless, it is possible to show that the game of interest is always an ordinal potential game. More precisely, both an atomic and nonatomic versions of the charging game are considered. In both cases, equilibrium analysis is conducted. In particular, important issues such as equilibrium uniqueness and efficiency are tackled. Interestingly, both analytical and numerical results show that the efficiency loss due to decentralization (e.g., when cost functions such as distribution network Joule losses or life of residential distribution transformers when no thermal inertia is assumed) induced by charging is small and the corresponding “efficiency”, a notion close to the Price of Anarchy, tends to one when the number of EV increases.",samson lasaulce,Nash equilibrium,2012.0,,"2012 6th International Conference on Network Games, Control and Optimization (NetGCooP)",Beaude2012,False,,IEEE,Not available,Charging games in networks of electrical vehicles,914d658c34542b3882aa11ffdb928190,
1455,"In this paper, a static non-cooperative game formulation of the problem of distributed charging in electrical vehicle (EV) networks is proposed. This formulation allows one to model the interaction between several EV which are connected to a common residential distribution transformer. Each EV aims at choosing the time at which it starts charging its battery in order to minimize an individual cost which is mainly related to the total power delivered by the transformer, the location of the time interval over which the charging operation is performed, and the charging duration needed for the considered EV to have its battery fully recharged. As individual cost functions are assumed to be memoryless, it is possible to show that the game of interest is always an ordinal potential game. More precisely, both an atomic and nonatomic versions of the charging game are considered. In both cases, equilibrium analysis is conducted. In particular, important issues such as equilibrium uniqueness and efficiency are tackled. Interestingly, both analytical and numerical results show that the efficiency loss due to decentralization (e.g., when cost functions such as distribution network Joule losses or life of residential distribution transformers when no thermal inertia is assumed) induced by charging is small and the corresponding “efficiency”, a notion close to the Price of Anarchy, tends to one when the number of EV increases.",samson lasaulce,price of anarchy,2012.0,,"2012 6th International Conference on Network Games, Control and Optimization (NetGCooP)",Beaude2012,False,,IEEE,Not available,Charging games in networks of electrical vehicles,914d658c34542b3882aa11ffdb928190,
1456,"In this paper, a static non-cooperative game formulation of the problem of distributed charging in electrical vehicle (EV) networks is proposed. This formulation allows one to model the interaction between several EV which are connected to a common residential distribution transformer. Each EV aims at choosing the time at which it starts charging its battery in order to minimize an individual cost which is mainly related to the total power delivered by the transformer, the location of the time interval over which the charging operation is performed, and the charging duration needed for the considered EV to have its battery fully recharged. As individual cost functions are assumed to be memoryless, it is possible to show that the game of interest is always an ordinal potential game. More precisely, both an atomic and nonatomic versions of the charging game are considered. In both cases, equilibrium analysis is conducted. In particular, important issues such as equilibrium uniqueness and efficiency are tackled. Interestingly, both analytical and numerical results show that the efficiency loss due to decentralization (e.g., when cost functions such as distribution network Joule losses or life of residential distribution transformers when no thermal inertia is assumed) induced by charging is small and the corresponding “efficiency”, a notion close to the Price of Anarchy, tends to one when the number of EV increases.",martin hennebel,Charging games,2012.0,,"2012 6th International Conference on Network Games, Control and Optimization (NetGCooP)",Beaude2012,False,,IEEE,Not available,Charging games in networks of electrical vehicles,914d658c34542b3882aa11ffdb928190,
1457,"In this paper, a static non-cooperative game formulation of the problem of distributed charging in electrical vehicle (EV) networks is proposed. This formulation allows one to model the interaction between several EV which are connected to a common residential distribution transformer. Each EV aims at choosing the time at which it starts charging its battery in order to minimize an individual cost which is mainly related to the total power delivered by the transformer, the location of the time interval over which the charging operation is performed, and the charging duration needed for the considered EV to have its battery fully recharged. As individual cost functions are assumed to be memoryless, it is possible to show that the game of interest is always an ordinal potential game. More precisely, both an atomic and nonatomic versions of the charging game are considered. In both cases, equilibrium analysis is conducted. In particular, important issues such as equilibrium uniqueness and efficiency are tackled. Interestingly, both analytical and numerical results show that the efficiency loss due to decentralization (e.g., when cost functions such as distribution network Joule losses or life of residential distribution transformers when no thermal inertia is assumed) induced by charging is small and the corresponding “efficiency”, a notion close to the Price of Anarchy, tends to one when the number of EV increases.",martin hennebel,electrical vehicle,2012.0,,"2012 6th International Conference on Network Games, Control and Optimization (NetGCooP)",Beaude2012,False,,IEEE,Not available,Charging games in networks of electrical vehicles,914d658c34542b3882aa11ffdb928190,
1458,"In this paper, a static non-cooperative game formulation of the problem of distributed charging in electrical vehicle (EV) networks is proposed. This formulation allows one to model the interaction between several EV which are connected to a common residential distribution transformer. Each EV aims at choosing the time at which it starts charging its battery in order to minimize an individual cost which is mainly related to the total power delivered by the transformer, the location of the time interval over which the charging operation is performed, and the charging duration needed for the considered EV to have its battery fully recharged. As individual cost functions are assumed to be memoryless, it is possible to show that the game of interest is always an ordinal potential game. More precisely, both an atomic and nonatomic versions of the charging game are considered. In both cases, equilibrium analysis is conducted. In particular, important issues such as equilibrium uniqueness and efficiency are tackled. Interestingly, both analytical and numerical results show that the efficiency loss due to decentralization (e.g., when cost functions such as distribution network Joule losses or life of residential distribution transformers when no thermal inertia is assumed) induced by charging is small and the corresponding “efficiency”, a notion close to the Price of Anarchy, tends to one when the number of EV increases.",martin hennebel,distribution networks,2012.0,,"2012 6th International Conference on Network Games, Control and Optimization (NetGCooP)",Beaude2012,False,,IEEE,Not available,Charging games in networks of electrical vehicles,914d658c34542b3882aa11ffdb928190,
1459,"In this paper, a static non-cooperative game formulation of the problem of distributed charging in electrical vehicle (EV) networks is proposed. This formulation allows one to model the interaction between several EV which are connected to a common residential distribution transformer. Each EV aims at choosing the time at which it starts charging its battery in order to minimize an individual cost which is mainly related to the total power delivered by the transformer, the location of the time interval over which the charging operation is performed, and the charging duration needed for the considered EV to have its battery fully recharged. As individual cost functions are assumed to be memoryless, it is possible to show that the game of interest is always an ordinal potential game. More precisely, both an atomic and nonatomic versions of the charging game are considered. In both cases, equilibrium analysis is conducted. In particular, important issues such as equilibrium uniqueness and efficiency are tackled. Interestingly, both analytical and numerical results show that the efficiency loss due to decentralization (e.g., when cost functions such as distribution network Joule losses or life of residential distribution transformers when no thermal inertia is assumed) induced by charging is small and the corresponding “efficiency”, a notion close to the Price of Anarchy, tends to one when the number of EV increases.",martin hennebel,potential games,2012.0,,"2012 6th International Conference on Network Games, Control and Optimization (NetGCooP)",Beaude2012,False,,IEEE,Not available,Charging games in networks of electrical vehicles,914d658c34542b3882aa11ffdb928190,
1460,"In this paper, a static non-cooperative game formulation of the problem of distributed charging in electrical vehicle (EV) networks is proposed. This formulation allows one to model the interaction between several EV which are connected to a common residential distribution transformer. Each EV aims at choosing the time at which it starts charging its battery in order to minimize an individual cost which is mainly related to the total power delivered by the transformer, the location of the time interval over which the charging operation is performed, and the charging duration needed for the considered EV to have its battery fully recharged. As individual cost functions are assumed to be memoryless, it is possible to show that the game of interest is always an ordinal potential game. More precisely, both an atomic and nonatomic versions of the charging game are considered. In both cases, equilibrium analysis is conducted. In particular, important issues such as equilibrium uniqueness and efficiency are tackled. Interestingly, both analytical and numerical results show that the efficiency loss due to decentralization (e.g., when cost functions such as distribution network Joule losses or life of residential distribution transformers when no thermal inertia is assumed) induced by charging is small and the corresponding “efficiency”, a notion close to the Price of Anarchy, tends to one when the number of EV increases.",martin hennebel,Nash equilibrium,2012.0,,"2012 6th International Conference on Network Games, Control and Optimization (NetGCooP)",Beaude2012,False,,IEEE,Not available,Charging games in networks of electrical vehicles,914d658c34542b3882aa11ffdb928190,
1461,"In this paper, a static non-cooperative game formulation of the problem of distributed charging in electrical vehicle (EV) networks is proposed. This formulation allows one to model the interaction between several EV which are connected to a common residential distribution transformer. Each EV aims at choosing the time at which it starts charging its battery in order to minimize an individual cost which is mainly related to the total power delivered by the transformer, the location of the time interval over which the charging operation is performed, and the charging duration needed for the considered EV to have its battery fully recharged. As individual cost functions are assumed to be memoryless, it is possible to show that the game of interest is always an ordinal potential game. More precisely, both an atomic and nonatomic versions of the charging game are considered. In both cases, equilibrium analysis is conducted. In particular, important issues such as equilibrium uniqueness and efficiency are tackled. Interestingly, both analytical and numerical results show that the efficiency loss due to decentralization (e.g., when cost functions such as distribution network Joule losses or life of residential distribution transformers when no thermal inertia is assumed) induced by charging is small and the corresponding “efficiency”, a notion close to the Price of Anarchy, tends to one when the number of EV increases.",martin hennebel,price of anarchy,2012.0,,"2012 6th International Conference on Network Games, Control and Optimization (NetGCooP)",Beaude2012,False,,IEEE,Not available,Charging games in networks of electrical vehicles,914d658c34542b3882aa11ffdb928190,
1462,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
1463,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",yunpeng li,Mobile social networks,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
1464,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",yunpeng li,mobile crowdsensing,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
1465,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",yunpeng li,information sharing,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
1466,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",yunpeng li,routing game,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
1467,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",yunpeng li,price of anarchy,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
1468,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",yunpeng li,mechanism design,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
1469,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",yunpeng li,side payments,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
1470,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",yunpeng li,content-restriction,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
1471,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",costas courcoubetis,Mobile social networks,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
1472,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",costas courcoubetis,mobile crowdsensing,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
1473,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
1474,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",costas courcoubetis,information sharing,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
1475,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",costas courcoubetis,routing game,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
1476,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",costas courcoubetis,price of anarchy,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
1477,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",costas courcoubetis,mechanism design,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
1478,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",costas courcoubetis,side payments,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
1479,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",costas courcoubetis,content-restriction,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
1480,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",lingjie duan,Mobile social networks,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
1481,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",lingjie duan,mobile crowdsensing,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
1482,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",lingjie duan,information sharing,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
1483,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",lingjie duan,routing game,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
1484,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
1485,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",lingjie duan,price of anarchy,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
1486,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",lingjie duan,mechanism design,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
1487,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",lingjie duan,side payments,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
1488,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",lingjie duan,content-restriction,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
1489,"Flow scheduling is crucial in the next-generation network but hard to address due to fast changing link states and tremendous cost to explore the global structure. In this paper, we first design a distributed virtual game to solve the optimization of flow scheduling problem assuming the priori knowledge of the distribution of edge cost as a random variable. In our virtual game, we use incentives to stimulate selfish users to reach a Nash Equilibrium Point which is suboptimum based on the analysis of the `Price of Anarchy'. This algorithm is then generalized into the situation with unknown cost distribution, where the ultimate goal is to minimize the cost in the long run. In order to achieve a reasonable tradeoff between exploration of cost distribution and exploitation with limited information, we model this problem as a Multi-armed Bandit Game and combine the newly proposed DSEE with our virtual game design. Armed with these powerful tools, we find a totally distributed algorithm to ensure the logarithmic growing of regret with time, which is optimum in classic Multi-armed Bandit problem. Theoretical proof and simulation results both confirm the effectiveness of our algorithm. To the best of our knowledge, this is the first work to combine multi-armed bandit with distributed flow scheduling.",yaoqing yang,Distributed Flow Scheduling,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Yang2013,False,,IEEE,Not available,Distributed flow scheduling in an unknown environment,bd23c994ace8345256b396a372e12bfb,https://ieeexplore.ieee.org/document/6576397/
1490,"Flow scheduling is crucial in the next-generation network but hard to address due to fast changing link states and tremendous cost to explore the global structure. In this paper, we first design a distributed virtual game to solve the optimization of flow scheduling problem assuming the priori knowledge of the distribution of edge cost as a random variable. In our virtual game, we use incentives to stimulate selfish users to reach a Nash Equilibrium Point which is suboptimum based on the analysis of the `Price of Anarchy'. This algorithm is then generalized into the situation with unknown cost distribution, where the ultimate goal is to minimize the cost in the long run. In order to achieve a reasonable tradeoff between exploration of cost distribution and exploitation with limited information, we model this problem as a Multi-armed Bandit Game and combine the newly proposed DSEE with our virtual game design. Armed with these powerful tools, we find a totally distributed algorithm to ensure the logarithmic growing of regret with time, which is optimum in classic Multi-armed Bandit problem. Theoretical proof and simulation results both confirm the effectiveness of our algorithm. To the best of our knowledge, this is the first work to combine multi-armed bandit with distributed flow scheduling.",yaoqing yang,Price of Anarchy,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Yang2013,False,,IEEE,Not available,Distributed flow scheduling in an unknown environment,bd23c994ace8345256b396a372e12bfb,https://ieeexplore.ieee.org/document/6576397/
1491,"Flow scheduling is crucial in the next-generation network but hard to address due to fast changing link states and tremendous cost to explore the global structure. In this paper, we first design a distributed virtual game to solve the optimization of flow scheduling problem assuming the priori knowledge of the distribution of edge cost as a random variable. In our virtual game, we use incentives to stimulate selfish users to reach a Nash Equilibrium Point which is suboptimum based on the analysis of the `Price of Anarchy'. This algorithm is then generalized into the situation with unknown cost distribution, where the ultimate goal is to minimize the cost in the long run. In order to achieve a reasonable tradeoff between exploration of cost distribution and exploitation with limited information, we model this problem as a Multi-armed Bandit Game and combine the newly proposed DSEE with our virtual game design. Armed with these powerful tools, we find a totally distributed algorithm to ensure the logarithmic growing of regret with time, which is optimum in classic Multi-armed Bandit problem. Theoretical proof and simulation results both confirm the effectiveness of our algorithm. To the best of our knowledge, this is the first work to combine multi-armed bandit with distributed flow scheduling.",yaoqing yang,Multi-Armed Bandit,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Yang2013,False,,IEEE,Not available,Distributed flow scheduling in an unknown environment,bd23c994ace8345256b396a372e12bfb,https://ieeexplore.ieee.org/document/6576397/
1492,"Flow scheduling is crucial in the next-generation network but hard to address due to fast changing link states and tremendous cost to explore the global structure. In this paper, we first design a distributed virtual game to solve the optimization of flow scheduling problem assuming the priori knowledge of the distribution of edge cost as a random variable. In our virtual game, we use incentives to stimulate selfish users to reach a Nash Equilibrium Point which is suboptimum based on the analysis of the `Price of Anarchy'. This algorithm is then generalized into the situation with unknown cost distribution, where the ultimate goal is to minimize the cost in the long run. In order to achieve a reasonable tradeoff between exploration of cost distribution and exploitation with limited information, we model this problem as a Multi-armed Bandit Game and combine the newly proposed DSEE with our virtual game design. Armed with these powerful tools, we find a totally distributed algorithm to ensure the logarithmic growing of regret with time, which is optimum in classic Multi-armed Bandit problem. Theoretical proof and simulation results both confirm the effectiveness of our algorithm. To the best of our knowledge, this is the first work to combine multi-armed bandit with distributed flow scheduling.",yaoqing yang,Logarithmic Regret,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Yang2013,False,,IEEE,Not available,Distributed flow scheduling in an unknown environment,bd23c994ace8345256b396a372e12bfb,https://ieeexplore.ieee.org/document/6576397/
1493,"Flow scheduling is crucial in the next-generation network but hard to address due to fast changing link states and tremendous cost to explore the global structure. In this paper, we first design a distributed virtual game to solve the optimization of flow scheduling problem assuming the priori knowledge of the distribution of edge cost as a random variable. In our virtual game, we use incentives to stimulate selfish users to reach a Nash Equilibrium Point which is suboptimum based on the analysis of the `Price of Anarchy'. This algorithm is then generalized into the situation with unknown cost distribution, where the ultimate goal is to minimize the cost in the long run. In order to achieve a reasonable tradeoff between exploration of cost distribution and exploitation with limited information, we model this problem as a Multi-armed Bandit Game and combine the newly proposed DSEE with our virtual game design. Armed with these powerful tools, we find a totally distributed algorithm to ensure the logarithmic growing of regret with time, which is optimum in classic Multi-armed Bandit problem. Theoretical proof and simulation results both confirm the effectiveness of our algorithm. To the best of our knowledge, this is the first work to combine multi-armed bandit with distributed flow scheduling.",keqin liu,Distributed Flow Scheduling,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Yang2013,False,,IEEE,Not available,Distributed flow scheduling in an unknown environment,bd23c994ace8345256b396a372e12bfb,https://ieeexplore.ieee.org/document/6576397/
1494,"Flow scheduling is crucial in the next-generation network but hard to address due to fast changing link states and tremendous cost to explore the global structure. In this paper, we first design a distributed virtual game to solve the optimization of flow scheduling problem assuming the priori knowledge of the distribution of edge cost as a random variable. In our virtual game, we use incentives to stimulate selfish users to reach a Nash Equilibrium Point which is suboptimum based on the analysis of the `Price of Anarchy'. This algorithm is then generalized into the situation with unknown cost distribution, where the ultimate goal is to minimize the cost in the long run. In order to achieve a reasonable tradeoff between exploration of cost distribution and exploitation with limited information, we model this problem as a Multi-armed Bandit Game and combine the newly proposed DSEE with our virtual game design. Armed with these powerful tools, we find a totally distributed algorithm to ensure the logarithmic growing of regret with time, which is optimum in classic Multi-armed Bandit problem. Theoretical proof and simulation results both confirm the effectiveness of our algorithm. To the best of our knowledge, this is the first work to combine multi-armed bandit with distributed flow scheduling.",keqin liu,Price of Anarchy,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Yang2013,False,,IEEE,Not available,Distributed flow scheduling in an unknown environment,bd23c994ace8345256b396a372e12bfb,https://ieeexplore.ieee.org/document/6576397/
1495,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
1496,"Flow scheduling is crucial in the next-generation network but hard to address due to fast changing link states and tremendous cost to explore the global structure. In this paper, we first design a distributed virtual game to solve the optimization of flow scheduling problem assuming the priori knowledge of the distribution of edge cost as a random variable. In our virtual game, we use incentives to stimulate selfish users to reach a Nash Equilibrium Point which is suboptimum based on the analysis of the `Price of Anarchy'. This algorithm is then generalized into the situation with unknown cost distribution, where the ultimate goal is to minimize the cost in the long run. In order to achieve a reasonable tradeoff between exploration of cost distribution and exploitation with limited information, we model this problem as a Multi-armed Bandit Game and combine the newly proposed DSEE with our virtual game design. Armed with these powerful tools, we find a totally distributed algorithm to ensure the logarithmic growing of regret with time, which is optimum in classic Multi-armed Bandit problem. Theoretical proof and simulation results both confirm the effectiveness of our algorithm. To the best of our knowledge, this is the first work to combine multi-armed bandit with distributed flow scheduling.",keqin liu,Multi-Armed Bandit,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Yang2013,False,,IEEE,Not available,Distributed flow scheduling in an unknown environment,bd23c994ace8345256b396a372e12bfb,https://ieeexplore.ieee.org/document/6576397/
1497,"Flow scheduling is crucial in the next-generation network but hard to address due to fast changing link states and tremendous cost to explore the global structure. In this paper, we first design a distributed virtual game to solve the optimization of flow scheduling problem assuming the priori knowledge of the distribution of edge cost as a random variable. In our virtual game, we use incentives to stimulate selfish users to reach a Nash Equilibrium Point which is suboptimum based on the analysis of the `Price of Anarchy'. This algorithm is then generalized into the situation with unknown cost distribution, where the ultimate goal is to minimize the cost in the long run. In order to achieve a reasonable tradeoff between exploration of cost distribution and exploitation with limited information, we model this problem as a Multi-armed Bandit Game and combine the newly proposed DSEE with our virtual game design. Armed with these powerful tools, we find a totally distributed algorithm to ensure the logarithmic growing of regret with time, which is optimum in classic Multi-armed Bandit problem. Theoretical proof and simulation results both confirm the effectiveness of our algorithm. To the best of our knowledge, this is the first work to combine multi-armed bandit with distributed flow scheduling.",keqin liu,Logarithmic Regret,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Yang2013,False,,IEEE,Not available,Distributed flow scheduling in an unknown environment,bd23c994ace8345256b396a372e12bfb,https://ieeexplore.ieee.org/document/6576397/
1498,"Flow scheduling is crucial in the next-generation network but hard to address due to fast changing link states and tremendous cost to explore the global structure. In this paper, we first design a distributed virtual game to solve the optimization of flow scheduling problem assuming the priori knowledge of the distribution of edge cost as a random variable. In our virtual game, we use incentives to stimulate selfish users to reach a Nash Equilibrium Point which is suboptimum based on the analysis of the `Price of Anarchy'. This algorithm is then generalized into the situation with unknown cost distribution, where the ultimate goal is to minimize the cost in the long run. In order to achieve a reasonable tradeoff between exploration of cost distribution and exploitation with limited information, we model this problem as a Multi-armed Bandit Game and combine the newly proposed DSEE with our virtual game design. Armed with these powerful tools, we find a totally distributed algorithm to ensure the logarithmic growing of regret with time, which is optimum in classic Multi-armed Bandit problem. Theoretical proof and simulation results both confirm the effectiveness of our algorithm. To the best of our knowledge, this is the first work to combine multi-armed bandit with distributed flow scheduling.",pingyi fan,Distributed Flow Scheduling,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Yang2013,False,,IEEE,Not available,Distributed flow scheduling in an unknown environment,bd23c994ace8345256b396a372e12bfb,https://ieeexplore.ieee.org/document/6576397/
1499,"Flow scheduling is crucial in the next-generation network but hard to address due to fast changing link states and tremendous cost to explore the global structure. In this paper, we first design a distributed virtual game to solve the optimization of flow scheduling problem assuming the priori knowledge of the distribution of edge cost as a random variable. In our virtual game, we use incentives to stimulate selfish users to reach a Nash Equilibrium Point which is suboptimum based on the analysis of the `Price of Anarchy'. This algorithm is then generalized into the situation with unknown cost distribution, where the ultimate goal is to minimize the cost in the long run. In order to achieve a reasonable tradeoff between exploration of cost distribution and exploitation with limited information, we model this problem as a Multi-armed Bandit Game and combine the newly proposed DSEE with our virtual game design. Armed with these powerful tools, we find a totally distributed algorithm to ensure the logarithmic growing of regret with time, which is optimum in classic Multi-armed Bandit problem. Theoretical proof and simulation results both confirm the effectiveness of our algorithm. To the best of our knowledge, this is the first work to combine multi-armed bandit with distributed flow scheduling.",pingyi fan,Price of Anarchy,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Yang2013,False,,IEEE,Not available,Distributed flow scheduling in an unknown environment,bd23c994ace8345256b396a372e12bfb,https://ieeexplore.ieee.org/document/6576397/
1500,"Flow scheduling is crucial in the next-generation network but hard to address due to fast changing link states and tremendous cost to explore the global structure. In this paper, we first design a distributed virtual game to solve the optimization of flow scheduling problem assuming the priori knowledge of the distribution of edge cost as a random variable. In our virtual game, we use incentives to stimulate selfish users to reach a Nash Equilibrium Point which is suboptimum based on the analysis of the `Price of Anarchy'. This algorithm is then generalized into the situation with unknown cost distribution, where the ultimate goal is to minimize the cost in the long run. In order to achieve a reasonable tradeoff between exploration of cost distribution and exploitation with limited information, we model this problem as a Multi-armed Bandit Game and combine the newly proposed DSEE with our virtual game design. Armed with these powerful tools, we find a totally distributed algorithm to ensure the logarithmic growing of regret with time, which is optimum in classic Multi-armed Bandit problem. Theoretical proof and simulation results both confirm the effectiveness of our algorithm. To the best of our knowledge, this is the first work to combine multi-armed bandit with distributed flow scheduling.",pingyi fan,Multi-Armed Bandit,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Yang2013,False,,IEEE,Not available,Distributed flow scheduling in an unknown environment,bd23c994ace8345256b396a372e12bfb,https://ieeexplore.ieee.org/document/6576397/
1501,"Flow scheduling is crucial in the next-generation network but hard to address due to fast changing link states and tremendous cost to explore the global structure. In this paper, we first design a distributed virtual game to solve the optimization of flow scheduling problem assuming the priori knowledge of the distribution of edge cost as a random variable. In our virtual game, we use incentives to stimulate selfish users to reach a Nash Equilibrium Point which is suboptimum based on the analysis of the `Price of Anarchy'. This algorithm is then generalized into the situation with unknown cost distribution, where the ultimate goal is to minimize the cost in the long run. In order to achieve a reasonable tradeoff between exploration of cost distribution and exploitation with limited information, we model this problem as a Multi-armed Bandit Game and combine the newly proposed DSEE with our virtual game design. Armed with these powerful tools, we find a totally distributed algorithm to ensure the logarithmic growing of regret with time, which is optimum in classic Multi-armed Bandit problem. Theoretical proof and simulation results both confirm the effectiveness of our algorithm. To the best of our knowledge, this is the first work to combine multi-armed bandit with distributed flow scheduling.",pingyi fan,Logarithmic Regret,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Yang2013,False,,IEEE,Not available,Distributed flow scheduling in an unknown environment,bd23c994ace8345256b396a372e12bfb,https://ieeexplore.ieee.org/document/6576397/
1502,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",majed haddad,WLAN,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
1503,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",majed haddad,3G,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
1504,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",majed haddad,association problem,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
1505,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",majed haddad,misleading information,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
1506,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
1507,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",majed haddad,channel state information,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
1508,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",majed haddad,game theory,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
1509,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",majed haddad,Bayes-Nash equilibrium,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
1510,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",majed haddad,Bayes-Stackelberg equilibrium,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
1511,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",majed haddad,Price of Anarchy,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
1512,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",habib sidi,WLAN,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
1513,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",habib sidi,3G,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
1514,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",habib sidi,association problem,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
1515,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",habib sidi,misleading information,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
1516,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",habib sidi,channel state information,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
1517,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
1518,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
1519,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",habib sidi,game theory,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
1520,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",habib sidi,Bayes-Nash equilibrium,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
1521,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",habib sidi,Bayes-Stackelberg equilibrium,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
1522,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",habib sidi,Price of Anarchy,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
1523,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",piotr wiecek,WLAN,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
1524,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",piotr wiecek,3G,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
1525,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",piotr wiecek,association problem,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
1526,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",piotr wiecek,misleading information,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
1527,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",piotr wiecek,channel state information,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
1528,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",piotr wiecek,game theory,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
1529,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
1530,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",piotr wiecek,Bayes-Nash equilibrium,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
1531,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",piotr wiecek,Bayes-Stackelberg equilibrium,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
1532,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",piotr wiecek,Price of Anarchy,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
1533,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",eitan altman,WLAN,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
1534,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",eitan altman,3G,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
1535,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",eitan altman,association problem,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
1536,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",eitan altman,misleading information,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
1537,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",eitan altman,channel state information,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
1538,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",eitan altman,game theory,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
1539,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",eitan altman,Bayes-Nash equilibrium,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
1540,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
1541,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",eitan altman,Bayes-Stackelberg equilibrium,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
1542,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",eitan altman,Price of Anarchy,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
1543,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",wei zhong,Discrete power control,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
1544,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",wei zhong,Nash equilibrium,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
1545,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",wei zhong,potential games,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
1546,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",wei zhong,price of anarchy,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
1547,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",wei zhong,relay selection,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
1548,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",gang chen,Discrete power control,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
1549,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",gang chen,Nash equilibrium,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
1550,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",gang chen,potential games,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
1551,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
1552,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",gang chen,price of anarchy,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
1553,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",gang chen,relay selection,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
1554,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",shi jin,Discrete power control,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
1555,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",shi jin,Nash equilibrium,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
1556,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",shi jin,potential games,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
1557,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",shi jin,price of anarchy,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
1558,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",shi jin,relay selection,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
1559,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",kai-kit wong,Discrete power control,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
1560,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",kai-kit wong,Nash equilibrium,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
1561,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",kai-kit wong,potential games,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
1562,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
1563,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",kai-kit wong,price of anarchy,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
1564,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",kai-kit wong,relay selection,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
1565,"We study how an underlying network property affects network security when nodes are rational and have four choices - i) invest in protection, ii) purchase (incomplete coverage) insurance, iii) invest in protection and purchase insurance, or iv) do nothing. More specifically, using a population game model, we examine how the degree distribution of nodes influences their choices at Nash equilibria (NEs) and overall security level. We first show that there exists a degree threshold at NEs so that only the populations with degrees greater than or equal to the threshold invest in protection. Second, as the weighted degree distribution of nodes becomes stochastically larger, the risk or threat posed by a neighbor decreases, even though the aforementioned degree threshold tends to rise, hence only nodes with increasingly higher degrees invest in protection, at the same time. Third, we show that the social optimum also possesses similar properties. Finally, we derive an upper bound on the price of anarchy, which is an affine function of the average degree of nodes. This upper bound is tight in that it is achieved in some scenarios.",richard la,Cybersecurity,2014.0,10.1109/CDC.2014.7040216,53rd IEEE Conference on Decision and Control,La2014,False,,IEEE,Not available,Role of network topology in cybersecurity,b441e16e383d3046aa5174e6ac983ff1,https://ieeexplore.ieee.org/document/7040216/
1566,"We study how an underlying network property affects network security when nodes are rational and have four choices - i) invest in protection, ii) purchase (incomplete coverage) insurance, iii) invest in protection and purchase insurance, or iv) do nothing. More specifically, using a population game model, we examine how the degree distribution of nodes influences their choices at Nash equilibria (NEs) and overall security level. We first show that there exists a degree threshold at NEs so that only the populations with degrees greater than or equal to the threshold invest in protection. Second, as the weighted degree distribution of nodes becomes stochastically larger, the risk or threat posed by a neighbor decreases, even though the aforementioned degree threshold tends to rise, hence only nodes with increasingly higher degrees invest in protection, at the same time. Third, we show that the social optimum also possesses similar properties. Finally, we derive an upper bound on the price of anarchy, which is an affine function of the average degree of nodes. This upper bound is tight in that it is achieved in some scenarios.",richard la,game theory,2014.0,10.1109/CDC.2014.7040216,53rd IEEE Conference on Decision and Control,La2014,False,,IEEE,Not available,Role of network topology in cybersecurity,b441e16e383d3046aa5174e6ac983ff1,https://ieeexplore.ieee.org/document/7040216/
1567,"We study how an underlying network property affects network security when nodes are rational and have four choices - i) invest in protection, ii) purchase (incomplete coverage) insurance, iii) invest in protection and purchase insurance, or iv) do nothing. More specifically, using a population game model, we examine how the degree distribution of nodes influences their choices at Nash equilibria (NEs) and overall security level. We first show that there exists a degree threshold at NEs so that only the populations with degrees greater than or equal to the threshold invest in protection. Second, as the weighted degree distribution of nodes becomes stochastically larger, the risk or threat posed by a neighbor decreases, even though the aforementioned degree threshold tends to rise, hence only nodes with increasingly higher degrees invest in protection, at the same time. Third, we show that the social optimum also possesses similar properties. Finally, we derive an upper bound on the price of anarchy, which is an affine function of the average degree of nodes. This upper bound is tight in that it is achieved in some scenarios.",richard la,price of anarchy,2014.0,10.1109/CDC.2014.7040216,53rd IEEE Conference on Decision and Control,La2014,False,,IEEE,Not available,Role of network topology in cybersecurity,b441e16e383d3046aa5174e6ac983ff1,https://ieeexplore.ieee.org/document/7040216/
1568,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",shay kutten,Peer to peer computing,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
1569,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",shay kutten,Games,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
1570,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",shay kutten,Electronic mail,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
1571,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",shay kutten,Conferences,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
1572,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",shay kutten,Information systems,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
1573,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
1574,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",shay kutten,Electronic commerce,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
1575,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",shay kutten,Europe,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
1576,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",ron lavi,Peer to peer computing,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
1577,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",ron lavi,Games,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
1578,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",ron lavi,Electronic mail,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
1579,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",ron lavi,Conferences,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
1580,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",ron lavi,Information systems,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
1581,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",ron lavi,Electronic commerce,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
1582,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",ron lavi,Europe,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
1583,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",amitabh trehan,Peer to peer computing,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
1584,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
1585,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",amitabh trehan,Games,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
1586,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",amitabh trehan,Electronic mail,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
1587,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",amitabh trehan,Conferences,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
1588,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",amitabh trehan,Information systems,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
1589,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",amitabh trehan,Electronic commerce,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
1590,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",amitabh trehan,Europe,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
1591,"This note focuses on the design of cost-sharing rules to optimize the efficiency of the resulting equilibria in cost-sharing games with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst-case guarantees on the performance of the (worst or best) equilibria. Our first result characterizes the cost-sharing design that optimizes the price of anarchy, followed by the price of stability. This optimal cost-sharing rule is precisely the Shapley value cost-sharing rule. Our second result characterizes the cost-sharing design that optimizes the price of stability, followed by the price of anarchy. This optimal cost-sharing rule is precisely the marginal contribution cost-sharing rule. This analysis highlights a fundamental tradeoff between the price of anarchy and price of stability in the considered class of games. That is, given the optimality of both the Shapley value and marginal cost distribution rules in each of their respective domains, it is impossible to improve either the price of anarchy or price of stability without degrading its counterpart.",matthew phillips,Distributed control,2018.0,10.1109/TAC.2017.2765299,IEEE Transactions on Automatic Control,Phillips2018,False,,IEEE,Not available,Design Tradeoffs in Concave Cost-Sharing Games,307d2a94c902970607eb2e463edd6415,https://ieeexplore.ieee.org/document/8078240/
1592,"This note focuses on the design of cost-sharing rules to optimize the efficiency of the resulting equilibria in cost-sharing games with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst-case guarantees on the performance of the (worst or best) equilibria. Our first result characterizes the cost-sharing design that optimizes the price of anarchy, followed by the price of stability. This optimal cost-sharing rule is precisely the Shapley value cost-sharing rule. Our second result characterizes the cost-sharing design that optimizes the price of stability, followed by the price of anarchy. This optimal cost-sharing rule is precisely the marginal contribution cost-sharing rule. This analysis highlights a fundamental tradeoff between the price of anarchy and price of stability in the considered class of games. That is, given the optimality of both the Shapley value and marginal cost distribution rules in each of their respective domains, it is impossible to improve either the price of anarchy or price of stability without degrading its counterpart.",matthew phillips,game theory,2018.0,10.1109/TAC.2017.2765299,IEEE Transactions on Automatic Control,Phillips2018,False,,IEEE,Not available,Design Tradeoffs in Concave Cost-Sharing Games,307d2a94c902970607eb2e463edd6415,https://ieeexplore.ieee.org/document/8078240/
1593,"This note focuses on the design of cost-sharing rules to optimize the efficiency of the resulting equilibria in cost-sharing games with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst-case guarantees on the performance of the (worst or best) equilibria. Our first result characterizes the cost-sharing design that optimizes the price of anarchy, followed by the price of stability. This optimal cost-sharing rule is precisely the Shapley value cost-sharing rule. Our second result characterizes the cost-sharing design that optimizes the price of stability, followed by the price of anarchy. This optimal cost-sharing rule is precisely the marginal contribution cost-sharing rule. This analysis highlights a fundamental tradeoff between the price of anarchy and price of stability in the considered class of games. That is, given the optimality of both the Shapley value and marginal cost distribution rules in each of their respective domains, it is impossible to improve either the price of anarchy or price of stability without degrading its counterpart.",matthew phillips,multiagent systems,2018.0,10.1109/TAC.2017.2765299,IEEE Transactions on Automatic Control,Phillips2018,False,,IEEE,Not available,Design Tradeoffs in Concave Cost-Sharing Games,307d2a94c902970607eb2e463edd6415,https://ieeexplore.ieee.org/document/8078240/
1594,"This note focuses on the design of cost-sharing rules to optimize the efficiency of the resulting equilibria in cost-sharing games with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst-case guarantees on the performance of the (worst or best) equilibria. Our first result characterizes the cost-sharing design that optimizes the price of anarchy, followed by the price of stability. This optimal cost-sharing rule is precisely the Shapley value cost-sharing rule. Our second result characterizes the cost-sharing design that optimizes the price of stability, followed by the price of anarchy. This optimal cost-sharing rule is precisely the marginal contribution cost-sharing rule. This analysis highlights a fundamental tradeoff between the price of anarchy and price of stability in the considered class of games. That is, given the optimality of both the Shapley value and marginal cost distribution rules in each of their respective domains, it is impossible to improve either the price of anarchy or price of stability without degrading its counterpart.",matthew phillips,networked control systems,2018.0,10.1109/TAC.2017.2765299,IEEE Transactions on Automatic Control,Phillips2018,False,,IEEE,Not available,Design Tradeoffs in Concave Cost-Sharing Games,307d2a94c902970607eb2e463edd6415,https://ieeexplore.ieee.org/document/8078240/
1595,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
1596,"This note focuses on the design of cost-sharing rules to optimize the efficiency of the resulting equilibria in cost-sharing games with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst-case guarantees on the performance of the (worst or best) equilibria. Our first result characterizes the cost-sharing design that optimizes the price of anarchy, followed by the price of stability. This optimal cost-sharing rule is precisely the Shapley value cost-sharing rule. Our second result characterizes the cost-sharing design that optimizes the price of stability, followed by the price of anarchy. This optimal cost-sharing rule is precisely the marginal contribution cost-sharing rule. This analysis highlights a fundamental tradeoff between the price of anarchy and price of stability in the considered class of games. That is, given the optimality of both the Shapley value and marginal cost distribution rules in each of their respective domains, it is impossible to improve either the price of anarchy or price of stability without degrading its counterpart.",jason marden,Distributed control,2018.0,10.1109/TAC.2017.2765299,IEEE Transactions on Automatic Control,Phillips2018,False,,IEEE,Not available,Design Tradeoffs in Concave Cost-Sharing Games,307d2a94c902970607eb2e463edd6415,https://ieeexplore.ieee.org/document/8078240/
1597,"This note focuses on the design of cost-sharing rules to optimize the efficiency of the resulting equilibria in cost-sharing games with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst-case guarantees on the performance of the (worst or best) equilibria. Our first result characterizes the cost-sharing design that optimizes the price of anarchy, followed by the price of stability. This optimal cost-sharing rule is precisely the Shapley value cost-sharing rule. Our second result characterizes the cost-sharing design that optimizes the price of stability, followed by the price of anarchy. This optimal cost-sharing rule is precisely the marginal contribution cost-sharing rule. This analysis highlights a fundamental tradeoff between the price of anarchy and price of stability in the considered class of games. That is, given the optimality of both the Shapley value and marginal cost distribution rules in each of their respective domains, it is impossible to improve either the price of anarchy or price of stability without degrading its counterpart.",jason marden,game theory,2018.0,10.1109/TAC.2017.2765299,IEEE Transactions on Automatic Control,Phillips2018,False,,IEEE,Not available,Design Tradeoffs in Concave Cost-Sharing Games,307d2a94c902970607eb2e463edd6415,https://ieeexplore.ieee.org/document/8078240/
1598,"This note focuses on the design of cost-sharing rules to optimize the efficiency of the resulting equilibria in cost-sharing games with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst-case guarantees on the performance of the (worst or best) equilibria. Our first result characterizes the cost-sharing design that optimizes the price of anarchy, followed by the price of stability. This optimal cost-sharing rule is precisely the Shapley value cost-sharing rule. Our second result characterizes the cost-sharing design that optimizes the price of stability, followed by the price of anarchy. This optimal cost-sharing rule is precisely the marginal contribution cost-sharing rule. This analysis highlights a fundamental tradeoff between the price of anarchy and price of stability in the considered class of games. That is, given the optimality of both the Shapley value and marginal cost distribution rules in each of their respective domains, it is impossible to improve either the price of anarchy or price of stability without degrading its counterpart.",jason marden,multiagent systems,2018.0,10.1109/TAC.2017.2765299,IEEE Transactions on Automatic Control,Phillips2018,False,,IEEE,Not available,Design Tradeoffs in Concave Cost-Sharing Games,307d2a94c902970607eb2e463edd6415,https://ieeexplore.ieee.org/document/8078240/
1599,"This note focuses on the design of cost-sharing rules to optimize the efficiency of the resulting equilibria in cost-sharing games with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst-case guarantees on the performance of the (worst or best) equilibria. Our first result characterizes the cost-sharing design that optimizes the price of anarchy, followed by the price of stability. This optimal cost-sharing rule is precisely the Shapley value cost-sharing rule. Our second result characterizes the cost-sharing design that optimizes the price of stability, followed by the price of anarchy. This optimal cost-sharing rule is precisely the marginal contribution cost-sharing rule. This analysis highlights a fundamental tradeoff between the price of anarchy and price of stability in the considered class of games. That is, given the optimality of both the Shapley value and marginal cost distribution rules in each of their respective domains, it is impossible to improve either the price of anarchy or price of stability without degrading its counterpart.",jason marden,networked control systems,2018.0,10.1109/TAC.2017.2765299,IEEE Transactions on Automatic Control,Phillips2018,False,,IEEE,Not available,Design Tradeoffs in Concave Cost-Sharing Games,307d2a94c902970607eb2e463edd6415,https://ieeexplore.ieee.org/document/8078240/
1600,"In this paper, we study a sequential dynamic routing game on a line where the decision of a user is spatio-temporal control. Each user ships its demand over time on a shared resource. We address the case where only one user arrives at each time epoch. The state of a player evolves according to whether he decides to transmit or not. We provide explicit expressions of the equilibrium of such systems and compare them to the global optimum case. In particular, we compute the price of anarchy of such schemes and identify a Braess-type paradox in the context of sequential routing game.",majed haddad,Sequential routing game,2012.0,10.1109/ICCITechnol.2012.6285812,2012 International Conference on Communications and Information Technology (ICCIT),Haddad2012,False,,IEEE,Not available,Sequential routing game on the line: Transmit or relay?,f51da9a75fad1b45600d9c90f2e3465d,https://ieeexplore.ieee.org/document/6285812/
1601,"In this paper, we study a sequential dynamic routing game on a line where the decision of a user is spatio-temporal control. Each user ships its demand over time on a shared resource. We address the case where only one user arrives at each time epoch. The state of a player evolves according to whether he decides to transmit or not. We provide explicit expressions of the equilibrium of such systems and compare them to the global optimum case. In particular, we compute the price of anarchy of such schemes and identify a Braess-type paradox in the context of sequential routing game.",majed haddad,Nash equilibrium,2012.0,10.1109/ICCITechnol.2012.6285812,2012 International Conference on Communications and Information Technology (ICCIT),Haddad2012,False,,IEEE,Not available,Sequential routing game on the line: Transmit or relay?,f51da9a75fad1b45600d9c90f2e3465d,https://ieeexplore.ieee.org/document/6285812/
1602,"In this paper, we study a sequential dynamic routing game on a line where the decision of a user is spatio-temporal control. Each user ships its demand over time on a shared resource. We address the case where only one user arrives at each time epoch. The state of a player evolves according to whether he decides to transmit or not. We provide explicit expressions of the equilibrium of such systems and compare them to the global optimum case. In particular, we compute the price of anarchy of such schemes and identify a Braess-type paradox in the context of sequential routing game.",majed haddad,Price of anarchy,2012.0,10.1109/ICCITechnol.2012.6285812,2012 International Conference on Communications and Information Technology (ICCIT),Haddad2012,False,,IEEE,Not available,Sequential routing game on the line: Transmit or relay?,f51da9a75fad1b45600d9c90f2e3465d,https://ieeexplore.ieee.org/document/6285812/
1603,"In this paper, we study a sequential dynamic routing game on a line where the decision of a user is spatio-temporal control. Each user ships its demand over time on a shared resource. We address the case where only one user arrives at each time epoch. The state of a player evolves according to whether he decides to transmit or not. We provide explicit expressions of the equilibrium of such systems and compare them to the global optimum case. In particular, we compute the price of anarchy of such schemes and identify a Braess-type paradox in the context of sequential routing game.",majed haddad,Braess-type paradox,2012.0,10.1109/ICCITechnol.2012.6285812,2012 International Conference on Communications and Information Technology (ICCIT),Haddad2012,False,,IEEE,Not available,Sequential routing game on the line: Transmit or relay?,f51da9a75fad1b45600d9c90f2e3465d,https://ieeexplore.ieee.org/document/6285812/
1604,"In this paper, we study a sequential dynamic routing game on a line where the decision of a user is spatio-temporal control. Each user ships its demand over time on a shared resource. We address the case where only one user arrives at each time epoch. The state of a player evolves according to whether he decides to transmit or not. We provide explicit expressions of the equilibrium of such systems and compare them to the global optimum case. In particular, we compute the price of anarchy of such schemes and identify a Braess-type paradox in the context of sequential routing game.",eitan altman,Sequential routing game,2012.0,10.1109/ICCITechnol.2012.6285812,2012 International Conference on Communications and Information Technology (ICCIT),Haddad2012,False,,IEEE,Not available,Sequential routing game on the line: Transmit or relay?,f51da9a75fad1b45600d9c90f2e3465d,https://ieeexplore.ieee.org/document/6285812/
1605,"In this paper, we study a sequential dynamic routing game on a line where the decision of a user is spatio-temporal control. Each user ships its demand over time on a shared resource. We address the case where only one user arrives at each time epoch. The state of a player evolves according to whether he decides to transmit or not. We provide explicit expressions of the equilibrium of such systems and compare them to the global optimum case. In particular, we compute the price of anarchy of such schemes and identify a Braess-type paradox in the context of sequential routing game.",eitan altman,Nash equilibrium,2012.0,10.1109/ICCITechnol.2012.6285812,2012 International Conference on Communications and Information Technology (ICCIT),Haddad2012,False,,IEEE,Not available,Sequential routing game on the line: Transmit or relay?,f51da9a75fad1b45600d9c90f2e3465d,https://ieeexplore.ieee.org/document/6285812/
1606,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
1607,"In this paper, we study a sequential dynamic routing game on a line where the decision of a user is spatio-temporal control. Each user ships its demand over time on a shared resource. We address the case where only one user arrives at each time epoch. The state of a player evolves according to whether he decides to transmit or not. We provide explicit expressions of the equilibrium of such systems and compare them to the global optimum case. In particular, we compute the price of anarchy of such schemes and identify a Braess-type paradox in the context of sequential routing game.",eitan altman,Price of anarchy,2012.0,10.1109/ICCITechnol.2012.6285812,2012 International Conference on Communications and Information Technology (ICCIT),Haddad2012,False,,IEEE,Not available,Sequential routing game on the line: Transmit or relay?,f51da9a75fad1b45600d9c90f2e3465d,https://ieeexplore.ieee.org/document/6285812/
1608,"In this paper, we study a sequential dynamic routing game on a line where the decision of a user is spatio-temporal control. Each user ships its demand over time on a shared resource. We address the case where only one user arrives at each time epoch. The state of a player evolves according to whether he decides to transmit or not. We provide explicit expressions of the equilibrium of such systems and compare them to the global optimum case. In particular, we compute the price of anarchy of such schemes and identify a Braess-type paradox in the context of sequential routing game.",eitan altman,Braess-type paradox,2012.0,10.1109/ICCITechnol.2012.6285812,2012 International Conference on Communications and Information Technology (ICCIT),Haddad2012,False,,IEEE,Not available,Sequential routing game on the line: Transmit or relay?,f51da9a75fad1b45600d9c90f2e3465d,https://ieeexplore.ieee.org/document/6285812/
1609,"In this paper, we study a sequential dynamic routing game on a line where the decision of a user is spatio-temporal control. Each user ships its demand over time on a shared resource. We address the case where only one user arrives at each time epoch. The state of a player evolves according to whether he decides to transmit or not. We provide explicit expressions of the equilibrium of such systems and compare them to the global optimum case. In particular, we compute the price of anarchy of such schemes and identify a Braess-type paradox in the context of sequential routing game.",julien gaillard,Sequential routing game,2012.0,10.1109/ICCITechnol.2012.6285812,2012 International Conference on Communications and Information Technology (ICCIT),Haddad2012,False,,IEEE,Not available,Sequential routing game on the line: Transmit or relay?,f51da9a75fad1b45600d9c90f2e3465d,https://ieeexplore.ieee.org/document/6285812/
1610,"In this paper, we study a sequential dynamic routing game on a line where the decision of a user is spatio-temporal control. Each user ships its demand over time on a shared resource. We address the case where only one user arrives at each time epoch. The state of a player evolves according to whether he decides to transmit or not. We provide explicit expressions of the equilibrium of such systems and compare them to the global optimum case. In particular, we compute the price of anarchy of such schemes and identify a Braess-type paradox in the context of sequential routing game.",julien gaillard,Nash equilibrium,2012.0,10.1109/ICCITechnol.2012.6285812,2012 International Conference on Communications and Information Technology (ICCIT),Haddad2012,False,,IEEE,Not available,Sequential routing game on the line: Transmit or relay?,f51da9a75fad1b45600d9c90f2e3465d,https://ieeexplore.ieee.org/document/6285812/
1611,"In this paper, we study a sequential dynamic routing game on a line where the decision of a user is spatio-temporal control. Each user ships its demand over time on a shared resource. We address the case where only one user arrives at each time epoch. The state of a player evolves according to whether he decides to transmit or not. We provide explicit expressions of the equilibrium of such systems and compare them to the global optimum case. In particular, we compute the price of anarchy of such schemes and identify a Braess-type paradox in the context of sequential routing game.",julien gaillard,Price of anarchy,2012.0,10.1109/ICCITechnol.2012.6285812,2012 International Conference on Communications and Information Technology (ICCIT),Haddad2012,False,,IEEE,Not available,Sequential routing game on the line: Transmit or relay?,f51da9a75fad1b45600d9c90f2e3465d,https://ieeexplore.ieee.org/document/6285812/
1612,"In this paper, we study a sequential dynamic routing game on a line where the decision of a user is spatio-temporal control. Each user ships its demand over time on a shared resource. We address the case where only one user arrives at each time epoch. The state of a player evolves according to whether he decides to transmit or not. We provide explicit expressions of the equilibrium of such systems and compare them to the global optimum case. In particular, we compute the price of anarchy of such schemes and identify a Braess-type paradox in the context of sequential routing game.",julien gaillard,Braess-type paradox,2012.0,10.1109/ICCITechnol.2012.6285812,2012 International Conference on Communications and Information Technology (ICCIT),Haddad2012,False,,IEEE,Not available,Sequential routing game on the line: Transmit or relay?,f51da9a75fad1b45600d9c90f2e3465d,https://ieeexplore.ieee.org/document/6285812/
1613,"We analyze a four node wireless network in which the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here we analyze the so called price of anarchy, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Our results show that there is a big possibility for improvement of the sum rate at the Nash equilibrium if the players are ldquoencouragedrdquo to cooperate or to choose a strategy (power policy) that is not selfish. The network operator, therefore, can design a mechanism in which both players maximize their own utilities but also the sum rate at the Nash equilibrium is much closer to the optimal sum rate.",ninoslav marina,Cooperative communications,2008.0,10.1109/EW.2008.4623877,2008 14th European Wireless Conference,Marina2008,False,,IEEE,Not available,Game theoretic analysis of a cooperative communication system,e5690a93b0e30f892b1cabc344ec64b3,https://ieeexplore.ieee.org/document/4623877/
1614,"We analyze a four node wireless network in which the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here we analyze the so called price of anarchy, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Our results show that there is a big possibility for improvement of the sum rate at the Nash equilibrium if the players are ldquoencouragedrdquo to cooperate or to choose a strategy (power policy) that is not selfish. The network operator, therefore, can design a mechanism in which both players maximize their own utilities but also the sum rate at the Nash equilibrium is much closer to the optimal sum rate.",ninoslav marina,relay channels,2008.0,10.1109/EW.2008.4623877,2008 14th European Wireless Conference,Marina2008,False,,IEEE,Not available,Game theoretic analysis of a cooperative communication system,e5690a93b0e30f892b1cabc344ec64b3,https://ieeexplore.ieee.org/document/4623877/
1615,"We analyze a four node wireless network in which the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here we analyze the so called price of anarchy, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Our results show that there is a big possibility for improvement of the sum rate at the Nash equilibrium if the players are ldquoencouragedrdquo to cooperate or to choose a strategy (power policy) that is not selfish. The network operator, therefore, can design a mechanism in which both players maximize their own utilities but also the sum rate at the Nash equilibrium is much closer to the optimal sum rate.",ninoslav marina,ad-hoc networks,2008.0,10.1109/EW.2008.4623877,2008 14th European Wireless Conference,Marina2008,False,,IEEE,Not available,Game theoretic analysis of a cooperative communication system,e5690a93b0e30f892b1cabc344ec64b3,https://ieeexplore.ieee.org/document/4623877/
1616,"We analyze a four node wireless network in which the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here we analyze the so called price of anarchy, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Our results show that there is a big possibility for improvement of the sum rate at the Nash equilibrium if the players are ldquoencouragedrdquo to cooperate or to choose a strategy (power policy) that is not selfish. The network operator, therefore, can design a mechanism in which both players maximize their own utilities but also the sum rate at the Nash equilibrium is much closer to the optimal sum rate.",ninoslav marina,game theory,2008.0,10.1109/EW.2008.4623877,2008 14th European Wireless Conference,Marina2008,False,,IEEE,Not available,Game theoretic analysis of a cooperative communication system,e5690a93b0e30f892b1cabc344ec64b3,https://ieeexplore.ieee.org/document/4623877/
1617,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
1618,"We analyze a four node wireless network in which the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here we analyze the so called price of anarchy, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Our results show that there is a big possibility for improvement of the sum rate at the Nash equilibrium if the players are ldquoencouragedrdquo to cooperate or to choose a strategy (power policy) that is not selfish. The network operator, therefore, can design a mechanism in which both players maximize their own utilities but also the sum rate at the Nash equilibrium is much closer to the optimal sum rate.",ninoslav marina,Nash equilibrium,2008.0,10.1109/EW.2008.4623877,2008 14th European Wireless Conference,Marina2008,False,,IEEE,Not available,Game theoretic analysis of a cooperative communication system,e5690a93b0e30f892b1cabc344ec64b3,https://ieeexplore.ieee.org/document/4623877/
1619,"We analyze a four node wireless network in which the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here we analyze the so called price of anarchy, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Our results show that there is a big possibility for improvement of the sum rate at the Nash equilibrium if the players are ldquoencouragedrdquo to cooperate or to choose a strategy (power policy) that is not selfish. The network operator, therefore, can design a mechanism in which both players maximize their own utilities but also the sum rate at the Nash equilibrium is much closer to the optimal sum rate.",ninoslav marina,price of anarchy,2008.0,10.1109/EW.2008.4623877,2008 14th European Wireless Conference,Marina2008,False,,IEEE,Not available,Game theoretic analysis of a cooperative communication system,e5690a93b0e30f892b1cabc344ec64b3,https://ieeexplore.ieee.org/document/4623877/
1620,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",qingqing huang,Aggregates,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
1621,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",qingqing huang,Load modeling,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
1622,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",qingqing huang,Equations,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
1623,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",qingqing huang,Electricity supply industry,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
1624,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",qingqing huang,Dynamic scheduling,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
1625,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",qingqing huang,Mathematical model,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
1626,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",qingqing huang,Pricing,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
1627,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",mardavij roozbehani,Aggregates,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
1628,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
1629,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
1630,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",mardavij roozbehani,Load modeling,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
1631,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",mardavij roozbehani,Equations,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
1632,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",mardavij roozbehani,Electricity supply industry,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
1633,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",mardavij roozbehani,Dynamic scheduling,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
1634,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",mardavij roozbehani,Mathematical model,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
1635,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",mardavij roozbehani,Pricing,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
1636,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",munther dahleh,Aggregates,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
1637,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",munther dahleh,Load modeling,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
1638,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",munther dahleh,Equations,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
1639,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",munther dahleh,Electricity supply industry,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
1640,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
1641,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",munther dahleh,Dynamic scheduling,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
1642,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",munther dahleh,Mathematical model,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
1643,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",munther dahleh,Pricing,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
1644,"This paper considers the impact of incomplete information on incentives for node cooperation in parallel relay networks with one source node, one destination node, and multiple relay nodes. All nodes are selfish and strategic, interested in maximizing their own profit instead of the social welfare. The paper considers the practical situation where the channel state on any given relay path is not observable to the source or to the other relays. Different bargaining relationships between the source and the relays are considered, and a framework for studying the efficiency loss induced by incomplete information is proposed. The source of the efficiency loss is analyzed, and the amount of inefficiency which results is quantified.",hongda xiao,Pricing,2012.0,10.1109/JSAC.2012.120116,IEEE Journal on Selected Areas in Communications,Xiao2012,False,,IEEE,Not available,The Impact of Incomplete Information on Games in Parallel Relay Networks,c81d3ad2300f280a61dc7ba49879c394,https://ieeexplore.ieee.org/document/6117772/
1645,"This paper considers the impact of incomplete information on incentives for node cooperation in parallel relay networks with one source node, one destination node, and multiple relay nodes. All nodes are selfish and strategic, interested in maximizing their own profit instead of the social welfare. The paper considers the practical situation where the channel state on any given relay path is not observable to the source or to the other relays. Different bargaining relationships between the source and the relays are considered, and a framework for studying the efficiency loss induced by incomplete information is proposed. The source of the efficiency loss is analyzed, and the amount of inefficiency which results is quantified.",hongda xiao,incentives,2012.0,10.1109/JSAC.2012.120116,IEEE Journal on Selected Areas in Communications,Xiao2012,False,,IEEE,Not available,The Impact of Incomplete Information on Games in Parallel Relay Networks,c81d3ad2300f280a61dc7ba49879c394,https://ieeexplore.ieee.org/document/6117772/
1646,"This paper considers the impact of incomplete information on incentives for node cooperation in parallel relay networks with one source node, one destination node, and multiple relay nodes. All nodes are selfish and strategic, interested in maximizing their own profit instead of the social welfare. The paper considers the practical situation where the channel state on any given relay path is not observable to the source or to the other relays. Different bargaining relationships between the source and the relays are considered, and a framework for studying the efficiency loss induced by incomplete information is proposed. The source of the efficiency loss is analyzed, and the amount of inefficiency which results is quantified.",hongda xiao,game theory,2012.0,10.1109/JSAC.2012.120116,IEEE Journal on Selected Areas in Communications,Xiao2012,False,,IEEE,Not available,The Impact of Incomplete Information on Games in Parallel Relay Networks,c81d3ad2300f280a61dc7ba49879c394,https://ieeexplore.ieee.org/document/6117772/
1647,"This paper considers the impact of incomplete information on incentives for node cooperation in parallel relay networks with one source node, one destination node, and multiple relay nodes. All nodes are selfish and strategic, interested in maximizing their own profit instead of the social welfare. The paper considers the practical situation where the channel state on any given relay path is not observable to the source or to the other relays. Different bargaining relationships between the source and the relays are considered, and a framework for studying the efficiency loss induced by incomplete information is proposed. The source of the efficiency loss is analyzed, and the amount of inefficiency which results is quantified.",hongda xiao,incomplete information,2012.0,10.1109/JSAC.2012.120116,IEEE Journal on Selected Areas in Communications,Xiao2012,False,,IEEE,Not available,The Impact of Incomplete Information on Games in Parallel Relay Networks,c81d3ad2300f280a61dc7ba49879c394,https://ieeexplore.ieee.org/document/6117772/
1648,"This paper considers the impact of incomplete information on incentives for node cooperation in parallel relay networks with one source node, one destination node, and multiple relay nodes. All nodes are selfish and strategic, interested in maximizing their own profit instead of the social welfare. The paper considers the practical situation where the channel state on any given relay path is not observable to the source or to the other relays. Different bargaining relationships between the source and the relays are considered, and a framework for studying the efficiency loss induced by incomplete information is proposed. The source of the efficiency loss is analyzed, and the amount of inefficiency which results is quantified.",hongda xiao,relay networks,2012.0,10.1109/JSAC.2012.120116,IEEE Journal on Selected Areas in Communications,Xiao2012,False,,IEEE,Not available,The Impact of Incomplete Information on Games in Parallel Relay Networks,c81d3ad2300f280a61dc7ba49879c394,https://ieeexplore.ieee.org/document/6117772/
1649,"This paper considers the impact of incomplete information on incentives for node cooperation in parallel relay networks with one source node, one destination node, and multiple relay nodes. All nodes are selfish and strategic, interested in maximizing their own profit instead of the social welfare. The paper considers the practical situation where the channel state on any given relay path is not observable to the source or to the other relays. Different bargaining relationships between the source and the relays are considered, and a framework for studying the efficiency loss induced by incomplete information is proposed. The source of the efficiency loss is analyzed, and the amount of inefficiency which results is quantified.",hongda xiao,price of anarchy,2012.0,10.1109/JSAC.2012.120116,IEEE Journal on Selected Areas in Communications,Xiao2012,False,,IEEE,Not available,The Impact of Incomplete Information on Games in Parallel Relay Networks,c81d3ad2300f280a61dc7ba49879c394,https://ieeexplore.ieee.org/document/6117772/
1650,"This paper considers the impact of incomplete information on incentives for node cooperation in parallel relay networks with one source node, one destination node, and multiple relay nodes. All nodes are selfish and strategic, interested in maximizing their own profit instead of the social welfare. The paper considers the practical situation where the channel state on any given relay path is not observable to the source or to the other relays. Different bargaining relationships between the source and the relays are considered, and a framework for studying the efficiency loss induced by incomplete information is proposed. The source of the efficiency loss is analyzed, and the amount of inefficiency which results is quantified.",hongda xiao,Bayesian nash equilibrium,2012.0,10.1109/JSAC.2012.120116,IEEE Journal on Selected Areas in Communications,Xiao2012,False,,IEEE,Not available,The Impact of Incomplete Information on Games in Parallel Relay Networks,c81d3ad2300f280a61dc7ba49879c394,https://ieeexplore.ieee.org/document/6117772/
1651,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
1652,"This paper considers the impact of incomplete information on incentives for node cooperation in parallel relay networks with one source node, one destination node, and multiple relay nodes. All nodes are selfish and strategic, interested in maximizing their own profit instead of the social welfare. The paper considers the practical situation where the channel state on any given relay path is not observable to the source or to the other relays. Different bargaining relationships between the source and the relays are considered, and a framework for studying the efficiency loss induced by incomplete information is proposed. The source of the efficiency loss is analyzed, and the amount of inefficiency which results is quantified.",edmund yeh,Pricing,2012.0,10.1109/JSAC.2012.120116,IEEE Journal on Selected Areas in Communications,Xiao2012,False,,IEEE,Not available,The Impact of Incomplete Information on Games in Parallel Relay Networks,c81d3ad2300f280a61dc7ba49879c394,https://ieeexplore.ieee.org/document/6117772/
1653,"This paper considers the impact of incomplete information on incentives for node cooperation in parallel relay networks with one source node, one destination node, and multiple relay nodes. All nodes are selfish and strategic, interested in maximizing their own profit instead of the social welfare. The paper considers the practical situation where the channel state on any given relay path is not observable to the source or to the other relays. Different bargaining relationships between the source and the relays are considered, and a framework for studying the efficiency loss induced by incomplete information is proposed. The source of the efficiency loss is analyzed, and the amount of inefficiency which results is quantified.",edmund yeh,incentives,2012.0,10.1109/JSAC.2012.120116,IEEE Journal on Selected Areas in Communications,Xiao2012,False,,IEEE,Not available,The Impact of Incomplete Information on Games in Parallel Relay Networks,c81d3ad2300f280a61dc7ba49879c394,https://ieeexplore.ieee.org/document/6117772/
1654,"This paper considers the impact of incomplete information on incentives for node cooperation in parallel relay networks with one source node, one destination node, and multiple relay nodes. All nodes are selfish and strategic, interested in maximizing their own profit instead of the social welfare. The paper considers the practical situation where the channel state on any given relay path is not observable to the source or to the other relays. Different bargaining relationships between the source and the relays are considered, and a framework for studying the efficiency loss induced by incomplete information is proposed. The source of the efficiency loss is analyzed, and the amount of inefficiency which results is quantified.",edmund yeh,game theory,2012.0,10.1109/JSAC.2012.120116,IEEE Journal on Selected Areas in Communications,Xiao2012,False,,IEEE,Not available,The Impact of Incomplete Information on Games in Parallel Relay Networks,c81d3ad2300f280a61dc7ba49879c394,https://ieeexplore.ieee.org/document/6117772/
1655,"This paper considers the impact of incomplete information on incentives for node cooperation in parallel relay networks with one source node, one destination node, and multiple relay nodes. All nodes are selfish and strategic, interested in maximizing their own profit instead of the social welfare. The paper considers the practical situation where the channel state on any given relay path is not observable to the source or to the other relays. Different bargaining relationships between the source and the relays are considered, and a framework for studying the efficiency loss induced by incomplete information is proposed. The source of the efficiency loss is analyzed, and the amount of inefficiency which results is quantified.",edmund yeh,incomplete information,2012.0,10.1109/JSAC.2012.120116,IEEE Journal on Selected Areas in Communications,Xiao2012,False,,IEEE,Not available,The Impact of Incomplete Information on Games in Parallel Relay Networks,c81d3ad2300f280a61dc7ba49879c394,https://ieeexplore.ieee.org/document/6117772/
1656,"This paper considers the impact of incomplete information on incentives for node cooperation in parallel relay networks with one source node, one destination node, and multiple relay nodes. All nodes are selfish and strategic, interested in maximizing their own profit instead of the social welfare. The paper considers the practical situation where the channel state on any given relay path is not observable to the source or to the other relays. Different bargaining relationships between the source and the relays are considered, and a framework for studying the efficiency loss induced by incomplete information is proposed. The source of the efficiency loss is analyzed, and the amount of inefficiency which results is quantified.",edmund yeh,relay networks,2012.0,10.1109/JSAC.2012.120116,IEEE Journal on Selected Areas in Communications,Xiao2012,False,,IEEE,Not available,The Impact of Incomplete Information on Games in Parallel Relay Networks,c81d3ad2300f280a61dc7ba49879c394,https://ieeexplore.ieee.org/document/6117772/
1657,"This paper considers the impact of incomplete information on incentives for node cooperation in parallel relay networks with one source node, one destination node, and multiple relay nodes. All nodes are selfish and strategic, interested in maximizing their own profit instead of the social welfare. The paper considers the practical situation where the channel state on any given relay path is not observable to the source or to the other relays. Different bargaining relationships between the source and the relays are considered, and a framework for studying the efficiency loss induced by incomplete information is proposed. The source of the efficiency loss is analyzed, and the amount of inefficiency which results is quantified.",edmund yeh,price of anarchy,2012.0,10.1109/JSAC.2012.120116,IEEE Journal on Selected Areas in Communications,Xiao2012,False,,IEEE,Not available,The Impact of Incomplete Information on Games in Parallel Relay Networks,c81d3ad2300f280a61dc7ba49879c394,https://ieeexplore.ieee.org/document/6117772/
1658,"This paper considers the impact of incomplete information on incentives for node cooperation in parallel relay networks with one source node, one destination node, and multiple relay nodes. All nodes are selfish and strategic, interested in maximizing their own profit instead of the social welfare. The paper considers the practical situation where the channel state on any given relay path is not observable to the source or to the other relays. Different bargaining relationships between the source and the relays are considered, and a framework for studying the efficiency loss induced by incomplete information is proposed. The source of the efficiency loss is analyzed, and the amount of inefficiency which results is quantified.",edmund yeh,Bayesian nash equilibrium,2012.0,10.1109/JSAC.2012.120116,IEEE Journal on Selected Areas in Communications,Xiao2012,False,,IEEE,Not available,The Impact of Incomplete Information on Games in Parallel Relay Networks,c81d3ad2300f280a61dc7ba49879c394,https://ieeexplore.ieee.org/document/6117772/
1659,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,tejas bodas,Servers,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
1660,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,tejas bodas,Resource management,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
1661,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,tejas bodas,Routing,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
1662,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
1663,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,tejas bodas,Load management,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
1664,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,tejas bodas,Queueing analysis,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
1665,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,tejas bodas,Cost function,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
1666,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,tejas bodas,Delay,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
1667,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,ayalvadi ganesh,Servers,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
1668,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,ayalvadi ganesh,Resource management,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
1669,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,ayalvadi ganesh,Routing,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
1670,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,ayalvadi ganesh,Load management,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
1671,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,ayalvadi ganesh,Queueing analysis,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
1672,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,ayalvadi ganesh,Cost function,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
1673,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
1674,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,ayalvadi ganesh,Delay,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
1675,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,d. manjunath,Servers,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
1676,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,d. manjunath,Resource management,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
1677,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,d. manjunath,Routing,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
1678,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,d. manjunath,Load management,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
1679,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,d. manjunath,Queueing analysis,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
1680,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,d. manjunath,Cost function,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
1681,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,d. manjunath,Delay,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
1682,"This paper studies the performance of a wireless network when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We define the utility of each node as a weighted difference between a performance metric and some transmission costs. We consider expected goodput and expected delay as the performance metrics. The relative preference of nodes for their performance metrics and the transmission costs is represented by a tradeoff factor. We first consider a scenario in which nodes can be priced for the channel access. We relate the tradeoff factor to some pricing mechanism and compute the symmetric Nash equilibria of the game in closed form as a function of the price factor. We show that simple pricing mechanisms can be used to maximize system efficiency. In particular, we show that for a specific value of price factor, the selfish behavior of the nodes can be used to achieve the same performance as social optima at equilibrium. In the case without pricing where the dis-utility coincides with the transmission energy costs, we analyze the Price of Anarchy for these games. For the game with goodput based utility, we show that the Price of Anarchy is infinite at the tradeoff factor that achieves the global optimal goodput. For the game with delay based utility, we bound the Price of Anarchy and study the effect of the tradeoff factor.",manjesh hanawal,Game Theory,2012.0,10.1109/JSAC.2012.121207,IEEE Journal on Selected Areas in Communications,Hanawal2012,False,,IEEE,Not available,Stochastic Geometry Based Medium Access Games in Wireless Ad Hoc Networks,a8150a029cf597501477ef5918f2db7d,https://ieeexplore.ieee.org/document/6354273/
1683,"This paper studies the performance of a wireless network when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We define the utility of each node as a weighted difference between a performance metric and some transmission costs. We consider expected goodput and expected delay as the performance metrics. The relative preference of nodes for their performance metrics and the transmission costs is represented by a tradeoff factor. We first consider a scenario in which nodes can be priced for the channel access. We relate the tradeoff factor to some pricing mechanism and compute the symmetric Nash equilibria of the game in closed form as a function of the price factor. We show that simple pricing mechanisms can be used to maximize system efficiency. In particular, we show that for a specific value of price factor, the selfish behavior of the nodes can be used to achieve the same performance as social optima at equilibrium. In the case without pricing where the dis-utility coincides with the transmission energy costs, we analyze the Price of Anarchy for these games. For the game with goodput based utility, we show that the Price of Anarchy is infinite at the tradeoff factor that achieves the global optimal goodput. For the game with delay based utility, we bound the Price of Anarchy and study the effect of the tradeoff factor.",manjesh hanawal,Mobile Ad hoc Networks (MANETs),2012.0,10.1109/JSAC.2012.121207,IEEE Journal on Selected Areas in Communications,Hanawal2012,False,,IEEE,Not available,Stochastic Geometry Based Medium Access Games in Wireless Ad Hoc Networks,a8150a029cf597501477ef5918f2db7d,https://ieeexplore.ieee.org/document/6354273/
1684,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
1685,"This paper studies the performance of a wireless network when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We define the utility of each node as a weighted difference between a performance metric and some transmission costs. We consider expected goodput and expected delay as the performance metrics. The relative preference of nodes for their performance metrics and the transmission costs is represented by a tradeoff factor. We first consider a scenario in which nodes can be priced for the channel access. We relate the tradeoff factor to some pricing mechanism and compute the symmetric Nash equilibria of the game in closed form as a function of the price factor. We show that simple pricing mechanisms can be used to maximize system efficiency. In particular, we show that for a specific value of price factor, the selfish behavior of the nodes can be used to achieve the same performance as social optima at equilibrium. In the case without pricing where the dis-utility coincides with the transmission energy costs, we analyze the Price of Anarchy for these games. For the game with goodput based utility, we show that the Price of Anarchy is infinite at the tradeoff factor that achieves the global optimal goodput. For the game with delay based utility, we bound the Price of Anarchy and study the effect of the tradeoff factor.",manjesh hanawal,Pricing,2012.0,10.1109/JSAC.2012.121207,IEEE Journal on Selected Areas in Communications,Hanawal2012,False,,IEEE,Not available,Stochastic Geometry Based Medium Access Games in Wireless Ad Hoc Networks,a8150a029cf597501477ef5918f2db7d,https://ieeexplore.ieee.org/document/6354273/
1686,"This paper studies the performance of a wireless network when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We define the utility of each node as a weighted difference between a performance metric and some transmission costs. We consider expected goodput and expected delay as the performance metrics. The relative preference of nodes for their performance metrics and the transmission costs is represented by a tradeoff factor. We first consider a scenario in which nodes can be priced for the channel access. We relate the tradeoff factor to some pricing mechanism and compute the symmetric Nash equilibria of the game in closed form as a function of the price factor. We show that simple pricing mechanisms can be used to maximize system efficiency. In particular, we show that for a specific value of price factor, the selfish behavior of the nodes can be used to achieve the same performance as social optima at equilibrium. In the case without pricing where the dis-utility coincides with the transmission energy costs, we analyze the Price of Anarchy for these games. For the game with goodput based utility, we show that the Price of Anarchy is infinite at the tradeoff factor that achieves the global optimal goodput. For the game with delay based utility, we bound the Price of Anarchy and study the effect of the tradeoff factor.",manjesh hanawal,Medium Access Control,2012.0,10.1109/JSAC.2012.121207,IEEE Journal on Selected Areas in Communications,Hanawal2012,False,,IEEE,Not available,Stochastic Geometry Based Medium Access Games in Wireless Ad Hoc Networks,a8150a029cf597501477ef5918f2db7d,https://ieeexplore.ieee.org/document/6354273/
1687,"This paper studies the performance of a wireless network when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We define the utility of each node as a weighted difference between a performance metric and some transmission costs. We consider expected goodput and expected delay as the performance metrics. The relative preference of nodes for their performance metrics and the transmission costs is represented by a tradeoff factor. We first consider a scenario in which nodes can be priced for the channel access. We relate the tradeoff factor to some pricing mechanism and compute the symmetric Nash equilibria of the game in closed form as a function of the price factor. We show that simple pricing mechanisms can be used to maximize system efficiency. In particular, we show that for a specific value of price factor, the selfish behavior of the nodes can be used to achieve the same performance as social optima at equilibrium. In the case without pricing where the dis-utility coincides with the transmission energy costs, we analyze the Price of Anarchy for these games. For the game with goodput based utility, we show that the Price of Anarchy is infinite at the tradeoff factor that achieves the global optimal goodput. For the game with delay based utility, we bound the Price of Anarchy and study the effect of the tradeoff factor.",manjesh hanawal,Stochastic Geometry,2012.0,10.1109/JSAC.2012.121207,IEEE Journal on Selected Areas in Communications,Hanawal2012,False,,IEEE,Not available,Stochastic Geometry Based Medium Access Games in Wireless Ad Hoc Networks,a8150a029cf597501477ef5918f2db7d,https://ieeexplore.ieee.org/document/6354273/
1688,"This paper studies the performance of a wireless network when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We define the utility of each node as a weighted difference between a performance metric and some transmission costs. We consider expected goodput and expected delay as the performance metrics. The relative preference of nodes for their performance metrics and the transmission costs is represented by a tradeoff factor. We first consider a scenario in which nodes can be priced for the channel access. We relate the tradeoff factor to some pricing mechanism and compute the symmetric Nash equilibria of the game in closed form as a function of the price factor. We show that simple pricing mechanisms can be used to maximize system efficiency. In particular, we show that for a specific value of price factor, the selfish behavior of the nodes can be used to achieve the same performance as social optima at equilibrium. In the case without pricing where the dis-utility coincides with the transmission energy costs, we analyze the Price of Anarchy for these games. For the game with goodput based utility, we show that the Price of Anarchy is infinite at the tradeoff factor that achieves the global optimal goodput. For the game with delay based utility, we bound the Price of Anarchy and study the effect of the tradeoff factor.",manjesh hanawal,Replicator Dynamics,2012.0,10.1109/JSAC.2012.121207,IEEE Journal on Selected Areas in Communications,Hanawal2012,False,,IEEE,Not available,Stochastic Geometry Based Medium Access Games in Wireless Ad Hoc Networks,a8150a029cf597501477ef5918f2db7d,https://ieeexplore.ieee.org/document/6354273/
1689,"This paper studies the performance of a wireless network when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We define the utility of each node as a weighted difference between a performance metric and some transmission costs. We consider expected goodput and expected delay as the performance metrics. The relative preference of nodes for their performance metrics and the transmission costs is represented by a tradeoff factor. We first consider a scenario in which nodes can be priced for the channel access. We relate the tradeoff factor to some pricing mechanism and compute the symmetric Nash equilibria of the game in closed form as a function of the price factor. We show that simple pricing mechanisms can be used to maximize system efficiency. In particular, we show that for a specific value of price factor, the selfish behavior of the nodes can be used to achieve the same performance as social optima at equilibrium. In the case without pricing where the dis-utility coincides with the transmission energy costs, we analyze the Price of Anarchy for these games. For the game with goodput based utility, we show that the Price of Anarchy is infinite at the tradeoff factor that achieves the global optimal goodput. For the game with delay based utility, we bound the Price of Anarchy and study the effect of the tradeoff factor.",eitan altman,Game Theory,2012.0,10.1109/JSAC.2012.121207,IEEE Journal on Selected Areas in Communications,Hanawal2012,False,,IEEE,Not available,Stochastic Geometry Based Medium Access Games in Wireless Ad Hoc Networks,a8150a029cf597501477ef5918f2db7d,https://ieeexplore.ieee.org/document/6354273/
1690,"This paper studies the performance of a wireless network when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We define the utility of each node as a weighted difference between a performance metric and some transmission costs. We consider expected goodput and expected delay as the performance metrics. The relative preference of nodes for their performance metrics and the transmission costs is represented by a tradeoff factor. We first consider a scenario in which nodes can be priced for the channel access. We relate the tradeoff factor to some pricing mechanism and compute the symmetric Nash equilibria of the game in closed form as a function of the price factor. We show that simple pricing mechanisms can be used to maximize system efficiency. In particular, we show that for a specific value of price factor, the selfish behavior of the nodes can be used to achieve the same performance as social optima at equilibrium. In the case without pricing where the dis-utility coincides with the transmission energy costs, we analyze the Price of Anarchy for these games. For the game with goodput based utility, we show that the Price of Anarchy is infinite at the tradeoff factor that achieves the global optimal goodput. For the game with delay based utility, we bound the Price of Anarchy and study the effect of the tradeoff factor.",eitan altman,Mobile Ad hoc Networks (MANETs),2012.0,10.1109/JSAC.2012.121207,IEEE Journal on Selected Areas in Communications,Hanawal2012,False,,IEEE,Not available,Stochastic Geometry Based Medium Access Games in Wireless Ad Hoc Networks,a8150a029cf597501477ef5918f2db7d,https://ieeexplore.ieee.org/document/6354273/
1691,"This paper studies the performance of a wireless network when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We define the utility of each node as a weighted difference between a performance metric and some transmission costs. We consider expected goodput and expected delay as the performance metrics. The relative preference of nodes for their performance metrics and the transmission costs is represented by a tradeoff factor. We first consider a scenario in which nodes can be priced for the channel access. We relate the tradeoff factor to some pricing mechanism and compute the symmetric Nash equilibria of the game in closed form as a function of the price factor. We show that simple pricing mechanisms can be used to maximize system efficiency. In particular, we show that for a specific value of price factor, the selfish behavior of the nodes can be used to achieve the same performance as social optima at equilibrium. In the case without pricing where the dis-utility coincides with the transmission energy costs, we analyze the Price of Anarchy for these games. For the game with goodput based utility, we show that the Price of Anarchy is infinite at the tradeoff factor that achieves the global optimal goodput. For the game with delay based utility, we bound the Price of Anarchy and study the effect of the tradeoff factor.",eitan altman,Pricing,2012.0,10.1109/JSAC.2012.121207,IEEE Journal on Selected Areas in Communications,Hanawal2012,False,,IEEE,Not available,Stochastic Geometry Based Medium Access Games in Wireless Ad Hoc Networks,a8150a029cf597501477ef5918f2db7d,https://ieeexplore.ieee.org/document/6354273/
1692,"This paper studies the performance of a wireless network when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We define the utility of each node as a weighted difference between a performance metric and some transmission costs. We consider expected goodput and expected delay as the performance metrics. The relative preference of nodes for their performance metrics and the transmission costs is represented by a tradeoff factor. We first consider a scenario in which nodes can be priced for the channel access. We relate the tradeoff factor to some pricing mechanism and compute the symmetric Nash equilibria of the game in closed form as a function of the price factor. We show that simple pricing mechanisms can be used to maximize system efficiency. In particular, we show that for a specific value of price factor, the selfish behavior of the nodes can be used to achieve the same performance as social optima at equilibrium. In the case without pricing where the dis-utility coincides with the transmission energy costs, we analyze the Price of Anarchy for these games. For the game with goodput based utility, we show that the Price of Anarchy is infinite at the tradeoff factor that achieves the global optimal goodput. For the game with delay based utility, we bound the Price of Anarchy and study the effect of the tradeoff factor.",eitan altman,Medium Access Control,2012.0,10.1109/JSAC.2012.121207,IEEE Journal on Selected Areas in Communications,Hanawal2012,False,,IEEE,Not available,Stochastic Geometry Based Medium Access Games in Wireless Ad Hoc Networks,a8150a029cf597501477ef5918f2db7d,https://ieeexplore.ieee.org/document/6354273/
1693,"This paper studies the performance of a wireless network when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We define the utility of each node as a weighted difference between a performance metric and some transmission costs. We consider expected goodput and expected delay as the performance metrics. The relative preference of nodes for their performance metrics and the transmission costs is represented by a tradeoff factor. We first consider a scenario in which nodes can be priced for the channel access. We relate the tradeoff factor to some pricing mechanism and compute the symmetric Nash equilibria of the game in closed form as a function of the price factor. We show that simple pricing mechanisms can be used to maximize system efficiency. In particular, we show that for a specific value of price factor, the selfish behavior of the nodes can be used to achieve the same performance as social optima at equilibrium. In the case without pricing where the dis-utility coincides with the transmission energy costs, we analyze the Price of Anarchy for these games. For the game with goodput based utility, we show that the Price of Anarchy is infinite at the tradeoff factor that achieves the global optimal goodput. For the game with delay based utility, we bound the Price of Anarchy and study the effect of the tradeoff factor.",eitan altman,Stochastic Geometry,2012.0,10.1109/JSAC.2012.121207,IEEE Journal on Selected Areas in Communications,Hanawal2012,False,,IEEE,Not available,Stochastic Geometry Based Medium Access Games in Wireless Ad Hoc Networks,a8150a029cf597501477ef5918f2db7d,https://ieeexplore.ieee.org/document/6354273/
1694,"This paper studies the performance of a wireless network when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We define the utility of each node as a weighted difference between a performance metric and some transmission costs. We consider expected goodput and expected delay as the performance metrics. The relative preference of nodes for their performance metrics and the transmission costs is represented by a tradeoff factor. We first consider a scenario in which nodes can be priced for the channel access. We relate the tradeoff factor to some pricing mechanism and compute the symmetric Nash equilibria of the game in closed form as a function of the price factor. We show that simple pricing mechanisms can be used to maximize system efficiency. In particular, we show that for a specific value of price factor, the selfish behavior of the nodes can be used to achieve the same performance as social optima at equilibrium. In the case without pricing where the dis-utility coincides with the transmission energy costs, we analyze the Price of Anarchy for these games. For the game with goodput based utility, we show that the Price of Anarchy is infinite at the tradeoff factor that achieves the global optimal goodput. For the game with delay based utility, we bound the Price of Anarchy and study the effect of the tradeoff factor.",eitan altman,Replicator Dynamics,2012.0,10.1109/JSAC.2012.121207,IEEE Journal on Selected Areas in Communications,Hanawal2012,False,,IEEE,Not available,Stochastic Geometry Based Medium Access Games in Wireless Ad Hoc Networks,a8150a029cf597501477ef5918f2db7d,https://ieeexplore.ieee.org/document/6354273/
1695,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
1696,"This paper studies the performance of a wireless network when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We define the utility of each node as a weighted difference between a performance metric and some transmission costs. We consider expected goodput and expected delay as the performance metrics. The relative preference of nodes for their performance metrics and the transmission costs is represented by a tradeoff factor. We first consider a scenario in which nodes can be priced for the channel access. We relate the tradeoff factor to some pricing mechanism and compute the symmetric Nash equilibria of the game in closed form as a function of the price factor. We show that simple pricing mechanisms can be used to maximize system efficiency. In particular, we show that for a specific value of price factor, the selfish behavior of the nodes can be used to achieve the same performance as social optima at equilibrium. In the case without pricing where the dis-utility coincides with the transmission energy costs, we analyze the Price of Anarchy for these games. For the game with goodput based utility, we show that the Price of Anarchy is infinite at the tradeoff factor that achieves the global optimal goodput. For the game with delay based utility, we bound the Price of Anarchy and study the effect of the tradeoff factor.",francois baccelli,Game Theory,2012.0,10.1109/JSAC.2012.121207,IEEE Journal on Selected Areas in Communications,Hanawal2012,False,,IEEE,Not available,Stochastic Geometry Based Medium Access Games in Wireless Ad Hoc Networks,a8150a029cf597501477ef5918f2db7d,https://ieeexplore.ieee.org/document/6354273/
1697,"This paper studies the performance of a wireless network when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We define the utility of each node as a weighted difference between a performance metric and some transmission costs. We consider expected goodput and expected delay as the performance metrics. The relative preference of nodes for their performance metrics and the transmission costs is represented by a tradeoff factor. We first consider a scenario in which nodes can be priced for the channel access. We relate the tradeoff factor to some pricing mechanism and compute the symmetric Nash equilibria of the game in closed form as a function of the price factor. We show that simple pricing mechanisms can be used to maximize system efficiency. In particular, we show that for a specific value of price factor, the selfish behavior of the nodes can be used to achieve the same performance as social optima at equilibrium. In the case without pricing where the dis-utility coincides with the transmission energy costs, we analyze the Price of Anarchy for these games. For the game with goodput based utility, we show that the Price of Anarchy is infinite at the tradeoff factor that achieves the global optimal goodput. For the game with delay based utility, we bound the Price of Anarchy and study the effect of the tradeoff factor.",francois baccelli,Mobile Ad hoc Networks (MANETs),2012.0,10.1109/JSAC.2012.121207,IEEE Journal on Selected Areas in Communications,Hanawal2012,False,,IEEE,Not available,Stochastic Geometry Based Medium Access Games in Wireless Ad Hoc Networks,a8150a029cf597501477ef5918f2db7d,https://ieeexplore.ieee.org/document/6354273/
1698,"This paper studies the performance of a wireless network when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We define the utility of each node as a weighted difference between a performance metric and some transmission costs. We consider expected goodput and expected delay as the performance metrics. The relative preference of nodes for their performance metrics and the transmission costs is represented by a tradeoff factor. We first consider a scenario in which nodes can be priced for the channel access. We relate the tradeoff factor to some pricing mechanism and compute the symmetric Nash equilibria of the game in closed form as a function of the price factor. We show that simple pricing mechanisms can be used to maximize system efficiency. In particular, we show that for a specific value of price factor, the selfish behavior of the nodes can be used to achieve the same performance as social optima at equilibrium. In the case without pricing where the dis-utility coincides with the transmission energy costs, we analyze the Price of Anarchy for these games. For the game with goodput based utility, we show that the Price of Anarchy is infinite at the tradeoff factor that achieves the global optimal goodput. For the game with delay based utility, we bound the Price of Anarchy and study the effect of the tradeoff factor.",francois baccelli,Pricing,2012.0,10.1109/JSAC.2012.121207,IEEE Journal on Selected Areas in Communications,Hanawal2012,False,,IEEE,Not available,Stochastic Geometry Based Medium Access Games in Wireless Ad Hoc Networks,a8150a029cf597501477ef5918f2db7d,https://ieeexplore.ieee.org/document/6354273/
1699,"This paper studies the performance of a wireless network when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We define the utility of each node as a weighted difference between a performance metric and some transmission costs. We consider expected goodput and expected delay as the performance metrics. The relative preference of nodes for their performance metrics and the transmission costs is represented by a tradeoff factor. We first consider a scenario in which nodes can be priced for the channel access. We relate the tradeoff factor to some pricing mechanism and compute the symmetric Nash equilibria of the game in closed form as a function of the price factor. We show that simple pricing mechanisms can be used to maximize system efficiency. In particular, we show that for a specific value of price factor, the selfish behavior of the nodes can be used to achieve the same performance as social optima at equilibrium. In the case without pricing where the dis-utility coincides with the transmission energy costs, we analyze the Price of Anarchy for these games. For the game with goodput based utility, we show that the Price of Anarchy is infinite at the tradeoff factor that achieves the global optimal goodput. For the game with delay based utility, we bound the Price of Anarchy and study the effect of the tradeoff factor.",francois baccelli,Medium Access Control,2012.0,10.1109/JSAC.2012.121207,IEEE Journal on Selected Areas in Communications,Hanawal2012,False,,IEEE,Not available,Stochastic Geometry Based Medium Access Games in Wireless Ad Hoc Networks,a8150a029cf597501477ef5918f2db7d,https://ieeexplore.ieee.org/document/6354273/
1700,"This paper studies the performance of a wireless network when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We define the utility of each node as a weighted difference between a performance metric and some transmission costs. We consider expected goodput and expected delay as the performance metrics. The relative preference of nodes for their performance metrics and the transmission costs is represented by a tradeoff factor. We first consider a scenario in which nodes can be priced for the channel access. We relate the tradeoff factor to some pricing mechanism and compute the symmetric Nash equilibria of the game in closed form as a function of the price factor. We show that simple pricing mechanisms can be used to maximize system efficiency. In particular, we show that for a specific value of price factor, the selfish behavior of the nodes can be used to achieve the same performance as social optima at equilibrium. In the case without pricing where the dis-utility coincides with the transmission energy costs, we analyze the Price of Anarchy for these games. For the game with goodput based utility, we show that the Price of Anarchy is infinite at the tradeoff factor that achieves the global optimal goodput. For the game with delay based utility, we bound the Price of Anarchy and study the effect of the tradeoff factor.",francois baccelli,Stochastic Geometry,2012.0,10.1109/JSAC.2012.121207,IEEE Journal on Selected Areas in Communications,Hanawal2012,False,,IEEE,Not available,Stochastic Geometry Based Medium Access Games in Wireless Ad Hoc Networks,a8150a029cf597501477ef5918f2db7d,https://ieeexplore.ieee.org/document/6354273/
1701,"This paper studies the performance of a wireless network when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We define the utility of each node as a weighted difference between a performance metric and some transmission costs. We consider expected goodput and expected delay as the performance metrics. The relative preference of nodes for their performance metrics and the transmission costs is represented by a tradeoff factor. We first consider a scenario in which nodes can be priced for the channel access. We relate the tradeoff factor to some pricing mechanism and compute the symmetric Nash equilibria of the game in closed form as a function of the price factor. We show that simple pricing mechanisms can be used to maximize system efficiency. In particular, we show that for a specific value of price factor, the selfish behavior of the nodes can be used to achieve the same performance as social optima at equilibrium. In the case without pricing where the dis-utility coincides with the transmission energy costs, we analyze the Price of Anarchy for these games. For the game with goodput based utility, we show that the Price of Anarchy is infinite at the tradeoff factor that achieves the global optimal goodput. For the game with delay based utility, we bound the Price of Anarchy and study the effect of the tradeoff factor.",francois baccelli,Replicator Dynamics,2012.0,10.1109/JSAC.2012.121207,IEEE Journal on Selected Areas in Communications,Hanawal2012,False,,IEEE,Not available,Stochastic Geometry Based Medium Access Games in Wireless Ad Hoc Networks,a8150a029cf597501477ef5918f2db7d,https://ieeexplore.ieee.org/document/6354273/
1702,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",praneeth tota,Games,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
1703,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",praneeth tota,Resource management,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
1704,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",praneeth tota,Economics,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
1705,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",praneeth tota,Nash equilibrium,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
1706,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
1707,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",praneeth tota,Gain measurement,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
1708,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",praneeth tota,Computer science,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
1709,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",praneeth tota,Loss measurement,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
1710,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",sanjiv kapoor,Games,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
1711,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",sanjiv kapoor,Resource management,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
1712,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",sanjiv kapoor,Economics,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
1713,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",sanjiv kapoor,Nash equilibrium,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
1714,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",sanjiv kapoor,Gain measurement,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
1715,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",sanjiv kapoor,Computer science,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
1716,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",sanjiv kapoor,Loss measurement,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
1717,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
1718,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",benjamin grimmer,Games,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
1719,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",benjamin grimmer,Resource management,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
1720,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",benjamin grimmer,Economics,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
1721,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",benjamin grimmer,Nash equilibrium,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
1722,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",benjamin grimmer,Gain measurement,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
1723,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",benjamin grimmer,Computer science,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
1724,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",benjamin grimmer,Loss measurement,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
1725,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",evangelos bampas,Bottleneck games,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
1726,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",evangelos bampas,multifiber optical networks,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
1727,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",evangelos bampas,noncooperative games,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
1728,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
1729,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",evangelos bampas,path multicoloring,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
1730,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",evangelos bampas,price of anarchy,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
1731,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",evangelos bampas,selfish wavelength assignment,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
1732,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",aris pagourtzis,Bottleneck games,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
1733,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",aris pagourtzis,multifiber optical networks,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
1734,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",aris pagourtzis,noncooperative games,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
1735,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",aris pagourtzis,path multicoloring,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
1736,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",aris pagourtzis,price of anarchy,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
1737,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",aris pagourtzis,selfish wavelength assignment,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
1738,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",george pierrakos,Bottleneck games,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
1739,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
1740,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
1741,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",george pierrakos,multifiber optical networks,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
1742,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",george pierrakos,noncooperative games,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
1743,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",george pierrakos,path multicoloring,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
1744,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",george pierrakos,price of anarchy,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
1745,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",george pierrakos,selfish wavelength assignment,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
1746,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",katerina potika,Bottleneck games,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
1747,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",katerina potika,multifiber optical networks,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
1748,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",katerina potika,noncooperative games,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
1749,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",katerina potika,path multicoloring,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
1750,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",katerina potika,price of anarchy,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
1751,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
1752,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",katerina potika,selfish wavelength assignment,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
1753,"Wireless access networks are often characterized by the interaction of different end users, communication technologies, and network operators. This paper analyzes the dynamics among these ""actorsâ by focusing on the processes of wireless network selection, where end users may choose among multiple available access networks to get connectivity, and resource allocation, where network operators may set their radio resources to provide connectivity. The interaction among end users is modeled as a noncooperative congestion game, where players (end users) selfishly select the access network that minimizes their perceived selection cost. A method based on mathematical programming is proposed to find Nash equilibria and characterize their optimality under three cost functions, which are representative of different technological scenarios. System level simulations are then used to evaluate the actual throughput and fairness of the equilibrium points. The interaction among end users and network operators is then assessed through a two-stage multileader/multifollower game, where network operators (leaders) play in the first stage by properly setting the radio resources to maximize their users, and end users (followers) play in the second stage the aforementioned network selection game. The existence of exact and approximated subgame perfect Nash equilibria of the two-stage game is thoroughly assessed and numerical results are provided on the ""qualityâ of such equilibria.",ilaria malanchini,Wireless access networks,2013.0,10.1109/TMC.2012.207,IEEE Transactions on Mobile Computing,Malanchini2013,False,,IEEE,Not available,Network Selection and Resource Allocation Games for Wireless Access Networks,2afd935f8a424d9998febbaaf4532fd0,https://ieeexplore.ieee.org/document/6320552/
1754,"Wireless access networks are often characterized by the interaction of different end users, communication technologies, and network operators. This paper analyzes the dynamics among these ""actorsâ by focusing on the processes of wireless network selection, where end users may choose among multiple available access networks to get connectivity, and resource allocation, where network operators may set their radio resources to provide connectivity. The interaction among end users is modeled as a noncooperative congestion game, where players (end users) selfishly select the access network that minimizes their perceived selection cost. A method based on mathematical programming is proposed to find Nash equilibria and characterize their optimality under three cost functions, which are representative of different technological scenarios. System level simulations are then used to evaluate the actual throughput and fairness of the equilibrium points. The interaction among end users and network operators is then assessed through a two-stage multileader/multifollower game, where network operators (leaders) play in the first stage by properly setting the radio resources to maximize their users, and end users (followers) play in the second stage the aforementioned network selection game. The existence of exact and approximated subgame perfect Nash equilibria of the two-stage game is thoroughly assessed and numerical results are provided on the ""qualityâ of such equilibria.",ilaria malanchini,network selection,2013.0,10.1109/TMC.2012.207,IEEE Transactions on Mobile Computing,Malanchini2013,False,,IEEE,Not available,Network Selection and Resource Allocation Games for Wireless Access Networks,2afd935f8a424d9998febbaaf4532fd0,https://ieeexplore.ieee.org/document/6320552/
1755,"Wireless access networks are often characterized by the interaction of different end users, communication technologies, and network operators. This paper analyzes the dynamics among these ""actorsâ by focusing on the processes of wireless network selection, where end users may choose among multiple available access networks to get connectivity, and resource allocation, where network operators may set their radio resources to provide connectivity. The interaction among end users is modeled as a noncooperative congestion game, where players (end users) selfishly select the access network that minimizes their perceived selection cost. A method based on mathematical programming is proposed to find Nash equilibria and characterize their optimality under three cost functions, which are representative of different technological scenarios. System level simulations are then used to evaluate the actual throughput and fairness of the equilibrium points. The interaction among end users and network operators is then assessed through a two-stage multileader/multifollower game, where network operators (leaders) play in the first stage by properly setting the radio resources to maximize their users, and end users (followers) play in the second stage the aforementioned network selection game. The existence of exact and approximated subgame perfect Nash equilibria of the two-stage game is thoroughly assessed and numerical results are provided on the ""qualityâ of such equilibria.",ilaria malanchini,congestion games,2013.0,10.1109/TMC.2012.207,IEEE Transactions on Mobile Computing,Malanchini2013,False,,IEEE,Not available,Network Selection and Resource Allocation Games for Wireless Access Networks,2afd935f8a424d9998febbaaf4532fd0,https://ieeexplore.ieee.org/document/6320552/
1756,"Wireless access networks are often characterized by the interaction of different end users, communication technologies, and network operators. This paper analyzes the dynamics among these ""actorsâ by focusing on the processes of wireless network selection, where end users may choose among multiple available access networks to get connectivity, and resource allocation, where network operators may set their radio resources to provide connectivity. The interaction among end users is modeled as a noncooperative congestion game, where players (end users) selfishly select the access network that minimizes their perceived selection cost. A method based on mathematical programming is proposed to find Nash equilibria and characterize their optimality under three cost functions, which are representative of different technological scenarios. System level simulations are then used to evaluate the actual throughput and fairness of the equilibrium points. The interaction among end users and network operators is then assessed through a two-stage multileader/multifollower game, where network operators (leaders) play in the first stage by properly setting the radio resources to maximize their users, and end users (followers) play in the second stage the aforementioned network selection game. The existence of exact and approximated subgame perfect Nash equilibria of the two-stage game is thoroughly assessed and numerical results are provided on the ""qualityâ of such equilibria.",ilaria malanchini,price-of-stability,2013.0,10.1109/TMC.2012.207,IEEE Transactions on Mobile Computing,Malanchini2013,False,,IEEE,Not available,Network Selection and Resource Allocation Games for Wireless Access Networks,2afd935f8a424d9998febbaaf4532fd0,https://ieeexplore.ieee.org/document/6320552/
1757,"Wireless access networks are often characterized by the interaction of different end users, communication technologies, and network operators. This paper analyzes the dynamics among these ""actorsâ by focusing on the processes of wireless network selection, where end users may choose among multiple available access networks to get connectivity, and resource allocation, where network operators may set their radio resources to provide connectivity. The interaction among end users is modeled as a noncooperative congestion game, where players (end users) selfishly select the access network that minimizes their perceived selection cost. A method based on mathematical programming is proposed to find Nash equilibria and characterize their optimality under three cost functions, which are representative of different technological scenarios. System level simulations are then used to evaluate the actual throughput and fairness of the equilibrium points. The interaction among end users and network operators is then assessed through a two-stage multileader/multifollower game, where network operators (leaders) play in the first stage by properly setting the radio resources to maximize their users, and end users (followers) play in the second stage the aforementioned network selection game. The existence of exact and approximated subgame perfect Nash equilibria of the two-stage game is thoroughly assessed and numerical results are provided on the ""qualityâ of such equilibria.",ilaria malanchini,price-of-anarchy,2013.0,10.1109/TMC.2012.207,IEEE Transactions on Mobile Computing,Malanchini2013,False,,IEEE,Not available,Network Selection and Resource Allocation Games for Wireless Access Networks,2afd935f8a424d9998febbaaf4532fd0,https://ieeexplore.ieee.org/document/6320552/
1758,"Wireless access networks are often characterized by the interaction of different end users, communication technologies, and network operators. This paper analyzes the dynamics among these ""actorsâ by focusing on the processes of wireless network selection, where end users may choose among multiple available access networks to get connectivity, and resource allocation, where network operators may set their radio resources to provide connectivity. The interaction among end users is modeled as a noncooperative congestion game, where players (end users) selfishly select the access network that minimizes their perceived selection cost. A method based on mathematical programming is proposed to find Nash equilibria and characterize their optimality under three cost functions, which are representative of different technological scenarios. System level simulations are then used to evaluate the actual throughput and fairness of the equilibrium points. The interaction among end users and network operators is then assessed through a two-stage multileader/multifollower game, where network operators (leaders) play in the first stage by properly setting the radio resources to maximize their users, and end users (followers) play in the second stage the aforementioned network selection game. The existence of exact and approximated subgame perfect Nash equilibria of the two-stage game is thoroughly assessed and numerical results are provided on the ""qualityâ of such equilibria.",matteo cesana,Wireless access networks,2013.0,10.1109/TMC.2012.207,IEEE Transactions on Mobile Computing,Malanchini2013,False,,IEEE,Not available,Network Selection and Resource Allocation Games for Wireless Access Networks,2afd935f8a424d9998febbaaf4532fd0,https://ieeexplore.ieee.org/document/6320552/
1759,"Wireless access networks are often characterized by the interaction of different end users, communication technologies, and network operators. This paper analyzes the dynamics among these ""actorsâ by focusing on the processes of wireless network selection, where end users may choose among multiple available access networks to get connectivity, and resource allocation, where network operators may set their radio resources to provide connectivity. The interaction among end users is modeled as a noncooperative congestion game, where players (end users) selfishly select the access network that minimizes their perceived selection cost. A method based on mathematical programming is proposed to find Nash equilibria and characterize their optimality under three cost functions, which are representative of different technological scenarios. System level simulations are then used to evaluate the actual throughput and fairness of the equilibrium points. The interaction among end users and network operators is then assessed through a two-stage multileader/multifollower game, where network operators (leaders) play in the first stage by properly setting the radio resources to maximize their users, and end users (followers) play in the second stage the aforementioned network selection game. The existence of exact and approximated subgame perfect Nash equilibria of the two-stage game is thoroughly assessed and numerical results are provided on the ""qualityâ of such equilibria.",matteo cesana,network selection,2013.0,10.1109/TMC.2012.207,IEEE Transactions on Mobile Computing,Malanchini2013,False,,IEEE,Not available,Network Selection and Resource Allocation Games for Wireless Access Networks,2afd935f8a424d9998febbaaf4532fd0,https://ieeexplore.ieee.org/document/6320552/
1760,"Wireless access networks are often characterized by the interaction of different end users, communication technologies, and network operators. This paper analyzes the dynamics among these ""actorsâ by focusing on the processes of wireless network selection, where end users may choose among multiple available access networks to get connectivity, and resource allocation, where network operators may set their radio resources to provide connectivity. The interaction among end users is modeled as a noncooperative congestion game, where players (end users) selfishly select the access network that minimizes their perceived selection cost. A method based on mathematical programming is proposed to find Nash equilibria and characterize their optimality under three cost functions, which are representative of different technological scenarios. System level simulations are then used to evaluate the actual throughput and fairness of the equilibrium points. The interaction among end users and network operators is then assessed through a two-stage multileader/multifollower game, where network operators (leaders) play in the first stage by properly setting the radio resources to maximize their users, and end users (followers) play in the second stage the aforementioned network selection game. The existence of exact and approximated subgame perfect Nash equilibria of the two-stage game is thoroughly assessed and numerical results are provided on the ""qualityâ of such equilibria.",matteo cesana,congestion games,2013.0,10.1109/TMC.2012.207,IEEE Transactions on Mobile Computing,Malanchini2013,False,,IEEE,Not available,Network Selection and Resource Allocation Games for Wireless Access Networks,2afd935f8a424d9998febbaaf4532fd0,https://ieeexplore.ieee.org/document/6320552/
1761,"Wireless access networks are often characterized by the interaction of different end users, communication technologies, and network operators. This paper analyzes the dynamics among these ""actorsâ by focusing on the processes of wireless network selection, where end users may choose among multiple available access networks to get connectivity, and resource allocation, where network operators may set their radio resources to provide connectivity. The interaction among end users is modeled as a noncooperative congestion game, where players (end users) selfishly select the access network that minimizes their perceived selection cost. A method based on mathematical programming is proposed to find Nash equilibria and characterize their optimality under three cost functions, which are representative of different technological scenarios. System level simulations are then used to evaluate the actual throughput and fairness of the equilibrium points. The interaction among end users and network operators is then assessed through a two-stage multileader/multifollower game, where network operators (leaders) play in the first stage by properly setting the radio resources to maximize their users, and end users (followers) play in the second stage the aforementioned network selection game. The existence of exact and approximated subgame perfect Nash equilibria of the two-stage game is thoroughly assessed and numerical results are provided on the ""qualityâ of such equilibria.",matteo cesana,price-of-stability,2013.0,10.1109/TMC.2012.207,IEEE Transactions on Mobile Computing,Malanchini2013,False,,IEEE,Not available,Network Selection and Resource Allocation Games for Wireless Access Networks,2afd935f8a424d9998febbaaf4532fd0,https://ieeexplore.ieee.org/document/6320552/
1762,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
1763,"Wireless access networks are often characterized by the interaction of different end users, communication technologies, and network operators. This paper analyzes the dynamics among these ""actorsâ by focusing on the processes of wireless network selection, where end users may choose among multiple available access networks to get connectivity, and resource allocation, where network operators may set their radio resources to provide connectivity. The interaction among end users is modeled as a noncooperative congestion game, where players (end users) selfishly select the access network that minimizes their perceived selection cost. A method based on mathematical programming is proposed to find Nash equilibria and characterize their optimality under three cost functions, which are representative of different technological scenarios. System level simulations are then used to evaluate the actual throughput and fairness of the equilibrium points. The interaction among end users and network operators is then assessed through a two-stage multileader/multifollower game, where network operators (leaders) play in the first stage by properly setting the radio resources to maximize their users, and end users (followers) play in the second stage the aforementioned network selection game. The existence of exact and approximated subgame perfect Nash equilibria of the two-stage game is thoroughly assessed and numerical results are provided on the ""qualityâ of such equilibria.",matteo cesana,price-of-anarchy,2013.0,10.1109/TMC.2012.207,IEEE Transactions on Mobile Computing,Malanchini2013,False,,IEEE,Not available,Network Selection and Resource Allocation Games for Wireless Access Networks,2afd935f8a424d9998febbaaf4532fd0,https://ieeexplore.ieee.org/document/6320552/
1764,"Wireless access networks are often characterized by the interaction of different end users, communication technologies, and network operators. This paper analyzes the dynamics among these ""actorsâ by focusing on the processes of wireless network selection, where end users may choose among multiple available access networks to get connectivity, and resource allocation, where network operators may set their radio resources to provide connectivity. The interaction among end users is modeled as a noncooperative congestion game, where players (end users) selfishly select the access network that minimizes their perceived selection cost. A method based on mathematical programming is proposed to find Nash equilibria and characterize their optimality under three cost functions, which are representative of different technological scenarios. System level simulations are then used to evaluate the actual throughput and fairness of the equilibrium points. The interaction among end users and network operators is then assessed through a two-stage multileader/multifollower game, where network operators (leaders) play in the first stage by properly setting the radio resources to maximize their users, and end users (followers) play in the second stage the aforementioned network selection game. The existence of exact and approximated subgame perfect Nash equilibria of the two-stage game is thoroughly assessed and numerical results are provided on the ""qualityâ of such equilibria.",nicola gatti,Wireless access networks,2013.0,10.1109/TMC.2012.207,IEEE Transactions on Mobile Computing,Malanchini2013,False,,IEEE,Not available,Network Selection and Resource Allocation Games for Wireless Access Networks,2afd935f8a424d9998febbaaf4532fd0,https://ieeexplore.ieee.org/document/6320552/
1765,"Wireless access networks are often characterized by the interaction of different end users, communication technologies, and network operators. This paper analyzes the dynamics among these ""actorsâ by focusing on the processes of wireless network selection, where end users may choose among multiple available access networks to get connectivity, and resource allocation, where network operators may set their radio resources to provide connectivity. The interaction among end users is modeled as a noncooperative congestion game, where players (end users) selfishly select the access network that minimizes their perceived selection cost. A method based on mathematical programming is proposed to find Nash equilibria and characterize their optimality under three cost functions, which are representative of different technological scenarios. System level simulations are then used to evaluate the actual throughput and fairness of the equilibrium points. The interaction among end users and network operators is then assessed through a two-stage multileader/multifollower game, where network operators (leaders) play in the first stage by properly setting the radio resources to maximize their users, and end users (followers) play in the second stage the aforementioned network selection game. The existence of exact and approximated subgame perfect Nash equilibria of the two-stage game is thoroughly assessed and numerical results are provided on the ""qualityâ of such equilibria.",nicola gatti,network selection,2013.0,10.1109/TMC.2012.207,IEEE Transactions on Mobile Computing,Malanchini2013,False,,IEEE,Not available,Network Selection and Resource Allocation Games for Wireless Access Networks,2afd935f8a424d9998febbaaf4532fd0,https://ieeexplore.ieee.org/document/6320552/
1766,"Wireless access networks are often characterized by the interaction of different end users, communication technologies, and network operators. This paper analyzes the dynamics among these ""actorsâ by focusing on the processes of wireless network selection, where end users may choose among multiple available access networks to get connectivity, and resource allocation, where network operators may set their radio resources to provide connectivity. The interaction among end users is modeled as a noncooperative congestion game, where players (end users) selfishly select the access network that minimizes their perceived selection cost. A method based on mathematical programming is proposed to find Nash equilibria and characterize their optimality under three cost functions, which are representative of different technological scenarios. System level simulations are then used to evaluate the actual throughput and fairness of the equilibrium points. The interaction among end users and network operators is then assessed through a two-stage multileader/multifollower game, where network operators (leaders) play in the first stage by properly setting the radio resources to maximize their users, and end users (followers) play in the second stage the aforementioned network selection game. The existence of exact and approximated subgame perfect Nash equilibria of the two-stage game is thoroughly assessed and numerical results are provided on the ""qualityâ of such equilibria.",nicola gatti,congestion games,2013.0,10.1109/TMC.2012.207,IEEE Transactions on Mobile Computing,Malanchini2013,False,,IEEE,Not available,Network Selection and Resource Allocation Games for Wireless Access Networks,2afd935f8a424d9998febbaaf4532fd0,https://ieeexplore.ieee.org/document/6320552/
1767,"Wireless access networks are often characterized by the interaction of different end users, communication technologies, and network operators. This paper analyzes the dynamics among these ""actorsâ by focusing on the processes of wireless network selection, where end users may choose among multiple available access networks to get connectivity, and resource allocation, where network operators may set their radio resources to provide connectivity. The interaction among end users is modeled as a noncooperative congestion game, where players (end users) selfishly select the access network that minimizes their perceived selection cost. A method based on mathematical programming is proposed to find Nash equilibria and characterize their optimality under three cost functions, which are representative of different technological scenarios. System level simulations are then used to evaluate the actual throughput and fairness of the equilibrium points. The interaction among end users and network operators is then assessed through a two-stage multileader/multifollower game, where network operators (leaders) play in the first stage by properly setting the radio resources to maximize their users, and end users (followers) play in the second stage the aforementioned network selection game. The existence of exact and approximated subgame perfect Nash equilibria of the two-stage game is thoroughly assessed and numerical results are provided on the ""qualityâ of such equilibria.",nicola gatti,price-of-stability,2013.0,10.1109/TMC.2012.207,IEEE Transactions on Mobile Computing,Malanchini2013,False,,IEEE,Not available,Network Selection and Resource Allocation Games for Wireless Access Networks,2afd935f8a424d9998febbaaf4532fd0,https://ieeexplore.ieee.org/document/6320552/
1768,"Wireless access networks are often characterized by the interaction of different end users, communication technologies, and network operators. This paper analyzes the dynamics among these ""actorsâ by focusing on the processes of wireless network selection, where end users may choose among multiple available access networks to get connectivity, and resource allocation, where network operators may set their radio resources to provide connectivity. The interaction among end users is modeled as a noncooperative congestion game, where players (end users) selfishly select the access network that minimizes their perceived selection cost. A method based on mathematical programming is proposed to find Nash equilibria and characterize their optimality under three cost functions, which are representative of different technological scenarios. System level simulations are then used to evaluate the actual throughput and fairness of the equilibrium points. The interaction among end users and network operators is then assessed through a two-stage multileader/multifollower game, where network operators (leaders) play in the first stage by properly setting the radio resources to maximize their users, and end users (followers) play in the second stage the aforementioned network selection game. The existence of exact and approximated subgame perfect Nash equilibria of the two-stage game is thoroughly assessed and numerical results are provided on the ""qualityâ of such equilibria.",nicola gatti,price-of-anarchy,2013.0,10.1109/TMC.2012.207,IEEE Transactions on Mobile Computing,Malanchini2013,False,,IEEE,Not available,Network Selection and Resource Allocation Games for Wireless Access Networks,2afd935f8a424d9998febbaaf4532fd0,https://ieeexplore.ieee.org/document/6320552/
1769,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",maria-florina balcan,Games,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
1770,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",maria-florina balcan,Couplings,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
1771,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",maria-florina balcan,Vectors,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
1772,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",maria-florina balcan,Convergence,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
1773,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
1774,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",maria-florina balcan,Delay,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
1775,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",maria-florina balcan,Nash equilibrium,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
1776,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",maria-florina balcan,Internet,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
1777,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",florin constantin,Games,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
1778,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",florin constantin,Couplings,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
1779,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",florin constantin,Vectors,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
1780,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",florin constantin,Convergence,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
1781,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",florin constantin,Delay,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
1782,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",florin constantin,Nash equilibrium,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
1783,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",florin constantin,Internet,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
1784,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
1785,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",georgios piliouras,Games,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
1786,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",georgios piliouras,Couplings,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
1787,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",georgios piliouras,Vectors,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
1788,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",georgios piliouras,Convergence,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
1789,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",georgios piliouras,Delay,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
1790,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",georgios piliouras,Nash equilibrium,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
1791,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",georgios piliouras,Internet,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
1792,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",jeff shamma,Games,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
1793,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",jeff shamma,Couplings,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
1794,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",jeff shamma,Vectors,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
1795,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
1796,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",jeff shamma,Convergence,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
1797,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",jeff shamma,Delay,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
1798,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",jeff shamma,Nash equilibrium,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
1799,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",jeff shamma,Internet,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
1800,"A game-theoretic framework is introduced for studying selfish user behavior in shared wireless networks. The investigation treats an n-unicast problem in a wireless network that employs a restricted form of network coding called reverse carpooling. Unicast sessions independently choose routes through the network. The cost of a set of unicast routes is the number of wireless transmissions required to establish those connections using those routes. Game theory is employed as a tool for analyzing the impact of cost sharing mechanisms on the global system performance when each unicast independently and selfishly chooses its route to minimize its individual cost. The investigation focuses on the performance of stable solutions, where a stable solution is one in which no single unicast can improve its individual cost by changing its route. The results include bounds on the best- and worst-case stable solutions compared to the best performance that could be found and implemented using a centralized controller. The optimal cost sharing protocol is derived and the worst-case solution is bounded. That worst-case stable performance cannot be improved using cost-sharing protocols that are independent of the network structure.",jason marden,Distributed control,2012.0,10.1109/TIT.2011.2177576,IEEE Transactions on Information Theory,Marden2012,False,,IEEE,Not available,The Price of Selfishness in Network Coding,5ae3c064fa4491cfb349ff133bfb3d5a,https://ieeexplore.ieee.org/document/6169190/
1801,"A game-theoretic framework is introduced for studying selfish user behavior in shared wireless networks. The investigation treats an n-unicast problem in a wireless network that employs a restricted form of network coding called reverse carpooling. Unicast sessions independently choose routes through the network. The cost of a set of unicast routes is the number of wireless transmissions required to establish those connections using those routes. Game theory is employed as a tool for analyzing the impact of cost sharing mechanisms on the global system performance when each unicast independently and selfishly chooses its route to minimize its individual cost. The investigation focuses on the performance of stable solutions, where a stable solution is one in which no single unicast can improve its individual cost by changing its route. The results include bounds on the best- and worst-case stable solutions compared to the best performance that could be found and implemented using a centralized controller. The optimal cost sharing protocol is derived and the worst-case solution is bounded. That worst-case stable performance cannot be improved using cost-sharing protocols that are independent of the network structure.",jason marden,game theory,2012.0,10.1109/TIT.2011.2177576,IEEE Transactions on Information Theory,Marden2012,False,,IEEE,Not available,The Price of Selfishness in Network Coding,5ae3c064fa4491cfb349ff133bfb3d5a,https://ieeexplore.ieee.org/document/6169190/
1802,"A game-theoretic framework is introduced for studying selfish user behavior in shared wireless networks. The investigation treats an n-unicast problem in a wireless network that employs a restricted form of network coding called reverse carpooling. Unicast sessions independently choose routes through the network. The cost of a set of unicast routes is the number of wireless transmissions required to establish those connections using those routes. Game theory is employed as a tool for analyzing the impact of cost sharing mechanisms on the global system performance when each unicast independently and selfishly chooses its route to minimize its individual cost. The investigation focuses on the performance of stable solutions, where a stable solution is one in which no single unicast can improve its individual cost by changing its route. The results include bounds on the best- and worst-case stable solutions compared to the best performance that could be found and implemented using a centralized controller. The optimal cost sharing protocol is derived and the worst-case solution is bounded. That worst-case stable performance cannot be improved using cost-sharing protocols that are independent of the network structure.",jason marden,network coding,2012.0,10.1109/TIT.2011.2177576,IEEE Transactions on Information Theory,Marden2012,False,,IEEE,Not available,The Price of Selfishness in Network Coding,5ae3c064fa4491cfb349ff133bfb3d5a,https://ieeexplore.ieee.org/document/6169190/
1803,"A game-theoretic framework is introduced for studying selfish user behavior in shared wireless networks. The investigation treats an n-unicast problem in a wireless network that employs a restricted form of network coding called reverse carpooling. Unicast sessions independently choose routes through the network. The cost of a set of unicast routes is the number of wireless transmissions required to establish those connections using those routes. Game theory is employed as a tool for analyzing the impact of cost sharing mechanisms on the global system performance when each unicast independently and selfishly chooses its route to minimize its individual cost. The investigation focuses on the performance of stable solutions, where a stable solution is one in which no single unicast can improve its individual cost by changing its route. The results include bounds on the best- and worst-case stable solutions compared to the best performance that could be found and implemented using a centralized controller. The optimal cost sharing protocol is derived and the worst-case solution is bounded. That worst-case stable performance cannot be improved using cost-sharing protocols that are independent of the network structure.",jason marden,price of anarchy (PoA),2012.0,10.1109/TIT.2011.2177576,IEEE Transactions on Information Theory,Marden2012,False,,IEEE,Not available,The Price of Selfishness in Network Coding,5ae3c064fa4491cfb349ff133bfb3d5a,https://ieeexplore.ieee.org/document/6169190/
1804,"A game-theoretic framework is introduced for studying selfish user behavior in shared wireless networks. The investigation treats an n-unicast problem in a wireless network that employs a restricted form of network coding called reverse carpooling. Unicast sessions independently choose routes through the network. The cost of a set of unicast routes is the number of wireless transmissions required to establish those connections using those routes. Game theory is employed as a tool for analyzing the impact of cost sharing mechanisms on the global system performance when each unicast independently and selfishly chooses its route to minimize its individual cost. The investigation focuses on the performance of stable solutions, where a stable solution is one in which no single unicast can improve its individual cost by changing its route. The results include bounds on the best- and worst-case stable solutions compared to the best performance that could be found and implemented using a centralized controller. The optimal cost sharing protocol is derived and the worst-case solution is bounded. That worst-case stable performance cannot be improved using cost-sharing protocols that are independent of the network structure.",jason marden,reverse carpooling,2012.0,10.1109/TIT.2011.2177576,IEEE Transactions on Information Theory,Marden2012,False,,IEEE,Not available,The Price of Selfishness in Network Coding,5ae3c064fa4491cfb349ff133bfb3d5a,https://ieeexplore.ieee.org/document/6169190/
1805,"A game-theoretic framework is introduced for studying selfish user behavior in shared wireless networks. The investigation treats an n-unicast problem in a wireless network that employs a restricted form of network coding called reverse carpooling. Unicast sessions independently choose routes through the network. The cost of a set of unicast routes is the number of wireless transmissions required to establish those connections using those routes. Game theory is employed as a tool for analyzing the impact of cost sharing mechanisms on the global system performance when each unicast independently and selfishly chooses its route to minimize its individual cost. The investigation focuses on the performance of stable solutions, where a stable solution is one in which no single unicast can improve its individual cost by changing its route. The results include bounds on the best- and worst-case stable solutions compared to the best performance that could be found and implemented using a centralized controller. The optimal cost sharing protocol is derived and the worst-case solution is bounded. That worst-case stable performance cannot be improved using cost-sharing protocols that are independent of the network structure.",michelle effros,Distributed control,2012.0,10.1109/TIT.2011.2177576,IEEE Transactions on Information Theory,Marden2012,False,,IEEE,Not available,The Price of Selfishness in Network Coding,5ae3c064fa4491cfb349ff133bfb3d5a,https://ieeexplore.ieee.org/document/6169190/
1806,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
1807,"A game-theoretic framework is introduced for studying selfish user behavior in shared wireless networks. The investigation treats an n-unicast problem in a wireless network that employs a restricted form of network coding called reverse carpooling. Unicast sessions independently choose routes through the network. The cost of a set of unicast routes is the number of wireless transmissions required to establish those connections using those routes. Game theory is employed as a tool for analyzing the impact of cost sharing mechanisms on the global system performance when each unicast independently and selfishly chooses its route to minimize its individual cost. The investigation focuses on the performance of stable solutions, where a stable solution is one in which no single unicast can improve its individual cost by changing its route. The results include bounds on the best- and worst-case stable solutions compared to the best performance that could be found and implemented using a centralized controller. The optimal cost sharing protocol is derived and the worst-case solution is bounded. That worst-case stable performance cannot be improved using cost-sharing protocols that are independent of the network structure.",michelle effros,game theory,2012.0,10.1109/TIT.2011.2177576,IEEE Transactions on Information Theory,Marden2012,False,,IEEE,Not available,The Price of Selfishness in Network Coding,5ae3c064fa4491cfb349ff133bfb3d5a,https://ieeexplore.ieee.org/document/6169190/
1808,"A game-theoretic framework is introduced for studying selfish user behavior in shared wireless networks. The investigation treats an n-unicast problem in a wireless network that employs a restricted form of network coding called reverse carpooling. Unicast sessions independently choose routes through the network. The cost of a set of unicast routes is the number of wireless transmissions required to establish those connections using those routes. Game theory is employed as a tool for analyzing the impact of cost sharing mechanisms on the global system performance when each unicast independently and selfishly chooses its route to minimize its individual cost. The investigation focuses on the performance of stable solutions, where a stable solution is one in which no single unicast can improve its individual cost by changing its route. The results include bounds on the best- and worst-case stable solutions compared to the best performance that could be found and implemented using a centralized controller. The optimal cost sharing protocol is derived and the worst-case solution is bounded. That worst-case stable performance cannot be improved using cost-sharing protocols that are independent of the network structure.",michelle effros,network coding,2012.0,10.1109/TIT.2011.2177576,IEEE Transactions on Information Theory,Marden2012,False,,IEEE,Not available,The Price of Selfishness in Network Coding,5ae3c064fa4491cfb349ff133bfb3d5a,https://ieeexplore.ieee.org/document/6169190/
1809,"A game-theoretic framework is introduced for studying selfish user behavior in shared wireless networks. The investigation treats an n-unicast problem in a wireless network that employs a restricted form of network coding called reverse carpooling. Unicast sessions independently choose routes through the network. The cost of a set of unicast routes is the number of wireless transmissions required to establish those connections using those routes. Game theory is employed as a tool for analyzing the impact of cost sharing mechanisms on the global system performance when each unicast independently and selfishly chooses its route to minimize its individual cost. The investigation focuses on the performance of stable solutions, where a stable solution is one in which no single unicast can improve its individual cost by changing its route. The results include bounds on the best- and worst-case stable solutions compared to the best performance that could be found and implemented using a centralized controller. The optimal cost sharing protocol is derived and the worst-case solution is bounded. That worst-case stable performance cannot be improved using cost-sharing protocols that are independent of the network structure.",michelle effros,price of anarchy (PoA),2012.0,10.1109/TIT.2011.2177576,IEEE Transactions on Information Theory,Marden2012,False,,IEEE,Not available,The Price of Selfishness in Network Coding,5ae3c064fa4491cfb349ff133bfb3d5a,https://ieeexplore.ieee.org/document/6169190/
1810,"A game-theoretic framework is introduced for studying selfish user behavior in shared wireless networks. The investigation treats an n-unicast problem in a wireless network that employs a restricted form of network coding called reverse carpooling. Unicast sessions independently choose routes through the network. The cost of a set of unicast routes is the number of wireless transmissions required to establish those connections using those routes. Game theory is employed as a tool for analyzing the impact of cost sharing mechanisms on the global system performance when each unicast independently and selfishly chooses its route to minimize its individual cost. The investigation focuses on the performance of stable solutions, where a stable solution is one in which no single unicast can improve its individual cost by changing its route. The results include bounds on the best- and worst-case stable solutions compared to the best performance that could be found and implemented using a centralized controller. The optimal cost sharing protocol is derived and the worst-case solution is bounded. That worst-case stable performance cannot be improved using cost-sharing protocols that are independent of the network structure.",michelle effros,reverse carpooling,2012.0,10.1109/TIT.2011.2177576,IEEE Transactions on Information Theory,Marden2012,False,,IEEE,Not available,The Price of Selfishness in Network Coding,5ae3c064fa4491cfb349ff133bfb3d5a,https://ieeexplore.ieee.org/document/6169190/
1811,"In the decentralized networks, an important requirement arises in the design of Medium Access Control protocols is the robustness to self-interested behavior of the users. Indeed it's well known that the Medium Access Control protocols are designed based on the assumption that all mobile users act selfishly and follow a personal objective, such behavior may decrease the performance of the majority of users, hence causing fairness issue and decreasing the global energy consumption significantly. In this paper we propose a reward mechanism in a non-cooperative game framework. We assume that the base station promises the user a reward which can be a number of amounts of credit that the users use to transmit their own packets. The reward is given only to a user that transmits its packet successfully. First, we analyze the implementation of our mechanism on the equilibrium and show that as the arrival rate increases, the behavior of users become more and more aggressive resulting in a global deterioration of the expected reward the base station pays. Second and in order to achieve an efficient outcome despite the selfish behavior of users, we propose an incentive mechanism when each failure transmission of a packet incurs a certain number of costs. The cost could in fact be expressed in terms of the energy consumption when attempting to access the wireless channel. Under the proposed scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via the price of anarchy we show that the global performance of the system is improved considerably compared to the original game in particular at high loads.",moulay lmater,Wireless Networks,2015.0,10.1109/WINCOM.2015.7381303,2015 International Conference on Wireless Networks and Mobile Communications (WINCOM),Lmater2015,False,,IEEE,Not available,An efficient pricing mechanism of random access in wireless network with self-interested mobile users,0abf002fd892b61c3b904d03fc474daa,https://ieeexplore.ieee.org/document/7381303/
1812,"In the decentralized networks, an important requirement arises in the design of Medium Access Control protocols is the robustness to self-interested behavior of the users. Indeed it's well known that the Medium Access Control protocols are designed based on the assumption that all mobile users act selfishly and follow a personal objective, such behavior may decrease the performance of the majority of users, hence causing fairness issue and decreasing the global energy consumption significantly. In this paper we propose a reward mechanism in a non-cooperative game framework. We assume that the base station promises the user a reward which can be a number of amounts of credit that the users use to transmit their own packets. The reward is given only to a user that transmits its packet successfully. First, we analyze the implementation of our mechanism on the equilibrium and show that as the arrival rate increases, the behavior of users become more and more aggressive resulting in a global deterioration of the expected reward the base station pays. Second and in order to achieve an efficient outcome despite the selfish behavior of users, we propose an incentive mechanism when each failure transmission of a packet incurs a certain number of costs. The cost could in fact be expressed in terms of the energy consumption when attempting to access the wireless channel. Under the proposed scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via the price of anarchy we show that the global performance of the system is improved considerably compared to the original game in particular at high loads.",moulay lmater,Wireless Random Access Protocol,2015.0,10.1109/WINCOM.2015.7381303,2015 International Conference on Wireless Networks and Mobile Communications (WINCOM),Lmater2015,False,,IEEE,Not available,An efficient pricing mechanism of random access in wireless network with self-interested mobile users,0abf002fd892b61c3b904d03fc474daa,https://ieeexplore.ieee.org/document/7381303/
1813,"In the decentralized networks, an important requirement arises in the design of Medium Access Control protocols is the robustness to self-interested behavior of the users. Indeed it's well known that the Medium Access Control protocols are designed based on the assumption that all mobile users act selfishly and follow a personal objective, such behavior may decrease the performance of the majority of users, hence causing fairness issue and decreasing the global energy consumption significantly. In this paper we propose a reward mechanism in a non-cooperative game framework. We assume that the base station promises the user a reward which can be a number of amounts of credit that the users use to transmit their own packets. The reward is given only to a user that transmits its packet successfully. First, we analyze the implementation of our mechanism on the equilibrium and show that as the arrival rate increases, the behavior of users become more and more aggressive resulting in a global deterioration of the expected reward the base station pays. Second and in order to achieve an efficient outcome despite the selfish behavior of users, we propose an incentive mechanism when each failure transmission of a packet incurs a certain number of costs. The cost could in fact be expressed in terms of the energy consumption when attempting to access the wireless channel. Under the proposed scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via the price of anarchy we show that the global performance of the system is improved considerably compared to the original game in particular at high loads.",moulay lmater,MAC Layer,2015.0,10.1109/WINCOM.2015.7381303,2015 International Conference on Wireless Networks and Mobile Communications (WINCOM),Lmater2015,False,,IEEE,Not available,An efficient pricing mechanism of random access in wireless network with self-interested mobile users,0abf002fd892b61c3b904d03fc474daa,https://ieeexplore.ieee.org/document/7381303/
1814,"In the decentralized networks, an important requirement arises in the design of Medium Access Control protocols is the robustness to self-interested behavior of the users. Indeed it's well known that the Medium Access Control protocols are designed based on the assumption that all mobile users act selfishly and follow a personal objective, such behavior may decrease the performance of the majority of users, hence causing fairness issue and decreasing the global energy consumption significantly. In this paper we propose a reward mechanism in a non-cooperative game framework. We assume that the base station promises the user a reward which can be a number of amounts of credit that the users use to transmit their own packets. The reward is given only to a user that transmits its packet successfully. First, we analyze the implementation of our mechanism on the equilibrium and show that as the arrival rate increases, the behavior of users become more and more aggressive resulting in a global deterioration of the expected reward the base station pays. Second and in order to achieve an efficient outcome despite the selfish behavior of users, we propose an incentive mechanism when each failure transmission of a packet incurs a certain number of costs. The cost could in fact be expressed in terms of the energy consumption when attempting to access the wireless channel. Under the proposed scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via the price of anarchy we show that the global performance of the system is improved considerably compared to the original game in particular at high loads.",moulay lmater,Markov Chains,2015.0,10.1109/WINCOM.2015.7381303,2015 International Conference on Wireless Networks and Mobile Communications (WINCOM),Lmater2015,False,,IEEE,Not available,An efficient pricing mechanism of random access in wireless network with self-interested mobile users,0abf002fd892b61c3b904d03fc474daa,https://ieeexplore.ieee.org/document/7381303/
1815,"In the decentralized networks, an important requirement arises in the design of Medium Access Control protocols is the robustness to self-interested behavior of the users. Indeed it's well known that the Medium Access Control protocols are designed based on the assumption that all mobile users act selfishly and follow a personal objective, such behavior may decrease the performance of the majority of users, hence causing fairness issue and decreasing the global energy consumption significantly. In this paper we propose a reward mechanism in a non-cooperative game framework. We assume that the base station promises the user a reward which can be a number of amounts of credit that the users use to transmit their own packets. The reward is given only to a user that transmits its packet successfully. First, we analyze the implementation of our mechanism on the equilibrium and show that as the arrival rate increases, the behavior of users become more and more aggressive resulting in a global deterioration of the expected reward the base station pays. Second and in order to achieve an efficient outcome despite the selfish behavior of users, we propose an incentive mechanism when each failure transmission of a packet incurs a certain number of costs. The cost could in fact be expressed in terms of the energy consumption when attempting to access the wireless channel. Under the proposed scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via the price of anarchy we show that the global performance of the system is improved considerably compared to the original game in particular at high loads.",moulay lmater,Game Theory,2015.0,10.1109/WINCOM.2015.7381303,2015 International Conference on Wireless Networks and Mobile Communications (WINCOM),Lmater2015,False,,IEEE,Not available,An efficient pricing mechanism of random access in wireless network with self-interested mobile users,0abf002fd892b61c3b904d03fc474daa,https://ieeexplore.ieee.org/document/7381303/
1816,"In the decentralized networks, an important requirement arises in the design of Medium Access Control protocols is the robustness to self-interested behavior of the users. Indeed it's well known that the Medium Access Control protocols are designed based on the assumption that all mobile users act selfishly and follow a personal objective, such behavior may decrease the performance of the majority of users, hence causing fairness issue and decreasing the global energy consumption significantly. In this paper we propose a reward mechanism in a non-cooperative game framework. We assume that the base station promises the user a reward which can be a number of amounts of credit that the users use to transmit their own packets. The reward is given only to a user that transmits its packet successfully. First, we analyze the implementation of our mechanism on the equilibrium and show that as the arrival rate increases, the behavior of users become more and more aggressive resulting in a global deterioration of the expected reward the base station pays. Second and in order to achieve an efficient outcome despite the selfish behavior of users, we propose an incentive mechanism when each failure transmission of a packet incurs a certain number of costs. The cost could in fact be expressed in terms of the energy consumption when attempting to access the wireless channel. Under the proposed scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via the price of anarchy we show that the global performance of the system is improved considerably compared to the original game in particular at high loads.",moulay lmater,Nash Equilibrium,2015.0,10.1109/WINCOM.2015.7381303,2015 International Conference on Wireless Networks and Mobile Communications (WINCOM),Lmater2015,False,,IEEE,Not available,An efficient pricing mechanism of random access in wireless network with self-interested mobile users,0abf002fd892b61c3b904d03fc474daa,https://ieeexplore.ieee.org/document/7381303/
1817,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
1818,"In the decentralized networks, an important requirement arises in the design of Medium Access Control protocols is the robustness to self-interested behavior of the users. Indeed it's well known that the Medium Access Control protocols are designed based on the assumption that all mobile users act selfishly and follow a personal objective, such behavior may decrease the performance of the majority of users, hence causing fairness issue and decreasing the global energy consumption significantly. In this paper we propose a reward mechanism in a non-cooperative game framework. We assume that the base station promises the user a reward which can be a number of amounts of credit that the users use to transmit their own packets. The reward is given only to a user that transmits its packet successfully. First, we analyze the implementation of our mechanism on the equilibrium and show that as the arrival rate increases, the behavior of users become more and more aggressive resulting in a global deterioration of the expected reward the base station pays. Second and in order to achieve an efficient outcome despite the selfish behavior of users, we propose an incentive mechanism when each failure transmission of a packet incurs a certain number of costs. The cost could in fact be expressed in terms of the energy consumption when attempting to access the wireless channel. Under the proposed scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via the price of anarchy we show that the global performance of the system is improved considerably compared to the original game in particular at high loads.",abdelillah karouit,Wireless Networks,2015.0,10.1109/WINCOM.2015.7381303,2015 International Conference on Wireless Networks and Mobile Communications (WINCOM),Lmater2015,False,,IEEE,Not available,An efficient pricing mechanism of random access in wireless network with self-interested mobile users,0abf002fd892b61c3b904d03fc474daa,https://ieeexplore.ieee.org/document/7381303/
1819,"In the decentralized networks, an important requirement arises in the design of Medium Access Control protocols is the robustness to self-interested behavior of the users. Indeed it's well known that the Medium Access Control protocols are designed based on the assumption that all mobile users act selfishly and follow a personal objective, such behavior may decrease the performance of the majority of users, hence causing fairness issue and decreasing the global energy consumption significantly. In this paper we propose a reward mechanism in a non-cooperative game framework. We assume that the base station promises the user a reward which can be a number of amounts of credit that the users use to transmit their own packets. The reward is given only to a user that transmits its packet successfully. First, we analyze the implementation of our mechanism on the equilibrium and show that as the arrival rate increases, the behavior of users become more and more aggressive resulting in a global deterioration of the expected reward the base station pays. Second and in order to achieve an efficient outcome despite the selfish behavior of users, we propose an incentive mechanism when each failure transmission of a packet incurs a certain number of costs. The cost could in fact be expressed in terms of the energy consumption when attempting to access the wireless channel. Under the proposed scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via the price of anarchy we show that the global performance of the system is improved considerably compared to the original game in particular at high loads.",abdelillah karouit,Wireless Random Access Protocol,2015.0,10.1109/WINCOM.2015.7381303,2015 International Conference on Wireless Networks and Mobile Communications (WINCOM),Lmater2015,False,,IEEE,Not available,An efficient pricing mechanism of random access in wireless network with self-interested mobile users,0abf002fd892b61c3b904d03fc474daa,https://ieeexplore.ieee.org/document/7381303/
1820,"In the decentralized networks, an important requirement arises in the design of Medium Access Control protocols is the robustness to self-interested behavior of the users. Indeed it's well known that the Medium Access Control protocols are designed based on the assumption that all mobile users act selfishly and follow a personal objective, such behavior may decrease the performance of the majority of users, hence causing fairness issue and decreasing the global energy consumption significantly. In this paper we propose a reward mechanism in a non-cooperative game framework. We assume that the base station promises the user a reward which can be a number of amounts of credit that the users use to transmit their own packets. The reward is given only to a user that transmits its packet successfully. First, we analyze the implementation of our mechanism on the equilibrium and show that as the arrival rate increases, the behavior of users become more and more aggressive resulting in a global deterioration of the expected reward the base station pays. Second and in order to achieve an efficient outcome despite the selfish behavior of users, we propose an incentive mechanism when each failure transmission of a packet incurs a certain number of costs. The cost could in fact be expressed in terms of the energy consumption when attempting to access the wireless channel. Under the proposed scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via the price of anarchy we show that the global performance of the system is improved considerably compared to the original game in particular at high loads.",abdelillah karouit,MAC Layer,2015.0,10.1109/WINCOM.2015.7381303,2015 International Conference on Wireless Networks and Mobile Communications (WINCOM),Lmater2015,False,,IEEE,Not available,An efficient pricing mechanism of random access in wireless network with self-interested mobile users,0abf002fd892b61c3b904d03fc474daa,https://ieeexplore.ieee.org/document/7381303/
1821,"In the decentralized networks, an important requirement arises in the design of Medium Access Control protocols is the robustness to self-interested behavior of the users. Indeed it's well known that the Medium Access Control protocols are designed based on the assumption that all mobile users act selfishly and follow a personal objective, such behavior may decrease the performance of the majority of users, hence causing fairness issue and decreasing the global energy consumption significantly. In this paper we propose a reward mechanism in a non-cooperative game framework. We assume that the base station promises the user a reward which can be a number of amounts of credit that the users use to transmit their own packets. The reward is given only to a user that transmits its packet successfully. First, we analyze the implementation of our mechanism on the equilibrium and show that as the arrival rate increases, the behavior of users become more and more aggressive resulting in a global deterioration of the expected reward the base station pays. Second and in order to achieve an efficient outcome despite the selfish behavior of users, we propose an incentive mechanism when each failure transmission of a packet incurs a certain number of costs. The cost could in fact be expressed in terms of the energy consumption when attempting to access the wireless channel. Under the proposed scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via the price of anarchy we show that the global performance of the system is improved considerably compared to the original game in particular at high loads.",abdelillah karouit,Markov Chains,2015.0,10.1109/WINCOM.2015.7381303,2015 International Conference on Wireless Networks and Mobile Communications (WINCOM),Lmater2015,False,,IEEE,Not available,An efficient pricing mechanism of random access in wireless network with self-interested mobile users,0abf002fd892b61c3b904d03fc474daa,https://ieeexplore.ieee.org/document/7381303/
1822,"In the decentralized networks, an important requirement arises in the design of Medium Access Control protocols is the robustness to self-interested behavior of the users. Indeed it's well known that the Medium Access Control protocols are designed based on the assumption that all mobile users act selfishly and follow a personal objective, such behavior may decrease the performance of the majority of users, hence causing fairness issue and decreasing the global energy consumption significantly. In this paper we propose a reward mechanism in a non-cooperative game framework. We assume that the base station promises the user a reward which can be a number of amounts of credit that the users use to transmit their own packets. The reward is given only to a user that transmits its packet successfully. First, we analyze the implementation of our mechanism on the equilibrium and show that as the arrival rate increases, the behavior of users become more and more aggressive resulting in a global deterioration of the expected reward the base station pays. Second and in order to achieve an efficient outcome despite the selfish behavior of users, we propose an incentive mechanism when each failure transmission of a packet incurs a certain number of costs. The cost could in fact be expressed in terms of the energy consumption when attempting to access the wireless channel. Under the proposed scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via the price of anarchy we show that the global performance of the system is improved considerably compared to the original game in particular at high loads.",abdelillah karouit,Game Theory,2015.0,10.1109/WINCOM.2015.7381303,2015 International Conference on Wireless Networks and Mobile Communications (WINCOM),Lmater2015,False,,IEEE,Not available,An efficient pricing mechanism of random access in wireless network with self-interested mobile users,0abf002fd892b61c3b904d03fc474daa,https://ieeexplore.ieee.org/document/7381303/
1823,"In the decentralized networks, an important requirement arises in the design of Medium Access Control protocols is the robustness to self-interested behavior of the users. Indeed it's well known that the Medium Access Control protocols are designed based on the assumption that all mobile users act selfishly and follow a personal objective, such behavior may decrease the performance of the majority of users, hence causing fairness issue and decreasing the global energy consumption significantly. In this paper we propose a reward mechanism in a non-cooperative game framework. We assume that the base station promises the user a reward which can be a number of amounts of credit that the users use to transmit their own packets. The reward is given only to a user that transmits its packet successfully. First, we analyze the implementation of our mechanism on the equilibrium and show that as the arrival rate increases, the behavior of users become more and more aggressive resulting in a global deterioration of the expected reward the base station pays. Second and in order to achieve an efficient outcome despite the selfish behavior of users, we propose an incentive mechanism when each failure transmission of a packet incurs a certain number of costs. The cost could in fact be expressed in terms of the energy consumption when attempting to access the wireless channel. Under the proposed scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via the price of anarchy we show that the global performance of the system is improved considerably compared to the original game in particular at high loads.",abdelillah karouit,Nash Equilibrium,2015.0,10.1109/WINCOM.2015.7381303,2015 International Conference on Wireless Networks and Mobile Communications (WINCOM),Lmater2015,False,,IEEE,Not available,An efficient pricing mechanism of random access in wireless network with self-interested mobile users,0abf002fd892b61c3b904d03fc474daa,https://ieeexplore.ieee.org/document/7381303/
1824,"In the decentralized networks, an important requirement arises in the design of Medium Access Control protocols is the robustness to self-interested behavior of the users. Indeed it's well known that the Medium Access Control protocols are designed based on the assumption that all mobile users act selfishly and follow a personal objective, such behavior may decrease the performance of the majority of users, hence causing fairness issue and decreasing the global energy consumption significantly. In this paper we propose a reward mechanism in a non-cooperative game framework. We assume that the base station promises the user a reward which can be a number of amounts of credit that the users use to transmit their own packets. The reward is given only to a user that transmits its packet successfully. First, we analyze the implementation of our mechanism on the equilibrium and show that as the arrival rate increases, the behavior of users become more and more aggressive resulting in a global deterioration of the expected reward the base station pays. Second and in order to achieve an efficient outcome despite the selfish behavior of users, we propose an incentive mechanism when each failure transmission of a packet incurs a certain number of costs. The cost could in fact be expressed in terms of the energy consumption when attempting to access the wireless channel. Under the proposed scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via the price of anarchy we show that the global performance of the system is improved considerably compared to the original game in particular at high loads.",abdelkrim haqiq,Wireless Networks,2015.0,10.1109/WINCOM.2015.7381303,2015 International Conference on Wireless Networks and Mobile Communications (WINCOM),Lmater2015,False,,IEEE,Not available,An efficient pricing mechanism of random access in wireless network with self-interested mobile users,0abf002fd892b61c3b904d03fc474daa,https://ieeexplore.ieee.org/document/7381303/
1825,"In the decentralized networks, an important requirement arises in the design of Medium Access Control protocols is the robustness to self-interested behavior of the users. Indeed it's well known that the Medium Access Control protocols are designed based on the assumption that all mobile users act selfishly and follow a personal objective, such behavior may decrease the performance of the majority of users, hence causing fairness issue and decreasing the global energy consumption significantly. In this paper we propose a reward mechanism in a non-cooperative game framework. We assume that the base station promises the user a reward which can be a number of amounts of credit that the users use to transmit their own packets. The reward is given only to a user that transmits its packet successfully. First, we analyze the implementation of our mechanism on the equilibrium and show that as the arrival rate increases, the behavior of users become more and more aggressive resulting in a global deterioration of the expected reward the base station pays. Second and in order to achieve an efficient outcome despite the selfish behavior of users, we propose an incentive mechanism when each failure transmission of a packet incurs a certain number of costs. The cost could in fact be expressed in terms of the energy consumption when attempting to access the wireless channel. Under the proposed scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via the price of anarchy we show that the global performance of the system is improved considerably compared to the original game in particular at high loads.",abdelkrim haqiq,Wireless Random Access Protocol,2015.0,10.1109/WINCOM.2015.7381303,2015 International Conference on Wireless Networks and Mobile Communications (WINCOM),Lmater2015,False,,IEEE,Not available,An efficient pricing mechanism of random access in wireless network with self-interested mobile users,0abf002fd892b61c3b904d03fc474daa,https://ieeexplore.ieee.org/document/7381303/
1826,"In the decentralized networks, an important requirement arises in the design of Medium Access Control protocols is the robustness to self-interested behavior of the users. Indeed it's well known that the Medium Access Control protocols are designed based on the assumption that all mobile users act selfishly and follow a personal objective, such behavior may decrease the performance of the majority of users, hence causing fairness issue and decreasing the global energy consumption significantly. In this paper we propose a reward mechanism in a non-cooperative game framework. We assume that the base station promises the user a reward which can be a number of amounts of credit that the users use to transmit their own packets. The reward is given only to a user that transmits its packet successfully. First, we analyze the implementation of our mechanism on the equilibrium and show that as the arrival rate increases, the behavior of users become more and more aggressive resulting in a global deterioration of the expected reward the base station pays. Second and in order to achieve an efficient outcome despite the selfish behavior of users, we propose an incentive mechanism when each failure transmission of a packet incurs a certain number of costs. The cost could in fact be expressed in terms of the energy consumption when attempting to access the wireless channel. Under the proposed scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via the price of anarchy we show that the global performance of the system is improved considerably compared to the original game in particular at high loads.",abdelkrim haqiq,MAC Layer,2015.0,10.1109/WINCOM.2015.7381303,2015 International Conference on Wireless Networks and Mobile Communications (WINCOM),Lmater2015,False,,IEEE,Not available,An efficient pricing mechanism of random access in wireless network with self-interested mobile users,0abf002fd892b61c3b904d03fc474daa,https://ieeexplore.ieee.org/document/7381303/
1827,"In the decentralized networks, an important requirement arises in the design of Medium Access Control protocols is the robustness to self-interested behavior of the users. Indeed it's well known that the Medium Access Control protocols are designed based on the assumption that all mobile users act selfishly and follow a personal objective, such behavior may decrease the performance of the majority of users, hence causing fairness issue and decreasing the global energy consumption significantly. In this paper we propose a reward mechanism in a non-cooperative game framework. We assume that the base station promises the user a reward which can be a number of amounts of credit that the users use to transmit their own packets. The reward is given only to a user that transmits its packet successfully. First, we analyze the implementation of our mechanism on the equilibrium and show that as the arrival rate increases, the behavior of users become more and more aggressive resulting in a global deterioration of the expected reward the base station pays. Second and in order to achieve an efficient outcome despite the selfish behavior of users, we propose an incentive mechanism when each failure transmission of a packet incurs a certain number of costs. The cost could in fact be expressed in terms of the energy consumption when attempting to access the wireless channel. Under the proposed scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via the price of anarchy we show that the global performance of the system is improved considerably compared to the original game in particular at high loads.",abdelkrim haqiq,Markov Chains,2015.0,10.1109/WINCOM.2015.7381303,2015 International Conference on Wireless Networks and Mobile Communications (WINCOM),Lmater2015,False,,IEEE,Not available,An efficient pricing mechanism of random access in wireless network with self-interested mobile users,0abf002fd892b61c3b904d03fc474daa,https://ieeexplore.ieee.org/document/7381303/
1828,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
1829,"In the decentralized networks, an important requirement arises in the design of Medium Access Control protocols is the robustness to self-interested behavior of the users. Indeed it's well known that the Medium Access Control protocols are designed based on the assumption that all mobile users act selfishly and follow a personal objective, such behavior may decrease the performance of the majority of users, hence causing fairness issue and decreasing the global energy consumption significantly. In this paper we propose a reward mechanism in a non-cooperative game framework. We assume that the base station promises the user a reward which can be a number of amounts of credit that the users use to transmit their own packets. The reward is given only to a user that transmits its packet successfully. First, we analyze the implementation of our mechanism on the equilibrium and show that as the arrival rate increases, the behavior of users become more and more aggressive resulting in a global deterioration of the expected reward the base station pays. Second and in order to achieve an efficient outcome despite the selfish behavior of users, we propose an incentive mechanism when each failure transmission of a packet incurs a certain number of costs. The cost could in fact be expressed in terms of the energy consumption when attempting to access the wireless channel. Under the proposed scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via the price of anarchy we show that the global performance of the system is improved considerably compared to the original game in particular at high loads.",abdelkrim haqiq,Game Theory,2015.0,10.1109/WINCOM.2015.7381303,2015 International Conference on Wireless Networks and Mobile Communications (WINCOM),Lmater2015,False,,IEEE,Not available,An efficient pricing mechanism of random access in wireless network with self-interested mobile users,0abf002fd892b61c3b904d03fc474daa,https://ieeexplore.ieee.org/document/7381303/
1830,"In the decentralized networks, an important requirement arises in the design of Medium Access Control protocols is the robustness to self-interested behavior of the users. Indeed it's well known that the Medium Access Control protocols are designed based on the assumption that all mobile users act selfishly and follow a personal objective, such behavior may decrease the performance of the majority of users, hence causing fairness issue and decreasing the global energy consumption significantly. In this paper we propose a reward mechanism in a non-cooperative game framework. We assume that the base station promises the user a reward which can be a number of amounts of credit that the users use to transmit their own packets. The reward is given only to a user that transmits its packet successfully. First, we analyze the implementation of our mechanism on the equilibrium and show that as the arrival rate increases, the behavior of users become more and more aggressive resulting in a global deterioration of the expected reward the base station pays. Second and in order to achieve an efficient outcome despite the selfish behavior of users, we propose an incentive mechanism when each failure transmission of a packet incurs a certain number of costs. The cost could in fact be expressed in terms of the energy consumption when attempting to access the wireless channel. Under the proposed scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via the price of anarchy we show that the global performance of the system is improved considerably compared to the original game in particular at high loads.",abdelkrim haqiq,Nash Equilibrium,2015.0,10.1109/WINCOM.2015.7381303,2015 International Conference on Wireless Networks and Mobile Communications (WINCOM),Lmater2015,False,,IEEE,Not available,An efficient pricing mechanism of random access in wireless network with self-interested mobile users,0abf002fd892b61c3b904d03fc474daa,https://ieeexplore.ieee.org/document/7381303/
1831,"This paper focuses on the design of local agent objective functions for resource allocation problems with separable, convex, and increasing system level objective functions. We employ two well-known measures to characterize the quality of local utility functions: Price of Anarchy (PoA) and Price of Stability (PoS), which provide a measure the best and worst Nash equilibrium, respectively. Our main results characterize the tradeoff between optimizing the PoA and optimizing the PoS; we show that if optimal PoA (resp. PoS) is achieved, there is a limitation on the achievable PoS (resp. PoA). Further, we show that the Shapley value objective function is the unique rule which optimizes PoA followed by PoS, and the marginal contribution rule is the unique rule which optimizes PoS followed by PoA. Lastly, we show that relaxation in the objective of optimizing PoA impacts the attainable PoS guarantees.",emily jensen,Games,2018.0,10.23919/ACC.2018.8431131,2018 Annual American Control Conference (ACC),Jensen2018,False,,IEEE,Not available,Optimal Utility Design in Convex Distributed Welfare Games,f69f7610c53e7b970ab060b2b2581fa1,https://ieeexplore.ieee.org/document/8431131/
1832,"This paper focuses on the design of local agent objective functions for resource allocation problems with separable, convex, and increasing system level objective functions. We employ two well-known measures to characterize the quality of local utility functions: Price of Anarchy (PoA) and Price of Stability (PoS), which provide a measure the best and worst Nash equilibrium, respectively. Our main results characterize the tradeoff between optimizing the PoA and optimizing the PoS; we show that if optimal PoA (resp. PoS) is achieved, there is a limitation on the achievable PoS (resp. PoA). Further, we show that the Shapley value objective function is the unique rule which optimizes PoA followed by PoS, and the marginal contribution rule is the unique rule which optimizes PoS followed by PoA. Lastly, we show that relaxation in the objective of optimizing PoA impacts the attainable PoS guarantees.",emily jensen,Resource management,2018.0,10.23919/ACC.2018.8431131,2018 Annual American Control Conference (ACC),Jensen2018,False,,IEEE,Not available,Optimal Utility Design in Convex Distributed Welfare Games,f69f7610c53e7b970ab060b2b2581fa1,https://ieeexplore.ieee.org/document/8431131/
1833,"This paper focuses on the design of local agent objective functions for resource allocation problems with separable, convex, and increasing system level objective functions. We employ two well-known measures to characterize the quality of local utility functions: Price of Anarchy (PoA) and Price of Stability (PoS), which provide a measure the best and worst Nash equilibrium, respectively. Our main results characterize the tradeoff between optimizing the PoA and optimizing the PoS; we show that if optimal PoA (resp. PoS) is achieved, there is a limitation on the achievable PoS (resp. PoA). Further, we show that the Shapley value objective function is the unique rule which optimizes PoA followed by PoS, and the marginal contribution rule is the unique rule which optimizes PoS followed by PoA. Lastly, we show that relaxation in the objective of optimizing PoA impacts the attainable PoS guarantees.",emily jensen,Linear programming,2018.0,10.23919/ACC.2018.8431131,2018 Annual American Control Conference (ACC),Jensen2018,False,,IEEE,Not available,Optimal Utility Design in Convex Distributed Welfare Games,f69f7610c53e7b970ab060b2b2581fa1,https://ieeexplore.ieee.org/document/8431131/
1834,"This paper focuses on the design of local agent objective functions for resource allocation problems with separable, convex, and increasing system level objective functions. We employ two well-known measures to characterize the quality of local utility functions: Price of Anarchy (PoA) and Price of Stability (PoS), which provide a measure the best and worst Nash equilibrium, respectively. Our main results characterize the tradeoff between optimizing the PoA and optimizing the PoS; we show that if optimal PoA (resp. PoS) is achieved, there is a limitation on the achievable PoS (resp. PoA). Further, we show that the Shapley value objective function is the unique rule which optimizes PoA followed by PoS, and the marginal contribution rule is the unique rule which optimizes PoS followed by PoA. Lastly, we show that relaxation in the objective of optimizing PoA impacts the attainable PoS guarantees.",emily jensen,Nash equilibrium,2018.0,10.23919/ACC.2018.8431131,2018 Annual American Control Conference (ACC),Jensen2018,False,,IEEE,Not available,Optimal Utility Design in Convex Distributed Welfare Games,f69f7610c53e7b970ab060b2b2581fa1,https://ieeexplore.ieee.org/document/8431131/
1835,"This paper focuses on the design of local agent objective functions for resource allocation problems with separable, convex, and increasing system level objective functions. We employ two well-known measures to characterize the quality of local utility functions: Price of Anarchy (PoA) and Price of Stability (PoS), which provide a measure the best and worst Nash equilibrium, respectively. Our main results characterize the tradeoff between optimizing the PoA and optimizing the PoS; we show that if optimal PoA (resp. PoS) is achieved, there is a limitation on the achievable PoS (resp. PoA). Further, we show that the Shapley value objective function is the unique rule which optimizes PoA followed by PoS, and the marginal contribution rule is the unique rule which optimizes PoS followed by PoA. Lastly, we show that relaxation in the objective of optimizing PoA impacts the attainable PoS guarantees.",emily jensen,Transportation,2018.0,10.23919/ACC.2018.8431131,2018 Annual American Control Conference (ACC),Jensen2018,False,,IEEE,Not available,Optimal Utility Design in Convex Distributed Welfare Games,f69f7610c53e7b970ab060b2b2581fa1,https://ieeexplore.ieee.org/document/8431131/
1836,"This paper focuses on the design of local agent objective functions for resource allocation problems with separable, convex, and increasing system level objective functions. We employ two well-known measures to characterize the quality of local utility functions: Price of Anarchy (PoA) and Price of Stability (PoS), which provide a measure the best and worst Nash equilibrium, respectively. Our main results characterize the tradeoff between optimizing the PoA and optimizing the PoS; we show that if optimal PoA (resp. PoS) is achieved, there is a limitation on the achievable PoS (resp. PoA). Further, we show that the Shapley value objective function is the unique rule which optimizes PoA followed by PoS, and the marginal contribution rule is the unique rule which optimizes PoS followed by PoA. Lastly, we show that relaxation in the objective of optimizing PoA impacts the attainable PoS guarantees.",emily jensen,Measurement,2018.0,10.23919/ACC.2018.8431131,2018 Annual American Control Conference (ACC),Jensen2018,False,,IEEE,Not available,Optimal Utility Design in Convex Distributed Welfare Games,f69f7610c53e7b970ab060b2b2581fa1,https://ieeexplore.ieee.org/document/8431131/
1837,"This paper focuses on the design of local agent objective functions for resource allocation problems with separable, convex, and increasing system level objective functions. We employ two well-known measures to characterize the quality of local utility functions: Price of Anarchy (PoA) and Price of Stability (PoS), which provide a measure the best and worst Nash equilibrium, respectively. Our main results characterize the tradeoff between optimizing the PoA and optimizing the PoS; we show that if optimal PoA (resp. PoS) is achieved, there is a limitation on the achievable PoS (resp. PoA). Further, we show that the Shapley value objective function is the unique rule which optimizes PoA followed by PoS, and the marginal contribution rule is the unique rule which optimizes PoS followed by PoA. Lastly, we show that relaxation in the objective of optimizing PoA impacts the attainable PoS guarantees.",emily jensen,Task analysis,2018.0,10.23919/ACC.2018.8431131,2018 Annual American Control Conference (ACC),Jensen2018,False,,IEEE,Not available,Optimal Utility Design in Convex Distributed Welfare Games,f69f7610c53e7b970ab060b2b2581fa1,https://ieeexplore.ieee.org/document/8431131/
1838,"This paper focuses on the design of local agent objective functions for resource allocation problems with separable, convex, and increasing system level objective functions. We employ two well-known measures to characterize the quality of local utility functions: Price of Anarchy (PoA) and Price of Stability (PoS), which provide a measure the best and worst Nash equilibrium, respectively. Our main results characterize the tradeoff between optimizing the PoA and optimizing the PoS; we show that if optimal PoA (resp. PoS) is achieved, there is a limitation on the achievable PoS (resp. PoA). Further, we show that the Shapley value objective function is the unique rule which optimizes PoA followed by PoS, and the marginal contribution rule is the unique rule which optimizes PoS followed by PoA. Lastly, we show that relaxation in the objective of optimizing PoA impacts the attainable PoS guarantees.",jason marden,Games,2018.0,10.23919/ACC.2018.8431131,2018 Annual American Control Conference (ACC),Jensen2018,False,,IEEE,Not available,Optimal Utility Design in Convex Distributed Welfare Games,f69f7610c53e7b970ab060b2b2581fa1,https://ieeexplore.ieee.org/document/8431131/
1839,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
1840,"This paper focuses on the design of local agent objective functions for resource allocation problems with separable, convex, and increasing system level objective functions. We employ two well-known measures to characterize the quality of local utility functions: Price of Anarchy (PoA) and Price of Stability (PoS), which provide a measure the best and worst Nash equilibrium, respectively. Our main results characterize the tradeoff between optimizing the PoA and optimizing the PoS; we show that if optimal PoA (resp. PoS) is achieved, there is a limitation on the achievable PoS (resp. PoA). Further, we show that the Shapley value objective function is the unique rule which optimizes PoA followed by PoS, and the marginal contribution rule is the unique rule which optimizes PoS followed by PoA. Lastly, we show that relaxation in the objective of optimizing PoA impacts the attainable PoS guarantees.",jason marden,Resource management,2018.0,10.23919/ACC.2018.8431131,2018 Annual American Control Conference (ACC),Jensen2018,False,,IEEE,Not available,Optimal Utility Design in Convex Distributed Welfare Games,f69f7610c53e7b970ab060b2b2581fa1,https://ieeexplore.ieee.org/document/8431131/
1841,"This paper focuses on the design of local agent objective functions for resource allocation problems with separable, convex, and increasing system level objective functions. We employ two well-known measures to characterize the quality of local utility functions: Price of Anarchy (PoA) and Price of Stability (PoS), which provide a measure the best and worst Nash equilibrium, respectively. Our main results characterize the tradeoff between optimizing the PoA and optimizing the PoS; we show that if optimal PoA (resp. PoS) is achieved, there is a limitation on the achievable PoS (resp. PoA). Further, we show that the Shapley value objective function is the unique rule which optimizes PoA followed by PoS, and the marginal contribution rule is the unique rule which optimizes PoS followed by PoA. Lastly, we show that relaxation in the objective of optimizing PoA impacts the attainable PoS guarantees.",jason marden,Linear programming,2018.0,10.23919/ACC.2018.8431131,2018 Annual American Control Conference (ACC),Jensen2018,False,,IEEE,Not available,Optimal Utility Design in Convex Distributed Welfare Games,f69f7610c53e7b970ab060b2b2581fa1,https://ieeexplore.ieee.org/document/8431131/
1842,"This paper focuses on the design of local agent objective functions for resource allocation problems with separable, convex, and increasing system level objective functions. We employ two well-known measures to characterize the quality of local utility functions: Price of Anarchy (PoA) and Price of Stability (PoS), which provide a measure the best and worst Nash equilibrium, respectively. Our main results characterize the tradeoff between optimizing the PoA and optimizing the PoS; we show that if optimal PoA (resp. PoS) is achieved, there is a limitation on the achievable PoS (resp. PoA). Further, we show that the Shapley value objective function is the unique rule which optimizes PoA followed by PoS, and the marginal contribution rule is the unique rule which optimizes PoS followed by PoA. Lastly, we show that relaxation in the objective of optimizing PoA impacts the attainable PoS guarantees.",jason marden,Nash equilibrium,2018.0,10.23919/ACC.2018.8431131,2018 Annual American Control Conference (ACC),Jensen2018,False,,IEEE,Not available,Optimal Utility Design in Convex Distributed Welfare Games,f69f7610c53e7b970ab060b2b2581fa1,https://ieeexplore.ieee.org/document/8431131/
1843,"This paper focuses on the design of local agent objective functions for resource allocation problems with separable, convex, and increasing system level objective functions. We employ two well-known measures to characterize the quality of local utility functions: Price of Anarchy (PoA) and Price of Stability (PoS), which provide a measure the best and worst Nash equilibrium, respectively. Our main results characterize the tradeoff between optimizing the PoA and optimizing the PoS; we show that if optimal PoA (resp. PoS) is achieved, there is a limitation on the achievable PoS (resp. PoA). Further, we show that the Shapley value objective function is the unique rule which optimizes PoA followed by PoS, and the marginal contribution rule is the unique rule which optimizes PoS followed by PoA. Lastly, we show that relaxation in the objective of optimizing PoA impacts the attainable PoS guarantees.",jason marden,Transportation,2018.0,10.23919/ACC.2018.8431131,2018 Annual American Control Conference (ACC),Jensen2018,False,,IEEE,Not available,Optimal Utility Design in Convex Distributed Welfare Games,f69f7610c53e7b970ab060b2b2581fa1,https://ieeexplore.ieee.org/document/8431131/
1844,"This paper focuses on the design of local agent objective functions for resource allocation problems with separable, convex, and increasing system level objective functions. We employ two well-known measures to characterize the quality of local utility functions: Price of Anarchy (PoA) and Price of Stability (PoS), which provide a measure the best and worst Nash equilibrium, respectively. Our main results characterize the tradeoff between optimizing the PoA and optimizing the PoS; we show that if optimal PoA (resp. PoS) is achieved, there is a limitation on the achievable PoS (resp. PoA). Further, we show that the Shapley value objective function is the unique rule which optimizes PoA followed by PoS, and the marginal contribution rule is the unique rule which optimizes PoS followed by PoA. Lastly, we show that relaxation in the objective of optimizing PoA impacts the attainable PoS guarantees.",jason marden,Measurement,2018.0,10.23919/ACC.2018.8431131,2018 Annual American Control Conference (ACC),Jensen2018,False,,IEEE,Not available,Optimal Utility Design in Convex Distributed Welfare Games,f69f7610c53e7b970ab060b2b2581fa1,https://ieeexplore.ieee.org/document/8431131/
1845,"This paper focuses on the design of local agent objective functions for resource allocation problems with separable, convex, and increasing system level objective functions. We employ two well-known measures to characterize the quality of local utility functions: Price of Anarchy (PoA) and Price of Stability (PoS), which provide a measure the best and worst Nash equilibrium, respectively. Our main results characterize the tradeoff between optimizing the PoA and optimizing the PoS; we show that if optimal PoA (resp. PoS) is achieved, there is a limitation on the achievable PoS (resp. PoA). Further, we show that the Shapley value objective function is the unique rule which optimizes PoA followed by PoS, and the marginal contribution rule is the unique rule which optimizes PoS followed by PoA. Lastly, we show that relaxation in the objective of optimizing PoA impacts the attainable PoS guarantees.",jason marden,Task analysis,2018.0,10.23919/ACC.2018.8431131,2018 Annual American Control Conference (ACC),Jensen2018,False,,IEEE,Not available,Optimal Utility Design in Convex Distributed Welfare Games,f69f7610c53e7b970ab060b2b2581fa1,https://ieeexplore.ieee.org/document/8431131/
1846,"We study decentralized power markets with strategic power generators. In decentralized markets, each generator submits its supply function (i.e., the amount of electricity it is willing to produce at various unit prices) to the independent system operator (ISO), who takes the submitted supply functions as the true marginal cost functions, and dispatches the generators to clear the market. If all generators reported their true marginal cost functions, the market outcome would be efficient (i.e., the total generation cost is minimized). However, when generators are strategic and aim to maximize their own profits, the reported supply functions are not necessarily the marginal cost functions, and the resulting market outcome may be inefficient. The efficiency loss depends on the topology of the underlying transmission network, because the topology sets constraints on the feasible power supply from generators. This paper provides an analytical upper bound of the efficiency loss due to strategic generators. Our upper bound sheds light on how the efficiency loss depends on the (mesh) transmission network topology (e.g., the degrees of buses, the admittances and flow limits of transmission lines).",yuanzhang xiao,Power markets,2016.0,10.1109/GlobalSIP.2016.7905965,2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP),Xiao2016,False,,IEEE,Not available,Supply function equilibrium in power markets: Mesh networks,3470af782022cdf4b510cfa4718e6209,https://ieeexplore.ieee.org/document/7905965/
1847,"We study decentralized power markets with strategic power generators. In decentralized markets, each generator submits its supply function (i.e., the amount of electricity it is willing to produce at various unit prices) to the independent system operator (ISO), who takes the submitted supply functions as the true marginal cost functions, and dispatches the generators to clear the market. If all generators reported their true marginal cost functions, the market outcome would be efficient (i.e., the total generation cost is minimized). However, when generators are strategic and aim to maximize their own profits, the reported supply functions are not necessarily the marginal cost functions, and the resulting market outcome may be inefficient. The efficiency loss depends on the topology of the underlying transmission network, because the topology sets constraints on the feasible power supply from generators. This paper provides an analytical upper bound of the efficiency loss due to strategic generators. Our upper bound sheds light on how the efficiency loss depends on the (mesh) transmission network topology (e.g., the degrees of buses, the admittances and flow limits of transmission lines).",yuanzhang xiao,supply function bidding,2016.0,10.1109/GlobalSIP.2016.7905965,2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP),Xiao2016,False,,IEEE,Not available,Supply function equilibrium in power markets: Mesh networks,3470af782022cdf4b510cfa4718e6209,https://ieeexplore.ieee.org/document/7905965/
1848,"We study decentralized power markets with strategic power generators. In decentralized markets, each generator submits its supply function (i.e., the amount of electricity it is willing to produce at various unit prices) to the independent system operator (ISO), who takes the submitted supply functions as the true marginal cost functions, and dispatches the generators to clear the market. If all generators reported their true marginal cost functions, the market outcome would be efficient (i.e., the total generation cost is minimized). However, when generators are strategic and aim to maximize their own profits, the reported supply functions are not necessarily the marginal cost functions, and the resulting market outcome may be inefficient. The efficiency loss depends on the topology of the underlying transmission network, because the topology sets constraints on the feasible power supply from generators. This paper provides an analytical upper bound of the efficiency loss due to strategic generators. Our upper bound sheds light on how the efficiency loss depends on the (mesh) transmission network topology (e.g., the degrees of buses, the admittances and flow limits of transmission lines).",yuanzhang xiao,price of anarchy,2016.0,10.1109/GlobalSIP.2016.7905965,2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP),Xiao2016,False,,IEEE,Not available,Supply function equilibrium in power markets: Mesh networks,3470af782022cdf4b510cfa4718e6209,https://ieeexplore.ieee.org/document/7905965/
1849,"We study decentralized power markets with strategic power generators. In decentralized markets, each generator submits its supply function (i.e., the amount of electricity it is willing to produce at various unit prices) to the independent system operator (ISO), who takes the submitted supply functions as the true marginal cost functions, and dispatches the generators to clear the market. If all generators reported their true marginal cost functions, the market outcome would be efficient (i.e., the total generation cost is minimized). However, when generators are strategic and aim to maximize their own profits, the reported supply functions are not necessarily the marginal cost functions, and the resulting market outcome may be inefficient. The efficiency loss depends on the topology of the underlying transmission network, because the topology sets constraints on the feasible power supply from generators. This paper provides an analytical upper bound of the efficiency loss due to strategic generators. Our upper bound sheds light on how the efficiency loss depends on the (mesh) transmission network topology (e.g., the degrees of buses, the admittances and flow limits of transmission lines).",chaithanya bandi,Power markets,2016.0,10.1109/GlobalSIP.2016.7905965,2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP),Xiao2016,False,,IEEE,Not available,Supply function equilibrium in power markets: Mesh networks,3470af782022cdf4b510cfa4718e6209,https://ieeexplore.ieee.org/document/7905965/
1850,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
1851,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
1852,"We study decentralized power markets with strategic power generators. In decentralized markets, each generator submits its supply function (i.e., the amount of electricity it is willing to produce at various unit prices) to the independent system operator (ISO), who takes the submitted supply functions as the true marginal cost functions, and dispatches the generators to clear the market. If all generators reported their true marginal cost functions, the market outcome would be efficient (i.e., the total generation cost is minimized). However, when generators are strategic and aim to maximize their own profits, the reported supply functions are not necessarily the marginal cost functions, and the resulting market outcome may be inefficient. The efficiency loss depends on the topology of the underlying transmission network, because the topology sets constraints on the feasible power supply from generators. This paper provides an analytical upper bound of the efficiency loss due to strategic generators. Our upper bound sheds light on how the efficiency loss depends on the (mesh) transmission network topology (e.g., the degrees of buses, the admittances and flow limits of transmission lines).",chaithanya bandi,supply function bidding,2016.0,10.1109/GlobalSIP.2016.7905965,2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP),Xiao2016,False,,IEEE,Not available,Supply function equilibrium in power markets: Mesh networks,3470af782022cdf4b510cfa4718e6209,https://ieeexplore.ieee.org/document/7905965/
1853,"We study decentralized power markets with strategic power generators. In decentralized markets, each generator submits its supply function (i.e., the amount of electricity it is willing to produce at various unit prices) to the independent system operator (ISO), who takes the submitted supply functions as the true marginal cost functions, and dispatches the generators to clear the market. If all generators reported their true marginal cost functions, the market outcome would be efficient (i.e., the total generation cost is minimized). However, when generators are strategic and aim to maximize their own profits, the reported supply functions are not necessarily the marginal cost functions, and the resulting market outcome may be inefficient. The efficiency loss depends on the topology of the underlying transmission network, because the topology sets constraints on the feasible power supply from generators. This paper provides an analytical upper bound of the efficiency loss due to strategic generators. Our upper bound sheds light on how the efficiency loss depends on the (mesh) transmission network topology (e.g., the degrees of buses, the admittances and flow limits of transmission lines).",chaithanya bandi,price of anarchy,2016.0,10.1109/GlobalSIP.2016.7905965,2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP),Xiao2016,False,,IEEE,Not available,Supply function equilibrium in power markets: Mesh networks,3470af782022cdf4b510cfa4718e6209,https://ieeexplore.ieee.org/document/7905965/
1854,"We study decentralized power markets with strategic power generators. In decentralized markets, each generator submits its supply function (i.e., the amount of electricity it is willing to produce at various unit prices) to the independent system operator (ISO), who takes the submitted supply functions as the true marginal cost functions, and dispatches the generators to clear the market. If all generators reported their true marginal cost functions, the market outcome would be efficient (i.e., the total generation cost is minimized). However, when generators are strategic and aim to maximize their own profits, the reported supply functions are not necessarily the marginal cost functions, and the resulting market outcome may be inefficient. The efficiency loss depends on the topology of the underlying transmission network, because the topology sets constraints on the feasible power supply from generators. This paper provides an analytical upper bound of the efficiency loss due to strategic generators. Our upper bound sheds light on how the efficiency loss depends on the (mesh) transmission network topology (e.g., the degrees of buses, the admittances and flow limits of transmission lines).",ermin wei,Power markets,2016.0,10.1109/GlobalSIP.2016.7905965,2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP),Xiao2016,False,,IEEE,Not available,Supply function equilibrium in power markets: Mesh networks,3470af782022cdf4b510cfa4718e6209,https://ieeexplore.ieee.org/document/7905965/
1855,"We study decentralized power markets with strategic power generators. In decentralized markets, each generator submits its supply function (i.e., the amount of electricity it is willing to produce at various unit prices) to the independent system operator (ISO), who takes the submitted supply functions as the true marginal cost functions, and dispatches the generators to clear the market. If all generators reported their true marginal cost functions, the market outcome would be efficient (i.e., the total generation cost is minimized). However, when generators are strategic and aim to maximize their own profits, the reported supply functions are not necessarily the marginal cost functions, and the resulting market outcome may be inefficient. The efficiency loss depends on the topology of the underlying transmission network, because the topology sets constraints on the feasible power supply from generators. This paper provides an analytical upper bound of the efficiency loss due to strategic generators. Our upper bound sheds light on how the efficiency loss depends on the (mesh) transmission network topology (e.g., the degrees of buses, the admittances and flow limits of transmission lines).",ermin wei,supply function bidding,2016.0,10.1109/GlobalSIP.2016.7905965,2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP),Xiao2016,False,,IEEE,Not available,Supply function equilibrium in power markets: Mesh networks,3470af782022cdf4b510cfa4718e6209,https://ieeexplore.ieee.org/document/7905965/
1856,"We study decentralized power markets with strategic power generators. In decentralized markets, each generator submits its supply function (i.e., the amount of electricity it is willing to produce at various unit prices) to the independent system operator (ISO), who takes the submitted supply functions as the true marginal cost functions, and dispatches the generators to clear the market. If all generators reported their true marginal cost functions, the market outcome would be efficient (i.e., the total generation cost is minimized). However, when generators are strategic and aim to maximize their own profits, the reported supply functions are not necessarily the marginal cost functions, and the resulting market outcome may be inefficient. The efficiency loss depends on the topology of the underlying transmission network, because the topology sets constraints on the feasible power supply from generators. This paper provides an analytical upper bound of the efficiency loss due to strategic generators. Our upper bound sheds light on how the efficiency loss depends on the (mesh) transmission network topology (e.g., the degrees of buses, the admittances and flow limits of transmission lines).",ermin wei,price of anarchy,2016.0,10.1109/GlobalSIP.2016.7905965,2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP),Xiao2016,False,,IEEE,Not available,Supply function equilibrium in power markets: Mesh networks,3470af782022cdf4b510cfa4718e6209,https://ieeexplore.ieee.org/document/7905965/
1857,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",m.x. goemans,Mobile ad hoc networks,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
1858,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",m.x. goemans,Nash equilibrium,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
1859,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",m.x. goemans,price of anarchy,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
1860,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",m.x. goemans,third-generation (3G) wireless networks,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
1861,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",m.x. goemans,unified architecture,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
1862,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
1863,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",li li,Mobile ad hoc networks,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
1864,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",li li,Nash equilibrium,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
1865,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",li li,price of anarchy,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
1866,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",li li,third-generation (3G) wireless networks,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
1867,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",li li,unified architecture,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
1868,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",v.s. mirrokni,Mobile ad hoc networks,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
1869,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",v.s. mirrokni,Nash equilibrium,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
1870,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",v.s. mirrokni,price of anarchy,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
1871,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",v.s. mirrokni,third-generation (3G) wireless networks,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
1872,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",v.s. mirrokni,unified architecture,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
1873,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
1874,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",m. thottan,Mobile ad hoc networks,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
1875,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",m. thottan,Nash equilibrium,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
1876,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",m. thottan,price of anarchy,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
1877,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",m. thottan,third-generation (3G) wireless networks,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
1878,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",m. thottan,unified architecture,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
1879,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",tobias harks,Stability,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
1880,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",tobias harks,Resource management,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
1881,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",tobias harks,Cost function,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
1882,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",tobias harks,Nash equilibrium,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
1883,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",tobias harks,Pricing,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
1884,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
1885,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",tobias harks,Aggregates,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
1886,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",tobias harks,Polynomials,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
1887,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",tobias harks,Transport protocols,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
1888,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",tobias harks,Delay,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
1889,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",tobias harks,Roads,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
1890,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",konstantin miller,Stability,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
1891,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",konstantin miller,Resource management,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
1892,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",konstantin miller,Cost function,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
1893,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",konstantin miller,Nash equilibrium,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
1894,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",konstantin miller,Pricing,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
1895,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
1896,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",konstantin miller,Aggregates,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
1897,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",konstantin miller,Polynomials,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
1898,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",konstantin miller,Transport protocols,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
1899,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",konstantin miller,Delay,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
1900,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",konstantin miller,Roads,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
1901,"Game theoretic models have been widely employed in many networking contexts. Research to date has mainly focused on non-cooperative networking games, where the selfish agents cannot reach a binding agreement on the way they would share the network infrastructure and the operating points are the Nash equilibria. These are typically inefficient, as manifested by large values of the Price of Anarchy (PoA). Many approaches have been proposed for mitigating this problem, however under the standing assumption of a non-cooperative game. In a growing number of networking scenarios it is possible for the selfish agents to communicate and reach an agreement, i.e., play a cooperative game. Therefore, the degradation of performance should be considered at an operating point that is a cooperative game solution. Accordingly, our goal is to lay foundations for the application of cooperative game theory to fundamental problems in networking. We explain our choice of the Nash Bargaining Scheme (NBS) as the solution concept, and we introduce the Price of Selfishness (PoS), which considers the degradation of performance at an NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we study the classical scenario of agents that consider the same performance objectives. While the PoA here can be very large, we establish that, under plausible assumptions, the PoS attains its minimum value, i.e., through bargaining, the selfish agents reach social optimality. We then extend our study to consider the “heterogeneous” case, where agents may consider vastly different performance objectives. We demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures may now be unsuitable. Accordingly, we introduce the Price of Heterogeneity (PoH), as a proper extension of the PoA. We establish an upper-bound on the PoH for a general class of heterogeneous performance objectives, and indicate that it provides incentives for bargaining also in this general case. We discuss network design guidelines that follow from our findings.",gideon blocq,Games,2012.0,10.1109/INFCOM.2012.6195636,2012 Proceedings IEEE INFOCOM,Blocq2012,False,,IEEE,Not available,How good is bargained routing?,b9b57e7e44e105b7977be0bad1fbd0c0,https://ieeexplore.ieee.org/document/6195636/
1902,"Game theoretic models have been widely employed in many networking contexts. Research to date has mainly focused on non-cooperative networking games, where the selfish agents cannot reach a binding agreement on the way they would share the network infrastructure and the operating points are the Nash equilibria. These are typically inefficient, as manifested by large values of the Price of Anarchy (PoA). Many approaches have been proposed for mitigating this problem, however under the standing assumption of a non-cooperative game. In a growing number of networking scenarios it is possible for the selfish agents to communicate and reach an agreement, i.e., play a cooperative game. Therefore, the degradation of performance should be considered at an operating point that is a cooperative game solution. Accordingly, our goal is to lay foundations for the application of cooperative game theory to fundamental problems in networking. We explain our choice of the Nash Bargaining Scheme (NBS) as the solution concept, and we introduce the Price of Selfishness (PoS), which considers the degradation of performance at an NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we study the classical scenario of agents that consider the same performance objectives. While the PoA here can be very large, we establish that, under plausible assumptions, the PoS attains its minimum value, i.e., through bargaining, the selfish agents reach social optimality. We then extend our study to consider the “heterogeneous” case, where agents may consider vastly different performance objectives. We demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures may now be unsuitable. Accordingly, we introduce the Price of Heterogeneity (PoH), as a proper extension of the PoA. We establish an upper-bound on the PoH for a general class of heterogeneous performance objectives, and indicate that it provides incentives for bargaining also in this general case. We discuss network design guidelines that follow from our findings.",gideon blocq,Routing,2012.0,10.1109/INFCOM.2012.6195636,2012 Proceedings IEEE INFOCOM,Blocq2012,False,,IEEE,Not available,How good is bargained routing?,b9b57e7e44e105b7977be0bad1fbd0c0,https://ieeexplore.ieee.org/document/6195636/
1903,"Game theoretic models have been widely employed in many networking contexts. Research to date has mainly focused on non-cooperative networking games, where the selfish agents cannot reach a binding agreement on the way they would share the network infrastructure and the operating points are the Nash equilibria. These are typically inefficient, as manifested by large values of the Price of Anarchy (PoA). Many approaches have been proposed for mitigating this problem, however under the standing assumption of a non-cooperative game. In a growing number of networking scenarios it is possible for the selfish agents to communicate and reach an agreement, i.e., play a cooperative game. Therefore, the degradation of performance should be considered at an operating point that is a cooperative game solution. Accordingly, our goal is to lay foundations for the application of cooperative game theory to fundamental problems in networking. We explain our choice of the Nash Bargaining Scheme (NBS) as the solution concept, and we introduce the Price of Selfishness (PoS), which considers the degradation of performance at an NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we study the classical scenario of agents that consider the same performance objectives. While the PoA here can be very large, we establish that, under plausible assumptions, the PoS attains its minimum value, i.e., through bargaining, the selfish agents reach social optimality. We then extend our study to consider the “heterogeneous” case, where agents may consider vastly different performance objectives. We demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures may now be unsuitable. Accordingly, we introduce the Price of Heterogeneity (PoH), as a proper extension of the PoA. We establish an upper-bound on the PoH for a general class of heterogeneous performance objectives, and indicate that it provides incentives for bargaining also in this general case. We discuss network design guidelines that follow from our findings.",gideon blocq,Vectors,2012.0,10.1109/INFCOM.2012.6195636,2012 Proceedings IEEE INFOCOM,Blocq2012,False,,IEEE,Not available,How good is bargained routing?,b9b57e7e44e105b7977be0bad1fbd0c0,https://ieeexplore.ieee.org/document/6195636/
1904,"Game theoretic models have been widely employed in many networking contexts. Research to date has mainly focused on non-cooperative networking games, where the selfish agents cannot reach a binding agreement on the way they would share the network infrastructure and the operating points are the Nash equilibria. These are typically inefficient, as manifested by large values of the Price of Anarchy (PoA). Many approaches have been proposed for mitigating this problem, however under the standing assumption of a non-cooperative game. In a growing number of networking scenarios it is possible for the selfish agents to communicate and reach an agreement, i.e., play a cooperative game. Therefore, the degradation of performance should be considered at an operating point that is a cooperative game solution. Accordingly, our goal is to lay foundations for the application of cooperative game theory to fundamental problems in networking. We explain our choice of the Nash Bargaining Scheme (NBS) as the solution concept, and we introduce the Price of Selfishness (PoS), which considers the degradation of performance at an NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we study the classical scenario of agents that consider the same performance objectives. While the PoA here can be very large, we establish that, under plausible assumptions, the PoS attains its minimum value, i.e., through bargaining, the selfish agents reach social optimality. We then extend our study to consider the “heterogeneous” case, where agents may consider vastly different performance objectives. We demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures may now be unsuitable. Accordingly, we introduce the Price of Heterogeneity (PoH), as a proper extension of the PoA. We establish an upper-bound on the PoH for a general class of heterogeneous performance objectives, and indicate that it provides incentives for bargaining also in this general case. We discuss network design guidelines that follow from our findings.",gideon blocq,NIST,2012.0,10.1109/INFCOM.2012.6195636,2012 Proceedings IEEE INFOCOM,Blocq2012,False,,IEEE,Not available,How good is bargained routing?,b9b57e7e44e105b7977be0bad1fbd0c0,https://ieeexplore.ieee.org/document/6195636/
1905,"Game theoretic models have been widely employed in many networking contexts. Research to date has mainly focused on non-cooperative networking games, where the selfish agents cannot reach a binding agreement on the way they would share the network infrastructure and the operating points are the Nash equilibria. These are typically inefficient, as manifested by large values of the Price of Anarchy (PoA). Many approaches have been proposed for mitigating this problem, however under the standing assumption of a non-cooperative game. In a growing number of networking scenarios it is possible for the selfish agents to communicate and reach an agreement, i.e., play a cooperative game. Therefore, the degradation of performance should be considered at an operating point that is a cooperative game solution. Accordingly, our goal is to lay foundations for the application of cooperative game theory to fundamental problems in networking. We explain our choice of the Nash Bargaining Scheme (NBS) as the solution concept, and we introduce the Price of Selfishness (PoS), which considers the degradation of performance at an NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we study the classical scenario of agents that consider the same performance objectives. While the PoA here can be very large, we establish that, under plausible assumptions, the PoS attains its minimum value, i.e., through bargaining, the selfish agents reach social optimality. We then extend our study to consider the “heterogeneous” case, where agents may consider vastly different performance objectives. We demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures may now be unsuitable. Accordingly, we introduce the Price of Heterogeneity (PoH), as a proper extension of the PoA. We establish an upper-bound on the PoH for a general class of heterogeneous performance objectives, and indicate that it provides incentives for bargaining also in this general case. We discuss network design guidelines that follow from our findings.",gideon blocq,Cost function,2012.0,10.1109/INFCOM.2012.6195636,2012 Proceedings IEEE INFOCOM,Blocq2012,False,,IEEE,Not available,How good is bargained routing?,b9b57e7e44e105b7977be0bad1fbd0c0,https://ieeexplore.ieee.org/document/6195636/
1906,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
1907,"Game theoretic models have been widely employed in many networking contexts. Research to date has mainly focused on non-cooperative networking games, where the selfish agents cannot reach a binding agreement on the way they would share the network infrastructure and the operating points are the Nash equilibria. These are typically inefficient, as manifested by large values of the Price of Anarchy (PoA). Many approaches have been proposed for mitigating this problem, however under the standing assumption of a non-cooperative game. In a growing number of networking scenarios it is possible for the selfish agents to communicate and reach an agreement, i.e., play a cooperative game. Therefore, the degradation of performance should be considered at an operating point that is a cooperative game solution. Accordingly, our goal is to lay foundations for the application of cooperative game theory to fundamental problems in networking. We explain our choice of the Nash Bargaining Scheme (NBS) as the solution concept, and we introduce the Price of Selfishness (PoS), which considers the degradation of performance at an NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we study the classical scenario of agents that consider the same performance objectives. While the PoA here can be very large, we establish that, under plausible assumptions, the PoS attains its minimum value, i.e., through bargaining, the selfish agents reach social optimality. We then extend our study to consider the “heterogeneous” case, where agents may consider vastly different performance objectives. We demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures may now be unsuitable. Accordingly, we introduce the Price of Heterogeneity (PoH), as a proper extension of the PoA. We establish an upper-bound on the PoH for a general class of heterogeneous performance objectives, and indicate that it provides incentives for bargaining also in this general case. We discuss network design guidelines that follow from our findings.",gideon blocq,Delay,2012.0,10.1109/INFCOM.2012.6195636,2012 Proceedings IEEE INFOCOM,Blocq2012,False,,IEEE,Not available,How good is bargained routing?,b9b57e7e44e105b7977be0bad1fbd0c0,https://ieeexplore.ieee.org/document/6195636/
1908,"Game theoretic models have been widely employed in many networking contexts. Research to date has mainly focused on non-cooperative networking games, where the selfish agents cannot reach a binding agreement on the way they would share the network infrastructure and the operating points are the Nash equilibria. These are typically inefficient, as manifested by large values of the Price of Anarchy (PoA). Many approaches have been proposed for mitigating this problem, however under the standing assumption of a non-cooperative game. In a growing number of networking scenarios it is possible for the selfish agents to communicate and reach an agreement, i.e., play a cooperative game. Therefore, the degradation of performance should be considered at an operating point that is a cooperative game solution. Accordingly, our goal is to lay foundations for the application of cooperative game theory to fundamental problems in networking. We explain our choice of the Nash Bargaining Scheme (NBS) as the solution concept, and we introduce the Price of Selfishness (PoS), which considers the degradation of performance at an NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we study the classical scenario of agents that consider the same performance objectives. While the PoA here can be very large, we establish that, under plausible assumptions, the PoS attains its minimum value, i.e., through bargaining, the selfish agents reach social optimality. We then extend our study to consider the “heterogeneous” case, where agents may consider vastly different performance objectives. We demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures may now be unsuitable. Accordingly, we introduce the Price of Heterogeneity (PoH), as a proper extension of the PoA. We establish an upper-bound on the PoH for a general class of heterogeneous performance objectives, and indicate that it provides incentives for bargaining also in this general case. We discuss network design guidelines that follow from our findings.",gideon blocq,Nash equilibrium,2012.0,10.1109/INFCOM.2012.6195636,2012 Proceedings IEEE INFOCOM,Blocq2012,False,,IEEE,Not available,How good is bargained routing?,b9b57e7e44e105b7977be0bad1fbd0c0,https://ieeexplore.ieee.org/document/6195636/
1909,"Game theoretic models have been widely employed in many networking contexts. Research to date has mainly focused on non-cooperative networking games, where the selfish agents cannot reach a binding agreement on the way they would share the network infrastructure and the operating points are the Nash equilibria. These are typically inefficient, as manifested by large values of the Price of Anarchy (PoA). Many approaches have been proposed for mitigating this problem, however under the standing assumption of a non-cooperative game. In a growing number of networking scenarios it is possible for the selfish agents to communicate and reach an agreement, i.e., play a cooperative game. Therefore, the degradation of performance should be considered at an operating point that is a cooperative game solution. Accordingly, our goal is to lay foundations for the application of cooperative game theory to fundamental problems in networking. We explain our choice of the Nash Bargaining Scheme (NBS) as the solution concept, and we introduce the Price of Selfishness (PoS), which considers the degradation of performance at an NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we study the classical scenario of agents that consider the same performance objectives. While the PoA here can be very large, we establish that, under plausible assumptions, the PoS attains its minimum value, i.e., through bargaining, the selfish agents reach social optimality. We then extend our study to consider the “heterogeneous” case, where agents may consider vastly different performance objectives. We demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures may now be unsuitable. Accordingly, we introduce the Price of Heterogeneity (PoH), as a proper extension of the PoA. We establish an upper-bound on the PoH for a general class of heterogeneous performance objectives, and indicate that it provides incentives for bargaining also in this general case. We discuss network design guidelines that follow from our findings.",ariel orda,Games,2012.0,10.1109/INFCOM.2012.6195636,2012 Proceedings IEEE INFOCOM,Blocq2012,False,,IEEE,Not available,How good is bargained routing?,b9b57e7e44e105b7977be0bad1fbd0c0,https://ieeexplore.ieee.org/document/6195636/
1910,"Game theoretic models have been widely employed in many networking contexts. Research to date has mainly focused on non-cooperative networking games, where the selfish agents cannot reach a binding agreement on the way they would share the network infrastructure and the operating points are the Nash equilibria. These are typically inefficient, as manifested by large values of the Price of Anarchy (PoA). Many approaches have been proposed for mitigating this problem, however under the standing assumption of a non-cooperative game. In a growing number of networking scenarios it is possible for the selfish agents to communicate and reach an agreement, i.e., play a cooperative game. Therefore, the degradation of performance should be considered at an operating point that is a cooperative game solution. Accordingly, our goal is to lay foundations for the application of cooperative game theory to fundamental problems in networking. We explain our choice of the Nash Bargaining Scheme (NBS) as the solution concept, and we introduce the Price of Selfishness (PoS), which considers the degradation of performance at an NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we study the classical scenario of agents that consider the same performance objectives. While the PoA here can be very large, we establish that, under plausible assumptions, the PoS attains its minimum value, i.e., through bargaining, the selfish agents reach social optimality. We then extend our study to consider the “heterogeneous” case, where agents may consider vastly different performance objectives. We demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures may now be unsuitable. Accordingly, we introduce the Price of Heterogeneity (PoH), as a proper extension of the PoA. We establish an upper-bound on the PoH for a general class of heterogeneous performance objectives, and indicate that it provides incentives for bargaining also in this general case. We discuss network design guidelines that follow from our findings.",ariel orda,Routing,2012.0,10.1109/INFCOM.2012.6195636,2012 Proceedings IEEE INFOCOM,Blocq2012,False,,IEEE,Not available,How good is bargained routing?,b9b57e7e44e105b7977be0bad1fbd0c0,https://ieeexplore.ieee.org/document/6195636/
1911,"Game theoretic models have been widely employed in many networking contexts. Research to date has mainly focused on non-cooperative networking games, where the selfish agents cannot reach a binding agreement on the way they would share the network infrastructure and the operating points are the Nash equilibria. These are typically inefficient, as manifested by large values of the Price of Anarchy (PoA). Many approaches have been proposed for mitigating this problem, however under the standing assumption of a non-cooperative game. In a growing number of networking scenarios it is possible for the selfish agents to communicate and reach an agreement, i.e., play a cooperative game. Therefore, the degradation of performance should be considered at an operating point that is a cooperative game solution. Accordingly, our goal is to lay foundations for the application of cooperative game theory to fundamental problems in networking. We explain our choice of the Nash Bargaining Scheme (NBS) as the solution concept, and we introduce the Price of Selfishness (PoS), which considers the degradation of performance at an NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we study the classical scenario of agents that consider the same performance objectives. While the PoA here can be very large, we establish that, under plausible assumptions, the PoS attains its minimum value, i.e., through bargaining, the selfish agents reach social optimality. We then extend our study to consider the “heterogeneous” case, where agents may consider vastly different performance objectives. We demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures may now be unsuitable. Accordingly, we introduce the Price of Heterogeneity (PoH), as a proper extension of the PoA. We establish an upper-bound on the PoH for a general class of heterogeneous performance objectives, and indicate that it provides incentives for bargaining also in this general case. We discuss network design guidelines that follow from our findings.",ariel orda,Vectors,2012.0,10.1109/INFCOM.2012.6195636,2012 Proceedings IEEE INFOCOM,Blocq2012,False,,IEEE,Not available,How good is bargained routing?,b9b57e7e44e105b7977be0bad1fbd0c0,https://ieeexplore.ieee.org/document/6195636/
1912,"Game theoretic models have been widely employed in many networking contexts. Research to date has mainly focused on non-cooperative networking games, where the selfish agents cannot reach a binding agreement on the way they would share the network infrastructure and the operating points are the Nash equilibria. These are typically inefficient, as manifested by large values of the Price of Anarchy (PoA). Many approaches have been proposed for mitigating this problem, however under the standing assumption of a non-cooperative game. In a growing number of networking scenarios it is possible for the selfish agents to communicate and reach an agreement, i.e., play a cooperative game. Therefore, the degradation of performance should be considered at an operating point that is a cooperative game solution. Accordingly, our goal is to lay foundations for the application of cooperative game theory to fundamental problems in networking. We explain our choice of the Nash Bargaining Scheme (NBS) as the solution concept, and we introduce the Price of Selfishness (PoS), which considers the degradation of performance at an NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we study the classical scenario of agents that consider the same performance objectives. While the PoA here can be very large, we establish that, under plausible assumptions, the PoS attains its minimum value, i.e., through bargaining, the selfish agents reach social optimality. We then extend our study to consider the “heterogeneous” case, where agents may consider vastly different performance objectives. We demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures may now be unsuitable. Accordingly, we introduce the Price of Heterogeneity (PoH), as a proper extension of the PoA. We establish an upper-bound on the PoH for a general class of heterogeneous performance objectives, and indicate that it provides incentives for bargaining also in this general case. We discuss network design guidelines that follow from our findings.",ariel orda,NIST,2012.0,10.1109/INFCOM.2012.6195636,2012 Proceedings IEEE INFOCOM,Blocq2012,False,,IEEE,Not available,How good is bargained routing?,b9b57e7e44e105b7977be0bad1fbd0c0,https://ieeexplore.ieee.org/document/6195636/
1913,"Game theoretic models have been widely employed in many networking contexts. Research to date has mainly focused on non-cooperative networking games, where the selfish agents cannot reach a binding agreement on the way they would share the network infrastructure and the operating points are the Nash equilibria. These are typically inefficient, as manifested by large values of the Price of Anarchy (PoA). Many approaches have been proposed for mitigating this problem, however under the standing assumption of a non-cooperative game. In a growing number of networking scenarios it is possible for the selfish agents to communicate and reach an agreement, i.e., play a cooperative game. Therefore, the degradation of performance should be considered at an operating point that is a cooperative game solution. Accordingly, our goal is to lay foundations for the application of cooperative game theory to fundamental problems in networking. We explain our choice of the Nash Bargaining Scheme (NBS) as the solution concept, and we introduce the Price of Selfishness (PoS), which considers the degradation of performance at an NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we study the classical scenario of agents that consider the same performance objectives. While the PoA here can be very large, we establish that, under plausible assumptions, the PoS attains its minimum value, i.e., through bargaining, the selfish agents reach social optimality. We then extend our study to consider the “heterogeneous” case, where agents may consider vastly different performance objectives. We demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures may now be unsuitable. Accordingly, we introduce the Price of Heterogeneity (PoH), as a proper extension of the PoA. We establish an upper-bound on the PoH for a general class of heterogeneous performance objectives, and indicate that it provides incentives for bargaining also in this general case. We discuss network design guidelines that follow from our findings.",ariel orda,Cost function,2012.0,10.1109/INFCOM.2012.6195636,2012 Proceedings IEEE INFOCOM,Blocq2012,False,,IEEE,Not available,How good is bargained routing?,b9b57e7e44e105b7977be0bad1fbd0c0,https://ieeexplore.ieee.org/document/6195636/
1914,"Game theoretic models have been widely employed in many networking contexts. Research to date has mainly focused on non-cooperative networking games, where the selfish agents cannot reach a binding agreement on the way they would share the network infrastructure and the operating points are the Nash equilibria. These are typically inefficient, as manifested by large values of the Price of Anarchy (PoA). Many approaches have been proposed for mitigating this problem, however under the standing assumption of a non-cooperative game. In a growing number of networking scenarios it is possible for the selfish agents to communicate and reach an agreement, i.e., play a cooperative game. Therefore, the degradation of performance should be considered at an operating point that is a cooperative game solution. Accordingly, our goal is to lay foundations for the application of cooperative game theory to fundamental problems in networking. We explain our choice of the Nash Bargaining Scheme (NBS) as the solution concept, and we introduce the Price of Selfishness (PoS), which considers the degradation of performance at an NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we study the classical scenario of agents that consider the same performance objectives. While the PoA here can be very large, we establish that, under plausible assumptions, the PoS attains its minimum value, i.e., through bargaining, the selfish agents reach social optimality. We then extend our study to consider the “heterogeneous” case, where agents may consider vastly different performance objectives. We demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures may now be unsuitable. Accordingly, we introduce the Price of Heterogeneity (PoH), as a proper extension of the PoA. We establish an upper-bound on the PoH for a general class of heterogeneous performance objectives, and indicate that it provides incentives for bargaining also in this general case. We discuss network design guidelines that follow from our findings.",ariel orda,Delay,2012.0,10.1109/INFCOM.2012.6195636,2012 Proceedings IEEE INFOCOM,Blocq2012,False,,IEEE,Not available,How good is bargained routing?,b9b57e7e44e105b7977be0bad1fbd0c0,https://ieeexplore.ieee.org/document/6195636/
1915,"Game theoretic models have been widely employed in many networking contexts. Research to date has mainly focused on non-cooperative networking games, where the selfish agents cannot reach a binding agreement on the way they would share the network infrastructure and the operating points are the Nash equilibria. These are typically inefficient, as manifested by large values of the Price of Anarchy (PoA). Many approaches have been proposed for mitigating this problem, however under the standing assumption of a non-cooperative game. In a growing number of networking scenarios it is possible for the selfish agents to communicate and reach an agreement, i.e., play a cooperative game. Therefore, the degradation of performance should be considered at an operating point that is a cooperative game solution. Accordingly, our goal is to lay foundations for the application of cooperative game theory to fundamental problems in networking. We explain our choice of the Nash Bargaining Scheme (NBS) as the solution concept, and we introduce the Price of Selfishness (PoS), which considers the degradation of performance at an NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we study the classical scenario of agents that consider the same performance objectives. While the PoA here can be very large, we establish that, under plausible assumptions, the PoS attains its minimum value, i.e., through bargaining, the selfish agents reach social optimality. We then extend our study to consider the “heterogeneous” case, where agents may consider vastly different performance objectives. We demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures may now be unsuitable. Accordingly, we introduce the Price of Heterogeneity (PoH), as a proper extension of the PoA. We establish an upper-bound on the PoH for a general class of heterogeneous performance objectives, and indicate that it provides incentives for bargaining also in this general case. We discuss network design guidelines that follow from our findings.",ariel orda,Nash equilibrium,2012.0,10.1109/INFCOM.2012.6195636,2012 Proceedings IEEE INFOCOM,Blocq2012,False,,IEEE,Not available,How good is bargained routing?,b9b57e7e44e105b7977be0bad1fbd0c0,https://ieeexplore.ieee.org/document/6195636/
1916,"This paper considers a scheduling game problem on identical parallel machines with flexible and periodic maintenance. Each machine needs to be maintained periodically, and the interval of any two consecutive maintenance activities is in a given time window. Each job is owned by a selfish agent, whose objective is to minimize the completion time of its job. The system's objective is to minimize the makespan. We design an LPT-NF coordination mechanism based on the longest processing time (LPT) and next fit (NF) rules. Then we give a greedy LPT-NF algorithm to obtain the Nash Equilibrium, and the lower bound of the optimal solution. Finally, we evaluate the performance of the LPT-NF coordination mechanism with a set of computational experiments, and analyze the impact of maintenance time, the minimum maintenance spacing, and the maximum maintenance spacing on the Nash Equilibrium solutions. The results show that the Nash Equilibrium is very close to the optimal solution for all the experiments. In addition, it is shown that the LPT-NF coordination mechanism works well and tends to perform better when facing the larger-scale scenarios.",cui-lin zhang,scheduling game,2018.0,10.1109/ICNSC.2018.8361314,"2018 IEEE 15th International Conference on Networking, Sensing and Control (ICNSC)",Zhang2018,False,,IEEE,Not available,A coordination mechanism for scheduling game on parallel machines with flexible maintenance,c8ddbd676e1628cc9d1da4d7a32430a4,https://ieeexplore.ieee.org/document/8361314/
1917,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
1918,"This paper considers a scheduling game problem on identical parallel machines with flexible and periodic maintenance. Each machine needs to be maintained periodically, and the interval of any two consecutive maintenance activities is in a given time window. Each job is owned by a selfish agent, whose objective is to minimize the completion time of its job. The system's objective is to minimize the makespan. We design an LPT-NF coordination mechanism based on the longest processing time (LPT) and next fit (NF) rules. Then we give a greedy LPT-NF algorithm to obtain the Nash Equilibrium, and the lower bound of the optimal solution. Finally, we evaluate the performance of the LPT-NF coordination mechanism with a set of computational experiments, and analyze the impact of maintenance time, the minimum maintenance spacing, and the maximum maintenance spacing on the Nash Equilibrium solutions. The results show that the Nash Equilibrium is very close to the optimal solution for all the experiments. In addition, it is shown that the LPT-NF coordination mechanism works well and tends to perform better when facing the larger-scale scenarios.",cui-lin zhang,flexible maintenance,2018.0,10.1109/ICNSC.2018.8361314,"2018 IEEE 15th International Conference on Networking, Sensing and Control (ICNSC)",Zhang2018,False,,IEEE,Not available,A coordination mechanism for scheduling game on parallel machines with flexible maintenance,c8ddbd676e1628cc9d1da4d7a32430a4,https://ieeexplore.ieee.org/document/8361314/
1919,"This paper considers a scheduling game problem on identical parallel machines with flexible and periodic maintenance. Each machine needs to be maintained periodically, and the interval of any two consecutive maintenance activities is in a given time window. Each job is owned by a selfish agent, whose objective is to minimize the completion time of its job. The system's objective is to minimize the makespan. We design an LPT-NF coordination mechanism based on the longest processing time (LPT) and next fit (NF) rules. Then we give a greedy LPT-NF algorithm to obtain the Nash Equilibrium, and the lower bound of the optimal solution. Finally, we evaluate the performance of the LPT-NF coordination mechanism with a set of computational experiments, and analyze the impact of maintenance time, the minimum maintenance spacing, and the maximum maintenance spacing on the Nash Equilibrium solutions. The results show that the Nash Equilibrium is very close to the optimal solution for all the experiments. In addition, it is shown that the LPT-NF coordination mechanism works well and tends to perform better when facing the larger-scale scenarios.",cui-lin zhang,coordination mechanism,2018.0,10.1109/ICNSC.2018.8361314,"2018 IEEE 15th International Conference on Networking, Sensing and Control (ICNSC)",Zhang2018,False,,IEEE,Not available,A coordination mechanism for scheduling game on parallel machines with flexible maintenance,c8ddbd676e1628cc9d1da4d7a32430a4,https://ieeexplore.ieee.org/document/8361314/
1920,"This paper considers a scheduling game problem on identical parallel machines with flexible and periodic maintenance. Each machine needs to be maintained periodically, and the interval of any two consecutive maintenance activities is in a given time window. Each job is owned by a selfish agent, whose objective is to minimize the completion time of its job. The system's objective is to minimize the makespan. We design an LPT-NF coordination mechanism based on the longest processing time (LPT) and next fit (NF) rules. Then we give a greedy LPT-NF algorithm to obtain the Nash Equilibrium, and the lower bound of the optimal solution. Finally, we evaluate the performance of the LPT-NF coordination mechanism with a set of computational experiments, and analyze the impact of maintenance time, the minimum maintenance spacing, and the maximum maintenance spacing on the Nash Equilibrium solutions. The results show that the Nash Equilibrium is very close to the optimal solution for all the experiments. In addition, it is shown that the LPT-NF coordination mechanism works well and tends to perform better when facing the larger-scale scenarios.",cui-lin zhang,Nash Equilibrium,2018.0,10.1109/ICNSC.2018.8361314,"2018 IEEE 15th International Conference on Networking, Sensing and Control (ICNSC)",Zhang2018,False,,IEEE,Not available,A coordination mechanism for scheduling game on parallel machines with flexible maintenance,c8ddbd676e1628cc9d1da4d7a32430a4,https://ieeexplore.ieee.org/document/8361314/
1921,"This paper considers a scheduling game problem on identical parallel machines with flexible and periodic maintenance. Each machine needs to be maintained periodically, and the interval of any two consecutive maintenance activities is in a given time window. Each job is owned by a selfish agent, whose objective is to minimize the completion time of its job. The system's objective is to minimize the makespan. We design an LPT-NF coordination mechanism based on the longest processing time (LPT) and next fit (NF) rules. Then we give a greedy LPT-NF algorithm to obtain the Nash Equilibrium, and the lower bound of the optimal solution. Finally, we evaluate the performance of the LPT-NF coordination mechanism with a set of computational experiments, and analyze the impact of maintenance time, the minimum maintenance spacing, and the maximum maintenance spacing on the Nash Equilibrium solutions. The results show that the Nash Equilibrium is very close to the optimal solution for all the experiments. In addition, it is shown that the LPT-NF coordination mechanism works well and tends to perform better when facing the larger-scale scenarios.",cui-lin zhang,Price of Anarchy,2018.0,10.1109/ICNSC.2018.8361314,"2018 IEEE 15th International Conference on Networking, Sensing and Control (ICNSC)",Zhang2018,False,,IEEE,Not available,A coordination mechanism for scheduling game on parallel machines with flexible maintenance,c8ddbd676e1628cc9d1da4d7a32430a4,https://ieeexplore.ieee.org/document/8361314/
1922,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Pricing,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
1923,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Routing,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
1924,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Relays,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
1925,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Telecommunication traffic,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
1926,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Spread spectrum communication,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
1927,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Network topology,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
1928,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
1929,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Oligopoly,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
1930,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Costs,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
1931,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Traffic control,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
1932,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Communication networks,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
1933,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Pricing,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
1934,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Routing,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
1935,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Relays,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
1936,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Telecommunication traffic,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
1937,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Spread spectrum communication,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
1938,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Network topology,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
1939,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
1940,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Oligopoly,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
1941,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Costs,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
1942,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Traffic control,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
1943,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Communication networks,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
1944,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",lingjie duan,Pricing,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
1945,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",lingjie duan,Investments,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
1946,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",lingjie duan,Costs,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
1947,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",lingjie duan,Resource management,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
1948,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",lingjie duan,Environmental economics,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
1949,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",lingjie duan,Frequency division multiplexing,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
1950,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
1951,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",lingjie duan,Communications Society,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
1952,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",lingjie duan,Engineering management,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
1953,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",lingjie duan,Government,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
1954,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",lingjie duan,Area measurement,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
1955,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",jianwei huang,Pricing,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
1956,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",jianwei huang,Investments,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
1957,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",jianwei huang,Costs,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
1958,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",jianwei huang,Resource management,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
1959,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",jianwei huang,Environmental economics,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
1960,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",jianwei huang,Frequency division multiplexing,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
1961,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
1962,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
1963,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",jianwei huang,Communications Society,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
1964,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",jianwei huang,Engineering management,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
1965,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",jianwei huang,Government,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
1966,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",jianwei huang,Area measurement,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
1967,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",biying shou,Pricing,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
1968,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",biying shou,Investments,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
1969,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",biying shou,Costs,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
1970,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",biying shou,Resource management,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
1971,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",biying shou,Environmental economics,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
1972,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",biying shou,Frequency division multiplexing,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
1973,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
1974,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",biying shou,Communications Society,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
1975,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",biying shou,Engineering management,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
1976,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",biying shou,Government,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
1977,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",biying shou,Area measurement,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
1978,"Several works have recently suggested to model the problem of coordinating the charging needs of a fleet of electric vehicles as a game, and have proposed distributed algorithms to coordinate the vehicles towards a Nash equilibrium of such game. However, Nash equilibria have been shown to posses desirable system-level properties only in simplified cases. In this letter, we use the concept of price of anarchy (PoA) to analyze the inefficiency of Nash equilibria when compared to the social optimum solution. More precisely, we show that: 1) for linear price functions depending on all the charging instants, the PoA converges to one as the population of vehicles grows; 2) for price functions that depend only on the instantaneous demand, the PoA converges to one if the price function takes the form of a positive pure monomial; and 3) for general classes of price functions, the asymptotic PoA can be bounded. For finite populations, we additionally provide a bound on the PoA as a function of the number vehicles in the system. We support the theoretical findings by means of numerical simulations.",dario paccagnan,Game theory,2018.0,10.1109/LCSYS.2018.2845674,IEEE Control Systems Letters,Paccagnan2018,False,,IEEE,Not available,On the Efficiency of Nash Equilibria in Aggregative Charging Games,7a18e44e1af260dc8d75edee6a2b0880,https://ieeexplore.ieee.org/document/8375654/
1979,"Several works have recently suggested to model the problem of coordinating the charging needs of a fleet of electric vehicles as a game, and have proposed distributed algorithms to coordinate the vehicles towards a Nash equilibrium of such game. However, Nash equilibria have been shown to posses desirable system-level properties only in simplified cases. In this letter, we use the concept of price of anarchy (PoA) to analyze the inefficiency of Nash equilibria when compared to the social optimum solution. More precisely, we show that: 1) for linear price functions depending on all the charging instants, the PoA converges to one as the population of vehicles grows; 2) for price functions that depend only on the instantaneous demand, the PoA converges to one if the price function takes the form of a positive pure monomial; and 3) for general classes of price functions, the asymptotic PoA can be bounded. For finite populations, we additionally provide a bound on the PoA as a function of the number vehicles in the system. We support the theoretical findings by means of numerical simulations.",dario paccagnan,optimization,2018.0,10.1109/LCSYS.2018.2845674,IEEE Control Systems Letters,Paccagnan2018,False,,IEEE,Not available,On the Efficiency of Nash Equilibria in Aggregative Charging Games,7a18e44e1af260dc8d75edee6a2b0880,https://ieeexplore.ieee.org/document/8375654/
1980,"Several works have recently suggested to model the problem of coordinating the charging needs of a fleet of electric vehicles as a game, and have proposed distributed algorithms to coordinate the vehicles towards a Nash equilibrium of such game. However, Nash equilibria have been shown to posses desirable system-level properties only in simplified cases. In this letter, we use the concept of price of anarchy (PoA) to analyze the inefficiency of Nash equilibria when compared to the social optimum solution. More precisely, we show that: 1) for linear price functions depending on all the charging instants, the PoA converges to one as the population of vehicles grows; 2) for price functions that depend only on the instantaneous demand, the PoA converges to one if the price function takes the form of a positive pure monomial; and 3) for general classes of price functions, the asymptotic PoA can be bounded. For finite populations, we additionally provide a bound on the PoA as a function of the number vehicles in the system. We support the theoretical findings by means of numerical simulations.",dario paccagnan,large-scale systems,2018.0,10.1109/LCSYS.2018.2845674,IEEE Control Systems Letters,Paccagnan2018,False,,IEEE,Not available,On the Efficiency of Nash Equilibria in Aggregative Charging Games,7a18e44e1af260dc8d75edee6a2b0880,https://ieeexplore.ieee.org/document/8375654/
1981,"Several works have recently suggested to model the problem of coordinating the charging needs of a fleet of electric vehicles as a game, and have proposed distributed algorithms to coordinate the vehicles towards a Nash equilibrium of such game. However, Nash equilibria have been shown to posses desirable system-level properties only in simplified cases. In this letter, we use the concept of price of anarchy (PoA) to analyze the inefficiency of Nash equilibria when compared to the social optimum solution. More precisely, we show that: 1) for linear price functions depending on all the charging instants, the PoA converges to one as the population of vehicles grows; 2) for price functions that depend only on the instantaneous demand, the PoA converges to one if the price function takes the form of a positive pure monomial; and 3) for general classes of price functions, the asymptotic PoA can be bounded. For finite populations, we additionally provide a bound on the PoA as a function of the number vehicles in the system. We support the theoretical findings by means of numerical simulations.",francesca parise,Game theory,2018.0,10.1109/LCSYS.2018.2845674,IEEE Control Systems Letters,Paccagnan2018,False,,IEEE,Not available,On the Efficiency of Nash Equilibria in Aggregative Charging Games,7a18e44e1af260dc8d75edee6a2b0880,https://ieeexplore.ieee.org/document/8375654/
1982,"Several works have recently suggested to model the problem of coordinating the charging needs of a fleet of electric vehicles as a game, and have proposed distributed algorithms to coordinate the vehicles towards a Nash equilibrium of such game. However, Nash equilibria have been shown to posses desirable system-level properties only in simplified cases. In this letter, we use the concept of price of anarchy (PoA) to analyze the inefficiency of Nash equilibria when compared to the social optimum solution. More precisely, we show that: 1) for linear price functions depending on all the charging instants, the PoA converges to one as the population of vehicles grows; 2) for price functions that depend only on the instantaneous demand, the PoA converges to one if the price function takes the form of a positive pure monomial; and 3) for general classes of price functions, the asymptotic PoA can be bounded. For finite populations, we additionally provide a bound on the PoA as a function of the number vehicles in the system. We support the theoretical findings by means of numerical simulations.",francesca parise,optimization,2018.0,10.1109/LCSYS.2018.2845674,IEEE Control Systems Letters,Paccagnan2018,False,,IEEE,Not available,On the Efficiency of Nash Equilibria in Aggregative Charging Games,7a18e44e1af260dc8d75edee6a2b0880,https://ieeexplore.ieee.org/document/8375654/
1983,"Several works have recently suggested to model the problem of coordinating the charging needs of a fleet of electric vehicles as a game, and have proposed distributed algorithms to coordinate the vehicles towards a Nash equilibrium of such game. However, Nash equilibria have been shown to posses desirable system-level properties only in simplified cases. In this letter, we use the concept of price of anarchy (PoA) to analyze the inefficiency of Nash equilibria when compared to the social optimum solution. More precisely, we show that: 1) for linear price functions depending on all the charging instants, the PoA converges to one as the population of vehicles grows; 2) for price functions that depend only on the instantaneous demand, the PoA converges to one if the price function takes the form of a positive pure monomial; and 3) for general classes of price functions, the asymptotic PoA can be bounded. For finite populations, we additionally provide a bound on the PoA as a function of the number vehicles in the system. We support the theoretical findings by means of numerical simulations.",francesca parise,large-scale systems,2018.0,10.1109/LCSYS.2018.2845674,IEEE Control Systems Letters,Paccagnan2018,False,,IEEE,Not available,On the Efficiency of Nash Equilibria in Aggregative Charging Games,7a18e44e1af260dc8d75edee6a2b0880,https://ieeexplore.ieee.org/document/8375654/
1984,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
1985,"Several works have recently suggested to model the problem of coordinating the charging needs of a fleet of electric vehicles as a game, and have proposed distributed algorithms to coordinate the vehicles towards a Nash equilibrium of such game. However, Nash equilibria have been shown to posses desirable system-level properties only in simplified cases. In this letter, we use the concept of price of anarchy (PoA) to analyze the inefficiency of Nash equilibria when compared to the social optimum solution. More precisely, we show that: 1) for linear price functions depending on all the charging instants, the PoA converges to one as the population of vehicles grows; 2) for price functions that depend only on the instantaneous demand, the PoA converges to one if the price function takes the form of a positive pure monomial; and 3) for general classes of price functions, the asymptotic PoA can be bounded. For finite populations, we additionally provide a bound on the PoA as a function of the number vehicles in the system. We support the theoretical findings by means of numerical simulations.",john lygeros,Game theory,2018.0,10.1109/LCSYS.2018.2845674,IEEE Control Systems Letters,Paccagnan2018,False,,IEEE,Not available,On the Efficiency of Nash Equilibria in Aggregative Charging Games,7a18e44e1af260dc8d75edee6a2b0880,https://ieeexplore.ieee.org/document/8375654/
1986,"Several works have recently suggested to model the problem of coordinating the charging needs of a fleet of electric vehicles as a game, and have proposed distributed algorithms to coordinate the vehicles towards a Nash equilibrium of such game. However, Nash equilibria have been shown to posses desirable system-level properties only in simplified cases. In this letter, we use the concept of price of anarchy (PoA) to analyze the inefficiency of Nash equilibria when compared to the social optimum solution. More precisely, we show that: 1) for linear price functions depending on all the charging instants, the PoA converges to one as the population of vehicles grows; 2) for price functions that depend only on the instantaneous demand, the PoA converges to one if the price function takes the form of a positive pure monomial; and 3) for general classes of price functions, the asymptotic PoA can be bounded. For finite populations, we additionally provide a bound on the PoA as a function of the number vehicles in the system. We support the theoretical findings by means of numerical simulations.",john lygeros,optimization,2018.0,10.1109/LCSYS.2018.2845674,IEEE Control Systems Letters,Paccagnan2018,False,,IEEE,Not available,On the Efficiency of Nash Equilibria in Aggregative Charging Games,7a18e44e1af260dc8d75edee6a2b0880,https://ieeexplore.ieee.org/document/8375654/
1987,"Several works have recently suggested to model the problem of coordinating the charging needs of a fleet of electric vehicles as a game, and have proposed distributed algorithms to coordinate the vehicles towards a Nash equilibrium of such game. However, Nash equilibria have been shown to posses desirable system-level properties only in simplified cases. In this letter, we use the concept of price of anarchy (PoA) to analyze the inefficiency of Nash equilibria when compared to the social optimum solution. More precisely, we show that: 1) for linear price functions depending on all the charging instants, the PoA converges to one as the population of vehicles grows; 2) for price functions that depend only on the instantaneous demand, the PoA converges to one if the price function takes the form of a positive pure monomial; and 3) for general classes of price functions, the asymptotic PoA can be bounded. For finite populations, we additionally provide a bound on the PoA as a function of the number vehicles in the system. We support the theoretical findings by means of numerical simulations.",john lygeros,large-scale systems,2018.0,10.1109/LCSYS.2018.2845674,IEEE Control Systems Letters,Paccagnan2018,False,,IEEE,Not available,On the Efficiency of Nash Equilibria in Aggregative Charging Games,7a18e44e1af260dc8d75edee6a2b0880,https://ieeexplore.ieee.org/document/8375654/
1988,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",majed haddad,Heterogeneous network,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
1989,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",majed haddad,macro cell,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
1990,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",majed haddad,small cell,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
1991,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",majed haddad,WiFi,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
1992,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",majed haddad,network selection,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
1993,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",majed haddad,dynamic offset,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
1994,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",majed haddad,traffic steering,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
1995,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
1996,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",majed haddad,channel distribution information,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
1997,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",majed haddad,channel state information,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
1998,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",majed haddad,game theory,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
1999,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",majed haddad,price of anarchy.,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
2000,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",piotr wiecek,Heterogeneous network,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
2001,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",piotr wiecek,macro cell,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
2002,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",piotr wiecek,small cell,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
2003,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",piotr wiecek,WiFi,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
2004,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",piotr wiecek,network selection,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
2005,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",piotr wiecek,dynamic offset,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
2006,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
2007,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",piotr wiecek,traffic steering,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
2008,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",piotr wiecek,channel distribution information,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
2009,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",piotr wiecek,channel state information,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
2010,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",piotr wiecek,game theory,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
2011,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",piotr wiecek,price of anarchy.,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
2012,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",habib sidi,Heterogeneous network,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
2013,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",habib sidi,macro cell,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
2014,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",habib sidi,small cell,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
2015,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",habib sidi,WiFi,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
2016,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",habib sidi,network selection,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
2017,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
2018,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",habib sidi,dynamic offset,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
2019,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",habib sidi,traffic steering,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
2020,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",habib sidi,channel distribution information,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
2021,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",habib sidi,channel state information,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
2022,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",habib sidi,game theory,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
2023,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",habib sidi,price of anarchy.,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
2024,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",eitan altman,Heterogeneous network,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
2025,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",eitan altman,macro cell,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
2026,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",eitan altman,small cell,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
2027,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",eitan altman,WiFi,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
2028,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
2029,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",eitan altman,network selection,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
2030,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",eitan altman,dynamic offset,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
2031,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",eitan altman,traffic steering,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
2032,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",eitan altman,channel distribution information,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
2033,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",eitan altman,channel state information,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
2034,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",eitan altman,game theory,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
2035,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",eitan altman,price of anarchy.,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
2036,"In peer-to-peer storage systems, peers replicate each others' data in order to increase availability. If the matching is done centrally, the algorithm can optimize data availability in an equitable manner for all participants. However, if matching is decentralized, the peers' selfishness can greatly alter the results, leading to performance inequities that can render the system unreliable and thus ultimately unusable. We analyze the problem using both theoretical approaches (complexity analysis for the centralized system, game theory for the decentralized one) and simulation. We prove that the problem of optimizing availability in a centralized system is NP-hard. In decentralized settings, we show that the rational behavior of selfish peers will be to replicate only with similarly-available peers. Compared to the socially-optimal solution, highly available peers have their data availability increased at the expense of decreased data availability for less available peers. The price of anarchy is high: unbounded in one model, and linear with the number of time slots in the second model. We also propose centralized and decentralized heuristics that, according to our experiments, converge fast in the average case. The high price of anarchy means that a completely decentralized system could be too hostile for peers with low availability, who could never achieve satisfying replication parameters. Moreover, we experimentally show that even explicit consideration and exploitation of diurnal patterns of peer availability has a small effect on the data availability-except when the system has truly global scope. Yet a fully centralized system is infeasible, not only because of problems in information gathering, but also the complexity of optimizing availability. The solution to this dilemma is to create system-wide cooperation rules that allow a decentralized algorithm, but also limit the selfishness of the participants.",krzysztof rzadca,price of anarchy,2010.0,10.1109/ICDCS.2010.67,2010 IEEE 30th International Conference on Distributed Computing Systems,Rzadca2010,False,,IEEE,Not available,Replica Placement in P2P Storage: Complexity and Game Theoretic Analyses,460329b9e0ca072aecab540d5529a23f,https://ieeexplore.ieee.org/document/5541690/
2037,"In peer-to-peer storage systems, peers replicate each others' data in order to increase availability. If the matching is done centrally, the algorithm can optimize data availability in an equitable manner for all participants. However, if matching is decentralized, the peers' selfishness can greatly alter the results, leading to performance inequities that can render the system unreliable and thus ultimately unusable. We analyze the problem using both theoretical approaches (complexity analysis for the centralized system, game theory for the decentralized one) and simulation. We prove that the problem of optimizing availability in a centralized system is NP-hard. In decentralized settings, we show that the rational behavior of selfish peers will be to replicate only with similarly-available peers. Compared to the socially-optimal solution, highly available peers have their data availability increased at the expense of decreased data availability for less available peers. The price of anarchy is high: unbounded in one model, and linear with the number of time slots in the second model. We also propose centralized and decentralized heuristics that, according to our experiments, converge fast in the average case. The high price of anarchy means that a completely decentralized system could be too hostile for peers with low availability, who could never achieve satisfying replication parameters. Moreover, we experimentally show that even explicit consideration and exploitation of diurnal patterns of peer availability has a small effect on the data availability-except when the system has truly global scope. Yet a fully centralized system is infeasible, not only because of problems in information gathering, but also the complexity of optimizing availability. The solution to this dilemma is to create system-wide cooperation rules that allow a decentralized algorithm, but also limit the selfishness of the participants.",krzysztof rzadca,equitable optimization,2010.0,10.1109/ICDCS.2010.67,2010 IEEE 30th International Conference on Distributed Computing Systems,Rzadca2010,False,,IEEE,Not available,Replica Placement in P2P Storage: Complexity and Game Theoretic Analyses,460329b9e0ca072aecab540d5529a23f,https://ieeexplore.ieee.org/document/5541690/
2038,"In peer-to-peer storage systems, peers replicate each others' data in order to increase availability. If the matching is done centrally, the algorithm can optimize data availability in an equitable manner for all participants. However, if matching is decentralized, the peers' selfishness can greatly alter the results, leading to performance inequities that can render the system unreliable and thus ultimately unusable. We analyze the problem using both theoretical approaches (complexity analysis for the centralized system, game theory for the decentralized one) and simulation. We prove that the problem of optimizing availability in a centralized system is NP-hard. In decentralized settings, we show that the rational behavior of selfish peers will be to replicate only with similarly-available peers. Compared to the socially-optimal solution, highly available peers have their data availability increased at the expense of decreased data availability for less available peers. The price of anarchy is high: unbounded in one model, and linear with the number of time slots in the second model. We also propose centralized and decentralized heuristics that, according to our experiments, converge fast in the average case. The high price of anarchy means that a completely decentralized system could be too hostile for peers with low availability, who could never achieve satisfying replication parameters. Moreover, we experimentally show that even explicit consideration and exploitation of diurnal patterns of peer availability has a small effect on the data availability-except when the system has truly global scope. Yet a fully centralized system is infeasible, not only because of problems in information gathering, but also the complexity of optimizing availability. The solution to this dilemma is to create system-wide cooperation rules that allow a decentralized algorithm, but also limit the selfishness of the participants.",krzysztof rzadca,distributed storage,2010.0,10.1109/ICDCS.2010.67,2010 IEEE 30th International Conference on Distributed Computing Systems,Rzadca2010,False,,IEEE,Not available,Replica Placement in P2P Storage: Complexity and Game Theoretic Analyses,460329b9e0ca072aecab540d5529a23f,https://ieeexplore.ieee.org/document/5541690/
2039,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
2040,"In peer-to-peer storage systems, peers replicate each others' data in order to increase availability. If the matching is done centrally, the algorithm can optimize data availability in an equitable manner for all participants. However, if matching is decentralized, the peers' selfishness can greatly alter the results, leading to performance inequities that can render the system unreliable and thus ultimately unusable. We analyze the problem using both theoretical approaches (complexity analysis for the centralized system, game theory for the decentralized one) and simulation. We prove that the problem of optimizing availability in a centralized system is NP-hard. In decentralized settings, we show that the rational behavior of selfish peers will be to replicate only with similarly-available peers. Compared to the socially-optimal solution, highly available peers have their data availability increased at the expense of decreased data availability for less available peers. The price of anarchy is high: unbounded in one model, and linear with the number of time slots in the second model. We also propose centralized and decentralized heuristics that, according to our experiments, converge fast in the average case. The high price of anarchy means that a completely decentralized system could be too hostile for peers with low availability, who could never achieve satisfying replication parameters. Moreover, we experimentally show that even explicit consideration and exploitation of diurnal patterns of peer availability has a small effect on the data availability-except when the system has truly global scope. Yet a fully centralized system is infeasible, not only because of problems in information gathering, but also the complexity of optimizing availability. The solution to this dilemma is to create system-wide cooperation rules that allow a decentralized algorithm, but also limit the selfishness of the participants.",anwitaman datta,price of anarchy,2010.0,10.1109/ICDCS.2010.67,2010 IEEE 30th International Conference on Distributed Computing Systems,Rzadca2010,False,,IEEE,Not available,Replica Placement in P2P Storage: Complexity and Game Theoretic Analyses,460329b9e0ca072aecab540d5529a23f,https://ieeexplore.ieee.org/document/5541690/
2041,"In peer-to-peer storage systems, peers replicate each others' data in order to increase availability. If the matching is done centrally, the algorithm can optimize data availability in an equitable manner for all participants. However, if matching is decentralized, the peers' selfishness can greatly alter the results, leading to performance inequities that can render the system unreliable and thus ultimately unusable. We analyze the problem using both theoretical approaches (complexity analysis for the centralized system, game theory for the decentralized one) and simulation. We prove that the problem of optimizing availability in a centralized system is NP-hard. In decentralized settings, we show that the rational behavior of selfish peers will be to replicate only with similarly-available peers. Compared to the socially-optimal solution, highly available peers have their data availability increased at the expense of decreased data availability for less available peers. The price of anarchy is high: unbounded in one model, and linear with the number of time slots in the second model. We also propose centralized and decentralized heuristics that, according to our experiments, converge fast in the average case. The high price of anarchy means that a completely decentralized system could be too hostile for peers with low availability, who could never achieve satisfying replication parameters. Moreover, we experimentally show that even explicit consideration and exploitation of diurnal patterns of peer availability has a small effect on the data availability-except when the system has truly global scope. Yet a fully centralized system is infeasible, not only because of problems in information gathering, but also the complexity of optimizing availability. The solution to this dilemma is to create system-wide cooperation rules that allow a decentralized algorithm, but also limit the selfishness of the participants.",anwitaman datta,equitable optimization,2010.0,10.1109/ICDCS.2010.67,2010 IEEE 30th International Conference on Distributed Computing Systems,Rzadca2010,False,,IEEE,Not available,Replica Placement in P2P Storage: Complexity and Game Theoretic Analyses,460329b9e0ca072aecab540d5529a23f,https://ieeexplore.ieee.org/document/5541690/
2042,"In peer-to-peer storage systems, peers replicate each others' data in order to increase availability. If the matching is done centrally, the algorithm can optimize data availability in an equitable manner for all participants. However, if matching is decentralized, the peers' selfishness can greatly alter the results, leading to performance inequities that can render the system unreliable and thus ultimately unusable. We analyze the problem using both theoretical approaches (complexity analysis for the centralized system, game theory for the decentralized one) and simulation. We prove that the problem of optimizing availability in a centralized system is NP-hard. In decentralized settings, we show that the rational behavior of selfish peers will be to replicate only with similarly-available peers. Compared to the socially-optimal solution, highly available peers have their data availability increased at the expense of decreased data availability for less available peers. The price of anarchy is high: unbounded in one model, and linear with the number of time slots in the second model. We also propose centralized and decentralized heuristics that, according to our experiments, converge fast in the average case. The high price of anarchy means that a completely decentralized system could be too hostile for peers with low availability, who could never achieve satisfying replication parameters. Moreover, we experimentally show that even explicit consideration and exploitation of diurnal patterns of peer availability has a small effect on the data availability-except when the system has truly global scope. Yet a fully centralized system is infeasible, not only because of problems in information gathering, but also the complexity of optimizing availability. The solution to this dilemma is to create system-wide cooperation rules that allow a decentralized algorithm, but also limit the selfishness of the participants.",anwitaman datta,distributed storage,2010.0,10.1109/ICDCS.2010.67,2010 IEEE 30th International Conference on Distributed Computing Systems,Rzadca2010,False,,IEEE,Not available,Replica Placement in P2P Storage: Complexity and Game Theoretic Analyses,460329b9e0ca072aecab540d5529a23f,https://ieeexplore.ieee.org/document/5541690/
2043,"In peer-to-peer storage systems, peers replicate each others' data in order to increase availability. If the matching is done centrally, the algorithm can optimize data availability in an equitable manner for all participants. However, if matching is decentralized, the peers' selfishness can greatly alter the results, leading to performance inequities that can render the system unreliable and thus ultimately unusable. We analyze the problem using both theoretical approaches (complexity analysis for the centralized system, game theory for the decentralized one) and simulation. We prove that the problem of optimizing availability in a centralized system is NP-hard. In decentralized settings, we show that the rational behavior of selfish peers will be to replicate only with similarly-available peers. Compared to the socially-optimal solution, highly available peers have their data availability increased at the expense of decreased data availability for less available peers. The price of anarchy is high: unbounded in one model, and linear with the number of time slots in the second model. We also propose centralized and decentralized heuristics that, according to our experiments, converge fast in the average case. The high price of anarchy means that a completely decentralized system could be too hostile for peers with low availability, who could never achieve satisfying replication parameters. Moreover, we experimentally show that even explicit consideration and exploitation of diurnal patterns of peer availability has a small effect on the data availability-except when the system has truly global scope. Yet a fully centralized system is infeasible, not only because of problems in information gathering, but also the complexity of optimizing availability. The solution to this dilemma is to create system-wide cooperation rules that allow a decentralized algorithm, but also limit the selfishness of the participants.",sonja buchegger,price of anarchy,2010.0,10.1109/ICDCS.2010.67,2010 IEEE 30th International Conference on Distributed Computing Systems,Rzadca2010,False,,IEEE,Not available,Replica Placement in P2P Storage: Complexity and Game Theoretic Analyses,460329b9e0ca072aecab540d5529a23f,https://ieeexplore.ieee.org/document/5541690/
2044,"In peer-to-peer storage systems, peers replicate each others' data in order to increase availability. If the matching is done centrally, the algorithm can optimize data availability in an equitable manner for all participants. However, if matching is decentralized, the peers' selfishness can greatly alter the results, leading to performance inequities that can render the system unreliable and thus ultimately unusable. We analyze the problem using both theoretical approaches (complexity analysis for the centralized system, game theory for the decentralized one) and simulation. We prove that the problem of optimizing availability in a centralized system is NP-hard. In decentralized settings, we show that the rational behavior of selfish peers will be to replicate only with similarly-available peers. Compared to the socially-optimal solution, highly available peers have their data availability increased at the expense of decreased data availability for less available peers. The price of anarchy is high: unbounded in one model, and linear with the number of time slots in the second model. We also propose centralized and decentralized heuristics that, according to our experiments, converge fast in the average case. The high price of anarchy means that a completely decentralized system could be too hostile for peers with low availability, who could never achieve satisfying replication parameters. Moreover, we experimentally show that even explicit consideration and exploitation of diurnal patterns of peer availability has a small effect on the data availability-except when the system has truly global scope. Yet a fully centralized system is infeasible, not only because of problems in information gathering, but also the complexity of optimizing availability. The solution to this dilemma is to create system-wide cooperation rules that allow a decentralized algorithm, but also limit the selfishness of the participants.",sonja buchegger,equitable optimization,2010.0,10.1109/ICDCS.2010.67,2010 IEEE 30th International Conference on Distributed Computing Systems,Rzadca2010,False,,IEEE,Not available,Replica Placement in P2P Storage: Complexity and Game Theoretic Analyses,460329b9e0ca072aecab540d5529a23f,https://ieeexplore.ieee.org/document/5541690/
2045,"In peer-to-peer storage systems, peers replicate each others' data in order to increase availability. If the matching is done centrally, the algorithm can optimize data availability in an equitable manner for all participants. However, if matching is decentralized, the peers' selfishness can greatly alter the results, leading to performance inequities that can render the system unreliable and thus ultimately unusable. We analyze the problem using both theoretical approaches (complexity analysis for the centralized system, game theory for the decentralized one) and simulation. We prove that the problem of optimizing availability in a centralized system is NP-hard. In decentralized settings, we show that the rational behavior of selfish peers will be to replicate only with similarly-available peers. Compared to the socially-optimal solution, highly available peers have their data availability increased at the expense of decreased data availability for less available peers. The price of anarchy is high: unbounded in one model, and linear with the number of time slots in the second model. We also propose centralized and decentralized heuristics that, according to our experiments, converge fast in the average case. The high price of anarchy means that a completely decentralized system could be too hostile for peers with low availability, who could never achieve satisfying replication parameters. Moreover, we experimentally show that even explicit consideration and exploitation of diurnal patterns of peer availability has a small effect on the data availability-except when the system has truly global scope. Yet a fully centralized system is infeasible, not only because of problems in information gathering, but also the complexity of optimizing availability. The solution to this dilemma is to create system-wide cooperation rules that allow a decentralized algorithm, but also limit the selfishness of the participants.",sonja buchegger,distributed storage,2010.0,10.1109/ICDCS.2010.67,2010 IEEE 30th International Conference on Distributed Computing Systems,Rzadca2010,False,,IEEE,Not available,Replica Placement in P2P Storage: Complexity and Game Theoretic Analyses,460329b9e0ca072aecab540d5529a23f,https://ieeexplore.ieee.org/document/5541690/
2046,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",s. etesami,Games,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
2047,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",s. etesami,Batteries,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
2048,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",s. etesami,Charging stations,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
2049,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",s. etesami,Routing,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
2050,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
2051,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",s. etesami,Smart grids,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
2052,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",s. etesami,Pricing,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
2053,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",s. etesami,Roads,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
2054,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",walid saad,Games,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
2055,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",walid saad,Batteries,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
2056,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",walid saad,Charging stations,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
2057,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",walid saad,Routing,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
2058,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",walid saad,Smart grids,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
2059,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",walid saad,Pricing,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
2060,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",walid saad,Roads,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
2061,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
2062,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",narayan mandayam,Games,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
2063,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",narayan mandayam,Batteries,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
2064,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",narayan mandayam,Charging stations,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
2065,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",narayan mandayam,Routing,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
2066,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",narayan mandayam,Smart grids,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
2067,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",narayan mandayam,Pricing,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
2068,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",narayan mandayam,Roads,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
2069,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",h. poor,Games,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
2070,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",h. poor,Batteries,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
2071,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",h. poor,Charging stations,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
2072,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
2073,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
2074,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
2075,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",h. poor,Routing,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
2076,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",h. poor,Smart grids,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
2077,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",h. poor,Pricing,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
2078,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",h. poor,Roads,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
2079,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",nassim kaci,Quality of service,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
2080,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",nassim kaci,Telecommunications,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
2081,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",nassim kaci,Costs,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
2082,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",nassim kaci,Finance,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
2083,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",nassim kaci,Loss measurement,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
2084,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",nassim kaci,Mobile computing,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
2085,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
2086,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",nassim kaci,Wireless networks,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
2087,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",nassim kaci,Pricing,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
2088,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",nassim kaci,Wireless communication,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
2089,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",nassim kaci,Communications technology,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
2090,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",patrick maille,Quality of service,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
2091,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",patrick maille,Telecommunications,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
2092,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",patrick maille,Costs,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
2093,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",patrick maille,Finance,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
2094,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",patrick maille,Loss measurement,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
2095,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",patrick maille,Mobile computing,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
2096,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
2097,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",patrick maille,Wireless networks,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
2098,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",patrick maille,Pricing,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
2099,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",patrick maille,Wireless communication,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
2100,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",patrick maille,Communications technology,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
2101,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",jean-marie bonnin,Quality of service,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
2102,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",jean-marie bonnin,Telecommunications,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
2103,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",jean-marie bonnin,Costs,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
2104,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",jean-marie bonnin,Finance,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
2105,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",jean-marie bonnin,Loss measurement,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
2106,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",jean-marie bonnin,Mobile computing,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
2107,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
2108,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",jean-marie bonnin,Wireless networks,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
2109,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",jean-marie bonnin,Pricing,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
2110,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",jean-marie bonnin,Wireless communication,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
2111,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",jean-marie bonnin,Communications technology,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
2112,"In self-organized wireless network, such as ad hoc network, sensor network or mesh network, nodes are independent individuals which have different benefit; Therefore, selfish nodes refuse to forward packets for other nodes in order to save energy which causes the network fault. At the same time, some nodes may be malicious, whose aim is to damage the network. In this paper, we analyze the cooperation stimulation and security in self-organized wireless networks under a game theoretic framework. We first analyze a four node wireless network in which nodes share the channel by relaying for others during its idle periods in order to help the other nodes, each node has to use a part of its available channel capacity. And then, the fault tolerance and security problem is modeled as a non-cooperative game in which each player maximizes its own utility function. The goal of the game is to maximize the utility function in the giving condition in order to get better network efficiency. At last, for characterizing the efficiency of Nash equilibria, we analyze the so called price of anarchy, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Our results show that the players can get the biggest payoff if they obey cooperation strategy.",jing chen,Game theory,2009.0,10.1109/MINES.2009.113,2009 International Conference on Multimedia Information Networking and Security,Chen2009,False,,IEEE,Not available,Fault Tolerance and Security in Forwarding Packets Using Game Theory,22012ee60dafefdbdfe2deb9566ef4eb,https://ieeexplore.ieee.org/document/5370999/
2113,"In self-organized wireless network, such as ad hoc network, sensor network or mesh network, nodes are independent individuals which have different benefit; Therefore, selfish nodes refuse to forward packets for other nodes in order to save energy which causes the network fault. At the same time, some nodes may be malicious, whose aim is to damage the network. In this paper, we analyze the cooperation stimulation and security in self-organized wireless networks under a game theoretic framework. We first analyze a four node wireless network in which nodes share the channel by relaying for others during its idle periods in order to help the other nodes, each node has to use a part of its available channel capacity. And then, the fault tolerance and security problem is modeled as a non-cooperative game in which each player maximizes its own utility function. The goal of the game is to maximize the utility function in the giving condition in order to get better network efficiency. At last, for characterizing the efficiency of Nash equilibria, we analyze the so called price of anarchy, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Our results show that the players can get the biggest payoff if they obey cooperation strategy.",jing chen,Fault Tolerance,2009.0,10.1109/MINES.2009.113,2009 International Conference on Multimedia Information Networking and Security,Chen2009,False,,IEEE,Not available,Fault Tolerance and Security in Forwarding Packets Using Game Theory,22012ee60dafefdbdfe2deb9566ef4eb,https://ieeexplore.ieee.org/document/5370999/
2114,"In self-organized wireless network, such as ad hoc network, sensor network or mesh network, nodes are independent individuals which have different benefit; Therefore, selfish nodes refuse to forward packets for other nodes in order to save energy which causes the network fault. At the same time, some nodes may be malicious, whose aim is to damage the network. In this paper, we analyze the cooperation stimulation and security in self-organized wireless networks under a game theoretic framework. We first analyze a four node wireless network in which nodes share the channel by relaying for others during its idle periods in order to help the other nodes, each node has to use a part of its available channel capacity. And then, the fault tolerance and security problem is modeled as a non-cooperative game in which each player maximizes its own utility function. The goal of the game is to maximize the utility function in the giving condition in order to get better network efficiency. At last, for characterizing the efficiency of Nash equilibria, we analyze the so called price of anarchy, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Our results show that the players can get the biggest payoff if they obey cooperation strategy.",jing chen,Security,2009.0,10.1109/MINES.2009.113,2009 International Conference on Multimedia Information Networking and Security,Chen2009,False,,IEEE,Not available,Fault Tolerance and Security in Forwarding Packets Using Game Theory,22012ee60dafefdbdfe2deb9566ef4eb,https://ieeexplore.ieee.org/document/5370999/
2115,"In self-organized wireless network, such as ad hoc network, sensor network or mesh network, nodes are independent individuals which have different benefit; Therefore, selfish nodes refuse to forward packets for other nodes in order to save energy which causes the network fault. At the same time, some nodes may be malicious, whose aim is to damage the network. In this paper, we analyze the cooperation stimulation and security in self-organized wireless networks under a game theoretic framework. We first analyze a four node wireless network in which nodes share the channel by relaying for others during its idle periods in order to help the other nodes, each node has to use a part of its available channel capacity. And then, the fault tolerance and security problem is modeled as a non-cooperative game in which each player maximizes its own utility function. The goal of the game is to maximize the utility function in the giving condition in order to get better network efficiency. At last, for characterizing the efficiency of Nash equilibria, we analyze the so called price of anarchy, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Our results show that the players can get the biggest payoff if they obey cooperation strategy.",ruiying du,Game theory,2009.0,10.1109/MINES.2009.113,2009 International Conference on Multimedia Information Networking and Security,Chen2009,False,,IEEE,Not available,Fault Tolerance and Security in Forwarding Packets Using Game Theory,22012ee60dafefdbdfe2deb9566ef4eb,https://ieeexplore.ieee.org/document/5370999/
2116,"In self-organized wireless network, such as ad hoc network, sensor network or mesh network, nodes are independent individuals which have different benefit; Therefore, selfish nodes refuse to forward packets for other nodes in order to save energy which causes the network fault. At the same time, some nodes may be malicious, whose aim is to damage the network. In this paper, we analyze the cooperation stimulation and security in self-organized wireless networks under a game theoretic framework. We first analyze a four node wireless network in which nodes share the channel by relaying for others during its idle periods in order to help the other nodes, each node has to use a part of its available channel capacity. And then, the fault tolerance and security problem is modeled as a non-cooperative game in which each player maximizes its own utility function. The goal of the game is to maximize the utility function in the giving condition in order to get better network efficiency. At last, for characterizing the efficiency of Nash equilibria, we analyze the so called price of anarchy, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Our results show that the players can get the biggest payoff if they obey cooperation strategy.",ruiying du,Fault Tolerance,2009.0,10.1109/MINES.2009.113,2009 International Conference on Multimedia Information Networking and Security,Chen2009,False,,IEEE,Not available,Fault Tolerance and Security in Forwarding Packets Using Game Theory,22012ee60dafefdbdfe2deb9566ef4eb,https://ieeexplore.ieee.org/document/5370999/
2117,"In self-organized wireless network, such as ad hoc network, sensor network or mesh network, nodes are independent individuals which have different benefit; Therefore, selfish nodes refuse to forward packets for other nodes in order to save energy which causes the network fault. At the same time, some nodes may be malicious, whose aim is to damage the network. In this paper, we analyze the cooperation stimulation and security in self-organized wireless networks under a game theoretic framework. We first analyze a four node wireless network in which nodes share the channel by relaying for others during its idle periods in order to help the other nodes, each node has to use a part of its available channel capacity. And then, the fault tolerance and security problem is modeled as a non-cooperative game in which each player maximizes its own utility function. The goal of the game is to maximize the utility function in the giving condition in order to get better network efficiency. At last, for characterizing the efficiency of Nash equilibria, we analyze the so called price of anarchy, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Our results show that the players can get the biggest payoff if they obey cooperation strategy.",ruiying du,Security,2009.0,10.1109/MINES.2009.113,2009 International Conference on Multimedia Information Networking and Security,Chen2009,False,,IEEE,Not available,Fault Tolerance and Security in Forwarding Packets Using Game Theory,22012ee60dafefdbdfe2deb9566ef4eb,https://ieeexplore.ieee.org/document/5370999/
2118,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
2119,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",danilo ardagna,Cloud computing,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
2120,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",danilo ardagna,Game Theory,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
2121,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",danilo ardagna,resource allocation,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
2122,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",danilo ardagna,performance attributes,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
2123,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",danilo ardagna,client/server,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
2124,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",danilo ardagna,distributed applications,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
2125,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",danilo ardagna,quality concepts,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
2126,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",barbara panicucci,Cloud computing,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
2127,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",barbara panicucci,Game Theory,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
2128,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",barbara panicucci,resource allocation,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
2129,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
2130,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",barbara panicucci,performance attributes,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
2131,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",barbara panicucci,client/server,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
2132,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",barbara panicucci,distributed applications,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
2133,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",barbara panicucci,quality concepts,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
2134,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",mauro passacantando,Cloud computing,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
2135,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",mauro passacantando,Game Theory,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
2136,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",mauro passacantando,resource allocation,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
2137,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",mauro passacantando,performance attributes,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
2138,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",mauro passacantando,client/server,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
2139,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",mauro passacantando,distributed applications,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
2140,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
2141,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",mauro passacantando,quality concepts,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
2142,"In this paper, a class of non-cooperative games termed resource contention games is studied, modeled through multi-class Stochastic Flow Models (SFMs). We contrast the solutions between system-centric and user-centric optimization in this game setting, and illustrate the gap between the two solutions, which is commonly referred to as the “price of anarchy.”",christos cassandras,Games,2010.0,10.1109/EEEI.2010.5661913,2010 IEEE 26-th Convention of Electrical and Electronics Engineers in Israel,Cassandras2010,False,,IEEE,Not available,A Stochastic Hybrid Systems view at a class of non-cooperative games,270ecdf0f9a96ac464976a90b236c964,https://ieeexplore.ieee.org/document/5661913/
2143,"In this paper, a class of non-cooperative games termed resource contention games is studied, modeled through multi-class Stochastic Flow Models (SFMs). We contrast the solutions between system-centric and user-centric optimization in this game setting, and illustrate the gap between the two solutions, which is commonly referred to as the “price of anarchy.”",christos cassandras,Stochastic processes,2010.0,10.1109/EEEI.2010.5661913,2010 IEEE 26-th Convention of Electrical and Electronics Engineers in Israel,Cassandras2010,False,,IEEE,Not available,A Stochastic Hybrid Systems view at a class of non-cooperative games,270ecdf0f9a96ac464976a90b236c964,https://ieeexplore.ieee.org/document/5661913/
2144,"In this paper, a class of non-cooperative games termed resource contention games is studied, modeled through multi-class Stochastic Flow Models (SFMs). We contrast the solutions between system-centric and user-centric optimization in this game setting, and illustrate the gap between the two solutions, which is commonly referred to as the “price of anarchy.”",christos cassandras,Optimization,2010.0,10.1109/EEEI.2010.5661913,2010 IEEE 26-th Convention of Electrical and Electronics Engineers in Israel,Cassandras2010,False,,IEEE,Not available,A Stochastic Hybrid Systems view at a class of non-cooperative games,270ecdf0f9a96ac464976a90b236c964,https://ieeexplore.ieee.org/document/5661913/
2145,"In this paper, a class of non-cooperative games termed resource contention games is studied, modeled through multi-class Stochastic Flow Models (SFMs). We contrast the solutions between system-centric and user-centric optimization in this game setting, and illustrate the gap between the two solutions, which is commonly referred to as the “price of anarchy.”",christos cassandras,Analytical models,2010.0,10.1109/EEEI.2010.5661913,2010 IEEE 26-th Convention of Electrical and Electronics Engineers in Israel,Cassandras2010,False,,IEEE,Not available,A Stochastic Hybrid Systems view at a class of non-cooperative games,270ecdf0f9a96ac464976a90b236c964,https://ieeexplore.ieee.org/document/5661913/
2146,"In this paper, a class of non-cooperative games termed resource contention games is studied, modeled through multi-class Stochastic Flow Models (SFMs). We contrast the solutions between system-centric and user-centric optimization in this game setting, and illustrate the gap between the two solutions, which is commonly referred to as the “price of anarchy.”",christos cassandras,Measurement,2010.0,10.1109/EEEI.2010.5661913,2010 IEEE 26-th Convention of Electrical and Electronics Engineers in Israel,Cassandras2010,False,,IEEE,Not available,A Stochastic Hybrid Systems view at a class of non-cooperative games,270ecdf0f9a96ac464976a90b236c964,https://ieeexplore.ieee.org/document/5661913/
2147,"In this paper, a class of non-cooperative games termed resource contention games is studied, modeled through multi-class Stochastic Flow Models (SFMs). We contrast the solutions between system-centric and user-centric optimization in this game setting, and illustrate the gap between the two solutions, which is commonly referred to as the “price of anarchy.”",christos cassandras,Lot sizing,2010.0,10.1109/EEEI.2010.5661913,2010 IEEE 26-th Convention of Electrical and Electronics Engineers in Israel,Cassandras2010,False,,IEEE,Not available,A Stochastic Hybrid Systems view at a class of non-cooperative games,270ecdf0f9a96ac464976a90b236c964,https://ieeexplore.ieee.org/document/5661913/
2148,"In this paper, a class of non-cooperative games termed resource contention games is studied, modeled through multi-class Stochastic Flow Models (SFMs). We contrast the solutions between system-centric and user-centric optimization in this game setting, and illustrate the gap between the two solutions, which is commonly referred to as the “price of anarchy.”",chen yao,Games,2010.0,10.1109/EEEI.2010.5661913,2010 IEEE 26-th Convention of Electrical and Electronics Engineers in Israel,Cassandras2010,False,,IEEE,Not available,A Stochastic Hybrid Systems view at a class of non-cooperative games,270ecdf0f9a96ac464976a90b236c964,https://ieeexplore.ieee.org/document/5661913/
2149,"In this paper, a class of non-cooperative games termed resource contention games is studied, modeled through multi-class Stochastic Flow Models (SFMs). We contrast the solutions between system-centric and user-centric optimization in this game setting, and illustrate the gap between the two solutions, which is commonly referred to as the “price of anarchy.”",chen yao,Stochastic processes,2010.0,10.1109/EEEI.2010.5661913,2010 IEEE 26-th Convention of Electrical and Electronics Engineers in Israel,Cassandras2010,False,,IEEE,Not available,A Stochastic Hybrid Systems view at a class of non-cooperative games,270ecdf0f9a96ac464976a90b236c964,https://ieeexplore.ieee.org/document/5661913/
2150,"In this paper, a class of non-cooperative games termed resource contention games is studied, modeled through multi-class Stochastic Flow Models (SFMs). We contrast the solutions between system-centric and user-centric optimization in this game setting, and illustrate the gap between the two solutions, which is commonly referred to as the “price of anarchy.”",chen yao,Optimization,2010.0,10.1109/EEEI.2010.5661913,2010 IEEE 26-th Convention of Electrical and Electronics Engineers in Israel,Cassandras2010,False,,IEEE,Not available,A Stochastic Hybrid Systems view at a class of non-cooperative games,270ecdf0f9a96ac464976a90b236c964,https://ieeexplore.ieee.org/document/5661913/
2151,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
2152,"In this paper, a class of non-cooperative games termed resource contention games is studied, modeled through multi-class Stochastic Flow Models (SFMs). We contrast the solutions between system-centric and user-centric optimization in this game setting, and illustrate the gap between the two solutions, which is commonly referred to as the “price of anarchy.”",chen yao,Analytical models,2010.0,10.1109/EEEI.2010.5661913,2010 IEEE 26-th Convention of Electrical and Electronics Engineers in Israel,Cassandras2010,False,,IEEE,Not available,A Stochastic Hybrid Systems view at a class of non-cooperative games,270ecdf0f9a96ac464976a90b236c964,https://ieeexplore.ieee.org/document/5661913/
2153,"In this paper, a class of non-cooperative games termed resource contention games is studied, modeled through multi-class Stochastic Flow Models (SFMs). We contrast the solutions between system-centric and user-centric optimization in this game setting, and illustrate the gap between the two solutions, which is commonly referred to as the “price of anarchy.”",chen yao,Measurement,2010.0,10.1109/EEEI.2010.5661913,2010 IEEE 26-th Convention of Electrical and Electronics Engineers in Israel,Cassandras2010,False,,IEEE,Not available,A Stochastic Hybrid Systems view at a class of non-cooperative games,270ecdf0f9a96ac464976a90b236c964,https://ieeexplore.ieee.org/document/5661913/
2154,"In this paper, a class of non-cooperative games termed resource contention games is studied, modeled through multi-class Stochastic Flow Models (SFMs). We contrast the solutions between system-centric and user-centric optimization in this game setting, and illustrate the gap between the two solutions, which is commonly referred to as the “price of anarchy.”",chen yao,Lot sizing,2010.0,10.1109/EEEI.2010.5661913,2010 IEEE 26-th Convention of Electrical and Electronics Engineers in Israel,Cassandras2010,False,,IEEE,Not available,A Stochastic Hybrid Systems view at a class of non-cooperative games,270ecdf0f9a96ac464976a90b236c964,https://ieeexplore.ieee.org/document/5661913/
2155,"We study the performance of noncooperative networks in light of three major topology design considerations, namely the price of establishing a link, path delay, and path proneness to congestion, the latter being modeled through the “relaying extent” of the nodes. We analyze these considerations and the tradeoffs between them from a game-theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. For the latter case, we indicate, by simulations, that practical scenarios tend to admit a Nash equilibrium. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by noncooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (“social”) agent with the ability to impose the initial configuration on the system.",amir nahir,Communication networks,2014.0,10.1109/TNET.2013.2254125,IEEE/ACM Transactions on Networking,Nahir2014,False,,IEEE,Not available,Topology Design of Communication Networks: A Game-Theoretic Perspective,034b94ff5f5e55fcb748e8600a316ad2,https://ieeexplore.ieee.org/document/6495502/
2156,"We study the performance of noncooperative networks in light of three major topology design considerations, namely the price of establishing a link, path delay, and path proneness to congestion, the latter being modeled through the “relaying extent” of the nodes. We analyze these considerations and the tradeoffs between them from a game-theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. For the latter case, we indicate, by simulations, that practical scenarios tend to admit a Nash equilibrium. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by noncooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (“social”) agent with the ability to impose the initial configuration on the system.",amir nahir,game theory,2014.0,10.1109/TNET.2013.2254125,IEEE/ACM Transactions on Networking,Nahir2014,False,,IEEE,Not available,Topology Design of Communication Networks: A Game-Theoretic Perspective,034b94ff5f5e55fcb748e8600a316ad2,https://ieeexplore.ieee.org/document/6495502/
2157,"We study the performance of noncooperative networks in light of three major topology design considerations, namely the price of establishing a link, path delay, and path proneness to congestion, the latter being modeled through the “relaying extent” of the nodes. We analyze these considerations and the tradeoffs between them from a game-theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. For the latter case, we indicate, by simulations, that practical scenarios tend to admit a Nash equilibrium. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by noncooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (“social”) agent with the ability to impose the initial configuration on the system.",ariel orda,Communication networks,2014.0,10.1109/TNET.2013.2254125,IEEE/ACM Transactions on Networking,Nahir2014,False,,IEEE,Not available,Topology Design of Communication Networks: A Game-Theoretic Perspective,034b94ff5f5e55fcb748e8600a316ad2,https://ieeexplore.ieee.org/document/6495502/
2158,"We study the performance of noncooperative networks in light of three major topology design considerations, namely the price of establishing a link, path delay, and path proneness to congestion, the latter being modeled through the “relaying extent” of the nodes. We analyze these considerations and the tradeoffs between them from a game-theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. For the latter case, we indicate, by simulations, that practical scenarios tend to admit a Nash equilibrium. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by noncooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (“social”) agent with the ability to impose the initial configuration on the system.",ariel orda,game theory,2014.0,10.1109/TNET.2013.2254125,IEEE/ACM Transactions on Networking,Nahir2014,False,,IEEE,Not available,Topology Design of Communication Networks: A Game-Theoretic Perspective,034b94ff5f5e55fcb748e8600a316ad2,https://ieeexplore.ieee.org/document/6495502/
2159,"We study the performance of noncooperative networks in light of three major topology design considerations, namely the price of establishing a link, path delay, and path proneness to congestion, the latter being modeled through the “relaying extent” of the nodes. We analyze these considerations and the tradeoffs between them from a game-theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. For the latter case, we indicate, by simulations, that practical scenarios tend to admit a Nash equilibrium. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by noncooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (“social”) agent with the ability to impose the initial configuration on the system.",ari freund,Communication networks,2014.0,10.1109/TNET.2013.2254125,IEEE/ACM Transactions on Networking,Nahir2014,False,,IEEE,Not available,Topology Design of Communication Networks: A Game-Theoretic Perspective,034b94ff5f5e55fcb748e8600a316ad2,https://ieeexplore.ieee.org/document/6495502/
2160,"We study the performance of noncooperative networks in light of three major topology design considerations, namely the price of establishing a link, path delay, and path proneness to congestion, the latter being modeled through the “relaying extent” of the nodes. We analyze these considerations and the tradeoffs between them from a game-theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. For the latter case, we indicate, by simulations, that practical scenarios tend to admit a Nash equilibrium. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by noncooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (“social”) agent with the ability to impose the initial configuration on the system.",ari freund,game theory,2014.0,10.1109/TNET.2013.2254125,IEEE/ACM Transactions on Networking,Nahir2014,False,,IEEE,Not available,Topology Design of Communication Networks: A Game-Theoretic Perspective,034b94ff5f5e55fcb748e8600a316ad2,https://ieeexplore.ieee.org/document/6495502/
2161,"An extensive body of recent work studies the welfare guarantees of simple and prevalent combinatorial auction formats, such as selling m items via simultaneous second price auctions (SiSPAs) [1], [2], [3]. These guarantees hold even when the auctions are repeatedly executed and the players use no-regret learning algorithms to choose their actions. Unfortunately, off-the-shelf no-regret learning algorithms for these auctions are computationally inefficient as the number of actions available to the players becomes exponential. We show that this obstacle is inevitable: there are no polynomial-time no-regret learning algorithms for SiSPAs, unless RP ⊇ NP, even when the bidders are unit-demand. Our lower bound raises the question of how good outcomes polynomially-bounded bidders may discover in such auctions. To answer this question, we propose a novel concept of learning in auctions, termed ""no-envy learning."" This notion is founded upon Walrasian equilibrium, and we show that it is both efficiently implementable and results in approximately optimal welfare, even when the bidders have valuations from the broad class of fractionally subadditive (XOS) valuations (assuming demand oracle access to the valuations) or coverage valuations (even without demand oracles). No-envy learning outcomes are a relaxation of no-regret learning outcomes, which maintain their approximate welfare optimality while endowing them with computational tractability. Our positive and negative results extend to several auction formats that have been studied in the literature via the smoothness paradigm. Our positive results for XOS valuations are enabled by a novel Follow-The-Perturbed-Leader algorithm for settings where the number of experts and states of nature are both infinite, and the payoff function of the learner is non-linear. We show that this algorithm has applications outside of auction settings, establishing significant gains in a recent application of no-regret learning in security games. Our efficient learning result for coverage valuations is based on a novel use of convex rounding schemes and a reduction to online convex optimization.",constantinos daskalakis,online learning,2016.0,10.1109/FOCS.2016.31,2016 IEEE 57th Annual Symposium on Foundations of Computer Science (FOCS),Daskalakis2016,False,,IEEE,Not available,"Learning in Auctions: Regret is Hard, Envy is Easy",9979bd1aa5340f782ca08d394f42d3e5,https://ieeexplore.ieee.org/document/7782934/
2162,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
2163,"An extensive body of recent work studies the welfare guarantees of simple and prevalent combinatorial auction formats, such as selling m items via simultaneous second price auctions (SiSPAs) [1], [2], [3]. These guarantees hold even when the auctions are repeatedly executed and the players use no-regret learning algorithms to choose their actions. Unfortunately, off-the-shelf no-regret learning algorithms for these auctions are computationally inefficient as the number of actions available to the players becomes exponential. We show that this obstacle is inevitable: there are no polynomial-time no-regret learning algorithms for SiSPAs, unless RP ⊇ NP, even when the bidders are unit-demand. Our lower bound raises the question of how good outcomes polynomially-bounded bidders may discover in such auctions. To answer this question, we propose a novel concept of learning in auctions, termed ""no-envy learning."" This notion is founded upon Walrasian equilibrium, and we show that it is both efficiently implementable and results in approximately optimal welfare, even when the bidders have valuations from the broad class of fractionally subadditive (XOS) valuations (assuming demand oracle access to the valuations) or coverage valuations (even without demand oracles). No-envy learning outcomes are a relaxation of no-regret learning outcomes, which maintain their approximate welfare optimality while endowing them with computational tractability. Our positive and negative results extend to several auction formats that have been studied in the literature via the smoothness paradigm. Our positive results for XOS valuations are enabled by a novel Follow-The-Perturbed-Leader algorithm for settings where the number of experts and states of nature are both infinite, and the payoff function of the learner is non-linear. We show that this algorithm has applications outside of auction settings, establishing significant gains in a recent application of no-regret learning in security games. Our efficient learning result for coverage valuations is based on a novel use of convex rounding schemes and a reduction to online convex optimization.",constantinos daskalakis,auctions,2016.0,10.1109/FOCS.2016.31,2016 IEEE 57th Annual Symposium on Foundations of Computer Science (FOCS),Daskalakis2016,False,,IEEE,Not available,"Learning in Auctions: Regret is Hard, Envy is Easy",9979bd1aa5340f782ca08d394f42d3e5,https://ieeexplore.ieee.org/document/7782934/
2164,"An extensive body of recent work studies the welfare guarantees of simple and prevalent combinatorial auction formats, such as selling m items via simultaneous second price auctions (SiSPAs) [1], [2], [3]. These guarantees hold even when the auctions are repeatedly executed and the players use no-regret learning algorithms to choose their actions. Unfortunately, off-the-shelf no-regret learning algorithms for these auctions are computationally inefficient as the number of actions available to the players becomes exponential. We show that this obstacle is inevitable: there are no polynomial-time no-regret learning algorithms for SiSPAs, unless RP ⊇ NP, even when the bidders are unit-demand. Our lower bound raises the question of how good outcomes polynomially-bounded bidders may discover in such auctions. To answer this question, we propose a novel concept of learning in auctions, termed ""no-envy learning."" This notion is founded upon Walrasian equilibrium, and we show that it is both efficiently implementable and results in approximately optimal welfare, even when the bidders have valuations from the broad class of fractionally subadditive (XOS) valuations (assuming demand oracle access to the valuations) or coverage valuations (even without demand oracles). No-envy learning outcomes are a relaxation of no-regret learning outcomes, which maintain their approximate welfare optimality while endowing them with computational tractability. Our positive and negative results extend to several auction formats that have been studied in the literature via the smoothness paradigm. Our positive results for XOS valuations are enabled by a novel Follow-The-Perturbed-Leader algorithm for settings where the number of experts and states of nature are both infinite, and the payoff function of the learner is non-linear. We show that this algorithm has applications outside of auction settings, establishing significant gains in a recent application of no-regret learning in security games. Our efficient learning result for coverage valuations is based on a novel use of convex rounding schemes and a reduction to online convex optimization.",constantinos daskalakis,mechanism design,2016.0,10.1109/FOCS.2016.31,2016 IEEE 57th Annual Symposium on Foundations of Computer Science (FOCS),Daskalakis2016,False,,IEEE,Not available,"Learning in Auctions: Regret is Hard, Envy is Easy",9979bd1aa5340f782ca08d394f42d3e5,https://ieeexplore.ieee.org/document/7782934/
2165,"An extensive body of recent work studies the welfare guarantees of simple and prevalent combinatorial auction formats, such as selling m items via simultaneous second price auctions (SiSPAs) [1], [2], [3]. These guarantees hold even when the auctions are repeatedly executed and the players use no-regret learning algorithms to choose their actions. Unfortunately, off-the-shelf no-regret learning algorithms for these auctions are computationally inefficient as the number of actions available to the players becomes exponential. We show that this obstacle is inevitable: there are no polynomial-time no-regret learning algorithms for SiSPAs, unless RP ⊇ NP, even when the bidders are unit-demand. Our lower bound raises the question of how good outcomes polynomially-bounded bidders may discover in such auctions. To answer this question, we propose a novel concept of learning in auctions, termed ""no-envy learning."" This notion is founded upon Walrasian equilibrium, and we show that it is both efficiently implementable and results in approximately optimal welfare, even when the bidders have valuations from the broad class of fractionally subadditive (XOS) valuations (assuming demand oracle access to the valuations) or coverage valuations (even without demand oracles). No-envy learning outcomes are a relaxation of no-regret learning outcomes, which maintain their approximate welfare optimality while endowing them with computational tractability. Our positive and negative results extend to several auction formats that have been studied in the literature via the smoothness paradigm. Our positive results for XOS valuations are enabled by a novel Follow-The-Perturbed-Leader algorithm for settings where the number of experts and states of nature are both infinite, and the payoff function of the learner is non-linear. We show that this algorithm has applications outside of auction settings, establishing significant gains in a recent application of no-regret learning in security games. Our efficient learning result for coverage valuations is based on a novel use of convex rounding schemes and a reduction to online convex optimization.",constantinos daskalakis,price of anarchy,2016.0,10.1109/FOCS.2016.31,2016 IEEE 57th Annual Symposium on Foundations of Computer Science (FOCS),Daskalakis2016,False,,IEEE,Not available,"Learning in Auctions: Regret is Hard, Envy is Easy",9979bd1aa5340f782ca08d394f42d3e5,https://ieeexplore.ieee.org/document/7782934/
2166,"An extensive body of recent work studies the welfare guarantees of simple and prevalent combinatorial auction formats, such as selling m items via simultaneous second price auctions (SiSPAs) [1], [2], [3]. These guarantees hold even when the auctions are repeatedly executed and the players use no-regret learning algorithms to choose their actions. Unfortunately, off-the-shelf no-regret learning algorithms for these auctions are computationally inefficient as the number of actions available to the players becomes exponential. We show that this obstacle is inevitable: there are no polynomial-time no-regret learning algorithms for SiSPAs, unless RP ⊇ NP, even when the bidders are unit-demand. Our lower bound raises the question of how good outcomes polynomially-bounded bidders may discover in such auctions. To answer this question, we propose a novel concept of learning in auctions, termed ""no-envy learning."" This notion is founded upon Walrasian equilibrium, and we show that it is both efficiently implementable and results in approximately optimal welfare, even when the bidders have valuations from the broad class of fractionally subadditive (XOS) valuations (assuming demand oracle access to the valuations) or coverage valuations (even without demand oracles). No-envy learning outcomes are a relaxation of no-regret learning outcomes, which maintain their approximate welfare optimality while endowing them with computational tractability. Our positive and negative results extend to several auction formats that have been studied in the literature via the smoothness paradigm. Our positive results for XOS valuations are enabled by a novel Follow-The-Perturbed-Leader algorithm for settings where the number of experts and states of nature are both infinite, and the payoff function of the learner is non-linear. We show that this algorithm has applications outside of auction settings, establishing significant gains in a recent application of no-regret learning in security games. Our efficient learning result for coverage valuations is based on a novel use of convex rounding schemes and a reduction to online convex optimization.",constantinos daskalakis,computational complexity,2016.0,10.1109/FOCS.2016.31,2016 IEEE 57th Annual Symposium on Foundations of Computer Science (FOCS),Daskalakis2016,False,,IEEE,Not available,"Learning in Auctions: Regret is Hard, Envy is Easy",9979bd1aa5340f782ca08d394f42d3e5,https://ieeexplore.ieee.org/document/7782934/
2167,"An extensive body of recent work studies the welfare guarantees of simple and prevalent combinatorial auction formats, such as selling m items via simultaneous second price auctions (SiSPAs) [1], [2], [3]. These guarantees hold even when the auctions are repeatedly executed and the players use no-regret learning algorithms to choose their actions. Unfortunately, off-the-shelf no-regret learning algorithms for these auctions are computationally inefficient as the number of actions available to the players becomes exponential. We show that this obstacle is inevitable: there are no polynomial-time no-regret learning algorithms for SiSPAs, unless RP ⊇ NP, even when the bidders are unit-demand. Our lower bound raises the question of how good outcomes polynomially-bounded bidders may discover in such auctions. To answer this question, we propose a novel concept of learning in auctions, termed ""no-envy learning."" This notion is founded upon Walrasian equilibrium, and we show that it is both efficiently implementable and results in approximately optimal welfare, even when the bidders have valuations from the broad class of fractionally subadditive (XOS) valuations (assuming demand oracle access to the valuations) or coverage valuations (even without demand oracles). No-envy learning outcomes are a relaxation of no-regret learning outcomes, which maintain their approximate welfare optimality while endowing them with computational tractability. Our positive and negative results extend to several auction formats that have been studied in the literature via the smoothness paradigm. Our positive results for XOS valuations are enabled by a novel Follow-The-Perturbed-Leader algorithm for settings where the number of experts and states of nature are both infinite, and the payoff function of the learner is non-linear. We show that this algorithm has applications outside of auction settings, establishing significant gains in a recent application of no-regret learning in security games. Our efficient learning result for coverage valuations is based on a novel use of convex rounding schemes and a reduction to online convex optimization.",vasilis syrgkanis,online learning,2016.0,10.1109/FOCS.2016.31,2016 IEEE 57th Annual Symposium on Foundations of Computer Science (FOCS),Daskalakis2016,False,,IEEE,Not available,"Learning in Auctions: Regret is Hard, Envy is Easy",9979bd1aa5340f782ca08d394f42d3e5,https://ieeexplore.ieee.org/document/7782934/
2168,"An extensive body of recent work studies the welfare guarantees of simple and prevalent combinatorial auction formats, such as selling m items via simultaneous second price auctions (SiSPAs) [1], [2], [3]. These guarantees hold even when the auctions are repeatedly executed and the players use no-regret learning algorithms to choose their actions. Unfortunately, off-the-shelf no-regret learning algorithms for these auctions are computationally inefficient as the number of actions available to the players becomes exponential. We show that this obstacle is inevitable: there are no polynomial-time no-regret learning algorithms for SiSPAs, unless RP ⊇ NP, even when the bidders are unit-demand. Our lower bound raises the question of how good outcomes polynomially-bounded bidders may discover in such auctions. To answer this question, we propose a novel concept of learning in auctions, termed ""no-envy learning."" This notion is founded upon Walrasian equilibrium, and we show that it is both efficiently implementable and results in approximately optimal welfare, even when the bidders have valuations from the broad class of fractionally subadditive (XOS) valuations (assuming demand oracle access to the valuations) or coverage valuations (even without demand oracles). No-envy learning outcomes are a relaxation of no-regret learning outcomes, which maintain their approximate welfare optimality while endowing them with computational tractability. Our positive and negative results extend to several auction formats that have been studied in the literature via the smoothness paradigm. Our positive results for XOS valuations are enabled by a novel Follow-The-Perturbed-Leader algorithm for settings where the number of experts and states of nature are both infinite, and the payoff function of the learner is non-linear. We show that this algorithm has applications outside of auction settings, establishing significant gains in a recent application of no-regret learning in security games. Our efficient learning result for coverage valuations is based on a novel use of convex rounding schemes and a reduction to online convex optimization.",vasilis syrgkanis,auctions,2016.0,10.1109/FOCS.2016.31,2016 IEEE 57th Annual Symposium on Foundations of Computer Science (FOCS),Daskalakis2016,False,,IEEE,Not available,"Learning in Auctions: Regret is Hard, Envy is Easy",9979bd1aa5340f782ca08d394f42d3e5,https://ieeexplore.ieee.org/document/7782934/
2169,"An extensive body of recent work studies the welfare guarantees of simple and prevalent combinatorial auction formats, such as selling m items via simultaneous second price auctions (SiSPAs) [1], [2], [3]. These guarantees hold even when the auctions are repeatedly executed and the players use no-regret learning algorithms to choose their actions. Unfortunately, off-the-shelf no-regret learning algorithms for these auctions are computationally inefficient as the number of actions available to the players becomes exponential. We show that this obstacle is inevitable: there are no polynomial-time no-regret learning algorithms for SiSPAs, unless RP ⊇ NP, even when the bidders are unit-demand. Our lower bound raises the question of how good outcomes polynomially-bounded bidders may discover in such auctions. To answer this question, we propose a novel concept of learning in auctions, termed ""no-envy learning."" This notion is founded upon Walrasian equilibrium, and we show that it is both efficiently implementable and results in approximately optimal welfare, even when the bidders have valuations from the broad class of fractionally subadditive (XOS) valuations (assuming demand oracle access to the valuations) or coverage valuations (even without demand oracles). No-envy learning outcomes are a relaxation of no-regret learning outcomes, which maintain their approximate welfare optimality while endowing them with computational tractability. Our positive and negative results extend to several auction formats that have been studied in the literature via the smoothness paradigm. Our positive results for XOS valuations are enabled by a novel Follow-The-Perturbed-Leader algorithm for settings where the number of experts and states of nature are both infinite, and the payoff function of the learner is non-linear. We show that this algorithm has applications outside of auction settings, establishing significant gains in a recent application of no-regret learning in security games. Our efficient learning result for coverage valuations is based on a novel use of convex rounding schemes and a reduction to online convex optimization.",vasilis syrgkanis,mechanism design,2016.0,10.1109/FOCS.2016.31,2016 IEEE 57th Annual Symposium on Foundations of Computer Science (FOCS),Daskalakis2016,False,,IEEE,Not available,"Learning in Auctions: Regret is Hard, Envy is Easy",9979bd1aa5340f782ca08d394f42d3e5,https://ieeexplore.ieee.org/document/7782934/
2170,"An extensive body of recent work studies the welfare guarantees of simple and prevalent combinatorial auction formats, such as selling m items via simultaneous second price auctions (SiSPAs) [1], [2], [3]. These guarantees hold even when the auctions are repeatedly executed and the players use no-regret learning algorithms to choose their actions. Unfortunately, off-the-shelf no-regret learning algorithms for these auctions are computationally inefficient as the number of actions available to the players becomes exponential. We show that this obstacle is inevitable: there are no polynomial-time no-regret learning algorithms for SiSPAs, unless RP ⊇ NP, even when the bidders are unit-demand. Our lower bound raises the question of how good outcomes polynomially-bounded bidders may discover in such auctions. To answer this question, we propose a novel concept of learning in auctions, termed ""no-envy learning."" This notion is founded upon Walrasian equilibrium, and we show that it is both efficiently implementable and results in approximately optimal welfare, even when the bidders have valuations from the broad class of fractionally subadditive (XOS) valuations (assuming demand oracle access to the valuations) or coverage valuations (even without demand oracles). No-envy learning outcomes are a relaxation of no-regret learning outcomes, which maintain their approximate welfare optimality while endowing them with computational tractability. Our positive and negative results extend to several auction formats that have been studied in the literature via the smoothness paradigm. Our positive results for XOS valuations are enabled by a novel Follow-The-Perturbed-Leader algorithm for settings where the number of experts and states of nature are both infinite, and the payoff function of the learner is non-linear. We show that this algorithm has applications outside of auction settings, establishing significant gains in a recent application of no-regret learning in security games. Our efficient learning result for coverage valuations is based on a novel use of convex rounding schemes and a reduction to online convex optimization.",vasilis syrgkanis,price of anarchy,2016.0,10.1109/FOCS.2016.31,2016 IEEE 57th Annual Symposium on Foundations of Computer Science (FOCS),Daskalakis2016,False,,IEEE,Not available,"Learning in Auctions: Regret is Hard, Envy is Easy",9979bd1aa5340f782ca08d394f42d3e5,https://ieeexplore.ieee.org/document/7782934/
2171,"An extensive body of recent work studies the welfare guarantees of simple and prevalent combinatorial auction formats, such as selling m items via simultaneous second price auctions (SiSPAs) [1], [2], [3]. These guarantees hold even when the auctions are repeatedly executed and the players use no-regret learning algorithms to choose their actions. Unfortunately, off-the-shelf no-regret learning algorithms for these auctions are computationally inefficient as the number of actions available to the players becomes exponential. We show that this obstacle is inevitable: there are no polynomial-time no-regret learning algorithms for SiSPAs, unless RP ⊇ NP, even when the bidders are unit-demand. Our lower bound raises the question of how good outcomes polynomially-bounded bidders may discover in such auctions. To answer this question, we propose a novel concept of learning in auctions, termed ""no-envy learning."" This notion is founded upon Walrasian equilibrium, and we show that it is both efficiently implementable and results in approximately optimal welfare, even when the bidders have valuations from the broad class of fractionally subadditive (XOS) valuations (assuming demand oracle access to the valuations) or coverage valuations (even without demand oracles). No-envy learning outcomes are a relaxation of no-regret learning outcomes, which maintain their approximate welfare optimality while endowing them with computational tractability. Our positive and negative results extend to several auction formats that have been studied in the literature via the smoothness paradigm. Our positive results for XOS valuations are enabled by a novel Follow-The-Perturbed-Leader algorithm for settings where the number of experts and states of nature are both infinite, and the payoff function of the learner is non-linear. We show that this algorithm has applications outside of auction settings, establishing significant gains in a recent application of no-regret learning in security games. Our efficient learning result for coverage valuations is based on a novel use of convex rounding schemes and a reduction to online convex optimization.",vasilis syrgkanis,computational complexity,2016.0,10.1109/FOCS.2016.31,2016 IEEE 57th Annual Symposium on Foundations of Computer Science (FOCS),Daskalakis2016,False,,IEEE,Not available,"Learning in Auctions: Regret is Hard, Envy is Easy",9979bd1aa5340f782ca08d394f42d3e5,https://ieeexplore.ieee.org/document/7782934/
2172,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",ilaria malanchini,Games,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
2173,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
2174,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",ilaria malanchini,Interference,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
2175,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",ilaria malanchini,Resource management,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
2176,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",ilaria malanchini,Nash equilibrium,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
2177,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",ilaria malanchini,Transmitters,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
2178,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",ilaria malanchini,Noise,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
2179,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",ilaria malanchini,Analytical models,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
2180,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",steven weber,Games,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
2181,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",steven weber,Interference,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
2182,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",steven weber,Resource management,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
2183,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",steven weber,Nash equilibrium,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
2184,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
2185,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
2186,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",steven weber,Transmitters,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
2187,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",steven weber,Noise,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
2188,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",steven weber,Analytical models,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
2189,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",matteo cesana,Games,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
2190,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",matteo cesana,Interference,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
2191,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",matteo cesana,Resource management,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
2192,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",matteo cesana,Nash equilibrium,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
2193,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",matteo cesana,Transmitters,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
2194,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",matteo cesana,Noise,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
2195,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",matteo cesana,Analytical models,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
2196,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
2197,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of a game arising in a two-user decentralized interference channel (DIC) with noisy feedback in which transmit-receiver pairs seek an optimal individual transmission rate are fully characterized. In particular, it is shown that in all interference regimes, there always exists at least one Pareto optimal Nash equilibrium (NE). More specifically, there always exists an NE at which players maximize the network sum-rate and thus, the PoS of the corresponding game is always equal to one. A second result provides closed form expressions for the PoA, which allows the full characterization of the reduction of the sum rate due to the anarchic behavior of all transmitter-receiver pairs.",samir perlaza,Games,2014.0,10.1109/ISCCSP.2014.6877900,"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)",Perlaza2014,False,,IEEE,Not available,Decentralized interference channels with noisy feedback possess Pareto optimal Nash equilibria,68af928085080cc846bbbcd98fcf8b9d,https://ieeexplore.ieee.org/document/6877900/
2198,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of a game arising in a two-user decentralized interference channel (DIC) with noisy feedback in which transmit-receiver pairs seek an optimal individual transmission rate are fully characterized. In particular, it is shown that in all interference regimes, there always exists at least one Pareto optimal Nash equilibrium (NE). More specifically, there always exists an NE at which players maximize the network sum-rate and thus, the PoS of the corresponding game is always equal to one. A second result provides closed form expressions for the PoA, which allows the full characterization of the reduction of the sum rate due to the anarchic behavior of all transmitter-receiver pairs.",samir perlaza,Noise measurement,2014.0,10.1109/ISCCSP.2014.6877900,"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)",Perlaza2014,False,,IEEE,Not available,Decentralized interference channels with noisy feedback possess Pareto optimal Nash equilibria,68af928085080cc846bbbcd98fcf8b9d,https://ieeexplore.ieee.org/document/6877900/
2199,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of a game arising in a two-user decentralized interference channel (DIC) with noisy feedback in which transmit-receiver pairs seek an optimal individual transmission rate are fully characterized. In particular, it is shown that in all interference regimes, there always exists at least one Pareto optimal Nash equilibrium (NE). More specifically, there always exists an NE at which players maximize the network sum-rate and thus, the PoS of the corresponding game is always equal to one. A second result provides closed form expressions for the PoA, which allows the full characterization of the reduction of the sum rate due to the anarchic behavior of all transmitter-receiver pairs.",samir perlaza,Transmitters,2014.0,10.1109/ISCCSP.2014.6877900,"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)",Perlaza2014,False,,IEEE,Not available,Decentralized interference channels with noisy feedback possess Pareto optimal Nash equilibria,68af928085080cc846bbbcd98fcf8b9d,https://ieeexplore.ieee.org/document/6877900/
2200,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of a game arising in a two-user decentralized interference channel (DIC) with noisy feedback in which transmit-receiver pairs seek an optimal individual transmission rate are fully characterized. In particular, it is shown that in all interference regimes, there always exists at least one Pareto optimal Nash equilibrium (NE). More specifically, there always exists an NE at which players maximize the network sum-rate and thus, the PoS of the corresponding game is always equal to one. A second result provides closed form expressions for the PoA, which allows the full characterization of the reduction of the sum rate due to the anarchic behavior of all transmitter-receiver pairs.",samir perlaza,Receivers,2014.0,10.1109/ISCCSP.2014.6877900,"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)",Perlaza2014,False,,IEEE,Not available,Decentralized interference channels with noisy feedback possess Pareto optimal Nash equilibria,68af928085080cc846bbbcd98fcf8b9d,https://ieeexplore.ieee.org/document/6877900/
2201,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of a game arising in a two-user decentralized interference channel (DIC) with noisy feedback in which transmit-receiver pairs seek an optimal individual transmission rate are fully characterized. In particular, it is shown that in all interference regimes, there always exists at least one Pareto optimal Nash equilibrium (NE). More specifically, there always exists an NE at which players maximize the network sum-rate and thus, the PoS of the corresponding game is always equal to one. A second result provides closed form expressions for the PoA, which allows the full characterization of the reduction of the sum rate due to the anarchic behavior of all transmitter-receiver pairs.",samir perlaza,Interference channels,2014.0,10.1109/ISCCSP.2014.6877900,"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)",Perlaza2014,False,,IEEE,Not available,Decentralized interference channels with noisy feedback possess Pareto optimal Nash equilibria,68af928085080cc846bbbcd98fcf8b9d,https://ieeexplore.ieee.org/document/6877900/
2202,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of a game arising in a two-user decentralized interference channel (DIC) with noisy feedback in which transmit-receiver pairs seek an optimal individual transmission rate are fully characterized. In particular, it is shown that in all interference regimes, there always exists at least one Pareto optimal Nash equilibrium (NE). More specifically, there always exists an NE at which players maximize the network sum-rate and thus, the PoS of the corresponding game is always equal to one. A second result provides closed form expressions for the PoA, which allows the full characterization of the reduction of the sum rate due to the anarchic behavior of all transmitter-receiver pairs.",samir perlaza,Nash equilibrium,2014.0,10.1109/ISCCSP.2014.6877900,"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)",Perlaza2014,False,,IEEE,Not available,Decentralized interference channels with noisy feedback possess Pareto optimal Nash equilibria,68af928085080cc846bbbcd98fcf8b9d,https://ieeexplore.ieee.org/document/6877900/
2203,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of a game arising in a two-user decentralized interference channel (DIC) with noisy feedback in which transmit-receiver pairs seek an optimal individual transmission rate are fully characterized. In particular, it is shown that in all interference regimes, there always exists at least one Pareto optimal Nash equilibrium (NE). More specifically, there always exists an NE at which players maximize the network sum-rate and thus, the PoS of the corresponding game is always equal to one. A second result provides closed form expressions for the PoA, which allows the full characterization of the reduction of the sum rate due to the anarchic behavior of all transmitter-receiver pairs.",ravi tandon,Games,2014.0,10.1109/ISCCSP.2014.6877900,"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)",Perlaza2014,False,,IEEE,Not available,Decentralized interference channels with noisy feedback possess Pareto optimal Nash equilibria,68af928085080cc846bbbcd98fcf8b9d,https://ieeexplore.ieee.org/document/6877900/
2204,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of a game arising in a two-user decentralized interference channel (DIC) with noisy feedback in which transmit-receiver pairs seek an optimal individual transmission rate are fully characterized. In particular, it is shown that in all interference regimes, there always exists at least one Pareto optimal Nash equilibrium (NE). More specifically, there always exists an NE at which players maximize the network sum-rate and thus, the PoS of the corresponding game is always equal to one. A second result provides closed form expressions for the PoA, which allows the full characterization of the reduction of the sum rate due to the anarchic behavior of all transmitter-receiver pairs.",ravi tandon,Noise measurement,2014.0,10.1109/ISCCSP.2014.6877900,"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)",Perlaza2014,False,,IEEE,Not available,Decentralized interference channels with noisy feedback possess Pareto optimal Nash equilibria,68af928085080cc846bbbcd98fcf8b9d,https://ieeexplore.ieee.org/document/6877900/
2205,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of a game arising in a two-user decentralized interference channel (DIC) with noisy feedback in which transmit-receiver pairs seek an optimal individual transmission rate are fully characterized. In particular, it is shown that in all interference regimes, there always exists at least one Pareto optimal Nash equilibrium (NE). More specifically, there always exists an NE at which players maximize the network sum-rate and thus, the PoS of the corresponding game is always equal to one. A second result provides closed form expressions for the PoA, which allows the full characterization of the reduction of the sum rate due to the anarchic behavior of all transmitter-receiver pairs.",ravi tandon,Transmitters,2014.0,10.1109/ISCCSP.2014.6877900,"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)",Perlaza2014,False,,IEEE,Not available,Decentralized interference channels with noisy feedback possess Pareto optimal Nash equilibria,68af928085080cc846bbbcd98fcf8b9d,https://ieeexplore.ieee.org/document/6877900/
2206,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of a game arising in a two-user decentralized interference channel (DIC) with noisy feedback in which transmit-receiver pairs seek an optimal individual transmission rate are fully characterized. In particular, it is shown that in all interference regimes, there always exists at least one Pareto optimal Nash equilibrium (NE). More specifically, there always exists an NE at which players maximize the network sum-rate and thus, the PoS of the corresponding game is always equal to one. A second result provides closed form expressions for the PoA, which allows the full characterization of the reduction of the sum rate due to the anarchic behavior of all transmitter-receiver pairs.",ravi tandon,Receivers,2014.0,10.1109/ISCCSP.2014.6877900,"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)",Perlaza2014,False,,IEEE,Not available,Decentralized interference channels with noisy feedback possess Pareto optimal Nash equilibria,68af928085080cc846bbbcd98fcf8b9d,https://ieeexplore.ieee.org/document/6877900/
2207,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
2208,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of a game arising in a two-user decentralized interference channel (DIC) with noisy feedback in which transmit-receiver pairs seek an optimal individual transmission rate are fully characterized. In particular, it is shown that in all interference regimes, there always exists at least one Pareto optimal Nash equilibrium (NE). More specifically, there always exists an NE at which players maximize the network sum-rate and thus, the PoS of the corresponding game is always equal to one. A second result provides closed form expressions for the PoA, which allows the full characterization of the reduction of the sum rate due to the anarchic behavior of all transmitter-receiver pairs.",ravi tandon,Interference channels,2014.0,10.1109/ISCCSP.2014.6877900,"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)",Perlaza2014,False,,IEEE,Not available,Decentralized interference channels with noisy feedback possess Pareto optimal Nash equilibria,68af928085080cc846bbbcd98fcf8b9d,https://ieeexplore.ieee.org/document/6877900/
2209,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of a game arising in a two-user decentralized interference channel (DIC) with noisy feedback in which transmit-receiver pairs seek an optimal individual transmission rate are fully characterized. In particular, it is shown that in all interference regimes, there always exists at least one Pareto optimal Nash equilibrium (NE). More specifically, there always exists an NE at which players maximize the network sum-rate and thus, the PoS of the corresponding game is always equal to one. A second result provides closed form expressions for the PoA, which allows the full characterization of the reduction of the sum rate due to the anarchic behavior of all transmitter-receiver pairs.",ravi tandon,Nash equilibrium,2014.0,10.1109/ISCCSP.2014.6877900,"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)",Perlaza2014,False,,IEEE,Not available,Decentralized interference channels with noisy feedback possess Pareto optimal Nash equilibria,68af928085080cc846bbbcd98fcf8b9d,https://ieeexplore.ieee.org/document/6877900/
2210,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of a game arising in a two-user decentralized interference channel (DIC) with noisy feedback in which transmit-receiver pairs seek an optimal individual transmission rate are fully characterized. In particular, it is shown that in all interference regimes, there always exists at least one Pareto optimal Nash equilibrium (NE). More specifically, there always exists an NE at which players maximize the network sum-rate and thus, the PoS of the corresponding game is always equal to one. A second result provides closed form expressions for the PoA, which allows the full characterization of the reduction of the sum rate due to the anarchic behavior of all transmitter-receiver pairs.",h. poor,Games,2014.0,10.1109/ISCCSP.2014.6877900,"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)",Perlaza2014,False,,IEEE,Not available,Decentralized interference channels with noisy feedback possess Pareto optimal Nash equilibria,68af928085080cc846bbbcd98fcf8b9d,https://ieeexplore.ieee.org/document/6877900/
2211,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of a game arising in a two-user decentralized interference channel (DIC) with noisy feedback in which transmit-receiver pairs seek an optimal individual transmission rate are fully characterized. In particular, it is shown that in all interference regimes, there always exists at least one Pareto optimal Nash equilibrium (NE). More specifically, there always exists an NE at which players maximize the network sum-rate and thus, the PoS of the corresponding game is always equal to one. A second result provides closed form expressions for the PoA, which allows the full characterization of the reduction of the sum rate due to the anarchic behavior of all transmitter-receiver pairs.",h. poor,Noise measurement,2014.0,10.1109/ISCCSP.2014.6877900,"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)",Perlaza2014,False,,IEEE,Not available,Decentralized interference channels with noisy feedback possess Pareto optimal Nash equilibria,68af928085080cc846bbbcd98fcf8b9d,https://ieeexplore.ieee.org/document/6877900/
2212,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of a game arising in a two-user decentralized interference channel (DIC) with noisy feedback in which transmit-receiver pairs seek an optimal individual transmission rate are fully characterized. In particular, it is shown that in all interference regimes, there always exists at least one Pareto optimal Nash equilibrium (NE). More specifically, there always exists an NE at which players maximize the network sum-rate and thus, the PoS of the corresponding game is always equal to one. A second result provides closed form expressions for the PoA, which allows the full characterization of the reduction of the sum rate due to the anarchic behavior of all transmitter-receiver pairs.",h. poor,Transmitters,2014.0,10.1109/ISCCSP.2014.6877900,"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)",Perlaza2014,False,,IEEE,Not available,Decentralized interference channels with noisy feedback possess Pareto optimal Nash equilibria,68af928085080cc846bbbcd98fcf8b9d,https://ieeexplore.ieee.org/document/6877900/
2213,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of a game arising in a two-user decentralized interference channel (DIC) with noisy feedback in which transmit-receiver pairs seek an optimal individual transmission rate are fully characterized. In particular, it is shown that in all interference regimes, there always exists at least one Pareto optimal Nash equilibrium (NE). More specifically, there always exists an NE at which players maximize the network sum-rate and thus, the PoS of the corresponding game is always equal to one. A second result provides closed form expressions for the PoA, which allows the full characterization of the reduction of the sum rate due to the anarchic behavior of all transmitter-receiver pairs.",h. poor,Receivers,2014.0,10.1109/ISCCSP.2014.6877900,"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)",Perlaza2014,False,,IEEE,Not available,Decentralized interference channels with noisy feedback possess Pareto optimal Nash equilibria,68af928085080cc846bbbcd98fcf8b9d,https://ieeexplore.ieee.org/document/6877900/
2214,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of a game arising in a two-user decentralized interference channel (DIC) with noisy feedback in which transmit-receiver pairs seek an optimal individual transmission rate are fully characterized. In particular, it is shown that in all interference regimes, there always exists at least one Pareto optimal Nash equilibrium (NE). More specifically, there always exists an NE at which players maximize the network sum-rate and thus, the PoS of the corresponding game is always equal to one. A second result provides closed form expressions for the PoA, which allows the full characterization of the reduction of the sum rate due to the anarchic behavior of all transmitter-receiver pairs.",h. poor,Interference channels,2014.0,10.1109/ISCCSP.2014.6877900,"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)",Perlaza2014,False,,IEEE,Not available,Decentralized interference channels with noisy feedback possess Pareto optimal Nash equilibria,68af928085080cc846bbbcd98fcf8b9d,https://ieeexplore.ieee.org/document/6877900/
2215,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of a game arising in a two-user decentralized interference channel (DIC) with noisy feedback in which transmit-receiver pairs seek an optimal individual transmission rate are fully characterized. In particular, it is shown that in all interference regimes, there always exists at least one Pareto optimal Nash equilibrium (NE). More specifically, there always exists an NE at which players maximize the network sum-rate and thus, the PoS of the corresponding game is always equal to one. A second result provides closed form expressions for the PoA, which allows the full characterization of the reduction of the sum rate due to the anarchic behavior of all transmitter-receiver pairs.",h. poor,Nash equilibrium,2014.0,10.1109/ISCCSP.2014.6877900,"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)",Perlaza2014,False,,IEEE,Not available,Decentralized interference channels with noisy feedback possess Pareto optimal Nash equilibria,68af928085080cc846bbbcd98fcf8b9d,https://ieeexplore.ieee.org/document/6877900/
2216,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",mathew goonewardena,Games,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
2217,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",mathew goonewardena,Heuristic algorithms,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
2218,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
2219,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",mathew goonewardena,Color,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
2220,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",mathew goonewardena,Routing,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
2221,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",mathew goonewardena,Wireless communication,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
2222,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",mathew goonewardena,Convergence,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
2223,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",mathew goonewardena,Cost function,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
2224,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",hoda akbari,Games,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
2225,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",hoda akbari,Heuristic algorithms,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
2226,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",hoda akbari,Color,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
2227,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",hoda akbari,Routing,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
2228,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",hoda akbari,Wireless communication,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
2229,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
2230,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",hoda akbari,Convergence,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
2231,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",hoda akbari,Cost function,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
2232,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",wessam ajib,Games,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
2233,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",wessam ajib,Heuristic algorithms,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
2234,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",wessam ajib,Color,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
2235,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",wessam ajib,Routing,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
2236,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",wessam ajib,Wireless communication,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
2237,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",wessam ajib,Convergence,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
2238,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",wessam ajib,Cost function,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
2239,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",halima elbiaze,Games,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
2240,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
2241,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",halima elbiaze,Heuristic algorithms,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
2242,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",halima elbiaze,Color,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
2243,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",halima elbiaze,Routing,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
2244,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",halima elbiaze,Wireless communication,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
2245,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",halima elbiaze,Convergence,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
2246,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",halima elbiaze,Cost function,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
2247,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",giovanni accongiagioco,Internet Modeling,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
2248,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",giovanni accongiagioco,Complex Networks,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
2249,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",giovanni accongiagioco,Game Theory,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
2250,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",giovanni accongiagioco,AS-level Internet Topology,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
2251,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
2252,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",giovanni accongiagioco,Supermodular Games,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
2253,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",eitan altman,Internet Modeling,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
2254,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",eitan altman,Complex Networks,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
2255,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",eitan altman,Game Theory,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
2256,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",eitan altman,AS-level Internet Topology,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
2257,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",eitan altman,Supermodular Games,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
2258,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",enrico gregori,Internet Modeling,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
2259,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",enrico gregori,Complex Networks,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
2260,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",enrico gregori,Game Theory,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
2261,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",enrico gregori,AS-level Internet Topology,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
2262,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
2263,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",enrico gregori,Supermodular Games,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
2264,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",luciano lenzini,Internet Modeling,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
2265,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",luciano lenzini,Complex Networks,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
2266,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",luciano lenzini,Game Theory,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
2267,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",luciano lenzini,AS-level Internet Topology,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
2268,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",luciano lenzini,Supermodular Games,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
2269,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",diego lucerna,Game theory,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2270,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",diego lucerna,WDM networks,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2271,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",diego lucerna,Optical fiber networks,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2272,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",diego lucerna,Repeaters,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2273,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
2274,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",diego lucerna,Nash equilibrium,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2275,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",diego lucerna,Wavelength division multiplexing,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2276,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",diego lucerna,Mathematical model,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2277,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",diego lucerna,Optical signal processing,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2278,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",diego lucerna,Upper bound,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2279,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",diego lucerna,Mathematical programming,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2280,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",nicola gatti,Game theory,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2281,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",nicola gatti,WDM networks,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2282,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",nicola gatti,Optical fiber networks,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2283,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",nicola gatti,Repeaters,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2284,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
2285,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",nicola gatti,Nash equilibrium,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2286,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",nicola gatti,Wavelength division multiplexing,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2287,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",nicola gatti,Mathematical model,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2288,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",nicola gatti,Optical signal processing,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2289,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",nicola gatti,Upper bound,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2290,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",nicola gatti,Mathematical programming,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2291,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",guido maier,Game theory,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2292,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",guido maier,WDM networks,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2293,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",guido maier,Optical fiber networks,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2294,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",guido maier,Repeaters,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2295,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
2296,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
2297,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",guido maier,Nash equilibrium,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2298,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",guido maier,Wavelength division multiplexing,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2299,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",guido maier,Mathematical model,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2300,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",guido maier,Optical signal processing,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2301,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",guido maier,Upper bound,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2302,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",guido maier,Mathematical programming,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2303,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",achille pattavina,Game theory,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2304,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",achille pattavina,WDM networks,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2305,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",achille pattavina,Optical fiber networks,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2306,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",achille pattavina,Repeaters,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2307,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2308,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",achille pattavina,Nash equilibrium,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2309,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",achille pattavina,Wavelength division multiplexing,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2310,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",achille pattavina,Mathematical model,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2311,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",achille pattavina,Optical signal processing,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2312,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",achille pattavina,Upper bound,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2313,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",achille pattavina,Mathematical programming,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
2314,"The Nash equilibrium region for a 2-user game was defined and characterized first for a linear deterministic channel and then for a Gaussian channel. Challenges in extending this understanding to some special K-user cases have also been explored. In this paper, we study two indices which compare the performance (sum-rate) of the `best' and the `worst' Nash equilibria to the optimum (sum-capacity) and reflect the `price of stability' and the `price of anarchy', respectively. These indices are evaluated for the 2-user and some special K-user linear deterministic interference channels. We further investigate the impact on these indices of changing the payoff functions of each user to include a cost of transmission.",suvarup saha,Interference channels,2010.0,10.1109/ACSSC.2010.5757523,"2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers",Saha2010,False,,IEEE,Not available,On information theoretic games for interference networks,487af391c98553951dedbd104bdb1869,https://ieeexplore.ieee.org/document/5757523/
2315,"The Nash equilibrium region for a 2-user game was defined and characterized first for a linear deterministic channel and then for a Gaussian channel. Challenges in extending this understanding to some special K-user cases have also been explored. In this paper, we study two indices which compare the performance (sum-rate) of the `best' and the `worst' Nash equilibria to the optimum (sum-capacity) and reflect the `price of stability' and the `price of anarchy', respectively. These indices are evaluated for the 2-user and some special K-user linear deterministic interference channels. We further investigate the impact on these indices of changing the payoff functions of each user to include a cost of transmission.",suvarup saha,Games,2010.0,10.1109/ACSSC.2010.5757523,"2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers",Saha2010,False,,IEEE,Not available,On information theoretic games for interference networks,487af391c98553951dedbd104bdb1869,https://ieeexplore.ieee.org/document/5757523/
2316,"The Nash equilibrium region for a 2-user game was defined and characterized first for a linear deterministic channel and then for a Gaussian channel. Challenges in extending this understanding to some special K-user cases have also been explored. In this paper, we study two indices which compare the performance (sum-rate) of the `best' and the `worst' Nash equilibria to the optimum (sum-capacity) and reflect the `price of stability' and the `price of anarchy', respectively. These indices are evaluated for the 2-user and some special K-user linear deterministic interference channels. We further investigate the impact on these indices of changing the payoff functions of each user to include a cost of transmission.",suvarup saha,Receivers,2010.0,10.1109/ACSSC.2010.5757523,"2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers",Saha2010,False,,IEEE,Not available,On information theoretic games for interference networks,487af391c98553951dedbd104bdb1869,https://ieeexplore.ieee.org/document/5757523/
2317,"The Nash equilibrium region for a 2-user game was defined and characterized first for a linear deterministic channel and then for a Gaussian channel. Challenges in extending this understanding to some special K-user cases have also been explored. In this paper, we study two indices which compare the performance (sum-rate) of the `best' and the `worst' Nash equilibria to the optimum (sum-capacity) and reflect the `price of stability' and the `price of anarchy', respectively. These indices are evaluated for the 2-user and some special K-user linear deterministic interference channels. We further investigate the impact on these indices of changing the payoff functions of each user to include a cost of transmission.",suvarup saha,Noise,2010.0,10.1109/ACSSC.2010.5757523,"2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers",Saha2010,False,,IEEE,Not available,On information theoretic games for interference networks,487af391c98553951dedbd104bdb1869,https://ieeexplore.ieee.org/document/5757523/
2318,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2319,"The Nash equilibrium region for a 2-user game was defined and characterized first for a linear deterministic channel and then for a Gaussian channel. Challenges in extending this understanding to some special K-user cases have also been explored. In this paper, we study two indices which compare the performance (sum-rate) of the `best' and the `worst' Nash equilibria to the optimum (sum-capacity) and reflect the `price of stability' and the `price of anarchy', respectively. These indices are evaluated for the 2-user and some special K-user linear deterministic interference channels. We further investigate the impact on these indices of changing the payoff functions of each user to include a cost of transmission.",suvarup saha,Transmitters,2010.0,10.1109/ACSSC.2010.5757523,"2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers",Saha2010,False,,IEEE,Not available,On information theoretic games for interference networks,487af391c98553951dedbd104bdb1869,https://ieeexplore.ieee.org/document/5757523/
2320,"The Nash equilibrium region for a 2-user game was defined and characterized first for a linear deterministic channel and then for a Gaussian channel. Challenges in extending this understanding to some special K-user cases have also been explored. In this paper, we study two indices which compare the performance (sum-rate) of the `best' and the `worst' Nash equilibria to the optimum (sum-capacity) and reflect the `price of stability' and the `price of anarchy', respectively. These indices are evaluated for the 2-user and some special K-user linear deterministic interference channels. We further investigate the impact on these indices of changing the payoff functions of each user to include a cost of transmission.",suvarup saha,Nash equilibrium,2010.0,10.1109/ACSSC.2010.5757523,"2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers",Saha2010,False,,IEEE,Not available,On information theoretic games for interference networks,487af391c98553951dedbd104bdb1869,https://ieeexplore.ieee.org/document/5757523/
2321,"The Nash equilibrium region for a 2-user game was defined and characterized first for a linear deterministic channel and then for a Gaussian channel. Challenges in extending this understanding to some special K-user cases have also been explored. In this paper, we study two indices which compare the performance (sum-rate) of the `best' and the `worst' Nash equilibria to the optimum (sum-capacity) and reflect the `price of stability' and the `price of anarchy', respectively. These indices are evaluated for the 2-user and some special K-user linear deterministic interference channels. We further investigate the impact on these indices of changing the payoff functions of each user to include a cost of transmission.",randall berry,Interference channels,2010.0,10.1109/ACSSC.2010.5757523,"2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers",Saha2010,False,,IEEE,Not available,On information theoretic games for interference networks,487af391c98553951dedbd104bdb1869,https://ieeexplore.ieee.org/document/5757523/
2322,"The Nash equilibrium region for a 2-user game was defined and characterized first for a linear deterministic channel and then for a Gaussian channel. Challenges in extending this understanding to some special K-user cases have also been explored. In this paper, we study two indices which compare the performance (sum-rate) of the `best' and the `worst' Nash equilibria to the optimum (sum-capacity) and reflect the `price of stability' and the `price of anarchy', respectively. These indices are evaluated for the 2-user and some special K-user linear deterministic interference channels. We further investigate the impact on these indices of changing the payoff functions of each user to include a cost of transmission.",randall berry,Games,2010.0,10.1109/ACSSC.2010.5757523,"2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers",Saha2010,False,,IEEE,Not available,On information theoretic games for interference networks,487af391c98553951dedbd104bdb1869,https://ieeexplore.ieee.org/document/5757523/
2323,"The Nash equilibrium region for a 2-user game was defined and characterized first for a linear deterministic channel and then for a Gaussian channel. Challenges in extending this understanding to some special K-user cases have also been explored. In this paper, we study two indices which compare the performance (sum-rate) of the `best' and the `worst' Nash equilibria to the optimum (sum-capacity) and reflect the `price of stability' and the `price of anarchy', respectively. These indices are evaluated for the 2-user and some special K-user linear deterministic interference channels. We further investigate the impact on these indices of changing the payoff functions of each user to include a cost of transmission.",randall berry,Receivers,2010.0,10.1109/ACSSC.2010.5757523,"2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers",Saha2010,False,,IEEE,Not available,On information theoretic games for interference networks,487af391c98553951dedbd104bdb1869,https://ieeexplore.ieee.org/document/5757523/
2324,"The Nash equilibrium region for a 2-user game was defined and characterized first for a linear deterministic channel and then for a Gaussian channel. Challenges in extending this understanding to some special K-user cases have also been explored. In this paper, we study two indices which compare the performance (sum-rate) of the `best' and the `worst' Nash equilibria to the optimum (sum-capacity) and reflect the `price of stability' and the `price of anarchy', respectively. These indices are evaluated for the 2-user and some special K-user linear deterministic interference channels. We further investigate the impact on these indices of changing the payoff functions of each user to include a cost of transmission.",randall berry,Noise,2010.0,10.1109/ACSSC.2010.5757523,"2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers",Saha2010,False,,IEEE,Not available,On information theoretic games for interference networks,487af391c98553951dedbd104bdb1869,https://ieeexplore.ieee.org/document/5757523/
2325,"The Nash equilibrium region for a 2-user game was defined and characterized first for a linear deterministic channel and then for a Gaussian channel. Challenges in extending this understanding to some special K-user cases have also been explored. In this paper, we study two indices which compare the performance (sum-rate) of the `best' and the `worst' Nash equilibria to the optimum (sum-capacity) and reflect the `price of stability' and the `price of anarchy', respectively. These indices are evaluated for the 2-user and some special K-user linear deterministic interference channels. We further investigate the impact on these indices of changing the payoff functions of each user to include a cost of transmission.",randall berry,Transmitters,2010.0,10.1109/ACSSC.2010.5757523,"2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers",Saha2010,False,,IEEE,Not available,On information theoretic games for interference networks,487af391c98553951dedbd104bdb1869,https://ieeexplore.ieee.org/document/5757523/
2326,"The Nash equilibrium region for a 2-user game was defined and characterized first for a linear deterministic channel and then for a Gaussian channel. Challenges in extending this understanding to some special K-user cases have also been explored. In this paper, we study two indices which compare the performance (sum-rate) of the `best' and the `worst' Nash equilibria to the optimum (sum-capacity) and reflect the `price of stability' and the `price of anarchy', respectively. These indices are evaluated for the 2-user and some special K-user linear deterministic interference channels. We further investigate the impact on these indices of changing the payoff functions of each user to include a cost of transmission.",randall berry,Nash equilibrium,2010.0,10.1109/ACSSC.2010.5757523,"2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers",Saha2010,False,,IEEE,Not available,On information theoretic games for interference networks,487af391c98553951dedbd104bdb1869,https://ieeexplore.ieee.org/document/5757523/
2327,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",jun zhao,Quality of service,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2328,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",jun zhao,Games,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2329,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2330,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",jun zhao,Resource management,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2331,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",jun zhao,Base stations,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2332,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",jun zhao,Interference,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2333,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",jun zhao,Throughput,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2334,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",jun zhao,Algorithm design and analysis,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2335,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",haijun zhang,Quality of service,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2336,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",haijun zhang,Games,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2337,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",haijun zhang,Resource management,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2338,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",haijun zhang,Base stations,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2339,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",haijun zhang,Interference,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2340,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2341,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",haijun zhang,Throughput,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2342,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",haijun zhang,Algorithm design and analysis,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2343,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",zhaoming lu,Quality of service,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2344,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",zhaoming lu,Games,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2345,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",zhaoming lu,Resource management,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2346,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",zhaoming lu,Base stations,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2347,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",zhaoming lu,Interference,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2348,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",zhaoming lu,Throughput,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2349,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",zhaoming lu,Algorithm design and analysis,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2350,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",xiangming wen,Quality of service,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2351,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2352,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",xiangming wen,Games,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2353,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",xiangming wen,Resource management,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2354,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",xiangming wen,Base stations,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2355,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",xiangming wen,Interference,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2356,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",xiangming wen,Throughput,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2357,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",xiangming wen,Algorithm design and analysis,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2358,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",wei zheng,Quality of service,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2359,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",wei zheng,Games,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2360,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",wei zheng,Resource management,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2361,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",wei zheng,Base stations,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2362,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2363,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",wei zheng,Interference,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2364,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",wei zheng,Throughput,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2365,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",wei zheng,Algorithm design and analysis,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2366,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",xidong wang,Quality of service,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2367,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",xidong wang,Games,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2368,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",xidong wang,Resource management,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2369,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",xidong wang,Base stations,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2370,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",xidong wang,Interference,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2371,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",xidong wang,Throughput,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2372,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",xidong wang,Algorithm design and analysis,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2373,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2374,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",zhiqun hu,Quality of service,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2375,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",zhiqun hu,Games,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2376,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",zhiqun hu,Resource management,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2377,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",zhiqun hu,Base stations,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2378,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",zhiqun hu,Interference,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2379,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",zhiqun hu,Throughput,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2380,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",zhiqun hu,Algorithm design and analysis,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
2381,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",yupeng li,Congestion game,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
2382,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",yupeng li,agent failure,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
2383,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",yupeng li,resource failure,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
2384,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2385,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",yupeng li,Nash equilibrium,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
2386,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",yupeng li,price of anarchy,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
2387,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",yongzheng jia,Congestion game,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
2388,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",yongzheng jia,agent failure,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
2389,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",yongzheng jia,resource failure,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
2390,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",yongzheng jia,Nash equilibrium,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
2391,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",yongzheng jia,price of anarchy,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
2392,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",haisheng tan,Congestion game,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
2393,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",haisheng tan,agent failure,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
2394,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",haisheng tan,resource failure,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
2395,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2396,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",haisheng tan,Nash equilibrium,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
2397,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",haisheng tan,price of anarchy,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
2398,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",rui wang,Congestion game,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
2399,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",rui wang,agent failure,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
2400,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",rui wang,resource failure,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
2401,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",rui wang,Nash equilibrium,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
2402,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",rui wang,price of anarchy,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
2403,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",zhenhua han,Congestion game,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
2404,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",zhenhua han,agent failure,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
2405,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",zhenhua han,resource failure,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
2406,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
2407,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2408,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",zhenhua han,Nash equilibrium,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
2409,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",zhenhua han,price of anarchy,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
2410,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",francis lau,Congestion game,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
2411,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",francis lau,agent failure,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
2412,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",francis lau,resource failure,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
2413,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",francis lau,Nash equilibrium,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
2414,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",francis lau,price of anarchy,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
2415,"Server selection plays an essential role in content replication networks, such as peer-to-peer (P2P) and content delivery networks (CDNs). In this paper, we perform an analytical investigation of the strengths and weaknesses of existing server selection policies, based initially on an &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 processor sharing (PS) queueing-theoretic model. We develop a theoretical benchmark to evaluate the performance of two general server selection policies, referred to as EQ_DELAY and EQ_LOAD, which characterize a wide range of existing server selection algorithms. We find that EQ_LOAD achieves an average delay always higher than or equal to that of EQ_DELAY. A key theoretical result of this paper is that in an &lt;i&gt;N&lt;/i&gt;-server system, the worst case ratio between the average delay of EQ_DELAY or EQ_LOAD and the minimal average delay (obtained from the benchmark) is precisely &lt;i&gt;N&lt;/i&gt;. We constructively show how this worst case scenario can arise in highly heterogeneous systems. This result, when interpreted in the context of selfish routing, means that the price of anarchy in unbounded delay networks depends on the topology, and can potentially be very large. Our analytical findings are extended in asymptotic regimes to the &lt;i&gt;G&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 first-come first-serve and multi-class &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1-PS models and supported by simulations run for various arrival and service processes, scheduling disciplines, and workload exhibiting temporal locality. These results indicate that our analysis is applicable to realistic scenarios.",tao wu,Content delivery networks,2008.0,10.1109/TNET.2007.909752,IEEE/ACM Transactions on Networking,Wu2008,False,,IEEE,Not available,A Comparative Analysis of Server Selection in Content Replication Networks,19c4fbd837166c20b209d320503781c4,https://ieeexplore.ieee.org/document/4469924/
2416,"Server selection plays an essential role in content replication networks, such as peer-to-peer (P2P) and content delivery networks (CDNs). In this paper, we perform an analytical investigation of the strengths and weaknesses of existing server selection policies, based initially on an &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 processor sharing (PS) queueing-theoretic model. We develop a theoretical benchmark to evaluate the performance of two general server selection policies, referred to as EQ_DELAY and EQ_LOAD, which characterize a wide range of existing server selection algorithms. We find that EQ_LOAD achieves an average delay always higher than or equal to that of EQ_DELAY. A key theoretical result of this paper is that in an &lt;i&gt;N&lt;/i&gt;-server system, the worst case ratio between the average delay of EQ_DELAY or EQ_LOAD and the minimal average delay (obtained from the benchmark) is precisely &lt;i&gt;N&lt;/i&gt;. We constructively show how this worst case scenario can arise in highly heterogeneous systems. This result, when interpreted in the context of selfish routing, means that the price of anarchy in unbounded delay networks depends on the topology, and can potentially be very large. Our analytical findings are extended in asymptotic regimes to the &lt;i&gt;G&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 first-come first-serve and multi-class &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1-PS models and supported by simulations run for various arrival and service processes, scheduling disciplines, and workload exhibiting temporal locality. These results indicate that our analysis is applicable to realistic scenarios.",tao wu,distributed systems,2008.0,10.1109/TNET.2007.909752,IEEE/ACM Transactions on Networking,Wu2008,False,,IEEE,Not available,A Comparative Analysis of Server Selection in Content Replication Networks,19c4fbd837166c20b209d320503781c4,https://ieeexplore.ieee.org/document/4469924/
2417,"Server selection plays an essential role in content replication networks, such as peer-to-peer (P2P) and content delivery networks (CDNs). In this paper, we perform an analytical investigation of the strengths and weaknesses of existing server selection policies, based initially on an &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 processor sharing (PS) queueing-theoretic model. We develop a theoretical benchmark to evaluate the performance of two general server selection policies, referred to as EQ_DELAY and EQ_LOAD, which characterize a wide range of existing server selection algorithms. We find that EQ_LOAD achieves an average delay always higher than or equal to that of EQ_DELAY. A key theoretical result of this paper is that in an &lt;i&gt;N&lt;/i&gt;-server system, the worst case ratio between the average delay of EQ_DELAY or EQ_LOAD and the minimal average delay (obtained from the benchmark) is precisely &lt;i&gt;N&lt;/i&gt;. We constructively show how this worst case scenario can arise in highly heterogeneous systems. This result, when interpreted in the context of selfish routing, means that the price of anarchy in unbounded delay networks depends on the topology, and can potentially be very large. Our analytical findings are extended in asymptotic regimes to the &lt;i&gt;G&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 first-come first-serve and multi-class &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1-PS models and supported by simulations run for various arrival and service processes, scheduling disciplines, and workload exhibiting temporal locality. These results indicate that our analysis is applicable to realistic scenarios.",tao wu,game theory,2008.0,10.1109/TNET.2007.909752,IEEE/ACM Transactions on Networking,Wu2008,False,,IEEE,Not available,A Comparative Analysis of Server Selection in Content Replication Networks,19c4fbd837166c20b209d320503781c4,https://ieeexplore.ieee.org/document/4469924/
2418,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2419,"Server selection plays an essential role in content replication networks, such as peer-to-peer (P2P) and content delivery networks (CDNs). In this paper, we perform an analytical investigation of the strengths and weaknesses of existing server selection policies, based initially on an &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 processor sharing (PS) queueing-theoretic model. We develop a theoretical benchmark to evaluate the performance of two general server selection policies, referred to as EQ_DELAY and EQ_LOAD, which characterize a wide range of existing server selection algorithms. We find that EQ_LOAD achieves an average delay always higher than or equal to that of EQ_DELAY. A key theoretical result of this paper is that in an &lt;i&gt;N&lt;/i&gt;-server system, the worst case ratio between the average delay of EQ_DELAY or EQ_LOAD and the minimal average delay (obtained from the benchmark) is precisely &lt;i&gt;N&lt;/i&gt;. We constructively show how this worst case scenario can arise in highly heterogeneous systems. This result, when interpreted in the context of selfish routing, means that the price of anarchy in unbounded delay networks depends on the topology, and can potentially be very large. Our analytical findings are extended in asymptotic regimes to the &lt;i&gt;G&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 first-come first-serve and multi-class &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1-PS models and supported by simulations run for various arrival and service processes, scheduling disciplines, and workload exhibiting temporal locality. These results indicate that our analysis is applicable to realistic scenarios.",tao wu,load balancing,2008.0,10.1109/TNET.2007.909752,IEEE/ACM Transactions on Networking,Wu2008,False,,IEEE,Not available,A Comparative Analysis of Server Selection in Content Replication Networks,19c4fbd837166c20b209d320503781c4,https://ieeexplore.ieee.org/document/4469924/
2420,"Server selection plays an essential role in content replication networks, such as peer-to-peer (P2P) and content delivery networks (CDNs). In this paper, we perform an analytical investigation of the strengths and weaknesses of existing server selection policies, based initially on an &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 processor sharing (PS) queueing-theoretic model. We develop a theoretical benchmark to evaluate the performance of two general server selection policies, referred to as EQ_DELAY and EQ_LOAD, which characterize a wide range of existing server selection algorithms. We find that EQ_LOAD achieves an average delay always higher than or equal to that of EQ_DELAY. A key theoretical result of this paper is that in an &lt;i&gt;N&lt;/i&gt;-server system, the worst case ratio between the average delay of EQ_DELAY or EQ_LOAD and the minimal average delay (obtained from the benchmark) is precisely &lt;i&gt;N&lt;/i&gt;. We constructively show how this worst case scenario can arise in highly heterogeneous systems. This result, when interpreted in the context of selfish routing, means that the price of anarchy in unbounded delay networks depends on the topology, and can potentially be very large. Our analytical findings are extended in asymptotic regimes to the &lt;i&gt;G&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 first-come first-serve and multi-class &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1-PS models and supported by simulations run for various arrival and service processes, scheduling disciplines, and workload exhibiting temporal locality. These results indicate that our analysis is applicable to realistic scenarios.",tao wu,peer-to-peer networks,2008.0,10.1109/TNET.2007.909752,IEEE/ACM Transactions on Networking,Wu2008,False,,IEEE,Not available,A Comparative Analysis of Server Selection in Content Replication Networks,19c4fbd837166c20b209d320503781c4,https://ieeexplore.ieee.org/document/4469924/
2421,"Server selection plays an essential role in content replication networks, such as peer-to-peer (P2P) and content delivery networks (CDNs). In this paper, we perform an analytical investigation of the strengths and weaknesses of existing server selection policies, based initially on an &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 processor sharing (PS) queueing-theoretic model. We develop a theoretical benchmark to evaluate the performance of two general server selection policies, referred to as EQ_DELAY and EQ_LOAD, which characterize a wide range of existing server selection algorithms. We find that EQ_LOAD achieves an average delay always higher than or equal to that of EQ_DELAY. A key theoretical result of this paper is that in an &lt;i&gt;N&lt;/i&gt;-server system, the worst case ratio between the average delay of EQ_DELAY or EQ_LOAD and the minimal average delay (obtained from the benchmark) is precisely &lt;i&gt;N&lt;/i&gt;. We constructively show how this worst case scenario can arise in highly heterogeneous systems. This result, when interpreted in the context of selfish routing, means that the price of anarchy in unbounded delay networks depends on the topology, and can potentially be very large. Our analytical findings are extended in asymptotic regimes to the &lt;i&gt;G&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 first-come first-serve and multi-class &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1-PS models and supported by simulations run for various arrival and service processes, scheduling disciplines, and workload exhibiting temporal locality. These results indicate that our analysis is applicable to realistic scenarios.",tao wu,price of anarchy,2008.0,10.1109/TNET.2007.909752,IEEE/ACM Transactions on Networking,Wu2008,False,,IEEE,Not available,A Comparative Analysis of Server Selection in Content Replication Networks,19c4fbd837166c20b209d320503781c4,https://ieeexplore.ieee.org/document/4469924/
2422,"Server selection plays an essential role in content replication networks, such as peer-to-peer (P2P) and content delivery networks (CDNs). In this paper, we perform an analytical investigation of the strengths and weaknesses of existing server selection policies, based initially on an &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 processor sharing (PS) queueing-theoretic model. We develop a theoretical benchmark to evaluate the performance of two general server selection policies, referred to as EQ_DELAY and EQ_LOAD, which characterize a wide range of existing server selection algorithms. We find that EQ_LOAD achieves an average delay always higher than or equal to that of EQ_DELAY. A key theoretical result of this paper is that in an &lt;i&gt;N&lt;/i&gt;-server system, the worst case ratio between the average delay of EQ_DELAY or EQ_LOAD and the minimal average delay (obtained from the benchmark) is precisely &lt;i&gt;N&lt;/i&gt;. We constructively show how this worst case scenario can arise in highly heterogeneous systems. This result, when interpreted in the context of selfish routing, means that the price of anarchy in unbounded delay networks depends on the topology, and can potentially be very large. Our analytical findings are extended in asymptotic regimes to the &lt;i&gt;G&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 first-come first-serve and multi-class &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1-PS models and supported by simulations run for various arrival and service processes, scheduling disciplines, and workload exhibiting temporal locality. These results indicate that our analysis is applicable to realistic scenarios.",david starobinski,Content delivery networks,2008.0,10.1109/TNET.2007.909752,IEEE/ACM Transactions on Networking,Wu2008,False,,IEEE,Not available,A Comparative Analysis of Server Selection in Content Replication Networks,19c4fbd837166c20b209d320503781c4,https://ieeexplore.ieee.org/document/4469924/
2423,"Server selection plays an essential role in content replication networks, such as peer-to-peer (P2P) and content delivery networks (CDNs). In this paper, we perform an analytical investigation of the strengths and weaknesses of existing server selection policies, based initially on an &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 processor sharing (PS) queueing-theoretic model. We develop a theoretical benchmark to evaluate the performance of two general server selection policies, referred to as EQ_DELAY and EQ_LOAD, which characterize a wide range of existing server selection algorithms. We find that EQ_LOAD achieves an average delay always higher than or equal to that of EQ_DELAY. A key theoretical result of this paper is that in an &lt;i&gt;N&lt;/i&gt;-server system, the worst case ratio between the average delay of EQ_DELAY or EQ_LOAD and the minimal average delay (obtained from the benchmark) is precisely &lt;i&gt;N&lt;/i&gt;. We constructively show how this worst case scenario can arise in highly heterogeneous systems. This result, when interpreted in the context of selfish routing, means that the price of anarchy in unbounded delay networks depends on the topology, and can potentially be very large. Our analytical findings are extended in asymptotic regimes to the &lt;i&gt;G&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 first-come first-serve and multi-class &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1-PS models and supported by simulations run for various arrival and service processes, scheduling disciplines, and workload exhibiting temporal locality. These results indicate that our analysis is applicable to realistic scenarios.",david starobinski,distributed systems,2008.0,10.1109/TNET.2007.909752,IEEE/ACM Transactions on Networking,Wu2008,False,,IEEE,Not available,A Comparative Analysis of Server Selection in Content Replication Networks,19c4fbd837166c20b209d320503781c4,https://ieeexplore.ieee.org/document/4469924/
2424,"Server selection plays an essential role in content replication networks, such as peer-to-peer (P2P) and content delivery networks (CDNs). In this paper, we perform an analytical investigation of the strengths and weaknesses of existing server selection policies, based initially on an &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 processor sharing (PS) queueing-theoretic model. We develop a theoretical benchmark to evaluate the performance of two general server selection policies, referred to as EQ_DELAY and EQ_LOAD, which characterize a wide range of existing server selection algorithms. We find that EQ_LOAD achieves an average delay always higher than or equal to that of EQ_DELAY. A key theoretical result of this paper is that in an &lt;i&gt;N&lt;/i&gt;-server system, the worst case ratio between the average delay of EQ_DELAY or EQ_LOAD and the minimal average delay (obtained from the benchmark) is precisely &lt;i&gt;N&lt;/i&gt;. We constructively show how this worst case scenario can arise in highly heterogeneous systems. This result, when interpreted in the context of selfish routing, means that the price of anarchy in unbounded delay networks depends on the topology, and can potentially be very large. Our analytical findings are extended in asymptotic regimes to the &lt;i&gt;G&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 first-come first-serve and multi-class &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1-PS models and supported by simulations run for various arrival and service processes, scheduling disciplines, and workload exhibiting temporal locality. These results indicate that our analysis is applicable to realistic scenarios.",david starobinski,game theory,2008.0,10.1109/TNET.2007.909752,IEEE/ACM Transactions on Networking,Wu2008,False,,IEEE,Not available,A Comparative Analysis of Server Selection in Content Replication Networks,19c4fbd837166c20b209d320503781c4,https://ieeexplore.ieee.org/document/4469924/
2425,"Server selection plays an essential role in content replication networks, such as peer-to-peer (P2P) and content delivery networks (CDNs). In this paper, we perform an analytical investigation of the strengths and weaknesses of existing server selection policies, based initially on an &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 processor sharing (PS) queueing-theoretic model. We develop a theoretical benchmark to evaluate the performance of two general server selection policies, referred to as EQ_DELAY and EQ_LOAD, which characterize a wide range of existing server selection algorithms. We find that EQ_LOAD achieves an average delay always higher than or equal to that of EQ_DELAY. A key theoretical result of this paper is that in an &lt;i&gt;N&lt;/i&gt;-server system, the worst case ratio between the average delay of EQ_DELAY or EQ_LOAD and the minimal average delay (obtained from the benchmark) is precisely &lt;i&gt;N&lt;/i&gt;. We constructively show how this worst case scenario can arise in highly heterogeneous systems. This result, when interpreted in the context of selfish routing, means that the price of anarchy in unbounded delay networks depends on the topology, and can potentially be very large. Our analytical findings are extended in asymptotic regimes to the &lt;i&gt;G&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 first-come first-serve and multi-class &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1-PS models and supported by simulations run for various arrival and service processes, scheduling disciplines, and workload exhibiting temporal locality. These results indicate that our analysis is applicable to realistic scenarios.",david starobinski,load balancing,2008.0,10.1109/TNET.2007.909752,IEEE/ACM Transactions on Networking,Wu2008,False,,IEEE,Not available,A Comparative Analysis of Server Selection in Content Replication Networks,19c4fbd837166c20b209d320503781c4,https://ieeexplore.ieee.org/document/4469924/
2426,"Server selection plays an essential role in content replication networks, such as peer-to-peer (P2P) and content delivery networks (CDNs). In this paper, we perform an analytical investigation of the strengths and weaknesses of existing server selection policies, based initially on an &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 processor sharing (PS) queueing-theoretic model. We develop a theoretical benchmark to evaluate the performance of two general server selection policies, referred to as EQ_DELAY and EQ_LOAD, which characterize a wide range of existing server selection algorithms. We find that EQ_LOAD achieves an average delay always higher than or equal to that of EQ_DELAY. A key theoretical result of this paper is that in an &lt;i&gt;N&lt;/i&gt;-server system, the worst case ratio between the average delay of EQ_DELAY or EQ_LOAD and the minimal average delay (obtained from the benchmark) is precisely &lt;i&gt;N&lt;/i&gt;. We constructively show how this worst case scenario can arise in highly heterogeneous systems. This result, when interpreted in the context of selfish routing, means that the price of anarchy in unbounded delay networks depends on the topology, and can potentially be very large. Our analytical findings are extended in asymptotic regimes to the &lt;i&gt;G&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 first-come first-serve and multi-class &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1-PS models and supported by simulations run for various arrival and service processes, scheduling disciplines, and workload exhibiting temporal locality. These results indicate that our analysis is applicable to realistic scenarios.",david starobinski,peer-to-peer networks,2008.0,10.1109/TNET.2007.909752,IEEE/ACM Transactions on Networking,Wu2008,False,,IEEE,Not available,A Comparative Analysis of Server Selection in Content Replication Networks,19c4fbd837166c20b209d320503781c4,https://ieeexplore.ieee.org/document/4469924/
2427,"Server selection plays an essential role in content replication networks, such as peer-to-peer (P2P) and content delivery networks (CDNs). In this paper, we perform an analytical investigation of the strengths and weaknesses of existing server selection policies, based initially on an &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 processor sharing (PS) queueing-theoretic model. We develop a theoretical benchmark to evaluate the performance of two general server selection policies, referred to as EQ_DELAY and EQ_LOAD, which characterize a wide range of existing server selection algorithms. We find that EQ_LOAD achieves an average delay always higher than or equal to that of EQ_DELAY. A key theoretical result of this paper is that in an &lt;i&gt;N&lt;/i&gt;-server system, the worst case ratio between the average delay of EQ_DELAY or EQ_LOAD and the minimal average delay (obtained from the benchmark) is precisely &lt;i&gt;N&lt;/i&gt;. We constructively show how this worst case scenario can arise in highly heterogeneous systems. This result, when interpreted in the context of selfish routing, means that the price of anarchy in unbounded delay networks depends on the topology, and can potentially be very large. Our analytical findings are extended in asymptotic regimes to the &lt;i&gt;G&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 first-come first-serve and multi-class &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1-PS models and supported by simulations run for various arrival and service processes, scheduling disciplines, and workload exhibiting temporal locality. These results indicate that our analysis is applicable to realistic scenarios.",david starobinski,price of anarchy,2008.0,10.1109/TNET.2007.909752,IEEE/ACM Transactions on Networking,Wu2008,False,,IEEE,Not available,A Comparative Analysis of Server Selection in Content Replication Networks,19c4fbd837166c20b209d320503781c4,https://ieeexplore.ieee.org/document/4469924/
2428,"We consider a geographically distributed request processing system composed of various organizations and their servers connected by the Internet. The latency a user observes is a sum of communication delays and the time needed to handle the request on a server. The handling time depends on the server congestion, i.e. the total number of requests a server must handle. We analyze the problem of balancing the load in a network of servers in order to minimize the total observed latency. We consider both cooperative and selfish organizations (each organization aiming to minimize the latency of the locally-produced requests). The problem can be generalized to the task scheduling in a distributed cloud; or to content delivery in an organizationally-distributed CDNs. In a cooperative network, we show that the problem is polynomially solvable. We also present a distributed algorithm iteratively balancing the load. We show how to estimate the distance between the current solution and the optimum based on the amount of load exchanged by the algorithm. During the experimental evaluation, we show that the distributed algorithm is efficient, therefore it can be used in networks with dynamically changing loads. In a network of selfish organizations, we prove that the price of anarchy (the worst-case loss of performance due to selfishness) is low when the network is homogeneous and the servers are loaded (the request handling time is high compared to the communication delay). After relaxing these assumptions, we assess the loss of performance caused by the selfishness experimentally, showing that it remains low. Our results indicate that a set of servers handling requests, connected in a heterogeneous network, can be efficiently managed by a distributed algorithm. Additionally, even if the network is organizationally distributed, with individual organizations optimizing performance of their requests, the network remains efficient.",piotr skowron,load balancing,2013.0,10.1109/IPDPSW.2013.21,"2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum",Skowron2013,False,,IEEE,Not available,Network Delay-Aware Load Balancing in Selfish and Cooperative Distributed Systems,fc60b1bb89747a09a889abb542672d4f,https://ieeexplore.ieee.org/document/6650867/
2429,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2430,"We consider a geographically distributed request processing system composed of various organizations and their servers connected by the Internet. The latency a user observes is a sum of communication delays and the time needed to handle the request on a server. The handling time depends on the server congestion, i.e. the total number of requests a server must handle. We analyze the problem of balancing the load in a network of servers in order to minimize the total observed latency. We consider both cooperative and selfish organizations (each organization aiming to minimize the latency of the locally-produced requests). The problem can be generalized to the task scheduling in a distributed cloud; or to content delivery in an organizationally-distributed CDNs. In a cooperative network, we show that the problem is polynomially solvable. We also present a distributed algorithm iteratively balancing the load. We show how to estimate the distance between the current solution and the optimum based on the amount of load exchanged by the algorithm. During the experimental evaluation, we show that the distributed algorithm is efficient, therefore it can be used in networks with dynamically changing loads. In a network of selfish organizations, we prove that the price of anarchy (the worst-case loss of performance due to selfishness) is low when the network is homogeneous and the servers are loaded (the request handling time is high compared to the communication delay). After relaxing these assumptions, we assess the loss of performance caused by the selfishness experimentally, showing that it remains low. Our results indicate that a set of servers handling requests, connected in a heterogeneous network, can be efficiently managed by a distributed algorithm. Additionally, even if the network is organizationally distributed, with individual organizations optimizing performance of their requests, the network remains efficient.",piotr skowron,distributed algorithm,2013.0,10.1109/IPDPSW.2013.21,"2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum",Skowron2013,False,,IEEE,Not available,Network Delay-Aware Load Balancing in Selfish and Cooperative Distributed Systems,fc60b1bb89747a09a889abb542672d4f,https://ieeexplore.ieee.org/document/6650867/
2431,"We consider a geographically distributed request processing system composed of various organizations and their servers connected by the Internet. The latency a user observes is a sum of communication delays and the time needed to handle the request on a server. The handling time depends on the server congestion, i.e. the total number of requests a server must handle. We analyze the problem of balancing the load in a network of servers in order to minimize the total observed latency. We consider both cooperative and selfish organizations (each organization aiming to minimize the latency of the locally-produced requests). The problem can be generalized to the task scheduling in a distributed cloud; or to content delivery in an organizationally-distributed CDNs. In a cooperative network, we show that the problem is polynomially solvable. We also present a distributed algorithm iteratively balancing the load. We show how to estimate the distance between the current solution and the optimum based on the amount of load exchanged by the algorithm. During the experimental evaluation, we show that the distributed algorithm is efficient, therefore it can be used in networks with dynamically changing loads. In a network of selfish organizations, we prove that the price of anarchy (the worst-case loss of performance due to selfishness) is low when the network is homogeneous and the servers are loaded (the request handling time is high compared to the communication delay). After relaxing these assumptions, we assess the loss of performance caused by the selfishness experimentally, showing that it remains low. Our results indicate that a set of servers handling requests, connected in a heterogeneous network, can be efficiently managed by a distributed algorithm. Additionally, even if the network is organizationally distributed, with individual organizations optimizing performance of their requests, the network remains efficient.",piotr skowron,price of anarchy,2013.0,10.1109/IPDPSW.2013.21,"2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum",Skowron2013,False,,IEEE,Not available,Network Delay-Aware Load Balancing in Selfish and Cooperative Distributed Systems,fc60b1bb89747a09a889abb542672d4f,https://ieeexplore.ieee.org/document/6650867/
2432,"We consider a geographically distributed request processing system composed of various organizations and their servers connected by the Internet. The latency a user observes is a sum of communication delays and the time needed to handle the request on a server. The handling time depends on the server congestion, i.e. the total number of requests a server must handle. We analyze the problem of balancing the load in a network of servers in order to minimize the total observed latency. We consider both cooperative and selfish organizations (each organization aiming to minimize the latency of the locally-produced requests). The problem can be generalized to the task scheduling in a distributed cloud; or to content delivery in an organizationally-distributed CDNs. In a cooperative network, we show that the problem is polynomially solvable. We also present a distributed algorithm iteratively balancing the load. We show how to estimate the distance between the current solution and the optimum based on the amount of load exchanged by the algorithm. During the experimental evaluation, we show that the distributed algorithm is efficient, therefore it can be used in networks with dynamically changing loads. In a network of selfish organizations, we prove that the price of anarchy (the worst-case loss of performance due to selfishness) is low when the network is homogeneous and the servers are loaded (the request handling time is high compared to the communication delay). After relaxing these assumptions, we assess the loss of performance caused by the selfishness experimentally, showing that it remains low. Our results indicate that a set of servers handling requests, connected in a heterogeneous network, can be efficiently managed by a distributed algorithm. Additionally, even if the network is organizationally distributed, with individual organizations optimizing performance of their requests, the network remains efficient.",krzysztof rzadca,load balancing,2013.0,10.1109/IPDPSW.2013.21,"2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum",Skowron2013,False,,IEEE,Not available,Network Delay-Aware Load Balancing in Selfish and Cooperative Distributed Systems,fc60b1bb89747a09a889abb542672d4f,https://ieeexplore.ieee.org/document/6650867/
2433,"We consider a geographically distributed request processing system composed of various organizations and their servers connected by the Internet. The latency a user observes is a sum of communication delays and the time needed to handle the request on a server. The handling time depends on the server congestion, i.e. the total number of requests a server must handle. We analyze the problem of balancing the load in a network of servers in order to minimize the total observed latency. We consider both cooperative and selfish organizations (each organization aiming to minimize the latency of the locally-produced requests). The problem can be generalized to the task scheduling in a distributed cloud; or to content delivery in an organizationally-distributed CDNs. In a cooperative network, we show that the problem is polynomially solvable. We also present a distributed algorithm iteratively balancing the load. We show how to estimate the distance between the current solution and the optimum based on the amount of load exchanged by the algorithm. During the experimental evaluation, we show that the distributed algorithm is efficient, therefore it can be used in networks with dynamically changing loads. In a network of selfish organizations, we prove that the price of anarchy (the worst-case loss of performance due to selfishness) is low when the network is homogeneous and the servers are loaded (the request handling time is high compared to the communication delay). After relaxing these assumptions, we assess the loss of performance caused by the selfishness experimentally, showing that it remains low. Our results indicate that a set of servers handling requests, connected in a heterogeneous network, can be efficiently managed by a distributed algorithm. Additionally, even if the network is organizationally distributed, with individual organizations optimizing performance of their requests, the network remains efficient.",krzysztof rzadca,distributed algorithm,2013.0,10.1109/IPDPSW.2013.21,"2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum",Skowron2013,False,,IEEE,Not available,Network Delay-Aware Load Balancing in Selfish and Cooperative Distributed Systems,fc60b1bb89747a09a889abb542672d4f,https://ieeexplore.ieee.org/document/6650867/
2434,"We consider a geographically distributed request processing system composed of various organizations and their servers connected by the Internet. The latency a user observes is a sum of communication delays and the time needed to handle the request on a server. The handling time depends on the server congestion, i.e. the total number of requests a server must handle. We analyze the problem of balancing the load in a network of servers in order to minimize the total observed latency. We consider both cooperative and selfish organizations (each organization aiming to minimize the latency of the locally-produced requests). The problem can be generalized to the task scheduling in a distributed cloud; or to content delivery in an organizationally-distributed CDNs. In a cooperative network, we show that the problem is polynomially solvable. We also present a distributed algorithm iteratively balancing the load. We show how to estimate the distance between the current solution and the optimum based on the amount of load exchanged by the algorithm. During the experimental evaluation, we show that the distributed algorithm is efficient, therefore it can be used in networks with dynamically changing loads. In a network of selfish organizations, we prove that the price of anarchy (the worst-case loss of performance due to selfishness) is low when the network is homogeneous and the servers are loaded (the request handling time is high compared to the communication delay). After relaxing these assumptions, we assess the loss of performance caused by the selfishness experimentally, showing that it remains low. Our results indicate that a set of servers handling requests, connected in a heterogeneous network, can be efficiently managed by a distributed algorithm. Additionally, even if the network is organizationally distributed, with individual organizations optimizing performance of their requests, the network remains efficient.",krzysztof rzadca,price of anarchy,2013.0,10.1109/IPDPSW.2013.21,"2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum",Skowron2013,False,,IEEE,Not available,Network Delay-Aware Load Balancing in Selfish and Cooperative Distributed Systems,fc60b1bb89747a09a889abb542672d4f,https://ieeexplore.ieee.org/document/6650867/
2435,"A classic optimization problem in network routing is to minimize C + D, where C is the maximum edge congestion and D is the maximum path length (also known as dilation). The problem of computing the optimal C* + D* is NP-complete even when either C* or D* is a small constant. We study routing games in general networks where each player i selfishly selects a path that minimizes C&lt;sub&gt;i&lt;/sub&gt; + D&lt;sub&gt;i&lt;/sub&gt; the sum of congestion and dilation of the player's path. We first show that there are instances of this game without Nash equilibria. We then turn to the related quality of routing (QoR) games which always have Nash equilibria. QoR games represent networks with a small number of service classes where paths in different classes do not interfere with each other (with frequency or time division multiplexing). QoR games have O(log&lt;sup&gt;4&lt;/sup&gt; n) price of anarchy when either C* or D* is a constant. Thus, Nash equilibria of QoR games give poly-log approximations to hard optimization problems.",costas busch,Algorithmic game theory,2012.0,10.1109/TC.2011.145,IEEE Transactions on Computers,Busch2012,False,,IEEE,Not available,Approximating Congestion + Dilation in Networks via &amp;#x0022;Quality of Routing&amp;amp;#x201D; Games,9915f48a2e9721b4a32e0a807083d647,https://ieeexplore.ieee.org/document/5963649/
2436,"A classic optimization problem in network routing is to minimize C + D, where C is the maximum edge congestion and D is the maximum path length (also known as dilation). The problem of computing the optimal C* + D* is NP-complete even when either C* or D* is a small constant. We study routing games in general networks where each player i selfishly selects a path that minimizes C&lt;sub&gt;i&lt;/sub&gt; + D&lt;sub&gt;i&lt;/sub&gt; the sum of congestion and dilation of the player's path. We first show that there are instances of this game without Nash equilibria. We then turn to the related quality of routing (QoR) games which always have Nash equilibria. QoR games represent networks with a small number of service classes where paths in different classes do not interfere with each other (with frequency or time division multiplexing). QoR games have O(log&lt;sup&gt;4&lt;/sup&gt; n) price of anarchy when either C* or D* is a constant. Thus, Nash equilibria of QoR games give poly-log approximations to hard optimization problems.",costas busch,congestion game,2012.0,10.1109/TC.2011.145,IEEE Transactions on Computers,Busch2012,False,,IEEE,Not available,Approximating Congestion + Dilation in Networks via &amp;#x0022;Quality of Routing&amp;amp;#x201D; Games,9915f48a2e9721b4a32e0a807083d647,https://ieeexplore.ieee.org/document/5963649/
2437,"A classic optimization problem in network routing is to minimize C + D, where C is the maximum edge congestion and D is the maximum path length (also known as dilation). The problem of computing the optimal C* + D* is NP-complete even when either C* or D* is a small constant. We study routing games in general networks where each player i selfishly selects a path that minimizes C&lt;sub&gt;i&lt;/sub&gt; + D&lt;sub&gt;i&lt;/sub&gt; the sum of congestion and dilation of the player's path. We first show that there are instances of this game without Nash equilibria. We then turn to the related quality of routing (QoR) games which always have Nash equilibria. QoR games represent networks with a small number of service classes where paths in different classes do not interfere with each other (with frequency or time division multiplexing). QoR games have O(log&lt;sup&gt;4&lt;/sup&gt; n) price of anarchy when either C* or D* is a constant. Thus, Nash equilibria of QoR games give poly-log approximations to hard optimization problems.",costas busch,routing game,2012.0,10.1109/TC.2011.145,IEEE Transactions on Computers,Busch2012,False,,IEEE,Not available,Approximating Congestion + Dilation in Networks via &amp;#x0022;Quality of Routing&amp;amp;#x201D; Games,9915f48a2e9721b4a32e0a807083d647,https://ieeexplore.ieee.org/document/5963649/
2438,"A classic optimization problem in network routing is to minimize C + D, where C is the maximum edge congestion and D is the maximum path length (also known as dilation). The problem of computing the optimal C* + D* is NP-complete even when either C* or D* is a small constant. We study routing games in general networks where each player i selfishly selects a path that minimizes C&lt;sub&gt;i&lt;/sub&gt; + D&lt;sub&gt;i&lt;/sub&gt; the sum of congestion and dilation of the player's path. We first show that there are instances of this game without Nash equilibria. We then turn to the related quality of routing (QoR) games which always have Nash equilibria. QoR games represent networks with a small number of service classes where paths in different classes do not interfere with each other (with frequency or time division multiplexing). QoR games have O(log&lt;sup&gt;4&lt;/sup&gt; n) price of anarchy when either C* or D* is a constant. Thus, Nash equilibria of QoR games give poly-log approximations to hard optimization problems.",costas busch,Nash equilibrium,2012.0,10.1109/TC.2011.145,IEEE Transactions on Computers,Busch2012,False,,IEEE,Not available,Approximating Congestion + Dilation in Networks via &amp;#x0022;Quality of Routing&amp;amp;#x201D; Games,9915f48a2e9721b4a32e0a807083d647,https://ieeexplore.ieee.org/document/5963649/
2439,"A classic optimization problem in network routing is to minimize C + D, where C is the maximum edge congestion and D is the maximum path length (also known as dilation). The problem of computing the optimal C* + D* is NP-complete even when either C* or D* is a small constant. We study routing games in general networks where each player i selfishly selects a path that minimizes C&lt;sub&gt;i&lt;/sub&gt; + D&lt;sub&gt;i&lt;/sub&gt; the sum of congestion and dilation of the player's path. We first show that there are instances of this game without Nash equilibria. We then turn to the related quality of routing (QoR) games which always have Nash equilibria. QoR games represent networks with a small number of service classes where paths in different classes do not interfere with each other (with frequency or time division multiplexing). QoR games have O(log&lt;sup&gt;4&lt;/sup&gt; n) price of anarchy when either C* or D* is a constant. Thus, Nash equilibria of QoR games give poly-log approximations to hard optimization problems.",costas busch,price of anarchy.,2012.0,10.1109/TC.2011.145,IEEE Transactions on Computers,Busch2012,False,,IEEE,Not available,Approximating Congestion + Dilation in Networks via &amp;#x0022;Quality of Routing&amp;amp;#x201D; Games,9915f48a2e9721b4a32e0a807083d647,https://ieeexplore.ieee.org/document/5963649/
2440,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2441,"A classic optimization problem in network routing is to minimize C + D, where C is the maximum edge congestion and D is the maximum path length (also known as dilation). The problem of computing the optimal C* + D* is NP-complete even when either C* or D* is a small constant. We study routing games in general networks where each player i selfishly selects a path that minimizes C&lt;sub&gt;i&lt;/sub&gt; + D&lt;sub&gt;i&lt;/sub&gt; the sum of congestion and dilation of the player's path. We first show that there are instances of this game without Nash equilibria. We then turn to the related quality of routing (QoR) games which always have Nash equilibria. QoR games represent networks with a small number of service classes where paths in different classes do not interfere with each other (with frequency or time division multiplexing). QoR games have O(log&lt;sup&gt;4&lt;/sup&gt; n) price of anarchy when either C* or D* is a constant. Thus, Nash equilibria of QoR games give poly-log approximations to hard optimization problems.",rajgopal kannan,Algorithmic game theory,2012.0,10.1109/TC.2011.145,IEEE Transactions on Computers,Busch2012,False,,IEEE,Not available,Approximating Congestion + Dilation in Networks via &amp;#x0022;Quality of Routing&amp;amp;#x201D; Games,9915f48a2e9721b4a32e0a807083d647,https://ieeexplore.ieee.org/document/5963649/
2442,"A classic optimization problem in network routing is to minimize C + D, where C is the maximum edge congestion and D is the maximum path length (also known as dilation). The problem of computing the optimal C* + D* is NP-complete even when either C* or D* is a small constant. We study routing games in general networks where each player i selfishly selects a path that minimizes C&lt;sub&gt;i&lt;/sub&gt; + D&lt;sub&gt;i&lt;/sub&gt; the sum of congestion and dilation of the player's path. We first show that there are instances of this game without Nash equilibria. We then turn to the related quality of routing (QoR) games which always have Nash equilibria. QoR games represent networks with a small number of service classes where paths in different classes do not interfere with each other (with frequency or time division multiplexing). QoR games have O(log&lt;sup&gt;4&lt;/sup&gt; n) price of anarchy when either C* or D* is a constant. Thus, Nash equilibria of QoR games give poly-log approximations to hard optimization problems.",rajgopal kannan,congestion game,2012.0,10.1109/TC.2011.145,IEEE Transactions on Computers,Busch2012,False,,IEEE,Not available,Approximating Congestion + Dilation in Networks via &amp;#x0022;Quality of Routing&amp;amp;#x201D; Games,9915f48a2e9721b4a32e0a807083d647,https://ieeexplore.ieee.org/document/5963649/
2443,"A classic optimization problem in network routing is to minimize C + D, where C is the maximum edge congestion and D is the maximum path length (also known as dilation). The problem of computing the optimal C* + D* is NP-complete even when either C* or D* is a small constant. We study routing games in general networks where each player i selfishly selects a path that minimizes C&lt;sub&gt;i&lt;/sub&gt; + D&lt;sub&gt;i&lt;/sub&gt; the sum of congestion and dilation of the player's path. We first show that there are instances of this game without Nash equilibria. We then turn to the related quality of routing (QoR) games which always have Nash equilibria. QoR games represent networks with a small number of service classes where paths in different classes do not interfere with each other (with frequency or time division multiplexing). QoR games have O(log&lt;sup&gt;4&lt;/sup&gt; n) price of anarchy when either C* or D* is a constant. Thus, Nash equilibria of QoR games give poly-log approximations to hard optimization problems.",rajgopal kannan,routing game,2012.0,10.1109/TC.2011.145,IEEE Transactions on Computers,Busch2012,False,,IEEE,Not available,Approximating Congestion + Dilation in Networks via &amp;#x0022;Quality of Routing&amp;amp;#x201D; Games,9915f48a2e9721b4a32e0a807083d647,https://ieeexplore.ieee.org/document/5963649/
2444,"A classic optimization problem in network routing is to minimize C + D, where C is the maximum edge congestion and D is the maximum path length (also known as dilation). The problem of computing the optimal C* + D* is NP-complete even when either C* or D* is a small constant. We study routing games in general networks where each player i selfishly selects a path that minimizes C&lt;sub&gt;i&lt;/sub&gt; + D&lt;sub&gt;i&lt;/sub&gt; the sum of congestion and dilation of the player's path. We first show that there are instances of this game without Nash equilibria. We then turn to the related quality of routing (QoR) games which always have Nash equilibria. QoR games represent networks with a small number of service classes where paths in different classes do not interfere with each other (with frequency or time division multiplexing). QoR games have O(log&lt;sup&gt;4&lt;/sup&gt; n) price of anarchy when either C* or D* is a constant. Thus, Nash equilibria of QoR games give poly-log approximations to hard optimization problems.",rajgopal kannan,Nash equilibrium,2012.0,10.1109/TC.2011.145,IEEE Transactions on Computers,Busch2012,False,,IEEE,Not available,Approximating Congestion + Dilation in Networks via &amp;#x0022;Quality of Routing&amp;amp;#x201D; Games,9915f48a2e9721b4a32e0a807083d647,https://ieeexplore.ieee.org/document/5963649/
2445,"A classic optimization problem in network routing is to minimize C + D, where C is the maximum edge congestion and D is the maximum path length (also known as dilation). The problem of computing the optimal C* + D* is NP-complete even when either C* or D* is a small constant. We study routing games in general networks where each player i selfishly selects a path that minimizes C&lt;sub&gt;i&lt;/sub&gt; + D&lt;sub&gt;i&lt;/sub&gt; the sum of congestion and dilation of the player's path. We first show that there are instances of this game without Nash equilibria. We then turn to the related quality of routing (QoR) games which always have Nash equilibria. QoR games represent networks with a small number of service classes where paths in different classes do not interfere with each other (with frequency or time division multiplexing). QoR games have O(log&lt;sup&gt;4&lt;/sup&gt; n) price of anarchy when either C* or D* is a constant. Thus, Nash equilibria of QoR games give poly-log approximations to hard optimization problems.",rajgopal kannan,price of anarchy.,2012.0,10.1109/TC.2011.145,IEEE Transactions on Computers,Busch2012,False,,IEEE,Not available,Approximating Congestion + Dilation in Networks via &amp;#x0022;Quality of Routing&amp;amp;#x201D; Games,9915f48a2e9721b4a32e0a807083d647,https://ieeexplore.ieee.org/document/5963649/
2446,"A classic optimization problem in network routing is to minimize C + D, where C is the maximum edge congestion and D is the maximum path length (also known as dilation). The problem of computing the optimal C* + D* is NP-complete even when either C* or D* is a small constant. We study routing games in general networks where each player i selfishly selects a path that minimizes C&lt;sub&gt;i&lt;/sub&gt; + D&lt;sub&gt;i&lt;/sub&gt; the sum of congestion and dilation of the player's path. We first show that there are instances of this game without Nash equilibria. We then turn to the related quality of routing (QoR) games which always have Nash equilibria. QoR games represent networks with a small number of service classes where paths in different classes do not interfere with each other (with frequency or time division multiplexing). QoR games have O(log&lt;sup&gt;4&lt;/sup&gt; n) price of anarchy when either C* or D* is a constant. Thus, Nash equilibria of QoR games give poly-log approximations to hard optimization problems.",athanasios vasilakos,Algorithmic game theory,2012.0,10.1109/TC.2011.145,IEEE Transactions on Computers,Busch2012,False,,IEEE,Not available,Approximating Congestion + Dilation in Networks via &amp;#x0022;Quality of Routing&amp;amp;#x201D; Games,9915f48a2e9721b4a32e0a807083d647,https://ieeexplore.ieee.org/document/5963649/
2447,"A classic optimization problem in network routing is to minimize C + D, where C is the maximum edge congestion and D is the maximum path length (also known as dilation). The problem of computing the optimal C* + D* is NP-complete even when either C* or D* is a small constant. We study routing games in general networks where each player i selfishly selects a path that minimizes C&lt;sub&gt;i&lt;/sub&gt; + D&lt;sub&gt;i&lt;/sub&gt; the sum of congestion and dilation of the player's path. We first show that there are instances of this game without Nash equilibria. We then turn to the related quality of routing (QoR) games which always have Nash equilibria. QoR games represent networks with a small number of service classes where paths in different classes do not interfere with each other (with frequency or time division multiplexing). QoR games have O(log&lt;sup&gt;4&lt;/sup&gt; n) price of anarchy when either C* or D* is a constant. Thus, Nash equilibria of QoR games give poly-log approximations to hard optimization problems.",athanasios vasilakos,congestion game,2012.0,10.1109/TC.2011.145,IEEE Transactions on Computers,Busch2012,False,,IEEE,Not available,Approximating Congestion + Dilation in Networks via &amp;#x0022;Quality of Routing&amp;amp;#x201D; Games,9915f48a2e9721b4a32e0a807083d647,https://ieeexplore.ieee.org/document/5963649/
2448,"A classic optimization problem in network routing is to minimize C + D, where C is the maximum edge congestion and D is the maximum path length (also known as dilation). The problem of computing the optimal C* + D* is NP-complete even when either C* or D* is a small constant. We study routing games in general networks where each player i selfishly selects a path that minimizes C&lt;sub&gt;i&lt;/sub&gt; + D&lt;sub&gt;i&lt;/sub&gt; the sum of congestion and dilation of the player's path. We first show that there are instances of this game without Nash equilibria. We then turn to the related quality of routing (QoR) games which always have Nash equilibria. QoR games represent networks with a small number of service classes where paths in different classes do not interfere with each other (with frequency or time division multiplexing). QoR games have O(log&lt;sup&gt;4&lt;/sup&gt; n) price of anarchy when either C* or D* is a constant. Thus, Nash equilibria of QoR games give poly-log approximations to hard optimization problems.",athanasios vasilakos,routing game,2012.0,10.1109/TC.2011.145,IEEE Transactions on Computers,Busch2012,False,,IEEE,Not available,Approximating Congestion + Dilation in Networks via &amp;#x0022;Quality of Routing&amp;amp;#x201D; Games,9915f48a2e9721b4a32e0a807083d647,https://ieeexplore.ieee.org/document/5963649/
2449,"A classic optimization problem in network routing is to minimize C + D, where C is the maximum edge congestion and D is the maximum path length (also known as dilation). The problem of computing the optimal C* + D* is NP-complete even when either C* or D* is a small constant. We study routing games in general networks where each player i selfishly selects a path that minimizes C&lt;sub&gt;i&lt;/sub&gt; + D&lt;sub&gt;i&lt;/sub&gt; the sum of congestion and dilation of the player's path. We first show that there are instances of this game without Nash equilibria. We then turn to the related quality of routing (QoR) games which always have Nash equilibria. QoR games represent networks with a small number of service classes where paths in different classes do not interfere with each other (with frequency or time division multiplexing). QoR games have O(log&lt;sup&gt;4&lt;/sup&gt; n) price of anarchy when either C* or D* is a constant. Thus, Nash equilibria of QoR games give poly-log approximations to hard optimization problems.",athanasios vasilakos,Nash equilibrium,2012.0,10.1109/TC.2011.145,IEEE Transactions on Computers,Busch2012,False,,IEEE,Not available,Approximating Congestion + Dilation in Networks via &amp;#x0022;Quality of Routing&amp;amp;#x201D; Games,9915f48a2e9721b4a32e0a807083d647,https://ieeexplore.ieee.org/document/5963649/
2450,"A classic optimization problem in network routing is to minimize C + D, where C is the maximum edge congestion and D is the maximum path length (also known as dilation). The problem of computing the optimal C* + D* is NP-complete even when either C* or D* is a small constant. We study routing games in general networks where each player i selfishly selects a path that minimizes C&lt;sub&gt;i&lt;/sub&gt; + D&lt;sub&gt;i&lt;/sub&gt; the sum of congestion and dilation of the player's path. We first show that there are instances of this game without Nash equilibria. We then turn to the related quality of routing (QoR) games which always have Nash equilibria. QoR games represent networks with a small number of service classes where paths in different classes do not interfere with each other (with frequency or time division multiplexing). QoR games have O(log&lt;sup&gt;4&lt;/sup&gt; n) price of anarchy when either C* or D* is a constant. Thus, Nash equilibria of QoR games give poly-log approximations to hard optimization problems.",athanasios vasilakos,price of anarchy.,2012.0,10.1109/TC.2011.145,IEEE Transactions on Computers,Busch2012,False,,IEEE,Not available,Approximating Congestion + Dilation in Networks via &amp;#x0022;Quality of Routing&amp;amp;#x201D; Games,9915f48a2e9721b4a32e0a807083d647,https://ieeexplore.ieee.org/document/5963649/
2451,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2452,"Max-min fairness (MMF) is a widely known approach to a fair allocation of bandwidth to each of the users in a network. This allocation can be computed by uniformly raising the bandwidths of all users without violating capacity constraints. We consider an extension of these allocations by raising the bandwidth with arbitrary and not necessarily uniform time-depending velocities (allocation rates). These allocations are used in a game-theoretic context for routing choices, which we formalize in progressive filling games (PFGs). We present a variety of results for equilibria in PFGs. We show that these games possess pure Nash and strong equilibria. While computation in general is NP-hard, there are polynomial-time algorithms for prominent classes of Max-Min-Fair Games (MMFG), including the case when all users have the same source-destination pair. We characterize prices of anarchy and stability for pure Nash and strong equilibria in PFGs and MMFGs when players have different or the same source-destination pairs. In addition, we show that when a designer can adjust allocation rates, it is possible to design games with optimal strong equilibria. Some initial results on polynomial-time algorithms in this direction are also derived.",tobias harks,routing,2014.0,10.1109/INFOCOM.2014.6847957,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Harks2014,False,,IEEE,Not available,Routing games with progressive filling,6b17bacf29a5695f60101e6004d6507c,https://ieeexplore.ieee.org/document/6847957/
2453,"Max-min fairness (MMF) is a widely known approach to a fair allocation of bandwidth to each of the users in a network. This allocation can be computed by uniformly raising the bandwidths of all users without violating capacity constraints. We consider an extension of these allocations by raising the bandwidth with arbitrary and not necessarily uniform time-depending velocities (allocation rates). These allocations are used in a game-theoretic context for routing choices, which we formalize in progressive filling games (PFGs). We present a variety of results for equilibria in PFGs. We show that these games possess pure Nash and strong equilibria. While computation in general is NP-hard, there are polynomial-time algorithms for prominent classes of Max-Min-Fair Games (MMFG), including the case when all users have the same source-destination pair. We characterize prices of anarchy and stability for pure Nash and strong equilibria in PFGs and MMFGs when players have different or the same source-destination pairs. In addition, we show that when a designer can adjust allocation rates, it is possible to design games with optimal strong equilibria. Some initial results on polynomial-time algorithms in this direction are also derived.",tobias harks,congestion control,2014.0,10.1109/INFOCOM.2014.6847957,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Harks2014,False,,IEEE,Not available,Routing games with progressive filling,6b17bacf29a5695f60101e6004d6507c,https://ieeexplore.ieee.org/document/6847957/
2454,"Max-min fairness (MMF) is a widely known approach to a fair allocation of bandwidth to each of the users in a network. This allocation can be computed by uniformly raising the bandwidths of all users without violating capacity constraints. We consider an extension of these allocations by raising the bandwidth with arbitrary and not necessarily uniform time-depending velocities (allocation rates). These allocations are used in a game-theoretic context for routing choices, which we formalize in progressive filling games (PFGs). We present a variety of results for equilibria in PFGs. We show that these games possess pure Nash and strong equilibria. While computation in general is NP-hard, there are polynomial-time algorithms for prominent classes of Max-Min-Fair Games (MMFG), including the case when all users have the same source-destination pair. We characterize prices of anarchy and stability for pure Nash and strong equilibria in PFGs and MMFGs when players have different or the same source-destination pairs. In addition, we show that when a designer can adjust allocation rates, it is possible to design games with optimal strong equilibria. Some initial results on polynomial-time algorithms in this direction are also derived.",tobias harks,existence of strong and Nash equilibrium,2014.0,10.1109/INFOCOM.2014.6847957,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Harks2014,False,,IEEE,Not available,Routing games with progressive filling,6b17bacf29a5695f60101e6004d6507c,https://ieeexplore.ieee.org/document/6847957/
2455,"Max-min fairness (MMF) is a widely known approach to a fair allocation of bandwidth to each of the users in a network. This allocation can be computed by uniformly raising the bandwidths of all users without violating capacity constraints. We consider an extension of these allocations by raising the bandwidth with arbitrary and not necessarily uniform time-depending velocities (allocation rates). These allocations are used in a game-theoretic context for routing choices, which we formalize in progressive filling games (PFGs). We present a variety of results for equilibria in PFGs. We show that these games possess pure Nash and strong equilibria. While computation in general is NP-hard, there are polynomial-time algorithms for prominent classes of Max-Min-Fair Games (MMFG), including the case when all users have the same source-destination pair. We characterize prices of anarchy and stability for pure Nash and strong equilibria in PFGs and MMFGs when players have different or the same source-destination pairs. In addition, we show that when a designer can adjust allocation rates, it is possible to design games with optimal strong equilibria. Some initial results on polynomial-time algorithms in this direction are also derived.",tobias harks,complexity and convergence,2014.0,10.1109/INFOCOM.2014.6847957,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Harks2014,False,,IEEE,Not available,Routing games with progressive filling,6b17bacf29a5695f60101e6004d6507c,https://ieeexplore.ieee.org/document/6847957/
2456,"Max-min fairness (MMF) is a widely known approach to a fair allocation of bandwidth to each of the users in a network. This allocation can be computed by uniformly raising the bandwidths of all users without violating capacity constraints. We consider an extension of these allocations by raising the bandwidth with arbitrary and not necessarily uniform time-depending velocities (allocation rates). These allocations are used in a game-theoretic context for routing choices, which we formalize in progressive filling games (PFGs). We present a variety of results for equilibria in PFGs. We show that these games possess pure Nash and strong equilibria. While computation in general is NP-hard, there are polynomial-time algorithms for prominent classes of Max-Min-Fair Games (MMFG), including the case when all users have the same source-destination pair. We characterize prices of anarchy and stability for pure Nash and strong equilibria in PFGs and MMFGs when players have different or the same source-destination pairs. In addition, we show that when a designer can adjust allocation rates, it is possible to design games with optimal strong equilibria. Some initial results on polynomial-time algorithms in this direction are also derived.",tobias harks,price of anarchy,2014.0,10.1109/INFOCOM.2014.6847957,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Harks2014,False,,IEEE,Not available,Routing games with progressive filling,6b17bacf29a5695f60101e6004d6507c,https://ieeexplore.ieee.org/document/6847957/
2457,"Max-min fairness (MMF) is a widely known approach to a fair allocation of bandwidth to each of the users in a network. This allocation can be computed by uniformly raising the bandwidths of all users without violating capacity constraints. We consider an extension of these allocations by raising the bandwidth with arbitrary and not necessarily uniform time-depending velocities (allocation rates). These allocations are used in a game-theoretic context for routing choices, which we formalize in progressive filling games (PFGs). We present a variety of results for equilibria in PFGs. We show that these games possess pure Nash and strong equilibria. While computation in general is NP-hard, there are polynomial-time algorithms for prominent classes of Max-Min-Fair Games (MMFG), including the case when all users have the same source-destination pair. We characterize prices of anarchy and stability for pure Nash and strong equilibria in PFGs and MMFGs when players have different or the same source-destination pairs. In addition, we show that when a designer can adjust allocation rates, it is possible to design games with optimal strong equilibria. Some initial results on polynomial-time algorithms in this direction are also derived.",martin hoefer,routing,2014.0,10.1109/INFOCOM.2014.6847957,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Harks2014,False,,IEEE,Not available,Routing games with progressive filling,6b17bacf29a5695f60101e6004d6507c,https://ieeexplore.ieee.org/document/6847957/
2458,"Max-min fairness (MMF) is a widely known approach to a fair allocation of bandwidth to each of the users in a network. This allocation can be computed by uniformly raising the bandwidths of all users without violating capacity constraints. We consider an extension of these allocations by raising the bandwidth with arbitrary and not necessarily uniform time-depending velocities (allocation rates). These allocations are used in a game-theoretic context for routing choices, which we formalize in progressive filling games (PFGs). We present a variety of results for equilibria in PFGs. We show that these games possess pure Nash and strong equilibria. While computation in general is NP-hard, there are polynomial-time algorithms for prominent classes of Max-Min-Fair Games (MMFG), including the case when all users have the same source-destination pair. We characterize prices of anarchy and stability for pure Nash and strong equilibria in PFGs and MMFGs when players have different or the same source-destination pairs. In addition, we show that when a designer can adjust allocation rates, it is possible to design games with optimal strong equilibria. Some initial results on polynomial-time algorithms in this direction are also derived.",martin hoefer,congestion control,2014.0,10.1109/INFOCOM.2014.6847957,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Harks2014,False,,IEEE,Not available,Routing games with progressive filling,6b17bacf29a5695f60101e6004d6507c,https://ieeexplore.ieee.org/document/6847957/
2459,"Max-min fairness (MMF) is a widely known approach to a fair allocation of bandwidth to each of the users in a network. This allocation can be computed by uniformly raising the bandwidths of all users without violating capacity constraints. We consider an extension of these allocations by raising the bandwidth with arbitrary and not necessarily uniform time-depending velocities (allocation rates). These allocations are used in a game-theoretic context for routing choices, which we formalize in progressive filling games (PFGs). We present a variety of results for equilibria in PFGs. We show that these games possess pure Nash and strong equilibria. While computation in general is NP-hard, there are polynomial-time algorithms for prominent classes of Max-Min-Fair Games (MMFG), including the case when all users have the same source-destination pair. We characterize prices of anarchy and stability for pure Nash and strong equilibria in PFGs and MMFGs when players have different or the same source-destination pairs. In addition, we show that when a designer can adjust allocation rates, it is possible to design games with optimal strong equilibria. Some initial results on polynomial-time algorithms in this direction are also derived.",martin hoefer,existence of strong and Nash equilibrium,2014.0,10.1109/INFOCOM.2014.6847957,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Harks2014,False,,IEEE,Not available,Routing games with progressive filling,6b17bacf29a5695f60101e6004d6507c,https://ieeexplore.ieee.org/document/6847957/
2460,"Max-min fairness (MMF) is a widely known approach to a fair allocation of bandwidth to each of the users in a network. This allocation can be computed by uniformly raising the bandwidths of all users without violating capacity constraints. We consider an extension of these allocations by raising the bandwidth with arbitrary and not necessarily uniform time-depending velocities (allocation rates). These allocations are used in a game-theoretic context for routing choices, which we formalize in progressive filling games (PFGs). We present a variety of results for equilibria in PFGs. We show that these games possess pure Nash and strong equilibria. While computation in general is NP-hard, there are polynomial-time algorithms for prominent classes of Max-Min-Fair Games (MMFG), including the case when all users have the same source-destination pair. We characterize prices of anarchy and stability for pure Nash and strong equilibria in PFGs and MMFGs when players have different or the same source-destination pairs. In addition, we show that when a designer can adjust allocation rates, it is possible to design games with optimal strong equilibria. Some initial results on polynomial-time algorithms in this direction are also derived.",martin hoefer,complexity and convergence,2014.0,10.1109/INFOCOM.2014.6847957,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Harks2014,False,,IEEE,Not available,Routing games with progressive filling,6b17bacf29a5695f60101e6004d6507c,https://ieeexplore.ieee.org/document/6847957/
2461,"Max-min fairness (MMF) is a widely known approach to a fair allocation of bandwidth to each of the users in a network. This allocation can be computed by uniformly raising the bandwidths of all users without violating capacity constraints. We consider an extension of these allocations by raising the bandwidth with arbitrary and not necessarily uniform time-depending velocities (allocation rates). These allocations are used in a game-theoretic context for routing choices, which we formalize in progressive filling games (PFGs). We present a variety of results for equilibria in PFGs. We show that these games possess pure Nash and strong equilibria. While computation in general is NP-hard, there are polynomial-time algorithms for prominent classes of Max-Min-Fair Games (MMFG), including the case when all users have the same source-destination pair. We characterize prices of anarchy and stability for pure Nash and strong equilibria in PFGs and MMFGs when players have different or the same source-destination pairs. In addition, we show that when a designer can adjust allocation rates, it is possible to design games with optimal strong equilibria. Some initial results on polynomial-time algorithms in this direction are also derived.",martin hoefer,price of anarchy,2014.0,10.1109/INFOCOM.2014.6847957,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Harks2014,False,,IEEE,Not available,Routing games with progressive filling,6b17bacf29a5695f60101e6004d6507c,https://ieeexplore.ieee.org/document/6847957/
2462,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2463,"Max-min fairness (MMF) is a widely known approach to a fair allocation of bandwidth to each of the users in a network. This allocation can be computed by uniformly raising the bandwidths of all users without violating capacity constraints. We consider an extension of these allocations by raising the bandwidth with arbitrary and not necessarily uniform time-depending velocities (allocation rates). These allocations are used in a game-theoretic context for routing choices, which we formalize in progressive filling games (PFGs). We present a variety of results for equilibria in PFGs. We show that these games possess pure Nash and strong equilibria. While computation in general is NP-hard, there are polynomial-time algorithms for prominent classes of Max-Min-Fair Games (MMFG), including the case when all users have the same source-destination pair. We characterize prices of anarchy and stability for pure Nash and strong equilibria in PFGs and MMFGs when players have different or the same source-destination pairs. In addition, we show that when a designer can adjust allocation rates, it is possible to design games with optimal strong equilibria. Some initial results on polynomial-time algorithms in this direction are also derived.",kevin schewior,routing,2014.0,10.1109/INFOCOM.2014.6847957,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Harks2014,False,,IEEE,Not available,Routing games with progressive filling,6b17bacf29a5695f60101e6004d6507c,https://ieeexplore.ieee.org/document/6847957/
2464,"Max-min fairness (MMF) is a widely known approach to a fair allocation of bandwidth to each of the users in a network. This allocation can be computed by uniformly raising the bandwidths of all users without violating capacity constraints. We consider an extension of these allocations by raising the bandwidth with arbitrary and not necessarily uniform time-depending velocities (allocation rates). These allocations are used in a game-theoretic context for routing choices, which we formalize in progressive filling games (PFGs). We present a variety of results for equilibria in PFGs. We show that these games possess pure Nash and strong equilibria. While computation in general is NP-hard, there are polynomial-time algorithms for prominent classes of Max-Min-Fair Games (MMFG), including the case when all users have the same source-destination pair. We characterize prices of anarchy and stability for pure Nash and strong equilibria in PFGs and MMFGs when players have different or the same source-destination pairs. In addition, we show that when a designer can adjust allocation rates, it is possible to design games with optimal strong equilibria. Some initial results on polynomial-time algorithms in this direction are also derived.",kevin schewior,congestion control,2014.0,10.1109/INFOCOM.2014.6847957,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Harks2014,False,,IEEE,Not available,Routing games with progressive filling,6b17bacf29a5695f60101e6004d6507c,https://ieeexplore.ieee.org/document/6847957/
2465,"Max-min fairness (MMF) is a widely known approach to a fair allocation of bandwidth to each of the users in a network. This allocation can be computed by uniformly raising the bandwidths of all users without violating capacity constraints. We consider an extension of these allocations by raising the bandwidth with arbitrary and not necessarily uniform time-depending velocities (allocation rates). These allocations are used in a game-theoretic context for routing choices, which we formalize in progressive filling games (PFGs). We present a variety of results for equilibria in PFGs. We show that these games possess pure Nash and strong equilibria. While computation in general is NP-hard, there are polynomial-time algorithms for prominent classes of Max-Min-Fair Games (MMFG), including the case when all users have the same source-destination pair. We characterize prices of anarchy and stability for pure Nash and strong equilibria in PFGs and MMFGs when players have different or the same source-destination pairs. In addition, we show that when a designer can adjust allocation rates, it is possible to design games with optimal strong equilibria. Some initial results on polynomial-time algorithms in this direction are also derived.",kevin schewior,existence of strong and Nash equilibrium,2014.0,10.1109/INFOCOM.2014.6847957,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Harks2014,False,,IEEE,Not available,Routing games with progressive filling,6b17bacf29a5695f60101e6004d6507c,https://ieeexplore.ieee.org/document/6847957/
2466,"Max-min fairness (MMF) is a widely known approach to a fair allocation of bandwidth to each of the users in a network. This allocation can be computed by uniformly raising the bandwidths of all users without violating capacity constraints. We consider an extension of these allocations by raising the bandwidth with arbitrary and not necessarily uniform time-depending velocities (allocation rates). These allocations are used in a game-theoretic context for routing choices, which we formalize in progressive filling games (PFGs). We present a variety of results for equilibria in PFGs. We show that these games possess pure Nash and strong equilibria. While computation in general is NP-hard, there are polynomial-time algorithms for prominent classes of Max-Min-Fair Games (MMFG), including the case when all users have the same source-destination pair. We characterize prices of anarchy and stability for pure Nash and strong equilibria in PFGs and MMFGs when players have different or the same source-destination pairs. In addition, we show that when a designer can adjust allocation rates, it is possible to design games with optimal strong equilibria. Some initial results on polynomial-time algorithms in this direction are also derived.",kevin schewior,complexity and convergence,2014.0,10.1109/INFOCOM.2014.6847957,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Harks2014,False,,IEEE,Not available,Routing games with progressive filling,6b17bacf29a5695f60101e6004d6507c,https://ieeexplore.ieee.org/document/6847957/
2467,"Max-min fairness (MMF) is a widely known approach to a fair allocation of bandwidth to each of the users in a network. This allocation can be computed by uniformly raising the bandwidths of all users without violating capacity constraints. We consider an extension of these allocations by raising the bandwidth with arbitrary and not necessarily uniform time-depending velocities (allocation rates). These allocations are used in a game-theoretic context for routing choices, which we formalize in progressive filling games (PFGs). We present a variety of results for equilibria in PFGs. We show that these games possess pure Nash and strong equilibria. While computation in general is NP-hard, there are polynomial-time algorithms for prominent classes of Max-Min-Fair Games (MMFG), including the case when all users have the same source-destination pair. We characterize prices of anarchy and stability for pure Nash and strong equilibria in PFGs and MMFGs when players have different or the same source-destination pairs. In addition, we show that when a designer can adjust allocation rates, it is possible to design games with optimal strong equilibria. Some initial results on polynomial-time algorithms in this direction are also derived.",kevin schewior,price of anarchy,2014.0,10.1109/INFOCOM.2014.6847957,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Harks2014,False,,IEEE,Not available,Routing games with progressive filling,6b17bacf29a5695f60101e6004d6507c,https://ieeexplore.ieee.org/document/6847957/
2468,"Max-min fairness (MMF) is a widely known approach to a fair allocation of bandwidth to each of the users in a network. This allocation can be computed by uniformly raising the bandwidths of all users without violating capacity constraints. We consider an extension of these allocations by raising the bandwidth with arbitrary and not necessarily uniform time-depending velocities (allocation rates). These allocations are used in a game-theoretic context for routing choices, which we formalize in progressive filling games (PFGs). We present a variety of results for equilibria in PFGs. We show that these games possess pure Nash and strong equilibria. While computation in general is NP-hard, there are polynomial-time algorithms for prominent classes of Max-Min-Fair Games (MMFG), including the case when all users have the same source-destination pair. We characterize prices of anarchy and stability for pure Nash and strong equilibria in PFGs and MMFGs when players have different or the same source-destination pairs. In addition, we show that when a designer can adjust allocation rates, it is possible to design games with optimal strong equilibria. Some initial results on polynomial-time algorithms in this direction are also derived.",alexander skopalik,routing,2014.0,10.1109/INFOCOM.2014.6847957,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Harks2014,False,,IEEE,Not available,Routing games with progressive filling,6b17bacf29a5695f60101e6004d6507c,https://ieeexplore.ieee.org/document/6847957/
2469,"Max-min fairness (MMF) is a widely known approach to a fair allocation of bandwidth to each of the users in a network. This allocation can be computed by uniformly raising the bandwidths of all users without violating capacity constraints. We consider an extension of these allocations by raising the bandwidth with arbitrary and not necessarily uniform time-depending velocities (allocation rates). These allocations are used in a game-theoretic context for routing choices, which we formalize in progressive filling games (PFGs). We present a variety of results for equilibria in PFGs. We show that these games possess pure Nash and strong equilibria. While computation in general is NP-hard, there are polynomial-time algorithms for prominent classes of Max-Min-Fair Games (MMFG), including the case when all users have the same source-destination pair. We characterize prices of anarchy and stability for pure Nash and strong equilibria in PFGs and MMFGs when players have different or the same source-destination pairs. In addition, we show that when a designer can adjust allocation rates, it is possible to design games with optimal strong equilibria. Some initial results on polynomial-time algorithms in this direction are also derived.",alexander skopalik,congestion control,2014.0,10.1109/INFOCOM.2014.6847957,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Harks2014,False,,IEEE,Not available,Routing games with progressive filling,6b17bacf29a5695f60101e6004d6507c,https://ieeexplore.ieee.org/document/6847957/
2470,"Max-min fairness (MMF) is a widely known approach to a fair allocation of bandwidth to each of the users in a network. This allocation can be computed by uniformly raising the bandwidths of all users without violating capacity constraints. We consider an extension of these allocations by raising the bandwidth with arbitrary and not necessarily uniform time-depending velocities (allocation rates). These allocations are used in a game-theoretic context for routing choices, which we formalize in progressive filling games (PFGs). We present a variety of results for equilibria in PFGs. We show that these games possess pure Nash and strong equilibria. While computation in general is NP-hard, there are polynomial-time algorithms for prominent classes of Max-Min-Fair Games (MMFG), including the case when all users have the same source-destination pair. We characterize prices of anarchy and stability for pure Nash and strong equilibria in PFGs and MMFGs when players have different or the same source-destination pairs. In addition, we show that when a designer can adjust allocation rates, it is possible to design games with optimal strong equilibria. Some initial results on polynomial-time algorithms in this direction are also derived.",alexander skopalik,existence of strong and Nash equilibrium,2014.0,10.1109/INFOCOM.2014.6847957,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Harks2014,False,,IEEE,Not available,Routing games with progressive filling,6b17bacf29a5695f60101e6004d6507c,https://ieeexplore.ieee.org/document/6847957/
2471,"Max-min fairness (MMF) is a widely known approach to a fair allocation of bandwidth to each of the users in a network. This allocation can be computed by uniformly raising the bandwidths of all users without violating capacity constraints. We consider an extension of these allocations by raising the bandwidth with arbitrary and not necessarily uniform time-depending velocities (allocation rates). These allocations are used in a game-theoretic context for routing choices, which we formalize in progressive filling games (PFGs). We present a variety of results for equilibria in PFGs. We show that these games possess pure Nash and strong equilibria. While computation in general is NP-hard, there are polynomial-time algorithms for prominent classes of Max-Min-Fair Games (MMFG), including the case when all users have the same source-destination pair. We characterize prices of anarchy and stability for pure Nash and strong equilibria in PFGs and MMFGs when players have different or the same source-destination pairs. In addition, we show that when a designer can adjust allocation rates, it is possible to design games with optimal strong equilibria. Some initial results on polynomial-time algorithms in this direction are also derived.",alexander skopalik,complexity and convergence,2014.0,10.1109/INFOCOM.2014.6847957,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Harks2014,False,,IEEE,Not available,Routing games with progressive filling,6b17bacf29a5695f60101e6004d6507c,https://ieeexplore.ieee.org/document/6847957/
2472,"Max-min fairness (MMF) is a widely known approach to a fair allocation of bandwidth to each of the users in a network. This allocation can be computed by uniformly raising the bandwidths of all users without violating capacity constraints. We consider an extension of these allocations by raising the bandwidth with arbitrary and not necessarily uniform time-depending velocities (allocation rates). These allocations are used in a game-theoretic context for routing choices, which we formalize in progressive filling games (PFGs). We present a variety of results for equilibria in PFGs. We show that these games possess pure Nash and strong equilibria. While computation in general is NP-hard, there are polynomial-time algorithms for prominent classes of Max-Min-Fair Games (MMFG), including the case when all users have the same source-destination pair. We characterize prices of anarchy and stability for pure Nash and strong equilibria in PFGs and MMFGs when players have different or the same source-destination pairs. In addition, we show that when a designer can adjust allocation rates, it is possible to design games with optimal strong equilibria. Some initial results on polynomial-time algorithms in this direction are also derived.",alexander skopalik,price of anarchy,2014.0,10.1109/INFOCOM.2014.6847957,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Harks2014,False,,IEEE,Not available,Routing games with progressive filling,6b17bacf29a5695f60101e6004d6507c,https://ieeexplore.ieee.org/document/6847957/
2473,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2474,"We introduce a network design game where the objective of the players is to design the interconnections between the nodes of two different networks G&lt;sub&gt;1&lt;/sub&gt; and G&lt;sub&gt;2&lt;/sub&gt; in order to maximize certain local utility functions. In this setting, each player is associated with a node in G&lt;sub&gt;1&lt;/sub&gt; and has functional dependencies on certain nodes in G&lt;sub&gt;2&lt;/sub&gt; . We use a distance-based utility for the players in which the goal of each player is to purchase a set of edges (incident to its associated node) such that the sum of the distances between its associated node and the nodes it depends on G&lt;sub&gt;2&lt;/sub&gt; is minimized. We consider a heterogeneous set of players (i.e., players have their own costs and benefits for constructing edges). We show that finding a best response of a player in this game is NP-hard. Despite this, we characterize some properties of the best response actions, which are helpful in determining a Nash equilibrium for certain instances of this game. In particular, we prove the existence of pure Nash equilibria in this game when G&lt;sub&gt;2&lt;/sub&gt; contains a star subgraph, and provide an algorithm that outputs such an equilibrium for any set of players. Finally, we show that the price of anarchy in this game can be arbitrarily large.",ebrahim shahrivar,Interconnected networks,2017.0,10.1109/JSAC.2017.2659358,IEEE Journal on Selected Areas in Communications,Shahrivar2017,False,,IEEE,Not available,The Game-Theoretic Formation of Interconnections Between Networks,6b993a9efbdbdac58cf381e4b3ea6a00,https://ieeexplore.ieee.org/document/7835681/
2475,"We introduce a network design game where the objective of the players is to design the interconnections between the nodes of two different networks G&lt;sub&gt;1&lt;/sub&gt; and G&lt;sub&gt;2&lt;/sub&gt; in order to maximize certain local utility functions. In this setting, each player is associated with a node in G&lt;sub&gt;1&lt;/sub&gt; and has functional dependencies on certain nodes in G&lt;sub&gt;2&lt;/sub&gt; . We use a distance-based utility for the players in which the goal of each player is to purchase a set of edges (incident to its associated node) such that the sum of the distances between its associated node and the nodes it depends on G&lt;sub&gt;2&lt;/sub&gt; is minimized. We consider a heterogeneous set of players (i.e., players have their own costs and benefits for constructing edges). We show that finding a best response of a player in this game is NP-hard. Despite this, we characterize some properties of the best response actions, which are helpful in determining a Nash equilibrium for certain instances of this game. In particular, we prove the existence of pure Nash equilibria in this game when G&lt;sub&gt;2&lt;/sub&gt; contains a star subgraph, and provide an algorithm that outputs such an equilibrium for any set of players. Finally, we show that the price of anarchy in this game can be arbitrarily large.",ebrahim shahrivar,network design,2017.0,10.1109/JSAC.2017.2659358,IEEE Journal on Selected Areas in Communications,Shahrivar2017,False,,IEEE,Not available,The Game-Theoretic Formation of Interconnections Between Networks,6b993a9efbdbdac58cf381e4b3ea6a00,https://ieeexplore.ieee.org/document/7835681/
2476,"We introduce a network design game where the objective of the players is to design the interconnections between the nodes of two different networks G&lt;sub&gt;1&lt;/sub&gt; and G&lt;sub&gt;2&lt;/sub&gt; in order to maximize certain local utility functions. In this setting, each player is associated with a node in G&lt;sub&gt;1&lt;/sub&gt; and has functional dependencies on certain nodes in G&lt;sub&gt;2&lt;/sub&gt; . We use a distance-based utility for the players in which the goal of each player is to purchase a set of edges (incident to its associated node) such that the sum of the distances between its associated node and the nodes it depends on G&lt;sub&gt;2&lt;/sub&gt; is minimized. We consider a heterogeneous set of players (i.e., players have their own costs and benefits for constructing edges). We show that finding a best response of a player in this game is NP-hard. Despite this, we characterize some properties of the best response actions, which are helpful in determining a Nash equilibrium for certain instances of this game. In particular, we prove the existence of pure Nash equilibria in this game when G&lt;sub&gt;2&lt;/sub&gt; contains a star subgraph, and provide an algorithm that outputs such an equilibrium for any set of players. Finally, we show that the price of anarchy in this game can be arbitrarily large.",ebrahim shahrivar,NP-hardness,2017.0,10.1109/JSAC.2017.2659358,IEEE Journal on Selected Areas in Communications,Shahrivar2017,False,,IEEE,Not available,The Game-Theoretic Formation of Interconnections Between Networks,6b993a9efbdbdac58cf381e4b3ea6a00,https://ieeexplore.ieee.org/document/7835681/
2477,"We introduce a network design game where the objective of the players is to design the interconnections between the nodes of two different networks G&lt;sub&gt;1&lt;/sub&gt; and G&lt;sub&gt;2&lt;/sub&gt; in order to maximize certain local utility functions. In this setting, each player is associated with a node in G&lt;sub&gt;1&lt;/sub&gt; and has functional dependencies on certain nodes in G&lt;sub&gt;2&lt;/sub&gt; . We use a distance-based utility for the players in which the goal of each player is to purchase a set of edges (incident to its associated node) such that the sum of the distances between its associated node and the nodes it depends on G&lt;sub&gt;2&lt;/sub&gt; is minimized. We consider a heterogeneous set of players (i.e., players have their own costs and benefits for constructing edges). We show that finding a best response of a player in this game is NP-hard. Despite this, we characterize some properties of the best response actions, which are helpful in determining a Nash equilibrium for certain instances of this game. In particular, we prove the existence of pure Nash equilibria in this game when G&lt;sub&gt;2&lt;/sub&gt; contains a star subgraph, and provide an algorithm that outputs such an equilibrium for any set of players. Finally, we show that the price of anarchy in this game can be arbitrarily large.",ebrahim shahrivar,Nash equilibria,2017.0,10.1109/JSAC.2017.2659358,IEEE Journal on Selected Areas in Communications,Shahrivar2017,False,,IEEE,Not available,The Game-Theoretic Formation of Interconnections Between Networks,6b993a9efbdbdac58cf381e4b3ea6a00,https://ieeexplore.ieee.org/document/7835681/
2478,"We introduce a network design game where the objective of the players is to design the interconnections between the nodes of two different networks G&lt;sub&gt;1&lt;/sub&gt; and G&lt;sub&gt;2&lt;/sub&gt; in order to maximize certain local utility functions. In this setting, each player is associated with a node in G&lt;sub&gt;1&lt;/sub&gt; and has functional dependencies on certain nodes in G&lt;sub&gt;2&lt;/sub&gt; . We use a distance-based utility for the players in which the goal of each player is to purchase a set of edges (incident to its associated node) such that the sum of the distances between its associated node and the nodes it depends on G&lt;sub&gt;2&lt;/sub&gt; is minimized. We consider a heterogeneous set of players (i.e., players have their own costs and benefits for constructing edges). We show that finding a best response of a player in this game is NP-hard. Despite this, we characterize some properties of the best response actions, which are helpful in determining a Nash equilibrium for certain instances of this game. In particular, we prove the existence of pure Nash equilibria in this game when G&lt;sub&gt;2&lt;/sub&gt; contains a star subgraph, and provide an algorithm that outputs such an equilibrium for any set of players. Finally, we show that the price of anarchy in this game can be arbitrarily large.",ebrahim shahrivar,price of anarchy,2017.0,10.1109/JSAC.2017.2659358,IEEE Journal on Selected Areas in Communications,Shahrivar2017,False,,IEEE,Not available,The Game-Theoretic Formation of Interconnections Between Networks,6b993a9efbdbdac58cf381e4b3ea6a00,https://ieeexplore.ieee.org/document/7835681/
2479,"We introduce a network design game where the objective of the players is to design the interconnections between the nodes of two different networks G&lt;sub&gt;1&lt;/sub&gt; and G&lt;sub&gt;2&lt;/sub&gt; in order to maximize certain local utility functions. In this setting, each player is associated with a node in G&lt;sub&gt;1&lt;/sub&gt; and has functional dependencies on certain nodes in G&lt;sub&gt;2&lt;/sub&gt; . We use a distance-based utility for the players in which the goal of each player is to purchase a set of edges (incident to its associated node) such that the sum of the distances between its associated node and the nodes it depends on G&lt;sub&gt;2&lt;/sub&gt; is minimized. We consider a heterogeneous set of players (i.e., players have their own costs and benefits for constructing edges). We show that finding a best response of a player in this game is NP-hard. Despite this, we characterize some properties of the best response actions, which are helpful in determining a Nash equilibrium for certain instances of this game. In particular, we prove the existence of pure Nash equilibria in this game when G&lt;sub&gt;2&lt;/sub&gt; contains a star subgraph, and provide an algorithm that outputs such an equilibrium for any set of players. Finally, we show that the price of anarchy in this game can be arbitrarily large.",ebrahim shahrivar,hub-and-spoke,2017.0,10.1109/JSAC.2017.2659358,IEEE Journal on Selected Areas in Communications,Shahrivar2017,False,,IEEE,Not available,The Game-Theoretic Formation of Interconnections Between Networks,6b993a9efbdbdac58cf381e4b3ea6a00,https://ieeexplore.ieee.org/document/7835681/
2480,"We introduce a network design game where the objective of the players is to design the interconnections between the nodes of two different networks G&lt;sub&gt;1&lt;/sub&gt; and G&lt;sub&gt;2&lt;/sub&gt; in order to maximize certain local utility functions. In this setting, each player is associated with a node in G&lt;sub&gt;1&lt;/sub&gt; and has functional dependencies on certain nodes in G&lt;sub&gt;2&lt;/sub&gt; . We use a distance-based utility for the players in which the goal of each player is to purchase a set of edges (incident to its associated node) such that the sum of the distances between its associated node and the nodes it depends on G&lt;sub&gt;2&lt;/sub&gt; is minimized. We consider a heterogeneous set of players (i.e., players have their own costs and benefits for constructing edges). We show that finding a best response of a player in this game is NP-hard. Despite this, we characterize some properties of the best response actions, which are helpful in determining a Nash equilibrium for certain instances of this game. In particular, we prove the existence of pure Nash equilibria in this game when G&lt;sub&gt;2&lt;/sub&gt; contains a star subgraph, and provide an algorithm that outputs such an equilibrium for any set of players. Finally, we show that the price of anarchy in this game can be arbitrarily large.",shreyas sundaram,Interconnected networks,2017.0,10.1109/JSAC.2017.2659358,IEEE Journal on Selected Areas in Communications,Shahrivar2017,False,,IEEE,Not available,The Game-Theoretic Formation of Interconnections Between Networks,6b993a9efbdbdac58cf381e4b3ea6a00,https://ieeexplore.ieee.org/document/7835681/
2481,"We introduce a network design game where the objective of the players is to design the interconnections between the nodes of two different networks G&lt;sub&gt;1&lt;/sub&gt; and G&lt;sub&gt;2&lt;/sub&gt; in order to maximize certain local utility functions. In this setting, each player is associated with a node in G&lt;sub&gt;1&lt;/sub&gt; and has functional dependencies on certain nodes in G&lt;sub&gt;2&lt;/sub&gt; . We use a distance-based utility for the players in which the goal of each player is to purchase a set of edges (incident to its associated node) such that the sum of the distances between its associated node and the nodes it depends on G&lt;sub&gt;2&lt;/sub&gt; is minimized. We consider a heterogeneous set of players (i.e., players have their own costs and benefits for constructing edges). We show that finding a best response of a player in this game is NP-hard. Despite this, we characterize some properties of the best response actions, which are helpful in determining a Nash equilibrium for certain instances of this game. In particular, we prove the existence of pure Nash equilibria in this game when G&lt;sub&gt;2&lt;/sub&gt; contains a star subgraph, and provide an algorithm that outputs such an equilibrium for any set of players. Finally, we show that the price of anarchy in this game can be arbitrarily large.",shreyas sundaram,network design,2017.0,10.1109/JSAC.2017.2659358,IEEE Journal on Selected Areas in Communications,Shahrivar2017,False,,IEEE,Not available,The Game-Theoretic Formation of Interconnections Between Networks,6b993a9efbdbdac58cf381e4b3ea6a00,https://ieeexplore.ieee.org/document/7835681/
2482,"We introduce a network design game where the objective of the players is to design the interconnections between the nodes of two different networks G&lt;sub&gt;1&lt;/sub&gt; and G&lt;sub&gt;2&lt;/sub&gt; in order to maximize certain local utility functions. In this setting, each player is associated with a node in G&lt;sub&gt;1&lt;/sub&gt; and has functional dependencies on certain nodes in G&lt;sub&gt;2&lt;/sub&gt; . We use a distance-based utility for the players in which the goal of each player is to purchase a set of edges (incident to its associated node) such that the sum of the distances between its associated node and the nodes it depends on G&lt;sub&gt;2&lt;/sub&gt; is minimized. We consider a heterogeneous set of players (i.e., players have their own costs and benefits for constructing edges). We show that finding a best response of a player in this game is NP-hard. Despite this, we characterize some properties of the best response actions, which are helpful in determining a Nash equilibrium for certain instances of this game. In particular, we prove the existence of pure Nash equilibria in this game when G&lt;sub&gt;2&lt;/sub&gt; contains a star subgraph, and provide an algorithm that outputs such an equilibrium for any set of players. Finally, we show that the price of anarchy in this game can be arbitrarily large.",shreyas sundaram,NP-hardness,2017.0,10.1109/JSAC.2017.2659358,IEEE Journal on Selected Areas in Communications,Shahrivar2017,False,,IEEE,Not available,The Game-Theoretic Formation of Interconnections Between Networks,6b993a9efbdbdac58cf381e4b3ea6a00,https://ieeexplore.ieee.org/document/7835681/
2483,"We introduce a network design game where the objective of the players is to design the interconnections between the nodes of two different networks G&lt;sub&gt;1&lt;/sub&gt; and G&lt;sub&gt;2&lt;/sub&gt; in order to maximize certain local utility functions. In this setting, each player is associated with a node in G&lt;sub&gt;1&lt;/sub&gt; and has functional dependencies on certain nodes in G&lt;sub&gt;2&lt;/sub&gt; . We use a distance-based utility for the players in which the goal of each player is to purchase a set of edges (incident to its associated node) such that the sum of the distances between its associated node and the nodes it depends on G&lt;sub&gt;2&lt;/sub&gt; is minimized. We consider a heterogeneous set of players (i.e., players have their own costs and benefits for constructing edges). We show that finding a best response of a player in this game is NP-hard. Despite this, we characterize some properties of the best response actions, which are helpful in determining a Nash equilibrium for certain instances of this game. In particular, we prove the existence of pure Nash equilibria in this game when G&lt;sub&gt;2&lt;/sub&gt; contains a star subgraph, and provide an algorithm that outputs such an equilibrium for any set of players. Finally, we show that the price of anarchy in this game can be arbitrarily large.",shreyas sundaram,Nash equilibria,2017.0,10.1109/JSAC.2017.2659358,IEEE Journal on Selected Areas in Communications,Shahrivar2017,False,,IEEE,Not available,The Game-Theoretic Formation of Interconnections Between Networks,6b993a9efbdbdac58cf381e4b3ea6a00,https://ieeexplore.ieee.org/document/7835681/
2484,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2485,"We introduce a network design game where the objective of the players is to design the interconnections between the nodes of two different networks G&lt;sub&gt;1&lt;/sub&gt; and G&lt;sub&gt;2&lt;/sub&gt; in order to maximize certain local utility functions. In this setting, each player is associated with a node in G&lt;sub&gt;1&lt;/sub&gt; and has functional dependencies on certain nodes in G&lt;sub&gt;2&lt;/sub&gt; . We use a distance-based utility for the players in which the goal of each player is to purchase a set of edges (incident to its associated node) such that the sum of the distances between its associated node and the nodes it depends on G&lt;sub&gt;2&lt;/sub&gt; is minimized. We consider a heterogeneous set of players (i.e., players have their own costs and benefits for constructing edges). We show that finding a best response of a player in this game is NP-hard. Despite this, we characterize some properties of the best response actions, which are helpful in determining a Nash equilibrium for certain instances of this game. In particular, we prove the existence of pure Nash equilibria in this game when G&lt;sub&gt;2&lt;/sub&gt; contains a star subgraph, and provide an algorithm that outputs such an equilibrium for any set of players. Finally, we show that the price of anarchy in this game can be arbitrarily large.",shreyas sundaram,price of anarchy,2017.0,10.1109/JSAC.2017.2659358,IEEE Journal on Selected Areas in Communications,Shahrivar2017,False,,IEEE,Not available,The Game-Theoretic Formation of Interconnections Between Networks,6b993a9efbdbdac58cf381e4b3ea6a00,https://ieeexplore.ieee.org/document/7835681/
2486,"We introduce a network design game where the objective of the players is to design the interconnections between the nodes of two different networks G&lt;sub&gt;1&lt;/sub&gt; and G&lt;sub&gt;2&lt;/sub&gt; in order to maximize certain local utility functions. In this setting, each player is associated with a node in G&lt;sub&gt;1&lt;/sub&gt; and has functional dependencies on certain nodes in G&lt;sub&gt;2&lt;/sub&gt; . We use a distance-based utility for the players in which the goal of each player is to purchase a set of edges (incident to its associated node) such that the sum of the distances between its associated node and the nodes it depends on G&lt;sub&gt;2&lt;/sub&gt; is minimized. We consider a heterogeneous set of players (i.e., players have their own costs and benefits for constructing edges). We show that finding a best response of a player in this game is NP-hard. Despite this, we characterize some properties of the best response actions, which are helpful in determining a Nash equilibrium for certain instances of this game. In particular, we prove the existence of pure Nash equilibria in this game when G&lt;sub&gt;2&lt;/sub&gt; contains a star subgraph, and provide an algorithm that outputs such an equilibrium for any set of players. Finally, we show that the price of anarchy in this game can be arbitrarily large.",shreyas sundaram,hub-and-spoke,2017.0,10.1109/JSAC.2017.2659358,IEEE Journal on Selected Areas in Communications,Shahrivar2017,False,,IEEE,Not available,The Game-Theoretic Formation of Interconnections Between Networks,6b993a9efbdbdac58cf381e4b3ea6a00,https://ieeexplore.ieee.org/document/7835681/
2487,"The number of tasks performed on wireless mobile devices instead of stationary computers is steadily increasing. Due to the limited resources of battery and computation capability on these devices, computation offloading became a relevant concept. We consider several mobile users with a splittable computation task each, which try to minimize their own computation time. All of them are connected to a central access point, where a cloudlet with limited computation power can be utilized for offloading fractions of their tasks. To account for the selfishness of the users and their individual goals, we propose a game theoretic framework resulting in a nonconvex generalized Nash game. The decision of each mobile user, which fraction of his task to offload, depends on the offloading decisions of the others, since they share the communication resources and computation capabilities of the cloudlet. We prove the existence and uniqueness of the generalized Nash equilibrium and propose an algorithm for computing it efficiently. In addition, we show that the price of anarchy of our model is one, which is the best possible value, and investigate the advantage of computation offloading numerically. Furthermore, we extend our model to a scenario, where mobile users are able to offload parts of their computation in repeated sessions during a given time period. This allows every mobile user to offload multiple successive tasks.",daniel nowak,Mobile Edge Computing,2018.0,10.1109/MobileCloud.2018.00022,"2018 6th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)",Nowak2018,False,,IEEE,Not available,A Generalized Nash Game for Mobile Edge Computation Offloading,669cd3cd3d554869621c5abac1669402,https://ieeexplore.ieee.org/document/8350444/
2488,"The number of tasks performed on wireless mobile devices instead of stationary computers is steadily increasing. Due to the limited resources of battery and computation capability on these devices, computation offloading became a relevant concept. We consider several mobile users with a splittable computation task each, which try to minimize their own computation time. All of them are connected to a central access point, where a cloudlet with limited computation power can be utilized for offloading fractions of their tasks. To account for the selfishness of the users and their individual goals, we propose a game theoretic framework resulting in a nonconvex generalized Nash game. The decision of each mobile user, which fraction of his task to offload, depends on the offloading decisions of the others, since they share the communication resources and computation capabilities of the cloudlet. We prove the existence and uniqueness of the generalized Nash equilibrium and propose an algorithm for computing it efficiently. In addition, we show that the price of anarchy of our model is one, which is the best possible value, and investigate the advantage of computation offloading numerically. Furthermore, we extend our model to a scenario, where mobile users are able to offload parts of their computation in repeated sessions during a given time period. This allows every mobile user to offload multiple successive tasks.",daniel nowak,Computation Offloading,2018.0,10.1109/MobileCloud.2018.00022,"2018 6th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)",Nowak2018,False,,IEEE,Not available,A Generalized Nash Game for Mobile Edge Computation Offloading,669cd3cd3d554869621c5abac1669402,https://ieeexplore.ieee.org/document/8350444/
2489,"The number of tasks performed on wireless mobile devices instead of stationary computers is steadily increasing. Due to the limited resources of battery and computation capability on these devices, computation offloading became a relevant concept. We consider several mobile users with a splittable computation task each, which try to minimize their own computation time. All of them are connected to a central access point, where a cloudlet with limited computation power can be utilized for offloading fractions of their tasks. To account for the selfishness of the users and their individual goals, we propose a game theoretic framework resulting in a nonconvex generalized Nash game. The decision of each mobile user, which fraction of his task to offload, depends on the offloading decisions of the others, since they share the communication resources and computation capabilities of the cloudlet. We prove the existence and uniqueness of the generalized Nash equilibrium and propose an algorithm for computing it efficiently. In addition, we show that the price of anarchy of our model is one, which is the best possible value, and investigate the advantage of computation offloading numerically. Furthermore, we extend our model to a scenario, where mobile users are able to offload parts of their computation in repeated sessions during a given time period. This allows every mobile user to offload multiple successive tasks.",daniel nowak,Game Theory,2018.0,10.1109/MobileCloud.2018.00022,"2018 6th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)",Nowak2018,False,,IEEE,Not available,A Generalized Nash Game for Mobile Edge Computation Offloading,669cd3cd3d554869621c5abac1669402,https://ieeexplore.ieee.org/document/8350444/
2490,"The number of tasks performed on wireless mobile devices instead of stationary computers is steadily increasing. Due to the limited resources of battery and computation capability on these devices, computation offloading became a relevant concept. We consider several mobile users with a splittable computation task each, which try to minimize their own computation time. All of them are connected to a central access point, where a cloudlet with limited computation power can be utilized for offloading fractions of their tasks. To account for the selfishness of the users and their individual goals, we propose a game theoretic framework resulting in a nonconvex generalized Nash game. The decision of each mobile user, which fraction of his task to offload, depends on the offloading decisions of the others, since they share the communication resources and computation capabilities of the cloudlet. We prove the existence and uniqueness of the generalized Nash equilibrium and propose an algorithm for computing it efficiently. In addition, we show that the price of anarchy of our model is one, which is the best possible value, and investigate the advantage of computation offloading numerically. Furthermore, we extend our model to a scenario, where mobile users are able to offload parts of their computation in repeated sessions during a given time period. This allows every mobile user to offload multiple successive tasks.",daniel nowak,Task Splitting,2018.0,10.1109/MobileCloud.2018.00022,"2018 6th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)",Nowak2018,False,,IEEE,Not available,A Generalized Nash Game for Mobile Edge Computation Offloading,669cd3cd3d554869621c5abac1669402,https://ieeexplore.ieee.org/document/8350444/
2491,"The number of tasks performed on wireless mobile devices instead of stationary computers is steadily increasing. Due to the limited resources of battery and computation capability on these devices, computation offloading became a relevant concept. We consider several mobile users with a splittable computation task each, which try to minimize their own computation time. All of them are connected to a central access point, where a cloudlet with limited computation power can be utilized for offloading fractions of their tasks. To account for the selfishness of the users and their individual goals, we propose a game theoretic framework resulting in a nonconvex generalized Nash game. The decision of each mobile user, which fraction of his task to offload, depends on the offloading decisions of the others, since they share the communication resources and computation capabilities of the cloudlet. We prove the existence and uniqueness of the generalized Nash equilibrium and propose an algorithm for computing it efficiently. In addition, we show that the price of anarchy of our model is one, which is the best possible value, and investigate the advantage of computation offloading numerically. Furthermore, we extend our model to a scenario, where mobile users are able to offload parts of their computation in repeated sessions during a given time period. This allows every mobile user to offload multiple successive tasks.",daniel nowak,Completion Time,2018.0,10.1109/MobileCloud.2018.00022,"2018 6th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)",Nowak2018,False,,IEEE,Not available,A Generalized Nash Game for Mobile Edge Computation Offloading,669cd3cd3d554869621c5abac1669402,https://ieeexplore.ieee.org/document/8350444/
2492,"The number of tasks performed on wireless mobile devices instead of stationary computers is steadily increasing. Due to the limited resources of battery and computation capability on these devices, computation offloading became a relevant concept. We consider several mobile users with a splittable computation task each, which try to minimize their own computation time. All of them are connected to a central access point, where a cloudlet with limited computation power can be utilized for offloading fractions of their tasks. To account for the selfishness of the users and their individual goals, we propose a game theoretic framework resulting in a nonconvex generalized Nash game. The decision of each mobile user, which fraction of his task to offload, depends on the offloading decisions of the others, since they share the communication resources and computation capabilities of the cloudlet. We prove the existence and uniqueness of the generalized Nash equilibrium and propose an algorithm for computing it efficiently. In addition, we show that the price of anarchy of our model is one, which is the best possible value, and investigate the advantage of computation offloading numerically. Furthermore, we extend our model to a scenario, where mobile users are able to offload parts of their computation in repeated sessions during a given time period. This allows every mobile user to offload multiple successive tasks.",daniel nowak,Price of Anarchy,2018.0,10.1109/MobileCloud.2018.00022,"2018 6th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)",Nowak2018,False,,IEEE,Not available,A Generalized Nash Game for Mobile Edge Computation Offloading,669cd3cd3d554869621c5abac1669402,https://ieeexplore.ieee.org/document/8350444/
2493,"The number of tasks performed on wireless mobile devices instead of stationary computers is steadily increasing. Due to the limited resources of battery and computation capability on these devices, computation offloading became a relevant concept. We consider several mobile users with a splittable computation task each, which try to minimize their own computation time. All of them are connected to a central access point, where a cloudlet with limited computation power can be utilized for offloading fractions of their tasks. To account for the selfishness of the users and their individual goals, we propose a game theoretic framework resulting in a nonconvex generalized Nash game. The decision of each mobile user, which fraction of his task to offload, depends on the offloading decisions of the others, since they share the communication resources and computation capabilities of the cloudlet. We prove the existence and uniqueness of the generalized Nash equilibrium and propose an algorithm for computing it efficiently. In addition, we show that the price of anarchy of our model is one, which is the best possible value, and investigate the advantage of computation offloading numerically. Furthermore, we extend our model to a scenario, where mobile users are able to offload parts of their computation in repeated sessions during a given time period. This allows every mobile user to offload multiple successive tasks.",tobias mahn,Mobile Edge Computing,2018.0,10.1109/MobileCloud.2018.00022,"2018 6th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)",Nowak2018,False,,IEEE,Not available,A Generalized Nash Game for Mobile Edge Computation Offloading,669cd3cd3d554869621c5abac1669402,https://ieeexplore.ieee.org/document/8350444/
2494,"The number of tasks performed on wireless mobile devices instead of stationary computers is steadily increasing. Due to the limited resources of battery and computation capability on these devices, computation offloading became a relevant concept. We consider several mobile users with a splittable computation task each, which try to minimize their own computation time. All of them are connected to a central access point, where a cloudlet with limited computation power can be utilized for offloading fractions of their tasks. To account for the selfishness of the users and their individual goals, we propose a game theoretic framework resulting in a nonconvex generalized Nash game. The decision of each mobile user, which fraction of his task to offload, depends on the offloading decisions of the others, since they share the communication resources and computation capabilities of the cloudlet. We prove the existence and uniqueness of the generalized Nash equilibrium and propose an algorithm for computing it efficiently. In addition, we show that the price of anarchy of our model is one, which is the best possible value, and investigate the advantage of computation offloading numerically. Furthermore, we extend our model to a scenario, where mobile users are able to offload parts of their computation in repeated sessions during a given time period. This allows every mobile user to offload multiple successive tasks.",tobias mahn,Computation Offloading,2018.0,10.1109/MobileCloud.2018.00022,"2018 6th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)",Nowak2018,False,,IEEE,Not available,A Generalized Nash Game for Mobile Edge Computation Offloading,669cd3cd3d554869621c5abac1669402,https://ieeexplore.ieee.org/document/8350444/
2495,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2496,"The number of tasks performed on wireless mobile devices instead of stationary computers is steadily increasing. Due to the limited resources of battery and computation capability on these devices, computation offloading became a relevant concept. We consider several mobile users with a splittable computation task each, which try to minimize their own computation time. All of them are connected to a central access point, where a cloudlet with limited computation power can be utilized for offloading fractions of their tasks. To account for the selfishness of the users and their individual goals, we propose a game theoretic framework resulting in a nonconvex generalized Nash game. The decision of each mobile user, which fraction of his task to offload, depends on the offloading decisions of the others, since they share the communication resources and computation capabilities of the cloudlet. We prove the existence and uniqueness of the generalized Nash equilibrium and propose an algorithm for computing it efficiently. In addition, we show that the price of anarchy of our model is one, which is the best possible value, and investigate the advantage of computation offloading numerically. Furthermore, we extend our model to a scenario, where mobile users are able to offload parts of their computation in repeated sessions during a given time period. This allows every mobile user to offload multiple successive tasks.",tobias mahn,Game Theory,2018.0,10.1109/MobileCloud.2018.00022,"2018 6th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)",Nowak2018,False,,IEEE,Not available,A Generalized Nash Game for Mobile Edge Computation Offloading,669cd3cd3d554869621c5abac1669402,https://ieeexplore.ieee.org/document/8350444/
2497,"The number of tasks performed on wireless mobile devices instead of stationary computers is steadily increasing. Due to the limited resources of battery and computation capability on these devices, computation offloading became a relevant concept. We consider several mobile users with a splittable computation task each, which try to minimize their own computation time. All of them are connected to a central access point, where a cloudlet with limited computation power can be utilized for offloading fractions of their tasks. To account for the selfishness of the users and their individual goals, we propose a game theoretic framework resulting in a nonconvex generalized Nash game. The decision of each mobile user, which fraction of his task to offload, depends on the offloading decisions of the others, since they share the communication resources and computation capabilities of the cloudlet. We prove the existence and uniqueness of the generalized Nash equilibrium and propose an algorithm for computing it efficiently. In addition, we show that the price of anarchy of our model is one, which is the best possible value, and investigate the advantage of computation offloading numerically. Furthermore, we extend our model to a scenario, where mobile users are able to offload parts of their computation in repeated sessions during a given time period. This allows every mobile user to offload multiple successive tasks.",tobias mahn,Task Splitting,2018.0,10.1109/MobileCloud.2018.00022,"2018 6th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)",Nowak2018,False,,IEEE,Not available,A Generalized Nash Game for Mobile Edge Computation Offloading,669cd3cd3d554869621c5abac1669402,https://ieeexplore.ieee.org/document/8350444/
2498,"The number of tasks performed on wireless mobile devices instead of stationary computers is steadily increasing. Due to the limited resources of battery and computation capability on these devices, computation offloading became a relevant concept. We consider several mobile users with a splittable computation task each, which try to minimize their own computation time. All of them are connected to a central access point, where a cloudlet with limited computation power can be utilized for offloading fractions of their tasks. To account for the selfishness of the users and their individual goals, we propose a game theoretic framework resulting in a nonconvex generalized Nash game. The decision of each mobile user, which fraction of his task to offload, depends on the offloading decisions of the others, since they share the communication resources and computation capabilities of the cloudlet. We prove the existence and uniqueness of the generalized Nash equilibrium and propose an algorithm for computing it efficiently. In addition, we show that the price of anarchy of our model is one, which is the best possible value, and investigate the advantage of computation offloading numerically. Furthermore, we extend our model to a scenario, where mobile users are able to offload parts of their computation in repeated sessions during a given time period. This allows every mobile user to offload multiple successive tasks.",tobias mahn,Completion Time,2018.0,10.1109/MobileCloud.2018.00022,"2018 6th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)",Nowak2018,False,,IEEE,Not available,A Generalized Nash Game for Mobile Edge Computation Offloading,669cd3cd3d554869621c5abac1669402,https://ieeexplore.ieee.org/document/8350444/
2499,"The number of tasks performed on wireless mobile devices instead of stationary computers is steadily increasing. Due to the limited resources of battery and computation capability on these devices, computation offloading became a relevant concept. We consider several mobile users with a splittable computation task each, which try to minimize their own computation time. All of them are connected to a central access point, where a cloudlet with limited computation power can be utilized for offloading fractions of their tasks. To account for the selfishness of the users and their individual goals, we propose a game theoretic framework resulting in a nonconvex generalized Nash game. The decision of each mobile user, which fraction of his task to offload, depends on the offloading decisions of the others, since they share the communication resources and computation capabilities of the cloudlet. We prove the existence and uniqueness of the generalized Nash equilibrium and propose an algorithm for computing it efficiently. In addition, we show that the price of anarchy of our model is one, which is the best possible value, and investigate the advantage of computation offloading numerically. Furthermore, we extend our model to a scenario, where mobile users are able to offload parts of their computation in repeated sessions during a given time period. This allows every mobile user to offload multiple successive tasks.",tobias mahn,Price of Anarchy,2018.0,10.1109/MobileCloud.2018.00022,"2018 6th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)",Nowak2018,False,,IEEE,Not available,A Generalized Nash Game for Mobile Edge Computation Offloading,669cd3cd3d554869621c5abac1669402,https://ieeexplore.ieee.org/document/8350444/
2500,"The number of tasks performed on wireless mobile devices instead of stationary computers is steadily increasing. Due to the limited resources of battery and computation capability on these devices, computation offloading became a relevant concept. We consider several mobile users with a splittable computation task each, which try to minimize their own computation time. All of them are connected to a central access point, where a cloudlet with limited computation power can be utilized for offloading fractions of their tasks. To account for the selfishness of the users and their individual goals, we propose a game theoretic framework resulting in a nonconvex generalized Nash game. The decision of each mobile user, which fraction of his task to offload, depends on the offloading decisions of the others, since they share the communication resources and computation capabilities of the cloudlet. We prove the existence and uniqueness of the generalized Nash equilibrium and propose an algorithm for computing it efficiently. In addition, we show that the price of anarchy of our model is one, which is the best possible value, and investigate the advantage of computation offloading numerically. Furthermore, we extend our model to a scenario, where mobile users are able to offload parts of their computation in repeated sessions during a given time period. This allows every mobile user to offload multiple successive tasks.",hussein al-shatri,Mobile Edge Computing,2018.0,10.1109/MobileCloud.2018.00022,"2018 6th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)",Nowak2018,False,,IEEE,Not available,A Generalized Nash Game for Mobile Edge Computation Offloading,669cd3cd3d554869621c5abac1669402,https://ieeexplore.ieee.org/document/8350444/
2501,"The number of tasks performed on wireless mobile devices instead of stationary computers is steadily increasing. Due to the limited resources of battery and computation capability on these devices, computation offloading became a relevant concept. We consider several mobile users with a splittable computation task each, which try to minimize their own computation time. All of them are connected to a central access point, where a cloudlet with limited computation power can be utilized for offloading fractions of their tasks. To account for the selfishness of the users and their individual goals, we propose a game theoretic framework resulting in a nonconvex generalized Nash game. The decision of each mobile user, which fraction of his task to offload, depends on the offloading decisions of the others, since they share the communication resources and computation capabilities of the cloudlet. We prove the existence and uniqueness of the generalized Nash equilibrium and propose an algorithm for computing it efficiently. In addition, we show that the price of anarchy of our model is one, which is the best possible value, and investigate the advantage of computation offloading numerically. Furthermore, we extend our model to a scenario, where mobile users are able to offload parts of their computation in repeated sessions during a given time period. This allows every mobile user to offload multiple successive tasks.",hussein al-shatri,Computation Offloading,2018.0,10.1109/MobileCloud.2018.00022,"2018 6th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)",Nowak2018,False,,IEEE,Not available,A Generalized Nash Game for Mobile Edge Computation Offloading,669cd3cd3d554869621c5abac1669402,https://ieeexplore.ieee.org/document/8350444/
2502,"The number of tasks performed on wireless mobile devices instead of stationary computers is steadily increasing. Due to the limited resources of battery and computation capability on these devices, computation offloading became a relevant concept. We consider several mobile users with a splittable computation task each, which try to minimize their own computation time. All of them are connected to a central access point, where a cloudlet with limited computation power can be utilized for offloading fractions of their tasks. To account for the selfishness of the users and their individual goals, we propose a game theoretic framework resulting in a nonconvex generalized Nash game. The decision of each mobile user, which fraction of his task to offload, depends on the offloading decisions of the others, since they share the communication resources and computation capabilities of the cloudlet. We prove the existence and uniqueness of the generalized Nash equilibrium and propose an algorithm for computing it efficiently. In addition, we show that the price of anarchy of our model is one, which is the best possible value, and investigate the advantage of computation offloading numerically. Furthermore, we extend our model to a scenario, where mobile users are able to offload parts of their computation in repeated sessions during a given time period. This allows every mobile user to offload multiple successive tasks.",hussein al-shatri,Game Theory,2018.0,10.1109/MobileCloud.2018.00022,"2018 6th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)",Nowak2018,False,,IEEE,Not available,A Generalized Nash Game for Mobile Edge Computation Offloading,669cd3cd3d554869621c5abac1669402,https://ieeexplore.ieee.org/document/8350444/
2503,"The number of tasks performed on wireless mobile devices instead of stationary computers is steadily increasing. Due to the limited resources of battery and computation capability on these devices, computation offloading became a relevant concept. We consider several mobile users with a splittable computation task each, which try to minimize their own computation time. All of them are connected to a central access point, where a cloudlet with limited computation power can be utilized for offloading fractions of their tasks. To account for the selfishness of the users and their individual goals, we propose a game theoretic framework resulting in a nonconvex generalized Nash game. The decision of each mobile user, which fraction of his task to offload, depends on the offloading decisions of the others, since they share the communication resources and computation capabilities of the cloudlet. We prove the existence and uniqueness of the generalized Nash equilibrium and propose an algorithm for computing it efficiently. In addition, we show that the price of anarchy of our model is one, which is the best possible value, and investigate the advantage of computation offloading numerically. Furthermore, we extend our model to a scenario, where mobile users are able to offload parts of their computation in repeated sessions during a given time period. This allows every mobile user to offload multiple successive tasks.",hussein al-shatri,Task Splitting,2018.0,10.1109/MobileCloud.2018.00022,"2018 6th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)",Nowak2018,False,,IEEE,Not available,A Generalized Nash Game for Mobile Edge Computation Offloading,669cd3cd3d554869621c5abac1669402,https://ieeexplore.ieee.org/document/8350444/
2504,"The number of tasks performed on wireless mobile devices instead of stationary computers is steadily increasing. Due to the limited resources of battery and computation capability on these devices, computation offloading became a relevant concept. We consider several mobile users with a splittable computation task each, which try to minimize their own computation time. All of them are connected to a central access point, where a cloudlet with limited computation power can be utilized for offloading fractions of their tasks. To account for the selfishness of the users and their individual goals, we propose a game theoretic framework resulting in a nonconvex generalized Nash game. The decision of each mobile user, which fraction of his task to offload, depends on the offloading decisions of the others, since they share the communication resources and computation capabilities of the cloudlet. We prove the existence and uniqueness of the generalized Nash equilibrium and propose an algorithm for computing it efficiently. In addition, we show that the price of anarchy of our model is one, which is the best possible value, and investigate the advantage of computation offloading numerically. Furthermore, we extend our model to a scenario, where mobile users are able to offload parts of their computation in repeated sessions during a given time period. This allows every mobile user to offload multiple successive tasks.",hussein al-shatri,Completion Time,2018.0,10.1109/MobileCloud.2018.00022,"2018 6th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)",Nowak2018,False,,IEEE,Not available,A Generalized Nash Game for Mobile Edge Computation Offloading,669cd3cd3d554869621c5abac1669402,https://ieeexplore.ieee.org/document/8350444/
2505,"The number of tasks performed on wireless mobile devices instead of stationary computers is steadily increasing. Due to the limited resources of battery and computation capability on these devices, computation offloading became a relevant concept. We consider several mobile users with a splittable computation task each, which try to minimize their own computation time. All of them are connected to a central access point, where a cloudlet with limited computation power can be utilized for offloading fractions of their tasks. To account for the selfishness of the users and their individual goals, we propose a game theoretic framework resulting in a nonconvex generalized Nash game. The decision of each mobile user, which fraction of his task to offload, depends on the offloading decisions of the others, since they share the communication resources and computation capabilities of the cloudlet. We prove the existence and uniqueness of the generalized Nash equilibrium and propose an algorithm for computing it efficiently. In addition, we show that the price of anarchy of our model is one, which is the best possible value, and investigate the advantage of computation offloading numerically. Furthermore, we extend our model to a scenario, where mobile users are able to offload parts of their computation in repeated sessions during a given time period. This allows every mobile user to offload multiple successive tasks.",hussein al-shatri,Price of Anarchy,2018.0,10.1109/MobileCloud.2018.00022,"2018 6th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)",Nowak2018,False,,IEEE,Not available,A Generalized Nash Game for Mobile Edge Computation Offloading,669cd3cd3d554869621c5abac1669402,https://ieeexplore.ieee.org/document/8350444/
2506,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2507,"The number of tasks performed on wireless mobile devices instead of stationary computers is steadily increasing. Due to the limited resources of battery and computation capability on these devices, computation offloading became a relevant concept. We consider several mobile users with a splittable computation task each, which try to minimize their own computation time. All of them are connected to a central access point, where a cloudlet with limited computation power can be utilized for offloading fractions of their tasks. To account for the selfishness of the users and their individual goals, we propose a game theoretic framework resulting in a nonconvex generalized Nash game. The decision of each mobile user, which fraction of his task to offload, depends on the offloading decisions of the others, since they share the communication resources and computation capabilities of the cloudlet. We prove the existence and uniqueness of the generalized Nash equilibrium and propose an algorithm for computing it efficiently. In addition, we show that the price of anarchy of our model is one, which is the best possible value, and investigate the advantage of computation offloading numerically. Furthermore, we extend our model to a scenario, where mobile users are able to offload parts of their computation in repeated sessions during a given time period. This allows every mobile user to offload multiple successive tasks.",alexandra schwartz,Mobile Edge Computing,2018.0,10.1109/MobileCloud.2018.00022,"2018 6th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)",Nowak2018,False,,IEEE,Not available,A Generalized Nash Game for Mobile Edge Computation Offloading,669cd3cd3d554869621c5abac1669402,https://ieeexplore.ieee.org/document/8350444/
2508,"The number of tasks performed on wireless mobile devices instead of stationary computers is steadily increasing. Due to the limited resources of battery and computation capability on these devices, computation offloading became a relevant concept. We consider several mobile users with a splittable computation task each, which try to minimize their own computation time. All of them are connected to a central access point, where a cloudlet with limited computation power can be utilized for offloading fractions of their tasks. To account for the selfishness of the users and their individual goals, we propose a game theoretic framework resulting in a nonconvex generalized Nash game. The decision of each mobile user, which fraction of his task to offload, depends on the offloading decisions of the others, since they share the communication resources and computation capabilities of the cloudlet. We prove the existence and uniqueness of the generalized Nash equilibrium and propose an algorithm for computing it efficiently. In addition, we show that the price of anarchy of our model is one, which is the best possible value, and investigate the advantage of computation offloading numerically. Furthermore, we extend our model to a scenario, where mobile users are able to offload parts of their computation in repeated sessions during a given time period. This allows every mobile user to offload multiple successive tasks.",alexandra schwartz,Computation Offloading,2018.0,10.1109/MobileCloud.2018.00022,"2018 6th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)",Nowak2018,False,,IEEE,Not available,A Generalized Nash Game for Mobile Edge Computation Offloading,669cd3cd3d554869621c5abac1669402,https://ieeexplore.ieee.org/document/8350444/
2509,"The number of tasks performed on wireless mobile devices instead of stationary computers is steadily increasing. Due to the limited resources of battery and computation capability on these devices, computation offloading became a relevant concept. We consider several mobile users with a splittable computation task each, which try to minimize their own computation time. All of them are connected to a central access point, where a cloudlet with limited computation power can be utilized for offloading fractions of their tasks. To account for the selfishness of the users and their individual goals, we propose a game theoretic framework resulting in a nonconvex generalized Nash game. The decision of each mobile user, which fraction of his task to offload, depends on the offloading decisions of the others, since they share the communication resources and computation capabilities of the cloudlet. We prove the existence and uniqueness of the generalized Nash equilibrium and propose an algorithm for computing it efficiently. In addition, we show that the price of anarchy of our model is one, which is the best possible value, and investigate the advantage of computation offloading numerically. Furthermore, we extend our model to a scenario, where mobile users are able to offload parts of their computation in repeated sessions during a given time period. This allows every mobile user to offload multiple successive tasks.",alexandra schwartz,Game Theory,2018.0,10.1109/MobileCloud.2018.00022,"2018 6th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)",Nowak2018,False,,IEEE,Not available,A Generalized Nash Game for Mobile Edge Computation Offloading,669cd3cd3d554869621c5abac1669402,https://ieeexplore.ieee.org/document/8350444/
2510,"The number of tasks performed on wireless mobile devices instead of stationary computers is steadily increasing. Due to the limited resources of battery and computation capability on these devices, computation offloading became a relevant concept. We consider several mobile users with a splittable computation task each, which try to minimize their own computation time. All of them are connected to a central access point, where a cloudlet with limited computation power can be utilized for offloading fractions of their tasks. To account for the selfishness of the users and their individual goals, we propose a game theoretic framework resulting in a nonconvex generalized Nash game. The decision of each mobile user, which fraction of his task to offload, depends on the offloading decisions of the others, since they share the communication resources and computation capabilities of the cloudlet. We prove the existence and uniqueness of the generalized Nash equilibrium and propose an algorithm for computing it efficiently. In addition, we show that the price of anarchy of our model is one, which is the best possible value, and investigate the advantage of computation offloading numerically. Furthermore, we extend our model to a scenario, where mobile users are able to offload parts of their computation in repeated sessions during a given time period. This allows every mobile user to offload multiple successive tasks.",alexandra schwartz,Task Splitting,2018.0,10.1109/MobileCloud.2018.00022,"2018 6th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)",Nowak2018,False,,IEEE,Not available,A Generalized Nash Game for Mobile Edge Computation Offloading,669cd3cd3d554869621c5abac1669402,https://ieeexplore.ieee.org/document/8350444/
2511,"The number of tasks performed on wireless mobile devices instead of stationary computers is steadily increasing. Due to the limited resources of battery and computation capability on these devices, computation offloading became a relevant concept. We consider several mobile users with a splittable computation task each, which try to minimize their own computation time. All of them are connected to a central access point, where a cloudlet with limited computation power can be utilized for offloading fractions of their tasks. To account for the selfishness of the users and their individual goals, we propose a game theoretic framework resulting in a nonconvex generalized Nash game. The decision of each mobile user, which fraction of his task to offload, depends on the offloading decisions of the others, since they share the communication resources and computation capabilities of the cloudlet. We prove the existence and uniqueness of the generalized Nash equilibrium and propose an algorithm for computing it efficiently. In addition, we show that the price of anarchy of our model is one, which is the best possible value, and investigate the advantage of computation offloading numerically. Furthermore, we extend our model to a scenario, where mobile users are able to offload parts of their computation in repeated sessions during a given time period. This allows every mobile user to offload multiple successive tasks.",alexandra schwartz,Completion Time,2018.0,10.1109/MobileCloud.2018.00022,"2018 6th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)",Nowak2018,False,,IEEE,Not available,A Generalized Nash Game for Mobile Edge Computation Offloading,669cd3cd3d554869621c5abac1669402,https://ieeexplore.ieee.org/document/8350444/
2512,"The number of tasks performed on wireless mobile devices instead of stationary computers is steadily increasing. Due to the limited resources of battery and computation capability on these devices, computation offloading became a relevant concept. We consider several mobile users with a splittable computation task each, which try to minimize their own computation time. All of them are connected to a central access point, where a cloudlet with limited computation power can be utilized for offloading fractions of their tasks. To account for the selfishness of the users and their individual goals, we propose a game theoretic framework resulting in a nonconvex generalized Nash game. The decision of each mobile user, which fraction of his task to offload, depends on the offloading decisions of the others, since they share the communication resources and computation capabilities of the cloudlet. We prove the existence and uniqueness of the generalized Nash equilibrium and propose an algorithm for computing it efficiently. In addition, we show that the price of anarchy of our model is one, which is the best possible value, and investigate the advantage of computation offloading numerically. Furthermore, we extend our model to a scenario, where mobile users are able to offload parts of their computation in repeated sessions during a given time period. This allows every mobile user to offload multiple successive tasks.",alexandra schwartz,Price of Anarchy,2018.0,10.1109/MobileCloud.2018.00022,"2018 6th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)",Nowak2018,False,,IEEE,Not available,A Generalized Nash Game for Mobile Edge Computation Offloading,669cd3cd3d554869621c5abac1669402,https://ieeexplore.ieee.org/document/8350444/
2513,"The number of tasks performed on wireless mobile devices instead of stationary computers is steadily increasing. Due to the limited resources of battery and computation capability on these devices, computation offloading became a relevant concept. We consider several mobile users with a splittable computation task each, which try to minimize their own computation time. All of them are connected to a central access point, where a cloudlet with limited computation power can be utilized for offloading fractions of their tasks. To account for the selfishness of the users and their individual goals, we propose a game theoretic framework resulting in a nonconvex generalized Nash game. The decision of each mobile user, which fraction of his task to offload, depends on the offloading decisions of the others, since they share the communication resources and computation capabilities of the cloudlet. We prove the existence and uniqueness of the generalized Nash equilibrium and propose an algorithm for computing it efficiently. In addition, we show that the price of anarchy of our model is one, which is the best possible value, and investigate the advantage of computation offloading numerically. Furthermore, we extend our model to a scenario, where mobile users are able to offload parts of their computation in repeated sessions during a given time period. This allows every mobile user to offload multiple successive tasks.",anja klein,Mobile Edge Computing,2018.0,10.1109/MobileCloud.2018.00022,"2018 6th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)",Nowak2018,False,,IEEE,Not available,A Generalized Nash Game for Mobile Edge Computation Offloading,669cd3cd3d554869621c5abac1669402,https://ieeexplore.ieee.org/document/8350444/
2514,"The number of tasks performed on wireless mobile devices instead of stationary computers is steadily increasing. Due to the limited resources of battery and computation capability on these devices, computation offloading became a relevant concept. We consider several mobile users with a splittable computation task each, which try to minimize their own computation time. All of them are connected to a central access point, where a cloudlet with limited computation power can be utilized for offloading fractions of their tasks. To account for the selfishness of the users and their individual goals, we propose a game theoretic framework resulting in a nonconvex generalized Nash game. The decision of each mobile user, which fraction of his task to offload, depends on the offloading decisions of the others, since they share the communication resources and computation capabilities of the cloudlet. We prove the existence and uniqueness of the generalized Nash equilibrium and propose an algorithm for computing it efficiently. In addition, we show that the price of anarchy of our model is one, which is the best possible value, and investigate the advantage of computation offloading numerically. Furthermore, we extend our model to a scenario, where mobile users are able to offload parts of their computation in repeated sessions during a given time period. This allows every mobile user to offload multiple successive tasks.",anja klein,Computation Offloading,2018.0,10.1109/MobileCloud.2018.00022,"2018 6th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)",Nowak2018,False,,IEEE,Not available,A Generalized Nash Game for Mobile Edge Computation Offloading,669cd3cd3d554869621c5abac1669402,https://ieeexplore.ieee.org/document/8350444/
2515,"The number of tasks performed on wireless mobile devices instead of stationary computers is steadily increasing. Due to the limited resources of battery and computation capability on these devices, computation offloading became a relevant concept. We consider several mobile users with a splittable computation task each, which try to minimize their own computation time. All of them are connected to a central access point, where a cloudlet with limited computation power can be utilized for offloading fractions of their tasks. To account for the selfishness of the users and their individual goals, we propose a game theoretic framework resulting in a nonconvex generalized Nash game. The decision of each mobile user, which fraction of his task to offload, depends on the offloading decisions of the others, since they share the communication resources and computation capabilities of the cloudlet. We prove the existence and uniqueness of the generalized Nash equilibrium and propose an algorithm for computing it efficiently. In addition, we show that the price of anarchy of our model is one, which is the best possible value, and investigate the advantage of computation offloading numerically. Furthermore, we extend our model to a scenario, where mobile users are able to offload parts of their computation in repeated sessions during a given time period. This allows every mobile user to offload multiple successive tasks.",anja klein,Game Theory,2018.0,10.1109/MobileCloud.2018.00022,"2018 6th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)",Nowak2018,False,,IEEE,Not available,A Generalized Nash Game for Mobile Edge Computation Offloading,669cd3cd3d554869621c5abac1669402,https://ieeexplore.ieee.org/document/8350444/
2516,"The number of tasks performed on wireless mobile devices instead of stationary computers is steadily increasing. Due to the limited resources of battery and computation capability on these devices, computation offloading became a relevant concept. We consider several mobile users with a splittable computation task each, which try to minimize their own computation time. All of them are connected to a central access point, where a cloudlet with limited computation power can be utilized for offloading fractions of their tasks. To account for the selfishness of the users and their individual goals, we propose a game theoretic framework resulting in a nonconvex generalized Nash game. The decision of each mobile user, which fraction of his task to offload, depends on the offloading decisions of the others, since they share the communication resources and computation capabilities of the cloudlet. We prove the existence and uniqueness of the generalized Nash equilibrium and propose an algorithm for computing it efficiently. In addition, we show that the price of anarchy of our model is one, which is the best possible value, and investigate the advantage of computation offloading numerically. Furthermore, we extend our model to a scenario, where mobile users are able to offload parts of their computation in repeated sessions during a given time period. This allows every mobile user to offload multiple successive tasks.",anja klein,Task Splitting,2018.0,10.1109/MobileCloud.2018.00022,"2018 6th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)",Nowak2018,False,,IEEE,Not available,A Generalized Nash Game for Mobile Edge Computation Offloading,669cd3cd3d554869621c5abac1669402,https://ieeexplore.ieee.org/document/8350444/
2517,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
2518,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2519,"The number of tasks performed on wireless mobile devices instead of stationary computers is steadily increasing. Due to the limited resources of battery and computation capability on these devices, computation offloading became a relevant concept. We consider several mobile users with a splittable computation task each, which try to minimize their own computation time. All of them are connected to a central access point, where a cloudlet with limited computation power can be utilized for offloading fractions of their tasks. To account for the selfishness of the users and their individual goals, we propose a game theoretic framework resulting in a nonconvex generalized Nash game. The decision of each mobile user, which fraction of his task to offload, depends on the offloading decisions of the others, since they share the communication resources and computation capabilities of the cloudlet. We prove the existence and uniqueness of the generalized Nash equilibrium and propose an algorithm for computing it efficiently. In addition, we show that the price of anarchy of our model is one, which is the best possible value, and investigate the advantage of computation offloading numerically. Furthermore, we extend our model to a scenario, where mobile users are able to offload parts of their computation in repeated sessions during a given time period. This allows every mobile user to offload multiple successive tasks.",anja klein,Completion Time,2018.0,10.1109/MobileCloud.2018.00022,"2018 6th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)",Nowak2018,False,,IEEE,Not available,A Generalized Nash Game for Mobile Edge Computation Offloading,669cd3cd3d554869621c5abac1669402,https://ieeexplore.ieee.org/document/8350444/
2520,"The number of tasks performed on wireless mobile devices instead of stationary computers is steadily increasing. Due to the limited resources of battery and computation capability on these devices, computation offloading became a relevant concept. We consider several mobile users with a splittable computation task each, which try to minimize their own computation time. All of them are connected to a central access point, where a cloudlet with limited computation power can be utilized for offloading fractions of their tasks. To account for the selfishness of the users and their individual goals, we propose a game theoretic framework resulting in a nonconvex generalized Nash game. The decision of each mobile user, which fraction of his task to offload, depends on the offloading decisions of the others, since they share the communication resources and computation capabilities of the cloudlet. We prove the existence and uniqueness of the generalized Nash equilibrium and propose an algorithm for computing it efficiently. In addition, we show that the price of anarchy of our model is one, which is the best possible value, and investigate the advantage of computation offloading numerically. Furthermore, we extend our model to a scenario, where mobile users are able to offload parts of their computation in repeated sessions during a given time period. This allows every mobile user to offload multiple successive tasks.",anja klein,Price of Anarchy,2018.0,10.1109/MobileCloud.2018.00022,"2018 6th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)",Nowak2018,False,,IEEE,Not available,A Generalized Nash Game for Mobile Edge Computation Offloading,669cd3cd3d554869621c5abac1669402,https://ieeexplore.ieee.org/document/8350444/
2521,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",a. kesselman,Energy efficiency,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
2522,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",a. kesselman,Ad hoc networks,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
2523,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",a. kesselman,Multimedia communication,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
2524,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",a. kesselman,Mobile ad hoc networks,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
2525,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",a. kesselman,Delay,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
2526,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",a. kesselman,Costs,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
2527,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",a. kesselman,Power system modeling,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
2528,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",a. kesselman,System performance,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
2529,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2530,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",a. kesselman,Broadcasting,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
2531,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",a. kesselman,Degradation,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
2532,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",d. kowalski,Energy efficiency,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
2533,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",d. kowalski,Ad hoc networks,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
2534,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",d. kowalski,Multimedia communication,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
2535,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",d. kowalski,Mobile ad hoc networks,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
2536,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",d. kowalski,Delay,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
2537,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",d. kowalski,Costs,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
2538,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",d. kowalski,Power system modeling,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
2539,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",d. kowalski,System performance,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
2540,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2541,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",d. kowalski,Broadcasting,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
2542,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",d. kowalski,Degradation,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
2543,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",m. segal,Energy efficiency,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
2544,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",m. segal,Ad hoc networks,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
2545,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",m. segal,Multimedia communication,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
2546,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",m. segal,Mobile ad hoc networks,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
2547,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",m. segal,Delay,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
2548,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",m. segal,Costs,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
2549,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",m. segal,Power system modeling,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
2550,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",m. segal,System performance,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
2551,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2552,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",m. segal,Broadcasting,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
2553,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",m. segal,Degradation,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
2554,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",a. ramamoorthy,Network coding,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
2555,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",a. ramamoorthy,Cost function,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
2556,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",a. ramamoorthy,Source coding,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
2557,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",a. ramamoorthy,Lagrangian functions,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
2558,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",a. ramamoorthy,Entropy,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
2559,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",a. ramamoorthy,Communications Society,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
2560,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",a. ramamoorthy,Nash equilibrium,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
2561,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",a. ramamoorthy,Degradation,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
2562,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2563,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",a. ramamoorthy,Upper bound,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
2564,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",a. ramamoorthy,Large-scale systems,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
2565,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",v. roychowdhury,Network coding,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
2566,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",v. roychowdhury,Cost function,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
2567,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",v. roychowdhury,Source coding,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
2568,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",v. roychowdhury,Lagrangian functions,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
2569,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",v. roychowdhury,Entropy,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
2570,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",v. roychowdhury,Communications Society,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
2571,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",v. roychowdhury,Nash equilibrium,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
2572,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",v. roychowdhury,Degradation,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
2573,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2574,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",v. roychowdhury,Upper bound,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
2575,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",v. roychowdhury,Large-scale systems,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
2576,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",s. singh,Network coding,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
2577,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",s. singh,Cost function,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
2578,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",s. singh,Source coding,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
2579,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",s. singh,Lagrangian functions,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
2580,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",s. singh,Entropy,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
2581,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",s. singh,Communications Society,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
2582,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",s. singh,Nash equilibrium,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
2583,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",s. singh,Degradation,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
2584,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2585,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",s. singh,Upper bound,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
2586,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",s. singh,Large-scale systems,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
2587,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",quanyan zhu,AWGN,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
2588,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",quanyan zhu,Game theory,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
2589,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",quanyan zhu,Communication networks,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
2590,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",quanyan zhu,Wireless networks,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
2591,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",quanyan zhu,Multiaccess communication,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
2592,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",quanyan zhu,Stability,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
2593,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",quanyan zhu,Biological system modeling,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
2594,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",quanyan zhu,Environmental factors,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
2595,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2596,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",quanyan zhu,Throughput,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
2597,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",quanyan zhu,Power control,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
2598,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",hamidou tembine,AWGN,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
2599,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",hamidou tembine,Game theory,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
2600,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",hamidou tembine,Communication networks,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
2601,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",hamidou tembine,Wireless networks,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
2602,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",hamidou tembine,Multiaccess communication,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
2603,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",hamidou tembine,Stability,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
2604,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",hamidou tembine,Biological system modeling,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
2605,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",hamidou tembine,Environmental factors,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
2606,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2607,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",hamidou tembine,Throughput,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
2608,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",hamidou tembine,Power control,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
2609,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",tamer basar,AWGN,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
2610,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",tamer basar,Game theory,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
2611,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",tamer basar,Communication networks,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
2612,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",tamer basar,Wireless networks,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
2613,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",tamer basar,Multiaccess communication,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
2614,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",tamer basar,Stability,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
2615,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",tamer basar,Biological system modeling,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
2616,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",tamer basar,Environmental factors,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
2617,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2618,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",tamer basar,Throughput,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
2619,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",tamer basar,Power control,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
2620,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",salvatore d'oro,Network slicing,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
2621,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",salvatore d'oro,5G,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
2622,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",salvatore d'oro,congestion games,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
2623,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",salvatore d'oro,game theory,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
2624,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",salvatore d'oro,distributed algorithms.,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
2625,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",francesco restuccia,Network slicing,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
2626,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",francesco restuccia,5G,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
2627,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",francesco restuccia,congestion games,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
2628,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
2629,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2630,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",francesco restuccia,game theory,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
2631,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",francesco restuccia,distributed algorithms.,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
2632,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",tommaso melodia,Network slicing,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
2633,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",tommaso melodia,5G,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
2634,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",tommaso melodia,congestion games,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
2635,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",tommaso melodia,game theory,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
2636,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",tommaso melodia,distributed algorithms.,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
2637,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",sergio palazzo,Network slicing,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
2638,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",sergio palazzo,5G,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
2639,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",sergio palazzo,congestion games,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
2640,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2641,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",sergio palazzo,game theory,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
2642,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",sergio palazzo,distributed algorithms.,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
2643,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",a. mohsenian-rad,Network coding,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2644,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",a. mohsenian-rad,Pricing,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2645,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",a. mohsenian-rad,Resource management,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2646,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",a. mohsenian-rad,Nash equilibrium,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2647,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",a. mohsenian-rad,Game theory,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2648,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",a. mohsenian-rad,Routing,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2649,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",a. mohsenian-rad,Communications Society,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2650,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",a. mohsenian-rad,Electronic mail,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2651,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2652,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",a. mohsenian-rad,Wireless networks,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2653,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",a. mohsenian-rad,Encoding,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2654,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",j. huang,Network coding,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2655,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",j. huang,Pricing,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2656,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",j. huang,Resource management,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2657,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",j. huang,Nash equilibrium,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2658,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",j. huang,Game theory,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2659,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",j. huang,Routing,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2660,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",j. huang,Communications Society,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2661,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",j. huang,Electronic mail,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2662,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2663,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",j. huang,Wireless networks,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2664,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",j. huang,Encoding,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2665,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",v. wong,Network coding,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2666,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",v. wong,Pricing,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2667,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",v. wong,Resource management,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2668,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",v. wong,Nash equilibrium,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2669,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",v. wong,Game theory,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2670,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",v. wong,Routing,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2671,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",v. wong,Communications Society,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2672,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",v. wong,Electronic mail,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2673,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2674,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",v. wong,Wireless networks,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2675,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",v. wong,Encoding,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2676,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",s. jaggi,Network coding,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2677,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",s. jaggi,Pricing,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2678,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",s. jaggi,Resource management,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2679,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",s. jaggi,Nash equilibrium,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2680,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",s. jaggi,Game theory,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2681,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",s. jaggi,Routing,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2682,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",s. jaggi,Communications Society,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2683,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",s. jaggi,Electronic mail,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2684,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2685,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",s. jaggi,Wireless networks,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2686,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",s. jaggi,Encoding,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2687,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",r. schober,Network coding,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2688,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",r. schober,Pricing,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2689,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",r. schober,Resource management,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2690,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",r. schober,Nash equilibrium,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2691,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",r. schober,Game theory,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2692,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",r. schober,Routing,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2693,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",r. schober,Communications Society,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2694,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",r. schober,Electronic mail,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2695,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2696,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",r. schober,Wireless networks,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2697,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",r. schober,Encoding,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
2698,"In this work, we review the routing models that use game theoretical methodologies. A very common assumption in the analysis and development of networking algorithms is the full cooperation of the participating nodes. Most of the analytical tools are based on this assumption. However, the reality may differ considerably. The existence of multiple domains belonging to different authorities or even the selfishness of the nodes themselves could result in a performance that significantly deviates from the expected one. Even though it is known to be extensively used in the fields of economics and biology, game theory has attracted the interest of researchers in the field of communication networking as well. Nowadays, game theory is used for the analysis and modeling of protocols in several layers, routing included. This review aims at providing an elucidation of the terminology and principles behind game theory and the most popular and recent routing models. The examined networks are both the traditional networks where latency is of paramount importance and the emerging ad hoc and sensor networks, where energy is the main concern.",fotini-niovi pavlidou,Ad hoc networks,2008.0,10.1109/JCN.2008.6388348,Journal of Communications and Networks,Pavlidou2008,False,,IEEE,Not available,Game theory for routing modeling in communication networks — A survey,ad67da54003896be3cb03e4e499060e0,https://ieeexplore.ieee.org/document/6388348/
2699,"In this work, we review the routing models that use game theoretical methodologies. A very common assumption in the analysis and development of networking algorithms is the full cooperation of the participating nodes. Most of the analytical tools are based on this assumption. However, the reality may differ considerably. The existence of multiple domains belonging to different authorities or even the selfishness of the nodes themselves could result in a performance that significantly deviates from the expected one. Even though it is known to be extensively used in the fields of economics and biology, game theory has attracted the interest of researchers in the field of communication networking as well. Nowadays, game theory is used for the analysis and modeling of protocols in several layers, routing included. This review aims at providing an elucidation of the terminology and principles behind game theory and the most popular and recent routing models. The examined networks are both the traditional networks where latency is of paramount importance and the emerging ad hoc and sensor networks, where energy is the main concern.",fotini-niovi pavlidou,Bayesian games,2008.0,10.1109/JCN.2008.6388348,Journal of Communications and Networks,Pavlidou2008,False,,IEEE,Not available,Game theory for routing modeling in communication networks — A survey,ad67da54003896be3cb03e4e499060e0,https://ieeexplore.ieee.org/document/6388348/
2700,"In this work, we review the routing models that use game theoretical methodologies. A very common assumption in the analysis and development of networking algorithms is the full cooperation of the participating nodes. Most of the analytical tools are based on this assumption. However, the reality may differ considerably. The existence of multiple domains belonging to different authorities or even the selfishness of the nodes themselves could result in a performance that significantly deviates from the expected one. Even though it is known to be extensively used in the fields of economics and biology, game theory has attracted the interest of researchers in the field of communication networking as well. Nowadays, game theory is used for the analysis and modeling of protocols in several layers, routing included. This review aims at providing an elucidation of the terminology and principles behind game theory and the most popular and recent routing models. The examined networks are both the traditional networks where latency is of paramount importance and the emerging ad hoc and sensor networks, where energy is the main concern.",fotini-niovi pavlidou,game theory,2008.0,10.1109/JCN.2008.6388348,Journal of Communications and Networks,Pavlidou2008,False,,IEEE,Not available,Game theory for routing modeling in communication networks — A survey,ad67da54003896be3cb03e4e499060e0,https://ieeexplore.ieee.org/document/6388348/
2701,"In this work, we review the routing models that use game theoretical methodologies. A very common assumption in the analysis and development of networking algorithms is the full cooperation of the participating nodes. Most of the analytical tools are based on this assumption. However, the reality may differ considerably. The existence of multiple domains belonging to different authorities or even the selfishness of the nodes themselves could result in a performance that significantly deviates from the expected one. Even though it is known to be extensively used in the fields of economics and biology, game theory has attracted the interest of researchers in the field of communication networking as well. Nowadays, game theory is used for the analysis and modeling of protocols in several layers, routing included. This review aims at providing an elucidation of the terminology and principles behind game theory and the most popular and recent routing models. The examined networks are both the traditional networks where latency is of paramount importance and the emerging ad hoc and sensor networks, where energy is the main concern.",fotini-niovi pavlidou,Nash equilibrium,2008.0,10.1109/JCN.2008.6388348,Journal of Communications and Networks,Pavlidou2008,False,,IEEE,Not available,Game theory for routing modeling in communication networks — A survey,ad67da54003896be3cb03e4e499060e0,https://ieeexplore.ieee.org/document/6388348/
2702,"In this work, we review the routing models that use game theoretical methodologies. A very common assumption in the analysis and development of networking algorithms is the full cooperation of the participating nodes. Most of the analytical tools are based on this assumption. However, the reality may differ considerably. The existence of multiple domains belonging to different authorities or even the selfishness of the nodes themselves could result in a performance that significantly deviates from the expected one. Even though it is known to be extensively used in the fields of economics and biology, game theory has attracted the interest of researchers in the field of communication networking as well. Nowadays, game theory is used for the analysis and modeling of protocols in several layers, routing included. This review aims at providing an elucidation of the terminology and principles behind game theory and the most popular and recent routing models. The examined networks are both the traditional networks where latency is of paramount importance and the emerging ad hoc and sensor networks, where energy is the main concern.",fotini-niovi pavlidou,network routing,2008.0,10.1109/JCN.2008.6388348,Journal of Communications and Networks,Pavlidou2008,False,,IEEE,Not available,Game theory for routing modeling in communication networks — A survey,ad67da54003896be3cb03e4e499060e0,https://ieeexplore.ieee.org/document/6388348/
2703,"In this work, we review the routing models that use game theoretical methodologies. A very common assumption in the analysis and development of networking algorithms is the full cooperation of the participating nodes. Most of the analytical tools are based on this assumption. However, the reality may differ considerably. The existence of multiple domains belonging to different authorities or even the selfishness of the nodes themselves could result in a performance that significantly deviates from the expected one. Even though it is known to be extensively used in the fields of economics and biology, game theory has attracted the interest of researchers in the field of communication networking as well. Nowadays, game theory is used for the analysis and modeling of protocols in several layers, routing included. This review aims at providing an elucidation of the terminology and principles behind game theory and the most popular and recent routing models. The examined networks are both the traditional networks where latency is of paramount importance and the emerging ad hoc and sensor networks, where energy is the main concern.",fotini-niovi pavlidou,price of anarchy,2008.0,10.1109/JCN.2008.6388348,Journal of Communications and Networks,Pavlidou2008,False,,IEEE,Not available,Game theory for routing modeling in communication networks — A survey,ad67da54003896be3cb03e4e499060e0,https://ieeexplore.ieee.org/document/6388348/
2704,"In this work, we review the routing models that use game theoretical methodologies. A very common assumption in the analysis and development of networking algorithms is the full cooperation of the participating nodes. Most of the analytical tools are based on this assumption. However, the reality may differ considerably. The existence of multiple domains belonging to different authorities or even the selfishness of the nodes themselves could result in a performance that significantly deviates from the expected one. Even though it is known to be extensively used in the fields of economics and biology, game theory has attracted the interest of researchers in the field of communication networking as well. Nowadays, game theory is used for the analysis and modeling of protocols in several layers, routing included. This review aims at providing an elucidation of the terminology and principles behind game theory and the most popular and recent routing models. The examined networks are both the traditional networks where latency is of paramount importance and the emerging ad hoc and sensor networks, where energy is the main concern.",fotini-niovi pavlidou,routing modeling,2008.0,10.1109/JCN.2008.6388348,Journal of Communications and Networks,Pavlidou2008,False,,IEEE,Not available,Game theory for routing modeling in communication networks — A survey,ad67da54003896be3cb03e4e499060e0,https://ieeexplore.ieee.org/document/6388348/
2705,"In this work, we review the routing models that use game theoretical methodologies. A very common assumption in the analysis and development of networking algorithms is the full cooperation of the participating nodes. Most of the analytical tools are based on this assumption. However, the reality may differ considerably. The existence of multiple domains belonging to different authorities or even the selfishness of the nodes themselves could result in a performance that significantly deviates from the expected one. Even though it is known to be extensively used in the fields of economics and biology, game theory has attracted the interest of researchers in the field of communication networking as well. Nowadays, game theory is used for the analysis and modeling of protocols in several layers, routing included. This review aims at providing an elucidation of the terminology and principles behind game theory and the most popular and recent routing models. The examined networks are both the traditional networks where latency is of paramount importance and the emerging ad hoc and sensor networks, where energy is the main concern.",fotini-niovi pavlidou,sensor networks,2008.0,10.1109/JCN.2008.6388348,Journal of Communications and Networks,Pavlidou2008,False,,IEEE,Not available,Game theory for routing modeling in communication networks — A survey,ad67da54003896be3cb03e4e499060e0,https://ieeexplore.ieee.org/document/6388348/
2706,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2707,"In this work, we review the routing models that use game theoretical methodologies. A very common assumption in the analysis and development of networking algorithms is the full cooperation of the participating nodes. Most of the analytical tools are based on this assumption. However, the reality may differ considerably. The existence of multiple domains belonging to different authorities or even the selfishness of the nodes themselves could result in a performance that significantly deviates from the expected one. Even though it is known to be extensively used in the fields of economics and biology, game theory has attracted the interest of researchers in the field of communication networking as well. Nowadays, game theory is used for the analysis and modeling of protocols in several layers, routing included. This review aims at providing an elucidation of the terminology and principles behind game theory and the most popular and recent routing models. The examined networks are both the traditional networks where latency is of paramount importance and the emerging ad hoc and sensor networks, where energy is the main concern.",georgios koltsidas,Ad hoc networks,2008.0,10.1109/JCN.2008.6388348,Journal of Communications and Networks,Pavlidou2008,False,,IEEE,Not available,Game theory for routing modeling in communication networks — A survey,ad67da54003896be3cb03e4e499060e0,https://ieeexplore.ieee.org/document/6388348/
2708,"In this work, we review the routing models that use game theoretical methodologies. A very common assumption in the analysis and development of networking algorithms is the full cooperation of the participating nodes. Most of the analytical tools are based on this assumption. However, the reality may differ considerably. The existence of multiple domains belonging to different authorities or even the selfishness of the nodes themselves could result in a performance that significantly deviates from the expected one. Even though it is known to be extensively used in the fields of economics and biology, game theory has attracted the interest of researchers in the field of communication networking as well. Nowadays, game theory is used for the analysis and modeling of protocols in several layers, routing included. This review aims at providing an elucidation of the terminology and principles behind game theory and the most popular and recent routing models. The examined networks are both the traditional networks where latency is of paramount importance and the emerging ad hoc and sensor networks, where energy is the main concern.",georgios koltsidas,Bayesian games,2008.0,10.1109/JCN.2008.6388348,Journal of Communications and Networks,Pavlidou2008,False,,IEEE,Not available,Game theory for routing modeling in communication networks — A survey,ad67da54003896be3cb03e4e499060e0,https://ieeexplore.ieee.org/document/6388348/
2709,"In this work, we review the routing models that use game theoretical methodologies. A very common assumption in the analysis and development of networking algorithms is the full cooperation of the participating nodes. Most of the analytical tools are based on this assumption. However, the reality may differ considerably. The existence of multiple domains belonging to different authorities or even the selfishness of the nodes themselves could result in a performance that significantly deviates from the expected one. Even though it is known to be extensively used in the fields of economics and biology, game theory has attracted the interest of researchers in the field of communication networking as well. Nowadays, game theory is used for the analysis and modeling of protocols in several layers, routing included. This review aims at providing an elucidation of the terminology and principles behind game theory and the most popular and recent routing models. The examined networks are both the traditional networks where latency is of paramount importance and the emerging ad hoc and sensor networks, where energy is the main concern.",georgios koltsidas,game theory,2008.0,10.1109/JCN.2008.6388348,Journal of Communications and Networks,Pavlidou2008,False,,IEEE,Not available,Game theory for routing modeling in communication networks — A survey,ad67da54003896be3cb03e4e499060e0,https://ieeexplore.ieee.org/document/6388348/
2710,"In this work, we review the routing models that use game theoretical methodologies. A very common assumption in the analysis and development of networking algorithms is the full cooperation of the participating nodes. Most of the analytical tools are based on this assumption. However, the reality may differ considerably. The existence of multiple domains belonging to different authorities or even the selfishness of the nodes themselves could result in a performance that significantly deviates from the expected one. Even though it is known to be extensively used in the fields of economics and biology, game theory has attracted the interest of researchers in the field of communication networking as well. Nowadays, game theory is used for the analysis and modeling of protocols in several layers, routing included. This review aims at providing an elucidation of the terminology and principles behind game theory and the most popular and recent routing models. The examined networks are both the traditional networks where latency is of paramount importance and the emerging ad hoc and sensor networks, where energy is the main concern.",georgios koltsidas,Nash equilibrium,2008.0,10.1109/JCN.2008.6388348,Journal of Communications and Networks,Pavlidou2008,False,,IEEE,Not available,Game theory for routing modeling in communication networks — A survey,ad67da54003896be3cb03e4e499060e0,https://ieeexplore.ieee.org/document/6388348/
2711,"In this work, we review the routing models that use game theoretical methodologies. A very common assumption in the analysis and development of networking algorithms is the full cooperation of the participating nodes. Most of the analytical tools are based on this assumption. However, the reality may differ considerably. The existence of multiple domains belonging to different authorities or even the selfishness of the nodes themselves could result in a performance that significantly deviates from the expected one. Even though it is known to be extensively used in the fields of economics and biology, game theory has attracted the interest of researchers in the field of communication networking as well. Nowadays, game theory is used for the analysis and modeling of protocols in several layers, routing included. This review aims at providing an elucidation of the terminology and principles behind game theory and the most popular and recent routing models. The examined networks are both the traditional networks where latency is of paramount importance and the emerging ad hoc and sensor networks, where energy is the main concern.",georgios koltsidas,network routing,2008.0,10.1109/JCN.2008.6388348,Journal of Communications and Networks,Pavlidou2008,False,,IEEE,Not available,Game theory for routing modeling in communication networks — A survey,ad67da54003896be3cb03e4e499060e0,https://ieeexplore.ieee.org/document/6388348/
2712,"In this work, we review the routing models that use game theoretical methodologies. A very common assumption in the analysis and development of networking algorithms is the full cooperation of the participating nodes. Most of the analytical tools are based on this assumption. However, the reality may differ considerably. The existence of multiple domains belonging to different authorities or even the selfishness of the nodes themselves could result in a performance that significantly deviates from the expected one. Even though it is known to be extensively used in the fields of economics and biology, game theory has attracted the interest of researchers in the field of communication networking as well. Nowadays, game theory is used for the analysis and modeling of protocols in several layers, routing included. This review aims at providing an elucidation of the terminology and principles behind game theory and the most popular and recent routing models. The examined networks are both the traditional networks where latency is of paramount importance and the emerging ad hoc and sensor networks, where energy is the main concern.",georgios koltsidas,price of anarchy,2008.0,10.1109/JCN.2008.6388348,Journal of Communications and Networks,Pavlidou2008,False,,IEEE,Not available,Game theory for routing modeling in communication networks — A survey,ad67da54003896be3cb03e4e499060e0,https://ieeexplore.ieee.org/document/6388348/
2713,"In this work, we review the routing models that use game theoretical methodologies. A very common assumption in the analysis and development of networking algorithms is the full cooperation of the participating nodes. Most of the analytical tools are based on this assumption. However, the reality may differ considerably. The existence of multiple domains belonging to different authorities or even the selfishness of the nodes themselves could result in a performance that significantly deviates from the expected one. Even though it is known to be extensively used in the fields of economics and biology, game theory has attracted the interest of researchers in the field of communication networking as well. Nowadays, game theory is used for the analysis and modeling of protocols in several layers, routing included. This review aims at providing an elucidation of the terminology and principles behind game theory and the most popular and recent routing models. The examined networks are both the traditional networks where latency is of paramount importance and the emerging ad hoc and sensor networks, where energy is the main concern.",georgios koltsidas,routing modeling,2008.0,10.1109/JCN.2008.6388348,Journal of Communications and Networks,Pavlidou2008,False,,IEEE,Not available,Game theory for routing modeling in communication networks — A survey,ad67da54003896be3cb03e4e499060e0,https://ieeexplore.ieee.org/document/6388348/
2714,"In this work, we review the routing models that use game theoretical methodologies. A very common assumption in the analysis and development of networking algorithms is the full cooperation of the participating nodes. Most of the analytical tools are based on this assumption. However, the reality may differ considerably. The existence of multiple domains belonging to different authorities or even the selfishness of the nodes themselves could result in a performance that significantly deviates from the expected one. Even though it is known to be extensively used in the fields of economics and biology, game theory has attracted the interest of researchers in the field of communication networking as well. Nowadays, game theory is used for the analysis and modeling of protocols in several layers, routing included. This review aims at providing an elucidation of the terminology and principles behind game theory and the most popular and recent routing models. The examined networks are both the traditional networks where latency is of paramount importance and the emerging ad hoc and sensor networks, where energy is the main concern.",georgios koltsidas,sensor networks,2008.0,10.1109/JCN.2008.6388348,Journal of Communications and Networks,Pavlidou2008,False,,IEEE,Not available,Game theory for routing modeling in communication networks — A survey,ad67da54003896be3cb03e4e499060e0,https://ieeexplore.ieee.org/document/6388348/
2715,"Game theory is emerging as a popular tool for distributed control of multiagent systems. To take advantage of these game theoretic tools, the interactions of the autonomous agents must be designed within a game-theoretic environment. A central component of this game-theoretic design is the assignment of a local utility function to each agent. One promising approach to utility design is assigning each agent a utility function according to the agent's Shapley value. This method frequently results in games that possess many desirable features, such as the existence of pure Nash equilibria with near-optimal efficiency. In this paper, we explore the relationship between the Shapley value utility design and the resulting efficiency of both pure Nash equilibria and coarse correlated equilibria. To study this relationship, we introduce a simple class of resource allocation problems. Within this class, we derive an explicit relationship between the structure of the resource allocation problem and the efficiency of the resulting equilibria. Lastly, we derive a bicriteria bound for this class of resource allocation problems-a bound on the value of the optimal allocation relative to the value of an equilibrium allocation with additional agents.",jason marden,Cost sharing,2014.0,10.1109/TAC.2014.2301613,IEEE Transactions on Automatic Control,Marden2014,False,,IEEE,Not available,Generalized Efficiency Bounds in Distributed Resource Allocation,c9b098265a1c130b1283451fb88737f9,https://ieeexplore.ieee.org/document/6717015/
2716,"Game theory is emerging as a popular tool for distributed control of multiagent systems. To take advantage of these game theoretic tools, the interactions of the autonomous agents must be designed within a game-theoretic environment. A central component of this game-theoretic design is the assignment of a local utility function to each agent. One promising approach to utility design is assigning each agent a utility function according to the agent's Shapley value. This method frequently results in games that possess many desirable features, such as the existence of pure Nash equilibria with near-optimal efficiency. In this paper, we explore the relationship between the Shapley value utility design and the resulting efficiency of both pure Nash equilibria and coarse correlated equilibria. To study this relationship, we introduce a simple class of resource allocation problems. Within this class, we derive an explicit relationship between the structure of the resource allocation problem and the efficiency of the resulting equilibria. Lastly, we derive a bicriteria bound for this class of resource allocation problems-a bound on the value of the optimal allocation relative to the value of an equilibrium allocation with additional agents.",jason marden,distributed control,2014.0,10.1109/TAC.2014.2301613,IEEE Transactions on Automatic Control,Marden2014,False,,IEEE,Not available,Generalized Efficiency Bounds in Distributed Resource Allocation,c9b098265a1c130b1283451fb88737f9,https://ieeexplore.ieee.org/document/6717015/
2717,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2718,"Game theory is emerging as a popular tool for distributed control of multiagent systems. To take advantage of these game theoretic tools, the interactions of the autonomous agents must be designed within a game-theoretic environment. A central component of this game-theoretic design is the assignment of a local utility function to each agent. One promising approach to utility design is assigning each agent a utility function according to the agent's Shapley value. This method frequently results in games that possess many desirable features, such as the existence of pure Nash equilibria with near-optimal efficiency. In this paper, we explore the relationship between the Shapley value utility design and the resulting efficiency of both pure Nash equilibria and coarse correlated equilibria. To study this relationship, we introduce a simple class of resource allocation problems. Within this class, we derive an explicit relationship between the structure of the resource allocation problem and the efficiency of the resulting equilibria. Lastly, we derive a bicriteria bound for this class of resource allocation problems-a bound on the value of the optimal allocation relative to the value of an equilibrium allocation with additional agents.",jason marden,game theory,2014.0,10.1109/TAC.2014.2301613,IEEE Transactions on Automatic Control,Marden2014,False,,IEEE,Not available,Generalized Efficiency Bounds in Distributed Resource Allocation,c9b098265a1c130b1283451fb88737f9,https://ieeexplore.ieee.org/document/6717015/
2719,"Game theory is emerging as a popular tool for distributed control of multiagent systems. To take advantage of these game theoretic tools, the interactions of the autonomous agents must be designed within a game-theoretic environment. A central component of this game-theoretic design is the assignment of a local utility function to each agent. One promising approach to utility design is assigning each agent a utility function according to the agent's Shapley value. This method frequently results in games that possess many desirable features, such as the existence of pure Nash equilibria with near-optimal efficiency. In this paper, we explore the relationship between the Shapley value utility design and the resulting efficiency of both pure Nash equilibria and coarse correlated equilibria. To study this relationship, we introduce a simple class of resource allocation problems. Within this class, we derive an explicit relationship between the structure of the resource allocation problem and the efficiency of the resulting equilibria. Lastly, we derive a bicriteria bound for this class of resource allocation problems-a bound on the value of the optimal allocation relative to the value of an equilibrium allocation with additional agents.",jason marden,price of anarchy,2014.0,10.1109/TAC.2014.2301613,IEEE Transactions on Automatic Control,Marden2014,False,,IEEE,Not available,Generalized Efficiency Bounds in Distributed Resource Allocation,c9b098265a1c130b1283451fb88737f9,https://ieeexplore.ieee.org/document/6717015/
2720,"Game theory is emerging as a popular tool for distributed control of multiagent systems. To take advantage of these game theoretic tools, the interactions of the autonomous agents must be designed within a game-theoretic environment. A central component of this game-theoretic design is the assignment of a local utility function to each agent. One promising approach to utility design is assigning each agent a utility function according to the agent's Shapley value. This method frequently results in games that possess many desirable features, such as the existence of pure Nash equilibria with near-optimal efficiency. In this paper, we explore the relationship between the Shapley value utility design and the resulting efficiency of both pure Nash equilibria and coarse correlated equilibria. To study this relationship, we introduce a simple class of resource allocation problems. Within this class, we derive an explicit relationship between the structure of the resource allocation problem and the efficiency of the resulting equilibria. Lastly, we derive a bicriteria bound for this class of resource allocation problems-a bound on the value of the optimal allocation relative to the value of an equilibrium allocation with additional agents.",tim roughgarden,Cost sharing,2014.0,10.1109/TAC.2014.2301613,IEEE Transactions on Automatic Control,Marden2014,False,,IEEE,Not available,Generalized Efficiency Bounds in Distributed Resource Allocation,c9b098265a1c130b1283451fb88737f9,https://ieeexplore.ieee.org/document/6717015/
2721,"Game theory is emerging as a popular tool for distributed control of multiagent systems. To take advantage of these game theoretic tools, the interactions of the autonomous agents must be designed within a game-theoretic environment. A central component of this game-theoretic design is the assignment of a local utility function to each agent. One promising approach to utility design is assigning each agent a utility function according to the agent's Shapley value. This method frequently results in games that possess many desirable features, such as the existence of pure Nash equilibria with near-optimal efficiency. In this paper, we explore the relationship between the Shapley value utility design and the resulting efficiency of both pure Nash equilibria and coarse correlated equilibria. To study this relationship, we introduce a simple class of resource allocation problems. Within this class, we derive an explicit relationship between the structure of the resource allocation problem and the efficiency of the resulting equilibria. Lastly, we derive a bicriteria bound for this class of resource allocation problems-a bound on the value of the optimal allocation relative to the value of an equilibrium allocation with additional agents.",tim roughgarden,distributed control,2014.0,10.1109/TAC.2014.2301613,IEEE Transactions on Automatic Control,Marden2014,False,,IEEE,Not available,Generalized Efficiency Bounds in Distributed Resource Allocation,c9b098265a1c130b1283451fb88737f9,https://ieeexplore.ieee.org/document/6717015/
2722,"Game theory is emerging as a popular tool for distributed control of multiagent systems. To take advantage of these game theoretic tools, the interactions of the autonomous agents must be designed within a game-theoretic environment. A central component of this game-theoretic design is the assignment of a local utility function to each agent. One promising approach to utility design is assigning each agent a utility function according to the agent's Shapley value. This method frequently results in games that possess many desirable features, such as the existence of pure Nash equilibria with near-optimal efficiency. In this paper, we explore the relationship between the Shapley value utility design and the resulting efficiency of both pure Nash equilibria and coarse correlated equilibria. To study this relationship, we introduce a simple class of resource allocation problems. Within this class, we derive an explicit relationship between the structure of the resource allocation problem and the efficiency of the resulting equilibria. Lastly, we derive a bicriteria bound for this class of resource allocation problems-a bound on the value of the optimal allocation relative to the value of an equilibrium allocation with additional agents.",tim roughgarden,game theory,2014.0,10.1109/TAC.2014.2301613,IEEE Transactions on Automatic Control,Marden2014,False,,IEEE,Not available,Generalized Efficiency Bounds in Distributed Resource Allocation,c9b098265a1c130b1283451fb88737f9,https://ieeexplore.ieee.org/document/6717015/
2723,"Game theory is emerging as a popular tool for distributed control of multiagent systems. To take advantage of these game theoretic tools, the interactions of the autonomous agents must be designed within a game-theoretic environment. A central component of this game-theoretic design is the assignment of a local utility function to each agent. One promising approach to utility design is assigning each agent a utility function according to the agent's Shapley value. This method frequently results in games that possess many desirable features, such as the existence of pure Nash equilibria with near-optimal efficiency. In this paper, we explore the relationship between the Shapley value utility design and the resulting efficiency of both pure Nash equilibria and coarse correlated equilibria. To study this relationship, we introduce a simple class of resource allocation problems. Within this class, we derive an explicit relationship between the structure of the resource allocation problem and the efficiency of the resulting equilibria. Lastly, we derive a bicriteria bound for this class of resource allocation problems-a bound on the value of the optimal allocation relative to the value of an equilibrium allocation with additional agents.",tim roughgarden,price of anarchy,2014.0,10.1109/TAC.2014.2301613,IEEE Transactions on Automatic Control,Marden2014,False,,IEEE,Not available,Generalized Efficiency Bounds in Distributed Resource Allocation,c9b098265a1c130b1283451fb88737f9,https://ieeexplore.ieee.org/document/6717015/
2724,"In this paper, we present a game-theoretic study of the problem of routing in networks with max-min fair congestion control at the link level. The problem is formulated as a noncooperative game, in which each user aims to maximize its own bandwidth by selecting its routing path. We first prove the existence of Nash equilibria. This is important, because at a Nash equilibrium (NE), no user has any incentive to change its routing strategy-leading to a stable state. In addition, we investigate how the selfish behavior of users may affect the performance of the network as a whole. We next introduce a novel concept of observed available bandwidth on each link. It allows a user to find a path with maximum bandwidth under max-min fair congestion control in polynomial time, when paths of other users are fixed. We then present a game-based algorithm to compute an NE and prove that by following the natural game course, the network converges to an NE. Extensive simulations show that the algorithm converges to an NE within 10 iterations and also achieves better fairness compared to other algorithms .",dejun yang,Fair queueing,2013.0,10.1109/TNET.2013.2247416,IEEE/ACM Transactions on Networking,Yang2013,False,,IEEE,Not available,A Game-Theoretic Approach to Stable Routing in Max-Min Fair Networks,8f5ff0a490dc37131c396811f10cfc4f,https://ieeexplore.ieee.org/document/6493506/
2725,"In this paper, we present a game-theoretic study of the problem of routing in networks with max-min fair congestion control at the link level. The problem is formulated as a noncooperative game, in which each user aims to maximize its own bandwidth by selecting its routing path. We first prove the existence of Nash equilibria. This is important, because at a Nash equilibrium (NE), no user has any incentive to change its routing strategy-leading to a stable state. In addition, we investigate how the selfish behavior of users may affect the performance of the network as a whole. We next introduce a novel concept of observed available bandwidth on each link. It allows a user to find a path with maximum bandwidth under max-min fair congestion control in polynomial time, when paths of other users are fixed. We then present a game-based algorithm to compute an NE and prove that by following the natural game course, the network converges to an NE. Extensive simulations show that the algorithm converges to an NE within 10 iterations and also achieves better fairness compared to other algorithms .",dejun yang,Nash equilibrium (NE),2013.0,10.1109/TNET.2013.2247416,IEEE/ACM Transactions on Networking,Yang2013,False,,IEEE,Not available,A Game-Theoretic Approach to Stable Routing in Max-Min Fair Networks,8f5ff0a490dc37131c396811f10cfc4f,https://ieeexplore.ieee.org/document/6493506/
2726,"In this paper, we present a game-theoretic study of the problem of routing in networks with max-min fair congestion control at the link level. The problem is formulated as a noncooperative game, in which each user aims to maximize its own bandwidth by selecting its routing path. We first prove the existence of Nash equilibria. This is important, because at a Nash equilibrium (NE), no user has any incentive to change its routing strategy-leading to a stable state. In addition, we investigate how the selfish behavior of users may affect the performance of the network as a whole. We next introduce a novel concept of observed available bandwidth on each link. It allows a user to find a path with maximum bandwidth under max-min fair congestion control in polynomial time, when paths of other users are fixed. We then present a game-based algorithm to compute an NE and prove that by following the natural game course, the network converges to an NE. Extensive simulations show that the algorithm converges to an NE within 10 iterations and also achieves better fairness compared to other algorithms .",dejun yang,noncooperative game,2013.0,10.1109/TNET.2013.2247416,IEEE/ACM Transactions on Networking,Yang2013,False,,IEEE,Not available,A Game-Theoretic Approach to Stable Routing in Max-Min Fair Networks,8f5ff0a490dc37131c396811f10cfc4f,https://ieeexplore.ieee.org/document/6493506/
2727,"In this paper, we present a game-theoretic study of the problem of routing in networks with max-min fair congestion control at the link level. The problem is formulated as a noncooperative game, in which each user aims to maximize its own bandwidth by selecting its routing path. We first prove the existence of Nash equilibria. This is important, because at a Nash equilibrium (NE), no user has any incentive to change its routing strategy-leading to a stable state. In addition, we investigate how the selfish behavior of users may affect the performance of the network as a whole. We next introduce a novel concept of observed available bandwidth on each link. It allows a user to find a path with maximum bandwidth under max-min fair congestion control in polynomial time, when paths of other users are fixed. We then present a game-based algorithm to compute an NE and prove that by following the natural game course, the network converges to an NE. Extensive simulations show that the algorithm converges to an NE within 10 iterations and also achieves better fairness compared to other algorithms .",dejun yang,price of anarchy,2013.0,10.1109/TNET.2013.2247416,IEEE/ACM Transactions on Networking,Yang2013,False,,IEEE,Not available,A Game-Theoretic Approach to Stable Routing in Max-Min Fair Networks,8f5ff0a490dc37131c396811f10cfc4f,https://ieeexplore.ieee.org/document/6493506/
2728,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2729,"In this paper, we present a game-theoretic study of the problem of routing in networks with max-min fair congestion control at the link level. The problem is formulated as a noncooperative game, in which each user aims to maximize its own bandwidth by selecting its routing path. We first prove the existence of Nash equilibria. This is important, because at a Nash equilibrium (NE), no user has any incentive to change its routing strategy-leading to a stable state. In addition, we investigate how the selfish behavior of users may affect the performance of the network as a whole. We next introduce a novel concept of observed available bandwidth on each link. It allows a user to find a path with maximum bandwidth under max-min fair congestion control in polynomial time, when paths of other users are fixed. We then present a game-based algorithm to compute an NE and prove that by following the natural game course, the network converges to an NE. Extensive simulations show that the algorithm converges to an NE within 10 iterations and also achieves better fairness compared to other algorithms .",dejun yang,stable routing,2013.0,10.1109/TNET.2013.2247416,IEEE/ACM Transactions on Networking,Yang2013,False,,IEEE,Not available,A Game-Theoretic Approach to Stable Routing in Max-Min Fair Networks,8f5ff0a490dc37131c396811f10cfc4f,https://ieeexplore.ieee.org/document/6493506/
2730,"In this paper, we present a game-theoretic study of the problem of routing in networks with max-min fair congestion control at the link level. The problem is formulated as a noncooperative game, in which each user aims to maximize its own bandwidth by selecting its routing path. We first prove the existence of Nash equilibria. This is important, because at a Nash equilibrium (NE), no user has any incentive to change its routing strategy-leading to a stable state. In addition, we investigate how the selfish behavior of users may affect the performance of the network as a whole. We next introduce a novel concept of observed available bandwidth on each link. It allows a user to find a path with maximum bandwidth under max-min fair congestion control in polynomial time, when paths of other users are fixed. We then present a game-based algorithm to compute an NE and prove that by following the natural game course, the network converges to an NE. Extensive simulations show that the algorithm converges to an NE within 10 iterations and also achieves better fairness compared to other algorithms .",guoliang xue,Fair queueing,2013.0,10.1109/TNET.2013.2247416,IEEE/ACM Transactions on Networking,Yang2013,False,,IEEE,Not available,A Game-Theoretic Approach to Stable Routing in Max-Min Fair Networks,8f5ff0a490dc37131c396811f10cfc4f,https://ieeexplore.ieee.org/document/6493506/
2731,"In this paper, we present a game-theoretic study of the problem of routing in networks with max-min fair congestion control at the link level. The problem is formulated as a noncooperative game, in which each user aims to maximize its own bandwidth by selecting its routing path. We first prove the existence of Nash equilibria. This is important, because at a Nash equilibrium (NE), no user has any incentive to change its routing strategy-leading to a stable state. In addition, we investigate how the selfish behavior of users may affect the performance of the network as a whole. We next introduce a novel concept of observed available bandwidth on each link. It allows a user to find a path with maximum bandwidth under max-min fair congestion control in polynomial time, when paths of other users are fixed. We then present a game-based algorithm to compute an NE and prove that by following the natural game course, the network converges to an NE. Extensive simulations show that the algorithm converges to an NE within 10 iterations and also achieves better fairness compared to other algorithms .",guoliang xue,Nash equilibrium (NE),2013.0,10.1109/TNET.2013.2247416,IEEE/ACM Transactions on Networking,Yang2013,False,,IEEE,Not available,A Game-Theoretic Approach to Stable Routing in Max-Min Fair Networks,8f5ff0a490dc37131c396811f10cfc4f,https://ieeexplore.ieee.org/document/6493506/
2732,"In this paper, we present a game-theoretic study of the problem of routing in networks with max-min fair congestion control at the link level. The problem is formulated as a noncooperative game, in which each user aims to maximize its own bandwidth by selecting its routing path. We first prove the existence of Nash equilibria. This is important, because at a Nash equilibrium (NE), no user has any incentive to change its routing strategy-leading to a stable state. In addition, we investigate how the selfish behavior of users may affect the performance of the network as a whole. We next introduce a novel concept of observed available bandwidth on each link. It allows a user to find a path with maximum bandwidth under max-min fair congestion control in polynomial time, when paths of other users are fixed. We then present a game-based algorithm to compute an NE and prove that by following the natural game course, the network converges to an NE. Extensive simulations show that the algorithm converges to an NE within 10 iterations and also achieves better fairness compared to other algorithms .",guoliang xue,noncooperative game,2013.0,10.1109/TNET.2013.2247416,IEEE/ACM Transactions on Networking,Yang2013,False,,IEEE,Not available,A Game-Theoretic Approach to Stable Routing in Max-Min Fair Networks,8f5ff0a490dc37131c396811f10cfc4f,https://ieeexplore.ieee.org/document/6493506/
2733,"In this paper, we present a game-theoretic study of the problem of routing in networks with max-min fair congestion control at the link level. The problem is formulated as a noncooperative game, in which each user aims to maximize its own bandwidth by selecting its routing path. We first prove the existence of Nash equilibria. This is important, because at a Nash equilibrium (NE), no user has any incentive to change its routing strategy-leading to a stable state. In addition, we investigate how the selfish behavior of users may affect the performance of the network as a whole. We next introduce a novel concept of observed available bandwidth on each link. It allows a user to find a path with maximum bandwidth under max-min fair congestion control in polynomial time, when paths of other users are fixed. We then present a game-based algorithm to compute an NE and prove that by following the natural game course, the network converges to an NE. Extensive simulations show that the algorithm converges to an NE within 10 iterations and also achieves better fairness compared to other algorithms .",guoliang xue,price of anarchy,2013.0,10.1109/TNET.2013.2247416,IEEE/ACM Transactions on Networking,Yang2013,False,,IEEE,Not available,A Game-Theoretic Approach to Stable Routing in Max-Min Fair Networks,8f5ff0a490dc37131c396811f10cfc4f,https://ieeexplore.ieee.org/document/6493506/
2734,"In this paper, we present a game-theoretic study of the problem of routing in networks with max-min fair congestion control at the link level. The problem is formulated as a noncooperative game, in which each user aims to maximize its own bandwidth by selecting its routing path. We first prove the existence of Nash equilibria. This is important, because at a Nash equilibrium (NE), no user has any incentive to change its routing strategy-leading to a stable state. In addition, we investigate how the selfish behavior of users may affect the performance of the network as a whole. We next introduce a novel concept of observed available bandwidth on each link. It allows a user to find a path with maximum bandwidth under max-min fair congestion control in polynomial time, when paths of other users are fixed. We then present a game-based algorithm to compute an NE and prove that by following the natural game course, the network converges to an NE. Extensive simulations show that the algorithm converges to an NE within 10 iterations and also achieves better fairness compared to other algorithms .",guoliang xue,stable routing,2013.0,10.1109/TNET.2013.2247416,IEEE/ACM Transactions on Networking,Yang2013,False,,IEEE,Not available,A Game-Theoretic Approach to Stable Routing in Max-Min Fair Networks,8f5ff0a490dc37131c396811f10cfc4f,https://ieeexplore.ieee.org/document/6493506/
2735,"In this paper, we present a game-theoretic study of the problem of routing in networks with max-min fair congestion control at the link level. The problem is formulated as a noncooperative game, in which each user aims to maximize its own bandwidth by selecting its routing path. We first prove the existence of Nash equilibria. This is important, because at a Nash equilibrium (NE), no user has any incentive to change its routing strategy-leading to a stable state. In addition, we investigate how the selfish behavior of users may affect the performance of the network as a whole. We next introduce a novel concept of observed available bandwidth on each link. It allows a user to find a path with maximum bandwidth under max-min fair congestion control in polynomial time, when paths of other users are fixed. We then present a game-based algorithm to compute an NE and prove that by following the natural game course, the network converges to an NE. Extensive simulations show that the algorithm converges to an NE within 10 iterations and also achieves better fairness compared to other algorithms .",xi fang,Fair queueing,2013.0,10.1109/TNET.2013.2247416,IEEE/ACM Transactions on Networking,Yang2013,False,,IEEE,Not available,A Game-Theoretic Approach to Stable Routing in Max-Min Fair Networks,8f5ff0a490dc37131c396811f10cfc4f,https://ieeexplore.ieee.org/document/6493506/
2736,"In this paper, we present a game-theoretic study of the problem of routing in networks with max-min fair congestion control at the link level. The problem is formulated as a noncooperative game, in which each user aims to maximize its own bandwidth by selecting its routing path. We first prove the existence of Nash equilibria. This is important, because at a Nash equilibrium (NE), no user has any incentive to change its routing strategy-leading to a stable state. In addition, we investigate how the selfish behavior of users may affect the performance of the network as a whole. We next introduce a novel concept of observed available bandwidth on each link. It allows a user to find a path with maximum bandwidth under max-min fair congestion control in polynomial time, when paths of other users are fixed. We then present a game-based algorithm to compute an NE and prove that by following the natural game course, the network converges to an NE. Extensive simulations show that the algorithm converges to an NE within 10 iterations and also achieves better fairness compared to other algorithms .",xi fang,Nash equilibrium (NE),2013.0,10.1109/TNET.2013.2247416,IEEE/ACM Transactions on Networking,Yang2013,False,,IEEE,Not available,A Game-Theoretic Approach to Stable Routing in Max-Min Fair Networks,8f5ff0a490dc37131c396811f10cfc4f,https://ieeexplore.ieee.org/document/6493506/
2737,"In this paper, we present a game-theoretic study of the problem of routing in networks with max-min fair congestion control at the link level. The problem is formulated as a noncooperative game, in which each user aims to maximize its own bandwidth by selecting its routing path. We first prove the existence of Nash equilibria. This is important, because at a Nash equilibrium (NE), no user has any incentive to change its routing strategy-leading to a stable state. In addition, we investigate how the selfish behavior of users may affect the performance of the network as a whole. We next introduce a novel concept of observed available bandwidth on each link. It allows a user to find a path with maximum bandwidth under max-min fair congestion control in polynomial time, when paths of other users are fixed. We then present a game-based algorithm to compute an NE and prove that by following the natural game course, the network converges to an NE. Extensive simulations show that the algorithm converges to an NE within 10 iterations and also achieves better fairness compared to other algorithms .",xi fang,noncooperative game,2013.0,10.1109/TNET.2013.2247416,IEEE/ACM Transactions on Networking,Yang2013,False,,IEEE,Not available,A Game-Theoretic Approach to Stable Routing in Max-Min Fair Networks,8f5ff0a490dc37131c396811f10cfc4f,https://ieeexplore.ieee.org/document/6493506/
2738,"In this paper, we present a game-theoretic study of the problem of routing in networks with max-min fair congestion control at the link level. The problem is formulated as a noncooperative game, in which each user aims to maximize its own bandwidth by selecting its routing path. We first prove the existence of Nash equilibria. This is important, because at a Nash equilibrium (NE), no user has any incentive to change its routing strategy-leading to a stable state. In addition, we investigate how the selfish behavior of users may affect the performance of the network as a whole. We next introduce a novel concept of observed available bandwidth on each link. It allows a user to find a path with maximum bandwidth under max-min fair congestion control in polynomial time, when paths of other users are fixed. We then present a game-based algorithm to compute an NE and prove that by following the natural game course, the network converges to an NE. Extensive simulations show that the algorithm converges to an NE within 10 iterations and also achieves better fairness compared to other algorithms .",xi fang,price of anarchy,2013.0,10.1109/TNET.2013.2247416,IEEE/ACM Transactions on Networking,Yang2013,False,,IEEE,Not available,A Game-Theoretic Approach to Stable Routing in Max-Min Fair Networks,8f5ff0a490dc37131c396811f10cfc4f,https://ieeexplore.ieee.org/document/6493506/
2739,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
2740,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2741,"In this paper, we present a game-theoretic study of the problem of routing in networks with max-min fair congestion control at the link level. The problem is formulated as a noncooperative game, in which each user aims to maximize its own bandwidth by selecting its routing path. We first prove the existence of Nash equilibria. This is important, because at a Nash equilibrium (NE), no user has any incentive to change its routing strategy-leading to a stable state. In addition, we investigate how the selfish behavior of users may affect the performance of the network as a whole. We next introduce a novel concept of observed available bandwidth on each link. It allows a user to find a path with maximum bandwidth under max-min fair congestion control in polynomial time, when paths of other users are fixed. We then present a game-based algorithm to compute an NE and prove that by following the natural game course, the network converges to an NE. Extensive simulations show that the algorithm converges to an NE within 10 iterations and also achieves better fairness compared to other algorithms .",xi fang,stable routing,2013.0,10.1109/TNET.2013.2247416,IEEE/ACM Transactions on Networking,Yang2013,False,,IEEE,Not available,A Game-Theoretic Approach to Stable Routing in Max-Min Fair Networks,8f5ff0a490dc37131c396811f10cfc4f,https://ieeexplore.ieee.org/document/6493506/
2742,"In this paper, we present a game-theoretic study of the problem of routing in networks with max-min fair congestion control at the link level. The problem is formulated as a noncooperative game, in which each user aims to maximize its own bandwidth by selecting its routing path. We first prove the existence of Nash equilibria. This is important, because at a Nash equilibrium (NE), no user has any incentive to change its routing strategy-leading to a stable state. In addition, we investigate how the selfish behavior of users may affect the performance of the network as a whole. We next introduce a novel concept of observed available bandwidth on each link. It allows a user to find a path with maximum bandwidth under max-min fair congestion control in polynomial time, when paths of other users are fixed. We then present a game-based algorithm to compute an NE and prove that by following the natural game course, the network converges to an NE. Extensive simulations show that the algorithm converges to an NE within 10 iterations and also achieves better fairness compared to other algorithms .",satyajayant misra,Fair queueing,2013.0,10.1109/TNET.2013.2247416,IEEE/ACM Transactions on Networking,Yang2013,False,,IEEE,Not available,A Game-Theoretic Approach to Stable Routing in Max-Min Fair Networks,8f5ff0a490dc37131c396811f10cfc4f,https://ieeexplore.ieee.org/document/6493506/
2743,"In this paper, we present a game-theoretic study of the problem of routing in networks with max-min fair congestion control at the link level. The problem is formulated as a noncooperative game, in which each user aims to maximize its own bandwidth by selecting its routing path. We first prove the existence of Nash equilibria. This is important, because at a Nash equilibrium (NE), no user has any incentive to change its routing strategy-leading to a stable state. In addition, we investigate how the selfish behavior of users may affect the performance of the network as a whole. We next introduce a novel concept of observed available bandwidth on each link. It allows a user to find a path with maximum bandwidth under max-min fair congestion control in polynomial time, when paths of other users are fixed. We then present a game-based algorithm to compute an NE and prove that by following the natural game course, the network converges to an NE. Extensive simulations show that the algorithm converges to an NE within 10 iterations and also achieves better fairness compared to other algorithms .",satyajayant misra,Nash equilibrium (NE),2013.0,10.1109/TNET.2013.2247416,IEEE/ACM Transactions on Networking,Yang2013,False,,IEEE,Not available,A Game-Theoretic Approach to Stable Routing in Max-Min Fair Networks,8f5ff0a490dc37131c396811f10cfc4f,https://ieeexplore.ieee.org/document/6493506/
2744,"In this paper, we present a game-theoretic study of the problem of routing in networks with max-min fair congestion control at the link level. The problem is formulated as a noncooperative game, in which each user aims to maximize its own bandwidth by selecting its routing path. We first prove the existence of Nash equilibria. This is important, because at a Nash equilibrium (NE), no user has any incentive to change its routing strategy-leading to a stable state. In addition, we investigate how the selfish behavior of users may affect the performance of the network as a whole. We next introduce a novel concept of observed available bandwidth on each link. It allows a user to find a path with maximum bandwidth under max-min fair congestion control in polynomial time, when paths of other users are fixed. We then present a game-based algorithm to compute an NE and prove that by following the natural game course, the network converges to an NE. Extensive simulations show that the algorithm converges to an NE within 10 iterations and also achieves better fairness compared to other algorithms .",satyajayant misra,noncooperative game,2013.0,10.1109/TNET.2013.2247416,IEEE/ACM Transactions on Networking,Yang2013,False,,IEEE,Not available,A Game-Theoretic Approach to Stable Routing in Max-Min Fair Networks,8f5ff0a490dc37131c396811f10cfc4f,https://ieeexplore.ieee.org/document/6493506/
2745,"In this paper, we present a game-theoretic study of the problem of routing in networks with max-min fair congestion control at the link level. The problem is formulated as a noncooperative game, in which each user aims to maximize its own bandwidth by selecting its routing path. We first prove the existence of Nash equilibria. This is important, because at a Nash equilibrium (NE), no user has any incentive to change its routing strategy-leading to a stable state. In addition, we investigate how the selfish behavior of users may affect the performance of the network as a whole. We next introduce a novel concept of observed available bandwidth on each link. It allows a user to find a path with maximum bandwidth under max-min fair congestion control in polynomial time, when paths of other users are fixed. We then present a game-based algorithm to compute an NE and prove that by following the natural game course, the network converges to an NE. Extensive simulations show that the algorithm converges to an NE within 10 iterations and also achieves better fairness compared to other algorithms .",satyajayant misra,price of anarchy,2013.0,10.1109/TNET.2013.2247416,IEEE/ACM Transactions on Networking,Yang2013,False,,IEEE,Not available,A Game-Theoretic Approach to Stable Routing in Max-Min Fair Networks,8f5ff0a490dc37131c396811f10cfc4f,https://ieeexplore.ieee.org/document/6493506/
2746,"In this paper, we present a game-theoretic study of the problem of routing in networks with max-min fair congestion control at the link level. The problem is formulated as a noncooperative game, in which each user aims to maximize its own bandwidth by selecting its routing path. We first prove the existence of Nash equilibria. This is important, because at a Nash equilibrium (NE), no user has any incentive to change its routing strategy-leading to a stable state. In addition, we investigate how the selfish behavior of users may affect the performance of the network as a whole. We next introduce a novel concept of observed available bandwidth on each link. It allows a user to find a path with maximum bandwidth under max-min fair congestion control in polynomial time, when paths of other users are fixed. We then present a game-based algorithm to compute an NE and prove that by following the natural game course, the network converges to an NE. Extensive simulations show that the algorithm converges to an NE within 10 iterations and also achieves better fairness compared to other algorithms .",satyajayant misra,stable routing,2013.0,10.1109/TNET.2013.2247416,IEEE/ACM Transactions on Networking,Yang2013,False,,IEEE,Not available,A Game-Theoretic Approach to Stable Routing in Max-Min Fair Networks,8f5ff0a490dc37131c396811f10cfc4f,https://ieeexplore.ieee.org/document/6493506/
2747,"In this paper, we present a game-theoretic study of the problem of routing in networks with max-min fair congestion control at the link level. The problem is formulated as a noncooperative game, in which each user aims to maximize its own bandwidth by selecting its routing path. We first prove the existence of Nash equilibria. This is important, because at a Nash equilibrium (NE), no user has any incentive to change its routing strategy-leading to a stable state. In addition, we investigate how the selfish behavior of users may affect the performance of the network as a whole. We next introduce a novel concept of observed available bandwidth on each link. It allows a user to find a path with maximum bandwidth under max-min fair congestion control in polynomial time, when paths of other users are fixed. We then present a game-based algorithm to compute an NE and prove that by following the natural game course, the network converges to an NE. Extensive simulations show that the algorithm converges to an NE within 10 iterations and also achieves better fairness compared to other algorithms .",jin zhang,Fair queueing,2013.0,10.1109/TNET.2013.2247416,IEEE/ACM Transactions on Networking,Yang2013,False,,IEEE,Not available,A Game-Theoretic Approach to Stable Routing in Max-Min Fair Networks,8f5ff0a490dc37131c396811f10cfc4f,https://ieeexplore.ieee.org/document/6493506/
2748,"In this paper, we present a game-theoretic study of the problem of routing in networks with max-min fair congestion control at the link level. The problem is formulated as a noncooperative game, in which each user aims to maximize its own bandwidth by selecting its routing path. We first prove the existence of Nash equilibria. This is important, because at a Nash equilibrium (NE), no user has any incentive to change its routing strategy-leading to a stable state. In addition, we investigate how the selfish behavior of users may affect the performance of the network as a whole. We next introduce a novel concept of observed available bandwidth on each link. It allows a user to find a path with maximum bandwidth under max-min fair congestion control in polynomial time, when paths of other users are fixed. We then present a game-based algorithm to compute an NE and prove that by following the natural game course, the network converges to an NE. Extensive simulations show that the algorithm converges to an NE within 10 iterations and also achieves better fairness compared to other algorithms .",jin zhang,Nash equilibrium (NE),2013.0,10.1109/TNET.2013.2247416,IEEE/ACM Transactions on Networking,Yang2013,False,,IEEE,Not available,A Game-Theoretic Approach to Stable Routing in Max-Min Fair Networks,8f5ff0a490dc37131c396811f10cfc4f,https://ieeexplore.ieee.org/document/6493506/
2749,"In this paper, we present a game-theoretic study of the problem of routing in networks with max-min fair congestion control at the link level. The problem is formulated as a noncooperative game, in which each user aims to maximize its own bandwidth by selecting its routing path. We first prove the existence of Nash equilibria. This is important, because at a Nash equilibrium (NE), no user has any incentive to change its routing strategy-leading to a stable state. In addition, we investigate how the selfish behavior of users may affect the performance of the network as a whole. We next introduce a novel concept of observed available bandwidth on each link. It allows a user to find a path with maximum bandwidth under max-min fair congestion control in polynomial time, when paths of other users are fixed. We then present a game-based algorithm to compute an NE and prove that by following the natural game course, the network converges to an NE. Extensive simulations show that the algorithm converges to an NE within 10 iterations and also achieves better fairness compared to other algorithms .",jin zhang,noncooperative game,2013.0,10.1109/TNET.2013.2247416,IEEE/ACM Transactions on Networking,Yang2013,False,,IEEE,Not available,A Game-Theoretic Approach to Stable Routing in Max-Min Fair Networks,8f5ff0a490dc37131c396811f10cfc4f,https://ieeexplore.ieee.org/document/6493506/
2750,"In this paper, we present a game-theoretic study of the problem of routing in networks with max-min fair congestion control at the link level. The problem is formulated as a noncooperative game, in which each user aims to maximize its own bandwidth by selecting its routing path. We first prove the existence of Nash equilibria. This is important, because at a Nash equilibrium (NE), no user has any incentive to change its routing strategy-leading to a stable state. In addition, we investigate how the selfish behavior of users may affect the performance of the network as a whole. We next introduce a novel concept of observed available bandwidth on each link. It allows a user to find a path with maximum bandwidth under max-min fair congestion control in polynomial time, when paths of other users are fixed. We then present a game-based algorithm to compute an NE and prove that by following the natural game course, the network converges to an NE. Extensive simulations show that the algorithm converges to an NE within 10 iterations and also achieves better fairness compared to other algorithms .",jin zhang,price of anarchy,2013.0,10.1109/TNET.2013.2247416,IEEE/ACM Transactions on Networking,Yang2013,False,,IEEE,Not available,A Game-Theoretic Approach to Stable Routing in Max-Min Fair Networks,8f5ff0a490dc37131c396811f10cfc4f,https://ieeexplore.ieee.org/document/6493506/
2751,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2752,"In this paper, we present a game-theoretic study of the problem of routing in networks with max-min fair congestion control at the link level. The problem is formulated as a noncooperative game, in which each user aims to maximize its own bandwidth by selecting its routing path. We first prove the existence of Nash equilibria. This is important, because at a Nash equilibrium (NE), no user has any incentive to change its routing strategy-leading to a stable state. In addition, we investigate how the selfish behavior of users may affect the performance of the network as a whole. We next introduce a novel concept of observed available bandwidth on each link. It allows a user to find a path with maximum bandwidth under max-min fair congestion control in polynomial time, when paths of other users are fixed. We then present a game-based algorithm to compute an NE and prove that by following the natural game course, the network converges to an NE. Extensive simulations show that the algorithm converges to an NE within 10 iterations and also achieves better fairness compared to other algorithms .",jin zhang,stable routing,2013.0,10.1109/TNET.2013.2247416,IEEE/ACM Transactions on Networking,Yang2013,False,,IEEE,Not available,A Game-Theoretic Approach to Stable Routing in Max-Min Fair Networks,8f5ff0a490dc37131c396811f10cfc4f,https://ieeexplore.ieee.org/document/6493506/
2753,"In IEEE 802.11 wireless networks, users associate with access points that can provide the best service quality. In this paper, we analyze the convergence and steady state performance of a practically well performing load-based user association scheme. The analysis is based on a novel game theoretical model, which extends the results on atomic congestion games. We prove the existence of and convergence to a Nash equilibrium for this game. The bounds on the efficiency of equilibrium compared to centralized optimum solutions are established under different system costs.",ozgur ercetin,"Game theory, price of anarchy, atomic noncooperativegames, distributed optimization.  ",2008.0,10.1109/T-WC.2008.071418,IEEE Transactions on Wireless Communications,Ercetin2008,False,,IEEE,Not available,Association games in IEEE 802.11 wireless local area networks,4893d43b10565ef1cc2f21cb802d5f60,https://ieeexplore.ieee.org/document/4712732/
2754,"Cooperative control focuses on deriving desirable collective behavior in multiagent systems through the design of local control algorithms. Game theory is beginning to emerge as a valuable set of tools for achieving this objective. A central component of this game theoretic approach is the assignment of utility functions to the individual agents. Here, the goal is to assign utility functions within an “admissible” design space such that the resulting game possesses desirable properties. Our first set of results illustrates the complexity associated with such a task. In particular, we prove that if we restrict the class of utility functions to be local, scalable, and budget-balanced then 1) ensuring that the resulting game possesses a pure Nash equilibrium requires computing a Shapley value, which can be computationally prohibitive for large-scale systems, and 2) ensuring that the allocation which optimizes the system level objective is a pure Nash equilibrium is impossible. The last part of this paper demonstrates that both limitations can be overcome by introducing an underlying state space into the potential game structure.",jason marden,Cost sharing,2013.0,10.1109/TAC.2013.2237831,IEEE Transactions on Automatic Control,Marden2013,False,,IEEE,Not available,Overcoming the Limitations of Utility Design for Multiagent Systems,8676e6c5e3cf9d0a15c025cbcd92325d,https://ieeexplore.ieee.org/document/6403513/
2755,"Cooperative control focuses on deriving desirable collective behavior in multiagent systems through the design of local control algorithms. Game theory is beginning to emerge as a valuable set of tools for achieving this objective. A central component of this game theoretic approach is the assignment of utility functions to the individual agents. Here, the goal is to assign utility functions within an “admissible” design space such that the resulting game possesses desirable properties. Our first set of results illustrates the complexity associated with such a task. In particular, we prove that if we restrict the class of utility functions to be local, scalable, and budget-balanced then 1) ensuring that the resulting game possesses a pure Nash equilibrium requires computing a Shapley value, which can be computationally prohibitive for large-scale systems, and 2) ensuring that the allocation which optimizes the system level objective is a pure Nash equilibrium is impossible. The last part of this paper demonstrates that both limitations can be overcome by introducing an underlying state space into the potential game structure.",jason marden,distributed control,2013.0,10.1109/TAC.2013.2237831,IEEE Transactions on Automatic Control,Marden2013,False,,IEEE,Not available,Overcoming the Limitations of Utility Design for Multiagent Systems,8676e6c5e3cf9d0a15c025cbcd92325d,https://ieeexplore.ieee.org/document/6403513/
2756,"Cooperative control focuses on deriving desirable collective behavior in multiagent systems through the design of local control algorithms. Game theory is beginning to emerge as a valuable set of tools for achieving this objective. A central component of this game theoretic approach is the assignment of utility functions to the individual agents. Here, the goal is to assign utility functions within an “admissible” design space such that the resulting game possesses desirable properties. Our first set of results illustrates the complexity associated with such a task. In particular, we prove that if we restrict the class of utility functions to be local, scalable, and budget-balanced then 1) ensuring that the resulting game possesses a pure Nash equilibrium requires computing a Shapley value, which can be computationally prohibitive for large-scale systems, and 2) ensuring that the allocation which optimizes the system level objective is a pure Nash equilibrium is impossible. The last part of this paper demonstrates that both limitations can be overcome by introducing an underlying state space into the potential game structure.",jason marden,game theory,2013.0,10.1109/TAC.2013.2237831,IEEE Transactions on Automatic Control,Marden2013,False,,IEEE,Not available,Overcoming the Limitations of Utility Design for Multiagent Systems,8676e6c5e3cf9d0a15c025cbcd92325d,https://ieeexplore.ieee.org/document/6403513/
2757,"Cooperative control focuses on deriving desirable collective behavior in multiagent systems through the design of local control algorithms. Game theory is beginning to emerge as a valuable set of tools for achieving this objective. A central component of this game theoretic approach is the assignment of utility functions to the individual agents. Here, the goal is to assign utility functions within an “admissible” design space such that the resulting game possesses desirable properties. Our first set of results illustrates the complexity associated with such a task. In particular, we prove that if we restrict the class of utility functions to be local, scalable, and budget-balanced then 1) ensuring that the resulting game possesses a pure Nash equilibrium requires computing a Shapley value, which can be computationally prohibitive for large-scale systems, and 2) ensuring that the allocation which optimizes the system level objective is a pure Nash equilibrium is impossible. The last part of this paper demonstrates that both limitations can be overcome by introducing an underlying state space into the potential game structure.",jason marden,price of anarchy,2013.0,10.1109/TAC.2013.2237831,IEEE Transactions on Automatic Control,Marden2013,False,,IEEE,Not available,Overcoming the Limitations of Utility Design for Multiagent Systems,8676e6c5e3cf9d0a15c025cbcd92325d,https://ieeexplore.ieee.org/document/6403513/
2758,"Cooperative control focuses on deriving desirable collective behavior in multiagent systems through the design of local control algorithms. Game theory is beginning to emerge as a valuable set of tools for achieving this objective. A central component of this game theoretic approach is the assignment of utility functions to the individual agents. Here, the goal is to assign utility functions within an “admissible” design space such that the resulting game possesses desirable properties. Our first set of results illustrates the complexity associated with such a task. In particular, we prove that if we restrict the class of utility functions to be local, scalable, and budget-balanced then 1) ensuring that the resulting game possesses a pure Nash equilibrium requires computing a Shapley value, which can be computationally prohibitive for large-scale systems, and 2) ensuring that the allocation which optimizes the system level objective is a pure Nash equilibrium is impossible. The last part of this paper demonstrates that both limitations can be overcome by introducing an underlying state space into the potential game structure.",adam wierman,Cost sharing,2013.0,10.1109/TAC.2013.2237831,IEEE Transactions on Automatic Control,Marden2013,False,,IEEE,Not available,Overcoming the Limitations of Utility Design for Multiagent Systems,8676e6c5e3cf9d0a15c025cbcd92325d,https://ieeexplore.ieee.org/document/6403513/
2759,"Cooperative control focuses on deriving desirable collective behavior in multiagent systems through the design of local control algorithms. Game theory is beginning to emerge as a valuable set of tools for achieving this objective. A central component of this game theoretic approach is the assignment of utility functions to the individual agents. Here, the goal is to assign utility functions within an “admissible” design space such that the resulting game possesses desirable properties. Our first set of results illustrates the complexity associated with such a task. In particular, we prove that if we restrict the class of utility functions to be local, scalable, and budget-balanced then 1) ensuring that the resulting game possesses a pure Nash equilibrium requires computing a Shapley value, which can be computationally prohibitive for large-scale systems, and 2) ensuring that the allocation which optimizes the system level objective is a pure Nash equilibrium is impossible. The last part of this paper demonstrates that both limitations can be overcome by introducing an underlying state space into the potential game structure.",adam wierman,distributed control,2013.0,10.1109/TAC.2013.2237831,IEEE Transactions on Automatic Control,Marden2013,False,,IEEE,Not available,Overcoming the Limitations of Utility Design for Multiagent Systems,8676e6c5e3cf9d0a15c025cbcd92325d,https://ieeexplore.ieee.org/document/6403513/
2760,"Cooperative control focuses on deriving desirable collective behavior in multiagent systems through the design of local control algorithms. Game theory is beginning to emerge as a valuable set of tools for achieving this objective. A central component of this game theoretic approach is the assignment of utility functions to the individual agents. Here, the goal is to assign utility functions within an “admissible” design space such that the resulting game possesses desirable properties. Our first set of results illustrates the complexity associated with such a task. In particular, we prove that if we restrict the class of utility functions to be local, scalable, and budget-balanced then 1) ensuring that the resulting game possesses a pure Nash equilibrium requires computing a Shapley value, which can be computationally prohibitive for large-scale systems, and 2) ensuring that the allocation which optimizes the system level objective is a pure Nash equilibrium is impossible. The last part of this paper demonstrates that both limitations can be overcome by introducing an underlying state space into the potential game structure.",adam wierman,game theory,2013.0,10.1109/TAC.2013.2237831,IEEE Transactions on Automatic Control,Marden2013,False,,IEEE,Not available,Overcoming the Limitations of Utility Design for Multiagent Systems,8676e6c5e3cf9d0a15c025cbcd92325d,https://ieeexplore.ieee.org/document/6403513/
2761,"Cooperative control focuses on deriving desirable collective behavior in multiagent systems through the design of local control algorithms. Game theory is beginning to emerge as a valuable set of tools for achieving this objective. A central component of this game theoretic approach is the assignment of utility functions to the individual agents. Here, the goal is to assign utility functions within an “admissible” design space such that the resulting game possesses desirable properties. Our first set of results illustrates the complexity associated with such a task. In particular, we prove that if we restrict the class of utility functions to be local, scalable, and budget-balanced then 1) ensuring that the resulting game possesses a pure Nash equilibrium requires computing a Shapley value, which can be computationally prohibitive for large-scale systems, and 2) ensuring that the allocation which optimizes the system level objective is a pure Nash equilibrium is impossible. The last part of this paper demonstrates that both limitations can be overcome by introducing an underlying state space into the potential game structure.",adam wierman,price of anarchy,2013.0,10.1109/TAC.2013.2237831,IEEE Transactions on Automatic Control,Marden2013,False,,IEEE,Not available,Overcoming the Limitations of Utility Design for Multiagent Systems,8676e6c5e3cf9d0a15c025cbcd92325d,https://ieeexplore.ieee.org/document/6403513/
2762,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2763,"Well known in the theory of network flows, Braess paradox states that in a congested network, it may happen that adding a new path between destinations can increase the level of congestion. In transportation networks the phenomenon results from the decisions of network participants who selfishly seek to optimize their own performance metrics. In an electric power distribution network, an analogous increase in congestion can arise as a consequence Kirchhoff's laws. Even for the simplest linear network of resistors and voltage sources, the sudden appearance of congestion due to an additional conductive line is a nonlinear phenomenon that results in a discontinuous change in the network state. It is argued that the phenomenon can occur in almost any grid in which they are loops, and with the increasing penetration of small-scale distributed generation, it suggests challenges ahead in the operation of microgrids.",john baillieul,distribution networks,2015.0,10.1109/CDC.2015.7403252,2015 54th IEEE Conference on Decision and Control (CDC),Baillieul2015,False,,IEEE,Not available,The Kirchhoff-Braess paradox and its implications for smart microgrids,91293091c051e153b64c353e452bdc48,https://ieeexplore.ieee.org/document/7403252/
2764,"Well known in the theory of network flows, Braess paradox states that in a congested network, it may happen that adding a new path between destinations can increase the level of congestion. In transportation networks the phenomenon results from the decisions of network participants who selfishly seek to optimize their own performance metrics. In an electric power distribution network, an analogous increase in congestion can arise as a consequence Kirchhoff's laws. Even for the simplest linear network of resistors and voltage sources, the sudden appearance of congestion due to an additional conductive line is a nonlinear phenomenon that results in a discontinuous change in the network state. It is argued that the phenomenon can occur in almost any grid in which they are loops, and with the increasing penetration of small-scale distributed generation, it suggests challenges ahead in the operation of microgrids.",john baillieul,network congestion,2015.0,10.1109/CDC.2015.7403252,2015 54th IEEE Conference on Decision and Control (CDC),Baillieul2015,False,,IEEE,Not available,The Kirchhoff-Braess paradox and its implications for smart microgrids,91293091c051e153b64c353e452bdc48,https://ieeexplore.ieee.org/document/7403252/
2765,"Well known in the theory of network flows, Braess paradox states that in a congested network, it may happen that adding a new path between destinations can increase the level of congestion. In transportation networks the phenomenon results from the decisions of network participants who selfishly seek to optimize their own performance metrics. In an electric power distribution network, an analogous increase in congestion can arise as a consequence Kirchhoff's laws. Even for the simplest linear network of resistors and voltage sources, the sudden appearance of congestion due to an additional conductive line is a nonlinear phenomenon that results in a discontinuous change in the network state. It is argued that the phenomenon can occur in almost any grid in which they are loops, and with the increasing penetration of small-scale distributed generation, it suggests challenges ahead in the operation of microgrids.",john baillieul,loss cost,2015.0,10.1109/CDC.2015.7403252,2015 54th IEEE Conference on Decision and Control (CDC),Baillieul2015,False,,IEEE,Not available,The Kirchhoff-Braess paradox and its implications for smart microgrids,91293091c051e153b64c353e452bdc48,https://ieeexplore.ieee.org/document/7403252/
2766,"Well known in the theory of network flows, Braess paradox states that in a congested network, it may happen that adding a new path between destinations can increase the level of congestion. In transportation networks the phenomenon results from the decisions of network participants who selfishly seek to optimize their own performance metrics. In an electric power distribution network, an analogous increase in congestion can arise as a consequence Kirchhoff's laws. Even for the simplest linear network of resistors and voltage sources, the sudden appearance of congestion due to an additional conductive line is a nonlinear phenomenon that results in a discontinuous change in the network state. It is argued that the phenomenon can occur in almost any grid in which they are loops, and with the increasing penetration of small-scale distributed generation, it suggests challenges ahead in the operation of microgrids.",john baillieul,price of anarchy,2015.0,10.1109/CDC.2015.7403252,2015 54th IEEE Conference on Decision and Control (CDC),Baillieul2015,False,,IEEE,Not available,The Kirchhoff-Braess paradox and its implications for smart microgrids,91293091c051e153b64c353e452bdc48,https://ieeexplore.ieee.org/document/7403252/
2767,"Well known in the theory of network flows, Braess paradox states that in a congested network, it may happen that adding a new path between destinations can increase the level of congestion. In transportation networks the phenomenon results from the decisions of network participants who selfishly seek to optimize their own performance metrics. In an electric power distribution network, an analogous increase in congestion can arise as a consequence Kirchhoff's laws. Even for the simplest linear network of resistors and voltage sources, the sudden appearance of congestion due to an additional conductive line is a nonlinear phenomenon that results in a discontinuous change in the network state. It is argued that the phenomenon can occur in almost any grid in which they are loops, and with the increasing penetration of small-scale distributed generation, it suggests challenges ahead in the operation of microgrids.",bowen zhang,distribution networks,2015.0,10.1109/CDC.2015.7403252,2015 54th IEEE Conference on Decision and Control (CDC),Baillieul2015,False,,IEEE,Not available,The Kirchhoff-Braess paradox and its implications for smart microgrids,91293091c051e153b64c353e452bdc48,https://ieeexplore.ieee.org/document/7403252/
2768,"Well known in the theory of network flows, Braess paradox states that in a congested network, it may happen that adding a new path between destinations can increase the level of congestion. In transportation networks the phenomenon results from the decisions of network participants who selfishly seek to optimize their own performance metrics. In an electric power distribution network, an analogous increase in congestion can arise as a consequence Kirchhoff's laws. Even for the simplest linear network of resistors and voltage sources, the sudden appearance of congestion due to an additional conductive line is a nonlinear phenomenon that results in a discontinuous change in the network state. It is argued that the phenomenon can occur in almost any grid in which they are loops, and with the increasing penetration of small-scale distributed generation, it suggests challenges ahead in the operation of microgrids.",bowen zhang,network congestion,2015.0,10.1109/CDC.2015.7403252,2015 54th IEEE Conference on Decision and Control (CDC),Baillieul2015,False,,IEEE,Not available,The Kirchhoff-Braess paradox and its implications for smart microgrids,91293091c051e153b64c353e452bdc48,https://ieeexplore.ieee.org/document/7403252/
2769,"Well known in the theory of network flows, Braess paradox states that in a congested network, it may happen that adding a new path between destinations can increase the level of congestion. In transportation networks the phenomenon results from the decisions of network participants who selfishly seek to optimize their own performance metrics. In an electric power distribution network, an analogous increase in congestion can arise as a consequence Kirchhoff's laws. Even for the simplest linear network of resistors and voltage sources, the sudden appearance of congestion due to an additional conductive line is a nonlinear phenomenon that results in a discontinuous change in the network state. It is argued that the phenomenon can occur in almost any grid in which they are loops, and with the increasing penetration of small-scale distributed generation, it suggests challenges ahead in the operation of microgrids.",bowen zhang,loss cost,2015.0,10.1109/CDC.2015.7403252,2015 54th IEEE Conference on Decision and Control (CDC),Baillieul2015,False,,IEEE,Not available,The Kirchhoff-Braess paradox and its implications for smart microgrids,91293091c051e153b64c353e452bdc48,https://ieeexplore.ieee.org/document/7403252/
2770,"Well known in the theory of network flows, Braess paradox states that in a congested network, it may happen that adding a new path between destinations can increase the level of congestion. In transportation networks the phenomenon results from the decisions of network participants who selfishly seek to optimize their own performance metrics. In an electric power distribution network, an analogous increase in congestion can arise as a consequence Kirchhoff's laws. Even for the simplest linear network of resistors and voltage sources, the sudden appearance of congestion due to an additional conductive line is a nonlinear phenomenon that results in a discontinuous change in the network state. It is argued that the phenomenon can occur in almost any grid in which they are loops, and with the increasing penetration of small-scale distributed generation, it suggests challenges ahead in the operation of microgrids.",bowen zhang,price of anarchy,2015.0,10.1109/CDC.2015.7403252,2015 54th IEEE Conference on Decision and Control (CDC),Baillieul2015,False,,IEEE,Not available,The Kirchhoff-Braess paradox and its implications for smart microgrids,91293091c051e153b64c353e452bdc48,https://ieeexplore.ieee.org/document/7403252/
2771,"Well known in the theory of network flows, Braess paradox states that in a congested network, it may happen that adding a new path between destinations can increase the level of congestion. In transportation networks the phenomenon results from the decisions of network participants who selfishly seek to optimize their own performance metrics. In an electric power distribution network, an analogous increase in congestion can arise as a consequence Kirchhoff's laws. Even for the simplest linear network of resistors and voltage sources, the sudden appearance of congestion due to an additional conductive line is a nonlinear phenomenon that results in a discontinuous change in the network state. It is argued that the phenomenon can occur in almost any grid in which they are loops, and with the increasing penetration of small-scale distributed generation, it suggests challenges ahead in the operation of microgrids.",shuai wang,distribution networks,2015.0,10.1109/CDC.2015.7403252,2015 54th IEEE Conference on Decision and Control (CDC),Baillieul2015,False,,IEEE,Not available,The Kirchhoff-Braess paradox and its implications for smart microgrids,91293091c051e153b64c353e452bdc48,https://ieeexplore.ieee.org/document/7403252/
2772,"Well known in the theory of network flows, Braess paradox states that in a congested network, it may happen that adding a new path between destinations can increase the level of congestion. In transportation networks the phenomenon results from the decisions of network participants who selfishly seek to optimize their own performance metrics. In an electric power distribution network, an analogous increase in congestion can arise as a consequence Kirchhoff's laws. Even for the simplest linear network of resistors and voltage sources, the sudden appearance of congestion due to an additional conductive line is a nonlinear phenomenon that results in a discontinuous change in the network state. It is argued that the phenomenon can occur in almost any grid in which they are loops, and with the increasing penetration of small-scale distributed generation, it suggests challenges ahead in the operation of microgrids.",shuai wang,network congestion,2015.0,10.1109/CDC.2015.7403252,2015 54th IEEE Conference on Decision and Control (CDC),Baillieul2015,False,,IEEE,Not available,The Kirchhoff-Braess paradox and its implications for smart microgrids,91293091c051e153b64c353e452bdc48,https://ieeexplore.ieee.org/document/7403252/
2773,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2774,"Well known in the theory of network flows, Braess paradox states that in a congested network, it may happen that adding a new path between destinations can increase the level of congestion. In transportation networks the phenomenon results from the decisions of network participants who selfishly seek to optimize their own performance metrics. In an electric power distribution network, an analogous increase in congestion can arise as a consequence Kirchhoff's laws. Even for the simplest linear network of resistors and voltage sources, the sudden appearance of congestion due to an additional conductive line is a nonlinear phenomenon that results in a discontinuous change in the network state. It is argued that the phenomenon can occur in almost any grid in which they are loops, and with the increasing penetration of small-scale distributed generation, it suggests challenges ahead in the operation of microgrids.",shuai wang,loss cost,2015.0,10.1109/CDC.2015.7403252,2015 54th IEEE Conference on Decision and Control (CDC),Baillieul2015,False,,IEEE,Not available,The Kirchhoff-Braess paradox and its implications for smart microgrids,91293091c051e153b64c353e452bdc48,https://ieeexplore.ieee.org/document/7403252/
2775,"Well known in the theory of network flows, Braess paradox states that in a congested network, it may happen that adding a new path between destinations can increase the level of congestion. In transportation networks the phenomenon results from the decisions of network participants who selfishly seek to optimize their own performance metrics. In an electric power distribution network, an analogous increase in congestion can arise as a consequence Kirchhoff's laws. Even for the simplest linear network of resistors and voltage sources, the sudden appearance of congestion due to an additional conductive line is a nonlinear phenomenon that results in a discontinuous change in the network state. It is argued that the phenomenon can occur in almost any grid in which they are loops, and with the increasing penetration of small-scale distributed generation, it suggests challenges ahead in the operation of microgrids.",shuai wang,price of anarchy,2015.0,10.1109/CDC.2015.7403252,2015 54th IEEE Conference on Decision and Control (CDC),Baillieul2015,False,,IEEE,Not available,The Kirchhoff-Braess paradox and its implications for smart microgrids,91293091c051e153b64c353e452bdc48,https://ieeexplore.ieee.org/document/7403252/
2776,"Strong resilience properties of dynamical networks are analyzed for distributed routing policies. The latter are characterized by the property that the way the outflow at a non-destination node gets split among its outgoing links is allowed to depend only on local information about the current particle densities on the outgoing links. The strong resilience of the network is defined as the infimum sum of link-wise flow capacity reductions making the asymptotic total inflow to the destination node strictly less than the total outflow at the origin. A class of distributed routing policies that are responsive to local information is shown to yield the maximum possible strong resilience under such local information constraints for an acyclic dynamical network with a single origin-destination pair. The maximal achievable strong resilience is shown to be equal to the minimum node residual capacity of the network. The latter depends on the limit flow of the unperturbed network and is defined as the minimum, among all the non-destination nodes, of the sum, over all the links outgoing from the node, of the differences between the maximum flow capacity and the limit flow of the unperturbed network. We propose a simple convex optimization problem to solve for equilibrium flows of the unperturbed network that minimize average delay subject to strong resilience guarantees, and discuss the use of tolls to induce such an equilibrium flow in traffic networks. Finally, we present illustrative simulations to discuss the connection between cascaded failures and the resilience properties of the network.",giacomo como,Cascaded failures,2013.0,10.1109/TAC.2012.2209975,IEEE Transactions on Automatic Control,Como2013,False,,IEEE,Not available,"Robust Distributed Routing in Dynamical Networks–Part II: Strong Resilience, Equilibrium Selection and Cascaded Failures",ac3c0b5ab7aa157941d911dd44949469,https://ieeexplore.ieee.org/document/6248170/
2777,"Strong resilience properties of dynamical networks are analyzed for distributed routing policies. The latter are characterized by the property that the way the outflow at a non-destination node gets split among its outgoing links is allowed to depend only on local information about the current particle densities on the outgoing links. The strong resilience of the network is defined as the infimum sum of link-wise flow capacity reductions making the asymptotic total inflow to the destination node strictly less than the total outflow at the origin. A class of distributed routing policies that are responsive to local information is shown to yield the maximum possible strong resilience under such local information constraints for an acyclic dynamical network with a single origin-destination pair. The maximal achievable strong resilience is shown to be equal to the minimum node residual capacity of the network. The latter depends on the limit flow of the unperturbed network and is defined as the minimum, among all the non-destination nodes, of the sum, over all the links outgoing from the node, of the differences between the maximum flow capacity and the limit flow of the unperturbed network. We propose a simple convex optimization problem to solve for equilibrium flows of the unperturbed network that minimize average delay subject to strong resilience guarantees, and discuss the use of tolls to induce such an equilibrium flow in traffic networks. Finally, we present illustrative simulations to discuss the connection between cascaded failures and the resilience properties of the network.",giacomo como,distributed routing policies,2013.0,10.1109/TAC.2012.2209975,IEEE Transactions on Automatic Control,Como2013,False,,IEEE,Not available,"Robust Distributed Routing in Dynamical Networks–Part II: Strong Resilience, Equilibrium Selection and Cascaded Failures",ac3c0b5ab7aa157941d911dd44949469,https://ieeexplore.ieee.org/document/6248170/
2778,"Strong resilience properties of dynamical networks are analyzed for distributed routing policies. The latter are characterized by the property that the way the outflow at a non-destination node gets split among its outgoing links is allowed to depend only on local information about the current particle densities on the outgoing links. The strong resilience of the network is defined as the infimum sum of link-wise flow capacity reductions making the asymptotic total inflow to the destination node strictly less than the total outflow at the origin. A class of distributed routing policies that are responsive to local information is shown to yield the maximum possible strong resilience under such local information constraints for an acyclic dynamical network with a single origin-destination pair. The maximal achievable strong resilience is shown to be equal to the minimum node residual capacity of the network. The latter depends on the limit flow of the unperturbed network and is defined as the minimum, among all the non-destination nodes, of the sum, over all the links outgoing from the node, of the differences between the maximum flow capacity and the limit flow of the unperturbed network. We propose a simple convex optimization problem to solve for equilibrium flows of the unperturbed network that minimize average delay subject to strong resilience guarantees, and discuss the use of tolls to induce such an equilibrium flow in traffic networks. Finally, we present illustrative simulations to discuss the connection between cascaded failures and the resilience properties of the network.",giacomo como,dynamical networks,2013.0,10.1109/TAC.2012.2209975,IEEE Transactions on Automatic Control,Como2013,False,,IEEE,Not available,"Robust Distributed Routing in Dynamical Networks–Part II: Strong Resilience, Equilibrium Selection and Cascaded Failures",ac3c0b5ab7aa157941d911dd44949469,https://ieeexplore.ieee.org/document/6248170/
2779,"Strong resilience properties of dynamical networks are analyzed for distributed routing policies. The latter are characterized by the property that the way the outflow at a non-destination node gets split among its outgoing links is allowed to depend only on local information about the current particle densities on the outgoing links. The strong resilience of the network is defined as the infimum sum of link-wise flow capacity reductions making the asymptotic total inflow to the destination node strictly less than the total outflow at the origin. A class of distributed routing policies that are responsive to local information is shown to yield the maximum possible strong resilience under such local information constraints for an acyclic dynamical network with a single origin-destination pair. The maximal achievable strong resilience is shown to be equal to the minimum node residual capacity of the network. The latter depends on the limit flow of the unperturbed network and is defined as the minimum, among all the non-destination nodes, of the sum, over all the links outgoing from the node, of the differences between the maximum flow capacity and the limit flow of the unperturbed network. We propose a simple convex optimization problem to solve for equilibrium flows of the unperturbed network that minimize average delay subject to strong resilience guarantees, and discuss the use of tolls to induce such an equilibrium flow in traffic networks. Finally, we present illustrative simulations to discuss the connection between cascaded failures and the resilience properties of the network.",giacomo como,price of anarchy,2013.0,10.1109/TAC.2012.2209975,IEEE Transactions on Automatic Control,Como2013,False,,IEEE,Not available,"Robust Distributed Routing in Dynamical Networks–Part II: Strong Resilience, Equilibrium Selection and Cascaded Failures",ac3c0b5ab7aa157941d911dd44949469,https://ieeexplore.ieee.org/document/6248170/
2780,"Strong resilience properties of dynamical networks are analyzed for distributed routing policies. The latter are characterized by the property that the way the outflow at a non-destination node gets split among its outgoing links is allowed to depend only on local information about the current particle densities on the outgoing links. The strong resilience of the network is defined as the infimum sum of link-wise flow capacity reductions making the asymptotic total inflow to the destination node strictly less than the total outflow at the origin. A class of distributed routing policies that are responsive to local information is shown to yield the maximum possible strong resilience under such local information constraints for an acyclic dynamical network with a single origin-destination pair. The maximal achievable strong resilience is shown to be equal to the minimum node residual capacity of the network. The latter depends on the limit flow of the unperturbed network and is defined as the minimum, among all the non-destination nodes, of the sum, over all the links outgoing from the node, of the differences between the maximum flow capacity and the limit flow of the unperturbed network. We propose a simple convex optimization problem to solve for equilibrium flows of the unperturbed network that minimize average delay subject to strong resilience guarantees, and discuss the use of tolls to induce such an equilibrium flow in traffic networks. Finally, we present illustrative simulations to discuss the connection between cascaded failures and the resilience properties of the network.",giacomo como,strong resilience,2013.0,10.1109/TAC.2012.2209975,IEEE Transactions on Automatic Control,Como2013,False,,IEEE,Not available,"Robust Distributed Routing in Dynamical Networks–Part II: Strong Resilience, Equilibrium Selection and Cascaded Failures",ac3c0b5ab7aa157941d911dd44949469,https://ieeexplore.ieee.org/document/6248170/
2781,"Strong resilience properties of dynamical networks are analyzed for distributed routing policies. The latter are characterized by the property that the way the outflow at a non-destination node gets split among its outgoing links is allowed to depend only on local information about the current particle densities on the outgoing links. The strong resilience of the network is defined as the infimum sum of link-wise flow capacity reductions making the asymptotic total inflow to the destination node strictly less than the total outflow at the origin. A class of distributed routing policies that are responsive to local information is shown to yield the maximum possible strong resilience under such local information constraints for an acyclic dynamical network with a single origin-destination pair. The maximal achievable strong resilience is shown to be equal to the minimum node residual capacity of the network. The latter depends on the limit flow of the unperturbed network and is defined as the minimum, among all the non-destination nodes, of the sum, over all the links outgoing from the node, of the differences between the maximum flow capacity and the limit flow of the unperturbed network. We propose a simple convex optimization problem to solve for equilibrium flows of the unperturbed network that minimize average delay subject to strong resilience guarantees, and discuss the use of tolls to induce such an equilibrium flow in traffic networks. Finally, we present illustrative simulations to discuss the connection between cascaded failures and the resilience properties of the network.",ketan savla,Cascaded failures,2013.0,10.1109/TAC.2012.2209975,IEEE Transactions on Automatic Control,Como2013,False,,IEEE,Not available,"Robust Distributed Routing in Dynamical Networks–Part II: Strong Resilience, Equilibrium Selection and Cascaded Failures",ac3c0b5ab7aa157941d911dd44949469,https://ieeexplore.ieee.org/document/6248170/
2782,"Strong resilience properties of dynamical networks are analyzed for distributed routing policies. The latter are characterized by the property that the way the outflow at a non-destination node gets split among its outgoing links is allowed to depend only on local information about the current particle densities on the outgoing links. The strong resilience of the network is defined as the infimum sum of link-wise flow capacity reductions making the asymptotic total inflow to the destination node strictly less than the total outflow at the origin. A class of distributed routing policies that are responsive to local information is shown to yield the maximum possible strong resilience under such local information constraints for an acyclic dynamical network with a single origin-destination pair. The maximal achievable strong resilience is shown to be equal to the minimum node residual capacity of the network. The latter depends on the limit flow of the unperturbed network and is defined as the minimum, among all the non-destination nodes, of the sum, over all the links outgoing from the node, of the differences between the maximum flow capacity and the limit flow of the unperturbed network. We propose a simple convex optimization problem to solve for equilibrium flows of the unperturbed network that minimize average delay subject to strong resilience guarantees, and discuss the use of tolls to induce such an equilibrium flow in traffic networks. Finally, we present illustrative simulations to discuss the connection between cascaded failures and the resilience properties of the network.",ketan savla,distributed routing policies,2013.0,10.1109/TAC.2012.2209975,IEEE Transactions on Automatic Control,Como2013,False,,IEEE,Not available,"Robust Distributed Routing in Dynamical Networks–Part II: Strong Resilience, Equilibrium Selection and Cascaded Failures",ac3c0b5ab7aa157941d911dd44949469,https://ieeexplore.ieee.org/document/6248170/
2783,"Strong resilience properties of dynamical networks are analyzed for distributed routing policies. The latter are characterized by the property that the way the outflow at a non-destination node gets split among its outgoing links is allowed to depend only on local information about the current particle densities on the outgoing links. The strong resilience of the network is defined as the infimum sum of link-wise flow capacity reductions making the asymptotic total inflow to the destination node strictly less than the total outflow at the origin. A class of distributed routing policies that are responsive to local information is shown to yield the maximum possible strong resilience under such local information constraints for an acyclic dynamical network with a single origin-destination pair. The maximal achievable strong resilience is shown to be equal to the minimum node residual capacity of the network. The latter depends on the limit flow of the unperturbed network and is defined as the minimum, among all the non-destination nodes, of the sum, over all the links outgoing from the node, of the differences between the maximum flow capacity and the limit flow of the unperturbed network. We propose a simple convex optimization problem to solve for equilibrium flows of the unperturbed network that minimize average delay subject to strong resilience guarantees, and discuss the use of tolls to induce such an equilibrium flow in traffic networks. Finally, we present illustrative simulations to discuss the connection between cascaded failures and the resilience properties of the network.",ketan savla,dynamical networks,2013.0,10.1109/TAC.2012.2209975,IEEE Transactions on Automatic Control,Como2013,False,,IEEE,Not available,"Robust Distributed Routing in Dynamical Networks–Part II: Strong Resilience, Equilibrium Selection and Cascaded Failures",ac3c0b5ab7aa157941d911dd44949469,https://ieeexplore.ieee.org/document/6248170/
2784,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2785,"Strong resilience properties of dynamical networks are analyzed for distributed routing policies. The latter are characterized by the property that the way the outflow at a non-destination node gets split among its outgoing links is allowed to depend only on local information about the current particle densities on the outgoing links. The strong resilience of the network is defined as the infimum sum of link-wise flow capacity reductions making the asymptotic total inflow to the destination node strictly less than the total outflow at the origin. A class of distributed routing policies that are responsive to local information is shown to yield the maximum possible strong resilience under such local information constraints for an acyclic dynamical network with a single origin-destination pair. The maximal achievable strong resilience is shown to be equal to the minimum node residual capacity of the network. The latter depends on the limit flow of the unperturbed network and is defined as the minimum, among all the non-destination nodes, of the sum, over all the links outgoing from the node, of the differences between the maximum flow capacity and the limit flow of the unperturbed network. We propose a simple convex optimization problem to solve for equilibrium flows of the unperturbed network that minimize average delay subject to strong resilience guarantees, and discuss the use of tolls to induce such an equilibrium flow in traffic networks. Finally, we present illustrative simulations to discuss the connection between cascaded failures and the resilience properties of the network.",ketan savla,price of anarchy,2013.0,10.1109/TAC.2012.2209975,IEEE Transactions on Automatic Control,Como2013,False,,IEEE,Not available,"Robust Distributed Routing in Dynamical Networks–Part II: Strong Resilience, Equilibrium Selection and Cascaded Failures",ac3c0b5ab7aa157941d911dd44949469,https://ieeexplore.ieee.org/document/6248170/
2786,"Strong resilience properties of dynamical networks are analyzed for distributed routing policies. The latter are characterized by the property that the way the outflow at a non-destination node gets split among its outgoing links is allowed to depend only on local information about the current particle densities on the outgoing links. The strong resilience of the network is defined as the infimum sum of link-wise flow capacity reductions making the asymptotic total inflow to the destination node strictly less than the total outflow at the origin. A class of distributed routing policies that are responsive to local information is shown to yield the maximum possible strong resilience under such local information constraints for an acyclic dynamical network with a single origin-destination pair. The maximal achievable strong resilience is shown to be equal to the minimum node residual capacity of the network. The latter depends on the limit flow of the unperturbed network and is defined as the minimum, among all the non-destination nodes, of the sum, over all the links outgoing from the node, of the differences between the maximum flow capacity and the limit flow of the unperturbed network. We propose a simple convex optimization problem to solve for equilibrium flows of the unperturbed network that minimize average delay subject to strong resilience guarantees, and discuss the use of tolls to induce such an equilibrium flow in traffic networks. Finally, we present illustrative simulations to discuss the connection between cascaded failures and the resilience properties of the network.",ketan savla,strong resilience,2013.0,10.1109/TAC.2012.2209975,IEEE Transactions on Automatic Control,Como2013,False,,IEEE,Not available,"Robust Distributed Routing in Dynamical Networks–Part II: Strong Resilience, Equilibrium Selection and Cascaded Failures",ac3c0b5ab7aa157941d911dd44949469,https://ieeexplore.ieee.org/document/6248170/
2787,"Strong resilience properties of dynamical networks are analyzed for distributed routing policies. The latter are characterized by the property that the way the outflow at a non-destination node gets split among its outgoing links is allowed to depend only on local information about the current particle densities on the outgoing links. The strong resilience of the network is defined as the infimum sum of link-wise flow capacity reductions making the asymptotic total inflow to the destination node strictly less than the total outflow at the origin. A class of distributed routing policies that are responsive to local information is shown to yield the maximum possible strong resilience under such local information constraints for an acyclic dynamical network with a single origin-destination pair. The maximal achievable strong resilience is shown to be equal to the minimum node residual capacity of the network. The latter depends on the limit flow of the unperturbed network and is defined as the minimum, among all the non-destination nodes, of the sum, over all the links outgoing from the node, of the differences between the maximum flow capacity and the limit flow of the unperturbed network. We propose a simple convex optimization problem to solve for equilibrium flows of the unperturbed network that minimize average delay subject to strong resilience guarantees, and discuss the use of tolls to induce such an equilibrium flow in traffic networks. Finally, we present illustrative simulations to discuss the connection between cascaded failures and the resilience properties of the network.",daron acemoglu,Cascaded failures,2013.0,10.1109/TAC.2012.2209975,IEEE Transactions on Automatic Control,Como2013,False,,IEEE,Not available,"Robust Distributed Routing in Dynamical Networks–Part II: Strong Resilience, Equilibrium Selection and Cascaded Failures",ac3c0b5ab7aa157941d911dd44949469,https://ieeexplore.ieee.org/document/6248170/
2788,"Strong resilience properties of dynamical networks are analyzed for distributed routing policies. The latter are characterized by the property that the way the outflow at a non-destination node gets split among its outgoing links is allowed to depend only on local information about the current particle densities on the outgoing links. The strong resilience of the network is defined as the infimum sum of link-wise flow capacity reductions making the asymptotic total inflow to the destination node strictly less than the total outflow at the origin. A class of distributed routing policies that are responsive to local information is shown to yield the maximum possible strong resilience under such local information constraints for an acyclic dynamical network with a single origin-destination pair. The maximal achievable strong resilience is shown to be equal to the minimum node residual capacity of the network. The latter depends on the limit flow of the unperturbed network and is defined as the minimum, among all the non-destination nodes, of the sum, over all the links outgoing from the node, of the differences between the maximum flow capacity and the limit flow of the unperturbed network. We propose a simple convex optimization problem to solve for equilibrium flows of the unperturbed network that minimize average delay subject to strong resilience guarantees, and discuss the use of tolls to induce such an equilibrium flow in traffic networks. Finally, we present illustrative simulations to discuss the connection between cascaded failures and the resilience properties of the network.",daron acemoglu,distributed routing policies,2013.0,10.1109/TAC.2012.2209975,IEEE Transactions on Automatic Control,Como2013,False,,IEEE,Not available,"Robust Distributed Routing in Dynamical Networks–Part II: Strong Resilience, Equilibrium Selection and Cascaded Failures",ac3c0b5ab7aa157941d911dd44949469,https://ieeexplore.ieee.org/document/6248170/
2789,"Strong resilience properties of dynamical networks are analyzed for distributed routing policies. The latter are characterized by the property that the way the outflow at a non-destination node gets split among its outgoing links is allowed to depend only on local information about the current particle densities on the outgoing links. The strong resilience of the network is defined as the infimum sum of link-wise flow capacity reductions making the asymptotic total inflow to the destination node strictly less than the total outflow at the origin. A class of distributed routing policies that are responsive to local information is shown to yield the maximum possible strong resilience under such local information constraints for an acyclic dynamical network with a single origin-destination pair. The maximal achievable strong resilience is shown to be equal to the minimum node residual capacity of the network. The latter depends on the limit flow of the unperturbed network and is defined as the minimum, among all the non-destination nodes, of the sum, over all the links outgoing from the node, of the differences between the maximum flow capacity and the limit flow of the unperturbed network. We propose a simple convex optimization problem to solve for equilibrium flows of the unperturbed network that minimize average delay subject to strong resilience guarantees, and discuss the use of tolls to induce such an equilibrium flow in traffic networks. Finally, we present illustrative simulations to discuss the connection between cascaded failures and the resilience properties of the network.",daron acemoglu,dynamical networks,2013.0,10.1109/TAC.2012.2209975,IEEE Transactions on Automatic Control,Como2013,False,,IEEE,Not available,"Robust Distributed Routing in Dynamical Networks–Part II: Strong Resilience, Equilibrium Selection and Cascaded Failures",ac3c0b5ab7aa157941d911dd44949469,https://ieeexplore.ieee.org/document/6248170/
2790,"Strong resilience properties of dynamical networks are analyzed for distributed routing policies. The latter are characterized by the property that the way the outflow at a non-destination node gets split among its outgoing links is allowed to depend only on local information about the current particle densities on the outgoing links. The strong resilience of the network is defined as the infimum sum of link-wise flow capacity reductions making the asymptotic total inflow to the destination node strictly less than the total outflow at the origin. A class of distributed routing policies that are responsive to local information is shown to yield the maximum possible strong resilience under such local information constraints for an acyclic dynamical network with a single origin-destination pair. The maximal achievable strong resilience is shown to be equal to the minimum node residual capacity of the network. The latter depends on the limit flow of the unperturbed network and is defined as the minimum, among all the non-destination nodes, of the sum, over all the links outgoing from the node, of the differences between the maximum flow capacity and the limit flow of the unperturbed network. We propose a simple convex optimization problem to solve for equilibrium flows of the unperturbed network that minimize average delay subject to strong resilience guarantees, and discuss the use of tolls to induce such an equilibrium flow in traffic networks. Finally, we present illustrative simulations to discuss the connection between cascaded failures and the resilience properties of the network.",daron acemoglu,price of anarchy,2013.0,10.1109/TAC.2012.2209975,IEEE Transactions on Automatic Control,Como2013,False,,IEEE,Not available,"Robust Distributed Routing in Dynamical Networks–Part II: Strong Resilience, Equilibrium Selection and Cascaded Failures",ac3c0b5ab7aa157941d911dd44949469,https://ieeexplore.ieee.org/document/6248170/
2791,"Strong resilience properties of dynamical networks are analyzed for distributed routing policies. The latter are characterized by the property that the way the outflow at a non-destination node gets split among its outgoing links is allowed to depend only on local information about the current particle densities on the outgoing links. The strong resilience of the network is defined as the infimum sum of link-wise flow capacity reductions making the asymptotic total inflow to the destination node strictly less than the total outflow at the origin. A class of distributed routing policies that are responsive to local information is shown to yield the maximum possible strong resilience under such local information constraints for an acyclic dynamical network with a single origin-destination pair. The maximal achievable strong resilience is shown to be equal to the minimum node residual capacity of the network. The latter depends on the limit flow of the unperturbed network and is defined as the minimum, among all the non-destination nodes, of the sum, over all the links outgoing from the node, of the differences between the maximum flow capacity and the limit flow of the unperturbed network. We propose a simple convex optimization problem to solve for equilibrium flows of the unperturbed network that minimize average delay subject to strong resilience guarantees, and discuss the use of tolls to induce such an equilibrium flow in traffic networks. Finally, we present illustrative simulations to discuss the connection between cascaded failures and the resilience properties of the network.",daron acemoglu,strong resilience,2013.0,10.1109/TAC.2012.2209975,IEEE Transactions on Automatic Control,Como2013,False,,IEEE,Not available,"Robust Distributed Routing in Dynamical Networks–Part II: Strong Resilience, Equilibrium Selection and Cascaded Failures",ac3c0b5ab7aa157941d911dd44949469,https://ieeexplore.ieee.org/document/6248170/
2792,"Strong resilience properties of dynamical networks are analyzed for distributed routing policies. The latter are characterized by the property that the way the outflow at a non-destination node gets split among its outgoing links is allowed to depend only on local information about the current particle densities on the outgoing links. The strong resilience of the network is defined as the infimum sum of link-wise flow capacity reductions making the asymptotic total inflow to the destination node strictly less than the total outflow at the origin. A class of distributed routing policies that are responsive to local information is shown to yield the maximum possible strong resilience under such local information constraints for an acyclic dynamical network with a single origin-destination pair. The maximal achievable strong resilience is shown to be equal to the minimum node residual capacity of the network. The latter depends on the limit flow of the unperturbed network and is defined as the minimum, among all the non-destination nodes, of the sum, over all the links outgoing from the node, of the differences between the maximum flow capacity and the limit flow of the unperturbed network. We propose a simple convex optimization problem to solve for equilibrium flows of the unperturbed network that minimize average delay subject to strong resilience guarantees, and discuss the use of tolls to induce such an equilibrium flow in traffic networks. Finally, we present illustrative simulations to discuss the connection between cascaded failures and the resilience properties of the network.",munther dahleh,Cascaded failures,2013.0,10.1109/TAC.2012.2209975,IEEE Transactions on Automatic Control,Como2013,False,,IEEE,Not available,"Robust Distributed Routing in Dynamical Networks–Part II: Strong Resilience, Equilibrium Selection and Cascaded Failures",ac3c0b5ab7aa157941d911dd44949469,https://ieeexplore.ieee.org/document/6248170/
2793,"Strong resilience properties of dynamical networks are analyzed for distributed routing policies. The latter are characterized by the property that the way the outflow at a non-destination node gets split among its outgoing links is allowed to depend only on local information about the current particle densities on the outgoing links. The strong resilience of the network is defined as the infimum sum of link-wise flow capacity reductions making the asymptotic total inflow to the destination node strictly less than the total outflow at the origin. A class of distributed routing policies that are responsive to local information is shown to yield the maximum possible strong resilience under such local information constraints for an acyclic dynamical network with a single origin-destination pair. The maximal achievable strong resilience is shown to be equal to the minimum node residual capacity of the network. The latter depends on the limit flow of the unperturbed network and is defined as the minimum, among all the non-destination nodes, of the sum, over all the links outgoing from the node, of the differences between the maximum flow capacity and the limit flow of the unperturbed network. We propose a simple convex optimization problem to solve for equilibrium flows of the unperturbed network that minimize average delay subject to strong resilience guarantees, and discuss the use of tolls to induce such an equilibrium flow in traffic networks. Finally, we present illustrative simulations to discuss the connection between cascaded failures and the resilience properties of the network.",munther dahleh,distributed routing policies,2013.0,10.1109/TAC.2012.2209975,IEEE Transactions on Automatic Control,Como2013,False,,IEEE,Not available,"Robust Distributed Routing in Dynamical Networks–Part II: Strong Resilience, Equilibrium Selection and Cascaded Failures",ac3c0b5ab7aa157941d911dd44949469,https://ieeexplore.ieee.org/document/6248170/
2794,"Strong resilience properties of dynamical networks are analyzed for distributed routing policies. The latter are characterized by the property that the way the outflow at a non-destination node gets split among its outgoing links is allowed to depend only on local information about the current particle densities on the outgoing links. The strong resilience of the network is defined as the infimum sum of link-wise flow capacity reductions making the asymptotic total inflow to the destination node strictly less than the total outflow at the origin. A class of distributed routing policies that are responsive to local information is shown to yield the maximum possible strong resilience under such local information constraints for an acyclic dynamical network with a single origin-destination pair. The maximal achievable strong resilience is shown to be equal to the minimum node residual capacity of the network. The latter depends on the limit flow of the unperturbed network and is defined as the minimum, among all the non-destination nodes, of the sum, over all the links outgoing from the node, of the differences between the maximum flow capacity and the limit flow of the unperturbed network. We propose a simple convex optimization problem to solve for equilibrium flows of the unperturbed network that minimize average delay subject to strong resilience guarantees, and discuss the use of tolls to induce such an equilibrium flow in traffic networks. Finally, we present illustrative simulations to discuss the connection between cascaded failures and the resilience properties of the network.",munther dahleh,dynamical networks,2013.0,10.1109/TAC.2012.2209975,IEEE Transactions on Automatic Control,Como2013,False,,IEEE,Not available,"Robust Distributed Routing in Dynamical Networks–Part II: Strong Resilience, Equilibrium Selection and Cascaded Failures",ac3c0b5ab7aa157941d911dd44949469,https://ieeexplore.ieee.org/document/6248170/
2795,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2796,"Strong resilience properties of dynamical networks are analyzed for distributed routing policies. The latter are characterized by the property that the way the outflow at a non-destination node gets split among its outgoing links is allowed to depend only on local information about the current particle densities on the outgoing links. The strong resilience of the network is defined as the infimum sum of link-wise flow capacity reductions making the asymptotic total inflow to the destination node strictly less than the total outflow at the origin. A class of distributed routing policies that are responsive to local information is shown to yield the maximum possible strong resilience under such local information constraints for an acyclic dynamical network with a single origin-destination pair. The maximal achievable strong resilience is shown to be equal to the minimum node residual capacity of the network. The latter depends on the limit flow of the unperturbed network and is defined as the minimum, among all the non-destination nodes, of the sum, over all the links outgoing from the node, of the differences between the maximum flow capacity and the limit flow of the unperturbed network. We propose a simple convex optimization problem to solve for equilibrium flows of the unperturbed network that minimize average delay subject to strong resilience guarantees, and discuss the use of tolls to induce such an equilibrium flow in traffic networks. Finally, we present illustrative simulations to discuss the connection between cascaded failures and the resilience properties of the network.",munther dahleh,price of anarchy,2013.0,10.1109/TAC.2012.2209975,IEEE Transactions on Automatic Control,Como2013,False,,IEEE,Not available,"Robust Distributed Routing in Dynamical Networks–Part II: Strong Resilience, Equilibrium Selection and Cascaded Failures",ac3c0b5ab7aa157941d911dd44949469,https://ieeexplore.ieee.org/document/6248170/
2797,"Strong resilience properties of dynamical networks are analyzed for distributed routing policies. The latter are characterized by the property that the way the outflow at a non-destination node gets split among its outgoing links is allowed to depend only on local information about the current particle densities on the outgoing links. The strong resilience of the network is defined as the infimum sum of link-wise flow capacity reductions making the asymptotic total inflow to the destination node strictly less than the total outflow at the origin. A class of distributed routing policies that are responsive to local information is shown to yield the maximum possible strong resilience under such local information constraints for an acyclic dynamical network with a single origin-destination pair. The maximal achievable strong resilience is shown to be equal to the minimum node residual capacity of the network. The latter depends on the limit flow of the unperturbed network and is defined as the minimum, among all the non-destination nodes, of the sum, over all the links outgoing from the node, of the differences between the maximum flow capacity and the limit flow of the unperturbed network. We propose a simple convex optimization problem to solve for equilibrium flows of the unperturbed network that minimize average delay subject to strong resilience guarantees, and discuss the use of tolls to induce such an equilibrium flow in traffic networks. Finally, we present illustrative simulations to discuss the connection between cascaded failures and the resilience properties of the network.",munther dahleh,strong resilience,2013.0,10.1109/TAC.2012.2209975,IEEE Transactions on Automatic Control,Como2013,False,,IEEE,Not available,"Robust Distributed Routing in Dynamical Networks–Part II: Strong Resilience, Equilibrium Selection and Cascaded Failures",ac3c0b5ab7aa157941d911dd44949469,https://ieeexplore.ieee.org/document/6248170/
2798,"Strong resilience properties of dynamical networks are analyzed for distributed routing policies. The latter are characterized by the property that the way the outflow at a non-destination node gets split among its outgoing links is allowed to depend only on local information about the current particle densities on the outgoing links. The strong resilience of the network is defined as the infimum sum of link-wise flow capacity reductions making the asymptotic total inflow to the destination node strictly less than the total outflow at the origin. A class of distributed routing policies that are responsive to local information is shown to yield the maximum possible strong resilience under such local information constraints for an acyclic dynamical network with a single origin-destination pair. The maximal achievable strong resilience is shown to be equal to the minimum node residual capacity of the network. The latter depends on the limit flow of the unperturbed network and is defined as the minimum, among all the non-destination nodes, of the sum, over all the links outgoing from the node, of the differences between the maximum flow capacity and the limit flow of the unperturbed network. We propose a simple convex optimization problem to solve for equilibrium flows of the unperturbed network that minimize average delay subject to strong resilience guarantees, and discuss the use of tolls to induce such an equilibrium flow in traffic networks. Finally, we present illustrative simulations to discuss the connection between cascaded failures and the resilience properties of the network.",emilio frazzoli,Cascaded failures,2013.0,10.1109/TAC.2012.2209975,IEEE Transactions on Automatic Control,Como2013,False,,IEEE,Not available,"Robust Distributed Routing in Dynamical Networks–Part II: Strong Resilience, Equilibrium Selection and Cascaded Failures",ac3c0b5ab7aa157941d911dd44949469,https://ieeexplore.ieee.org/document/6248170/
2799,"Strong resilience properties of dynamical networks are analyzed for distributed routing policies. The latter are characterized by the property that the way the outflow at a non-destination node gets split among its outgoing links is allowed to depend only on local information about the current particle densities on the outgoing links. The strong resilience of the network is defined as the infimum sum of link-wise flow capacity reductions making the asymptotic total inflow to the destination node strictly less than the total outflow at the origin. A class of distributed routing policies that are responsive to local information is shown to yield the maximum possible strong resilience under such local information constraints for an acyclic dynamical network with a single origin-destination pair. The maximal achievable strong resilience is shown to be equal to the minimum node residual capacity of the network. The latter depends on the limit flow of the unperturbed network and is defined as the minimum, among all the non-destination nodes, of the sum, over all the links outgoing from the node, of the differences between the maximum flow capacity and the limit flow of the unperturbed network. We propose a simple convex optimization problem to solve for equilibrium flows of the unperturbed network that minimize average delay subject to strong resilience guarantees, and discuss the use of tolls to induce such an equilibrium flow in traffic networks. Finally, we present illustrative simulations to discuss the connection between cascaded failures and the resilience properties of the network.",emilio frazzoli,distributed routing policies,2013.0,10.1109/TAC.2012.2209975,IEEE Transactions on Automatic Control,Como2013,False,,IEEE,Not available,"Robust Distributed Routing in Dynamical Networks–Part II: Strong Resilience, Equilibrium Selection and Cascaded Failures",ac3c0b5ab7aa157941d911dd44949469,https://ieeexplore.ieee.org/document/6248170/
2800,"Strong resilience properties of dynamical networks are analyzed for distributed routing policies. The latter are characterized by the property that the way the outflow at a non-destination node gets split among its outgoing links is allowed to depend only on local information about the current particle densities on the outgoing links. The strong resilience of the network is defined as the infimum sum of link-wise flow capacity reductions making the asymptotic total inflow to the destination node strictly less than the total outflow at the origin. A class of distributed routing policies that are responsive to local information is shown to yield the maximum possible strong resilience under such local information constraints for an acyclic dynamical network with a single origin-destination pair. The maximal achievable strong resilience is shown to be equal to the minimum node residual capacity of the network. The latter depends on the limit flow of the unperturbed network and is defined as the minimum, among all the non-destination nodes, of the sum, over all the links outgoing from the node, of the differences between the maximum flow capacity and the limit flow of the unperturbed network. We propose a simple convex optimization problem to solve for equilibrium flows of the unperturbed network that minimize average delay subject to strong resilience guarantees, and discuss the use of tolls to induce such an equilibrium flow in traffic networks. Finally, we present illustrative simulations to discuss the connection between cascaded failures and the resilience properties of the network.",emilio frazzoli,dynamical networks,2013.0,10.1109/TAC.2012.2209975,IEEE Transactions on Automatic Control,Como2013,False,,IEEE,Not available,"Robust Distributed Routing in Dynamical Networks–Part II: Strong Resilience, Equilibrium Selection and Cascaded Failures",ac3c0b5ab7aa157941d911dd44949469,https://ieeexplore.ieee.org/document/6248170/
2801,"Strong resilience properties of dynamical networks are analyzed for distributed routing policies. The latter are characterized by the property that the way the outflow at a non-destination node gets split among its outgoing links is allowed to depend only on local information about the current particle densities on the outgoing links. The strong resilience of the network is defined as the infimum sum of link-wise flow capacity reductions making the asymptotic total inflow to the destination node strictly less than the total outflow at the origin. A class of distributed routing policies that are responsive to local information is shown to yield the maximum possible strong resilience under such local information constraints for an acyclic dynamical network with a single origin-destination pair. The maximal achievable strong resilience is shown to be equal to the minimum node residual capacity of the network. The latter depends on the limit flow of the unperturbed network and is defined as the minimum, among all the non-destination nodes, of the sum, over all the links outgoing from the node, of the differences between the maximum flow capacity and the limit flow of the unperturbed network. We propose a simple convex optimization problem to solve for equilibrium flows of the unperturbed network that minimize average delay subject to strong resilience guarantees, and discuss the use of tolls to induce such an equilibrium flow in traffic networks. Finally, we present illustrative simulations to discuss the connection between cascaded failures and the resilience properties of the network.",emilio frazzoli,price of anarchy,2013.0,10.1109/TAC.2012.2209975,IEEE Transactions on Automatic Control,Como2013,False,,IEEE,Not available,"Robust Distributed Routing in Dynamical Networks–Part II: Strong Resilience, Equilibrium Selection and Cascaded Failures",ac3c0b5ab7aa157941d911dd44949469,https://ieeexplore.ieee.org/document/6248170/
2802,"Strong resilience properties of dynamical networks are analyzed for distributed routing policies. The latter are characterized by the property that the way the outflow at a non-destination node gets split among its outgoing links is allowed to depend only on local information about the current particle densities on the outgoing links. The strong resilience of the network is defined as the infimum sum of link-wise flow capacity reductions making the asymptotic total inflow to the destination node strictly less than the total outflow at the origin. A class of distributed routing policies that are responsive to local information is shown to yield the maximum possible strong resilience under such local information constraints for an acyclic dynamical network with a single origin-destination pair. The maximal achievable strong resilience is shown to be equal to the minimum node residual capacity of the network. The latter depends on the limit flow of the unperturbed network and is defined as the minimum, among all the non-destination nodes, of the sum, over all the links outgoing from the node, of the differences between the maximum flow capacity and the limit flow of the unperturbed network. We propose a simple convex optimization problem to solve for equilibrium flows of the unperturbed network that minimize average delay subject to strong resilience guarantees, and discuss the use of tolls to induce such an equilibrium flow in traffic networks. Finally, we present illustrative simulations to discuss the connection between cascaded failures and the resilience properties of the network.",emilio frazzoli,strong resilience,2013.0,10.1109/TAC.2012.2209975,IEEE Transactions on Automatic Control,Como2013,False,,IEEE,Not available,"Robust Distributed Routing in Dynamical Networks–Part II: Strong Resilience, Equilibrium Selection and Cascaded Failures",ac3c0b5ab7aa157941d911dd44949469,https://ieeexplore.ieee.org/document/6248170/
2803,"This paper addresses a Bayesian game theoretic framework for determining the association rules that decide to which cell a given mobile user should associate in LTE two-tier Heterogeneous Networks (HetNets). Users are assumed to compete to maximize their throughput by picking the best locally serving cell with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a hierarchical game, in which the macro-cell BS is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We show by means of a Stackelberg formulation, how the operator, by dynamically choosing the offset about the state of the channel, can optimize its global utility while end-users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem. Numerical results validate the expectation from the theoretical analysis and illustrate the advantages of the proposed approach.",majed haddad,4G LTE macro-cell,2013.0,10.1109/ITC.2013.6662962,Proceedings of the 2013 25th International Teletraffic Congress (ITC),Haddad2013,False,,IEEE,Not available,A game theoretic approach for the association problem in two-tier HetNets,d46caffe3ae405272cbe29cd9d9bd085,https://ieeexplore.ieee.org/document/6662962/
2804,"This paper addresses a Bayesian game theoretic framework for determining the association rules that decide to which cell a given mobile user should associate in LTE two-tier Heterogeneous Networks (HetNets). Users are assumed to compete to maximize their throughput by picking the best locally serving cell with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a hierarchical game, in which the macro-cell BS is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We show by means of a Stackelberg formulation, how the operator, by dynamically choosing the offset about the state of the channel, can optimize its global utility while end-users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem. Numerical results validate the expectation from the theoretical analysis and illustrate the advantages of the proposed approach.",majed haddad,small-cells,2013.0,10.1109/ITC.2013.6662962,Proceedings of the 2013 25th International Teletraffic Congress (ITC),Haddad2013,False,,IEEE,Not available,A game theoretic approach for the association problem in two-tier HetNets,d46caffe3ae405272cbe29cd9d9bd085,https://ieeexplore.ieee.org/document/6662962/
2805,"This paper addresses a Bayesian game theoretic framework for determining the association rules that decide to which cell a given mobile user should associate in LTE two-tier Heterogeneous Networks (HetNets). Users are assumed to compete to maximize their throughput by picking the best locally serving cell with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a hierarchical game, in which the macro-cell BS is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We show by means of a Stackelberg formulation, how the operator, by dynamically choosing the offset about the state of the channel, can optimize its global utility while end-users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem. Numerical results validate the expectation from the theoretical analysis and illustrate the advantages of the proposed approach.",majed haddad,dynamic offset,2013.0,10.1109/ITC.2013.6662962,Proceedings of the 2013 25th International Teletraffic Congress (ITC),Haddad2013,False,,IEEE,Not available,A game theoretic approach for the association problem in two-tier HetNets,d46caffe3ae405272cbe29cd9d9bd085,https://ieeexplore.ieee.org/document/6662962/
2806,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2807,"This paper addresses a Bayesian game theoretic framework for determining the association rules that decide to which cell a given mobile user should associate in LTE two-tier Heterogeneous Networks (HetNets). Users are assumed to compete to maximize their throughput by picking the best locally serving cell with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a hierarchical game, in which the macro-cell BS is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We show by means of a Stackelberg formulation, how the operator, by dynamically choosing the offset about the state of the channel, can optimize its global utility while end-users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem. Numerical results validate the expectation from the theoretical analysis and illustrate the advantages of the proposed approach.",majed haddad,association problem,2013.0,10.1109/ITC.2013.6662962,Proceedings of the 2013 25th International Teletraffic Congress (ITC),Haddad2013,False,,IEEE,Not available,A game theoretic approach for the association problem in two-tier HetNets,d46caffe3ae405272cbe29cd9d9bd085,https://ieeexplore.ieee.org/document/6662962/
2808,"This paper addresses a Bayesian game theoretic framework for determining the association rules that decide to which cell a given mobile user should associate in LTE two-tier Heterogeneous Networks (HetNets). Users are assumed to compete to maximize their throughput by picking the best locally serving cell with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a hierarchical game, in which the macro-cell BS is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We show by means of a Stackelberg formulation, how the operator, by dynamically choosing the offset about the state of the channel, can optimize its global utility while end-users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem. Numerical results validate the expectation from the theoretical analysis and illustrate the advantages of the proposed approach.",majed haddad,channel state information,2013.0,10.1109/ITC.2013.6662962,Proceedings of the 2013 25th International Teletraffic Congress (ITC),Haddad2013,False,,IEEE,Not available,A game theoretic approach for the association problem in two-tier HetNets,d46caffe3ae405272cbe29cd9d9bd085,https://ieeexplore.ieee.org/document/6662962/
2809,"This paper addresses a Bayesian game theoretic framework for determining the association rules that decide to which cell a given mobile user should associate in LTE two-tier Heterogeneous Networks (HetNets). Users are assumed to compete to maximize their throughput by picking the best locally serving cell with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a hierarchical game, in which the macro-cell BS is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We show by means of a Stackelberg formulation, how the operator, by dynamically choosing the offset about the state of the channel, can optimize its global utility while end-users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem. Numerical results validate the expectation from the theoretical analysis and illustrate the advantages of the proposed approach.",majed haddad,game theory,2013.0,10.1109/ITC.2013.6662962,Proceedings of the 2013 25th International Teletraffic Congress (ITC),Haddad2013,False,,IEEE,Not available,A game theoretic approach for the association problem in two-tier HetNets,d46caffe3ae405272cbe29cd9d9bd085,https://ieeexplore.ieee.org/document/6662962/
2810,"This paper addresses a Bayesian game theoretic framework for determining the association rules that decide to which cell a given mobile user should associate in LTE two-tier Heterogeneous Networks (HetNets). Users are assumed to compete to maximize their throughput by picking the best locally serving cell with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a hierarchical game, in which the macro-cell BS is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We show by means of a Stackelberg formulation, how the operator, by dynamically choosing the offset about the state of the channel, can optimize its global utility while end-users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem. Numerical results validate the expectation from the theoretical analysis and illustrate the advantages of the proposed approach.",majed haddad,Bayes-Nash equilibrium,2013.0,10.1109/ITC.2013.6662962,Proceedings of the 2013 25th International Teletraffic Congress (ITC),Haddad2013,False,,IEEE,Not available,A game theoretic approach for the association problem in two-tier HetNets,d46caffe3ae405272cbe29cd9d9bd085,https://ieeexplore.ieee.org/document/6662962/
2811,"This paper addresses a Bayesian game theoretic framework for determining the association rules that decide to which cell a given mobile user should associate in LTE two-tier Heterogeneous Networks (HetNets). Users are assumed to compete to maximize their throughput by picking the best locally serving cell with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a hierarchical game, in which the macro-cell BS is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We show by means of a Stackelberg formulation, how the operator, by dynamically choosing the offset about the state of the channel, can optimize its global utility while end-users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem. Numerical results validate the expectation from the theoretical analysis and illustrate the advantages of the proposed approach.",majed haddad,Bayes-Stackelberg equilibrium,2013.0,10.1109/ITC.2013.6662962,Proceedings of the 2013 25th International Teletraffic Congress (ITC),Haddad2013,False,,IEEE,Not available,A game theoretic approach for the association problem in two-tier HetNets,d46caffe3ae405272cbe29cd9d9bd085,https://ieeexplore.ieee.org/document/6662962/
2812,"This paper addresses a Bayesian game theoretic framework for determining the association rules that decide to which cell a given mobile user should associate in LTE two-tier Heterogeneous Networks (HetNets). Users are assumed to compete to maximize their throughput by picking the best locally serving cell with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a hierarchical game, in which the macro-cell BS is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We show by means of a Stackelberg formulation, how the operator, by dynamically choosing the offset about the state of the channel, can optimize its global utility while end-users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem. Numerical results validate the expectation from the theoretical analysis and illustrate the advantages of the proposed approach.",majed haddad,price of anarchy,2013.0,10.1109/ITC.2013.6662962,Proceedings of the 2013 25th International Teletraffic Congress (ITC),Haddad2013,False,,IEEE,Not available,A game theoretic approach for the association problem in two-tier HetNets,d46caffe3ae405272cbe29cd9d9bd085,https://ieeexplore.ieee.org/document/6662962/
2813,"This paper addresses a Bayesian game theoretic framework for determining the association rules that decide to which cell a given mobile user should associate in LTE two-tier Heterogeneous Networks (HetNets). Users are assumed to compete to maximize their throughput by picking the best locally serving cell with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a hierarchical game, in which the macro-cell BS is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We show by means of a Stackelberg formulation, how the operator, by dynamically choosing the offset about the state of the channel, can optimize its global utility while end-users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem. Numerical results validate the expectation from the theoretical analysis and illustrate the advantages of the proposed approach.",piotr wiecek,4G LTE macro-cell,2013.0,10.1109/ITC.2013.6662962,Proceedings of the 2013 25th International Teletraffic Congress (ITC),Haddad2013,False,,IEEE,Not available,A game theoretic approach for the association problem in two-tier HetNets,d46caffe3ae405272cbe29cd9d9bd085,https://ieeexplore.ieee.org/document/6662962/
2814,"This paper addresses a Bayesian game theoretic framework for determining the association rules that decide to which cell a given mobile user should associate in LTE two-tier Heterogeneous Networks (HetNets). Users are assumed to compete to maximize their throughput by picking the best locally serving cell with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a hierarchical game, in which the macro-cell BS is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We show by means of a Stackelberg formulation, how the operator, by dynamically choosing the offset about the state of the channel, can optimize its global utility while end-users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem. Numerical results validate the expectation from the theoretical analysis and illustrate the advantages of the proposed approach.",piotr wiecek,small-cells,2013.0,10.1109/ITC.2013.6662962,Proceedings of the 2013 25th International Teletraffic Congress (ITC),Haddad2013,False,,IEEE,Not available,A game theoretic approach for the association problem in two-tier HetNets,d46caffe3ae405272cbe29cd9d9bd085,https://ieeexplore.ieee.org/document/6662962/
2815,"This paper addresses a Bayesian game theoretic framework for determining the association rules that decide to which cell a given mobile user should associate in LTE two-tier Heterogeneous Networks (HetNets). Users are assumed to compete to maximize their throughput by picking the best locally serving cell with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a hierarchical game, in which the macro-cell BS is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We show by means of a Stackelberg formulation, how the operator, by dynamically choosing the offset about the state of the channel, can optimize its global utility while end-users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem. Numerical results validate the expectation from the theoretical analysis and illustrate the advantages of the proposed approach.",piotr wiecek,dynamic offset,2013.0,10.1109/ITC.2013.6662962,Proceedings of the 2013 25th International Teletraffic Congress (ITC),Haddad2013,False,,IEEE,Not available,A game theoretic approach for the association problem in two-tier HetNets,d46caffe3ae405272cbe29cd9d9bd085,https://ieeexplore.ieee.org/document/6662962/
2816,"This paper addresses a Bayesian game theoretic framework for determining the association rules that decide to which cell a given mobile user should associate in LTE two-tier Heterogeneous Networks (HetNets). Users are assumed to compete to maximize their throughput by picking the best locally serving cell with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a hierarchical game, in which the macro-cell BS is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We show by means of a Stackelberg formulation, how the operator, by dynamically choosing the offset about the state of the channel, can optimize its global utility while end-users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem. Numerical results validate the expectation from the theoretical analysis and illustrate the advantages of the proposed approach.",piotr wiecek,association problem,2013.0,10.1109/ITC.2013.6662962,Proceedings of the 2013 25th International Teletraffic Congress (ITC),Haddad2013,False,,IEEE,Not available,A game theoretic approach for the association problem in two-tier HetNets,d46caffe3ae405272cbe29cd9d9bd085,https://ieeexplore.ieee.org/document/6662962/
2817,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2818,"This paper addresses a Bayesian game theoretic framework for determining the association rules that decide to which cell a given mobile user should associate in LTE two-tier Heterogeneous Networks (HetNets). Users are assumed to compete to maximize their throughput by picking the best locally serving cell with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a hierarchical game, in which the macro-cell BS is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We show by means of a Stackelberg formulation, how the operator, by dynamically choosing the offset about the state of the channel, can optimize its global utility while end-users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem. Numerical results validate the expectation from the theoretical analysis and illustrate the advantages of the proposed approach.",piotr wiecek,channel state information,2013.0,10.1109/ITC.2013.6662962,Proceedings of the 2013 25th International Teletraffic Congress (ITC),Haddad2013,False,,IEEE,Not available,A game theoretic approach for the association problem in two-tier HetNets,d46caffe3ae405272cbe29cd9d9bd085,https://ieeexplore.ieee.org/document/6662962/
2819,"This paper addresses a Bayesian game theoretic framework for determining the association rules that decide to which cell a given mobile user should associate in LTE two-tier Heterogeneous Networks (HetNets). Users are assumed to compete to maximize their throughput by picking the best locally serving cell with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a hierarchical game, in which the macro-cell BS is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We show by means of a Stackelberg formulation, how the operator, by dynamically choosing the offset about the state of the channel, can optimize its global utility while end-users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem. Numerical results validate the expectation from the theoretical analysis and illustrate the advantages of the proposed approach.",piotr wiecek,game theory,2013.0,10.1109/ITC.2013.6662962,Proceedings of the 2013 25th International Teletraffic Congress (ITC),Haddad2013,False,,IEEE,Not available,A game theoretic approach for the association problem in two-tier HetNets,d46caffe3ae405272cbe29cd9d9bd085,https://ieeexplore.ieee.org/document/6662962/
2820,"This paper addresses a Bayesian game theoretic framework for determining the association rules that decide to which cell a given mobile user should associate in LTE two-tier Heterogeneous Networks (HetNets). Users are assumed to compete to maximize their throughput by picking the best locally serving cell with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a hierarchical game, in which the macro-cell BS is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We show by means of a Stackelberg formulation, how the operator, by dynamically choosing the offset about the state of the channel, can optimize its global utility while end-users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem. Numerical results validate the expectation from the theoretical analysis and illustrate the advantages of the proposed approach.",piotr wiecek,Bayes-Nash equilibrium,2013.0,10.1109/ITC.2013.6662962,Proceedings of the 2013 25th International Teletraffic Congress (ITC),Haddad2013,False,,IEEE,Not available,A game theoretic approach for the association problem in two-tier HetNets,d46caffe3ae405272cbe29cd9d9bd085,https://ieeexplore.ieee.org/document/6662962/
2821,"This paper addresses a Bayesian game theoretic framework for determining the association rules that decide to which cell a given mobile user should associate in LTE two-tier Heterogeneous Networks (HetNets). Users are assumed to compete to maximize their throughput by picking the best locally serving cell with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a hierarchical game, in which the macro-cell BS is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We show by means of a Stackelberg formulation, how the operator, by dynamically choosing the offset about the state of the channel, can optimize its global utility while end-users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem. Numerical results validate the expectation from the theoretical analysis and illustrate the advantages of the proposed approach.",piotr wiecek,Bayes-Stackelberg equilibrium,2013.0,10.1109/ITC.2013.6662962,Proceedings of the 2013 25th International Teletraffic Congress (ITC),Haddad2013,False,,IEEE,Not available,A game theoretic approach for the association problem in two-tier HetNets,d46caffe3ae405272cbe29cd9d9bd085,https://ieeexplore.ieee.org/document/6662962/
2822,"This paper addresses a Bayesian game theoretic framework for determining the association rules that decide to which cell a given mobile user should associate in LTE two-tier Heterogeneous Networks (HetNets). Users are assumed to compete to maximize their throughput by picking the best locally serving cell with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a hierarchical game, in which the macro-cell BS is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We show by means of a Stackelberg formulation, how the operator, by dynamically choosing the offset about the state of the channel, can optimize its global utility while end-users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem. Numerical results validate the expectation from the theoretical analysis and illustrate the advantages of the proposed approach.",piotr wiecek,price of anarchy,2013.0,10.1109/ITC.2013.6662962,Proceedings of the 2013 25th International Teletraffic Congress (ITC),Haddad2013,False,,IEEE,Not available,A game theoretic approach for the association problem in two-tier HetNets,d46caffe3ae405272cbe29cd9d9bd085,https://ieeexplore.ieee.org/document/6662962/
2823,"This paper addresses a Bayesian game theoretic framework for determining the association rules that decide to which cell a given mobile user should associate in LTE two-tier Heterogeneous Networks (HetNets). Users are assumed to compete to maximize their throughput by picking the best locally serving cell with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a hierarchical game, in which the macro-cell BS is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We show by means of a Stackelberg formulation, how the operator, by dynamically choosing the offset about the state of the channel, can optimize its global utility while end-users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem. Numerical results validate the expectation from the theoretical analysis and illustrate the advantages of the proposed approach.",eitan altman,4G LTE macro-cell,2013.0,10.1109/ITC.2013.6662962,Proceedings of the 2013 25th International Teletraffic Congress (ITC),Haddad2013,False,,IEEE,Not available,A game theoretic approach for the association problem in two-tier HetNets,d46caffe3ae405272cbe29cd9d9bd085,https://ieeexplore.ieee.org/document/6662962/
2824,"This paper addresses a Bayesian game theoretic framework for determining the association rules that decide to which cell a given mobile user should associate in LTE two-tier Heterogeneous Networks (HetNets). Users are assumed to compete to maximize their throughput by picking the best locally serving cell with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a hierarchical game, in which the macro-cell BS is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We show by means of a Stackelberg formulation, how the operator, by dynamically choosing the offset about the state of the channel, can optimize its global utility while end-users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem. Numerical results validate the expectation from the theoretical analysis and illustrate the advantages of the proposed approach.",eitan altman,small-cells,2013.0,10.1109/ITC.2013.6662962,Proceedings of the 2013 25th International Teletraffic Congress (ITC),Haddad2013,False,,IEEE,Not available,A game theoretic approach for the association problem in two-tier HetNets,d46caffe3ae405272cbe29cd9d9bd085,https://ieeexplore.ieee.org/document/6662962/
2825,"This paper addresses a Bayesian game theoretic framework for determining the association rules that decide to which cell a given mobile user should associate in LTE two-tier Heterogeneous Networks (HetNets). Users are assumed to compete to maximize their throughput by picking the best locally serving cell with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a hierarchical game, in which the macro-cell BS is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We show by means of a Stackelberg formulation, how the operator, by dynamically choosing the offset about the state of the channel, can optimize its global utility while end-users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem. Numerical results validate the expectation from the theoretical analysis and illustrate the advantages of the proposed approach.",eitan altman,dynamic offset,2013.0,10.1109/ITC.2013.6662962,Proceedings of the 2013 25th International Teletraffic Congress (ITC),Haddad2013,False,,IEEE,Not available,A game theoretic approach for the association problem in two-tier HetNets,d46caffe3ae405272cbe29cd9d9bd085,https://ieeexplore.ieee.org/document/6662962/
2826,"This paper addresses a Bayesian game theoretic framework for determining the association rules that decide to which cell a given mobile user should associate in LTE two-tier Heterogeneous Networks (HetNets). Users are assumed to compete to maximize their throughput by picking the best locally serving cell with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a hierarchical game, in which the macro-cell BS is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We show by means of a Stackelberg formulation, how the operator, by dynamically choosing the offset about the state of the channel, can optimize its global utility while end-users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem. Numerical results validate the expectation from the theoretical analysis and illustrate the advantages of the proposed approach.",eitan altman,association problem,2013.0,10.1109/ITC.2013.6662962,Proceedings of the 2013 25th International Teletraffic Congress (ITC),Haddad2013,False,,IEEE,Not available,A game theoretic approach for the association problem in two-tier HetNets,d46caffe3ae405272cbe29cd9d9bd085,https://ieeexplore.ieee.org/document/6662962/
2827,"This paper addresses a Bayesian game theoretic framework for determining the association rules that decide to which cell a given mobile user should associate in LTE two-tier Heterogeneous Networks (HetNets). Users are assumed to compete to maximize their throughput by picking the best locally serving cell with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a hierarchical game, in which the macro-cell BS is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We show by means of a Stackelberg formulation, how the operator, by dynamically choosing the offset about the state of the channel, can optimize its global utility while end-users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem. Numerical results validate the expectation from the theoretical analysis and illustrate the advantages of the proposed approach.",eitan altman,channel state information,2013.0,10.1109/ITC.2013.6662962,Proceedings of the 2013 25th International Teletraffic Congress (ITC),Haddad2013,False,,IEEE,Not available,A game theoretic approach for the association problem in two-tier HetNets,d46caffe3ae405272cbe29cd9d9bd085,https://ieeexplore.ieee.org/document/6662962/
2828,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2829,"This paper addresses a Bayesian game theoretic framework for determining the association rules that decide to which cell a given mobile user should associate in LTE two-tier Heterogeneous Networks (HetNets). Users are assumed to compete to maximize their throughput by picking the best locally serving cell with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a hierarchical game, in which the macro-cell BS is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We show by means of a Stackelberg formulation, how the operator, by dynamically choosing the offset about the state of the channel, can optimize its global utility while end-users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem. Numerical results validate the expectation from the theoretical analysis and illustrate the advantages of the proposed approach.",eitan altman,game theory,2013.0,10.1109/ITC.2013.6662962,Proceedings of the 2013 25th International Teletraffic Congress (ITC),Haddad2013,False,,IEEE,Not available,A game theoretic approach for the association problem in two-tier HetNets,d46caffe3ae405272cbe29cd9d9bd085,https://ieeexplore.ieee.org/document/6662962/
2830,"This paper addresses a Bayesian game theoretic framework for determining the association rules that decide to which cell a given mobile user should associate in LTE two-tier Heterogeneous Networks (HetNets). Users are assumed to compete to maximize their throughput by picking the best locally serving cell with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a hierarchical game, in which the macro-cell BS is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We show by means of a Stackelberg formulation, how the operator, by dynamically choosing the offset about the state of the channel, can optimize its global utility while end-users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem. Numerical results validate the expectation from the theoretical analysis and illustrate the advantages of the proposed approach.",eitan altman,Bayes-Nash equilibrium,2013.0,10.1109/ITC.2013.6662962,Proceedings of the 2013 25th International Teletraffic Congress (ITC),Haddad2013,False,,IEEE,Not available,A game theoretic approach for the association problem in two-tier HetNets,d46caffe3ae405272cbe29cd9d9bd085,https://ieeexplore.ieee.org/document/6662962/
2831,"This paper addresses a Bayesian game theoretic framework for determining the association rules that decide to which cell a given mobile user should associate in LTE two-tier Heterogeneous Networks (HetNets). Users are assumed to compete to maximize their throughput by picking the best locally serving cell with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a hierarchical game, in which the macro-cell BS is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We show by means of a Stackelberg formulation, how the operator, by dynamically choosing the offset about the state of the channel, can optimize its global utility while end-users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem. Numerical results validate the expectation from the theoretical analysis and illustrate the advantages of the proposed approach.",eitan altman,Bayes-Stackelberg equilibrium,2013.0,10.1109/ITC.2013.6662962,Proceedings of the 2013 25th International Teletraffic Congress (ITC),Haddad2013,False,,IEEE,Not available,A game theoretic approach for the association problem in two-tier HetNets,d46caffe3ae405272cbe29cd9d9bd085,https://ieeexplore.ieee.org/document/6662962/
2832,"This paper addresses a Bayesian game theoretic framework for determining the association rules that decide to which cell a given mobile user should associate in LTE two-tier Heterogeneous Networks (HetNets). Users are assumed to compete to maximize their throughput by picking the best locally serving cell with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a hierarchical game, in which the macro-cell BS is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We show by means of a Stackelberg formulation, how the operator, by dynamically choosing the offset about the state of the channel, can optimize its global utility while end-users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem. Numerical results validate the expectation from the theoretical analysis and illustrate the advantages of the proposed approach.",eitan altman,price of anarchy,2013.0,10.1109/ITC.2013.6662962,Proceedings of the 2013 25th International Teletraffic Congress (ITC),Haddad2013,False,,IEEE,Not available,A game theoretic approach for the association problem in two-tier HetNets,d46caffe3ae405272cbe29cd9d9bd085,https://ieeexplore.ieee.org/document/6662962/
2833,"This paper addresses a Bayesian game theoretic framework for determining the association rules that decide to which cell a given mobile user should associate in LTE two-tier Heterogeneous Networks (HetNets). Users are assumed to compete to maximize their throughput by picking the best locally serving cell with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a hierarchical game, in which the macro-cell BS is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We show by means of a Stackelberg formulation, how the operator, by dynamically choosing the offset about the state of the channel, can optimize its global utility while end-users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem. Numerical results validate the expectation from the theoretical analysis and illustrate the advantages of the proposed approach.",habib sidi,4G LTE macro-cell,2013.0,10.1109/ITC.2013.6662962,Proceedings of the 2013 25th International Teletraffic Congress (ITC),Haddad2013,False,,IEEE,Not available,A game theoretic approach for the association problem in two-tier HetNets,d46caffe3ae405272cbe29cd9d9bd085,https://ieeexplore.ieee.org/document/6662962/
2834,"This paper addresses a Bayesian game theoretic framework for determining the association rules that decide to which cell a given mobile user should associate in LTE two-tier Heterogeneous Networks (HetNets). Users are assumed to compete to maximize their throughput by picking the best locally serving cell with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a hierarchical game, in which the macro-cell BS is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We show by means of a Stackelberg formulation, how the operator, by dynamically choosing the offset about the state of the channel, can optimize its global utility while end-users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem. Numerical results validate the expectation from the theoretical analysis and illustrate the advantages of the proposed approach.",habib sidi,small-cells,2013.0,10.1109/ITC.2013.6662962,Proceedings of the 2013 25th International Teletraffic Congress (ITC),Haddad2013,False,,IEEE,Not available,A game theoretic approach for the association problem in two-tier HetNets,d46caffe3ae405272cbe29cd9d9bd085,https://ieeexplore.ieee.org/document/6662962/
2835,"This paper addresses a Bayesian game theoretic framework for determining the association rules that decide to which cell a given mobile user should associate in LTE two-tier Heterogeneous Networks (HetNets). Users are assumed to compete to maximize their throughput by picking the best locally serving cell with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a hierarchical game, in which the macro-cell BS is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We show by means of a Stackelberg formulation, how the operator, by dynamically choosing the offset about the state of the channel, can optimize its global utility while end-users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem. Numerical results validate the expectation from the theoretical analysis and illustrate the advantages of the proposed approach.",habib sidi,dynamic offset,2013.0,10.1109/ITC.2013.6662962,Proceedings of the 2013 25th International Teletraffic Congress (ITC),Haddad2013,False,,IEEE,Not available,A game theoretic approach for the association problem in two-tier HetNets,d46caffe3ae405272cbe29cd9d9bd085,https://ieeexplore.ieee.org/document/6662962/
2836,"This paper addresses a Bayesian game theoretic framework for determining the association rules that decide to which cell a given mobile user should associate in LTE two-tier Heterogeneous Networks (HetNets). Users are assumed to compete to maximize their throughput by picking the best locally serving cell with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a hierarchical game, in which the macro-cell BS is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We show by means of a Stackelberg formulation, how the operator, by dynamically choosing the offset about the state of the channel, can optimize its global utility while end-users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem. Numerical results validate the expectation from the theoretical analysis and illustrate the advantages of the proposed approach.",habib sidi,association problem,2013.0,10.1109/ITC.2013.6662962,Proceedings of the 2013 25th International Teletraffic Congress (ITC),Haddad2013,False,,IEEE,Not available,A game theoretic approach for the association problem in two-tier HetNets,d46caffe3ae405272cbe29cd9d9bd085,https://ieeexplore.ieee.org/document/6662962/
2837,"This paper addresses a Bayesian game theoretic framework for determining the association rules that decide to which cell a given mobile user should associate in LTE two-tier Heterogeneous Networks (HetNets). Users are assumed to compete to maximize their throughput by picking the best locally serving cell with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a hierarchical game, in which the macro-cell BS is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We show by means of a Stackelberg formulation, how the operator, by dynamically choosing the offset about the state of the channel, can optimize its global utility while end-users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem. Numerical results validate the expectation from the theoretical analysis and illustrate the advantages of the proposed approach.",habib sidi,channel state information,2013.0,10.1109/ITC.2013.6662962,Proceedings of the 2013 25th International Teletraffic Congress (ITC),Haddad2013,False,,IEEE,Not available,A game theoretic approach for the association problem in two-tier HetNets,d46caffe3ae405272cbe29cd9d9bd085,https://ieeexplore.ieee.org/document/6662962/
2838,"This paper addresses a Bayesian game theoretic framework for determining the association rules that decide to which cell a given mobile user should associate in LTE two-tier Heterogeneous Networks (HetNets). Users are assumed to compete to maximize their throughput by picking the best locally serving cell with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a hierarchical game, in which the macro-cell BS is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We show by means of a Stackelberg formulation, how the operator, by dynamically choosing the offset about the state of the channel, can optimize its global utility while end-users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem. Numerical results validate the expectation from the theoretical analysis and illustrate the advantages of the proposed approach.",habib sidi,game theory,2013.0,10.1109/ITC.2013.6662962,Proceedings of the 2013 25th International Teletraffic Congress (ITC),Haddad2013,False,,IEEE,Not available,A game theoretic approach for the association problem in two-tier HetNets,d46caffe3ae405272cbe29cd9d9bd085,https://ieeexplore.ieee.org/document/6662962/
2839,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2840,"This paper addresses a Bayesian game theoretic framework for determining the association rules that decide to which cell a given mobile user should associate in LTE two-tier Heterogeneous Networks (HetNets). Users are assumed to compete to maximize their throughput by picking the best locally serving cell with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a hierarchical game, in which the macro-cell BS is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We show by means of a Stackelberg formulation, how the operator, by dynamically choosing the offset about the state of the channel, can optimize its global utility while end-users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem. Numerical results validate the expectation from the theoretical analysis and illustrate the advantages of the proposed approach.",habib sidi,Bayes-Nash equilibrium,2013.0,10.1109/ITC.2013.6662962,Proceedings of the 2013 25th International Teletraffic Congress (ITC),Haddad2013,False,,IEEE,Not available,A game theoretic approach for the association problem in two-tier HetNets,d46caffe3ae405272cbe29cd9d9bd085,https://ieeexplore.ieee.org/document/6662962/
2841,"This paper addresses a Bayesian game theoretic framework for determining the association rules that decide to which cell a given mobile user should associate in LTE two-tier Heterogeneous Networks (HetNets). Users are assumed to compete to maximize their throughput by picking the best locally serving cell with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a hierarchical game, in which the macro-cell BS is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We show by means of a Stackelberg formulation, how the operator, by dynamically choosing the offset about the state of the channel, can optimize its global utility while end-users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem. Numerical results validate the expectation from the theoretical analysis and illustrate the advantages of the proposed approach.",habib sidi,Bayes-Stackelberg equilibrium,2013.0,10.1109/ITC.2013.6662962,Proceedings of the 2013 25th International Teletraffic Congress (ITC),Haddad2013,False,,IEEE,Not available,A game theoretic approach for the association problem in two-tier HetNets,d46caffe3ae405272cbe29cd9d9bd085,https://ieeexplore.ieee.org/document/6662962/
2842,"This paper addresses a Bayesian game theoretic framework for determining the association rules that decide to which cell a given mobile user should associate in LTE two-tier Heterogeneous Networks (HetNets). Users are assumed to compete to maximize their throughput by picking the best locally serving cell with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a hierarchical game, in which the macro-cell BS is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We show by means of a Stackelberg formulation, how the operator, by dynamically choosing the offset about the state of the channel, can optimize its global utility while end-users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem. Numerical results validate the expectation from the theoretical analysis and illustrate the advantages of the proposed approach.",habib sidi,price of anarchy,2013.0,10.1109/ITC.2013.6662962,Proceedings of the 2013 25th International Teletraffic Congress (ITC),Haddad2013,False,,IEEE,Not available,A game theoretic approach for the association problem in two-tier HetNets,d46caffe3ae405272cbe29cd9d9bd085,https://ieeexplore.ieee.org/document/6662962/
2843,"We consider the problem of two wireless networks operating on the same (presumably unlicensed) frequency band. Pairs within a given network cooperate to schedule transmissions, but between networks there is competition for spectrum. To make the problem tractable, we assume transmissions are scheduled according to a random access protocol where each network chooses an access probability for its users. A game between the two networks is defined. We characterize the Nash Equilibrium behavior of the system. Three regimes are identified: one in which both networks simultaneously schedule all transmissions, one in which the denser network schedules all transmissions and the sparser only schedules a fraction, and one in which both networks schedule only a fraction of their transmissions. The regime of operation depends on the path loss exponent α, the latter regime being desirable but attainable only for α &gt; 4. This suggests that in certain environments, rival wireless networks may end up naturally cooperating. To substantiate our analytical results, we simulate a system where networks iteratively optimize their access probabilities in a greedy manner. We also discuss a distributed scheduling protocol that employs carrier sensing and demonstrate via simulations that again a near cooperative equilibrium exists for sufficiently large α.",leonard grokop,Carrier sensing,2010.0,10.1109/TNET.2010.2043114,IEEE/ACM Transactions on Networking,Grokop2010,False,,IEEE,Not available,Spectrum Sharing Between Wireless Networks,9f9a1356ed57958a943ca23254cbacf4,https://ieeexplore.ieee.org/document/5422705/
2844,"We consider the problem of two wireless networks operating on the same (presumably unlicensed) frequency band. Pairs within a given network cooperate to schedule transmissions, but between networks there is competition for spectrum. To make the problem tractable, we assume transmissions are scheduled according to a random access protocol where each network chooses an access probability for its users. A game between the two networks is defined. We characterize the Nash Equilibrium behavior of the system. Three regimes are identified: one in which both networks simultaneously schedule all transmissions, one in which the denser network schedules all transmissions and the sparser only schedules a fraction, and one in which both networks schedule only a fraction of their transmissions. The regime of operation depends on the path loss exponent α, the latter regime being desirable but attainable only for α &gt; 4. This suggests that in certain environments, rival wireless networks may end up naturally cooperating. To substantiate our analytical results, we simulate a system where networks iteratively optimize their access probabilities in a greedy manner. We also discuss a distributed scheduling protocol that employs carrier sensing and demonstrate via simulations that again a near cooperative equilibrium exists for sufficiently large α.",leonard grokop,game theory,2010.0,10.1109/TNET.2010.2043114,IEEE/ACM Transactions on Networking,Grokop2010,False,,IEEE,Not available,Spectrum Sharing Between Wireless Networks,9f9a1356ed57958a943ca23254cbacf4,https://ieeexplore.ieee.org/document/5422705/
2845,"We consider the problem of two wireless networks operating on the same (presumably unlicensed) frequency band. Pairs within a given network cooperate to schedule transmissions, but between networks there is competition for spectrum. To make the problem tractable, we assume transmissions are scheduled according to a random access protocol where each network chooses an access probability for its users. A game between the two networks is defined. We characterize the Nash Equilibrium behavior of the system. Three regimes are identified: one in which both networks simultaneously schedule all transmissions, one in which the denser network schedules all transmissions and the sparser only schedules a fraction, and one in which both networks schedule only a fraction of their transmissions. The regime of operation depends on the path loss exponent α, the latter regime being desirable but attainable only for α &gt; 4. This suggests that in certain environments, rival wireless networks may end up naturally cooperating. To substantiate our analytical results, we simulate a system where networks iteratively optimize their access probabilities in a greedy manner. We also discuss a distributed scheduling protocol that employs carrier sensing and demonstrate via simulations that again a near cooperative equilibrium exists for sufficiently large α.",leonard grokop,Nash equilibrium (N.E.),2010.0,10.1109/TNET.2010.2043114,IEEE/ACM Transactions on Networking,Grokop2010,False,,IEEE,Not available,Spectrum Sharing Between Wireless Networks,9f9a1356ed57958a943ca23254cbacf4,https://ieeexplore.ieee.org/document/5422705/
2846,"We consider the problem of two wireless networks operating on the same (presumably unlicensed) frequency band. Pairs within a given network cooperate to schedule transmissions, but between networks there is competition for spectrum. To make the problem tractable, we assume transmissions are scheduled according to a random access protocol where each network chooses an access probability for its users. A game between the two networks is defined. We characterize the Nash Equilibrium behavior of the system. Three regimes are identified: one in which both networks simultaneously schedule all transmissions, one in which the denser network schedules all transmissions and the sparser only schedules a fraction, and one in which both networks schedule only a fraction of their transmissions. The regime of operation depends on the path loss exponent α, the latter regime being desirable but attainable only for α &gt; 4. This suggests that in certain environments, rival wireless networks may end up naturally cooperating. To substantiate our analytical results, we simulate a system where networks iteratively optimize their access probabilities in a greedy manner. We also discuss a distributed scheduling protocol that employs carrier sensing and demonstrate via simulations that again a near cooperative equilibrium exists for sufficiently large α.",leonard grokop,price of anarchy,2010.0,10.1109/TNET.2010.2043114,IEEE/ACM Transactions on Networking,Grokop2010,False,,IEEE,Not available,Spectrum Sharing Between Wireless Networks,9f9a1356ed57958a943ca23254cbacf4,https://ieeexplore.ieee.org/document/5422705/
2847,"We consider the problem of two wireless networks operating on the same (presumably unlicensed) frequency band. Pairs within a given network cooperate to schedule transmissions, but between networks there is competition for spectrum. To make the problem tractable, we assume transmissions are scheduled according to a random access protocol where each network chooses an access probability for its users. A game between the two networks is defined. We characterize the Nash Equilibrium behavior of the system. Three regimes are identified: one in which both networks simultaneously schedule all transmissions, one in which the denser network schedules all transmissions and the sparser only schedules a fraction, and one in which both networks schedule only a fraction of their transmissions. The regime of operation depends on the path loss exponent α, the latter regime being desirable but attainable only for α &gt; 4. This suggests that in certain environments, rival wireless networks may end up naturally cooperating. To substantiate our analytical results, we simulate a system where networks iteratively optimize their access probabilities in a greedy manner. We also discuss a distributed scheduling protocol that employs carrier sensing and demonstrate via simulations that again a near cooperative equilibrium exists for sufficiently large α.",leonard grokop,random access,2010.0,10.1109/TNET.2010.2043114,IEEE/ACM Transactions on Networking,Grokop2010,False,,IEEE,Not available,Spectrum Sharing Between Wireless Networks,9f9a1356ed57958a943ca23254cbacf4,https://ieeexplore.ieee.org/document/5422705/
2848,"We consider the problem of two wireless networks operating on the same (presumably unlicensed) frequency band. Pairs within a given network cooperate to schedule transmissions, but between networks there is competition for spectrum. To make the problem tractable, we assume transmissions are scheduled according to a random access protocol where each network chooses an access probability for its users. A game between the two networks is defined. We characterize the Nash Equilibrium behavior of the system. Three regimes are identified: one in which both networks simultaneously schedule all transmissions, one in which the denser network schedules all transmissions and the sparser only schedules a fraction, and one in which both networks schedule only a fraction of their transmissions. The regime of operation depends on the path loss exponent α, the latter regime being desirable but attainable only for α &gt; 4. This suggests that in certain environments, rival wireless networks may end up naturally cooperating. To substantiate our analytical results, we simulate a system where networks iteratively optimize their access probabilities in a greedy manner. We also discuss a distributed scheduling protocol that employs carrier sensing and demonstrate via simulations that again a near cooperative equilibrium exists for sufficiently large α.",leonard grokop,spectrum sharing,2010.0,10.1109/TNET.2010.2043114,IEEE/ACM Transactions on Networking,Grokop2010,False,,IEEE,Not available,Spectrum Sharing Between Wireless Networks,9f9a1356ed57958a943ca23254cbacf4,https://ieeexplore.ieee.org/document/5422705/
2849,"We consider the problem of two wireless networks operating on the same (presumably unlicensed) frequency band. Pairs within a given network cooperate to schedule transmissions, but between networks there is competition for spectrum. To make the problem tractable, we assume transmissions are scheduled according to a random access protocol where each network chooses an access probability for its users. A game between the two networks is defined. We characterize the Nash Equilibrium behavior of the system. Three regimes are identified: one in which both networks simultaneously schedule all transmissions, one in which the denser network schedules all transmissions and the sparser only schedules a fraction, and one in which both networks schedule only a fraction of their transmissions. The regime of operation depends on the path loss exponent α, the latter regime being desirable but attainable only for α &gt; 4. This suggests that in certain environments, rival wireless networks may end up naturally cooperating. To substantiate our analytical results, we simulate a system where networks iteratively optimize their access probabilities in a greedy manner. We also discuss a distributed scheduling protocol that employs carrier sensing and demonstrate via simulations that again a near cooperative equilibrium exists for sufficiently large α.",leonard grokop,wireless ad hoc networks,2010.0,10.1109/TNET.2010.2043114,IEEE/ACM Transactions on Networking,Grokop2010,False,,IEEE,Not available,Spectrum Sharing Between Wireless Networks,9f9a1356ed57958a943ca23254cbacf4,https://ieeexplore.ieee.org/document/5422705/
2850,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
2851,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
2852,"We consider the problem of two wireless networks operating on the same (presumably unlicensed) frequency band. Pairs within a given network cooperate to schedule transmissions, but between networks there is competition for spectrum. To make the problem tractable, we assume transmissions are scheduled according to a random access protocol where each network chooses an access probability for its users. A game between the two networks is defined. We characterize the Nash Equilibrium behavior of the system. Three regimes are identified: one in which both networks simultaneously schedule all transmissions, one in which the denser network schedules all transmissions and the sparser only schedules a fraction, and one in which both networks schedule only a fraction of their transmissions. The regime of operation depends on the path loss exponent α, the latter regime being desirable but attainable only for α &gt; 4. This suggests that in certain environments, rival wireless networks may end up naturally cooperating. To substantiate our analytical results, we simulate a system where networks iteratively optimize their access probabilities in a greedy manner. We also discuss a distributed scheduling protocol that employs carrier sensing and demonstrate via simulations that again a near cooperative equilibrium exists for sufficiently large α.",david tse,Carrier sensing,2010.0,10.1109/TNET.2010.2043114,IEEE/ACM Transactions on Networking,Grokop2010,False,,IEEE,Not available,Spectrum Sharing Between Wireless Networks,9f9a1356ed57958a943ca23254cbacf4,https://ieeexplore.ieee.org/document/5422705/
2853,"We consider the problem of two wireless networks operating on the same (presumably unlicensed) frequency band. Pairs within a given network cooperate to schedule transmissions, but between networks there is competition for spectrum. To make the problem tractable, we assume transmissions are scheduled according to a random access protocol where each network chooses an access probability for its users. A game between the two networks is defined. We characterize the Nash Equilibrium behavior of the system. Three regimes are identified: one in which both networks simultaneously schedule all transmissions, one in which the denser network schedules all transmissions and the sparser only schedules a fraction, and one in which both networks schedule only a fraction of their transmissions. The regime of operation depends on the path loss exponent α, the latter regime being desirable but attainable only for α &gt; 4. This suggests that in certain environments, rival wireless networks may end up naturally cooperating. To substantiate our analytical results, we simulate a system where networks iteratively optimize their access probabilities in a greedy manner. We also discuss a distributed scheduling protocol that employs carrier sensing and demonstrate via simulations that again a near cooperative equilibrium exists for sufficiently large α.",david tse,game theory,2010.0,10.1109/TNET.2010.2043114,IEEE/ACM Transactions on Networking,Grokop2010,False,,IEEE,Not available,Spectrum Sharing Between Wireless Networks,9f9a1356ed57958a943ca23254cbacf4,https://ieeexplore.ieee.org/document/5422705/
2854,"We consider the problem of two wireless networks operating on the same (presumably unlicensed) frequency band. Pairs within a given network cooperate to schedule transmissions, but between networks there is competition for spectrum. To make the problem tractable, we assume transmissions are scheduled according to a random access protocol where each network chooses an access probability for its users. A game between the two networks is defined. We characterize the Nash Equilibrium behavior of the system. Three regimes are identified: one in which both networks simultaneously schedule all transmissions, one in which the denser network schedules all transmissions and the sparser only schedules a fraction, and one in which both networks schedule only a fraction of their transmissions. The regime of operation depends on the path loss exponent α, the latter regime being desirable but attainable only for α &gt; 4. This suggests that in certain environments, rival wireless networks may end up naturally cooperating. To substantiate our analytical results, we simulate a system where networks iteratively optimize their access probabilities in a greedy manner. We also discuss a distributed scheduling protocol that employs carrier sensing and demonstrate via simulations that again a near cooperative equilibrium exists for sufficiently large α.",david tse,Nash equilibrium (N.E.),2010.0,10.1109/TNET.2010.2043114,IEEE/ACM Transactions on Networking,Grokop2010,False,,IEEE,Not available,Spectrum Sharing Between Wireless Networks,9f9a1356ed57958a943ca23254cbacf4,https://ieeexplore.ieee.org/document/5422705/
2855,"We consider the problem of two wireless networks operating on the same (presumably unlicensed) frequency band. Pairs within a given network cooperate to schedule transmissions, but between networks there is competition for spectrum. To make the problem tractable, we assume transmissions are scheduled according to a random access protocol where each network chooses an access probability for its users. A game between the two networks is defined. We characterize the Nash Equilibrium behavior of the system. Three regimes are identified: one in which both networks simultaneously schedule all transmissions, one in which the denser network schedules all transmissions and the sparser only schedules a fraction, and one in which both networks schedule only a fraction of their transmissions. The regime of operation depends on the path loss exponent α, the latter regime being desirable but attainable only for α &gt; 4. This suggests that in certain environments, rival wireless networks may end up naturally cooperating. To substantiate our analytical results, we simulate a system where networks iteratively optimize their access probabilities in a greedy manner. We also discuss a distributed scheduling protocol that employs carrier sensing and demonstrate via simulations that again a near cooperative equilibrium exists for sufficiently large α.",david tse,price of anarchy,2010.0,10.1109/TNET.2010.2043114,IEEE/ACM Transactions on Networking,Grokop2010,False,,IEEE,Not available,Spectrum Sharing Between Wireless Networks,9f9a1356ed57958a943ca23254cbacf4,https://ieeexplore.ieee.org/document/5422705/
2856,"We consider the problem of two wireless networks operating on the same (presumably unlicensed) frequency band. Pairs within a given network cooperate to schedule transmissions, but between networks there is competition for spectrum. To make the problem tractable, we assume transmissions are scheduled according to a random access protocol where each network chooses an access probability for its users. A game between the two networks is defined. We characterize the Nash Equilibrium behavior of the system. Three regimes are identified: one in which both networks simultaneously schedule all transmissions, one in which the denser network schedules all transmissions and the sparser only schedules a fraction, and one in which both networks schedule only a fraction of their transmissions. The regime of operation depends on the path loss exponent α, the latter regime being desirable but attainable only for α &gt; 4. This suggests that in certain environments, rival wireless networks may end up naturally cooperating. To substantiate our analytical results, we simulate a system where networks iteratively optimize their access probabilities in a greedy manner. We also discuss a distributed scheduling protocol that employs carrier sensing and demonstrate via simulations that again a near cooperative equilibrium exists for sufficiently large α.",david tse,random access,2010.0,10.1109/TNET.2010.2043114,IEEE/ACM Transactions on Networking,Grokop2010,False,,IEEE,Not available,Spectrum Sharing Between Wireless Networks,9f9a1356ed57958a943ca23254cbacf4,https://ieeexplore.ieee.org/document/5422705/
2857,"We consider the problem of two wireless networks operating on the same (presumably unlicensed) frequency band. Pairs within a given network cooperate to schedule transmissions, but between networks there is competition for spectrum. To make the problem tractable, we assume transmissions are scheduled according to a random access protocol where each network chooses an access probability for its users. A game between the two networks is defined. We characterize the Nash Equilibrium behavior of the system. Three regimes are identified: one in which both networks simultaneously schedule all transmissions, one in which the denser network schedules all transmissions and the sparser only schedules a fraction, and one in which both networks schedule only a fraction of their transmissions. The regime of operation depends on the path loss exponent α, the latter regime being desirable but attainable only for α &gt; 4. This suggests that in certain environments, rival wireless networks may end up naturally cooperating. To substantiate our analytical results, we simulate a system where networks iteratively optimize their access probabilities in a greedy manner. We also discuss a distributed scheduling protocol that employs carrier sensing and demonstrate via simulations that again a near cooperative equilibrium exists for sufficiently large α.",david tse,spectrum sharing,2010.0,10.1109/TNET.2010.2043114,IEEE/ACM Transactions on Networking,Grokop2010,False,,IEEE,Not available,Spectrum Sharing Between Wireless Networks,9f9a1356ed57958a943ca23254cbacf4,https://ieeexplore.ieee.org/document/5422705/
2858,"We consider the problem of two wireless networks operating on the same (presumably unlicensed) frequency band. Pairs within a given network cooperate to schedule transmissions, but between networks there is competition for spectrum. To make the problem tractable, we assume transmissions are scheduled according to a random access protocol where each network chooses an access probability for its users. A game between the two networks is defined. We characterize the Nash Equilibrium behavior of the system. Three regimes are identified: one in which both networks simultaneously schedule all transmissions, one in which the denser network schedules all transmissions and the sparser only schedules a fraction, and one in which both networks schedule only a fraction of their transmissions. The regime of operation depends on the path loss exponent α, the latter regime being desirable but attainable only for α &gt; 4. This suggests that in certain environments, rival wireless networks may end up naturally cooperating. To substantiate our analytical results, we simulate a system where networks iteratively optimize their access probabilities in a greedy manner. We also discuss a distributed scheduling protocol that employs carrier sensing and demonstrate via simulations that again a near cooperative equilibrium exists for sufficiently large α.",david tse,wireless ad hoc networks,2010.0,10.1109/TNET.2010.2043114,IEEE/ACM Transactions on Networking,Grokop2010,False,,IEEE,Not available,Spectrum Sharing Between Wireless Networks,9f9a1356ed57958a943ca23254cbacf4,https://ieeexplore.ieee.org/document/5422705/
2859,"We consider a resource management problem in a multi-cell downlink OFDMA network whereby the goal is to find the optimal combination of (i) assignment of users to base stations and (ii) resource allocation strategies at each base station. Efficient resource management protocols must rely on users truthfully reporting privately held information such as downlink channel states. However, individual users can manipulate the resulting resource allocation (by misreporting their private information) if by doing so they can improve their payoff. Therefore, it is of interest to design efficient resource management protocols that are strategy-proof, i.e. it is in the users' best interests to truthfully report their private information. Unfortunately, we show that the implementation of any protocol that is efficient and strategy-proof is NP-hard. Thus, we propose a computationally tractable strategy-proof mechanism that is approximately efficient, i.e. the solution obtained yields at least 1/2 of the optimal throughput. Simulations are provided to illustrate the effectiveness of the proposed mechanism.",mingyi hong,Heterogenous Network,2012.0,10.1109/JSAC.2012.121216,IEEE Journal on Selected Areas in Communications,Hong2012,False,,IEEE,Not available,Mechanism Design for Base Station Association and Resource Allocation in Downlink OFDMA Network,7acbd14826500757d5f41e03fcc0c98e,https://ieeexplore.ieee.org/document/6354282/
2860,"We consider a resource management problem in a multi-cell downlink OFDMA network whereby the goal is to find the optimal combination of (i) assignment of users to base stations and (ii) resource allocation strategies at each base station. Efficient resource management protocols must rely on users truthfully reporting privately held information such as downlink channel states. However, individual users can manipulate the resulting resource allocation (by misreporting their private information) if by doing so they can improve their payoff. Therefore, it is of interest to design efficient resource management protocols that are strategy-proof, i.e. it is in the users' best interests to truthfully report their private information. Unfortunately, we show that the implementation of any protocol that is efficient and strategy-proof is NP-hard. Thus, we propose a computationally tractable strategy-proof mechanism that is approximately efficient, i.e. the solution obtained yields at least 1/2 of the optimal throughput. Simulations are provided to illustrate the effectiveness of the proposed mechanism.",mingyi hong,Mechanism Design,2012.0,10.1109/JSAC.2012.121216,IEEE Journal on Selected Areas in Communications,Hong2012,False,,IEEE,Not available,Mechanism Design for Base Station Association and Resource Allocation in Downlink OFDMA Network,7acbd14826500757d5f41e03fcc0c98e,https://ieeexplore.ieee.org/document/6354282/
2861,"We consider a resource management problem in a multi-cell downlink OFDMA network whereby the goal is to find the optimal combination of (i) assignment of users to base stations and (ii) resource allocation strategies at each base station. Efficient resource management protocols must rely on users truthfully reporting privately held information such as downlink channel states. However, individual users can manipulate the resulting resource allocation (by misreporting their private information) if by doing so they can improve their payoff. Therefore, it is of interest to design efficient resource management protocols that are strategy-proof, i.e. it is in the users' best interests to truthfully report their private information. Unfortunately, we show that the implementation of any protocol that is efficient and strategy-proof is NP-hard. Thus, we propose a computationally tractable strategy-proof mechanism that is approximately efficient, i.e. the solution obtained yields at least 1/2 of the optimal throughput. Simulations are provided to illustrate the effectiveness of the proposed mechanism.",mingyi hong,Resource Allocation,2012.0,10.1109/JSAC.2012.121216,IEEE Journal on Selected Areas in Communications,Hong2012,False,,IEEE,Not available,Mechanism Design for Base Station Association and Resource Allocation in Downlink OFDMA Network,7acbd14826500757d5f41e03fcc0c98e,https://ieeexplore.ieee.org/document/6354282/
2862,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
2863,"We consider a resource management problem in a multi-cell downlink OFDMA network whereby the goal is to find the optimal combination of (i) assignment of users to base stations and (ii) resource allocation strategies at each base station. Efficient resource management protocols must rely on users truthfully reporting privately held information such as downlink channel states. However, individual users can manipulate the resulting resource allocation (by misreporting their private information) if by doing so they can improve their payoff. Therefore, it is of interest to design efficient resource management protocols that are strategy-proof, i.e. it is in the users' best interests to truthfully report their private information. Unfortunately, we show that the implementation of any protocol that is efficient and strategy-proof is NP-hard. Thus, we propose a computationally tractable strategy-proof mechanism that is approximately efficient, i.e. the solution obtained yields at least 1/2 of the optimal throughput. Simulations are provided to illustrate the effectiveness of the proposed mechanism.",mingyi hong,Base Station Association,2012.0,10.1109/JSAC.2012.121216,IEEE Journal on Selected Areas in Communications,Hong2012,False,,IEEE,Not available,Mechanism Design for Base Station Association and Resource Allocation in Downlink OFDMA Network,7acbd14826500757d5f41e03fcc0c98e,https://ieeexplore.ieee.org/document/6354282/
2864,"We consider a resource management problem in a multi-cell downlink OFDMA network whereby the goal is to find the optimal combination of (i) assignment of users to base stations and (ii) resource allocation strategies at each base station. Efficient resource management protocols must rely on users truthfully reporting privately held information such as downlink channel states. However, individual users can manipulate the resulting resource allocation (by misreporting their private information) if by doing so they can improve their payoff. Therefore, it is of interest to design efficient resource management protocols that are strategy-proof, i.e. it is in the users' best interests to truthfully report their private information. Unfortunately, we show that the implementation of any protocol that is efficient and strategy-proof is NP-hard. Thus, we propose a computationally tractable strategy-proof mechanism that is approximately efficient, i.e. the solution obtained yields at least 1/2 of the optimal throughput. Simulations are provided to illustrate the effectiveness of the proposed mechanism.",mingyi hong,Approximation Bounds,2012.0,10.1109/JSAC.2012.121216,IEEE Journal on Selected Areas in Communications,Hong2012,False,,IEEE,Not available,Mechanism Design for Base Station Association and Resource Allocation in Downlink OFDMA Network,7acbd14826500757d5f41e03fcc0c98e,https://ieeexplore.ieee.org/document/6354282/
2865,"We consider a resource management problem in a multi-cell downlink OFDMA network whereby the goal is to find the optimal combination of (i) assignment of users to base stations and (ii) resource allocation strategies at each base station. Efficient resource management protocols must rely on users truthfully reporting privately held information such as downlink channel states. However, individual users can manipulate the resulting resource allocation (by misreporting their private information) if by doing so they can improve their payoff. Therefore, it is of interest to design efficient resource management protocols that are strategy-proof, i.e. it is in the users' best interests to truthfully report their private information. Unfortunately, we show that the implementation of any protocol that is efficient and strategy-proof is NP-hard. Thus, we propose a computationally tractable strategy-proof mechanism that is approximately efficient, i.e. the solution obtained yields at least 1/2 of the optimal throughput. Simulations are provided to illustrate the effectiveness of the proposed mechanism.",mingyi hong,Computational Complexity,2012.0,10.1109/JSAC.2012.121216,IEEE Journal on Selected Areas in Communications,Hong2012,False,,IEEE,Not available,Mechanism Design for Base Station Association and Resource Allocation in Downlink OFDMA Network,7acbd14826500757d5f41e03fcc0c98e,https://ieeexplore.ieee.org/document/6354282/
2866,"We consider a resource management problem in a multi-cell downlink OFDMA network whereby the goal is to find the optimal combination of (i) assignment of users to base stations and (ii) resource allocation strategies at each base station. Efficient resource management protocols must rely on users truthfully reporting privately held information such as downlink channel states. However, individual users can manipulate the resulting resource allocation (by misreporting their private information) if by doing so they can improve their payoff. Therefore, it is of interest to design efficient resource management protocols that are strategy-proof, i.e. it is in the users' best interests to truthfully report their private information. Unfortunately, we show that the implementation of any protocol that is efficient and strategy-proof is NP-hard. Thus, we propose a computationally tractable strategy-proof mechanism that is approximately efficient, i.e. the solution obtained yields at least 1/2 of the optimal throughput. Simulations are provided to illustrate the effectiveness of the proposed mechanism.",mingyi hong,Nash Equilibrium,2012.0,10.1109/JSAC.2012.121216,IEEE Journal on Selected Areas in Communications,Hong2012,False,,IEEE,Not available,Mechanism Design for Base Station Association and Resource Allocation in Downlink OFDMA Network,7acbd14826500757d5f41e03fcc0c98e,https://ieeexplore.ieee.org/document/6354282/
2867,"We consider a resource management problem in a multi-cell downlink OFDMA network whereby the goal is to find the optimal combination of (i) assignment of users to base stations and (ii) resource allocation strategies at each base station. Efficient resource management protocols must rely on users truthfully reporting privately held information such as downlink channel states. However, individual users can manipulate the resulting resource allocation (by misreporting their private information) if by doing so they can improve their payoff. Therefore, it is of interest to design efficient resource management protocols that are strategy-proof, i.e. it is in the users' best interests to truthfully report their private information. Unfortunately, we show that the implementation of any protocol that is efficient and strategy-proof is NP-hard. Thus, we propose a computationally tractable strategy-proof mechanism that is approximately efficient, i.e. the solution obtained yields at least 1/2 of the optimal throughput. Simulations are provided to illustrate the effectiveness of the proposed mechanism.",mingyi hong,Price of Anarchy,2012.0,10.1109/JSAC.2012.121216,IEEE Journal on Selected Areas in Communications,Hong2012,False,,IEEE,Not available,Mechanism Design for Base Station Association and Resource Allocation in Downlink OFDMA Network,7acbd14826500757d5f41e03fcc0c98e,https://ieeexplore.ieee.org/document/6354282/
2868,"We consider a resource management problem in a multi-cell downlink OFDMA network whereby the goal is to find the optimal combination of (i) assignment of users to base stations and (ii) resource allocation strategies at each base station. Efficient resource management protocols must rely on users truthfully reporting privately held information such as downlink channel states. However, individual users can manipulate the resulting resource allocation (by misreporting their private information) if by doing so they can improve their payoff. Therefore, it is of interest to design efficient resource management protocols that are strategy-proof, i.e. it is in the users' best interests to truthfully report their private information. Unfortunately, we show that the implementation of any protocol that is efficient and strategy-proof is NP-hard. Thus, we propose a computationally tractable strategy-proof mechanism that is approximately efficient, i.e. the solution obtained yields at least 1/2 of the optimal throughput. Simulations are provided to illustrate the effectiveness of the proposed mechanism.",alfredo garcia,Heterogenous Network,2012.0,10.1109/JSAC.2012.121216,IEEE Journal on Selected Areas in Communications,Hong2012,False,,IEEE,Not available,Mechanism Design for Base Station Association and Resource Allocation in Downlink OFDMA Network,7acbd14826500757d5f41e03fcc0c98e,https://ieeexplore.ieee.org/document/6354282/
2869,"We consider a resource management problem in a multi-cell downlink OFDMA network whereby the goal is to find the optimal combination of (i) assignment of users to base stations and (ii) resource allocation strategies at each base station. Efficient resource management protocols must rely on users truthfully reporting privately held information such as downlink channel states. However, individual users can manipulate the resulting resource allocation (by misreporting their private information) if by doing so they can improve their payoff. Therefore, it is of interest to design efficient resource management protocols that are strategy-proof, i.e. it is in the users' best interests to truthfully report their private information. Unfortunately, we show that the implementation of any protocol that is efficient and strategy-proof is NP-hard. Thus, we propose a computationally tractable strategy-proof mechanism that is approximately efficient, i.e. the solution obtained yields at least 1/2 of the optimal throughput. Simulations are provided to illustrate the effectiveness of the proposed mechanism.",alfredo garcia,Mechanism Design,2012.0,10.1109/JSAC.2012.121216,IEEE Journal on Selected Areas in Communications,Hong2012,False,,IEEE,Not available,Mechanism Design for Base Station Association and Resource Allocation in Downlink OFDMA Network,7acbd14826500757d5f41e03fcc0c98e,https://ieeexplore.ieee.org/document/6354282/
2870,"We consider a resource management problem in a multi-cell downlink OFDMA network whereby the goal is to find the optimal combination of (i) assignment of users to base stations and (ii) resource allocation strategies at each base station. Efficient resource management protocols must rely on users truthfully reporting privately held information such as downlink channel states. However, individual users can manipulate the resulting resource allocation (by misreporting their private information) if by doing so they can improve their payoff. Therefore, it is of interest to design efficient resource management protocols that are strategy-proof, i.e. it is in the users' best interests to truthfully report their private information. Unfortunately, we show that the implementation of any protocol that is efficient and strategy-proof is NP-hard. Thus, we propose a computationally tractable strategy-proof mechanism that is approximately efficient, i.e. the solution obtained yields at least 1/2 of the optimal throughput. Simulations are provided to illustrate the effectiveness of the proposed mechanism.",alfredo garcia,Resource Allocation,2012.0,10.1109/JSAC.2012.121216,IEEE Journal on Selected Areas in Communications,Hong2012,False,,IEEE,Not available,Mechanism Design for Base Station Association and Resource Allocation in Downlink OFDMA Network,7acbd14826500757d5f41e03fcc0c98e,https://ieeexplore.ieee.org/document/6354282/
2871,"We consider a resource management problem in a multi-cell downlink OFDMA network whereby the goal is to find the optimal combination of (i) assignment of users to base stations and (ii) resource allocation strategies at each base station. Efficient resource management protocols must rely on users truthfully reporting privately held information such as downlink channel states. However, individual users can manipulate the resulting resource allocation (by misreporting their private information) if by doing so they can improve their payoff. Therefore, it is of interest to design efficient resource management protocols that are strategy-proof, i.e. it is in the users' best interests to truthfully report their private information. Unfortunately, we show that the implementation of any protocol that is efficient and strategy-proof is NP-hard. Thus, we propose a computationally tractable strategy-proof mechanism that is approximately efficient, i.e. the solution obtained yields at least 1/2 of the optimal throughput. Simulations are provided to illustrate the effectiveness of the proposed mechanism.",alfredo garcia,Base Station Association,2012.0,10.1109/JSAC.2012.121216,IEEE Journal on Selected Areas in Communications,Hong2012,False,,IEEE,Not available,Mechanism Design for Base Station Association and Resource Allocation in Downlink OFDMA Network,7acbd14826500757d5f41e03fcc0c98e,https://ieeexplore.ieee.org/document/6354282/
2872,"We consider a resource management problem in a multi-cell downlink OFDMA network whereby the goal is to find the optimal combination of (i) assignment of users to base stations and (ii) resource allocation strategies at each base station. Efficient resource management protocols must rely on users truthfully reporting privately held information such as downlink channel states. However, individual users can manipulate the resulting resource allocation (by misreporting their private information) if by doing so they can improve their payoff. Therefore, it is of interest to design efficient resource management protocols that are strategy-proof, i.e. it is in the users' best interests to truthfully report their private information. Unfortunately, we show that the implementation of any protocol that is efficient and strategy-proof is NP-hard. Thus, we propose a computationally tractable strategy-proof mechanism that is approximately efficient, i.e. the solution obtained yields at least 1/2 of the optimal throughput. Simulations are provided to illustrate the effectiveness of the proposed mechanism.",alfredo garcia,Approximation Bounds,2012.0,10.1109/JSAC.2012.121216,IEEE Journal on Selected Areas in Communications,Hong2012,False,,IEEE,Not available,Mechanism Design for Base Station Association and Resource Allocation in Downlink OFDMA Network,7acbd14826500757d5f41e03fcc0c98e,https://ieeexplore.ieee.org/document/6354282/
2873,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
2874,"We consider a resource management problem in a multi-cell downlink OFDMA network whereby the goal is to find the optimal combination of (i) assignment of users to base stations and (ii) resource allocation strategies at each base station. Efficient resource management protocols must rely on users truthfully reporting privately held information such as downlink channel states. However, individual users can manipulate the resulting resource allocation (by misreporting their private information) if by doing so they can improve their payoff. Therefore, it is of interest to design efficient resource management protocols that are strategy-proof, i.e. it is in the users' best interests to truthfully report their private information. Unfortunately, we show that the implementation of any protocol that is efficient and strategy-proof is NP-hard. Thus, we propose a computationally tractable strategy-proof mechanism that is approximately efficient, i.e. the solution obtained yields at least 1/2 of the optimal throughput. Simulations are provided to illustrate the effectiveness of the proposed mechanism.",alfredo garcia,Computational Complexity,2012.0,10.1109/JSAC.2012.121216,IEEE Journal on Selected Areas in Communications,Hong2012,False,,IEEE,Not available,Mechanism Design for Base Station Association and Resource Allocation in Downlink OFDMA Network,7acbd14826500757d5f41e03fcc0c98e,https://ieeexplore.ieee.org/document/6354282/
2875,"We consider a resource management problem in a multi-cell downlink OFDMA network whereby the goal is to find the optimal combination of (i) assignment of users to base stations and (ii) resource allocation strategies at each base station. Efficient resource management protocols must rely on users truthfully reporting privately held information such as downlink channel states. However, individual users can manipulate the resulting resource allocation (by misreporting their private information) if by doing so they can improve their payoff. Therefore, it is of interest to design efficient resource management protocols that are strategy-proof, i.e. it is in the users' best interests to truthfully report their private information. Unfortunately, we show that the implementation of any protocol that is efficient and strategy-proof is NP-hard. Thus, we propose a computationally tractable strategy-proof mechanism that is approximately efficient, i.e. the solution obtained yields at least 1/2 of the optimal throughput. Simulations are provided to illustrate the effectiveness of the proposed mechanism.",alfredo garcia,Nash Equilibrium,2012.0,10.1109/JSAC.2012.121216,IEEE Journal on Selected Areas in Communications,Hong2012,False,,IEEE,Not available,Mechanism Design for Base Station Association and Resource Allocation in Downlink OFDMA Network,7acbd14826500757d5f41e03fcc0c98e,https://ieeexplore.ieee.org/document/6354282/
2876,"We consider a resource management problem in a multi-cell downlink OFDMA network whereby the goal is to find the optimal combination of (i) assignment of users to base stations and (ii) resource allocation strategies at each base station. Efficient resource management protocols must rely on users truthfully reporting privately held information such as downlink channel states. However, individual users can manipulate the resulting resource allocation (by misreporting their private information) if by doing so they can improve their payoff. Therefore, it is of interest to design efficient resource management protocols that are strategy-proof, i.e. it is in the users' best interests to truthfully report their private information. Unfortunately, we show that the implementation of any protocol that is efficient and strategy-proof is NP-hard. Thus, we propose a computationally tractable strategy-proof mechanism that is approximately efficient, i.e. the solution obtained yields at least 1/2 of the optimal throughput. Simulations are provided to illustrate the effectiveness of the proposed mechanism.",alfredo garcia,Price of Anarchy,2012.0,10.1109/JSAC.2012.121216,IEEE Journal on Selected Areas in Communications,Hong2012,False,,IEEE,Not available,Mechanism Design for Base Station Association and Resource Allocation in Downlink OFDMA Network,7acbd14826500757d5f41e03fcc0c98e,https://ieeexplore.ieee.org/document/6354282/
2877,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, subject to transmission and generator capacity constraints. Under the assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying game, and derive a tight bound on its price of anarchy. Under the more restrictive setting of a two-node power network, we present a detailed comparison of market outcomes predicted by the simultaneous-move formulation of the game against those predicted by the more plausible sequential-move formulation, where the ISO observes the generators' strategy profile prior to determining their production quantities.",weixuan lin,Production,2016.0,10.1109/CDC.2016.7798485,2016 IEEE 55th Conference on Decision and Control (CDC),Lin2016,False,,IEEE,Not available,Parameterized supply function equilibrium in power networks,acdbefa6303f83fc1143bded80b0ea96,https://ieeexplore.ieee.org/document/7798485/
2878,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, subject to transmission and generator capacity constraints. Under the assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying game, and derive a tight bound on its price of anarchy. Under the more restrictive setting of a two-node power network, we present a detailed comparison of market outcomes predicted by the simultaneous-move formulation of the game against those predicted by the more plausible sequential-move formulation, where the ISO observes the generators' strategy profile prior to determining their production quantities.",weixuan lin,ISO,2016.0,10.1109/CDC.2016.7798485,2016 IEEE 55th Conference on Decision and Control (CDC),Lin2016,False,,IEEE,Not available,Parameterized supply function equilibrium in power networks,acdbefa6303f83fc1143bded80b0ea96,https://ieeexplore.ieee.org/document/7798485/
2879,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, subject to transmission and generator capacity constraints. Under the assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying game, and derive a tight bound on its price of anarchy. Under the more restrictive setting of a two-node power network, we present a detailed comparison of market outcomes predicted by the simultaneous-move formulation of the game against those predicted by the more plausible sequential-move formulation, where the ISO observes the generators' strategy profile prior to determining their production quantities.",weixuan lin,Games,2016.0,10.1109/CDC.2016.7798485,2016 IEEE 55th Conference on Decision and Control (CDC),Lin2016,False,,IEEE,Not available,Parameterized supply function equilibrium in power networks,acdbefa6303f83fc1143bded80b0ea96,https://ieeexplore.ieee.org/document/7798485/
2880,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, subject to transmission and generator capacity constraints. Under the assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying game, and derive a tight bound on its price of anarchy. Under the more restrictive setting of a two-node power network, we present a detailed comparison of market outcomes predicted by the simultaneous-move formulation of the game against those predicted by the more plausible sequential-move formulation, where the ISO observes the generators' strategy profile prior to determining their production quantities.",weixuan lin,Nickel,2016.0,10.1109/CDC.2016.7798485,2016 IEEE 55th Conference on Decision and Control (CDC),Lin2016,False,,IEEE,Not available,Parameterized supply function equilibrium in power networks,acdbefa6303f83fc1143bded80b0ea96,https://ieeexplore.ieee.org/document/7798485/
2881,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, subject to transmission and generator capacity constraints. Under the assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying game, and derive a tight bound on its price of anarchy. Under the more restrictive setting of a two-node power network, we present a detailed comparison of market outcomes predicted by the simultaneous-move formulation of the game against those predicted by the more plausible sequential-move formulation, where the ISO observes the generators' strategy profile prior to determining their production quantities.",weixuan lin,Generators,2016.0,10.1109/CDC.2016.7798485,2016 IEEE 55th Conference on Decision and Control (CDC),Lin2016,False,,IEEE,Not available,Parameterized supply function equilibrium in power networks,acdbefa6303f83fc1143bded80b0ea96,https://ieeexplore.ieee.org/document/7798485/
2882,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, subject to transmission and generator capacity constraints. Under the assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying game, and derive a tight bound on its price of anarchy. Under the more restrictive setting of a two-node power network, we present a detailed comparison of market outcomes predicted by the simultaneous-move formulation of the game against those predicted by the more plausible sequential-move formulation, where the ISO observes the generators' strategy profile prior to determining their production quantities.",weixuan lin,Economics,2016.0,10.1109/CDC.2016.7798485,2016 IEEE 55th Conference on Decision and Control (CDC),Lin2016,False,,IEEE,Not available,Parameterized supply function equilibrium in power networks,acdbefa6303f83fc1143bded80b0ea96,https://ieeexplore.ieee.org/document/7798485/
2883,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, subject to transmission and generator capacity constraints. Under the assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying game, and derive a tight bound on its price of anarchy. Under the more restrictive setting of a two-node power network, we present a detailed comparison of market outcomes predicted by the simultaneous-move formulation of the game against those predicted by the more plausible sequential-move formulation, where the ISO observes the generators' strategy profile prior to determining their production quantities.",weixuan lin,Pricing,2016.0,10.1109/CDC.2016.7798485,2016 IEEE 55th Conference on Decision and Control (CDC),Lin2016,False,,IEEE,Not available,Parameterized supply function equilibrium in power networks,acdbefa6303f83fc1143bded80b0ea96,https://ieeexplore.ieee.org/document/7798485/
2884,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
2885,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, subject to transmission and generator capacity constraints. Under the assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying game, and derive a tight bound on its price of anarchy. Under the more restrictive setting of a two-node power network, we present a detailed comparison of market outcomes predicted by the simultaneous-move formulation of the game against those predicted by the more plausible sequential-move formulation, where the ISO observes the generators' strategy profile prior to determining their production quantities.",eilyan bitar,Production,2016.0,10.1109/CDC.2016.7798485,2016 IEEE 55th Conference on Decision and Control (CDC),Lin2016,False,,IEEE,Not available,Parameterized supply function equilibrium in power networks,acdbefa6303f83fc1143bded80b0ea96,https://ieeexplore.ieee.org/document/7798485/
2886,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, subject to transmission and generator capacity constraints. Under the assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying game, and derive a tight bound on its price of anarchy. Under the more restrictive setting of a two-node power network, we present a detailed comparison of market outcomes predicted by the simultaneous-move formulation of the game against those predicted by the more plausible sequential-move formulation, where the ISO observes the generators' strategy profile prior to determining their production quantities.",eilyan bitar,ISO,2016.0,10.1109/CDC.2016.7798485,2016 IEEE 55th Conference on Decision and Control (CDC),Lin2016,False,,IEEE,Not available,Parameterized supply function equilibrium in power networks,acdbefa6303f83fc1143bded80b0ea96,https://ieeexplore.ieee.org/document/7798485/
2887,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, subject to transmission and generator capacity constraints. Under the assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying game, and derive a tight bound on its price of anarchy. Under the more restrictive setting of a two-node power network, we present a detailed comparison of market outcomes predicted by the simultaneous-move formulation of the game against those predicted by the more plausible sequential-move formulation, where the ISO observes the generators' strategy profile prior to determining their production quantities.",eilyan bitar,Games,2016.0,10.1109/CDC.2016.7798485,2016 IEEE 55th Conference on Decision and Control (CDC),Lin2016,False,,IEEE,Not available,Parameterized supply function equilibrium in power networks,acdbefa6303f83fc1143bded80b0ea96,https://ieeexplore.ieee.org/document/7798485/
2888,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, subject to transmission and generator capacity constraints. Under the assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying game, and derive a tight bound on its price of anarchy. Under the more restrictive setting of a two-node power network, we present a detailed comparison of market outcomes predicted by the simultaneous-move formulation of the game against those predicted by the more plausible sequential-move formulation, where the ISO observes the generators' strategy profile prior to determining their production quantities.",eilyan bitar,Nickel,2016.0,10.1109/CDC.2016.7798485,2016 IEEE 55th Conference on Decision and Control (CDC),Lin2016,False,,IEEE,Not available,Parameterized supply function equilibrium in power networks,acdbefa6303f83fc1143bded80b0ea96,https://ieeexplore.ieee.org/document/7798485/
2889,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, subject to transmission and generator capacity constraints. Under the assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying game, and derive a tight bound on its price of anarchy. Under the more restrictive setting of a two-node power network, we present a detailed comparison of market outcomes predicted by the simultaneous-move formulation of the game against those predicted by the more plausible sequential-move formulation, where the ISO observes the generators' strategy profile prior to determining their production quantities.",eilyan bitar,Generators,2016.0,10.1109/CDC.2016.7798485,2016 IEEE 55th Conference on Decision and Control (CDC),Lin2016,False,,IEEE,Not available,Parameterized supply function equilibrium in power networks,acdbefa6303f83fc1143bded80b0ea96,https://ieeexplore.ieee.org/document/7798485/
2890,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, subject to transmission and generator capacity constraints. Under the assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying game, and derive a tight bound on its price of anarchy. Under the more restrictive setting of a two-node power network, we present a detailed comparison of market outcomes predicted by the simultaneous-move formulation of the game against those predicted by the more plausible sequential-move formulation, where the ISO observes the generators' strategy profile prior to determining their production quantities.",eilyan bitar,Economics,2016.0,10.1109/CDC.2016.7798485,2016 IEEE 55th Conference on Decision and Control (CDC),Lin2016,False,,IEEE,Not available,Parameterized supply function equilibrium in power networks,acdbefa6303f83fc1143bded80b0ea96,https://ieeexplore.ieee.org/document/7798485/
2891,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, subject to transmission and generator capacity constraints. Under the assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying game, and derive a tight bound on its price of anarchy. Under the more restrictive setting of a two-node power network, we present a detailed comparison of market outcomes predicted by the simultaneous-move formulation of the game against those predicted by the more plausible sequential-move formulation, where the ISO observes the generators' strategy profile prior to determining their production quantities.",eilyan bitar,Pricing,2016.0,10.1109/CDC.2016.7798485,2016 IEEE 55th Conference on Decision and Control (CDC),Lin2016,False,,IEEE,Not available,Parameterized supply function equilibrium in power networks,acdbefa6303f83fc1143bded80b0ea96,https://ieeexplore.ieee.org/document/7798485/
2892,"We consider a model of priced resource sharing that combines both queueing behavior and strategic behavior. We study a priority service model where a single server allocates its capacity to agents in proportion to their payment to the system, and users from different classes act to minimize the sum of their cost for processing delay and payment. As the exact processing time of this system is hard to compute and cannot be characterized in closed form, we introduce the notion of heavy traffic equilibrium as an approximation of the Nash equilibrium, derived by considering the asymptotic regime where the system load approaches capacity. We discuss efficiency and revenue, and in particular provide a bound for the price of anarchy of the heavy traffic equilibrium.",yu wu,resource sharing,2012.0,10.1109/JSAC.2012.121212,IEEE Journal on Selected Areas in Communications,Wu2012,False,,IEEE,Not available,Heavy Traffic Approximation of Equilibria in Resource Sharing Games,9a491a3b859471f8ada5a0833227b335,https://ieeexplore.ieee.org/document/6354278/
2893,"We consider a model of priced resource sharing that combines both queueing behavior and strategic behavior. We study a priority service model where a single server allocates its capacity to agents in proportion to their payment to the system, and users from different classes act to minimize the sum of their cost for processing delay and payment. As the exact processing time of this system is hard to compute and cannot be characterized in closed form, we introduce the notion of heavy traffic equilibrium as an approximation of the Nash equilibrium, derived by considering the asymptotic regime where the system load approaches capacity. We discuss efficiency and revenue, and in particular provide a bound for the price of anarchy of the heavy traffic equilibrium.",yu wu,discriminatory processor sharing,2012.0,10.1109/JSAC.2012.121212,IEEE Journal on Selected Areas in Communications,Wu2012,False,,IEEE,Not available,Heavy Traffic Approximation of Equilibria in Resource Sharing Games,9a491a3b859471f8ada5a0833227b335,https://ieeexplore.ieee.org/document/6354278/
2894,"We consider a model of priced resource sharing that combines both queueing behavior and strategic behavior. We study a priority service model where a single server allocates its capacity to agents in proportion to their payment to the system, and users from different classes act to minimize the sum of their cost for processing delay and payment. As the exact processing time of this system is hard to compute and cannot be characterized in closed form, we introduce the notion of heavy traffic equilibrium as an approximation of the Nash equilibrium, derived by considering the asymptotic regime where the system load approaches capacity. We discuss efficiency and revenue, and in particular provide a bound for the price of anarchy of the heavy traffic equilibrium.",yu wu,equilibrium,2012.0,10.1109/JSAC.2012.121212,IEEE Journal on Selected Areas in Communications,Wu2012,False,,IEEE,Not available,Heavy Traffic Approximation of Equilibria in Resource Sharing Games,9a491a3b859471f8ada5a0833227b335,https://ieeexplore.ieee.org/document/6354278/
2895,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
2896,"We consider a model of priced resource sharing that combines both queueing behavior and strategic behavior. We study a priority service model where a single server allocates its capacity to agents in proportion to their payment to the system, and users from different classes act to minimize the sum of their cost for processing delay and payment. As the exact processing time of this system is hard to compute and cannot be characterized in closed form, we introduce the notion of heavy traffic equilibrium as an approximation of the Nash equilibrium, derived by considering the asymptotic regime where the system load approaches capacity. We discuss efficiency and revenue, and in particular provide a bound for the price of anarchy of the heavy traffic equilibrium.",yu wu,heavy traffic approximation,2012.0,10.1109/JSAC.2012.121212,IEEE Journal on Selected Areas in Communications,Wu2012,False,,IEEE,Not available,Heavy Traffic Approximation of Equilibria in Resource Sharing Games,9a491a3b859471f8ada5a0833227b335,https://ieeexplore.ieee.org/document/6354278/
2897,"We consider a model of priced resource sharing that combines both queueing behavior and strategic behavior. We study a priority service model where a single server allocates its capacity to agents in proportion to their payment to the system, and users from different classes act to minimize the sum of their cost for processing delay and payment. As the exact processing time of this system is hard to compute and cannot be characterized in closed form, we introduce the notion of heavy traffic equilibrium as an approximation of the Nash equilibrium, derived by considering the asymptotic regime where the system load approaches capacity. We discuss efficiency and revenue, and in particular provide a bound for the price of anarchy of the heavy traffic equilibrium.",loc bui,resource sharing,2012.0,10.1109/JSAC.2012.121212,IEEE Journal on Selected Areas in Communications,Wu2012,False,,IEEE,Not available,Heavy Traffic Approximation of Equilibria in Resource Sharing Games,9a491a3b859471f8ada5a0833227b335,https://ieeexplore.ieee.org/document/6354278/
2898,"We consider a model of priced resource sharing that combines both queueing behavior and strategic behavior. We study a priority service model where a single server allocates its capacity to agents in proportion to their payment to the system, and users from different classes act to minimize the sum of their cost for processing delay and payment. As the exact processing time of this system is hard to compute and cannot be characterized in closed form, we introduce the notion of heavy traffic equilibrium as an approximation of the Nash equilibrium, derived by considering the asymptotic regime where the system load approaches capacity. We discuss efficiency and revenue, and in particular provide a bound for the price of anarchy of the heavy traffic equilibrium.",loc bui,discriminatory processor sharing,2012.0,10.1109/JSAC.2012.121212,IEEE Journal on Selected Areas in Communications,Wu2012,False,,IEEE,Not available,Heavy Traffic Approximation of Equilibria in Resource Sharing Games,9a491a3b859471f8ada5a0833227b335,https://ieeexplore.ieee.org/document/6354278/
2899,"We consider a model of priced resource sharing that combines both queueing behavior and strategic behavior. We study a priority service model where a single server allocates its capacity to agents in proportion to their payment to the system, and users from different classes act to minimize the sum of their cost for processing delay and payment. As the exact processing time of this system is hard to compute and cannot be characterized in closed form, we introduce the notion of heavy traffic equilibrium as an approximation of the Nash equilibrium, derived by considering the asymptotic regime where the system load approaches capacity. We discuss efficiency and revenue, and in particular provide a bound for the price of anarchy of the heavy traffic equilibrium.",loc bui,equilibrium,2012.0,10.1109/JSAC.2012.121212,IEEE Journal on Selected Areas in Communications,Wu2012,False,,IEEE,Not available,Heavy Traffic Approximation of Equilibria in Resource Sharing Games,9a491a3b859471f8ada5a0833227b335,https://ieeexplore.ieee.org/document/6354278/
2900,"We consider a model of priced resource sharing that combines both queueing behavior and strategic behavior. We study a priority service model where a single server allocates its capacity to agents in proportion to their payment to the system, and users from different classes act to minimize the sum of their cost for processing delay and payment. As the exact processing time of this system is hard to compute and cannot be characterized in closed form, we introduce the notion of heavy traffic equilibrium as an approximation of the Nash equilibrium, derived by considering the asymptotic regime where the system load approaches capacity. We discuss efficiency and revenue, and in particular provide a bound for the price of anarchy of the heavy traffic equilibrium.",loc bui,heavy traffic approximation,2012.0,10.1109/JSAC.2012.121212,IEEE Journal on Selected Areas in Communications,Wu2012,False,,IEEE,Not available,Heavy Traffic Approximation of Equilibria in Resource Sharing Games,9a491a3b859471f8ada5a0833227b335,https://ieeexplore.ieee.org/document/6354278/
2901,"We consider a model of priced resource sharing that combines both queueing behavior and strategic behavior. We study a priority service model where a single server allocates its capacity to agents in proportion to their payment to the system, and users from different classes act to minimize the sum of their cost for processing delay and payment. As the exact processing time of this system is hard to compute and cannot be characterized in closed form, we introduce the notion of heavy traffic equilibrium as an approximation of the Nash equilibrium, derived by considering the asymptotic regime where the system load approaches capacity. We discuss efficiency and revenue, and in particular provide a bound for the price of anarchy of the heavy traffic equilibrium.",ramesh johari,resource sharing,2012.0,10.1109/JSAC.2012.121212,IEEE Journal on Selected Areas in Communications,Wu2012,False,,IEEE,Not available,Heavy Traffic Approximation of Equilibria in Resource Sharing Games,9a491a3b859471f8ada5a0833227b335,https://ieeexplore.ieee.org/document/6354278/
2902,"We consider a model of priced resource sharing that combines both queueing behavior and strategic behavior. We study a priority service model where a single server allocates its capacity to agents in proportion to their payment to the system, and users from different classes act to minimize the sum of their cost for processing delay and payment. As the exact processing time of this system is hard to compute and cannot be characterized in closed form, we introduce the notion of heavy traffic equilibrium as an approximation of the Nash equilibrium, derived by considering the asymptotic regime where the system load approaches capacity. We discuss efficiency and revenue, and in particular provide a bound for the price of anarchy of the heavy traffic equilibrium.",ramesh johari,discriminatory processor sharing,2012.0,10.1109/JSAC.2012.121212,IEEE Journal on Selected Areas in Communications,Wu2012,False,,IEEE,Not available,Heavy Traffic Approximation of Equilibria in Resource Sharing Games,9a491a3b859471f8ada5a0833227b335,https://ieeexplore.ieee.org/document/6354278/
2903,"We consider a model of priced resource sharing that combines both queueing behavior and strategic behavior. We study a priority service model where a single server allocates its capacity to agents in proportion to their payment to the system, and users from different classes act to minimize the sum of their cost for processing delay and payment. As the exact processing time of this system is hard to compute and cannot be characterized in closed form, we introduce the notion of heavy traffic equilibrium as an approximation of the Nash equilibrium, derived by considering the asymptotic regime where the system load approaches capacity. We discuss efficiency and revenue, and in particular provide a bound for the price of anarchy of the heavy traffic equilibrium.",ramesh johari,equilibrium,2012.0,10.1109/JSAC.2012.121212,IEEE Journal on Selected Areas in Communications,Wu2012,False,,IEEE,Not available,Heavy Traffic Approximation of Equilibria in Resource Sharing Games,9a491a3b859471f8ada5a0833227b335,https://ieeexplore.ieee.org/document/6354278/
2904,"We consider a model of priced resource sharing that combines both queueing behavior and strategic behavior. We study a priority service model where a single server allocates its capacity to agents in proportion to their payment to the system, and users from different classes act to minimize the sum of their cost for processing delay and payment. As the exact processing time of this system is hard to compute and cannot be characterized in closed form, we introduce the notion of heavy traffic equilibrium as an approximation of the Nash equilibrium, derived by considering the asymptotic regime where the system load approaches capacity. We discuss efficiency and revenue, and in particular provide a bound for the price of anarchy of the heavy traffic equilibrium.",ramesh johari,heavy traffic approximation,2012.0,10.1109/JSAC.2012.121212,IEEE Journal on Selected Areas in Communications,Wu2012,False,,IEEE,Not available,Heavy Traffic Approximation of Equilibria in Resource Sharing Games,9a491a3b859471f8ada5a0833227b335,https://ieeexplore.ieee.org/document/6354278/
2905,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",konstantinos poularakis,Heuristic algorithms,2013.0,10.1109/INFCOMW.2013.6562882,2013 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS),Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6562882/
2906,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
2907,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",konstantinos poularakis,Games,2013.0,10.1109/INFCOMW.2013.6562882,2013 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS),Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6562882/
2908,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",konstantinos poularakis,Nash equilibrium,2013.0,10.1109/INFCOMW.2013.6562882,2013 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS),Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6562882/
2909,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",konstantinos poularakis,Aggregates,2013.0,10.1109/INFCOMW.2013.6562882,2013 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS),Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6562882/
2910,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",konstantinos poularakis,Vectors,2013.0,10.1109/INFCOMW.2013.6562882,2013 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS),Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6562882/
2911,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",konstantinos poularakis,Linear programming,2013.0,10.1109/INFCOMW.2013.6562882,2013 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS),Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6562882/
2912,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",konstantinos poularakis,Conferences,2013.0,10.1109/INFCOMW.2013.6562882,2013 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS),Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6562882/
2913,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",leandros tassiulas,Heuristic algorithms,2013.0,10.1109/INFCOMW.2013.6562882,2013 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS),Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6562882/
2914,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",leandros tassiulas,Games,2013.0,10.1109/INFCOMW.2013.6562882,2013 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS),Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6562882/
2915,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",leandros tassiulas,Nash equilibrium,2013.0,10.1109/INFCOMW.2013.6562882,2013 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS),Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6562882/
2916,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",leandros tassiulas,Aggregates,2013.0,10.1109/INFCOMW.2013.6562882,2013 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS),Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6562882/
2917,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
2918,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",leandros tassiulas,Vectors,2013.0,10.1109/INFCOMW.2013.6562882,2013 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS),Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6562882/
2919,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",leandros tassiulas,Linear programming,2013.0,10.1109/INFCOMW.2013.6562882,2013 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS),Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6562882/
2920,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",leandros tassiulas,Conferences,2013.0,10.1109/INFCOMW.2013.6562882,2013 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS),Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6562882/
2921,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",jocelyne elias,Cost function,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2922,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",jocelyne elias,Game theory,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2923,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",jocelyne elias,Nash equilibrium,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2924,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",jocelyne elias,Communications Society,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2925,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",jocelyne elias,IP networks,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2926,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",jocelyne elias,Network topology,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2927,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",jocelyne elias,Web and internet services,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2928,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
2929,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",jocelyne elias,System performance,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2930,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",jocelyne elias,Stability,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2931,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",jocelyne elias,Degradation,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2932,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",fabio martignon,Cost function,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2933,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",fabio martignon,Game theory,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2934,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",fabio martignon,Nash equilibrium,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2935,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",fabio martignon,Communications Society,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2936,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",fabio martignon,IP networks,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2937,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",fabio martignon,Network topology,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2938,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",fabio martignon,Web and internet services,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2939,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
2940,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",fabio martignon,System performance,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2941,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",fabio martignon,Stability,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2942,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",fabio martignon,Degradation,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2943,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",konstantin avrachenkov,Cost function,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2944,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",konstantin avrachenkov,Game theory,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2945,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",konstantin avrachenkov,Nash equilibrium,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2946,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",konstantin avrachenkov,Communications Society,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2947,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",konstantin avrachenkov,IP networks,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2948,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",konstantin avrachenkov,Network topology,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2949,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",konstantin avrachenkov,Web and internet services,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2950,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
2951,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",konstantin avrachenkov,System performance,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2952,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",konstantin avrachenkov,Stability,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2953,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",konstantin avrachenkov,Degradation,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2954,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",giovanni neglia,Cost function,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2955,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",giovanni neglia,Game theory,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2956,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",giovanni neglia,Nash equilibrium,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2957,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",giovanni neglia,Communications Society,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2958,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",giovanni neglia,IP networks,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2959,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",giovanni neglia,Network topology,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2960,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",giovanni neglia,Web and internet services,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2961,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
2962,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
2963,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",giovanni neglia,System performance,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2964,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",giovanni neglia,Stability,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2965,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",giovanni neglia,Degradation,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
2966,"We consider the concert queueing game in the fluid framework, where the service facility opens at a specified time, the customers are particles in a fluid with homogeneous costs that are linear and additive in the waiting time and in the time to service completion, and wish to choose their own arrival times so as to minimize their cost. This problem has recently been analyzed under the assumption that the total volume of arriving customers is deterministic and known beforehand. We consider here the more plausible setting where this volume may be random, and only its probability distribution is known beforehand. In this setting, we identify the unique symmetric Nash equilibrium and show that under it the customer behavior significantly differs from the case where such uncertainties do not exist. While, in the latter case, the equilibrium profile is uniform, in the former case it is uniform up to a point and then it tapers off. We also solve the associated optimization problem to determine the socially optimal solution when the central planner is unaware of the actual amount of arrivals. Interestingly, the Price of Anarchy (ratio of the social cost of the equilibrium solution to that of the optimal one) for this model turns out to be two exactly, as in the deterministic case, despite the different form of the social and equilibrium arrival profiles.",sandeep juneja,Fluids,2012.0,10.4108/valuetools.2012.250166,6th International ICST Conference on Performance Evaluation Methodologies and Tools,Juneja2012,False,,IEEE,Not available,The concert queueing game with a random volume of arrivals,9626b38ca07343c760573194f79e112c,https://ieeexplore.ieee.org/document/6376339/
2967,"We consider the concert queueing game in the fluid framework, where the service facility opens at a specified time, the customers are particles in a fluid with homogeneous costs that are linear and additive in the waiting time and in the time to service completion, and wish to choose their own arrival times so as to minimize their cost. This problem has recently been analyzed under the assumption that the total volume of arriving customers is deterministic and known beforehand. We consider here the more plausible setting where this volume may be random, and only its probability distribution is known beforehand. In this setting, we identify the unique symmetric Nash equilibrium and show that under it the customer behavior significantly differs from the case where such uncertainties do not exist. While, in the latter case, the equilibrium profile is uniform, in the former case it is uniform up to a point and then it tapers off. We also solve the associated optimization problem to determine the socially optimal solution when the central planner is unaware of the actual amount of arrivals. Interestingly, the Price of Anarchy (ratio of the social cost of the equilibrium solution to that of the optimal one) for this model turns out to be two exactly, as in the deterministic case, despite the different form of the social and equilibrium arrival profiles.",sandeep juneja,Standards,2012.0,10.4108/valuetools.2012.250166,6th International ICST Conference on Performance Evaluation Methodologies and Tools,Juneja2012,False,,IEEE,Not available,The concert queueing game with a random volume of arrivals,9626b38ca07343c760573194f79e112c,https://ieeexplore.ieee.org/document/6376339/
2968,"We consider the concert queueing game in the fluid framework, where the service facility opens at a specified time, the customers are particles in a fluid with homogeneous costs that are linear and additive in the waiting time and in the time to service completion, and wish to choose their own arrival times so as to minimize their cost. This problem has recently been analyzed under the assumption that the total volume of arriving customers is deterministic and known beforehand. We consider here the more plausible setting where this volume may be random, and only its probability distribution is known beforehand. In this setting, we identify the unique symmetric Nash equilibrium and show that under it the customer behavior significantly differs from the case where such uncertainties do not exist. While, in the latter case, the equilibrium profile is uniform, in the former case it is uniform up to a point and then it tapers off. We also solve the associated optimization problem to determine the socially optimal solution when the central planner is unaware of the actual amount of arrivals. Interestingly, the Price of Anarchy (ratio of the social cost of the equilibrium solution to that of the optimal one) for this model turns out to be two exactly, as in the deterministic case, despite the different form of the social and equilibrium arrival profiles.",sandeep juneja,Facsimile,2012.0,10.4108/valuetools.2012.250166,6th International ICST Conference on Performance Evaluation Methodologies and Tools,Juneja2012,False,,IEEE,Not available,The concert queueing game with a random volume of arrivals,9626b38ca07343c760573194f79e112c,https://ieeexplore.ieee.org/document/6376339/
2969,"We consider the concert queueing game in the fluid framework, where the service facility opens at a specified time, the customers are particles in a fluid with homogeneous costs that are linear and additive in the waiting time and in the time to service completion, and wish to choose their own arrival times so as to minimize their cost. This problem has recently been analyzed under the assumption that the total volume of arriving customers is deterministic and known beforehand. We consider here the more plausible setting where this volume may be random, and only its probability distribution is known beforehand. In this setting, we identify the unique symmetric Nash equilibrium and show that under it the customer behavior significantly differs from the case where such uncertainties do not exist. While, in the latter case, the equilibrium profile is uniform, in the former case it is uniform up to a point and then it tapers off. We also solve the associated optimization problem to determine the socially optimal solution when the central planner is unaware of the actual amount of arrivals. Interestingly, the Price of Anarchy (ratio of the social cost of the equilibrium solution to that of the optimal one) for this model turns out to be two exactly, as in the deterministic case, despite the different form of the social and equilibrium arrival profiles.",tushar raheja,Fluids,2012.0,10.4108/valuetools.2012.250166,6th International ICST Conference on Performance Evaluation Methodologies and Tools,Juneja2012,False,,IEEE,Not available,The concert queueing game with a random volume of arrivals,9626b38ca07343c760573194f79e112c,https://ieeexplore.ieee.org/document/6376339/
2970,"We consider the concert queueing game in the fluid framework, where the service facility opens at a specified time, the customers are particles in a fluid with homogeneous costs that are linear and additive in the waiting time and in the time to service completion, and wish to choose their own arrival times so as to minimize their cost. This problem has recently been analyzed under the assumption that the total volume of arriving customers is deterministic and known beforehand. We consider here the more plausible setting where this volume may be random, and only its probability distribution is known beforehand. In this setting, we identify the unique symmetric Nash equilibrium and show that under it the customer behavior significantly differs from the case where such uncertainties do not exist. While, in the latter case, the equilibrium profile is uniform, in the former case it is uniform up to a point and then it tapers off. We also solve the associated optimization problem to determine the socially optimal solution when the central planner is unaware of the actual amount of arrivals. Interestingly, the Price of Anarchy (ratio of the social cost of the equilibrium solution to that of the optimal one) for this model turns out to be two exactly, as in the deterministic case, despite the different form of the social and equilibrium arrival profiles.",tushar raheja,Standards,2012.0,10.4108/valuetools.2012.250166,6th International ICST Conference on Performance Evaluation Methodologies and Tools,Juneja2012,False,,IEEE,Not available,The concert queueing game with a random volume of arrivals,9626b38ca07343c760573194f79e112c,https://ieeexplore.ieee.org/document/6376339/
2971,"We consider the concert queueing game in the fluid framework, where the service facility opens at a specified time, the customers are particles in a fluid with homogeneous costs that are linear and additive in the waiting time and in the time to service completion, and wish to choose their own arrival times so as to minimize their cost. This problem has recently been analyzed under the assumption that the total volume of arriving customers is deterministic and known beforehand. We consider here the more plausible setting where this volume may be random, and only its probability distribution is known beforehand. In this setting, we identify the unique symmetric Nash equilibrium and show that under it the customer behavior significantly differs from the case where such uncertainties do not exist. While, in the latter case, the equilibrium profile is uniform, in the former case it is uniform up to a point and then it tapers off. We also solve the associated optimization problem to determine the socially optimal solution when the central planner is unaware of the actual amount of arrivals. Interestingly, the Price of Anarchy (ratio of the social cost of the equilibrium solution to that of the optimal one) for this model turns out to be two exactly, as in the deterministic case, despite the different form of the social and equilibrium arrival profiles.",tushar raheja,Facsimile,2012.0,10.4108/valuetools.2012.250166,6th International ICST Conference on Performance Evaluation Methodologies and Tools,Juneja2012,False,,IEEE,Not available,The concert queueing game with a random volume of arrivals,9626b38ca07343c760573194f79e112c,https://ieeexplore.ieee.org/document/6376339/
2972,"We consider the concert queueing game in the fluid framework, where the service facility opens at a specified time, the customers are particles in a fluid with homogeneous costs that are linear and additive in the waiting time and in the time to service completion, and wish to choose their own arrival times so as to minimize their cost. This problem has recently been analyzed under the assumption that the total volume of arriving customers is deterministic and known beforehand. We consider here the more plausible setting where this volume may be random, and only its probability distribution is known beforehand. In this setting, we identify the unique symmetric Nash equilibrium and show that under it the customer behavior significantly differs from the case where such uncertainties do not exist. While, in the latter case, the equilibrium profile is uniform, in the former case it is uniform up to a point and then it tapers off. We also solve the associated optimization problem to determine the socially optimal solution when the central planner is unaware of the actual amount of arrivals. Interestingly, the Price of Anarchy (ratio of the social cost of the equilibrium solution to that of the optimal one) for this model turns out to be two exactly, as in the deterministic case, despite the different form of the social and equilibrium arrival profiles.",nahum shimkin,Fluids,2012.0,10.4108/valuetools.2012.250166,6th International ICST Conference on Performance Evaluation Methodologies and Tools,Juneja2012,False,,IEEE,Not available,The concert queueing game with a random volume of arrivals,9626b38ca07343c760573194f79e112c,https://ieeexplore.ieee.org/document/6376339/
2973,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
2974,"We consider the concert queueing game in the fluid framework, where the service facility opens at a specified time, the customers are particles in a fluid with homogeneous costs that are linear and additive in the waiting time and in the time to service completion, and wish to choose their own arrival times so as to minimize their cost. This problem has recently been analyzed under the assumption that the total volume of arriving customers is deterministic and known beforehand. We consider here the more plausible setting where this volume may be random, and only its probability distribution is known beforehand. In this setting, we identify the unique symmetric Nash equilibrium and show that under it the customer behavior significantly differs from the case where such uncertainties do not exist. While, in the latter case, the equilibrium profile is uniform, in the former case it is uniform up to a point and then it tapers off. We also solve the associated optimization problem to determine the socially optimal solution when the central planner is unaware of the actual amount of arrivals. Interestingly, the Price of Anarchy (ratio of the social cost of the equilibrium solution to that of the optimal one) for this model turns out to be two exactly, as in the deterministic case, despite the different form of the social and equilibrium arrival profiles.",nahum shimkin,Standards,2012.0,10.4108/valuetools.2012.250166,6th International ICST Conference on Performance Evaluation Methodologies and Tools,Juneja2012,False,,IEEE,Not available,The concert queueing game with a random volume of arrivals,9626b38ca07343c760573194f79e112c,https://ieeexplore.ieee.org/document/6376339/
2975,"We consider the concert queueing game in the fluid framework, where the service facility opens at a specified time, the customers are particles in a fluid with homogeneous costs that are linear and additive in the waiting time and in the time to service completion, and wish to choose their own arrival times so as to minimize their cost. This problem has recently been analyzed under the assumption that the total volume of arriving customers is deterministic and known beforehand. We consider here the more plausible setting where this volume may be random, and only its probability distribution is known beforehand. In this setting, we identify the unique symmetric Nash equilibrium and show that under it the customer behavior significantly differs from the case where such uncertainties do not exist. While, in the latter case, the equilibrium profile is uniform, in the former case it is uniform up to a point and then it tapers off. We also solve the associated optimization problem to determine the socially optimal solution when the central planner is unaware of the actual amount of arrivals. Interestingly, the Price of Anarchy (ratio of the social cost of the equilibrium solution to that of the optimal one) for this model turns out to be two exactly, as in the deterministic case, despite the different form of the social and equilibrium arrival profiles.",nahum shimkin,Facsimile,2012.0,10.4108/valuetools.2012.250166,6th International ICST Conference on Performance Evaluation Methodologies and Tools,Juneja2012,False,,IEEE,Not available,The concert queueing game with a random volume of arrivals,9626b38ca07343c760573194f79e112c,https://ieeexplore.ieee.org/document/6376339/
2976,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",h. nama,Peer to peer computing,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
2977,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",h. nama,Costs,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
2978,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",h. nama,IP networks,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
2979,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",h. nama,Energy efficiency,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
2980,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",h. nama,IEEE news,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
2981,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",h. nama,Telecommunication traffic,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
2982,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",h. nama,Internet,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
2983,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",h. nama,Communications Society,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
2984,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
2985,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",h. nama,Mobile handsets,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
2986,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",h. nama,Personal digital assistants,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
2987,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",n. mandayam,Peer to peer computing,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
2988,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",n. mandayam,Costs,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
2989,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",n. mandayam,IP networks,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
2990,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",n. mandayam,Energy efficiency,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
2991,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",n. mandayam,IEEE news,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
2992,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",n. mandayam,Telecommunication traffic,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
2993,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",n. mandayam,Internet,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
2994,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",n. mandayam,Communications Society,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
2995,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
2996,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",n. mandayam,Mobile handsets,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
2997,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",n. mandayam,Personal digital assistants,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
2998,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",r. yates,Peer to peer computing,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
2999,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",r. yates,Costs,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
3000,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",r. yates,IP networks,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
3001,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",r. yates,Energy efficiency,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
3002,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",r. yates,IEEE news,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
3003,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",r. yates,Telecommunication traffic,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
3004,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",r. yates,Internet,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
3005,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",r. yates,Communications Society,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
3006,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
3007,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",r. yates,Mobile handsets,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
3008,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",r. yates,Personal digital assistants,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
3009,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",qingkai liang,Cognitive radio networks,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
3010,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",qingkai liang,game theory,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
3011,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",qingkai liang,routing,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
3012,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",qingkai liang,spectrum dynamics,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
3013,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",xinbing wang,Cognitive radio networks,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
3014,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",xinbing wang,game theory,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
3015,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",xinbing wang,routing,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
3016,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",xinbing wang,spectrum dynamics,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
3017,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
3018,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",xiaohua tian,Cognitive radio networks,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
3019,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",xiaohua tian,game theory,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
3020,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",xiaohua tian,routing,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
3021,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",xiaohua tian,spectrum dynamics,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
3022,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",fan wu,Cognitive radio networks,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
3023,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",fan wu,game theory,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
3024,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",fan wu,routing,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
3025,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",fan wu,spectrum dynamics,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
3026,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",qian zhang,Cognitive radio networks,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
3027,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",qian zhang,game theory,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
3028,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
3029,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",qian zhang,routing,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
3030,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",qian zhang,spectrum dynamics,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
3031,"We review network formation models, contrast their behavior, and conduct numerical experiments to investigate the structural features of the networks they generate. We focus primarily on problems related to minimum spanning trees and consider the cost of selfish behavior, more commonly known as the price of anarchy, in network formation. We also explore differences between local, decentralized methods for network formation and their global, centralized counterparts.",deanne mcpherson,Biological system modeling,2011.0,10.1109/ACSSC.2011.6190123,"2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)",McPherson2011,False,,IEEE,Not available,A contrasting look at network formation models and their application to the minimum spanning tree,445db4ee8bb6562e142d1a747d04a01d,https://ieeexplore.ieee.org/document/6190123/
3032,"We review network formation models, contrast their behavior, and conduct numerical experiments to investigate the structural features of the networks they generate. We focus primarily on problems related to minimum spanning trees and consider the cost of selfish behavior, more commonly known as the price of anarchy, in network formation. We also explore differences between local, decentralized methods for network formation and their global, centralized counterparts.",deanne mcpherson,Games,2011.0,10.1109/ACSSC.2011.6190123,"2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)",McPherson2011,False,,IEEE,Not available,A contrasting look at network formation models and their application to the minimum spanning tree,445db4ee8bb6562e142d1a747d04a01d,https://ieeexplore.ieee.org/document/6190123/
3033,"We review network formation models, contrast their behavior, and conduct numerical experiments to investigate the structural features of the networks they generate. We focus primarily on problems related to minimum spanning trees and consider the cost of selfish behavior, more commonly known as the price of anarchy, in network formation. We also explore differences between local, decentralized methods for network formation and their global, centralized counterparts.",deanne mcpherson,Numerical models,2011.0,10.1109/ACSSC.2011.6190123,"2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)",McPherson2011,False,,IEEE,Not available,A contrasting look at network formation models and their application to the minimum spanning tree,445db4ee8bb6562e142d1a747d04a01d,https://ieeexplore.ieee.org/document/6190123/
3034,"We review network formation models, contrast their behavior, and conduct numerical experiments to investigate the structural features of the networks they generate. We focus primarily on problems related to minimum spanning trees and consider the cost of selfish behavior, more commonly known as the price of anarchy, in network formation. We also explore differences between local, decentralized methods for network formation and their global, centralized counterparts.",deanne mcpherson,Nash equilibrium,2011.0,10.1109/ACSSC.2011.6190123,"2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)",McPherson2011,False,,IEEE,Not available,A contrasting look at network formation models and their application to the minimum spanning tree,445db4ee8bb6562e142d1a747d04a01d,https://ieeexplore.ieee.org/document/6190123/
3035,"We review network formation models, contrast their behavior, and conduct numerical experiments to investigate the structural features of the networks they generate. We focus primarily on problems related to minimum spanning trees and consider the cost of selfish behavior, more commonly known as the price of anarchy, in network formation. We also explore differences between local, decentralized methods for network formation and their global, centralized counterparts.",deanne mcpherson,Internet,2011.0,10.1109/ACSSC.2011.6190123,"2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)",McPherson2011,False,,IEEE,Not available,A contrasting look at network formation models and their application to the minimum spanning tree,445db4ee8bb6562e142d1a747d04a01d,https://ieeexplore.ieee.org/document/6190123/
3036,"We review network formation models, contrast their behavior, and conduct numerical experiments to investigate the structural features of the networks they generate. We focus primarily on problems related to minimum spanning trees and consider the cost of selfish behavior, more commonly known as the price of anarchy, in network formation. We also explore differences between local, decentralized methods for network formation and their global, centralized counterparts.",deanne mcpherson,Optimization,2011.0,10.1109/ACSSC.2011.6190123,"2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)",McPherson2011,False,,IEEE,Not available,A contrasting look at network formation models and their application to the minimum spanning tree,445db4ee8bb6562e142d1a747d04a01d,https://ieeexplore.ieee.org/document/6190123/
3037,"We review network formation models, contrast their behavior, and conduct numerical experiments to investigate the structural features of the networks they generate. We focus primarily on problems related to minimum spanning trees and consider the cost of selfish behavior, more commonly known as the price of anarchy, in network formation. We also explore differences between local, decentralized methods for network formation and their global, centralized counterparts.",deanne mcpherson,Robustness,2011.0,10.1109/ACSSC.2011.6190123,"2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)",McPherson2011,False,,IEEE,Not available,A contrasting look at network formation models and their application to the minimum spanning tree,445db4ee8bb6562e142d1a747d04a01d,https://ieeexplore.ieee.org/document/6190123/
3038,"We review network formation models, contrast their behavior, and conduct numerical experiments to investigate the structural features of the networks they generate. We focus primarily on problems related to minimum spanning trees and consider the cost of selfish behavior, more commonly known as the price of anarchy, in network formation. We also explore differences between local, decentralized methods for network formation and their global, centralized counterparts.",david alderson,Biological system modeling,2011.0,10.1109/ACSSC.2011.6190123,"2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)",McPherson2011,False,,IEEE,Not available,A contrasting look at network formation models and their application to the minimum spanning tree,445db4ee8bb6562e142d1a747d04a01d,https://ieeexplore.ieee.org/document/6190123/
3039,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
3040,"We review network formation models, contrast their behavior, and conduct numerical experiments to investigate the structural features of the networks they generate. We focus primarily on problems related to minimum spanning trees and consider the cost of selfish behavior, more commonly known as the price of anarchy, in network formation. We also explore differences between local, decentralized methods for network formation and their global, centralized counterparts.",david alderson,Games,2011.0,10.1109/ACSSC.2011.6190123,"2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)",McPherson2011,False,,IEEE,Not available,A contrasting look at network formation models and their application to the minimum spanning tree,445db4ee8bb6562e142d1a747d04a01d,https://ieeexplore.ieee.org/document/6190123/
3041,"We review network formation models, contrast their behavior, and conduct numerical experiments to investigate the structural features of the networks they generate. We focus primarily on problems related to minimum spanning trees and consider the cost of selfish behavior, more commonly known as the price of anarchy, in network formation. We also explore differences between local, decentralized methods for network formation and their global, centralized counterparts.",david alderson,Numerical models,2011.0,10.1109/ACSSC.2011.6190123,"2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)",McPherson2011,False,,IEEE,Not available,A contrasting look at network formation models and their application to the minimum spanning tree,445db4ee8bb6562e142d1a747d04a01d,https://ieeexplore.ieee.org/document/6190123/
3042,"We review network formation models, contrast their behavior, and conduct numerical experiments to investigate the structural features of the networks they generate. We focus primarily on problems related to minimum spanning trees and consider the cost of selfish behavior, more commonly known as the price of anarchy, in network formation. We also explore differences between local, decentralized methods for network formation and their global, centralized counterparts.",david alderson,Nash equilibrium,2011.0,10.1109/ACSSC.2011.6190123,"2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)",McPherson2011,False,,IEEE,Not available,A contrasting look at network formation models and their application to the minimum spanning tree,445db4ee8bb6562e142d1a747d04a01d,https://ieeexplore.ieee.org/document/6190123/
3043,"We review network formation models, contrast their behavior, and conduct numerical experiments to investigate the structural features of the networks they generate. We focus primarily on problems related to minimum spanning trees and consider the cost of selfish behavior, more commonly known as the price of anarchy, in network formation. We also explore differences between local, decentralized methods for network formation and their global, centralized counterparts.",david alderson,Internet,2011.0,10.1109/ACSSC.2011.6190123,"2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)",McPherson2011,False,,IEEE,Not available,A contrasting look at network formation models and their application to the minimum spanning tree,445db4ee8bb6562e142d1a747d04a01d,https://ieeexplore.ieee.org/document/6190123/
3044,"We review network formation models, contrast their behavior, and conduct numerical experiments to investigate the structural features of the networks they generate. We focus primarily on problems related to minimum spanning trees and consider the cost of selfish behavior, more commonly known as the price of anarchy, in network formation. We also explore differences between local, decentralized methods for network formation and their global, centralized counterparts.",david alderson,Optimization,2011.0,10.1109/ACSSC.2011.6190123,"2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)",McPherson2011,False,,IEEE,Not available,A contrasting look at network formation models and their application to the minimum spanning tree,445db4ee8bb6562e142d1a747d04a01d,https://ieeexplore.ieee.org/document/6190123/
3045,"We review network formation models, contrast their behavior, and conduct numerical experiments to investigate the structural features of the networks they generate. We focus primarily on problems related to minimum spanning trees and consider the cost of selfish behavior, more commonly known as the price of anarchy, in network formation. We also explore differences between local, decentralized methods for network formation and their global, centralized counterparts.",david alderson,Robustness,2011.0,10.1109/ACSSC.2011.6190123,"2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)",McPherson2011,False,,IEEE,Not available,A contrasting look at network formation models and their application to the minimum spanning tree,445db4ee8bb6562e142d1a747d04a01d,https://ieeexplore.ieee.org/document/6190123/
3046,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",ahmed alaa,Cognitive networking,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
3047,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",ahmed alaa,cognitive agents,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
3048,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",ahmed alaa,information networks,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
3049,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",ahmed alaa,network formation,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
3050,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
3051,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",ahmed alaa,self-organizing networks,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
3052,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",ahmed alaa,Cognitive networking,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
3053,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",ahmed alaa,cognitive agents,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
3054,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",ahmed alaa,information networks,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
3055,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",ahmed alaa,network formation,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
3056,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",ahmed alaa,self-organizing networks,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
3057,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",kartik ahuja,Cognitive networking,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
3058,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",kartik ahuja,cognitive agents,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
3059,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",kartik ahuja,information networks,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
3060,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",kartik ahuja,network formation,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
3061,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
3062,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",kartik ahuja,self-organizing networks,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
3063,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",kartik ahuja,Cognitive networking,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
3064,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",kartik ahuja,cognitive agents,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
3065,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",kartik ahuja,information networks,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
3066,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",kartik ahuja,network formation,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
3067,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",kartik ahuja,self-organizing networks,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
3068,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",mihaela schaar,Cognitive networking,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
3069,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",mihaela schaar,cognitive agents,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
3070,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",mihaela schaar,information networks,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
3071,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",mihaela schaar,network formation,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
3072,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
3073,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
3074,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",mihaela schaar,self-organizing networks,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
3075,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",mihaela schaar,Cognitive networking,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
3076,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",mihaela schaar,cognitive agents,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
3077,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",mihaela schaar,information networks,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
3078,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",mihaela schaar,network formation,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
3079,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",mihaela schaar,self-organizing networks,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
3080,"Renewable energy continues to increase its share of total US electricity production at a dramatic rate. Power derived from such resources is inherently variable and naturally incurs a balancing cost to the power system. A basic question we aim to address in this paper is, given a collection of variable energy producers, how to disentangle the individual sources of cost causation from the aggregate system cost and allocate it back to those responsible parties, so as to induce a near efficient outcome in the forward market for energy. In particular, we propose an ex post cost sharing mechanism, satisfying certain fairness axioms, to allocate to each player a share of the total system cost in proportion to her relative contribution to the aggregate system imbalance. We establish the existence and certain properties of Nash equilibria of the forward contract game under proportional cost sharing and provide an explicit characterization for the Price of Anarchy (PoA) as the number of participants in the market grows large. We also characterize a family of `worst case' prior distributions on the supply profile at which the asymptotic PoA is maximized.",weixuan lin,Renewable Energy,2014.0,10.1109/CDC.2014.7039645,53rd IEEE Conference on Decision and Control,Lin2014,False,,IEEE,Not available,Forward electricity markets with uncertain supply: Cost sharing and efficiency loss,0dd44b6f327d72e8d22639abc523a2c6,https://ieeexplore.ieee.org/document/7039645/
3081,"Renewable energy continues to increase its share of total US electricity production at a dramatic rate. Power derived from such resources is inherently variable and naturally incurs a balancing cost to the power system. A basic question we aim to address in this paper is, given a collection of variable energy producers, how to disentangle the individual sources of cost causation from the aggregate system cost and allocate it back to those responsible parties, so as to induce a near efficient outcome in the forward market for energy. In particular, we propose an ex post cost sharing mechanism, satisfying certain fairness axioms, to allocate to each player a share of the total system cost in proportion to her relative contribution to the aggregate system imbalance. We establish the existence and certain properties of Nash equilibria of the forward contract game under proportional cost sharing and provide an explicit characterization for the Price of Anarchy (PoA) as the number of participants in the market grows large. We also characterize a family of `worst case' prior distributions on the supply profile at which the asymptotic PoA is maximized.",weixuan lin,Cost Sharing Mechanisms,2014.0,10.1109/CDC.2014.7039645,53rd IEEE Conference on Decision and Control,Lin2014,False,,IEEE,Not available,Forward electricity markets with uncertain supply: Cost sharing and efficiency loss,0dd44b6f327d72e8d22639abc523a2c6,https://ieeexplore.ieee.org/document/7039645/
3082,"Renewable energy continues to increase its share of total US electricity production at a dramatic rate. Power derived from such resources is inherently variable and naturally incurs a balancing cost to the power system. A basic question we aim to address in this paper is, given a collection of variable energy producers, how to disentangle the individual sources of cost causation from the aggregate system cost and allocate it back to those responsible parties, so as to induce a near efficient outcome in the forward market for energy. In particular, we propose an ex post cost sharing mechanism, satisfying certain fairness axioms, to allocate to each player a share of the total system cost in proportion to her relative contribution to the aggregate system imbalance. We establish the existence and certain properties of Nash equilibria of the forward contract game under proportional cost sharing and provide an explicit characterization for the Price of Anarchy (PoA) as the number of participants in the market grows large. We also characterize a family of `worst case' prior distributions on the supply profile at which the asymptotic PoA is maximized.",weixuan lin,Electricity Markets,2014.0,10.1109/CDC.2014.7039645,53rd IEEE Conference on Decision and Control,Lin2014,False,,IEEE,Not available,Forward electricity markets with uncertain supply: Cost sharing and efficiency loss,0dd44b6f327d72e8d22639abc523a2c6,https://ieeexplore.ieee.org/document/7039645/
3083,"Renewable energy continues to increase its share of total US electricity production at a dramatic rate. Power derived from such resources is inherently variable and naturally incurs a balancing cost to the power system. A basic question we aim to address in this paper is, given a collection of variable energy producers, how to disentangle the individual sources of cost causation from the aggregate system cost and allocate it back to those responsible parties, so as to induce a near efficient outcome in the forward market for energy. In particular, we propose an ex post cost sharing mechanism, satisfying certain fairness axioms, to allocate to each player a share of the total system cost in proportion to her relative contribution to the aggregate system imbalance. We establish the existence and certain properties of Nash equilibria of the forward contract game under proportional cost sharing and provide an explicit characterization for the Price of Anarchy (PoA) as the number of participants in the market grows large. We also characterize a family of `worst case' prior distributions on the supply profile at which the asymptotic PoA is maximized.",eilyan bitar,Renewable Energy,2014.0,10.1109/CDC.2014.7039645,53rd IEEE Conference on Decision and Control,Lin2014,False,,IEEE,Not available,Forward electricity markets with uncertain supply: Cost sharing and efficiency loss,0dd44b6f327d72e8d22639abc523a2c6,https://ieeexplore.ieee.org/document/7039645/
3084,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
3085,"Renewable energy continues to increase its share of total US electricity production at a dramatic rate. Power derived from such resources is inherently variable and naturally incurs a balancing cost to the power system. A basic question we aim to address in this paper is, given a collection of variable energy producers, how to disentangle the individual sources of cost causation from the aggregate system cost and allocate it back to those responsible parties, so as to induce a near efficient outcome in the forward market for energy. In particular, we propose an ex post cost sharing mechanism, satisfying certain fairness axioms, to allocate to each player a share of the total system cost in proportion to her relative contribution to the aggregate system imbalance. We establish the existence and certain properties of Nash equilibria of the forward contract game under proportional cost sharing and provide an explicit characterization for the Price of Anarchy (PoA) as the number of participants in the market grows large. We also characterize a family of `worst case' prior distributions on the supply profile at which the asymptotic PoA is maximized.",eilyan bitar,Cost Sharing Mechanisms,2014.0,10.1109/CDC.2014.7039645,53rd IEEE Conference on Decision and Control,Lin2014,False,,IEEE,Not available,Forward electricity markets with uncertain supply: Cost sharing and efficiency loss,0dd44b6f327d72e8d22639abc523a2c6,https://ieeexplore.ieee.org/document/7039645/
3086,"Renewable energy continues to increase its share of total US electricity production at a dramatic rate. Power derived from such resources is inherently variable and naturally incurs a balancing cost to the power system. A basic question we aim to address in this paper is, given a collection of variable energy producers, how to disentangle the individual sources of cost causation from the aggregate system cost and allocate it back to those responsible parties, so as to induce a near efficient outcome in the forward market for energy. In particular, we propose an ex post cost sharing mechanism, satisfying certain fairness axioms, to allocate to each player a share of the total system cost in proportion to her relative contribution to the aggregate system imbalance. We establish the existence and certain properties of Nash equilibria of the forward contract game under proportional cost sharing and provide an explicit characterization for the Price of Anarchy (PoA) as the number of participants in the market grows large. We also characterize a family of `worst case' prior distributions on the supply profile at which the asymptotic PoA is maximized.",eilyan bitar,Electricity Markets,2014.0,10.1109/CDC.2014.7039645,53rd IEEE Conference on Decision and Control,Lin2014,False,,IEEE,Not available,Forward electricity markets with uncertain supply: Cost sharing and efficiency loss,0dd44b6f327d72e8d22639abc523a2c6,https://ieeexplore.ieee.org/document/7039645/
3087,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",yezekael hayel,Games,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
3088,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",yezekael hayel,Approximation methods,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
3089,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",yezekael hayel,Investment,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
3090,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",yezekael hayel,Nash equilibrium,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
3091,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",yezekael hayel,Optimized production technology,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
3092,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",yezekael hayel,Upper bound,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
3093,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",yezekael hayel,Communities,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
3094,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",stojan trajanovski,Games,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
3095,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
3096,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",stojan trajanovski,Approximation methods,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
3097,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",stojan trajanovski,Investment,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
3098,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",stojan trajanovski,Nash equilibrium,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
3099,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",stojan trajanovski,Optimized production technology,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
3100,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",stojan trajanovski,Upper bound,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
3101,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",stojan trajanovski,Communities,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
3102,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",eitan altman,Games,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
3103,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",eitan altman,Approximation methods,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
3104,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",eitan altman,Investment,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
3105,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",eitan altman,Nash equilibrium,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
3106,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
3107,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",eitan altman,Optimized production technology,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
3108,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",eitan altman,Upper bound,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
3109,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",eitan altman,Communities,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
3110,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",huijuan wang,Games,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
3111,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",huijuan wang,Approximation methods,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
3112,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",huijuan wang,Investment,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
3113,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",huijuan wang,Nash equilibrium,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
3114,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",huijuan wang,Optimized production technology,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
3115,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",huijuan wang,Upper bound,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
3116,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",huijuan wang,Communities,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
3117,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
3118,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",piet mieghem,Games,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
3119,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",piet mieghem,Approximation methods,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
3120,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",piet mieghem,Investment,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
3121,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",piet mieghem,Nash equilibrium,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
3122,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",piet mieghem,Optimized production technology,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
3123,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",piet mieghem,Upper bound,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
3124,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",piet mieghem,Communities,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
3125,"This paper studies the problem of non-cooperative joint channel and bandwidth allocations in multi-radio multichannel wireless networks. Existing works only studied non-cooperative multi-radio channel allocation and they did not consider two important issues, impact of traffic load to channel's transmission quality, and difference of bandwidth demands for different node pairs, which may have significant impact on the modeling and designing solutions. To address these two issues, we extend the problem of non-cooperative multi-radio channel allocation to Non-cooperative Joint Channel and Bandwidth Allocation problem (NJCBA). In the NJCBA problem, node pairs need to consider not only allocating radios to channels, but also allocating bandwidth to selected channels to maximize its own benefit. To the best of our knowledge, we are the first to study the NJCBA problem in multi-radio multi-channel wireless networks. We model the problem as a non-cooperative game, denoted by NJCBA game. Using the best response concept, we prove that there exist pure Nash Equilibriums (NEs) for the NJCBA game, which means that NJCBA can converge to a stable state. We also analyze the efficiency of the NEs for NJCBA game, and prove that these NEs can achieve a constant Price Of Anarchy (POA) in the heavy-load network. Here, POA denotes the ratio between the sum of the payoffs of all players in a globally optimal solution and the sum of the payoffs achieved in a worst-case NE. We design a distributed algorithm, denoted by NE Convergence (NEC) algorithm, to enable node pairs to converge to a pure NE. The NEC algorithm is evaluated through extensive simulations. The results show that NEC algorithms can improve the system throughput by 2 or 3 times compared with a greedy allocation algorithm.",wei feng,Game Theory,2011.0,10.1109/WCNC.2011.5779215,2011 IEEE Wireless Communications and Networking Conference,Feng2011,False,,IEEE,Not available,Non-cooperative quality-aware channel and bandwidth allocations in multi-radio multi-channel wireless networks,410b0604f9b53b68d708418580b5fa3f,https://ieeexplore.ieee.org/document/5779215/
3126,"This paper studies the problem of non-cooperative joint channel and bandwidth allocations in multi-radio multichannel wireless networks. Existing works only studied non-cooperative multi-radio channel allocation and they did not consider two important issues, impact of traffic load to channel's transmission quality, and difference of bandwidth demands for different node pairs, which may have significant impact on the modeling and designing solutions. To address these two issues, we extend the problem of non-cooperative multi-radio channel allocation to Non-cooperative Joint Channel and Bandwidth Allocation problem (NJCBA). In the NJCBA problem, node pairs need to consider not only allocating radios to channels, but also allocating bandwidth to selected channels to maximize its own benefit. To the best of our knowledge, we are the first to study the NJCBA problem in multi-radio multi-channel wireless networks. We model the problem as a non-cooperative game, denoted by NJCBA game. Using the best response concept, we prove that there exist pure Nash Equilibriums (NEs) for the NJCBA game, which means that NJCBA can converge to a stable state. We also analyze the efficiency of the NEs for NJCBA game, and prove that these NEs can achieve a constant Price Of Anarchy (POA) in the heavy-load network. Here, POA denotes the ratio between the sum of the payoffs of all players in a globally optimal solution and the sum of the payoffs achieved in a worst-case NE. We design a distributed algorithm, denoted by NE Convergence (NEC) algorithm, to enable node pairs to converge to a pure NE. The NEC algorithm is evaluated through extensive simulations. The results show that NEC algorithms can improve the system throughput by 2 or 3 times compared with a greedy allocation algorithm.",wei feng,Channel and Bandwidth Allocaiton,2011.0,10.1109/WCNC.2011.5779215,2011 IEEE Wireless Communications and Networking Conference,Feng2011,False,,IEEE,Not available,Non-cooperative quality-aware channel and bandwidth allocations in multi-radio multi-channel wireless networks,410b0604f9b53b68d708418580b5fa3f,https://ieeexplore.ieee.org/document/5779215/
3127,"This paper studies the problem of non-cooperative joint channel and bandwidth allocations in multi-radio multichannel wireless networks. Existing works only studied non-cooperative multi-radio channel allocation and they did not consider two important issues, impact of traffic load to channel's transmission quality, and difference of bandwidth demands for different node pairs, which may have significant impact on the modeling and designing solutions. To address these two issues, we extend the problem of non-cooperative multi-radio channel allocation to Non-cooperative Joint Channel and Bandwidth Allocation problem (NJCBA). In the NJCBA problem, node pairs need to consider not only allocating radios to channels, but also allocating bandwidth to selected channels to maximize its own benefit. To the best of our knowledge, we are the first to study the NJCBA problem in multi-radio multi-channel wireless networks. We model the problem as a non-cooperative game, denoted by NJCBA game. Using the best response concept, we prove that there exist pure Nash Equilibriums (NEs) for the NJCBA game, which means that NJCBA can converge to a stable state. We also analyze the efficiency of the NEs for NJCBA game, and prove that these NEs can achieve a constant Price Of Anarchy (POA) in the heavy-load network. Here, POA denotes the ratio between the sum of the payoffs of all players in a globally optimal solution and the sum of the payoffs achieved in a worst-case NE. We design a distributed algorithm, denoted by NE Convergence (NEC) algorithm, to enable node pairs to converge to a pure NE. The NEC algorithm is evaluated through extensive simulations. The results show that NEC algorithms can improve the system throughput by 2 or 3 times compared with a greedy allocation algorithm.",wei feng,Multi-Radio Multi-Channel,2011.0,10.1109/WCNC.2011.5779215,2011 IEEE Wireless Communications and Networking Conference,Feng2011,False,,IEEE,Not available,Non-cooperative quality-aware channel and bandwidth allocations in multi-radio multi-channel wireless networks,410b0604f9b53b68d708418580b5fa3f,https://ieeexplore.ieee.org/document/5779215/
3128,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
3129,"This paper studies the problem of non-cooperative joint channel and bandwidth allocations in multi-radio multichannel wireless networks. Existing works only studied non-cooperative multi-radio channel allocation and they did not consider two important issues, impact of traffic load to channel's transmission quality, and difference of bandwidth demands for different node pairs, which may have significant impact on the modeling and designing solutions. To address these two issues, we extend the problem of non-cooperative multi-radio channel allocation to Non-cooperative Joint Channel and Bandwidth Allocation problem (NJCBA). In the NJCBA problem, node pairs need to consider not only allocating radios to channels, but also allocating bandwidth to selected channels to maximize its own benefit. To the best of our knowledge, we are the first to study the NJCBA problem in multi-radio multi-channel wireless networks. We model the problem as a non-cooperative game, denoted by NJCBA game. Using the best response concept, we prove that there exist pure Nash Equilibriums (NEs) for the NJCBA game, which means that NJCBA can converge to a stable state. We also analyze the efficiency of the NEs for NJCBA game, and prove that these NEs can achieve a constant Price Of Anarchy (POA) in the heavy-load network. Here, POA denotes the ratio between the sum of the payoffs of all players in a globally optimal solution and the sum of the payoffs achieved in a worst-case NE. We design a distributed algorithm, denoted by NE Convergence (NEC) algorithm, to enable node pairs to converge to a pure NE. The NEC algorithm is evaluated through extensive simulations. The results show that NEC algorithms can improve the system throughput by 2 or 3 times compared with a greedy allocation algorithm.",jiannong cao,Game Theory,2011.0,10.1109/WCNC.2011.5779215,2011 IEEE Wireless Communications and Networking Conference,Feng2011,False,,IEEE,Not available,Non-cooperative quality-aware channel and bandwidth allocations in multi-radio multi-channel wireless networks,410b0604f9b53b68d708418580b5fa3f,https://ieeexplore.ieee.org/document/5779215/
3130,"This paper studies the problem of non-cooperative joint channel and bandwidth allocations in multi-radio multichannel wireless networks. Existing works only studied non-cooperative multi-radio channel allocation and they did not consider two important issues, impact of traffic load to channel's transmission quality, and difference of bandwidth demands for different node pairs, which may have significant impact on the modeling and designing solutions. To address these two issues, we extend the problem of non-cooperative multi-radio channel allocation to Non-cooperative Joint Channel and Bandwidth Allocation problem (NJCBA). In the NJCBA problem, node pairs need to consider not only allocating radios to channels, but also allocating bandwidth to selected channels to maximize its own benefit. To the best of our knowledge, we are the first to study the NJCBA problem in multi-radio multi-channel wireless networks. We model the problem as a non-cooperative game, denoted by NJCBA game. Using the best response concept, we prove that there exist pure Nash Equilibriums (NEs) for the NJCBA game, which means that NJCBA can converge to a stable state. We also analyze the efficiency of the NEs for NJCBA game, and prove that these NEs can achieve a constant Price Of Anarchy (POA) in the heavy-load network. Here, POA denotes the ratio between the sum of the payoffs of all players in a globally optimal solution and the sum of the payoffs achieved in a worst-case NE. We design a distributed algorithm, denoted by NE Convergence (NEC) algorithm, to enable node pairs to converge to a pure NE. The NEC algorithm is evaluated through extensive simulations. The results show that NEC algorithms can improve the system throughput by 2 or 3 times compared with a greedy allocation algorithm.",jiannong cao,Channel and Bandwidth Allocaiton,2011.0,10.1109/WCNC.2011.5779215,2011 IEEE Wireless Communications and Networking Conference,Feng2011,False,,IEEE,Not available,Non-cooperative quality-aware channel and bandwidth allocations in multi-radio multi-channel wireless networks,410b0604f9b53b68d708418580b5fa3f,https://ieeexplore.ieee.org/document/5779215/
3131,"This paper studies the problem of non-cooperative joint channel and bandwidth allocations in multi-radio multichannel wireless networks. Existing works only studied non-cooperative multi-radio channel allocation and they did not consider two important issues, impact of traffic load to channel's transmission quality, and difference of bandwidth demands for different node pairs, which may have significant impact on the modeling and designing solutions. To address these two issues, we extend the problem of non-cooperative multi-radio channel allocation to Non-cooperative Joint Channel and Bandwidth Allocation problem (NJCBA). In the NJCBA problem, node pairs need to consider not only allocating radios to channels, but also allocating bandwidth to selected channels to maximize its own benefit. To the best of our knowledge, we are the first to study the NJCBA problem in multi-radio multi-channel wireless networks. We model the problem as a non-cooperative game, denoted by NJCBA game. Using the best response concept, we prove that there exist pure Nash Equilibriums (NEs) for the NJCBA game, which means that NJCBA can converge to a stable state. We also analyze the efficiency of the NEs for NJCBA game, and prove that these NEs can achieve a constant Price Of Anarchy (POA) in the heavy-load network. Here, POA denotes the ratio between the sum of the payoffs of all players in a globally optimal solution and the sum of the payoffs achieved in a worst-case NE. We design a distributed algorithm, denoted by NE Convergence (NEC) algorithm, to enable node pairs to converge to a pure NE. The NEC algorithm is evaluated through extensive simulations. The results show that NEC algorithms can improve the system throughput by 2 or 3 times compared with a greedy allocation algorithm.",jiannong cao,Multi-Radio Multi-Channel,2011.0,10.1109/WCNC.2011.5779215,2011 IEEE Wireless Communications and Networking Conference,Feng2011,False,,IEEE,Not available,Non-cooperative quality-aware channel and bandwidth allocations in multi-radio multi-channel wireless networks,410b0604f9b53b68d708418580b5fa3f,https://ieeexplore.ieee.org/document/5779215/
3132,"This paper studies the problem of non-cooperative joint channel and bandwidth allocations in multi-radio multichannel wireless networks. Existing works only studied non-cooperative multi-radio channel allocation and they did not consider two important issues, impact of traffic load to channel's transmission quality, and difference of bandwidth demands for different node pairs, which may have significant impact on the modeling and designing solutions. To address these two issues, we extend the problem of non-cooperative multi-radio channel allocation to Non-cooperative Joint Channel and Bandwidth Allocation problem (NJCBA). In the NJCBA problem, node pairs need to consider not only allocating radios to channels, but also allocating bandwidth to selected channels to maximize its own benefit. To the best of our knowledge, we are the first to study the NJCBA problem in multi-radio multi-channel wireless networks. We model the problem as a non-cooperative game, denoted by NJCBA game. Using the best response concept, we prove that there exist pure Nash Equilibriums (NEs) for the NJCBA game, which means that NJCBA can converge to a stable state. We also analyze the efficiency of the NEs for NJCBA game, and prove that these NEs can achieve a constant Price Of Anarchy (POA) in the heavy-load network. Here, POA denotes the ratio between the sum of the payoffs of all players in a globally optimal solution and the sum of the payoffs achieved in a worst-case NE. We design a distributed algorithm, denoted by NE Convergence (NEC) algorithm, to enable node pairs to converge to a pure NE. The NEC algorithm is evaluated through extensive simulations. The results show that NEC algorithms can improve the system throughput by 2 or 3 times compared with a greedy allocation algorithm.",liang yang,Game Theory,2011.0,10.1109/WCNC.2011.5779215,2011 IEEE Wireless Communications and Networking Conference,Feng2011,False,,IEEE,Not available,Non-cooperative quality-aware channel and bandwidth allocations in multi-radio multi-channel wireless networks,410b0604f9b53b68d708418580b5fa3f,https://ieeexplore.ieee.org/document/5779215/
3133,"This paper studies the problem of non-cooperative joint channel and bandwidth allocations in multi-radio multichannel wireless networks. Existing works only studied non-cooperative multi-radio channel allocation and they did not consider two important issues, impact of traffic load to channel's transmission quality, and difference of bandwidth demands for different node pairs, which may have significant impact on the modeling and designing solutions. To address these two issues, we extend the problem of non-cooperative multi-radio channel allocation to Non-cooperative Joint Channel and Bandwidth Allocation problem (NJCBA). In the NJCBA problem, node pairs need to consider not only allocating radios to channels, but also allocating bandwidth to selected channels to maximize its own benefit. To the best of our knowledge, we are the first to study the NJCBA problem in multi-radio multi-channel wireless networks. We model the problem as a non-cooperative game, denoted by NJCBA game. Using the best response concept, we prove that there exist pure Nash Equilibriums (NEs) for the NJCBA game, which means that NJCBA can converge to a stable state. We also analyze the efficiency of the NEs for NJCBA game, and prove that these NEs can achieve a constant Price Of Anarchy (POA) in the heavy-load network. Here, POA denotes the ratio between the sum of the payoffs of all players in a globally optimal solution and the sum of the payoffs achieved in a worst-case NE. We design a distributed algorithm, denoted by NE Convergence (NEC) algorithm, to enable node pairs to converge to a pure NE. The NEC algorithm is evaluated through extensive simulations. The results show that NEC algorithms can improve the system throughput by 2 or 3 times compared with a greedy allocation algorithm.",liang yang,Channel and Bandwidth Allocaiton,2011.0,10.1109/WCNC.2011.5779215,2011 IEEE Wireless Communications and Networking Conference,Feng2011,False,,IEEE,Not available,Non-cooperative quality-aware channel and bandwidth allocations in multi-radio multi-channel wireless networks,410b0604f9b53b68d708418580b5fa3f,https://ieeexplore.ieee.org/document/5779215/
3134,"This paper studies the problem of non-cooperative joint channel and bandwidth allocations in multi-radio multichannel wireless networks. Existing works only studied non-cooperative multi-radio channel allocation and they did not consider two important issues, impact of traffic load to channel's transmission quality, and difference of bandwidth demands for different node pairs, which may have significant impact on the modeling and designing solutions. To address these two issues, we extend the problem of non-cooperative multi-radio channel allocation to Non-cooperative Joint Channel and Bandwidth Allocation problem (NJCBA). In the NJCBA problem, node pairs need to consider not only allocating radios to channels, but also allocating bandwidth to selected channels to maximize its own benefit. To the best of our knowledge, we are the first to study the NJCBA problem in multi-radio multi-channel wireless networks. We model the problem as a non-cooperative game, denoted by NJCBA game. Using the best response concept, we prove that there exist pure Nash Equilibriums (NEs) for the NJCBA game, which means that NJCBA can converge to a stable state. We also analyze the efficiency of the NEs for NJCBA game, and prove that these NEs can achieve a constant Price Of Anarchy (POA) in the heavy-load network. Here, POA denotes the ratio between the sum of the payoffs of all players in a globally optimal solution and the sum of the payoffs achieved in a worst-case NE. We design a distributed algorithm, denoted by NE Convergence (NEC) algorithm, to enable node pairs to converge to a pure NE. The NEC algorithm is evaluated through extensive simulations. The results show that NEC algorithms can improve the system throughput by 2 or 3 times compared with a greedy allocation algorithm.",liang yang,Multi-Radio Multi-Channel,2011.0,10.1109/WCNC.2011.5779215,2011 IEEE Wireless Communications and Networking Conference,Feng2011,False,,IEEE,Not available,Non-cooperative quality-aware channel and bandwidth allocations in multi-radio multi-channel wireless networks,410b0604f9b53b68d708418580b5fa3f,https://ieeexplore.ieee.org/document/5779215/
3135,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ahmed abdulla,Unmanned Aircraft System (UAS)-aided networks,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3136,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ahmed abdulla,energy efficiency,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3137,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ahmed abdulla,throughput per energy,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3138,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ahmed abdulla,fairness,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3139,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
3140,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ahmed abdulla,adaptive modulation,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3141,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ahmed abdulla,game theory,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3142,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ahmed abdulla,wireless network optimization,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3143,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",zubair fadlullah,Unmanned Aircraft System (UAS)-aided networks,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3144,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",zubair fadlullah,energy efficiency,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3145,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",zubair fadlullah,throughput per energy,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3146,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",zubair fadlullah,fairness,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3147,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",zubair fadlullah,adaptive modulation,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3148,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",zubair fadlullah,game theory,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3149,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",zubair fadlullah,wireless network optimization,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3150,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
3151,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",hiroki nishiyama,Unmanned Aircraft System (UAS)-aided networks,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3152,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",hiroki nishiyama,energy efficiency,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3153,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",hiroki nishiyama,throughput per energy,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3154,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",hiroki nishiyama,fairness,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3155,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",hiroki nishiyama,adaptive modulation,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3156,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",hiroki nishiyama,game theory,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3157,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",hiroki nishiyama,wireless network optimization,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3158,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",nei kato,Unmanned Aircraft System (UAS)-aided networks,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3159,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",nei kato,energy efficiency,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3160,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",nei kato,throughput per energy,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3161,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
3162,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",nei kato,fairness,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3163,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",nei kato,adaptive modulation,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3164,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",nei kato,game theory,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3165,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",nei kato,wireless network optimization,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3166,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",fumie ono,Unmanned Aircraft System (UAS)-aided networks,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3167,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",fumie ono,energy efficiency,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3168,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",fumie ono,throughput per energy,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3169,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",fumie ono,fairness,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3170,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",fumie ono,adaptive modulation,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3171,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",fumie ono,game theory,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3172,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
3173,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",fumie ono,wireless network optimization,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3174,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ryu miura,Unmanned Aircraft System (UAS)-aided networks,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3175,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ryu miura,energy efficiency,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3176,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ryu miura,throughput per energy,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3177,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ryu miura,fairness,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3178,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ryu miura,adaptive modulation,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3179,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ryu miura,game theory,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3180,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ryu miura,wireless network optimization,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
3181,"Queueing networks are typically analyzed assuming that the arrival process is exogenous, and unaffected by admission control, scheduling policies, etc. In many situations arriving users are strategic, and do time their arrivals taking delay and other metrics into account. This paper builds on, and extends the framework developed to a network setting. We first consider just a single population of users arriving into two queues in parallel (they can join either queue). The queues start serving at different times. We characterize the arrival process into both queues and the Price of Anarchy with strategic arrivals. We then extend this when there are multiple populations, each with different cost metrics. The whole analysis is done in the fluid limit.",harsha honnappa,Strategic arrivals,2010.0,10.1109/ALLERTON.2010.5706993,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Honnappa2010,False,,IEEE,Not available,Strategic arrivals into queueing networks,5b5adbba2f2ba0c09bc8a937d331c4e3,https://ieeexplore.ieee.org/document/5706993/
3182,"Queueing networks are typically analyzed assuming that the arrival process is exogenous, and unaffected by admission control, scheduling policies, etc. In many situations arriving users are strategic, and do time their arrivals taking delay and other metrics into account. This paper builds on, and extends the framework developed to a network setting. We first consider just a single population of users arriving into two queues in parallel (they can join either queue). The queues start serving at different times. We characterize the arrival process into both queues and the Price of Anarchy with strategic arrivals. We then extend this when there are multiple populations, each with different cost metrics. The whole analysis is done in the fluid limit.",harsha honnappa,Population games,2010.0,10.1109/ALLERTON.2010.5706993,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Honnappa2010,False,,IEEE,Not available,Strategic arrivals into queueing networks,5b5adbba2f2ba0c09bc8a937d331c4e3,https://ieeexplore.ieee.org/document/5706993/
3183,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
3184,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
3185,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
3186,"Queueing networks are typically analyzed assuming that the arrival process is exogenous, and unaffected by admission control, scheduling policies, etc. In many situations arriving users are strategic, and do time their arrivals taking delay and other metrics into account. This paper builds on, and extends the framework developed to a network setting. We first consider just a single population of users arriving into two queues in parallel (they can join either queue). The queues start serving at different times. We characterize the arrival process into both queues and the Price of Anarchy with strategic arrivals. We then extend this when there are multiple populations, each with different cost metrics. The whole analysis is done in the fluid limit.",harsha honnappa,Game theory,2010.0,10.1109/ALLERTON.2010.5706993,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Honnappa2010,False,,IEEE,Not available,Strategic arrivals into queueing networks,5b5adbba2f2ba0c09bc8a937d331c4e3,https://ieeexplore.ieee.org/document/5706993/
3187,"Queueing networks are typically analyzed assuming that the arrival process is exogenous, and unaffected by admission control, scheduling policies, etc. In many situations arriving users are strategic, and do time their arrivals taking delay and other metrics into account. This paper builds on, and extends the framework developed to a network setting. We first consider just a single population of users arriving into two queues in parallel (they can join either queue). The queues start serving at different times. We characterize the arrival process into both queues and the Price of Anarchy with strategic arrivals. We then extend this when there are multiple populations, each with different cost metrics. The whole analysis is done in the fluid limit.",harsha honnappa,Queueing Networks,2010.0,10.1109/ALLERTON.2010.5706993,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Honnappa2010,False,,IEEE,Not available,Strategic arrivals into queueing networks,5b5adbba2f2ba0c09bc8a937d331c4e3,https://ieeexplore.ieee.org/document/5706993/
3188,"Queueing networks are typically analyzed assuming that the arrival process is exogenous, and unaffected by admission control, scheduling policies, etc. In many situations arriving users are strategic, and do time their arrivals taking delay and other metrics into account. This paper builds on, and extends the framework developed to a network setting. We first consider just a single population of users arriving into two queues in parallel (they can join either queue). The queues start serving at different times. We characterize the arrival process into both queues and the Price of Anarchy with strategic arrivals. We then extend this when there are multiple populations, each with different cost metrics. The whole analysis is done in the fluid limit.",rahul jain,Strategic arrivals,2010.0,10.1109/ALLERTON.2010.5706993,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Honnappa2010,False,,IEEE,Not available,Strategic arrivals into queueing networks,5b5adbba2f2ba0c09bc8a937d331c4e3,https://ieeexplore.ieee.org/document/5706993/
3189,"Queueing networks are typically analyzed assuming that the arrival process is exogenous, and unaffected by admission control, scheduling policies, etc. In many situations arriving users are strategic, and do time their arrivals taking delay and other metrics into account. This paper builds on, and extends the framework developed to a network setting. We first consider just a single population of users arriving into two queues in parallel (they can join either queue). The queues start serving at different times. We characterize the arrival process into both queues and the Price of Anarchy with strategic arrivals. We then extend this when there are multiple populations, each with different cost metrics. The whole analysis is done in the fluid limit.",rahul jain,Population games,2010.0,10.1109/ALLERTON.2010.5706993,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Honnappa2010,False,,IEEE,Not available,Strategic arrivals into queueing networks,5b5adbba2f2ba0c09bc8a937d331c4e3,https://ieeexplore.ieee.org/document/5706993/
3190,"Queueing networks are typically analyzed assuming that the arrival process is exogenous, and unaffected by admission control, scheduling policies, etc. In many situations arriving users are strategic, and do time their arrivals taking delay and other metrics into account. This paper builds on, and extends the framework developed to a network setting. We first consider just a single population of users arriving into two queues in parallel (they can join either queue). The queues start serving at different times. We characterize the arrival process into both queues and the Price of Anarchy with strategic arrivals. We then extend this when there are multiple populations, each with different cost metrics. The whole analysis is done in the fluid limit.",rahul jain,Game theory,2010.0,10.1109/ALLERTON.2010.5706993,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Honnappa2010,False,,IEEE,Not available,Strategic arrivals into queueing networks,5b5adbba2f2ba0c09bc8a937d331c4e3,https://ieeexplore.ieee.org/document/5706993/
3191,"Queueing networks are typically analyzed assuming that the arrival process is exogenous, and unaffected by admission control, scheduling policies, etc. In many situations arriving users are strategic, and do time their arrivals taking delay and other metrics into account. This paper builds on, and extends the framework developed to a network setting. We first consider just a single population of users arriving into two queues in parallel (they can join either queue). The queues start serving at different times. We characterize the arrival process into both queues and the Price of Anarchy with strategic arrivals. We then extend this when there are multiple populations, each with different cost metrics. The whole analysis is done in the fluid limit.",rahul jain,Queueing Networks,2010.0,10.1109/ALLERTON.2010.5706993,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Honnappa2010,False,,IEEE,Not available,Strategic arrivals into queueing networks,5b5adbba2f2ba0c09bc8a937d331c4e3,https://ieeexplore.ieee.org/document/5706993/
3192,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",quansheng guan,Green communication networks,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
3193,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",quansheng guan,sleep scheduling algorithm,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
3194,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",quansheng guan,weighted cost sharing,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
3195,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",quansheng guan,approximate potential game,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
3196,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
3197,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",tianyu chen,Green communication networks,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
3198,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",tianyu chen,sleep scheduling algorithm,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
3199,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",tianyu chen,weighted cost sharing,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
3200,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",tianyu chen,approximate potential game,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
3201,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",shengming jiang,Green communication networks,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
3202,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",shengming jiang,sleep scheduling algorithm,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
3203,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",shengming jiang,weighted cost sharing,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
3204,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",shengming jiang,approximate potential game,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
3205,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",fei ji,Green communication networks,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
3206,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",fei ji,sleep scheduling algorithm,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
3207,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
3208,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",fei ji,weighted cost sharing,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
3209,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",fei ji,approximate potential game,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
3210,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",fangjiong chen,Green communication networks,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
3211,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",fangjiong chen,sleep scheduling algorithm,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
3212,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",fangjiong chen,weighted cost sharing,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
3213,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",fangjiong chen,approximate potential game,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
3214,"The purpose of this paper is to show how key concepts from control theory, game theory, and mean field theory can be exploited to design joint control-allocation policies in cognitive wireless networks. One of the key features of the proposed approach is that transmitters (which are assumed to be cognitive and autonomous decisionnally speaking) have a certain knowledge of the channel evolution law and want to reach a certain transmission rate target while minimizing the energy consumed by the power supply and not the one corresponding to radio-frequency signals (which is known to be important to design green wireless networks). The optimal centralized policy is derived in order to have an upper bound on the performance of the decentralized system. Then, the Nash equilibrium of the cognitive network is determined by using recent results from mean field theory (MFT). In order to evaluate the performance gap between decentralized and centralized policies we introduce and evaluate the MFT-based asymptotic price of anarchy (APoA).",hamidou tembine,Radio transmitters,2010.0,10.4108/ICST.CROWNCOM2010.9219,2010 Proceedings of the Fifth International Conference on Cognitive Radio Oriented Wireless Networks and Communications,Tembine2010,False,,IEEE,Not available,Joint power control-allocation for green cognitive wireless networks using mean field theory,a8ad7a5dd7b64f700329b584696f1929,https://ieeexplore.ieee.org/document/5577790/
3215,"The purpose of this paper is to show how key concepts from control theory, game theory, and mean field theory can be exploited to design joint control-allocation policies in cognitive wireless networks. One of the key features of the proposed approach is that transmitters (which are assumed to be cognitive and autonomous decisionnally speaking) have a certain knowledge of the channel evolution law and want to reach a certain transmission rate target while minimizing the energy consumed by the power supply and not the one corresponding to radio-frequency signals (which is known to be important to design green wireless networks). The optimal centralized policy is derived in order to have an upper bound on the performance of the decentralized system. Then, the Nash equilibrium of the cognitive network is determined by using recent results from mean field theory (MFT). In order to evaluate the performance gap between decentralized and centralized policies we introduce and evaluate the MFT-based asymptotic price of anarchy (APoA).",hamidou tembine,Resource management,2010.0,10.4108/ICST.CROWNCOM2010.9219,2010 Proceedings of the Fifth International Conference on Cognitive Radio Oriented Wireless Networks and Communications,Tembine2010,False,,IEEE,Not available,Joint power control-allocation for green cognitive wireless networks using mean field theory,a8ad7a5dd7b64f700329b584696f1929,https://ieeexplore.ieee.org/document/5577790/
3216,"The purpose of this paper is to show how key concepts from control theory, game theory, and mean field theory can be exploited to design joint control-allocation policies in cognitive wireless networks. One of the key features of the proposed approach is that transmitters (which are assumed to be cognitive and autonomous decisionnally speaking) have a certain knowledge of the channel evolution law and want to reach a certain transmission rate target while minimizing the energy consumed by the power supply and not the one corresponding to radio-frequency signals (which is known to be important to design green wireless networks). The optimal centralized policy is derived in order to have an upper bound on the performance of the decentralized system. Then, the Nash equilibrium of the cognitive network is determined by using recent results from mean field theory (MFT). In order to evaluate the performance gap between decentralized and centralized policies we introduce and evaluate the MFT-based asymptotic price of anarchy (APoA).",hamidou tembine,Games,2010.0,10.4108/ICST.CROWNCOM2010.9219,2010 Proceedings of the Fifth International Conference on Cognitive Radio Oriented Wireless Networks and Communications,Tembine2010,False,,IEEE,Not available,Joint power control-allocation for green cognitive wireless networks using mean field theory,a8ad7a5dd7b64f700329b584696f1929,https://ieeexplore.ieee.org/document/5577790/
3217,"The purpose of this paper is to show how key concepts from control theory, game theory, and mean field theory can be exploited to design joint control-allocation policies in cognitive wireless networks. One of the key features of the proposed approach is that transmitters (which are assumed to be cognitive and autonomous decisionnally speaking) have a certain knowledge of the channel evolution law and want to reach a certain transmission rate target while minimizing the energy consumed by the power supply and not the one corresponding to radio-frequency signals (which is known to be important to design green wireless networks). The optimal centralized policy is derived in order to have an upper bound on the performance of the decentralized system. Then, the Nash equilibrium of the cognitive network is determined by using recent results from mean field theory (MFT). In order to evaluate the performance gap between decentralized and centralized policies we introduce and evaluate the MFT-based asymptotic price of anarchy (APoA).",hamidou tembine,Equations,2010.0,10.4108/ICST.CROWNCOM2010.9219,2010 Proceedings of the Fifth International Conference on Cognitive Radio Oriented Wireless Networks and Communications,Tembine2010,False,,IEEE,Not available,Joint power control-allocation for green cognitive wireless networks using mean field theory,a8ad7a5dd7b64f700329b584696f1929,https://ieeexplore.ieee.org/document/5577790/
3218,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
3219,"The purpose of this paper is to show how key concepts from control theory, game theory, and mean field theory can be exploited to design joint control-allocation policies in cognitive wireless networks. One of the key features of the proposed approach is that transmitters (which are assumed to be cognitive and autonomous decisionnally speaking) have a certain knowledge of the channel evolution law and want to reach a certain transmission rate target while minimizing the energy consumed by the power supply and not the one corresponding to radio-frequency signals (which is known to be important to design green wireless networks). The optimal centralized policy is derived in order to have an upper bound on the performance of the decentralized system. Then, the Nash equilibrium of the cognitive network is determined by using recent results from mean field theory (MFT). In order to evaluate the performance gap between decentralized and centralized policies we introduce and evaluate the MFT-based asymptotic price of anarchy (APoA).",hamidou tembine,Wireless networks,2010.0,10.4108/ICST.CROWNCOM2010.9219,2010 Proceedings of the Fifth International Conference on Cognitive Radio Oriented Wireless Networks and Communications,Tembine2010,False,,IEEE,Not available,Joint power control-allocation for green cognitive wireless networks using mean field theory,a8ad7a5dd7b64f700329b584696f1929,https://ieeexplore.ieee.org/document/5577790/
3220,"The purpose of this paper is to show how key concepts from control theory, game theory, and mean field theory can be exploited to design joint control-allocation policies in cognitive wireless networks. One of the key features of the proposed approach is that transmitters (which are assumed to be cognitive and autonomous decisionnally speaking) have a certain knowledge of the channel evolution law and want to reach a certain transmission rate target while minimizing the energy consumed by the power supply and not the one corresponding to radio-frequency signals (which is known to be important to design green wireless networks). The optimal centralized policy is derived in order to have an upper bound on the performance of the decentralized system. Then, the Nash equilibrium of the cognitive network is determined by using recent results from mean field theory (MFT). In order to evaluate the performance gap between decentralized and centralized policies we introduce and evaluate the MFT-based asymptotic price of anarchy (APoA).",hamidou tembine,Convergence,2010.0,10.4108/ICST.CROWNCOM2010.9219,2010 Proceedings of the Fifth International Conference on Cognitive Radio Oriented Wireless Networks and Communications,Tembine2010,False,,IEEE,Not available,Joint power control-allocation for green cognitive wireless networks using mean field theory,a8ad7a5dd7b64f700329b584696f1929,https://ieeexplore.ieee.org/document/5577790/
3221,"The purpose of this paper is to show how key concepts from control theory, game theory, and mean field theory can be exploited to design joint control-allocation policies in cognitive wireless networks. One of the key features of the proposed approach is that transmitters (which are assumed to be cognitive and autonomous decisionnally speaking) have a certain knowledge of the channel evolution law and want to reach a certain transmission rate target while minimizing the energy consumed by the power supply and not the one corresponding to radio-frequency signals (which is known to be important to design green wireless networks). The optimal centralized policy is derived in order to have an upper bound on the performance of the decentralized system. Then, the Nash equilibrium of the cognitive network is determined by using recent results from mean field theory (MFT). In order to evaluate the performance gap between decentralized and centralized policies we introduce and evaluate the MFT-based asymptotic price of anarchy (APoA).",samson lasaulce,Radio transmitters,2010.0,10.4108/ICST.CROWNCOM2010.9219,2010 Proceedings of the Fifth International Conference on Cognitive Radio Oriented Wireless Networks and Communications,Tembine2010,False,,IEEE,Not available,Joint power control-allocation for green cognitive wireless networks using mean field theory,a8ad7a5dd7b64f700329b584696f1929,https://ieeexplore.ieee.org/document/5577790/
3222,"The purpose of this paper is to show how key concepts from control theory, game theory, and mean field theory can be exploited to design joint control-allocation policies in cognitive wireless networks. One of the key features of the proposed approach is that transmitters (which are assumed to be cognitive and autonomous decisionnally speaking) have a certain knowledge of the channel evolution law and want to reach a certain transmission rate target while minimizing the energy consumed by the power supply and not the one corresponding to radio-frequency signals (which is known to be important to design green wireless networks). The optimal centralized policy is derived in order to have an upper bound on the performance of the decentralized system. Then, the Nash equilibrium of the cognitive network is determined by using recent results from mean field theory (MFT). In order to evaluate the performance gap between decentralized and centralized policies we introduce and evaluate the MFT-based asymptotic price of anarchy (APoA).",samson lasaulce,Resource management,2010.0,10.4108/ICST.CROWNCOM2010.9219,2010 Proceedings of the Fifth International Conference on Cognitive Radio Oriented Wireless Networks and Communications,Tembine2010,False,,IEEE,Not available,Joint power control-allocation for green cognitive wireless networks using mean field theory,a8ad7a5dd7b64f700329b584696f1929,https://ieeexplore.ieee.org/document/5577790/
3223,"The purpose of this paper is to show how key concepts from control theory, game theory, and mean field theory can be exploited to design joint control-allocation policies in cognitive wireless networks. One of the key features of the proposed approach is that transmitters (which are assumed to be cognitive and autonomous decisionnally speaking) have a certain knowledge of the channel evolution law and want to reach a certain transmission rate target while minimizing the energy consumed by the power supply and not the one corresponding to radio-frequency signals (which is known to be important to design green wireless networks). The optimal centralized policy is derived in order to have an upper bound on the performance of the decentralized system. Then, the Nash equilibrium of the cognitive network is determined by using recent results from mean field theory (MFT). In order to evaluate the performance gap between decentralized and centralized policies we introduce and evaluate the MFT-based asymptotic price of anarchy (APoA).",samson lasaulce,Games,2010.0,10.4108/ICST.CROWNCOM2010.9219,2010 Proceedings of the Fifth International Conference on Cognitive Radio Oriented Wireless Networks and Communications,Tembine2010,False,,IEEE,Not available,Joint power control-allocation for green cognitive wireless networks using mean field theory,a8ad7a5dd7b64f700329b584696f1929,https://ieeexplore.ieee.org/document/5577790/
3224,"The purpose of this paper is to show how key concepts from control theory, game theory, and mean field theory can be exploited to design joint control-allocation policies in cognitive wireless networks. One of the key features of the proposed approach is that transmitters (which are assumed to be cognitive and autonomous decisionnally speaking) have a certain knowledge of the channel evolution law and want to reach a certain transmission rate target while minimizing the energy consumed by the power supply and not the one corresponding to radio-frequency signals (which is known to be important to design green wireless networks). The optimal centralized policy is derived in order to have an upper bound on the performance of the decentralized system. Then, the Nash equilibrium of the cognitive network is determined by using recent results from mean field theory (MFT). In order to evaluate the performance gap between decentralized and centralized policies we introduce and evaluate the MFT-based asymptotic price of anarchy (APoA).",samson lasaulce,Equations,2010.0,10.4108/ICST.CROWNCOM2010.9219,2010 Proceedings of the Fifth International Conference on Cognitive Radio Oriented Wireless Networks and Communications,Tembine2010,False,,IEEE,Not available,Joint power control-allocation for green cognitive wireless networks using mean field theory,a8ad7a5dd7b64f700329b584696f1929,https://ieeexplore.ieee.org/document/5577790/
3225,"The purpose of this paper is to show how key concepts from control theory, game theory, and mean field theory can be exploited to design joint control-allocation policies in cognitive wireless networks. One of the key features of the proposed approach is that transmitters (which are assumed to be cognitive and autonomous decisionnally speaking) have a certain knowledge of the channel evolution law and want to reach a certain transmission rate target while minimizing the energy consumed by the power supply and not the one corresponding to radio-frequency signals (which is known to be important to design green wireless networks). The optimal centralized policy is derived in order to have an upper bound on the performance of the decentralized system. Then, the Nash equilibrium of the cognitive network is determined by using recent results from mean field theory (MFT). In order to evaluate the performance gap between decentralized and centralized policies we introduce and evaluate the MFT-based asymptotic price of anarchy (APoA).",samson lasaulce,Wireless networks,2010.0,10.4108/ICST.CROWNCOM2010.9219,2010 Proceedings of the Fifth International Conference on Cognitive Radio Oriented Wireless Networks and Communications,Tembine2010,False,,IEEE,Not available,Joint power control-allocation for green cognitive wireless networks using mean field theory,a8ad7a5dd7b64f700329b584696f1929,https://ieeexplore.ieee.org/document/5577790/
3226,"The purpose of this paper is to show how key concepts from control theory, game theory, and mean field theory can be exploited to design joint control-allocation policies in cognitive wireless networks. One of the key features of the proposed approach is that transmitters (which are assumed to be cognitive and autonomous decisionnally speaking) have a certain knowledge of the channel evolution law and want to reach a certain transmission rate target while minimizing the energy consumed by the power supply and not the one corresponding to radio-frequency signals (which is known to be important to design green wireless networks). The optimal centralized policy is derived in order to have an upper bound on the performance of the decentralized system. Then, the Nash equilibrium of the cognitive network is determined by using recent results from mean field theory (MFT). In order to evaluate the performance gap between decentralized and centralized policies we introduce and evaluate the MFT-based asymptotic price of anarchy (APoA).",samson lasaulce,Convergence,2010.0,10.4108/ICST.CROWNCOM2010.9219,2010 Proceedings of the Fifth International Conference on Cognitive Radio Oriented Wireless Networks and Communications,Tembine2010,False,,IEEE,Not available,Joint power control-allocation for green cognitive wireless networks using mean field theory,a8ad7a5dd7b64f700329b584696f1929,https://ieeexplore.ieee.org/document/5577790/
3227,"The purpose of this paper is to show how key concepts from control theory, game theory, and mean field theory can be exploited to design joint control-allocation policies in cognitive wireless networks. One of the key features of the proposed approach is that transmitters (which are assumed to be cognitive and autonomous decisionnally speaking) have a certain knowledge of the channel evolution law and want to reach a certain transmission rate target while minimizing the energy consumed by the power supply and not the one corresponding to radio-frequency signals (which is known to be important to design green wireless networks). The optimal centralized policy is derived in order to have an upper bound on the performance of the decentralized system. Then, the Nash equilibrium of the cognitive network is determined by using recent results from mean field theory (MFT). In order to evaluate the performance gap between decentralized and centralized policies we introduce and evaluate the MFT-based asymptotic price of anarchy (APoA).",marc jungers,Radio transmitters,2010.0,10.4108/ICST.CROWNCOM2010.9219,2010 Proceedings of the Fifth International Conference on Cognitive Radio Oriented Wireless Networks and Communications,Tembine2010,False,,IEEE,Not available,Joint power control-allocation for green cognitive wireless networks using mean field theory,a8ad7a5dd7b64f700329b584696f1929,https://ieeexplore.ieee.org/document/5577790/
3228,"The purpose of this paper is to show how key concepts from control theory, game theory, and mean field theory can be exploited to design joint control-allocation policies in cognitive wireless networks. One of the key features of the proposed approach is that transmitters (which are assumed to be cognitive and autonomous decisionnally speaking) have a certain knowledge of the channel evolution law and want to reach a certain transmission rate target while minimizing the energy consumed by the power supply and not the one corresponding to radio-frequency signals (which is known to be important to design green wireless networks). The optimal centralized policy is derived in order to have an upper bound on the performance of the decentralized system. Then, the Nash equilibrium of the cognitive network is determined by using recent results from mean field theory (MFT). In order to evaluate the performance gap between decentralized and centralized policies we introduce and evaluate the MFT-based asymptotic price of anarchy (APoA).",marc jungers,Resource management,2010.0,10.4108/ICST.CROWNCOM2010.9219,2010 Proceedings of the Fifth International Conference on Cognitive Radio Oriented Wireless Networks and Communications,Tembine2010,False,,IEEE,Not available,Joint power control-allocation for green cognitive wireless networks using mean field theory,a8ad7a5dd7b64f700329b584696f1929,https://ieeexplore.ieee.org/document/5577790/
3229,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
3230,"The purpose of this paper is to show how key concepts from control theory, game theory, and mean field theory can be exploited to design joint control-allocation policies in cognitive wireless networks. One of the key features of the proposed approach is that transmitters (which are assumed to be cognitive and autonomous decisionnally speaking) have a certain knowledge of the channel evolution law and want to reach a certain transmission rate target while minimizing the energy consumed by the power supply and not the one corresponding to radio-frequency signals (which is known to be important to design green wireless networks). The optimal centralized policy is derived in order to have an upper bound on the performance of the decentralized system. Then, the Nash equilibrium of the cognitive network is determined by using recent results from mean field theory (MFT). In order to evaluate the performance gap between decentralized and centralized policies we introduce and evaluate the MFT-based asymptotic price of anarchy (APoA).",marc jungers,Games,2010.0,10.4108/ICST.CROWNCOM2010.9219,2010 Proceedings of the Fifth International Conference on Cognitive Radio Oriented Wireless Networks and Communications,Tembine2010,False,,IEEE,Not available,Joint power control-allocation for green cognitive wireless networks using mean field theory,a8ad7a5dd7b64f700329b584696f1929,https://ieeexplore.ieee.org/document/5577790/
3231,"The purpose of this paper is to show how key concepts from control theory, game theory, and mean field theory can be exploited to design joint control-allocation policies in cognitive wireless networks. One of the key features of the proposed approach is that transmitters (which are assumed to be cognitive and autonomous decisionnally speaking) have a certain knowledge of the channel evolution law and want to reach a certain transmission rate target while minimizing the energy consumed by the power supply and not the one corresponding to radio-frequency signals (which is known to be important to design green wireless networks). The optimal centralized policy is derived in order to have an upper bound on the performance of the decentralized system. Then, the Nash equilibrium of the cognitive network is determined by using recent results from mean field theory (MFT). In order to evaluate the performance gap between decentralized and centralized policies we introduce and evaluate the MFT-based asymptotic price of anarchy (APoA).",marc jungers,Equations,2010.0,10.4108/ICST.CROWNCOM2010.9219,2010 Proceedings of the Fifth International Conference on Cognitive Radio Oriented Wireless Networks and Communications,Tembine2010,False,,IEEE,Not available,Joint power control-allocation for green cognitive wireless networks using mean field theory,a8ad7a5dd7b64f700329b584696f1929,https://ieeexplore.ieee.org/document/5577790/
3232,"The purpose of this paper is to show how key concepts from control theory, game theory, and mean field theory can be exploited to design joint control-allocation policies in cognitive wireless networks. One of the key features of the proposed approach is that transmitters (which are assumed to be cognitive and autonomous decisionnally speaking) have a certain knowledge of the channel evolution law and want to reach a certain transmission rate target while minimizing the energy consumed by the power supply and not the one corresponding to radio-frequency signals (which is known to be important to design green wireless networks). The optimal centralized policy is derived in order to have an upper bound on the performance of the decentralized system. Then, the Nash equilibrium of the cognitive network is determined by using recent results from mean field theory (MFT). In order to evaluate the performance gap between decentralized and centralized policies we introduce and evaluate the MFT-based asymptotic price of anarchy (APoA).",marc jungers,Wireless networks,2010.0,10.4108/ICST.CROWNCOM2010.9219,2010 Proceedings of the Fifth International Conference on Cognitive Radio Oriented Wireless Networks and Communications,Tembine2010,False,,IEEE,Not available,Joint power control-allocation for green cognitive wireless networks using mean field theory,a8ad7a5dd7b64f700329b584696f1929,https://ieeexplore.ieee.org/document/5577790/
3233,"The purpose of this paper is to show how key concepts from control theory, game theory, and mean field theory can be exploited to design joint control-allocation policies in cognitive wireless networks. One of the key features of the proposed approach is that transmitters (which are assumed to be cognitive and autonomous decisionnally speaking) have a certain knowledge of the channel evolution law and want to reach a certain transmission rate target while minimizing the energy consumed by the power supply and not the one corresponding to radio-frequency signals (which is known to be important to design green wireless networks). The optimal centralized policy is derived in order to have an upper bound on the performance of the decentralized system. Then, the Nash equilibrium of the cognitive network is determined by using recent results from mean field theory (MFT). In order to evaluate the performance gap between decentralized and centralized policies we introduce and evaluate the MFT-based asymptotic price of anarchy (APoA).",marc jungers,Convergence,2010.0,10.4108/ICST.CROWNCOM2010.9219,2010 Proceedings of the Fifth International Conference on Cognitive Radio Oriented Wireless Networks and Communications,Tembine2010,False,,IEEE,Not available,Joint power control-allocation for green cognitive wireless networks using mean field theory,a8ad7a5dd7b64f700329b584696f1929,https://ieeexplore.ieee.org/document/5577790/
3234,"This paper reports on quantification and mitigation of the inefficiency of selfish investment in network recovery from Susceptible Infected Susceptible (SIS) infection in a practically important case of high losses due to infection. In this case, both socially optimal and selfish investments in the infection loss mitigation keep the system close to the boundary of the infection-free region. However, our analysis reveals that while socially optimal investments result in asymptotically zero infection losses, this is not the case for selfish investments. The inefficiency of selfish investments, which is measured by the corresponding Price of Anarchy (PoA), is due to positive externalities. In heterogeneous networks, positive externalities result in finite infection losses despite aggregate overinvestment due to imbalances of selfish investments. While the infection losses can be eliminated with ""small"" increase in the selfish investments, dealing with imbalances of selfish investments is more challenging. This assessment challenges conventional view that inefficiency of selfish investment in network security is due to aggregate underinvestment, at least in a practically important case of large infection losses. We discuss possible approaches to reduction of the second inefficiency component through regulations, incentives, or their combination, and outline directions of future research.",vladimir marbukh,Susceptible-Infected-Susceptible (SIS) infection,2018.0,10.1109/TrustCom/BigDataSE.2018.00293,"2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE)",Marbukh2018,False,,IEEE,Not available,On Mitigation Inefficiency of Selfish Investment in Network Recovery from High Loss SIS Infection,0f6e9fce6544dab492b0065c6c4ecaee,https://ieeexplore.ieee.org/document/8456161/
3235,"This paper reports on quantification and mitigation of the inefficiency of selfish investment in network recovery from Susceptible Infected Susceptible (SIS) infection in a practically important case of high losses due to infection. In this case, both socially optimal and selfish investments in the infection loss mitigation keep the system close to the boundary of the infection-free region. However, our analysis reveals that while socially optimal investments result in asymptotically zero infection losses, this is not the case for selfish investments. The inefficiency of selfish investments, which is measured by the corresponding Price of Anarchy (PoA), is due to positive externalities. In heterogeneous networks, positive externalities result in finite infection losses despite aggregate overinvestment due to imbalances of selfish investments. While the infection losses can be eliminated with ""small"" increase in the selfish investments, dealing with imbalances of selfish investments is more challenging. This assessment challenges conventional view that inefficiency of selfish investment in network security is due to aggregate underinvestment, at least in a practically important case of large infection losses. We discuss possible approaches to reduction of the second inefficiency component through regulations, incentives, or their combination, and outline directions of future research.",vladimir marbukh,selfish investment in recovery capability,2018.0,10.1109/TrustCom/BigDataSE.2018.00293,"2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE)",Marbukh2018,False,,IEEE,Not available,On Mitigation Inefficiency of Selfish Investment in Network Recovery from High Loss SIS Infection,0f6e9fce6544dab492b0065c6c4ecaee,https://ieeexplore.ieee.org/document/8456161/
3236,"This paper reports on quantification and mitigation of the inefficiency of selfish investment in network recovery from Susceptible Infected Susceptible (SIS) infection in a practically important case of high losses due to infection. In this case, both socially optimal and selfish investments in the infection loss mitigation keep the system close to the boundary of the infection-free region. However, our analysis reveals that while socially optimal investments result in asymptotically zero infection losses, this is not the case for selfish investments. The inefficiency of selfish investments, which is measured by the corresponding Price of Anarchy (PoA), is due to positive externalities. In heterogeneous networks, positive externalities result in finite infection losses despite aggregate overinvestment due to imbalances of selfish investments. While the infection losses can be eliminated with ""small"" increase in the selfish investments, dealing with imbalances of selfish investments is more challenging. This assessment challenges conventional view that inefficiency of selfish investment in network security is due to aggregate underinvestment, at least in a practically important case of large infection losses. We discuss possible approaches to reduction of the second inefficiency component through regulations, incentives, or their combination, and outline directions of future research.",vladimir marbukh,inefficiency evaluation and mitigation,2018.0,10.1109/TrustCom/BigDataSE.2018.00293,"2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE)",Marbukh2018,False,,IEEE,Not available,On Mitigation Inefficiency of Selfish Investment in Network Recovery from High Loss SIS Infection,0f6e9fce6544dab492b0065c6c4ecaee,https://ieeexplore.ieee.org/document/8456161/
3237,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",jie xu,Cooperative networks,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
3238,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",jie xu,distributed protocols,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
3239,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",jie xu,economics networks,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
3240,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
3241,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",jie xu,imperfect monitoring,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
3242,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",jie xu,incentive design,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
3243,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",jie xu,indirect reciprocity,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
3244,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",jie xu,ratings,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
3245,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",jie xu,repeated games,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
3246,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",jie xu,social networks,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
3247,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",jie xu,social reciprocation,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
3248,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",yangbo song,Cooperative networks,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
3249,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",yangbo song,distributed protocols,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
3250,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",yangbo song,economics networks,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
3251,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
3252,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",yangbo song,imperfect monitoring,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
3253,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",yangbo song,incentive design,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
3254,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",yangbo song,indirect reciprocity,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
3255,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",yangbo song,ratings,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
3256,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",yangbo song,repeated games,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
3257,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",yangbo song,social networks,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
3258,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",yangbo song,social reciprocation,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
3259,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",mihaela schaar,Cooperative networks,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
3260,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",mihaela schaar,distributed protocols,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
3261,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",mihaela schaar,economics networks,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
3262,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
3263,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",mihaela schaar,imperfect monitoring,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
3264,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",mihaela schaar,incentive design,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
3265,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",mihaela schaar,indirect reciprocity,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
3266,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",mihaela schaar,ratings,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
3267,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",mihaela schaar,repeated games,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
3268,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",mihaela schaar,social networks,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
3269,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",mihaela schaar,social reciprocation,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
3270,"We propose Flock; a simple and scalable protocol that enables live migration of Virtual Machines (VMs) across heterogeneous edge and conventional cloud platforms to improve the responsiveness of cloud services. Flock is designed with properties that are suitable for the use cases of the Internet of Things (IoT). We describe the properties of regularized latency measurements that Flock can use for asynchronous and autonomous migration decisions. Such decisions allow communicating VMs to follow a flocking-like behavior that consists of three simple rules: separation, alignment, and cohesion. Using game theory, we derive analytical bounds on Flock's Price of Anarchy (PoA), and prove that flocking VMs converge to a Nash Equilibrium while settling in the best possible cloud platforms. We verify the effectiveness of Flock through simulations and discuss how its generic objective can simply be tweaked to achieve other objectives, such as cloud load balancing and energy consumption minimization.",sherif abdelwahab,Internet of things,2017.0,10.1109/ICC.2017.7996630,2017 IEEE International Conference on Communications (ICC),Abdelwahab2017,False,,IEEE,Not available,Flocking virtual machines in quest for responsive IoT cloud services,1463df007ba5cebf1f72906e00fb7d68,https://ieeexplore.ieee.org/document/7996630/
3271,"We propose Flock; a simple and scalable protocol that enables live migration of Virtual Machines (VMs) across heterogeneous edge and conventional cloud platforms to improve the responsiveness of cloud services. Flock is designed with properties that are suitable for the use cases of the Internet of Things (IoT). We describe the properties of regularized latency measurements that Flock can use for asynchronous and autonomous migration decisions. Such decisions allow communicating VMs to follow a flocking-like behavior that consists of three simple rules: separation, alignment, and cohesion. Using game theory, we derive analytical bounds on Flock's Price of Anarchy (PoA), and prove that flocking VMs converge to a Nash Equilibrium while settling in the best possible cloud platforms. We verify the effectiveness of Flock through simulations and discuss how its generic objective can simply be tweaked to achieve other objectives, such as cloud load balancing and energy consumption minimization.",sherif abdelwahab,Edge computing,2017.0,10.1109/ICC.2017.7996630,2017 IEEE International Conference on Communications (ICC),Abdelwahab2017,False,,IEEE,Not available,Flocking virtual machines in quest for responsive IoT cloud services,1463df007ba5cebf1f72906e00fb7d68,https://ieeexplore.ieee.org/document/7996630/
3272,"We propose Flock; a simple and scalable protocol that enables live migration of Virtual Machines (VMs) across heterogeneous edge and conventional cloud platforms to improve the responsiveness of cloud services. Flock is designed with properties that are suitable for the use cases of the Internet of Things (IoT). We describe the properties of regularized latency measurements that Flock can use for asynchronous and autonomous migration decisions. Such decisions allow communicating VMs to follow a flocking-like behavior that consists of three simple rules: separation, alignment, and cohesion. Using game theory, we derive analytical bounds on Flock's Price of Anarchy (PoA), and prove that flocking VMs converge to a Nash Equilibrium while settling in the best possible cloud platforms. We verify the effectiveness of Flock through simulations and discuss how its generic objective can simply be tweaked to achieve other objectives, such as cloud load balancing and energy consumption minimization.",sherif abdelwahab,Game theory,2017.0,10.1109/ICC.2017.7996630,2017 IEEE International Conference on Communications (ICC),Abdelwahab2017,False,,IEEE,Not available,Flocking virtual machines in quest for responsive IoT cloud services,1463df007ba5cebf1f72906e00fb7d68,https://ieeexplore.ieee.org/document/7996630/
3273,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
3274,"We propose Flock; a simple and scalable protocol that enables live migration of Virtual Machines (VMs) across heterogeneous edge and conventional cloud platforms to improve the responsiveness of cloud services. Flock is designed with properties that are suitable for the use cases of the Internet of Things (IoT). We describe the properties of regularized latency measurements that Flock can use for asynchronous and autonomous migration decisions. Such decisions allow communicating VMs to follow a flocking-like behavior that consists of three simple rules: separation, alignment, and cohesion. Using game theory, we derive analytical bounds on Flock's Price of Anarchy (PoA), and prove that flocking VMs converge to a Nash Equilibrium while settling in the best possible cloud platforms. We verify the effectiveness of Flock through simulations and discuss how its generic objective can simply be tweaked to achieve other objectives, such as cloud load balancing and energy consumption minimization.",sherif abdelwahab,Resource management,2017.0,10.1109/ICC.2017.7996630,2017 IEEE International Conference on Communications (ICC),Abdelwahab2017,False,,IEEE,Not available,Flocking virtual machines in quest for responsive IoT cloud services,1463df007ba5cebf1f72906e00fb7d68,https://ieeexplore.ieee.org/document/7996630/
3275,"We propose Flock; a simple and scalable protocol that enables live migration of Virtual Machines (VMs) across heterogeneous edge and conventional cloud platforms to improve the responsiveness of cloud services. Flock is designed with properties that are suitable for the use cases of the Internet of Things (IoT). We describe the properties of regularized latency measurements that Flock can use for asynchronous and autonomous migration decisions. Such decisions allow communicating VMs to follow a flocking-like behavior that consists of three simple rules: separation, alignment, and cohesion. Using game theory, we derive analytical bounds on Flock's Price of Anarchy (PoA), and prove that flocking VMs converge to a Nash Equilibrium while settling in the best possible cloud platforms. We verify the effectiveness of Flock through simulations and discuss how its generic objective can simply be tweaked to achieve other objectives, such as cloud load balancing and energy consumption minimization.",bechir hamdaoui,Internet of things,2017.0,10.1109/ICC.2017.7996630,2017 IEEE International Conference on Communications (ICC),Abdelwahab2017,False,,IEEE,Not available,Flocking virtual machines in quest for responsive IoT cloud services,1463df007ba5cebf1f72906e00fb7d68,https://ieeexplore.ieee.org/document/7996630/
3276,"We propose Flock; a simple and scalable protocol that enables live migration of Virtual Machines (VMs) across heterogeneous edge and conventional cloud platforms to improve the responsiveness of cloud services. Flock is designed with properties that are suitable for the use cases of the Internet of Things (IoT). We describe the properties of regularized latency measurements that Flock can use for asynchronous and autonomous migration decisions. Such decisions allow communicating VMs to follow a flocking-like behavior that consists of three simple rules: separation, alignment, and cohesion. Using game theory, we derive analytical bounds on Flock's Price of Anarchy (PoA), and prove that flocking VMs converge to a Nash Equilibrium while settling in the best possible cloud platforms. We verify the effectiveness of Flock through simulations and discuss how its generic objective can simply be tweaked to achieve other objectives, such as cloud load balancing and energy consumption minimization.",bechir hamdaoui,Edge computing,2017.0,10.1109/ICC.2017.7996630,2017 IEEE International Conference on Communications (ICC),Abdelwahab2017,False,,IEEE,Not available,Flocking virtual machines in quest for responsive IoT cloud services,1463df007ba5cebf1f72906e00fb7d68,https://ieeexplore.ieee.org/document/7996630/
3277,"We propose Flock; a simple and scalable protocol that enables live migration of Virtual Machines (VMs) across heterogeneous edge and conventional cloud platforms to improve the responsiveness of cloud services. Flock is designed with properties that are suitable for the use cases of the Internet of Things (IoT). We describe the properties of regularized latency measurements that Flock can use for asynchronous and autonomous migration decisions. Such decisions allow communicating VMs to follow a flocking-like behavior that consists of three simple rules: separation, alignment, and cohesion. Using game theory, we derive analytical bounds on Flock's Price of Anarchy (PoA), and prove that flocking VMs converge to a Nash Equilibrium while settling in the best possible cloud platforms. We verify the effectiveness of Flock through simulations and discuss how its generic objective can simply be tweaked to achieve other objectives, such as cloud load balancing and energy consumption minimization.",bechir hamdaoui,Game theory,2017.0,10.1109/ICC.2017.7996630,2017 IEEE International Conference on Communications (ICC),Abdelwahab2017,False,,IEEE,Not available,Flocking virtual machines in quest for responsive IoT cloud services,1463df007ba5cebf1f72906e00fb7d68,https://ieeexplore.ieee.org/document/7996630/
3278,"We propose Flock; a simple and scalable protocol that enables live migration of Virtual Machines (VMs) across heterogeneous edge and conventional cloud platforms to improve the responsiveness of cloud services. Flock is designed with properties that are suitable for the use cases of the Internet of Things (IoT). We describe the properties of regularized latency measurements that Flock can use for asynchronous and autonomous migration decisions. Such decisions allow communicating VMs to follow a flocking-like behavior that consists of three simple rules: separation, alignment, and cohesion. Using game theory, we derive analytical bounds on Flock's Price of Anarchy (PoA), and prove that flocking VMs converge to a Nash Equilibrium while settling in the best possible cloud platforms. We verify the effectiveness of Flock through simulations and discuss how its generic objective can simply be tweaked to achieve other objectives, such as cloud load balancing and energy consumption minimization.",bechir hamdaoui,Resource management,2017.0,10.1109/ICC.2017.7996630,2017 IEEE International Conference on Communications (ICC),Abdelwahab2017,False,,IEEE,Not available,Flocking virtual machines in quest for responsive IoT cloud services,1463df007ba5cebf1f72906e00fb7d68,https://ieeexplore.ieee.org/document/7996630/
3279,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ahmed abdulla,Games,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3280,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ahmed abdulla,Signal to noise ratio,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3281,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ahmed abdulla,Modulation,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3282,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ahmed abdulla,Data collection,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3283,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ahmed abdulla,Convergence,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3284,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
3285,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ahmed abdulla,Bit error rate,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3286,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ahmed abdulla,Game theory,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3287,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",zubair fadlullah,Games,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3288,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",zubair fadlullah,Signal to noise ratio,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3289,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",zubair fadlullah,Modulation,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3290,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",zubair fadlullah,Data collection,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3291,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",zubair fadlullah,Convergence,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3292,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",zubair fadlullah,Bit error rate,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3293,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",zubair fadlullah,Game theory,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3294,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",hiroki nishiyama,Games,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3295,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
3296,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
3297,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",hiroki nishiyama,Signal to noise ratio,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3298,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",hiroki nishiyama,Modulation,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3299,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",hiroki nishiyama,Data collection,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3300,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",hiroki nishiyama,Convergence,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3301,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",hiroki nishiyama,Bit error rate,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3302,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",hiroki nishiyama,Game theory,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3303,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",nei kato,Games,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3304,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",nei kato,Signal to noise ratio,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3305,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",nei kato,Modulation,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3306,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",nei kato,Data collection,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3307,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
3308,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",nei kato,Convergence,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3309,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",nei kato,Bit error rate,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3310,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",nei kato,Game theory,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3311,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",fumie ono,Games,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3312,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",fumie ono,Signal to noise ratio,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3313,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",fumie ono,Modulation,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3314,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",fumie ono,Data collection,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3315,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",fumie ono,Convergence,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3316,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",fumie ono,Bit error rate,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3317,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",fumie ono,Game theory,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3318,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
3319,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ryu miura,Games,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3320,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ryu miura,Signal to noise ratio,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3321,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ryu miura,Modulation,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3322,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ryu miura,Data collection,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3323,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ryu miura,Convergence,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3324,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ryu miura,Bit error rate,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3325,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ryu miura,Game theory,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
3326,"We study a routing game in which one of the players unilaterally acts altruistically by taking into consideration the latency cost of other players as well as his own. By not playing selfishly, a player can not only improve the other players' equilibrium utility but also improve his own equilibrium utility. To quantify the effect, we define a metric called the Value of Unilateral Altruism (VoU) to be the ratio of the equilibrium utility of the altruistic user to the equilibrium utility he would have received in Nash equilibrium if he were selfish. We show by example that the VoU, in a game with nonlinear latency functions and atomic players, can be arbitrarily large. Since the Nash equilibrium social welfare of this example is arbitrarily far from social optimum, this example also has a Price of Anarchy (PoA) that is unbounded. The example is driven by there being a small number of players since the same example with non-atomic players yields a Nash equilibrium that is fully efficient.",amar azad,Games,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Azad2011,False,,IEEE,Not available,Unilateral altruism in network routing games with atomic players,408da6af440414521cc8e1dbab05f8cd,https://ieeexplore.ieee.org/document/6103893/
3327,"We study a routing game in which one of the players unilaterally acts altruistically by taking into consideration the latency cost of other players as well as his own. By not playing selfishly, a player can not only improve the other players' equilibrium utility but also improve his own equilibrium utility. To quantify the effect, we define a metric called the Value of Unilateral Altruism (VoU) to be the ratio of the equilibrium utility of the altruistic user to the equilibrium utility he would have received in Nash equilibrium if he were selfish. We show by example that the VoU, in a game with nonlinear latency functions and atomic players, can be arbitrarily large. Since the Nash equilibrium social welfare of this example is arbitrarily far from social optimum, this example also has a Price of Anarchy (PoA) that is unbounded. The example is driven by there being a small number of players since the same example with non-atomic players yields a Nash equilibrium that is fully efficient.",amar azad,Routing,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Azad2011,False,,IEEE,Not available,Unilateral altruism in network routing games with atomic players,408da6af440414521cc8e1dbab05f8cd,https://ieeexplore.ieee.org/document/6103893/
3328,"We study a routing game in which one of the players unilaterally acts altruistically by taking into consideration the latency cost of other players as well as his own. By not playing selfishly, a player can not only improve the other players' equilibrium utility but also improve his own equilibrium utility. To quantify the effect, we define a metric called the Value of Unilateral Altruism (VoU) to be the ratio of the equilibrium utility of the altruistic user to the equilibrium utility he would have received in Nash equilibrium if he were selfish. We show by example that the VoU, in a game with nonlinear latency functions and atomic players, can be arbitrarily large. Since the Nash equilibrium social welfare of this example is arbitrarily far from social optimum, this example also has a Price of Anarchy (PoA) that is unbounded. The example is driven by there being a small number of players since the same example with non-atomic players yields a Nash equilibrium that is fully efficient.",amar azad,Nash equilibrium,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Azad2011,False,,IEEE,Not available,Unilateral altruism in network routing games with atomic players,408da6af440414521cc8e1dbab05f8cd,https://ieeexplore.ieee.org/document/6103893/
3329,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
3330,"We study a routing game in which one of the players unilaterally acts altruistically by taking into consideration the latency cost of other players as well as his own. By not playing selfishly, a player can not only improve the other players' equilibrium utility but also improve his own equilibrium utility. To quantify the effect, we define a metric called the Value of Unilateral Altruism (VoU) to be the ratio of the equilibrium utility of the altruistic user to the equilibrium utility he would have received in Nash equilibrium if he were selfish. We show by example that the VoU, in a game with nonlinear latency functions and atomic players, can be arbitrarily large. Since the Nash equilibrium social welfare of this example is arbitrarily far from social optimum, this example also has a Price of Anarchy (PoA) that is unbounded. The example is driven by there being a small number of players since the same example with non-atomic players yields a Nash equilibrium that is fully efficient.",amar azad,Elbow,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Azad2011,False,,IEEE,Not available,Unilateral altruism in network routing games with atomic players,408da6af440414521cc8e1dbab05f8cd,https://ieeexplore.ieee.org/document/6103893/
3331,"We study a routing game in which one of the players unilaterally acts altruistically by taking into consideration the latency cost of other players as well as his own. By not playing selfishly, a player can not only improve the other players' equilibrium utility but also improve his own equilibrium utility. To quantify the effect, we define a metric called the Value of Unilateral Altruism (VoU) to be the ratio of the equilibrium utility of the altruistic user to the equilibrium utility he would have received in Nash equilibrium if he were selfish. We show by example that the VoU, in a game with nonlinear latency functions and atomic players, can be arbitrarily large. Since the Nash equilibrium social welfare of this example is arbitrarily far from social optimum, this example also has a Price of Anarchy (PoA) that is unbounded. The example is driven by there being a small number of players since the same example with non-atomic players yields a Nash equilibrium that is fully efficient.",amar azad,Cost function,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Azad2011,False,,IEEE,Not available,Unilateral altruism in network routing games with atomic players,408da6af440414521cc8e1dbab05f8cd,https://ieeexplore.ieee.org/document/6103893/
3332,"We study a routing game in which one of the players unilaterally acts altruistically by taking into consideration the latency cost of other players as well as his own. By not playing selfishly, a player can not only improve the other players' equilibrium utility but also improve his own equilibrium utility. To quantify the effect, we define a metric called the Value of Unilateral Altruism (VoU) to be the ratio of the equilibrium utility of the altruistic user to the equilibrium utility he would have received in Nash equilibrium if he were selfish. We show by example that the VoU, in a game with nonlinear latency functions and atomic players, can be arbitrarily large. Since the Nash equilibrium social welfare of this example is arbitrarily far from social optimum, this example also has a Price of Anarchy (PoA) that is unbounded. The example is driven by there being a small number of players since the same example with non-atomic players yields a Nash equilibrium that is fully efficient.",amar azad,Delay,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Azad2011,False,,IEEE,Not available,Unilateral altruism in network routing games with atomic players,408da6af440414521cc8e1dbab05f8cd,https://ieeexplore.ieee.org/document/6103893/
3333,"We study a routing game in which one of the players unilaterally acts altruistically by taking into consideration the latency cost of other players as well as his own. By not playing selfishly, a player can not only improve the other players' equilibrium utility but also improve his own equilibrium utility. To quantify the effect, we define a metric called the Value of Unilateral Altruism (VoU) to be the ratio of the equilibrium utility of the altruistic user to the equilibrium utility he would have received in Nash equilibrium if he were selfish. We show by example that the VoU, in a game with nonlinear latency functions and atomic players, can be arbitrarily large. Since the Nash equilibrium social welfare of this example is arbitrarily far from social optimum, this example also has a Price of Anarchy (PoA) that is unbounded. The example is driven by there being a small number of players since the same example with non-atomic players yields a Nash equilibrium that is fully efficient.",amar azad,Vectors,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Azad2011,False,,IEEE,Not available,Unilateral altruism in network routing games with atomic players,408da6af440414521cc8e1dbab05f8cd,https://ieeexplore.ieee.org/document/6103893/
3334,"We study a routing game in which one of the players unilaterally acts altruistically by taking into consideration the latency cost of other players as well as his own. By not playing selfishly, a player can not only improve the other players' equilibrium utility but also improve his own equilibrium utility. To quantify the effect, we define a metric called the Value of Unilateral Altruism (VoU) to be the ratio of the equilibrium utility of the altruistic user to the equilibrium utility he would have received in Nash equilibrium if he were selfish. We show by example that the VoU, in a game with nonlinear latency functions and atomic players, can be arbitrarily large. Since the Nash equilibrium social welfare of this example is arbitrarily far from social optimum, this example also has a Price of Anarchy (PoA) that is unbounded. The example is driven by there being a small number of players since the same example with non-atomic players yields a Nash equilibrium that is fully efficient.",john musacchio,Games,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Azad2011,False,,IEEE,Not available,Unilateral altruism in network routing games with atomic players,408da6af440414521cc8e1dbab05f8cd,https://ieeexplore.ieee.org/document/6103893/
3335,"We study a routing game in which one of the players unilaterally acts altruistically by taking into consideration the latency cost of other players as well as his own. By not playing selfishly, a player can not only improve the other players' equilibrium utility but also improve his own equilibrium utility. To quantify the effect, we define a metric called the Value of Unilateral Altruism (VoU) to be the ratio of the equilibrium utility of the altruistic user to the equilibrium utility he would have received in Nash equilibrium if he were selfish. We show by example that the VoU, in a game with nonlinear latency functions and atomic players, can be arbitrarily large. Since the Nash equilibrium social welfare of this example is arbitrarily far from social optimum, this example also has a Price of Anarchy (PoA) that is unbounded. The example is driven by there being a small number of players since the same example with non-atomic players yields a Nash equilibrium that is fully efficient.",john musacchio,Routing,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Azad2011,False,,IEEE,Not available,Unilateral altruism in network routing games with atomic players,408da6af440414521cc8e1dbab05f8cd,https://ieeexplore.ieee.org/document/6103893/
3336,"We study a routing game in which one of the players unilaterally acts altruistically by taking into consideration the latency cost of other players as well as his own. By not playing selfishly, a player can not only improve the other players' equilibrium utility but also improve his own equilibrium utility. To quantify the effect, we define a metric called the Value of Unilateral Altruism (VoU) to be the ratio of the equilibrium utility of the altruistic user to the equilibrium utility he would have received in Nash equilibrium if he were selfish. We show by example that the VoU, in a game with nonlinear latency functions and atomic players, can be arbitrarily large. Since the Nash equilibrium social welfare of this example is arbitrarily far from social optimum, this example also has a Price of Anarchy (PoA) that is unbounded. The example is driven by there being a small number of players since the same example with non-atomic players yields a Nash equilibrium that is fully efficient.",john musacchio,Nash equilibrium,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Azad2011,False,,IEEE,Not available,Unilateral altruism in network routing games with atomic players,408da6af440414521cc8e1dbab05f8cd,https://ieeexplore.ieee.org/document/6103893/
3337,"We study a routing game in which one of the players unilaterally acts altruistically by taking into consideration the latency cost of other players as well as his own. By not playing selfishly, a player can not only improve the other players' equilibrium utility but also improve his own equilibrium utility. To quantify the effect, we define a metric called the Value of Unilateral Altruism (VoU) to be the ratio of the equilibrium utility of the altruistic user to the equilibrium utility he would have received in Nash equilibrium if he were selfish. We show by example that the VoU, in a game with nonlinear latency functions and atomic players, can be arbitrarily large. Since the Nash equilibrium social welfare of this example is arbitrarily far from social optimum, this example also has a Price of Anarchy (PoA) that is unbounded. The example is driven by there being a small number of players since the same example with non-atomic players yields a Nash equilibrium that is fully efficient.",john musacchio,Elbow,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Azad2011,False,,IEEE,Not available,Unilateral altruism in network routing games with atomic players,408da6af440414521cc8e1dbab05f8cd,https://ieeexplore.ieee.org/document/6103893/
3338,"We study a routing game in which one of the players unilaterally acts altruistically by taking into consideration the latency cost of other players as well as his own. By not playing selfishly, a player can not only improve the other players' equilibrium utility but also improve his own equilibrium utility. To quantify the effect, we define a metric called the Value of Unilateral Altruism (VoU) to be the ratio of the equilibrium utility of the altruistic user to the equilibrium utility he would have received in Nash equilibrium if he were selfish. We show by example that the VoU, in a game with nonlinear latency functions and atomic players, can be arbitrarily large. Since the Nash equilibrium social welfare of this example is arbitrarily far from social optimum, this example also has a Price of Anarchy (PoA) that is unbounded. The example is driven by there being a small number of players since the same example with non-atomic players yields a Nash equilibrium that is fully efficient.",john musacchio,Cost function,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Azad2011,False,,IEEE,Not available,Unilateral altruism in network routing games with atomic players,408da6af440414521cc8e1dbab05f8cd,https://ieeexplore.ieee.org/document/6103893/
3339,"We study a routing game in which one of the players unilaterally acts altruistically by taking into consideration the latency cost of other players as well as his own. By not playing selfishly, a player can not only improve the other players' equilibrium utility but also improve his own equilibrium utility. To quantify the effect, we define a metric called the Value of Unilateral Altruism (VoU) to be the ratio of the equilibrium utility of the altruistic user to the equilibrium utility he would have received in Nash equilibrium if he were selfish. We show by example that the VoU, in a game with nonlinear latency functions and atomic players, can be arbitrarily large. Since the Nash equilibrium social welfare of this example is arbitrarily far from social optimum, this example also has a Price of Anarchy (PoA) that is unbounded. The example is driven by there being a small number of players since the same example with non-atomic players yields a Nash equilibrium that is fully efficient.",john musacchio,Delay,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Azad2011,False,,IEEE,Not available,Unilateral altruism in network routing games with atomic players,408da6af440414521cc8e1dbab05f8cd,https://ieeexplore.ieee.org/document/6103893/
3340,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
3341,"We study a routing game in which one of the players unilaterally acts altruistically by taking into consideration the latency cost of other players as well as his own. By not playing selfishly, a player can not only improve the other players' equilibrium utility but also improve his own equilibrium utility. To quantify the effect, we define a metric called the Value of Unilateral Altruism (VoU) to be the ratio of the equilibrium utility of the altruistic user to the equilibrium utility he would have received in Nash equilibrium if he were selfish. We show by example that the VoU, in a game with nonlinear latency functions and atomic players, can be arbitrarily large. Since the Nash equilibrium social welfare of this example is arbitrarily far from social optimum, this example also has a Price of Anarchy (PoA) that is unbounded. The example is driven by there being a small number of players since the same example with non-atomic players yields a Nash equilibrium that is fully efficient.",john musacchio,Vectors,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Azad2011,False,,IEEE,Not available,Unilateral altruism in network routing games with atomic players,408da6af440414521cc8e1dbab05f8cd,https://ieeexplore.ieee.org/document/6103893/
3342,"Forming, in a decentralized fashion, an optimal network topology while balancing multiple, possibly conflicting objectives like cost, high performance, security and resiliency to viruses is a challenging endeavor. In this paper, we take a game-formation approach to network design where each player, for instance an autonomous system in the Internet, aims to collectively minimize the cost of installing links, of protecting against viruses, and of assuring connectivity. In the game, minimizing virus risk as well as connectivity costs results in sparse graphs. We show that the Nash Equilibria are trees that, according to the Price of Anarchy (PoA), are close to the global optimum, while the worst-case Nash Equilibrium and the global optimum may significantly differ for small infection rate and link installation cost. Moreover, the types of trees, in both the Nash Equilibria and the optimal solution, depend on the virus infection rate, which provides new insights into how viruses spread: for high infection rate &amp;#x03C4;, the path graph is the worst- and the star graph is the best-case Nash Equilibrium. However, for small and intermediate values of &amp;#x03C4;, trees different from the path and star graphs may be optimal.",stojan trajanovski,Games,2015.0,10.1109/CDC.2015.7402216,2015 54th IEEE Conference on Decision and Control (CDC),Trajanovski2015,False,,IEEE,Not available,Designing virus-resistant networks: A game-formation approach,f01ec761a31087262975a75f48abb3d5,https://ieeexplore.ieee.org/document/7402216/
3343,"Forming, in a decentralized fashion, an optimal network topology while balancing multiple, possibly conflicting objectives like cost, high performance, security and resiliency to viruses is a challenging endeavor. In this paper, we take a game-formation approach to network design where each player, for instance an autonomous system in the Internet, aims to collectively minimize the cost of installing links, of protecting against viruses, and of assuring connectivity. In the game, minimizing virus risk as well as connectivity costs results in sparse graphs. We show that the Nash Equilibria are trees that, according to the Price of Anarchy (PoA), are close to the global optimum, while the worst-case Nash Equilibrium and the global optimum may significantly differ for small infection rate and link installation cost. Moreover, the types of trees, in both the Nash Equilibria and the optimal solution, depend on the virus infection rate, which provides new insights into how viruses spread: for high infection rate &amp;#x03C4;, the path graph is the worst- and the star graph is the best-case Nash Equilibrium. However, for small and intermediate values of &amp;#x03C4;, trees different from the path and star graphs may be optimal.",stojan trajanovski,Nash equilibrium,2015.0,10.1109/CDC.2015.7402216,2015 54th IEEE Conference on Decision and Control (CDC),Trajanovski2015,False,,IEEE,Not available,Designing virus-resistant networks: A game-formation approach,f01ec761a31087262975a75f48abb3d5,https://ieeexplore.ieee.org/document/7402216/
3344,"Forming, in a decentralized fashion, an optimal network topology while balancing multiple, possibly conflicting objectives like cost, high performance, security and resiliency to viruses is a challenging endeavor. In this paper, we take a game-formation approach to network design where each player, for instance an autonomous system in the Internet, aims to collectively minimize the cost of installing links, of protecting against viruses, and of assuring connectivity. In the game, minimizing virus risk as well as connectivity costs results in sparse graphs. We show that the Nash Equilibria are trees that, according to the Price of Anarchy (PoA), are close to the global optimum, while the worst-case Nash Equilibrium and the global optimum may significantly differ for small infection rate and link installation cost. Moreover, the types of trees, in both the Nash Equilibria and the optimal solution, depend on the virus infection rate, which provides new insights into how viruses spread: for high infection rate &amp;#x03C4;, the path graph is the worst- and the star graph is the best-case Nash Equilibrium. However, for small and intermediate values of &amp;#x03C4;, trees different from the path and star graphs may be optimal.",stojan trajanovski,Viruses (medical),2015.0,10.1109/CDC.2015.7402216,2015 54th IEEE Conference on Decision and Control (CDC),Trajanovski2015,False,,IEEE,Not available,Designing virus-resistant networks: A game-formation approach,f01ec761a31087262975a75f48abb3d5,https://ieeexplore.ieee.org/document/7402216/
3345,"Forming, in a decentralized fashion, an optimal network topology while balancing multiple, possibly conflicting objectives like cost, high performance, security and resiliency to viruses is a challenging endeavor. In this paper, we take a game-formation approach to network design where each player, for instance an autonomous system in the Internet, aims to collectively minimize the cost of installing links, of protecting against viruses, and of assuring connectivity. In the game, minimizing virus risk as well as connectivity costs results in sparse graphs. We show that the Nash Equilibria are trees that, according to the Price of Anarchy (PoA), are close to the global optimum, while the worst-case Nash Equilibrium and the global optimum may significantly differ for small infection rate and link installation cost. Moreover, the types of trees, in both the Nash Equilibria and the optimal solution, depend on the virus infection rate, which provides new insights into how viruses spread: for high infection rate &amp;#x03C4;, the path graph is the worst- and the star graph is the best-case Nash Equilibrium. However, for small and intermediate values of &amp;#x03C4;, trees different from the path and star graphs may be optimal.",stojan trajanovski,Network topology,2015.0,10.1109/CDC.2015.7402216,2015 54th IEEE Conference on Decision and Control (CDC),Trajanovski2015,False,,IEEE,Not available,Designing virus-resistant networks: A game-formation approach,f01ec761a31087262975a75f48abb3d5,https://ieeexplore.ieee.org/document/7402216/
3346,"Forming, in a decentralized fashion, an optimal network topology while balancing multiple, possibly conflicting objectives like cost, high performance, security and resiliency to viruses is a challenging endeavor. In this paper, we take a game-formation approach to network design where each player, for instance an autonomous system in the Internet, aims to collectively minimize the cost of installing links, of protecting against viruses, and of assuring connectivity. In the game, minimizing virus risk as well as connectivity costs results in sparse graphs. We show that the Nash Equilibria are trees that, according to the Price of Anarchy (PoA), are close to the global optimum, while the worst-case Nash Equilibrium and the global optimum may significantly differ for small infection rate and link installation cost. Moreover, the types of trees, in both the Nash Equilibria and the optimal solution, depend on the virus infection rate, which provides new insights into how viruses spread: for high infection rate &amp;#x03C4;, the path graph is the worst- and the star graph is the best-case Nash Equilibrium. However, for small and intermediate values of &amp;#x03C4;, trees different from the path and star graphs may be optimal.",stojan trajanovski,Peer-to-peer computing,2015.0,10.1109/CDC.2015.7402216,2015 54th IEEE Conference on Decision and Control (CDC),Trajanovski2015,False,,IEEE,Not available,Designing virus-resistant networks: A game-formation approach,f01ec761a31087262975a75f48abb3d5,https://ieeexplore.ieee.org/document/7402216/
3347,"Forming, in a decentralized fashion, an optimal network topology while balancing multiple, possibly conflicting objectives like cost, high performance, security and resiliency to viruses is a challenging endeavor. In this paper, we take a game-formation approach to network design where each player, for instance an autonomous system in the Internet, aims to collectively minimize the cost of installing links, of protecting against viruses, and of assuring connectivity. In the game, minimizing virus risk as well as connectivity costs results in sparse graphs. We show that the Nash Equilibria are trees that, according to the Price of Anarchy (PoA), are close to the global optimum, while the worst-case Nash Equilibrium and the global optimum may significantly differ for small infection rate and link installation cost. Moreover, the types of trees, in both the Nash Equilibria and the optimal solution, depend on the virus infection rate, which provides new insights into how viruses spread: for high infection rate &amp;#x03C4;, the path graph is the worst- and the star graph is the best-case Nash Equilibrium. However, for small and intermediate values of &amp;#x03C4;, trees different from the path and star graphs may be optimal.",stojan trajanovski,Stability analysis,2015.0,10.1109/CDC.2015.7402216,2015 54th IEEE Conference on Decision and Control (CDC),Trajanovski2015,False,,IEEE,Not available,Designing virus-resistant networks: A game-formation approach,f01ec761a31087262975a75f48abb3d5,https://ieeexplore.ieee.org/document/7402216/
3348,"Forming, in a decentralized fashion, an optimal network topology while balancing multiple, possibly conflicting objectives like cost, high performance, security and resiliency to viruses is a challenging endeavor. In this paper, we take a game-formation approach to network design where each player, for instance an autonomous system in the Internet, aims to collectively minimize the cost of installing links, of protecting against viruses, and of assuring connectivity. In the game, minimizing virus risk as well as connectivity costs results in sparse graphs. We show that the Nash Equilibria are trees that, according to the Price of Anarchy (PoA), are close to the global optimum, while the worst-case Nash Equilibrium and the global optimum may significantly differ for small infection rate and link installation cost. Moreover, the types of trees, in both the Nash Equilibria and the optimal solution, depend on the virus infection rate, which provides new insights into how viruses spread: for high infection rate &amp;#x03C4;, the path graph is the worst- and the star graph is the best-case Nash Equilibrium. However, for small and intermediate values of &amp;#x03C4;, trees different from the path and star graphs may be optimal.",stojan trajanovski,Security,2015.0,10.1109/CDC.2015.7402216,2015 54th IEEE Conference on Decision and Control (CDC),Trajanovski2015,False,,IEEE,Not available,Designing virus-resistant networks: A game-formation approach,f01ec761a31087262975a75f48abb3d5,https://ieeexplore.ieee.org/document/7402216/
3349,"Forming, in a decentralized fashion, an optimal network topology while balancing multiple, possibly conflicting objectives like cost, high performance, security and resiliency to viruses is a challenging endeavor. In this paper, we take a game-formation approach to network design where each player, for instance an autonomous system in the Internet, aims to collectively minimize the cost of installing links, of protecting against viruses, and of assuring connectivity. In the game, minimizing virus risk as well as connectivity costs results in sparse graphs. We show that the Nash Equilibria are trees that, according to the Price of Anarchy (PoA), are close to the global optimum, while the worst-case Nash Equilibrium and the global optimum may significantly differ for small infection rate and link installation cost. Moreover, the types of trees, in both the Nash Equilibria and the optimal solution, depend on the virus infection rate, which provides new insights into how viruses spread: for high infection rate &amp;#x03C4;, the path graph is the worst- and the star graph is the best-case Nash Equilibrium. However, for small and intermediate values of &amp;#x03C4;, trees different from the path and star graphs may be optimal.",fernando kuipers,Games,2015.0,10.1109/CDC.2015.7402216,2015 54th IEEE Conference on Decision and Control (CDC),Trajanovski2015,False,,IEEE,Not available,Designing virus-resistant networks: A game-formation approach,f01ec761a31087262975a75f48abb3d5,https://ieeexplore.ieee.org/document/7402216/
3350,"Forming, in a decentralized fashion, an optimal network topology while balancing multiple, possibly conflicting objectives like cost, high performance, security and resiliency to viruses is a challenging endeavor. In this paper, we take a game-formation approach to network design where each player, for instance an autonomous system in the Internet, aims to collectively minimize the cost of installing links, of protecting against viruses, and of assuring connectivity. In the game, minimizing virus risk as well as connectivity costs results in sparse graphs. We show that the Nash Equilibria are trees that, according to the Price of Anarchy (PoA), are close to the global optimum, while the worst-case Nash Equilibrium and the global optimum may significantly differ for small infection rate and link installation cost. Moreover, the types of trees, in both the Nash Equilibria and the optimal solution, depend on the virus infection rate, which provides new insights into how viruses spread: for high infection rate &amp;#x03C4;, the path graph is the worst- and the star graph is the best-case Nash Equilibrium. However, for small and intermediate values of &amp;#x03C4;, trees different from the path and star graphs may be optimal.",fernando kuipers,Nash equilibrium,2015.0,10.1109/CDC.2015.7402216,2015 54th IEEE Conference on Decision and Control (CDC),Trajanovski2015,False,,IEEE,Not available,Designing virus-resistant networks: A game-formation approach,f01ec761a31087262975a75f48abb3d5,https://ieeexplore.ieee.org/document/7402216/
3351,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
3352,"Forming, in a decentralized fashion, an optimal network topology while balancing multiple, possibly conflicting objectives like cost, high performance, security and resiliency to viruses is a challenging endeavor. In this paper, we take a game-formation approach to network design where each player, for instance an autonomous system in the Internet, aims to collectively minimize the cost of installing links, of protecting against viruses, and of assuring connectivity. In the game, minimizing virus risk as well as connectivity costs results in sparse graphs. We show that the Nash Equilibria are trees that, according to the Price of Anarchy (PoA), are close to the global optimum, while the worst-case Nash Equilibrium and the global optimum may significantly differ for small infection rate and link installation cost. Moreover, the types of trees, in both the Nash Equilibria and the optimal solution, depend on the virus infection rate, which provides new insights into how viruses spread: for high infection rate &amp;#x03C4;, the path graph is the worst- and the star graph is the best-case Nash Equilibrium. However, for small and intermediate values of &amp;#x03C4;, trees different from the path and star graphs may be optimal.",fernando kuipers,Viruses (medical),2015.0,10.1109/CDC.2015.7402216,2015 54th IEEE Conference on Decision and Control (CDC),Trajanovski2015,False,,IEEE,Not available,Designing virus-resistant networks: A game-formation approach,f01ec761a31087262975a75f48abb3d5,https://ieeexplore.ieee.org/document/7402216/
3353,"Forming, in a decentralized fashion, an optimal network topology while balancing multiple, possibly conflicting objectives like cost, high performance, security and resiliency to viruses is a challenging endeavor. In this paper, we take a game-formation approach to network design where each player, for instance an autonomous system in the Internet, aims to collectively minimize the cost of installing links, of protecting against viruses, and of assuring connectivity. In the game, minimizing virus risk as well as connectivity costs results in sparse graphs. We show that the Nash Equilibria are trees that, according to the Price of Anarchy (PoA), are close to the global optimum, while the worst-case Nash Equilibrium and the global optimum may significantly differ for small infection rate and link installation cost. Moreover, the types of trees, in both the Nash Equilibria and the optimal solution, depend on the virus infection rate, which provides new insights into how viruses spread: for high infection rate &amp;#x03C4;, the path graph is the worst- and the star graph is the best-case Nash Equilibrium. However, for small and intermediate values of &amp;#x03C4;, trees different from the path and star graphs may be optimal.",fernando kuipers,Network topology,2015.0,10.1109/CDC.2015.7402216,2015 54th IEEE Conference on Decision and Control (CDC),Trajanovski2015,False,,IEEE,Not available,Designing virus-resistant networks: A game-formation approach,f01ec761a31087262975a75f48abb3d5,https://ieeexplore.ieee.org/document/7402216/
3354,"Forming, in a decentralized fashion, an optimal network topology while balancing multiple, possibly conflicting objectives like cost, high performance, security and resiliency to viruses is a challenging endeavor. In this paper, we take a game-formation approach to network design where each player, for instance an autonomous system in the Internet, aims to collectively minimize the cost of installing links, of protecting against viruses, and of assuring connectivity. In the game, minimizing virus risk as well as connectivity costs results in sparse graphs. We show that the Nash Equilibria are trees that, according to the Price of Anarchy (PoA), are close to the global optimum, while the worst-case Nash Equilibrium and the global optimum may significantly differ for small infection rate and link installation cost. Moreover, the types of trees, in both the Nash Equilibria and the optimal solution, depend on the virus infection rate, which provides new insights into how viruses spread: for high infection rate &amp;#x03C4;, the path graph is the worst- and the star graph is the best-case Nash Equilibrium. However, for small and intermediate values of &amp;#x03C4;, trees different from the path and star graphs may be optimal.",fernando kuipers,Peer-to-peer computing,2015.0,10.1109/CDC.2015.7402216,2015 54th IEEE Conference on Decision and Control (CDC),Trajanovski2015,False,,IEEE,Not available,Designing virus-resistant networks: A game-formation approach,f01ec761a31087262975a75f48abb3d5,https://ieeexplore.ieee.org/document/7402216/
3355,"Forming, in a decentralized fashion, an optimal network topology while balancing multiple, possibly conflicting objectives like cost, high performance, security and resiliency to viruses is a challenging endeavor. In this paper, we take a game-formation approach to network design where each player, for instance an autonomous system in the Internet, aims to collectively minimize the cost of installing links, of protecting against viruses, and of assuring connectivity. In the game, minimizing virus risk as well as connectivity costs results in sparse graphs. We show that the Nash Equilibria are trees that, according to the Price of Anarchy (PoA), are close to the global optimum, while the worst-case Nash Equilibrium and the global optimum may significantly differ for small infection rate and link installation cost. Moreover, the types of trees, in both the Nash Equilibria and the optimal solution, depend on the virus infection rate, which provides new insights into how viruses spread: for high infection rate &amp;#x03C4;, the path graph is the worst- and the star graph is the best-case Nash Equilibrium. However, for small and intermediate values of &amp;#x03C4;, trees different from the path and star graphs may be optimal.",fernando kuipers,Stability analysis,2015.0,10.1109/CDC.2015.7402216,2015 54th IEEE Conference on Decision and Control (CDC),Trajanovski2015,False,,IEEE,Not available,Designing virus-resistant networks: A game-formation approach,f01ec761a31087262975a75f48abb3d5,https://ieeexplore.ieee.org/document/7402216/
3356,"Forming, in a decentralized fashion, an optimal network topology while balancing multiple, possibly conflicting objectives like cost, high performance, security and resiliency to viruses is a challenging endeavor. In this paper, we take a game-formation approach to network design where each player, for instance an autonomous system in the Internet, aims to collectively minimize the cost of installing links, of protecting against viruses, and of assuring connectivity. In the game, minimizing virus risk as well as connectivity costs results in sparse graphs. We show that the Nash Equilibria are trees that, according to the Price of Anarchy (PoA), are close to the global optimum, while the worst-case Nash Equilibrium and the global optimum may significantly differ for small infection rate and link installation cost. Moreover, the types of trees, in both the Nash Equilibria and the optimal solution, depend on the virus infection rate, which provides new insights into how viruses spread: for high infection rate &amp;#x03C4;, the path graph is the worst- and the star graph is the best-case Nash Equilibrium. However, for small and intermediate values of &amp;#x03C4;, trees different from the path and star graphs may be optimal.",fernando kuipers,Security,2015.0,10.1109/CDC.2015.7402216,2015 54th IEEE Conference on Decision and Control (CDC),Trajanovski2015,False,,IEEE,Not available,Designing virus-resistant networks: A game-formation approach,f01ec761a31087262975a75f48abb3d5,https://ieeexplore.ieee.org/document/7402216/
3357,"Forming, in a decentralized fashion, an optimal network topology while balancing multiple, possibly conflicting objectives like cost, high performance, security and resiliency to viruses is a challenging endeavor. In this paper, we take a game-formation approach to network design where each player, for instance an autonomous system in the Internet, aims to collectively minimize the cost of installing links, of protecting against viruses, and of assuring connectivity. In the game, minimizing virus risk as well as connectivity costs results in sparse graphs. We show that the Nash Equilibria are trees that, according to the Price of Anarchy (PoA), are close to the global optimum, while the worst-case Nash Equilibrium and the global optimum may significantly differ for small infection rate and link installation cost. Moreover, the types of trees, in both the Nash Equilibria and the optimal solution, depend on the virus infection rate, which provides new insights into how viruses spread: for high infection rate &amp;#x03C4;, the path graph is the worst- and the star graph is the best-case Nash Equilibrium. However, for small and intermediate values of &amp;#x03C4;, trees different from the path and star graphs may be optimal.",yezekael hayel,Games,2015.0,10.1109/CDC.2015.7402216,2015 54th IEEE Conference on Decision and Control (CDC),Trajanovski2015,False,,IEEE,Not available,Designing virus-resistant networks: A game-formation approach,f01ec761a31087262975a75f48abb3d5,https://ieeexplore.ieee.org/document/7402216/
3358,"Forming, in a decentralized fashion, an optimal network topology while balancing multiple, possibly conflicting objectives like cost, high performance, security and resiliency to viruses is a challenging endeavor. In this paper, we take a game-formation approach to network design where each player, for instance an autonomous system in the Internet, aims to collectively minimize the cost of installing links, of protecting against viruses, and of assuring connectivity. In the game, minimizing virus risk as well as connectivity costs results in sparse graphs. We show that the Nash Equilibria are trees that, according to the Price of Anarchy (PoA), are close to the global optimum, while the worst-case Nash Equilibrium and the global optimum may significantly differ for small infection rate and link installation cost. Moreover, the types of trees, in both the Nash Equilibria and the optimal solution, depend on the virus infection rate, which provides new insights into how viruses spread: for high infection rate &amp;#x03C4;, the path graph is the worst- and the star graph is the best-case Nash Equilibrium. However, for small and intermediate values of &amp;#x03C4;, trees different from the path and star graphs may be optimal.",yezekael hayel,Nash equilibrium,2015.0,10.1109/CDC.2015.7402216,2015 54th IEEE Conference on Decision and Control (CDC),Trajanovski2015,False,,IEEE,Not available,Designing virus-resistant networks: A game-formation approach,f01ec761a31087262975a75f48abb3d5,https://ieeexplore.ieee.org/document/7402216/
3359,"Forming, in a decentralized fashion, an optimal network topology while balancing multiple, possibly conflicting objectives like cost, high performance, security and resiliency to viruses is a challenging endeavor. In this paper, we take a game-formation approach to network design where each player, for instance an autonomous system in the Internet, aims to collectively minimize the cost of installing links, of protecting against viruses, and of assuring connectivity. In the game, minimizing virus risk as well as connectivity costs results in sparse graphs. We show that the Nash Equilibria are trees that, according to the Price of Anarchy (PoA), are close to the global optimum, while the worst-case Nash Equilibrium and the global optimum may significantly differ for small infection rate and link installation cost. Moreover, the types of trees, in both the Nash Equilibria and the optimal solution, depend on the virus infection rate, which provides new insights into how viruses spread: for high infection rate &amp;#x03C4;, the path graph is the worst- and the star graph is the best-case Nash Equilibrium. However, for small and intermediate values of &amp;#x03C4;, trees different from the path and star graphs may be optimal.",yezekael hayel,Viruses (medical),2015.0,10.1109/CDC.2015.7402216,2015 54th IEEE Conference on Decision and Control (CDC),Trajanovski2015,False,,IEEE,Not available,Designing virus-resistant networks: A game-formation approach,f01ec761a31087262975a75f48abb3d5,https://ieeexplore.ieee.org/document/7402216/
3360,"Forming, in a decentralized fashion, an optimal network topology while balancing multiple, possibly conflicting objectives like cost, high performance, security and resiliency to viruses is a challenging endeavor. In this paper, we take a game-formation approach to network design where each player, for instance an autonomous system in the Internet, aims to collectively minimize the cost of installing links, of protecting against viruses, and of assuring connectivity. In the game, minimizing virus risk as well as connectivity costs results in sparse graphs. We show that the Nash Equilibria are trees that, according to the Price of Anarchy (PoA), are close to the global optimum, while the worst-case Nash Equilibrium and the global optimum may significantly differ for small infection rate and link installation cost. Moreover, the types of trees, in both the Nash Equilibria and the optimal solution, depend on the virus infection rate, which provides new insights into how viruses spread: for high infection rate &amp;#x03C4;, the path graph is the worst- and the star graph is the best-case Nash Equilibrium. However, for small and intermediate values of &amp;#x03C4;, trees different from the path and star graphs may be optimal.",yezekael hayel,Network topology,2015.0,10.1109/CDC.2015.7402216,2015 54th IEEE Conference on Decision and Control (CDC),Trajanovski2015,False,,IEEE,Not available,Designing virus-resistant networks: A game-formation approach,f01ec761a31087262975a75f48abb3d5,https://ieeexplore.ieee.org/document/7402216/
3361,"Forming, in a decentralized fashion, an optimal network topology while balancing multiple, possibly conflicting objectives like cost, high performance, security and resiliency to viruses is a challenging endeavor. In this paper, we take a game-formation approach to network design where each player, for instance an autonomous system in the Internet, aims to collectively minimize the cost of installing links, of protecting against viruses, and of assuring connectivity. In the game, minimizing virus risk as well as connectivity costs results in sparse graphs. We show that the Nash Equilibria are trees that, according to the Price of Anarchy (PoA), are close to the global optimum, while the worst-case Nash Equilibrium and the global optimum may significantly differ for small infection rate and link installation cost. Moreover, the types of trees, in both the Nash Equilibria and the optimal solution, depend on the virus infection rate, which provides new insights into how viruses spread: for high infection rate &amp;#x03C4;, the path graph is the worst- and the star graph is the best-case Nash Equilibrium. However, for small and intermediate values of &amp;#x03C4;, trees different from the path and star graphs may be optimal.",yezekael hayel,Peer-to-peer computing,2015.0,10.1109/CDC.2015.7402216,2015 54th IEEE Conference on Decision and Control (CDC),Trajanovski2015,False,,IEEE,Not available,Designing virus-resistant networks: A game-formation approach,f01ec761a31087262975a75f48abb3d5,https://ieeexplore.ieee.org/document/7402216/
3362,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
3363,"Forming, in a decentralized fashion, an optimal network topology while balancing multiple, possibly conflicting objectives like cost, high performance, security and resiliency to viruses is a challenging endeavor. In this paper, we take a game-formation approach to network design where each player, for instance an autonomous system in the Internet, aims to collectively minimize the cost of installing links, of protecting against viruses, and of assuring connectivity. In the game, minimizing virus risk as well as connectivity costs results in sparse graphs. We show that the Nash Equilibria are trees that, according to the Price of Anarchy (PoA), are close to the global optimum, while the worst-case Nash Equilibrium and the global optimum may significantly differ for small infection rate and link installation cost. Moreover, the types of trees, in both the Nash Equilibria and the optimal solution, depend on the virus infection rate, which provides new insights into how viruses spread: for high infection rate &amp;#x03C4;, the path graph is the worst- and the star graph is the best-case Nash Equilibrium. However, for small and intermediate values of &amp;#x03C4;, trees different from the path and star graphs may be optimal.",yezekael hayel,Stability analysis,2015.0,10.1109/CDC.2015.7402216,2015 54th IEEE Conference on Decision and Control (CDC),Trajanovski2015,False,,IEEE,Not available,Designing virus-resistant networks: A game-formation approach,f01ec761a31087262975a75f48abb3d5,https://ieeexplore.ieee.org/document/7402216/
3364,"Forming, in a decentralized fashion, an optimal network topology while balancing multiple, possibly conflicting objectives like cost, high performance, security and resiliency to viruses is a challenging endeavor. In this paper, we take a game-formation approach to network design where each player, for instance an autonomous system in the Internet, aims to collectively minimize the cost of installing links, of protecting against viruses, and of assuring connectivity. In the game, minimizing virus risk as well as connectivity costs results in sparse graphs. We show that the Nash Equilibria are trees that, according to the Price of Anarchy (PoA), are close to the global optimum, while the worst-case Nash Equilibrium and the global optimum may significantly differ for small infection rate and link installation cost. Moreover, the types of trees, in both the Nash Equilibria and the optimal solution, depend on the virus infection rate, which provides new insights into how viruses spread: for high infection rate &amp;#x03C4;, the path graph is the worst- and the star graph is the best-case Nash Equilibrium. However, for small and intermediate values of &amp;#x03C4;, trees different from the path and star graphs may be optimal.",yezekael hayel,Security,2015.0,10.1109/CDC.2015.7402216,2015 54th IEEE Conference on Decision and Control (CDC),Trajanovski2015,False,,IEEE,Not available,Designing virus-resistant networks: A game-formation approach,f01ec761a31087262975a75f48abb3d5,https://ieeexplore.ieee.org/document/7402216/
3365,"Forming, in a decentralized fashion, an optimal network topology while balancing multiple, possibly conflicting objectives like cost, high performance, security and resiliency to viruses is a challenging endeavor. In this paper, we take a game-formation approach to network design where each player, for instance an autonomous system in the Internet, aims to collectively minimize the cost of installing links, of protecting against viruses, and of assuring connectivity. In the game, minimizing virus risk as well as connectivity costs results in sparse graphs. We show that the Nash Equilibria are trees that, according to the Price of Anarchy (PoA), are close to the global optimum, while the worst-case Nash Equilibrium and the global optimum may significantly differ for small infection rate and link installation cost. Moreover, the types of trees, in both the Nash Equilibria and the optimal solution, depend on the virus infection rate, which provides new insights into how viruses spread: for high infection rate &amp;#x03C4;, the path graph is the worst- and the star graph is the best-case Nash Equilibrium. However, for small and intermediate values of &amp;#x03C4;, trees different from the path and star graphs may be optimal.",eitan altman,Games,2015.0,10.1109/CDC.2015.7402216,2015 54th IEEE Conference on Decision and Control (CDC),Trajanovski2015,False,,IEEE,Not available,Designing virus-resistant networks: A game-formation approach,f01ec761a31087262975a75f48abb3d5,https://ieeexplore.ieee.org/document/7402216/
3366,"Forming, in a decentralized fashion, an optimal network topology while balancing multiple, possibly conflicting objectives like cost, high performance, security and resiliency to viruses is a challenging endeavor. In this paper, we take a game-formation approach to network design where each player, for instance an autonomous system in the Internet, aims to collectively minimize the cost of installing links, of protecting against viruses, and of assuring connectivity. In the game, minimizing virus risk as well as connectivity costs results in sparse graphs. We show that the Nash Equilibria are trees that, according to the Price of Anarchy (PoA), are close to the global optimum, while the worst-case Nash Equilibrium and the global optimum may significantly differ for small infection rate and link installation cost. Moreover, the types of trees, in both the Nash Equilibria and the optimal solution, depend on the virus infection rate, which provides new insights into how viruses spread: for high infection rate &amp;#x03C4;, the path graph is the worst- and the star graph is the best-case Nash Equilibrium. However, for small and intermediate values of &amp;#x03C4;, trees different from the path and star graphs may be optimal.",eitan altman,Nash equilibrium,2015.0,10.1109/CDC.2015.7402216,2015 54th IEEE Conference on Decision and Control (CDC),Trajanovski2015,False,,IEEE,Not available,Designing virus-resistant networks: A game-formation approach,f01ec761a31087262975a75f48abb3d5,https://ieeexplore.ieee.org/document/7402216/
3367,"Forming, in a decentralized fashion, an optimal network topology while balancing multiple, possibly conflicting objectives like cost, high performance, security and resiliency to viruses is a challenging endeavor. In this paper, we take a game-formation approach to network design where each player, for instance an autonomous system in the Internet, aims to collectively minimize the cost of installing links, of protecting against viruses, and of assuring connectivity. In the game, minimizing virus risk as well as connectivity costs results in sparse graphs. We show that the Nash Equilibria are trees that, according to the Price of Anarchy (PoA), are close to the global optimum, while the worst-case Nash Equilibrium and the global optimum may significantly differ for small infection rate and link installation cost. Moreover, the types of trees, in both the Nash Equilibria and the optimal solution, depend on the virus infection rate, which provides new insights into how viruses spread: for high infection rate &amp;#x03C4;, the path graph is the worst- and the star graph is the best-case Nash Equilibrium. However, for small and intermediate values of &amp;#x03C4;, trees different from the path and star graphs may be optimal.",eitan altman,Viruses (medical),2015.0,10.1109/CDC.2015.7402216,2015 54th IEEE Conference on Decision and Control (CDC),Trajanovski2015,False,,IEEE,Not available,Designing virus-resistant networks: A game-formation approach,f01ec761a31087262975a75f48abb3d5,https://ieeexplore.ieee.org/document/7402216/
3368,"Forming, in a decentralized fashion, an optimal network topology while balancing multiple, possibly conflicting objectives like cost, high performance, security and resiliency to viruses is a challenging endeavor. In this paper, we take a game-formation approach to network design where each player, for instance an autonomous system in the Internet, aims to collectively minimize the cost of installing links, of protecting against viruses, and of assuring connectivity. In the game, minimizing virus risk as well as connectivity costs results in sparse graphs. We show that the Nash Equilibria are trees that, according to the Price of Anarchy (PoA), are close to the global optimum, while the worst-case Nash Equilibrium and the global optimum may significantly differ for small infection rate and link installation cost. Moreover, the types of trees, in both the Nash Equilibria and the optimal solution, depend on the virus infection rate, which provides new insights into how viruses spread: for high infection rate &amp;#x03C4;, the path graph is the worst- and the star graph is the best-case Nash Equilibrium. However, for small and intermediate values of &amp;#x03C4;, trees different from the path and star graphs may be optimal.",eitan altman,Network topology,2015.0,10.1109/CDC.2015.7402216,2015 54th IEEE Conference on Decision and Control (CDC),Trajanovski2015,False,,IEEE,Not available,Designing virus-resistant networks: A game-formation approach,f01ec761a31087262975a75f48abb3d5,https://ieeexplore.ieee.org/document/7402216/
3369,"Forming, in a decentralized fashion, an optimal network topology while balancing multiple, possibly conflicting objectives like cost, high performance, security and resiliency to viruses is a challenging endeavor. In this paper, we take a game-formation approach to network design where each player, for instance an autonomous system in the Internet, aims to collectively minimize the cost of installing links, of protecting against viruses, and of assuring connectivity. In the game, minimizing virus risk as well as connectivity costs results in sparse graphs. We show that the Nash Equilibria are trees that, according to the Price of Anarchy (PoA), are close to the global optimum, while the worst-case Nash Equilibrium and the global optimum may significantly differ for small infection rate and link installation cost. Moreover, the types of trees, in both the Nash Equilibria and the optimal solution, depend on the virus infection rate, which provides new insights into how viruses spread: for high infection rate &amp;#x03C4;, the path graph is the worst- and the star graph is the best-case Nash Equilibrium. However, for small and intermediate values of &amp;#x03C4;, trees different from the path and star graphs may be optimal.",eitan altman,Peer-to-peer computing,2015.0,10.1109/CDC.2015.7402216,2015 54th IEEE Conference on Decision and Control (CDC),Trajanovski2015,False,,IEEE,Not available,Designing virus-resistant networks: A game-formation approach,f01ec761a31087262975a75f48abb3d5,https://ieeexplore.ieee.org/document/7402216/
3370,"Forming, in a decentralized fashion, an optimal network topology while balancing multiple, possibly conflicting objectives like cost, high performance, security and resiliency to viruses is a challenging endeavor. In this paper, we take a game-formation approach to network design where each player, for instance an autonomous system in the Internet, aims to collectively minimize the cost of installing links, of protecting against viruses, and of assuring connectivity. In the game, minimizing virus risk as well as connectivity costs results in sparse graphs. We show that the Nash Equilibria are trees that, according to the Price of Anarchy (PoA), are close to the global optimum, while the worst-case Nash Equilibrium and the global optimum may significantly differ for small infection rate and link installation cost. Moreover, the types of trees, in both the Nash Equilibria and the optimal solution, depend on the virus infection rate, which provides new insights into how viruses spread: for high infection rate &amp;#x03C4;, the path graph is the worst- and the star graph is the best-case Nash Equilibrium. However, for small and intermediate values of &amp;#x03C4;, trees different from the path and star graphs may be optimal.",eitan altman,Stability analysis,2015.0,10.1109/CDC.2015.7402216,2015 54th IEEE Conference on Decision and Control (CDC),Trajanovski2015,False,,IEEE,Not available,Designing virus-resistant networks: A game-formation approach,f01ec761a31087262975a75f48abb3d5,https://ieeexplore.ieee.org/document/7402216/
3371,"Forming, in a decentralized fashion, an optimal network topology while balancing multiple, possibly conflicting objectives like cost, high performance, security and resiliency to viruses is a challenging endeavor. In this paper, we take a game-formation approach to network design where each player, for instance an autonomous system in the Internet, aims to collectively minimize the cost of installing links, of protecting against viruses, and of assuring connectivity. In the game, minimizing virus risk as well as connectivity costs results in sparse graphs. We show that the Nash Equilibria are trees that, according to the Price of Anarchy (PoA), are close to the global optimum, while the worst-case Nash Equilibrium and the global optimum may significantly differ for small infection rate and link installation cost. Moreover, the types of trees, in both the Nash Equilibria and the optimal solution, depend on the virus infection rate, which provides new insights into how viruses spread: for high infection rate &amp;#x03C4;, the path graph is the worst- and the star graph is the best-case Nash Equilibrium. However, for small and intermediate values of &amp;#x03C4;, trees different from the path and star graphs may be optimal.",eitan altman,Security,2015.0,10.1109/CDC.2015.7402216,2015 54th IEEE Conference on Decision and Control (CDC),Trajanovski2015,False,,IEEE,Not available,Designing virus-resistant networks: A game-formation approach,f01ec761a31087262975a75f48abb3d5,https://ieeexplore.ieee.org/document/7402216/
3372,"Forming, in a decentralized fashion, an optimal network topology while balancing multiple, possibly conflicting objectives like cost, high performance, security and resiliency to viruses is a challenging endeavor. In this paper, we take a game-formation approach to network design where each player, for instance an autonomous system in the Internet, aims to collectively minimize the cost of installing links, of protecting against viruses, and of assuring connectivity. In the game, minimizing virus risk as well as connectivity costs results in sparse graphs. We show that the Nash Equilibria are trees that, according to the Price of Anarchy (PoA), are close to the global optimum, while the worst-case Nash Equilibrium and the global optimum may significantly differ for small infection rate and link installation cost. Moreover, the types of trees, in both the Nash Equilibria and the optimal solution, depend on the virus infection rate, which provides new insights into how viruses spread: for high infection rate &amp;#x03C4;, the path graph is the worst- and the star graph is the best-case Nash Equilibrium. However, for small and intermediate values of &amp;#x03C4;, trees different from the path and star graphs may be optimal.",piet mieghem,Games,2015.0,10.1109/CDC.2015.7402216,2015 54th IEEE Conference on Decision and Control (CDC),Trajanovski2015,False,,IEEE,Not available,Designing virus-resistant networks: A game-formation approach,f01ec761a31087262975a75f48abb3d5,https://ieeexplore.ieee.org/document/7402216/
3373,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
3374,"Forming, in a decentralized fashion, an optimal network topology while balancing multiple, possibly conflicting objectives like cost, high performance, security and resiliency to viruses is a challenging endeavor. In this paper, we take a game-formation approach to network design where each player, for instance an autonomous system in the Internet, aims to collectively minimize the cost of installing links, of protecting against viruses, and of assuring connectivity. In the game, minimizing virus risk as well as connectivity costs results in sparse graphs. We show that the Nash Equilibria are trees that, according to the Price of Anarchy (PoA), are close to the global optimum, while the worst-case Nash Equilibrium and the global optimum may significantly differ for small infection rate and link installation cost. Moreover, the types of trees, in both the Nash Equilibria and the optimal solution, depend on the virus infection rate, which provides new insights into how viruses spread: for high infection rate &amp;#x03C4;, the path graph is the worst- and the star graph is the best-case Nash Equilibrium. However, for small and intermediate values of &amp;#x03C4;, trees different from the path and star graphs may be optimal.",piet mieghem,Nash equilibrium,2015.0,10.1109/CDC.2015.7402216,2015 54th IEEE Conference on Decision and Control (CDC),Trajanovski2015,False,,IEEE,Not available,Designing virus-resistant networks: A game-formation approach,f01ec761a31087262975a75f48abb3d5,https://ieeexplore.ieee.org/document/7402216/
3375,"Forming, in a decentralized fashion, an optimal network topology while balancing multiple, possibly conflicting objectives like cost, high performance, security and resiliency to viruses is a challenging endeavor. In this paper, we take a game-formation approach to network design where each player, for instance an autonomous system in the Internet, aims to collectively minimize the cost of installing links, of protecting against viruses, and of assuring connectivity. In the game, minimizing virus risk as well as connectivity costs results in sparse graphs. We show that the Nash Equilibria are trees that, according to the Price of Anarchy (PoA), are close to the global optimum, while the worst-case Nash Equilibrium and the global optimum may significantly differ for small infection rate and link installation cost. Moreover, the types of trees, in both the Nash Equilibria and the optimal solution, depend on the virus infection rate, which provides new insights into how viruses spread: for high infection rate &amp;#x03C4;, the path graph is the worst- and the star graph is the best-case Nash Equilibrium. However, for small and intermediate values of &amp;#x03C4;, trees different from the path and star graphs may be optimal.",piet mieghem,Viruses (medical),2015.0,10.1109/CDC.2015.7402216,2015 54th IEEE Conference on Decision and Control (CDC),Trajanovski2015,False,,IEEE,Not available,Designing virus-resistant networks: A game-formation approach,f01ec761a31087262975a75f48abb3d5,https://ieeexplore.ieee.org/document/7402216/
3376,"Forming, in a decentralized fashion, an optimal network topology while balancing multiple, possibly conflicting objectives like cost, high performance, security and resiliency to viruses is a challenging endeavor. In this paper, we take a game-formation approach to network design where each player, for instance an autonomous system in the Internet, aims to collectively minimize the cost of installing links, of protecting against viruses, and of assuring connectivity. In the game, minimizing virus risk as well as connectivity costs results in sparse graphs. We show that the Nash Equilibria are trees that, according to the Price of Anarchy (PoA), are close to the global optimum, while the worst-case Nash Equilibrium and the global optimum may significantly differ for small infection rate and link installation cost. Moreover, the types of trees, in both the Nash Equilibria and the optimal solution, depend on the virus infection rate, which provides new insights into how viruses spread: for high infection rate &amp;#x03C4;, the path graph is the worst- and the star graph is the best-case Nash Equilibrium. However, for small and intermediate values of &amp;#x03C4;, trees different from the path and star graphs may be optimal.",piet mieghem,Network topology,2015.0,10.1109/CDC.2015.7402216,2015 54th IEEE Conference on Decision and Control (CDC),Trajanovski2015,False,,IEEE,Not available,Designing virus-resistant networks: A game-formation approach,f01ec761a31087262975a75f48abb3d5,https://ieeexplore.ieee.org/document/7402216/
3377,"Forming, in a decentralized fashion, an optimal network topology while balancing multiple, possibly conflicting objectives like cost, high performance, security and resiliency to viruses is a challenging endeavor. In this paper, we take a game-formation approach to network design where each player, for instance an autonomous system in the Internet, aims to collectively minimize the cost of installing links, of protecting against viruses, and of assuring connectivity. In the game, minimizing virus risk as well as connectivity costs results in sparse graphs. We show that the Nash Equilibria are trees that, according to the Price of Anarchy (PoA), are close to the global optimum, while the worst-case Nash Equilibrium and the global optimum may significantly differ for small infection rate and link installation cost. Moreover, the types of trees, in both the Nash Equilibria and the optimal solution, depend on the virus infection rate, which provides new insights into how viruses spread: for high infection rate &amp;#x03C4;, the path graph is the worst- and the star graph is the best-case Nash Equilibrium. However, for small and intermediate values of &amp;#x03C4;, trees different from the path and star graphs may be optimal.",piet mieghem,Peer-to-peer computing,2015.0,10.1109/CDC.2015.7402216,2015 54th IEEE Conference on Decision and Control (CDC),Trajanovski2015,False,,IEEE,Not available,Designing virus-resistant networks: A game-formation approach,f01ec761a31087262975a75f48abb3d5,https://ieeexplore.ieee.org/document/7402216/
3378,"Forming, in a decentralized fashion, an optimal network topology while balancing multiple, possibly conflicting objectives like cost, high performance, security and resiliency to viruses is a challenging endeavor. In this paper, we take a game-formation approach to network design where each player, for instance an autonomous system in the Internet, aims to collectively minimize the cost of installing links, of protecting against viruses, and of assuring connectivity. In the game, minimizing virus risk as well as connectivity costs results in sparse graphs. We show that the Nash Equilibria are trees that, according to the Price of Anarchy (PoA), are close to the global optimum, while the worst-case Nash Equilibrium and the global optimum may significantly differ for small infection rate and link installation cost. Moreover, the types of trees, in both the Nash Equilibria and the optimal solution, depend on the virus infection rate, which provides new insights into how viruses spread: for high infection rate &amp;#x03C4;, the path graph is the worst- and the star graph is the best-case Nash Equilibrium. However, for small and intermediate values of &amp;#x03C4;, trees different from the path and star graphs may be optimal.",piet mieghem,Stability analysis,2015.0,10.1109/CDC.2015.7402216,2015 54th IEEE Conference on Decision and Control (CDC),Trajanovski2015,False,,IEEE,Not available,Designing virus-resistant networks: A game-formation approach,f01ec761a31087262975a75f48abb3d5,https://ieeexplore.ieee.org/document/7402216/
3379,"Forming, in a decentralized fashion, an optimal network topology while balancing multiple, possibly conflicting objectives like cost, high performance, security and resiliency to viruses is a challenging endeavor. In this paper, we take a game-formation approach to network design where each player, for instance an autonomous system in the Internet, aims to collectively minimize the cost of installing links, of protecting against viruses, and of assuring connectivity. In the game, minimizing virus risk as well as connectivity costs results in sparse graphs. We show that the Nash Equilibria are trees that, according to the Price of Anarchy (PoA), are close to the global optimum, while the worst-case Nash Equilibrium and the global optimum may significantly differ for small infection rate and link installation cost. Moreover, the types of trees, in both the Nash Equilibria and the optimal solution, depend on the virus infection rate, which provides new insights into how viruses spread: for high infection rate &amp;#x03C4;, the path graph is the worst- and the star graph is the best-case Nash Equilibrium. However, for small and intermediate values of &amp;#x03C4;, trees different from the path and star graphs may be optimal.",piet mieghem,Security,2015.0,10.1109/CDC.2015.7402216,2015 54th IEEE Conference on Decision and Control (CDC),Trajanovski2015,False,,IEEE,Not available,Designing virus-resistant networks: A game-formation approach,f01ec761a31087262975a75f48abb3d5,https://ieeexplore.ieee.org/document/7402216/
3380,"Cloud computing is an emerging paradigm in which tasks are assigned to a combination (“cloud”) of servers and devices, accessed over a network. Typically, the cloud constitutes an additional means of computation and a user can perform workload factoring, i.e., split its load between the cloud and its other resources. Based on empirical data, we demonstrate that there is an intrinsic relation between the “benefit” that a user perceives from the cloud and the usage pattern followed by other users. This gives rise to a non-cooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the “price of anarchy” of the game and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the gap can be arbitrarily large. We show that, somewhat counter-intuitively, exercising admission control to the cloud may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the cloud to a wide range of user types.",amir nahir,Nash equilibrium,2012.0,10.1109/INFCOM.2012.6195654,2012 Proceedings IEEE INFOCOM,Nahir2012,False,,IEEE,Not available,Workload factoring with the cloud: A game-theoretic perspective,fc7bc0b9549818f101c17163380585b3,https://ieeexplore.ieee.org/document/6195654/
3381,"Cloud computing is an emerging paradigm in which tasks are assigned to a combination (“cloud”) of servers and devices, accessed over a network. Typically, the cloud constitutes an additional means of computation and a user can perform workload factoring, i.e., split its load between the cloud and its other resources. Based on empirical data, we demonstrate that there is an intrinsic relation between the “benefit” that a user perceives from the cloud and the usage pattern followed by other users. This gives rise to a non-cooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the “price of anarchy” of the game and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the gap can be arbitrarily large. We show that, somewhat counter-intuitively, exercising admission control to the cloud may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the cloud to a wide range of user types.",amir nahir,Games,2012.0,10.1109/INFCOM.2012.6195654,2012 Proceedings IEEE INFOCOM,Nahir2012,False,,IEEE,Not available,Workload factoring with the cloud: A game-theoretic perspective,fc7bc0b9549818f101c17163380585b3,https://ieeexplore.ieee.org/document/6195654/
3382,"Cloud computing is an emerging paradigm in which tasks are assigned to a combination (“cloud”) of servers and devices, accessed over a network. Typically, the cloud constitutes an additional means of computation and a user can perform workload factoring, i.e., split its load between the cloud and its other resources. Based on empirical data, we demonstrate that there is an intrinsic relation between the “benefit” that a user perceives from the cloud and the usage pattern followed by other users. This gives rise to a non-cooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the “price of anarchy” of the game and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the gap can be arbitrarily large. We show that, somewhat counter-intuitively, exercising admission control to the cloud may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the cloud to a wide range of user types.",amir nahir,Cloud computing,2012.0,10.1109/INFCOM.2012.6195654,2012 Proceedings IEEE INFOCOM,Nahir2012,False,,IEEE,Not available,Workload factoring with the cloud: A game-theoretic perspective,fc7bc0b9549818f101c17163380585b3,https://ieeexplore.ieee.org/document/6195654/
3383,"Cloud computing is an emerging paradigm in which tasks are assigned to a combination (“cloud”) of servers and devices, accessed over a network. Typically, the cloud constitutes an additional means of computation and a user can perform workload factoring, i.e., split its load between the cloud and its other resources. Based on empirical data, we demonstrate that there is an intrinsic relation between the “benefit” that a user perceives from the cloud and the usage pattern followed by other users. This gives rise to a non-cooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the “price of anarchy” of the game and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the gap can be arbitrarily large. We show that, somewhat counter-intuitively, exercising admission control to the cloud may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the cloud to a wide range of user types.",amir nahir,Time factors,2012.0,10.1109/INFCOM.2012.6195654,2012 Proceedings IEEE INFOCOM,Nahir2012,False,,IEEE,Not available,Workload factoring with the cloud: A game-theoretic perspective,fc7bc0b9549818f101c17163380585b3,https://ieeexplore.ieee.org/document/6195654/
3384,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
3385,"Cloud computing is an emerging paradigm in which tasks are assigned to a combination (“cloud”) of servers and devices, accessed over a network. Typically, the cloud constitutes an additional means of computation and a user can perform workload factoring, i.e., split its load between the cloud and its other resources. Based on empirical data, we demonstrate that there is an intrinsic relation between the “benefit” that a user perceives from the cloud and the usage pattern followed by other users. This gives rise to a non-cooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the “price of anarchy” of the game and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the gap can be arbitrarily large. We show that, somewhat counter-intuitively, exercising admission control to the cloud may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the cloud to a wide range of user types.",amir nahir,Delay,2012.0,10.1109/INFCOM.2012.6195654,2012 Proceedings IEEE INFOCOM,Nahir2012,False,,IEEE,Not available,Workload factoring with the cloud: A game-theoretic perspective,fc7bc0b9549818f101c17163380585b3,https://ieeexplore.ieee.org/document/6195654/
3386,"Cloud computing is an emerging paradigm in which tasks are assigned to a combination (“cloud”) of servers and devices, accessed over a network. Typically, the cloud constitutes an additional means of computation and a user can perform workload factoring, i.e., split its load between the cloud and its other resources. Based on empirical data, we demonstrate that there is an intrinsic relation between the “benefit” that a user perceives from the cloud and the usage pattern followed by other users. This gives rise to a non-cooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the “price of anarchy” of the game and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the gap can be arbitrarily large. We show that, somewhat counter-intuitively, exercising admission control to the cloud may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the cloud to a wide range of user types.",amir nahir,Servers,2012.0,10.1109/INFCOM.2012.6195654,2012 Proceedings IEEE INFOCOM,Nahir2012,False,,IEEE,Not available,Workload factoring with the cloud: A game-theoretic perspective,fc7bc0b9549818f101c17163380585b3,https://ieeexplore.ieee.org/document/6195654/
3387,"Cloud computing is an emerging paradigm in which tasks are assigned to a combination (“cloud”) of servers and devices, accessed over a network. Typically, the cloud constitutes an additional means of computation and a user can perform workload factoring, i.e., split its load between the cloud and its other resources. Based on empirical data, we demonstrate that there is an intrinsic relation between the “benefit” that a user perceives from the cloud and the usage pattern followed by other users. This gives rise to a non-cooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the “price of anarchy” of the game and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the gap can be arbitrarily large. We show that, somewhat counter-intuitively, exercising admission control to the cloud may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the cloud to a wide range of user types.",amir nahir,Outsourcing,2012.0,10.1109/INFCOM.2012.6195654,2012 Proceedings IEEE INFOCOM,Nahir2012,False,,IEEE,Not available,Workload factoring with the cloud: A game-theoretic perspective,fc7bc0b9549818f101c17163380585b3,https://ieeexplore.ieee.org/document/6195654/
3388,"Cloud computing is an emerging paradigm in which tasks are assigned to a combination (“cloud”) of servers and devices, accessed over a network. Typically, the cloud constitutes an additional means of computation and a user can perform workload factoring, i.e., split its load between the cloud and its other resources. Based on empirical data, we demonstrate that there is an intrinsic relation between the “benefit” that a user perceives from the cloud and the usage pattern followed by other users. This gives rise to a non-cooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the “price of anarchy” of the game and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the gap can be arbitrarily large. We show that, somewhat counter-intuitively, exercising admission control to the cloud may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the cloud to a wide range of user types.",ariel orda,Nash equilibrium,2012.0,10.1109/INFCOM.2012.6195654,2012 Proceedings IEEE INFOCOM,Nahir2012,False,,IEEE,Not available,Workload factoring with the cloud: A game-theoretic perspective,fc7bc0b9549818f101c17163380585b3,https://ieeexplore.ieee.org/document/6195654/
3389,"Cloud computing is an emerging paradigm in which tasks are assigned to a combination (“cloud”) of servers and devices, accessed over a network. Typically, the cloud constitutes an additional means of computation and a user can perform workload factoring, i.e., split its load between the cloud and its other resources. Based on empirical data, we demonstrate that there is an intrinsic relation between the “benefit” that a user perceives from the cloud and the usage pattern followed by other users. This gives rise to a non-cooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the “price of anarchy” of the game and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the gap can be arbitrarily large. We show that, somewhat counter-intuitively, exercising admission control to the cloud may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the cloud to a wide range of user types.",ariel orda,Games,2012.0,10.1109/INFCOM.2012.6195654,2012 Proceedings IEEE INFOCOM,Nahir2012,False,,IEEE,Not available,Workload factoring with the cloud: A game-theoretic perspective,fc7bc0b9549818f101c17163380585b3,https://ieeexplore.ieee.org/document/6195654/
3390,"Cloud computing is an emerging paradigm in which tasks are assigned to a combination (“cloud”) of servers and devices, accessed over a network. Typically, the cloud constitutes an additional means of computation and a user can perform workload factoring, i.e., split its load between the cloud and its other resources. Based on empirical data, we demonstrate that there is an intrinsic relation between the “benefit” that a user perceives from the cloud and the usage pattern followed by other users. This gives rise to a non-cooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the “price of anarchy” of the game and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the gap can be arbitrarily large. We show that, somewhat counter-intuitively, exercising admission control to the cloud may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the cloud to a wide range of user types.",ariel orda,Cloud computing,2012.0,10.1109/INFCOM.2012.6195654,2012 Proceedings IEEE INFOCOM,Nahir2012,False,,IEEE,Not available,Workload factoring with the cloud: A game-theoretic perspective,fc7bc0b9549818f101c17163380585b3,https://ieeexplore.ieee.org/document/6195654/
3391,"Cloud computing is an emerging paradigm in which tasks are assigned to a combination (“cloud”) of servers and devices, accessed over a network. Typically, the cloud constitutes an additional means of computation and a user can perform workload factoring, i.e., split its load between the cloud and its other resources. Based on empirical data, we demonstrate that there is an intrinsic relation between the “benefit” that a user perceives from the cloud and the usage pattern followed by other users. This gives rise to a non-cooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the “price of anarchy” of the game and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the gap can be arbitrarily large. We show that, somewhat counter-intuitively, exercising admission control to the cloud may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the cloud to a wide range of user types.",ariel orda,Time factors,2012.0,10.1109/INFCOM.2012.6195654,2012 Proceedings IEEE INFOCOM,Nahir2012,False,,IEEE,Not available,Workload factoring with the cloud: A game-theoretic perspective,fc7bc0b9549818f101c17163380585b3,https://ieeexplore.ieee.org/document/6195654/
3392,"Cloud computing is an emerging paradigm in which tasks are assigned to a combination (“cloud”) of servers and devices, accessed over a network. Typically, the cloud constitutes an additional means of computation and a user can perform workload factoring, i.e., split its load between the cloud and its other resources. Based on empirical data, we demonstrate that there is an intrinsic relation between the “benefit” that a user perceives from the cloud and the usage pattern followed by other users. This gives rise to a non-cooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the “price of anarchy” of the game and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the gap can be arbitrarily large. We show that, somewhat counter-intuitively, exercising admission control to the cloud may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the cloud to a wide range of user types.",ariel orda,Delay,2012.0,10.1109/INFCOM.2012.6195654,2012 Proceedings IEEE INFOCOM,Nahir2012,False,,IEEE,Not available,Workload factoring with the cloud: A game-theoretic perspective,fc7bc0b9549818f101c17163380585b3,https://ieeexplore.ieee.org/document/6195654/
3393,"Cloud computing is an emerging paradigm in which tasks are assigned to a combination (“cloud”) of servers and devices, accessed over a network. Typically, the cloud constitutes an additional means of computation and a user can perform workload factoring, i.e., split its load between the cloud and its other resources. Based on empirical data, we demonstrate that there is an intrinsic relation between the “benefit” that a user perceives from the cloud and the usage pattern followed by other users. This gives rise to a non-cooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the “price of anarchy” of the game and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the gap can be arbitrarily large. We show that, somewhat counter-intuitively, exercising admission control to the cloud may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the cloud to a wide range of user types.",ariel orda,Servers,2012.0,10.1109/INFCOM.2012.6195654,2012 Proceedings IEEE INFOCOM,Nahir2012,False,,IEEE,Not available,Workload factoring with the cloud: A game-theoretic perspective,fc7bc0b9549818f101c17163380585b3,https://ieeexplore.ieee.org/document/6195654/
3394,"Cloud computing is an emerging paradigm in which tasks are assigned to a combination (“cloud”) of servers and devices, accessed over a network. Typically, the cloud constitutes an additional means of computation and a user can perform workload factoring, i.e., split its load between the cloud and its other resources. Based on empirical data, we demonstrate that there is an intrinsic relation between the “benefit” that a user perceives from the cloud and the usage pattern followed by other users. This gives rise to a non-cooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the “price of anarchy” of the game and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the gap can be arbitrarily large. We show that, somewhat counter-intuitively, exercising admission control to the cloud may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the cloud to a wide range of user types.",ariel orda,Outsourcing,2012.0,10.1109/INFCOM.2012.6195654,2012 Proceedings IEEE INFOCOM,Nahir2012,False,,IEEE,Not available,Workload factoring with the cloud: A game-theoretic perspective,fc7bc0b9549818f101c17163380585b3,https://ieeexplore.ieee.org/document/6195654/
3395,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
3396,"Cloud computing is an emerging paradigm in which tasks are assigned to a combination (“cloud”) of servers and devices, accessed over a network. Typically, the cloud constitutes an additional means of computation and a user can perform workload factoring, i.e., split its load between the cloud and its other resources. Based on empirical data, we demonstrate that there is an intrinsic relation between the “benefit” that a user perceives from the cloud and the usage pattern followed by other users. This gives rise to a non-cooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the “price of anarchy” of the game and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the gap can be arbitrarily large. We show that, somewhat counter-intuitively, exercising admission control to the cloud may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the cloud to a wide range of user types.",danny raz,Nash equilibrium,2012.0,10.1109/INFCOM.2012.6195654,2012 Proceedings IEEE INFOCOM,Nahir2012,False,,IEEE,Not available,Workload factoring with the cloud: A game-theoretic perspective,fc7bc0b9549818f101c17163380585b3,https://ieeexplore.ieee.org/document/6195654/
3397,"Cloud computing is an emerging paradigm in which tasks are assigned to a combination (“cloud”) of servers and devices, accessed over a network. Typically, the cloud constitutes an additional means of computation and a user can perform workload factoring, i.e., split its load between the cloud and its other resources. Based on empirical data, we demonstrate that there is an intrinsic relation between the “benefit” that a user perceives from the cloud and the usage pattern followed by other users. This gives rise to a non-cooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the “price of anarchy” of the game and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the gap can be arbitrarily large. We show that, somewhat counter-intuitively, exercising admission control to the cloud may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the cloud to a wide range of user types.",danny raz,Games,2012.0,10.1109/INFCOM.2012.6195654,2012 Proceedings IEEE INFOCOM,Nahir2012,False,,IEEE,Not available,Workload factoring with the cloud: A game-theoretic perspective,fc7bc0b9549818f101c17163380585b3,https://ieeexplore.ieee.org/document/6195654/
3398,"Cloud computing is an emerging paradigm in which tasks are assigned to a combination (“cloud”) of servers and devices, accessed over a network. Typically, the cloud constitutes an additional means of computation and a user can perform workload factoring, i.e., split its load between the cloud and its other resources. Based on empirical data, we demonstrate that there is an intrinsic relation between the “benefit” that a user perceives from the cloud and the usage pattern followed by other users. This gives rise to a non-cooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the “price of anarchy” of the game and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the gap can be arbitrarily large. We show that, somewhat counter-intuitively, exercising admission control to the cloud may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the cloud to a wide range of user types.",danny raz,Cloud computing,2012.0,10.1109/INFCOM.2012.6195654,2012 Proceedings IEEE INFOCOM,Nahir2012,False,,IEEE,Not available,Workload factoring with the cloud: A game-theoretic perspective,fc7bc0b9549818f101c17163380585b3,https://ieeexplore.ieee.org/document/6195654/
3399,"Cloud computing is an emerging paradigm in which tasks are assigned to a combination (“cloud”) of servers and devices, accessed over a network. Typically, the cloud constitutes an additional means of computation and a user can perform workload factoring, i.e., split its load between the cloud and its other resources. Based on empirical data, we demonstrate that there is an intrinsic relation between the “benefit” that a user perceives from the cloud and the usage pattern followed by other users. This gives rise to a non-cooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the “price of anarchy” of the game and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the gap can be arbitrarily large. We show that, somewhat counter-intuitively, exercising admission control to the cloud may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the cloud to a wide range of user types.",danny raz,Time factors,2012.0,10.1109/INFCOM.2012.6195654,2012 Proceedings IEEE INFOCOM,Nahir2012,False,,IEEE,Not available,Workload factoring with the cloud: A game-theoretic perspective,fc7bc0b9549818f101c17163380585b3,https://ieeexplore.ieee.org/document/6195654/
3400,"Cloud computing is an emerging paradigm in which tasks are assigned to a combination (“cloud”) of servers and devices, accessed over a network. Typically, the cloud constitutes an additional means of computation and a user can perform workload factoring, i.e., split its load between the cloud and its other resources. Based on empirical data, we demonstrate that there is an intrinsic relation between the “benefit” that a user perceives from the cloud and the usage pattern followed by other users. This gives rise to a non-cooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the “price of anarchy” of the game and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the gap can be arbitrarily large. We show that, somewhat counter-intuitively, exercising admission control to the cloud may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the cloud to a wide range of user types.",danny raz,Delay,2012.0,10.1109/INFCOM.2012.6195654,2012 Proceedings IEEE INFOCOM,Nahir2012,False,,IEEE,Not available,Workload factoring with the cloud: A game-theoretic perspective,fc7bc0b9549818f101c17163380585b3,https://ieeexplore.ieee.org/document/6195654/
3401,"Cloud computing is an emerging paradigm in which tasks are assigned to a combination (“cloud”) of servers and devices, accessed over a network. Typically, the cloud constitutes an additional means of computation and a user can perform workload factoring, i.e., split its load between the cloud and its other resources. Based on empirical data, we demonstrate that there is an intrinsic relation between the “benefit” that a user perceives from the cloud and the usage pattern followed by other users. This gives rise to a non-cooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the “price of anarchy” of the game and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the gap can be arbitrarily large. We show that, somewhat counter-intuitively, exercising admission control to the cloud may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the cloud to a wide range of user types.",danny raz,Servers,2012.0,10.1109/INFCOM.2012.6195654,2012 Proceedings IEEE INFOCOM,Nahir2012,False,,IEEE,Not available,Workload factoring with the cloud: A game-theoretic perspective,fc7bc0b9549818f101c17163380585b3,https://ieeexplore.ieee.org/document/6195654/
3402,"Cloud computing is an emerging paradigm in which tasks are assigned to a combination (“cloud”) of servers and devices, accessed over a network. Typically, the cloud constitutes an additional means of computation and a user can perform workload factoring, i.e., split its load between the cloud and its other resources. Based on empirical data, we demonstrate that there is an intrinsic relation between the “benefit” that a user perceives from the cloud and the usage pattern followed by other users. This gives rise to a non-cooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the “price of anarchy” of the game and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the gap can be arbitrarily large. We show that, somewhat counter-intuitively, exercising admission control to the cloud may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the cloud to a wide range of user types.",danny raz,Outsourcing,2012.0,10.1109/INFCOM.2012.6195654,2012 Proceedings IEEE INFOCOM,Nahir2012,False,,IEEE,Not available,Workload factoring with the cloud: A game-theoretic perspective,fc7bc0b9549818f101c17163380585b3,https://ieeexplore.ieee.org/document/6195654/
3403,"This letter offers the first characterization of mixed Nash equilibria (MNE) for a wireless system with full-duplex (FD) capable terminals and slotted Aloha channel access. Focusing on a simple topology, we prove that MNE exist only if proportionality, driven by the accuracy of self-interference cancellation, is granted between the cost undergone for FD and half-duplex operations. The analysis shows how a proper selection of costs allows MNE that are also optimal from a network viewpoint in terms of aggregate throughput. The sensitivity of system performance to costs is tackled considering the price of anarchy.",andrea munari,Aloha,2018.0,10.1109/LWC.2017.2789284,IEEE Wireless Communications Letters,Munari2018,False,,IEEE,Not available,Mixed Nash Equilibria for In-Band Full-Duplex Networks,d1905ef61be9bbbdb0b4a987b918d171,https://ieeexplore.ieee.org/document/8245825/
3404,"This letter offers the first characterization of mixed Nash equilibria (MNE) for a wireless system with full-duplex (FD) capable terminals and slotted Aloha channel access. Focusing on a simple topology, we prove that MNE exist only if proportionality, driven by the accuracy of self-interference cancellation, is granted between the cost undergone for FD and half-duplex operations. The analysis shows how a proper selection of costs allows MNE that are also optimal from a network viewpoint in terms of aggregate throughput. The sensitivity of system performance to costs is tackled considering the price of anarchy.",andrea munari,full-duplex,2018.0,10.1109/LWC.2017.2789284,IEEE Wireless Communications Letters,Munari2018,False,,IEEE,Not available,Mixed Nash Equilibria for In-Band Full-Duplex Networks,d1905ef61be9bbbdb0b4a987b918d171,https://ieeexplore.ieee.org/document/8245825/
3405,"This letter offers the first characterization of mixed Nash equilibria (MNE) for a wireless system with full-duplex (FD) capable terminals and slotted Aloha channel access. Focusing on a simple topology, we prove that MNE exist only if proportionality, driven by the accuracy of self-interference cancellation, is granted between the cost undergone for FD and half-duplex operations. The analysis shows how a proper selection of costs allows MNE that are also optimal from a network viewpoint in terms of aggregate throughput. The sensitivity of system performance to costs is tackled considering the price of anarchy.",andrea munari,game theory,2018.0,10.1109/LWC.2017.2789284,IEEE Wireless Communications Letters,Munari2018,False,,IEEE,Not available,Mixed Nash Equilibria for In-Band Full-Duplex Networks,d1905ef61be9bbbdb0b4a987b918d171,https://ieeexplore.ieee.org/document/8245825/
3406,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
3407,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
3408,"This letter offers the first characterization of mixed Nash equilibria (MNE) for a wireless system with full-duplex (FD) capable terminals and slotted Aloha channel access. Focusing on a simple topology, we prove that MNE exist only if proportionality, driven by the accuracy of self-interference cancellation, is granted between the cost undergone for FD and half-duplex operations. The analysis shows how a proper selection of costs allows MNE that are also optimal from a network viewpoint in terms of aggregate throughput. The sensitivity of system performance to costs is tackled considering the price of anarchy.",vaggelis douros,Aloha,2018.0,10.1109/LWC.2017.2789284,IEEE Wireless Communications Letters,Munari2018,False,,IEEE,Not available,Mixed Nash Equilibria for In-Band Full-Duplex Networks,d1905ef61be9bbbdb0b4a987b918d171,https://ieeexplore.ieee.org/document/8245825/
3409,"This letter offers the first characterization of mixed Nash equilibria (MNE) for a wireless system with full-duplex (FD) capable terminals and slotted Aloha channel access. Focusing on a simple topology, we prove that MNE exist only if proportionality, driven by the accuracy of self-interference cancellation, is granted between the cost undergone for FD and half-duplex operations. The analysis shows how a proper selection of costs allows MNE that are also optimal from a network viewpoint in terms of aggregate throughput. The sensitivity of system performance to costs is tackled considering the price of anarchy.",vaggelis douros,full-duplex,2018.0,10.1109/LWC.2017.2789284,IEEE Wireless Communications Letters,Munari2018,False,,IEEE,Not available,Mixed Nash Equilibria for In-Band Full-Duplex Networks,d1905ef61be9bbbdb0b4a987b918d171,https://ieeexplore.ieee.org/document/8245825/
3410,"This letter offers the first characterization of mixed Nash equilibria (MNE) for a wireless system with full-duplex (FD) capable terminals and slotted Aloha channel access. Focusing on a simple topology, we prove that MNE exist only if proportionality, driven by the accuracy of self-interference cancellation, is granted between the cost undergone for FD and half-duplex operations. The analysis shows how a proper selection of costs allows MNE that are also optimal from a network viewpoint in terms of aggregate throughput. The sensitivity of system performance to costs is tackled considering the price of anarchy.",vaggelis douros,game theory,2018.0,10.1109/LWC.2017.2789284,IEEE Wireless Communications Letters,Munari2018,False,,IEEE,Not available,Mixed Nash Equilibria for In-Band Full-Duplex Networks,d1905ef61be9bbbdb0b4a987b918d171,https://ieeexplore.ieee.org/document/8245825/
3411,"This letter offers the first characterization of mixed Nash equilibria (MNE) for a wireless system with full-duplex (FD) capable terminals and slotted Aloha channel access. Focusing on a simple topology, we prove that MNE exist only if proportionality, driven by the accuracy of self-interference cancellation, is granted between the cost undergone for FD and half-duplex operations. The analysis shows how a proper selection of costs allows MNE that are also optimal from a network viewpoint in terms of aggregate throughput. The sensitivity of system performance to costs is tackled considering the price of anarchy.",petri mahonen,Aloha,2018.0,10.1109/LWC.2017.2789284,IEEE Wireless Communications Letters,Munari2018,False,,IEEE,Not available,Mixed Nash Equilibria for In-Band Full-Duplex Networks,d1905ef61be9bbbdb0b4a987b918d171,https://ieeexplore.ieee.org/document/8245825/
3412,"This letter offers the first characterization of mixed Nash equilibria (MNE) for a wireless system with full-duplex (FD) capable terminals and slotted Aloha channel access. Focusing on a simple topology, we prove that MNE exist only if proportionality, driven by the accuracy of self-interference cancellation, is granted between the cost undergone for FD and half-duplex operations. The analysis shows how a proper selection of costs allows MNE that are also optimal from a network viewpoint in terms of aggregate throughput. The sensitivity of system performance to costs is tackled considering the price of anarchy.",petri mahonen,full-duplex,2018.0,10.1109/LWC.2017.2789284,IEEE Wireless Communications Letters,Munari2018,False,,IEEE,Not available,Mixed Nash Equilibria for In-Band Full-Duplex Networks,d1905ef61be9bbbdb0b4a987b918d171,https://ieeexplore.ieee.org/document/8245825/
3413,"This letter offers the first characterization of mixed Nash equilibria (MNE) for a wireless system with full-duplex (FD) capable terminals and slotted Aloha channel access. Focusing on a simple topology, we prove that MNE exist only if proportionality, driven by the accuracy of self-interference cancellation, is granted between the cost undergone for FD and half-duplex operations. The analysis shows how a proper selection of costs allows MNE that are also optimal from a network viewpoint in terms of aggregate throughput. The sensitivity of system performance to costs is tackled considering the price of anarchy.",petri mahonen,game theory,2018.0,10.1109/LWC.2017.2789284,IEEE Wireless Communications Letters,Munari2018,False,,IEEE,Not available,Mixed Nash Equilibria for In-Band Full-Duplex Networks,d1905ef61be9bbbdb0b4a987b918d171,https://ieeexplore.ieee.org/document/8245825/
3414,"This article investigates the optimal transit fare structure and departure frequency under monopoly market regime. The proposed model treats the interaction between transit operators and government in the market as a Stackelberg game. In this game, the transit operator determines the fare structure and departure frequency so as to maximize its profit, whereas government could only promulgate regulation to influence the transit operator's decision, so as to maximize social welfare. First, under anarchy, the monopoly transit operator's optimal fare and departure frequency is determined. Then, under government regulation, it is found that, compared with profit maximization, the optimal fare for social welfare maximization is lower and the one for passengers' welfare maximization is lowest. The departure frequency has similar properties but goes to the opposite direction. In the end, the contract ranges of fare and departure frequency are given. With the use of the proposed model, a numerical example is given to assess the impact of government regulation on the optimal transit fare structure and departure frequency.",ding liu,monopoly,2009.0,10.1049/cp.2009.1606,5th Advanced Forum on Transportation of China (AFTC 2009),Liu2009,False,,IEEE,Not available,Optimal transit fare structure and departure frequency under monopoly market regime,0fddd9f7d2fc225a6d939a527eca3be8,
3415,"This article investigates the optimal transit fare structure and departure frequency under monopoly market regime. The proposed model treats the interaction between transit operators and government in the market as a Stackelberg game. In this game, the transit operator determines the fare structure and departure frequency so as to maximize its profit, whereas government could only promulgate regulation to influence the transit operator's decision, so as to maximize social welfare. First, under anarchy, the monopoly transit operator's optimal fare and departure frequency is determined. Then, under government regulation, it is found that, compared with profit maximization, the optimal fare for social welfare maximization is lower and the one for passengers' welfare maximization is lowest. The departure frequency has similar properties but goes to the opposite direction. In the end, the contract ranges of fare and departure frequency are given. With the use of the proposed model, a numerical example is given to assess the impact of government regulation on the optimal transit fare structure and departure frequency.",ding liu,fare structure and departure frequency,2009.0,10.1049/cp.2009.1606,5th Advanced Forum on Transportation of China (AFTC 2009),Liu2009,False,,IEEE,Not available,Optimal transit fare structure and departure frequency under monopoly market regime,0fddd9f7d2fc225a6d939a527eca3be8,
3416,"This article investigates the optimal transit fare structure and departure frequency under monopoly market regime. The proposed model treats the interaction between transit operators and government in the market as a Stackelberg game. In this game, the transit operator determines the fare structure and departure frequency so as to maximize its profit, whereas government could only promulgate regulation to influence the transit operator's decision, so as to maximize social welfare. First, under anarchy, the monopoly transit operator's optimal fare and departure frequency is determined. Then, under government regulation, it is found that, compared with profit maximization, the optimal fare for social welfare maximization is lower and the one for passengers' welfare maximization is lowest. The departure frequency has similar properties but goes to the opposite direction. In the end, the contract ranges of fare and departure frequency are given. With the use of the proposed model, a numerical example is given to assess the impact of government regulation on the optimal transit fare structure and departure frequency.",ding liu,government regulation,2009.0,10.1049/cp.2009.1606,5th Advanced Forum on Transportation of China (AFTC 2009),Liu2009,False,,IEEE,Not available,Optimal transit fare structure and departure frequency under monopoly market regime,0fddd9f7d2fc225a6d939a527eca3be8,
3417,"This article investigates the optimal transit fare structure and departure frequency under monopoly market regime. The proposed model treats the interaction between transit operators and government in the market as a Stackelberg game. In this game, the transit operator determines the fare structure and departure frequency so as to maximize its profit, whereas government could only promulgate regulation to influence the transit operator's decision, so as to maximize social welfare. First, under anarchy, the monopoly transit operator's optimal fare and departure frequency is determined. Then, under government regulation, it is found that, compared with profit maximization, the optimal fare for social welfare maximization is lower and the one for passengers' welfare maximization is lowest. The departure frequency has similar properties but goes to the opposite direction. In the end, the contract ranges of fare and departure frequency are given. With the use of the proposed model, a numerical example is given to assess the impact of government regulation on the optimal transit fare structure and departure frequency.",ding liu,society welfare,2009.0,10.1049/cp.2009.1606,5th Advanced Forum on Transportation of China (AFTC 2009),Liu2009,False,,IEEE,Not available,Optimal transit fare structure and departure frequency under monopoly market regime,0fddd9f7d2fc225a6d939a527eca3be8,
3418,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
3419,"This article investigates the optimal transit fare structure and departure frequency under monopoly market regime. The proposed model treats the interaction between transit operators and government in the market as a Stackelberg game. In this game, the transit operator determines the fare structure and departure frequency so as to maximize its profit, whereas government could only promulgate regulation to influence the transit operator's decision, so as to maximize social welfare. First, under anarchy, the monopoly transit operator's optimal fare and departure frequency is determined. Then, under government regulation, it is found that, compared with profit maximization, the optimal fare for social welfare maximization is lower and the one for passengers' welfare maximization is lowest. The departure frequency has similar properties but goes to the opposite direction. In the end, the contract ranges of fare and departure frequency are given. With the use of the proposed model, a numerical example is given to assess the impact of government regulation on the optimal transit fare structure and departure frequency.",ding liu,contract range,2009.0,10.1049/cp.2009.1606,5th Advanced Forum on Transportation of China (AFTC 2009),Liu2009,False,,IEEE,Not available,Optimal transit fare structure and departure frequency under monopoly market regime,0fddd9f7d2fc225a6d939a527eca3be8,
3420,"This article investigates the optimal transit fare structure and departure frequency under monopoly market regime. The proposed model treats the interaction between transit operators and government in the market as a Stackelberg game. In this game, the transit operator determines the fare structure and departure frequency so as to maximize its profit, whereas government could only promulgate regulation to influence the transit operator's decision, so as to maximize social welfare. First, under anarchy, the monopoly transit operator's optimal fare and departure frequency is determined. Then, under government regulation, it is found that, compared with profit maximization, the optimal fare for social welfare maximization is lower and the one for passengers' welfare maximization is lowest. The departure frequency has similar properties but goes to the opposite direction. In the end, the contract ranges of fare and departure frequency are given. With the use of the proposed model, a numerical example is given to assess the impact of government regulation on the optimal transit fare structure and departure frequency.",qiong tian,monopoly,2009.0,10.1049/cp.2009.1606,5th Advanced Forum on Transportation of China (AFTC 2009),Liu2009,False,,IEEE,Not available,Optimal transit fare structure and departure frequency under monopoly market regime,0fddd9f7d2fc225a6d939a527eca3be8,
3421,"This article investigates the optimal transit fare structure and departure frequency under monopoly market regime. The proposed model treats the interaction between transit operators and government in the market as a Stackelberg game. In this game, the transit operator determines the fare structure and departure frequency so as to maximize its profit, whereas government could only promulgate regulation to influence the transit operator's decision, so as to maximize social welfare. First, under anarchy, the monopoly transit operator's optimal fare and departure frequency is determined. Then, under government regulation, it is found that, compared with profit maximization, the optimal fare for social welfare maximization is lower and the one for passengers' welfare maximization is lowest. The departure frequency has similar properties but goes to the opposite direction. In the end, the contract ranges of fare and departure frequency are given. With the use of the proposed model, a numerical example is given to assess the impact of government regulation on the optimal transit fare structure and departure frequency.",qiong tian,fare structure and departure frequency,2009.0,10.1049/cp.2009.1606,5th Advanced Forum on Transportation of China (AFTC 2009),Liu2009,False,,IEEE,Not available,Optimal transit fare structure and departure frequency under monopoly market regime,0fddd9f7d2fc225a6d939a527eca3be8,
3422,"This article investigates the optimal transit fare structure and departure frequency under monopoly market regime. The proposed model treats the interaction between transit operators and government in the market as a Stackelberg game. In this game, the transit operator determines the fare structure and departure frequency so as to maximize its profit, whereas government could only promulgate regulation to influence the transit operator's decision, so as to maximize social welfare. First, under anarchy, the monopoly transit operator's optimal fare and departure frequency is determined. Then, under government regulation, it is found that, compared with profit maximization, the optimal fare for social welfare maximization is lower and the one for passengers' welfare maximization is lowest. The departure frequency has similar properties but goes to the opposite direction. In the end, the contract ranges of fare and departure frequency are given. With the use of the proposed model, a numerical example is given to assess the impact of government regulation on the optimal transit fare structure and departure frequency.",qiong tian,government regulation,2009.0,10.1049/cp.2009.1606,5th Advanced Forum on Transportation of China (AFTC 2009),Liu2009,False,,IEEE,Not available,Optimal transit fare structure and departure frequency under monopoly market regime,0fddd9f7d2fc225a6d939a527eca3be8,
3423,"This article investigates the optimal transit fare structure and departure frequency under monopoly market regime. The proposed model treats the interaction between transit operators and government in the market as a Stackelberg game. In this game, the transit operator determines the fare structure and departure frequency so as to maximize its profit, whereas government could only promulgate regulation to influence the transit operator's decision, so as to maximize social welfare. First, under anarchy, the monopoly transit operator's optimal fare and departure frequency is determined. Then, under government regulation, it is found that, compared with profit maximization, the optimal fare for social welfare maximization is lower and the one for passengers' welfare maximization is lowest. The departure frequency has similar properties but goes to the opposite direction. In the end, the contract ranges of fare and departure frequency are given. With the use of the proposed model, a numerical example is given to assess the impact of government regulation on the optimal transit fare structure and departure frequency.",qiong tian,society welfare,2009.0,10.1049/cp.2009.1606,5th Advanced Forum on Transportation of China (AFTC 2009),Liu2009,False,,IEEE,Not available,Optimal transit fare structure and departure frequency under monopoly market regime,0fddd9f7d2fc225a6d939a527eca3be8,
3424,"This article investigates the optimal transit fare structure and departure frequency under monopoly market regime. The proposed model treats the interaction between transit operators and government in the market as a Stackelberg game. In this game, the transit operator determines the fare structure and departure frequency so as to maximize its profit, whereas government could only promulgate regulation to influence the transit operator's decision, so as to maximize social welfare. First, under anarchy, the monopoly transit operator's optimal fare and departure frequency is determined. Then, under government regulation, it is found that, compared with profit maximization, the optimal fare for social welfare maximization is lower and the one for passengers' welfare maximization is lowest. The departure frequency has similar properties but goes to the opposite direction. In the end, the contract ranges of fare and departure frequency are given. With the use of the proposed model, a numerical example is given to assess the impact of government regulation on the optimal transit fare structure and departure frequency.",qiong tian,contract range,2009.0,10.1049/cp.2009.1606,5th Advanced Forum on Transportation of China (AFTC 2009),Liu2009,False,,IEEE,Not available,Optimal transit fare structure and departure frequency under monopoly market regime,0fddd9f7d2fc225a6d939a527eca3be8,
3425,"This article investigates the optimal transit fare structure and departure frequency under monopoly market regime. The proposed model treats the interaction between transit operators and government in the market as a Stackelberg game. In this game, the transit operator determines the fare structure and departure frequency so as to maximize its profit, whereas government could only promulgate regulation to influence the transit operator's decision, so as to maximize social welfare. First, under anarchy, the monopoly transit operator's optimal fare and departure frequency is determined. Then, under government regulation, it is found that, compared with profit maximization, the optimal fare for social welfare maximization is lower and the one for passengers' welfare maximization is lowest. The departure frequency has similar properties but goes to the opposite direction. In the end, the contract ranges of fare and departure frequency are given. With the use of the proposed model, a numerical example is given to assess the impact of government regulation on the optimal transit fare structure and departure frequency.",jianxun ding,monopoly,2009.0,10.1049/cp.2009.1606,5th Advanced Forum on Transportation of China (AFTC 2009),Liu2009,False,,IEEE,Not available,Optimal transit fare structure and departure frequency under monopoly market regime,0fddd9f7d2fc225a6d939a527eca3be8,
3426,"This article investigates the optimal transit fare structure and departure frequency under monopoly market regime. The proposed model treats the interaction between transit operators and government in the market as a Stackelberg game. In this game, the transit operator determines the fare structure and departure frequency so as to maximize its profit, whereas government could only promulgate regulation to influence the transit operator's decision, so as to maximize social welfare. First, under anarchy, the monopoly transit operator's optimal fare and departure frequency is determined. Then, under government regulation, it is found that, compared with profit maximization, the optimal fare for social welfare maximization is lower and the one for passengers' welfare maximization is lowest. The departure frequency has similar properties but goes to the opposite direction. In the end, the contract ranges of fare and departure frequency are given. With the use of the proposed model, a numerical example is given to assess the impact of government regulation on the optimal transit fare structure and departure frequency.",jianxun ding,fare structure and departure frequency,2009.0,10.1049/cp.2009.1606,5th Advanced Forum on Transportation of China (AFTC 2009),Liu2009,False,,IEEE,Not available,Optimal transit fare structure and departure frequency under monopoly market regime,0fddd9f7d2fc225a6d939a527eca3be8,
3427,"This article investigates the optimal transit fare structure and departure frequency under monopoly market regime. The proposed model treats the interaction between transit operators and government in the market as a Stackelberg game. In this game, the transit operator determines the fare structure and departure frequency so as to maximize its profit, whereas government could only promulgate regulation to influence the transit operator's decision, so as to maximize social welfare. First, under anarchy, the monopoly transit operator's optimal fare and departure frequency is determined. Then, under government regulation, it is found that, compared with profit maximization, the optimal fare for social welfare maximization is lower and the one for passengers' welfare maximization is lowest. The departure frequency has similar properties but goes to the opposite direction. In the end, the contract ranges of fare and departure frequency are given. With the use of the proposed model, a numerical example is given to assess the impact of government regulation on the optimal transit fare structure and departure frequency.",jianxun ding,government regulation,2009.0,10.1049/cp.2009.1606,5th Advanced Forum on Transportation of China (AFTC 2009),Liu2009,False,,IEEE,Not available,Optimal transit fare structure and departure frequency under monopoly market regime,0fddd9f7d2fc225a6d939a527eca3be8,
3428,"This article investigates the optimal transit fare structure and departure frequency under monopoly market regime. The proposed model treats the interaction between transit operators and government in the market as a Stackelberg game. In this game, the transit operator determines the fare structure and departure frequency so as to maximize its profit, whereas government could only promulgate regulation to influence the transit operator's decision, so as to maximize social welfare. First, under anarchy, the monopoly transit operator's optimal fare and departure frequency is determined. Then, under government regulation, it is found that, compared with profit maximization, the optimal fare for social welfare maximization is lower and the one for passengers' welfare maximization is lowest. The departure frequency has similar properties but goes to the opposite direction. In the end, the contract ranges of fare and departure frequency are given. With the use of the proposed model, a numerical example is given to assess the impact of government regulation on the optimal transit fare structure and departure frequency.",jianxun ding,society welfare,2009.0,10.1049/cp.2009.1606,5th Advanced Forum on Transportation of China (AFTC 2009),Liu2009,False,,IEEE,Not available,Optimal transit fare structure and departure frequency under monopoly market regime,0fddd9f7d2fc225a6d939a527eca3be8,
3429,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
3430,"This article investigates the optimal transit fare structure and departure frequency under monopoly market regime. The proposed model treats the interaction between transit operators and government in the market as a Stackelberg game. In this game, the transit operator determines the fare structure and departure frequency so as to maximize its profit, whereas government could only promulgate regulation to influence the transit operator's decision, so as to maximize social welfare. First, under anarchy, the monopoly transit operator's optimal fare and departure frequency is determined. Then, under government regulation, it is found that, compared with profit maximization, the optimal fare for social welfare maximization is lower and the one for passengers' welfare maximization is lowest. The departure frequency has similar properties but goes to the opposite direction. In the end, the contract ranges of fare and departure frequency are given. With the use of the proposed model, a numerical example is given to assess the impact of government regulation on the optimal transit fare structure and departure frequency.",jianxun ding,contract range,2009.0,10.1049/cp.2009.1606,5th Advanced Forum on Transportation of China (AFTC 2009),Liu2009,False,,IEEE,Not available,Optimal transit fare structure and departure frequency under monopoly market regime,0fddd9f7d2fc225a6d939a527eca3be8,
3431,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",sidi ezzahidi,Relays,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
3432,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",sidi ezzahidi,Games,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
3433,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",sidi ezzahidi,Nash equilibrium,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
3434,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",sidi ezzahidi,Approximation algorithms,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
3435,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",sidi ezzahidi,Delays,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
3436,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",sidi ezzahidi,Routing,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
3437,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",sidi ezzahidi,Algebra,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
3438,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",essaid sabir,Relays,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
3439,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",essaid sabir,Games,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
3440,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
3441,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",essaid sabir,Nash equilibrium,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
3442,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",essaid sabir,Approximation algorithms,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
3443,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",essaid sabir,Delays,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
3444,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",essaid sabir,Routing,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
3445,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",essaid sabir,Algebra,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
3446,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",el-houssine bouyakhf,Relays,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
3447,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",el-houssine bouyakhf,Games,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
3448,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",el-houssine bouyakhf,Nash equilibrium,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
3449,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",el-houssine bouyakhf,Approximation algorithms,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
3450,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",el-houssine bouyakhf,Delays,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
3451,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
3452,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",el-houssine bouyakhf,Routing,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
3453,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",el-houssine bouyakhf,Algebra,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
3454,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",youwen yi,Macrocell networks,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
3455,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",youwen yi,Throughput,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
3456,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",youwen yi,Games,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
3457,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",youwen yi,Noise measurement,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
3458,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",youwen yi,Radio frequency,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
3459,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",youwen yi,Wireless communication,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
3460,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",youwen yi,Ultrafast electronics,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
3461,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",jin zhang,Macrocell networks,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
3462,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
3463,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",jin zhang,Throughput,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
3464,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",jin zhang,Games,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
3465,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",jin zhang,Noise measurement,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
3466,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",jin zhang,Radio frequency,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
3467,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",jin zhang,Wireless communication,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
3468,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",jin zhang,Ultrafast electronics,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
3469,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",qian zhang,Macrocell networks,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
3470,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",qian zhang,Throughput,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
3471,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",qian zhang,Games,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
3472,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",qian zhang,Noise measurement,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
3473,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
3474,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",qian zhang,Radio frequency,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
3475,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",qian zhang,Wireless communication,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
3476,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",qian zhang,Ultrafast electronics,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
3477,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",tao jiang,Macrocell networks,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
3478,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",tao jiang,Throughput,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
3479,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",tao jiang,Games,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
3480,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",tao jiang,Noise measurement,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
3481,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",tao jiang,Radio frequency,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
3482,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",tao jiang,Wireless communication,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
3483,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",tao jiang,Ultrafast electronics,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
3484,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
3485,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",sangwoo moon,Games,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
3486,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",sangwoo moon,Sociology,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
3487,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",sangwoo moon,Statistics,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
3488,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",sangwoo moon,Heuristic algorithms,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
3489,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",sangwoo moon,Optimization,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
3490,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",sangwoo moon,Mobile communication,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
3491,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",sangwoo moon,Delays,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
3492,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",yung yi,Games,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
3493,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",yung yi,Sociology,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
3494,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",yung yi,Statistics,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
3495,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
3496,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",yung yi,Heuristic algorithms,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
3497,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",yung yi,Optimization,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
3498,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",yung yi,Mobile communication,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
3499,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",yung yi,Delays,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
3500,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",hongseok kim,Games,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
3501,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",hongseok kim,Sociology,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
3502,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",hongseok kim,Statistics,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
3503,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",hongseok kim,Heuristic algorithms,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
3504,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",hongseok kim,Optimization,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
3505,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",hongseok kim,Mobile communication,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
3506,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
3507,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",hongseok kim,Delays,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
3508,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",sangwoo moon,User association,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
3509,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",sangwoo moon,population game,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
3510,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",sangwoo moon,evolutionary dynamics,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
3511,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",sangwoo moon,load balancing,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
3512,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",sangwoo moon,cellular networks,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
3513,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",sangwoo moon,User association,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
3514,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",sangwoo moon,population game,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
3515,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",sangwoo moon,evolutionary dynamics,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
3516,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",sangwoo moon,load balancing,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
3517,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
3518,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
3519,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",sangwoo moon,cellular networks,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
3520,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",hongseok kim,User association,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
3521,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",hongseok kim,population game,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
3522,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",hongseok kim,evolutionary dynamics,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
3523,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",hongseok kim,load balancing,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
3524,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",hongseok kim,cellular networks,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
3525,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",hongseok kim,User association,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
3526,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",hongseok kim,population game,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
3527,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",hongseok kim,evolutionary dynamics,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
3528,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",hongseok kim,load balancing,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
3529,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
3530,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",hongseok kim,cellular networks,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
3531,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",yung yi,User association,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
3532,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",yung yi,population game,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
3533,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",yung yi,evolutionary dynamics,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
3534,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",yung yi,load balancing,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
3535,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",yung yi,cellular networks,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
3536,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",yung yi,User association,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
3537,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",yung yi,population game,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
3538,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",yung yi,evolutionary dynamics,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
3539,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",yung yi,load balancing,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
3540,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
3541,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",yung yi,cellular networks,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
3542,"This paper investigates the subcarrier allocation problem for a downlink multi-cell multiuser OFDMA network using potential game theory. Each player is considered to be a central base station together with all the mobiles distributed within its coverage area. In such a system, co-channel interferences (CCI), if left uncontrolled, could hinder the transmissions and limit the throughputs of the users, especially those near the cell-edge area. Certain remedies, including power control with pricing, did not seem to solve the problem completely. We specifically address this issue from an interference-minimizing approach, where the utility function adopted is meant to minimize the total CCI among players. Under such formulation, we show that the formulated game can be mathematically described by a potential game. Hence, a Nash equilibrium (NE) will be guaranteed for the proposed game and stable solutions can be achieved via myopic gameplays such as the best/better responses. We propose our iterative algorithm for obtaining the NEs and address several performance issues such as fairness for edge-users and the price of anarchy. Numerical results show the improvement in efficiency and fairness using this approach.",quang la,Downlink multi-cell OFDMA,2012.0,10.1109/TWC.2012.072512.112046,IEEE Transactions on Wireless Communications,La2012,False,,IEEE,Not available,Performance Analysis of Downlink Multi-Cell OFDMA Systems Based on Potential Game,f3fca19762ba02d434ee0cf5edc89e03,https://ieeexplore.ieee.org/document/6251826/
3543,"This paper investigates the subcarrier allocation problem for a downlink multi-cell multiuser OFDMA network using potential game theory. Each player is considered to be a central base station together with all the mobiles distributed within its coverage area. In such a system, co-channel interferences (CCI), if left uncontrolled, could hinder the transmissions and limit the throughputs of the users, especially those near the cell-edge area. Certain remedies, including power control with pricing, did not seem to solve the problem completely. We specifically address this issue from an interference-minimizing approach, where the utility function adopted is meant to minimize the total CCI among players. Under such formulation, we show that the formulated game can be mathematically described by a potential game. Hence, a Nash equilibrium (NE) will be guaranteed for the proposed game and stable solutions can be achieved via myopic gameplays such as the best/better responses. We propose our iterative algorithm for obtaining the NEs and address several performance issues such as fairness for edge-users and the price of anarchy. Numerical results show the improvement in efficiency and fairness using this approach.",quang la,potential game,2012.0,10.1109/TWC.2012.072512.112046,IEEE Transactions on Wireless Communications,La2012,False,,IEEE,Not available,Performance Analysis of Downlink Multi-Cell OFDMA Systems Based on Potential Game,f3fca19762ba02d434ee0cf5edc89e03,https://ieeexplore.ieee.org/document/6251826/
3544,"This paper investigates the subcarrier allocation problem for a downlink multi-cell multiuser OFDMA network using potential game theory. Each player is considered to be a central base station together with all the mobiles distributed within its coverage area. In such a system, co-channel interferences (CCI), if left uncontrolled, could hinder the transmissions and limit the throughputs of the users, especially those near the cell-edge area. Certain remedies, including power control with pricing, did not seem to solve the problem completely. We specifically address this issue from an interference-minimizing approach, where the utility function adopted is meant to minimize the total CCI among players. Under such formulation, we show that the formulated game can be mathematically described by a potential game. Hence, a Nash equilibrium (NE) will be guaranteed for the proposed game and stable solutions can be achieved via myopic gameplays such as the best/better responses. We propose our iterative algorithm for obtaining the NEs and address several performance issues such as fairness for edge-users and the price of anarchy. Numerical results show the improvement in efficiency and fairness using this approach.",quang la,interference minimization,2012.0,10.1109/TWC.2012.072512.112046,IEEE Transactions on Wireless Communications,La2012,False,,IEEE,Not available,Performance Analysis of Downlink Multi-Cell OFDMA Systems Based on Potential Game,f3fca19762ba02d434ee0cf5edc89e03,https://ieeexplore.ieee.org/document/6251826/
3545,"This paper investigates the subcarrier allocation problem for a downlink multi-cell multiuser OFDMA network using potential game theory. Each player is considered to be a central base station together with all the mobiles distributed within its coverage area. In such a system, co-channel interferences (CCI), if left uncontrolled, could hinder the transmissions and limit the throughputs of the users, especially those near the cell-edge area. Certain remedies, including power control with pricing, did not seem to solve the problem completely. We specifically address this issue from an interference-minimizing approach, where the utility function adopted is meant to minimize the total CCI among players. Under such formulation, we show that the formulated game can be mathematically described by a potential game. Hence, a Nash equilibrium (NE) will be guaranteed for the proposed game and stable solutions can be achieved via myopic gameplays such as the best/better responses. We propose our iterative algorithm for obtaining the NEs and address several performance issues such as fairness for edge-users and the price of anarchy. Numerical results show the improvement in efficiency and fairness using this approach.",quang la,Nash equilibrium,2012.0,10.1109/TWC.2012.072512.112046,IEEE Transactions on Wireless Communications,La2012,False,,IEEE,Not available,Performance Analysis of Downlink Multi-Cell OFDMA Systems Based on Potential Game,f3fca19762ba02d434ee0cf5edc89e03,https://ieeexplore.ieee.org/document/6251826/
3546,"This paper investigates the subcarrier allocation problem for a downlink multi-cell multiuser OFDMA network using potential game theory. Each player is considered to be a central base station together with all the mobiles distributed within its coverage area. In such a system, co-channel interferences (CCI), if left uncontrolled, could hinder the transmissions and limit the throughputs of the users, especially those near the cell-edge area. Certain remedies, including power control with pricing, did not seem to solve the problem completely. We specifically address this issue from an interference-minimizing approach, where the utility function adopted is meant to minimize the total CCI among players. Under such formulation, we show that the formulated game can be mathematically described by a potential game. Hence, a Nash equilibrium (NE) will be guaranteed for the proposed game and stable solutions can be achieved via myopic gameplays such as the best/better responses. We propose our iterative algorithm for obtaining the NEs and address several performance issues such as fairness for edge-users and the price of anarchy. Numerical results show the improvement in efficiency and fairness using this approach.",yong chew,Downlink multi-cell OFDMA,2012.0,10.1109/TWC.2012.072512.112046,IEEE Transactions on Wireless Communications,La2012,False,,IEEE,Not available,Performance Analysis of Downlink Multi-Cell OFDMA Systems Based on Potential Game,f3fca19762ba02d434ee0cf5edc89e03,https://ieeexplore.ieee.org/document/6251826/
3547,"This paper investigates the subcarrier allocation problem for a downlink multi-cell multiuser OFDMA network using potential game theory. Each player is considered to be a central base station together with all the mobiles distributed within its coverage area. In such a system, co-channel interferences (CCI), if left uncontrolled, could hinder the transmissions and limit the throughputs of the users, especially those near the cell-edge area. Certain remedies, including power control with pricing, did not seem to solve the problem completely. We specifically address this issue from an interference-minimizing approach, where the utility function adopted is meant to minimize the total CCI among players. Under such formulation, we show that the formulated game can be mathematically described by a potential game. Hence, a Nash equilibrium (NE) will be guaranteed for the proposed game and stable solutions can be achieved via myopic gameplays such as the best/better responses. We propose our iterative algorithm for obtaining the NEs and address several performance issues such as fairness for edge-users and the price of anarchy. Numerical results show the improvement in efficiency and fairness using this approach.",yong chew,potential game,2012.0,10.1109/TWC.2012.072512.112046,IEEE Transactions on Wireless Communications,La2012,False,,IEEE,Not available,Performance Analysis of Downlink Multi-Cell OFDMA Systems Based on Potential Game,f3fca19762ba02d434ee0cf5edc89e03,https://ieeexplore.ieee.org/document/6251826/
3548,"This paper investigates the subcarrier allocation problem for a downlink multi-cell multiuser OFDMA network using potential game theory. Each player is considered to be a central base station together with all the mobiles distributed within its coverage area. In such a system, co-channel interferences (CCI), if left uncontrolled, could hinder the transmissions and limit the throughputs of the users, especially those near the cell-edge area. Certain remedies, including power control with pricing, did not seem to solve the problem completely. We specifically address this issue from an interference-minimizing approach, where the utility function adopted is meant to minimize the total CCI among players. Under such formulation, we show that the formulated game can be mathematically described by a potential game. Hence, a Nash equilibrium (NE) will be guaranteed for the proposed game and stable solutions can be achieved via myopic gameplays such as the best/better responses. We propose our iterative algorithm for obtaining the NEs and address several performance issues such as fairness for edge-users and the price of anarchy. Numerical results show the improvement in efficiency and fairness using this approach.",yong chew,interference minimization,2012.0,10.1109/TWC.2012.072512.112046,IEEE Transactions on Wireless Communications,La2012,False,,IEEE,Not available,Performance Analysis of Downlink Multi-Cell OFDMA Systems Based on Potential Game,f3fca19762ba02d434ee0cf5edc89e03,https://ieeexplore.ieee.org/document/6251826/
3549,"This paper investigates the subcarrier allocation problem for a downlink multi-cell multiuser OFDMA network using potential game theory. Each player is considered to be a central base station together with all the mobiles distributed within its coverage area. In such a system, co-channel interferences (CCI), if left uncontrolled, could hinder the transmissions and limit the throughputs of the users, especially those near the cell-edge area. Certain remedies, including power control with pricing, did not seem to solve the problem completely. We specifically address this issue from an interference-minimizing approach, where the utility function adopted is meant to minimize the total CCI among players. Under such formulation, we show that the formulated game can be mathematically described by a potential game. Hence, a Nash equilibrium (NE) will be guaranteed for the proposed game and stable solutions can be achieved via myopic gameplays such as the best/better responses. We propose our iterative algorithm for obtaining the NEs and address several performance issues such as fairness for edge-users and the price of anarchy. Numerical results show the improvement in efficiency and fairness using this approach.",yong chew,Nash equilibrium,2012.0,10.1109/TWC.2012.072512.112046,IEEE Transactions on Wireless Communications,La2012,False,,IEEE,Not available,Performance Analysis of Downlink Multi-Cell OFDMA Systems Based on Potential Game,f3fca19762ba02d434ee0cf5edc89e03,https://ieeexplore.ieee.org/document/6251826/
3550,"This paper investigates the subcarrier allocation problem for a downlink multi-cell multiuser OFDMA network using potential game theory. Each player is considered to be a central base station together with all the mobiles distributed within its coverage area. In such a system, co-channel interferences (CCI), if left uncontrolled, could hinder the transmissions and limit the throughputs of the users, especially those near the cell-edge area. Certain remedies, including power control with pricing, did not seem to solve the problem completely. We specifically address this issue from an interference-minimizing approach, where the utility function adopted is meant to minimize the total CCI among players. Under such formulation, we show that the formulated game can be mathematically described by a potential game. Hence, a Nash equilibrium (NE) will be guaranteed for the proposed game and stable solutions can be achieved via myopic gameplays such as the best/better responses. We propose our iterative algorithm for obtaining the NEs and address several performance issues such as fairness for edge-users and the price of anarchy. Numerical results show the improvement in efficiency and fairness using this approach.",boon soong,Downlink multi-cell OFDMA,2012.0,10.1109/TWC.2012.072512.112046,IEEE Transactions on Wireless Communications,La2012,False,,IEEE,Not available,Performance Analysis of Downlink Multi-Cell OFDMA Systems Based on Potential Game,f3fca19762ba02d434ee0cf5edc89e03,https://ieeexplore.ieee.org/document/6251826/
3551,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
3552,"This paper investigates the subcarrier allocation problem for a downlink multi-cell multiuser OFDMA network using potential game theory. Each player is considered to be a central base station together with all the mobiles distributed within its coverage area. In such a system, co-channel interferences (CCI), if left uncontrolled, could hinder the transmissions and limit the throughputs of the users, especially those near the cell-edge area. Certain remedies, including power control with pricing, did not seem to solve the problem completely. We specifically address this issue from an interference-minimizing approach, where the utility function adopted is meant to minimize the total CCI among players. Under such formulation, we show that the formulated game can be mathematically described by a potential game. Hence, a Nash equilibrium (NE) will be guaranteed for the proposed game and stable solutions can be achieved via myopic gameplays such as the best/better responses. We propose our iterative algorithm for obtaining the NEs and address several performance issues such as fairness for edge-users and the price of anarchy. Numerical results show the improvement in efficiency and fairness using this approach.",boon soong,potential game,2012.0,10.1109/TWC.2012.072512.112046,IEEE Transactions on Wireless Communications,La2012,False,,IEEE,Not available,Performance Analysis of Downlink Multi-Cell OFDMA Systems Based on Potential Game,f3fca19762ba02d434ee0cf5edc89e03,https://ieeexplore.ieee.org/document/6251826/
3553,"This paper investigates the subcarrier allocation problem for a downlink multi-cell multiuser OFDMA network using potential game theory. Each player is considered to be a central base station together with all the mobiles distributed within its coverage area. In such a system, co-channel interferences (CCI), if left uncontrolled, could hinder the transmissions and limit the throughputs of the users, especially those near the cell-edge area. Certain remedies, including power control with pricing, did not seem to solve the problem completely. We specifically address this issue from an interference-minimizing approach, where the utility function adopted is meant to minimize the total CCI among players. Under such formulation, we show that the formulated game can be mathematically described by a potential game. Hence, a Nash equilibrium (NE) will be guaranteed for the proposed game and stable solutions can be achieved via myopic gameplays such as the best/better responses. We propose our iterative algorithm for obtaining the NEs and address several performance issues such as fairness for edge-users and the price of anarchy. Numerical results show the improvement in efficiency and fairness using this approach.",boon soong,interference minimization,2012.0,10.1109/TWC.2012.072512.112046,IEEE Transactions on Wireless Communications,La2012,False,,IEEE,Not available,Performance Analysis of Downlink Multi-Cell OFDMA Systems Based on Potential Game,f3fca19762ba02d434ee0cf5edc89e03,https://ieeexplore.ieee.org/document/6251826/
3554,"This paper investigates the subcarrier allocation problem for a downlink multi-cell multiuser OFDMA network using potential game theory. Each player is considered to be a central base station together with all the mobiles distributed within its coverage area. In such a system, co-channel interferences (CCI), if left uncontrolled, could hinder the transmissions and limit the throughputs of the users, especially those near the cell-edge area. Certain remedies, including power control with pricing, did not seem to solve the problem completely. We specifically address this issue from an interference-minimizing approach, where the utility function adopted is meant to minimize the total CCI among players. Under such formulation, we show that the formulated game can be mathematically described by a potential game. Hence, a Nash equilibrium (NE) will be guaranteed for the proposed game and stable solutions can be achieved via myopic gameplays such as the best/better responses. We propose our iterative algorithm for obtaining the NEs and address several performance issues such as fairness for edge-users and the price of anarchy. Numerical results show the improvement in efficiency and fairness using this approach.",boon soong,Nash equilibrium,2012.0,10.1109/TWC.2012.072512.112046,IEEE Transactions on Wireless Communications,La2012,False,,IEEE,Not available,Performance Analysis of Downlink Multi-Cell OFDMA Systems Based on Potential Game,f3fca19762ba02d434ee0cf5edc89e03,https://ieeexplore.ieee.org/document/6251826/
3555,"Recent results have shown that selfish users do not have an incentive to participate in intersession network coding in a static noncooperative game setting. Because of this, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 20%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be improved to 36%. We design a grim-trigger strategy that encourages users to cooperate and participate in the intersession network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We resolve the conflict of interest among the users through a bargaining process and obtain tight upper bounds for the price-of-anarchy that are valid for any possible bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve these upper bounds, as confirmed through simulation studies. The coexistence of multiple selfish network coding sessions as well as the coexistence of selfish network coding and routing sessions are also investigated. Our results represent a first step toward designing practical intersession network coding schemes that achieve reasonable performance for selfish users.",hamed mohsenian-rad,Min-max bargaining solution,2014.0,10.1109/TNET.2013.2271038,IEEE/ACM Transactions on Networking,Mohsenian-Rad2014,False,,IEEE,Not available,Repeated Intersession Network Coding Games: Efficiency and Min-Max Bargaining Solution,0769f49a69f3d7e0c6d89d0918096dfd,https://ieeexplore.ieee.org/document/6565417/
3556,"Recent results have shown that selfish users do not have an incentive to participate in intersession network coding in a static noncooperative game setting. Because of this, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 20%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be improved to 36%. We design a grim-trigger strategy that encourages users to cooperate and participate in the intersession network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We resolve the conflict of interest among the users through a bargaining process and obtain tight upper bounds for the price-of-anarchy that are valid for any possible bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve these upper bounds, as confirmed through simulation studies. The coexistence of multiple selfish network coding sessions as well as the coexistence of selfish network coding and routing sessions are also investigated. Our results represent a first step toward designing practical intersession network coding schemes that achieve reasonable performance for selfish users.",hamed mohsenian-rad,network coding,2014.0,10.1109/TNET.2013.2271038,IEEE/ACM Transactions on Networking,Mohsenian-Rad2014,False,,IEEE,Not available,Repeated Intersession Network Coding Games: Efficiency and Min-Max Bargaining Solution,0769f49a69f3d7e0c6d89d0918096dfd,https://ieeexplore.ieee.org/document/6565417/
3557,"Recent results have shown that selfish users do not have an incentive to participate in intersession network coding in a static noncooperative game setting. Because of this, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 20%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be improved to 36%. We design a grim-trigger strategy that encourages users to cooperate and participate in the intersession network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We resolve the conflict of interest among the users through a bargaining process and obtain tight upper bounds for the price-of-anarchy that are valid for any possible bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve these upper bounds, as confirmed through simulation studies. The coexistence of multiple selfish network coding sessions as well as the coexistence of selfish network coding and routing sessions are also investigated. Our results represent a first step toward designing practical intersession network coding schemes that achieve reasonable performance for selfish users.",hamed mohsenian-rad,repeated game theory,2014.0,10.1109/TNET.2013.2271038,IEEE/ACM Transactions on Networking,Mohsenian-Rad2014,False,,IEEE,Not available,Repeated Intersession Network Coding Games: Efficiency and Min-Max Bargaining Solution,0769f49a69f3d7e0c6d89d0918096dfd,https://ieeexplore.ieee.org/document/6565417/
3558,"Recent results have shown that selfish users do not have an incentive to participate in intersession network coding in a static noncooperative game setting. Because of this, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 20%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be improved to 36%. We design a grim-trigger strategy that encourages users to cooperate and participate in the intersession network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We resolve the conflict of interest among the users through a bargaining process and obtain tight upper bounds for the price-of-anarchy that are valid for any possible bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve these upper bounds, as confirmed through simulation studies. The coexistence of multiple selfish network coding sessions as well as the coexistence of selfish network coding and routing sessions are also investigated. Our results represent a first step toward designing practical intersession network coding schemes that achieve reasonable performance for selfish users.",hamed mohsenian-rad,resource management,2014.0,10.1109/TNET.2013.2271038,IEEE/ACM Transactions on Networking,Mohsenian-Rad2014,False,,IEEE,Not available,Repeated Intersession Network Coding Games: Efficiency and Min-Max Bargaining Solution,0769f49a69f3d7e0c6d89d0918096dfd,https://ieeexplore.ieee.org/document/6565417/
3559,"Recent results have shown that selfish users do not have an incentive to participate in intersession network coding in a static noncooperative game setting. Because of this, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 20%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be improved to 36%. We design a grim-trigger strategy that encourages users to cooperate and participate in the intersession network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We resolve the conflict of interest among the users through a bargaining process and obtain tight upper bounds for the price-of-anarchy that are valid for any possible bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve these upper bounds, as confirmed through simulation studies. The coexistence of multiple selfish network coding sessions as well as the coexistence of selfish network coding and routing sessions are also investigated. Our results represent a first step toward designing practical intersession network coding schemes that achieve reasonable performance for selfish users.",jianwei huang,Min-max bargaining solution,2014.0,10.1109/TNET.2013.2271038,IEEE/ACM Transactions on Networking,Mohsenian-Rad2014,False,,IEEE,Not available,Repeated Intersession Network Coding Games: Efficiency and Min-Max Bargaining Solution,0769f49a69f3d7e0c6d89d0918096dfd,https://ieeexplore.ieee.org/document/6565417/
3560,"Recent results have shown that selfish users do not have an incentive to participate in intersession network coding in a static noncooperative game setting. Because of this, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 20%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be improved to 36%. We design a grim-trigger strategy that encourages users to cooperate and participate in the intersession network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We resolve the conflict of interest among the users through a bargaining process and obtain tight upper bounds for the price-of-anarchy that are valid for any possible bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve these upper bounds, as confirmed through simulation studies. The coexistence of multiple selfish network coding sessions as well as the coexistence of selfish network coding and routing sessions are also investigated. Our results represent a first step toward designing practical intersession network coding schemes that achieve reasonable performance for selfish users.",jianwei huang,network coding,2014.0,10.1109/TNET.2013.2271038,IEEE/ACM Transactions on Networking,Mohsenian-Rad2014,False,,IEEE,Not available,Repeated Intersession Network Coding Games: Efficiency and Min-Max Bargaining Solution,0769f49a69f3d7e0c6d89d0918096dfd,https://ieeexplore.ieee.org/document/6565417/
3561,"Recent results have shown that selfish users do not have an incentive to participate in intersession network coding in a static noncooperative game setting. Because of this, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 20%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be improved to 36%. We design a grim-trigger strategy that encourages users to cooperate and participate in the intersession network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We resolve the conflict of interest among the users through a bargaining process and obtain tight upper bounds for the price-of-anarchy that are valid for any possible bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve these upper bounds, as confirmed through simulation studies. The coexistence of multiple selfish network coding sessions as well as the coexistence of selfish network coding and routing sessions are also investigated. Our results represent a first step toward designing practical intersession network coding schemes that achieve reasonable performance for selfish users.",jianwei huang,repeated game theory,2014.0,10.1109/TNET.2013.2271038,IEEE/ACM Transactions on Networking,Mohsenian-Rad2014,False,,IEEE,Not available,Repeated Intersession Network Coding Games: Efficiency and Min-Max Bargaining Solution,0769f49a69f3d7e0c6d89d0918096dfd,https://ieeexplore.ieee.org/document/6565417/
3562,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
3563,"Recent results have shown that selfish users do not have an incentive to participate in intersession network coding in a static noncooperative game setting. Because of this, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 20%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be improved to 36%. We design a grim-trigger strategy that encourages users to cooperate and participate in the intersession network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We resolve the conflict of interest among the users through a bargaining process and obtain tight upper bounds for the price-of-anarchy that are valid for any possible bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve these upper bounds, as confirmed through simulation studies. The coexistence of multiple selfish network coding sessions as well as the coexistence of selfish network coding and routing sessions are also investigated. Our results represent a first step toward designing practical intersession network coding schemes that achieve reasonable performance for selfish users.",jianwei huang,resource management,2014.0,10.1109/TNET.2013.2271038,IEEE/ACM Transactions on Networking,Mohsenian-Rad2014,False,,IEEE,Not available,Repeated Intersession Network Coding Games: Efficiency and Min-Max Bargaining Solution,0769f49a69f3d7e0c6d89d0918096dfd,https://ieeexplore.ieee.org/document/6565417/
3564,"Recent results have shown that selfish users do not have an incentive to participate in intersession network coding in a static noncooperative game setting. Because of this, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 20%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be improved to 36%. We design a grim-trigger strategy that encourages users to cooperate and participate in the intersession network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We resolve the conflict of interest among the users through a bargaining process and obtain tight upper bounds for the price-of-anarchy that are valid for any possible bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve these upper bounds, as confirmed through simulation studies. The coexistence of multiple selfish network coding sessions as well as the coexistence of selfish network coding and routing sessions are also investigated. Our results represent a first step toward designing practical intersession network coding schemes that achieve reasonable performance for selfish users.",vincent wong,Min-max bargaining solution,2014.0,10.1109/TNET.2013.2271038,IEEE/ACM Transactions on Networking,Mohsenian-Rad2014,False,,IEEE,Not available,Repeated Intersession Network Coding Games: Efficiency and Min-Max Bargaining Solution,0769f49a69f3d7e0c6d89d0918096dfd,https://ieeexplore.ieee.org/document/6565417/
3565,"Recent results have shown that selfish users do not have an incentive to participate in intersession network coding in a static noncooperative game setting. Because of this, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 20%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be improved to 36%. We design a grim-trigger strategy that encourages users to cooperate and participate in the intersession network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We resolve the conflict of interest among the users through a bargaining process and obtain tight upper bounds for the price-of-anarchy that are valid for any possible bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve these upper bounds, as confirmed through simulation studies. The coexistence of multiple selfish network coding sessions as well as the coexistence of selfish network coding and routing sessions are also investigated. Our results represent a first step toward designing practical intersession network coding schemes that achieve reasonable performance for selfish users.",vincent wong,network coding,2014.0,10.1109/TNET.2013.2271038,IEEE/ACM Transactions on Networking,Mohsenian-Rad2014,False,,IEEE,Not available,Repeated Intersession Network Coding Games: Efficiency and Min-Max Bargaining Solution,0769f49a69f3d7e0c6d89d0918096dfd,https://ieeexplore.ieee.org/document/6565417/
3566,"Recent results have shown that selfish users do not have an incentive to participate in intersession network coding in a static noncooperative game setting. Because of this, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 20%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be improved to 36%. We design a grim-trigger strategy that encourages users to cooperate and participate in the intersession network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We resolve the conflict of interest among the users through a bargaining process and obtain tight upper bounds for the price-of-anarchy that are valid for any possible bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve these upper bounds, as confirmed through simulation studies. The coexistence of multiple selfish network coding sessions as well as the coexistence of selfish network coding and routing sessions are also investigated. Our results represent a first step toward designing practical intersession network coding schemes that achieve reasonable performance for selfish users.",vincent wong,repeated game theory,2014.0,10.1109/TNET.2013.2271038,IEEE/ACM Transactions on Networking,Mohsenian-Rad2014,False,,IEEE,Not available,Repeated Intersession Network Coding Games: Efficiency and Min-Max Bargaining Solution,0769f49a69f3d7e0c6d89d0918096dfd,https://ieeexplore.ieee.org/document/6565417/
3567,"Recent results have shown that selfish users do not have an incentive to participate in intersession network coding in a static noncooperative game setting. Because of this, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 20%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be improved to 36%. We design a grim-trigger strategy that encourages users to cooperate and participate in the intersession network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We resolve the conflict of interest among the users through a bargaining process and obtain tight upper bounds for the price-of-anarchy that are valid for any possible bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve these upper bounds, as confirmed through simulation studies. The coexistence of multiple selfish network coding sessions as well as the coexistence of selfish network coding and routing sessions are also investigated. Our results represent a first step toward designing practical intersession network coding schemes that achieve reasonable performance for selfish users.",vincent wong,resource management,2014.0,10.1109/TNET.2013.2271038,IEEE/ACM Transactions on Networking,Mohsenian-Rad2014,False,,IEEE,Not available,Repeated Intersession Network Coding Games: Efficiency and Min-Max Bargaining Solution,0769f49a69f3d7e0c6d89d0918096dfd,https://ieeexplore.ieee.org/document/6565417/
3568,"Recent results have shown that selfish users do not have an incentive to participate in intersession network coding in a static noncooperative game setting. Because of this, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 20%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be improved to 36%. We design a grim-trigger strategy that encourages users to cooperate and participate in the intersession network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We resolve the conflict of interest among the users through a bargaining process and obtain tight upper bounds for the price-of-anarchy that are valid for any possible bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve these upper bounds, as confirmed through simulation studies. The coexistence of multiple selfish network coding sessions as well as the coexistence of selfish network coding and routing sessions are also investigated. Our results represent a first step toward designing practical intersession network coding schemes that achieve reasonable performance for selfish users.",robert schober,Min-max bargaining solution,2014.0,10.1109/TNET.2013.2271038,IEEE/ACM Transactions on Networking,Mohsenian-Rad2014,False,,IEEE,Not available,Repeated Intersession Network Coding Games: Efficiency and Min-Max Bargaining Solution,0769f49a69f3d7e0c6d89d0918096dfd,https://ieeexplore.ieee.org/document/6565417/
3569,"Recent results have shown that selfish users do not have an incentive to participate in intersession network coding in a static noncooperative game setting. Because of this, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 20%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be improved to 36%. We design a grim-trigger strategy that encourages users to cooperate and participate in the intersession network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We resolve the conflict of interest among the users through a bargaining process and obtain tight upper bounds for the price-of-anarchy that are valid for any possible bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve these upper bounds, as confirmed through simulation studies. The coexistence of multiple selfish network coding sessions as well as the coexistence of selfish network coding and routing sessions are also investigated. Our results represent a first step toward designing practical intersession network coding schemes that achieve reasonable performance for selfish users.",robert schober,network coding,2014.0,10.1109/TNET.2013.2271038,IEEE/ACM Transactions on Networking,Mohsenian-Rad2014,False,,IEEE,Not available,Repeated Intersession Network Coding Games: Efficiency and Min-Max Bargaining Solution,0769f49a69f3d7e0c6d89d0918096dfd,https://ieeexplore.ieee.org/document/6565417/
3570,"Recent results have shown that selfish users do not have an incentive to participate in intersession network coding in a static noncooperative game setting. Because of this, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 20%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be improved to 36%. We design a grim-trigger strategy that encourages users to cooperate and participate in the intersession network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We resolve the conflict of interest among the users through a bargaining process and obtain tight upper bounds for the price-of-anarchy that are valid for any possible bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve these upper bounds, as confirmed through simulation studies. The coexistence of multiple selfish network coding sessions as well as the coexistence of selfish network coding and routing sessions are also investigated. Our results represent a first step toward designing practical intersession network coding schemes that achieve reasonable performance for selfish users.",robert schober,repeated game theory,2014.0,10.1109/TNET.2013.2271038,IEEE/ACM Transactions on Networking,Mohsenian-Rad2014,False,,IEEE,Not available,Repeated Intersession Network Coding Games: Efficiency and Min-Max Bargaining Solution,0769f49a69f3d7e0c6d89d0918096dfd,https://ieeexplore.ieee.org/document/6565417/
3571,"Recent results have shown that selfish users do not have an incentive to participate in intersession network coding in a static noncooperative game setting. Because of this, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 20%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be improved to 36%. We design a grim-trigger strategy that encourages users to cooperate and participate in the intersession network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We resolve the conflict of interest among the users through a bargaining process and obtain tight upper bounds for the price-of-anarchy that are valid for any possible bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve these upper bounds, as confirmed through simulation studies. The coexistence of multiple selfish network coding sessions as well as the coexistence of selfish network coding and routing sessions are also investigated. Our results represent a first step toward designing practical intersession network coding schemes that achieve reasonable performance for selfish users.",robert schober,resource management,2014.0,10.1109/TNET.2013.2271038,IEEE/ACM Transactions on Networking,Mohsenian-Rad2014,False,,IEEE,Not available,Repeated Intersession Network Coding Games: Efficiency and Min-Max Bargaining Solution,0769f49a69f3d7e0c6d89d0918096dfd,https://ieeexplore.ieee.org/document/6565417/
3572,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",j. doncel,Servers,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
3573,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
3574,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",j. doncel,Routing,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
3575,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",j. doncel,Games,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
3576,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",j. doncel,Nash equilibrium,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
3577,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",j. doncel,Vectors,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
3578,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",j. doncel,Optimization,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
3579,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",j. doncel,Computer architecture,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
3580,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",u. ayesta,Servers,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
3581,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",u. ayesta,Routing,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
3582,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",u. ayesta,Games,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
3583,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",u. ayesta,Nash equilibrium,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
3584,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
3585,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",u. ayesta,Vectors,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
3586,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",u. ayesta,Optimization,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
3587,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",u. ayesta,Computer architecture,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
3588,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",o. brun,Servers,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
3589,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",o. brun,Routing,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
3590,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",o. brun,Games,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
3591,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",o. brun,Nash equilibrium,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
3592,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",o. brun,Vectors,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
3593,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",o. brun,Optimization,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
3594,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",o. brun,Computer architecture,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
3595,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
3596,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",b.j. prabhu,Servers,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
3597,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",b.j. prabhu,Routing,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
3598,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",b.j. prabhu,Games,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
3599,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",b.j. prabhu,Nash equilibrium,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
3600,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",b.j. prabhu,Vectors,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
3601,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",b.j. prabhu,Optimization,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
3602,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",b.j. prabhu,Computer architecture,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
3603,"We will present recent work on the resilience and risk of failure emerging in cyber-physical infrastructures such as smart transportation systems and the smart grid. In the first part of the talk, we present results on the volatility and risk of failure associated with real-time response in the future smart grid. Real-time demand response has been postulated as the solution to the intermittency problem created by renewable generation. The proposed market architecture is simple, namely, consumers react directly to spot market prices in order to fulfill their demands. This mechanism creates a closed loop system between price and demand that has implications on efficiency, demand and price volatility, and risk of demand spikes. In this talk, we first present an analysis of this closed loop system for homogeneous consumers and highlight the tradeoffs between market efficiency and demand and price volatility. Then, we present an abstracted framework to analyze the tradeoffs between efficiency and risk for heterogeneous consumers in the presence of shiftable demands. In this context, we expand the market mechanism to study the impact of coordination on such a tradeoff. We show that although the non-cooperative load-shifting scheme leads to an efficiency loss (otherwise known as the price of anarchy), the scheme has a smaller tail probability of the aggregate unshiftable demand distribution than cooperative schemes. This tail distribution is important as it corresponds to rare and undesirable demand spikes. Such instances highlight the role of the market mechanisms in striking a balance between efficiency and risk in real-time markets. In the second part of the talk, we present results on the robustness (resilience) properticlosedes of transportation networks for various agents' route-choice behavior. We perform the analysis within a dynamical system framework over a directed acyclic graph between a single origin-destination pair. We give a precise characterization of various margins of resilience of the network with respect to the topology, `pre-disturbance' equilibrium, and agents' local route-choice behavior. We show that the cooperative route choice behavior is maximally resilient in this setting. We also setup a simple convex optimization problem to find the most resilient `pre-disturbance' equilibrium for the network and determine link-wise tolls that yield such an equilibrium. Finally, we extend the analysis to link-wise outflow functions that accommodate the possibility of cascaded failures and study the effect of such phenomena on the margins of resilience of the network.",munther dahleh,Resilience,2014.0,10.1109/MED.2014.6961439,22nd Mediterranean Conference on Control and Automation,Dahleh2014,False,,IEEE,Not available,Plenary talk: Resilience and risk in networked systems,d54786112c97b8c2b879ee53c7b69094,https://ieeexplore.ieee.org/document/6961439/
3604,"We will present recent work on the resilience and risk of failure emerging in cyber-physical infrastructures such as smart transportation systems and the smart grid. In the first part of the talk, we present results on the volatility and risk of failure associated with real-time response in the future smart grid. Real-time demand response has been postulated as the solution to the intermittency problem created by renewable generation. The proposed market architecture is simple, namely, consumers react directly to spot market prices in order to fulfill their demands. This mechanism creates a closed loop system between price and demand that has implications on efficiency, demand and price volatility, and risk of demand spikes. In this talk, we first present an analysis of this closed loop system for homogeneous consumers and highlight the tradeoffs between market efficiency and demand and price volatility. Then, we present an abstracted framework to analyze the tradeoffs between efficiency and risk for heterogeneous consumers in the presence of shiftable demands. In this context, we expand the market mechanism to study the impact of coordination on such a tradeoff. We show that although the non-cooperative load-shifting scheme leads to an efficiency loss (otherwise known as the price of anarchy), the scheme has a smaller tail probability of the aggregate unshiftable demand distribution than cooperative schemes. This tail distribution is important as it corresponds to rare and undesirable demand spikes. Such instances highlight the role of the market mechanisms in striking a balance between efficiency and risk in real-time markets. In the second part of the talk, we present results on the robustness (resilience) properticlosedes of transportation networks for various agents' route-choice behavior. We perform the analysis within a dynamical system framework over a directed acyclic graph between a single origin-destination pair. We give a precise characterization of various margins of resilience of the network with respect to the topology, `pre-disturbance' equilibrium, and agents' local route-choice behavior. We show that the cooperative route choice behavior is maximally resilient in this setting. We also setup a simple convex optimization problem to find the most resilient `pre-disturbance' equilibrium for the network and determine link-wise tolls that yield such an equilibrium. Finally, we extend the analysis to link-wise outflow functions that accommodate the possibility of cascaded failures and study the effect of such phenomena on the margins of resilience of the network.",munther dahleh,Real-time systems,2014.0,10.1109/MED.2014.6961439,22nd Mediterranean Conference on Control and Automation,Dahleh2014,False,,IEEE,Not available,Plenary talk: Resilience and risk in networked systems,d54786112c97b8c2b879ee53c7b69094,https://ieeexplore.ieee.org/document/6961439/
3605,"We will present recent work on the resilience and risk of failure emerging in cyber-physical infrastructures such as smart transportation systems and the smart grid. In the first part of the talk, we present results on the volatility and risk of failure associated with real-time response in the future smart grid. Real-time demand response has been postulated as the solution to the intermittency problem created by renewable generation. The proposed market architecture is simple, namely, consumers react directly to spot market prices in order to fulfill their demands. This mechanism creates a closed loop system between price and demand that has implications on efficiency, demand and price volatility, and risk of demand spikes. In this talk, we first present an analysis of this closed loop system for homogeneous consumers and highlight the tradeoffs between market efficiency and demand and price volatility. Then, we present an abstracted framework to analyze the tradeoffs between efficiency and risk for heterogeneous consumers in the presence of shiftable demands. In this context, we expand the market mechanism to study the impact of coordination on such a tradeoff. We show that although the non-cooperative load-shifting scheme leads to an efficiency loss (otherwise known as the price of anarchy), the scheme has a smaller tail probability of the aggregate unshiftable demand distribution than cooperative schemes. This tail distribution is important as it corresponds to rare and undesirable demand spikes. Such instances highlight the role of the market mechanisms in striking a balance between efficiency and risk in real-time markets. In the second part of the talk, we present results on the robustness (resilience) properticlosedes of transportation networks for various agents' route-choice behavior. We perform the analysis within a dynamical system framework over a directed acyclic graph between a single origin-destination pair. We give a precise characterization of various margins of resilience of the network with respect to the topology, `pre-disturbance' equilibrium, and agents' local route-choice behavior. We show that the cooperative route choice behavior is maximally resilient in this setting. We also setup a simple convex optimization problem to find the most resilient `pre-disturbance' equilibrium for the network and determine link-wise tolls that yield such an equilibrium. Finally, we extend the analysis to link-wise outflow functions that accommodate the possibility of cascaded failures and study the effect of such phenomena on the margins of resilience of the network.",munther dahleh,Transportation,2014.0,10.1109/MED.2014.6961439,22nd Mediterranean Conference on Control and Automation,Dahleh2014,False,,IEEE,Not available,Plenary talk: Resilience and risk in networked systems,d54786112c97b8c2b879ee53c7b69094,https://ieeexplore.ieee.org/document/6961439/
3606,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
3607,"We will present recent work on the resilience and risk of failure emerging in cyber-physical infrastructures such as smart transportation systems and the smart grid. In the first part of the talk, we present results on the volatility and risk of failure associated with real-time response in the future smart grid. Real-time demand response has been postulated as the solution to the intermittency problem created by renewable generation. The proposed market architecture is simple, namely, consumers react directly to spot market prices in order to fulfill their demands. This mechanism creates a closed loop system between price and demand that has implications on efficiency, demand and price volatility, and risk of demand spikes. In this talk, we first present an analysis of this closed loop system for homogeneous consumers and highlight the tradeoffs between market efficiency and demand and price volatility. Then, we present an abstracted framework to analyze the tradeoffs between efficiency and risk for heterogeneous consumers in the presence of shiftable demands. In this context, we expand the market mechanism to study the impact of coordination on such a tradeoff. We show that although the non-cooperative load-shifting scheme leads to an efficiency loss (otherwise known as the price of anarchy), the scheme has a smaller tail probability of the aggregate unshiftable demand distribution than cooperative schemes. This tail distribution is important as it corresponds to rare and undesirable demand spikes. Such instances highlight the role of the market mechanisms in striking a balance between efficiency and risk in real-time markets. In the second part of the talk, we present results on the robustness (resilience) properticlosedes of transportation networks for various agents' route-choice behavior. We perform the analysis within a dynamical system framework over a directed acyclic graph between a single origin-destination pair. We give a precise characterization of various margins of resilience of the network with respect to the topology, `pre-disturbance' equilibrium, and agents' local route-choice behavior. We show that the cooperative route choice behavior is maximally resilient in this setting. We also setup a simple convex optimization problem to find the most resilient `pre-disturbance' equilibrium for the network and determine link-wise tolls that yield such an equilibrium. Finally, we extend the analysis to link-wise outflow functions that accommodate the possibility of cascaded failures and study the effect of such phenomena on the margins of resilience of the network.",munther dahleh,Smart grids,2014.0,10.1109/MED.2014.6961439,22nd Mediterranean Conference on Control and Automation,Dahleh2014,False,,IEEE,Not available,Plenary talk: Resilience and risk in networked systems,d54786112c97b8c2b879ee53c7b69094,https://ieeexplore.ieee.org/document/6961439/
3608,"We will present recent work on the resilience and risk of failure emerging in cyber-physical infrastructures such as smart transportation systems and the smart grid. In the first part of the talk, we present results on the volatility and risk of failure associated with real-time response in the future smart grid. Real-time demand response has been postulated as the solution to the intermittency problem created by renewable generation. The proposed market architecture is simple, namely, consumers react directly to spot market prices in order to fulfill their demands. This mechanism creates a closed loop system between price and demand that has implications on efficiency, demand and price volatility, and risk of demand spikes. In this talk, we first present an analysis of this closed loop system for homogeneous consumers and highlight the tradeoffs between market efficiency and demand and price volatility. Then, we present an abstracted framework to analyze the tradeoffs between efficiency and risk for heterogeneous consumers in the presence of shiftable demands. In this context, we expand the market mechanism to study the impact of coordination on such a tradeoff. We show that although the non-cooperative load-shifting scheme leads to an efficiency loss (otherwise known as the price of anarchy), the scheme has a smaller tail probability of the aggregate unshiftable demand distribution than cooperative schemes. This tail distribution is important as it corresponds to rare and undesirable demand spikes. Such instances highlight the role of the market mechanisms in striking a balance between efficiency and risk in real-time markets. In the second part of the talk, we present results on the robustness (resilience) properticlosedes of transportation networks for various agents' route-choice behavior. We perform the analysis within a dynamical system framework over a directed acyclic graph between a single origin-destination pair. We give a precise characterization of various margins of resilience of the network with respect to the topology, `pre-disturbance' equilibrium, and agents' local route-choice behavior. We show that the cooperative route choice behavior is maximally resilient in this setting. We also setup a simple convex optimization problem to find the most resilient `pre-disturbance' equilibrium for the network and determine link-wise tolls that yield such an equilibrium. Finally, we extend the analysis to link-wise outflow functions that accommodate the possibility of cascaded failures and study the effect of such phenomena on the margins of resilience of the network.",munther dahleh,Closed loop systems,2014.0,10.1109/MED.2014.6961439,22nd Mediterranean Conference on Control and Automation,Dahleh2014,False,,IEEE,Not available,Plenary talk: Resilience and risk in networked systems,d54786112c97b8c2b879ee53c7b69094,https://ieeexplore.ieee.org/document/6961439/
3609,"We will present recent work on the resilience and risk of failure emerging in cyber-physical infrastructures such as smart transportation systems and the smart grid. In the first part of the talk, we present results on the volatility and risk of failure associated with real-time response in the future smart grid. Real-time demand response has been postulated as the solution to the intermittency problem created by renewable generation. The proposed market architecture is simple, namely, consumers react directly to spot market prices in order to fulfill their demands. This mechanism creates a closed loop system between price and demand that has implications on efficiency, demand and price volatility, and risk of demand spikes. In this talk, we first present an analysis of this closed loop system for homogeneous consumers and highlight the tradeoffs between market efficiency and demand and price volatility. Then, we present an abstracted framework to analyze the tradeoffs between efficiency and risk for heterogeneous consumers in the presence of shiftable demands. In this context, we expand the market mechanism to study the impact of coordination on such a tradeoff. We show that although the non-cooperative load-shifting scheme leads to an efficiency loss (otherwise known as the price of anarchy), the scheme has a smaller tail probability of the aggregate unshiftable demand distribution than cooperative schemes. This tail distribution is important as it corresponds to rare and undesirable demand spikes. Such instances highlight the role of the market mechanisms in striking a balance between efficiency and risk in real-time markets. In the second part of the talk, we present results on the robustness (resilience) properticlosedes of transportation networks for various agents' route-choice behavior. We perform the analysis within a dynamical system framework over a directed acyclic graph between a single origin-destination pair. We give a precise characterization of various margins of resilience of the network with respect to the topology, `pre-disturbance' equilibrium, and agents' local route-choice behavior. We show that the cooperative route choice behavior is maximally resilient in this setting. We also setup a simple convex optimization problem to find the most resilient `pre-disturbance' equilibrium for the network and determine link-wise tolls that yield such an equilibrium. Finally, we extend the analysis to link-wise outflow functions that accommodate the possibility of cascaded failures and study the effect of such phenomena on the margins of resilience of the network.",munther dahleh,Automation,2014.0,10.1109/MED.2014.6961439,22nd Mediterranean Conference on Control and Automation,Dahleh2014,False,,IEEE,Not available,Plenary talk: Resilience and risk in networked systems,d54786112c97b8c2b879ee53c7b69094,https://ieeexplore.ieee.org/document/6961439/
3610,"We will present recent work on the resilience and risk of failure emerging in cyber-physical infrastructures such as smart transportation systems and the smart grid. In the first part of the talk, we present results on the volatility and risk of failure associated with real-time response in the future smart grid. Real-time demand response has been postulated as the solution to the intermittency problem created by renewable generation. The proposed market architecture is simple, namely, consumers react directly to spot market prices in order to fulfill their demands. This mechanism creates a closed loop system between price and demand that has implications on efficiency, demand and price volatility, and risk of demand spikes. In this talk, we first present an analysis of this closed loop system for homogeneous consumers and highlight the tradeoffs between market efficiency and demand and price volatility. Then, we present an abstracted framework to analyze the tradeoffs between efficiency and risk for heterogeneous consumers in the presence of shiftable demands. In this context, we expand the market mechanism to study the impact of coordination on such a tradeoff. We show that although the non-cooperative load-shifting scheme leads to an efficiency loss (otherwise known as the price of anarchy), the scheme has a smaller tail probability of the aggregate unshiftable demand distribution than cooperative schemes. This tail distribution is important as it corresponds to rare and undesirable demand spikes. Such instances highlight the role of the market mechanisms in striking a balance between efficiency and risk in real-time markets. In the second part of the talk, we present results on the robustness (resilience) properticlosedes of transportation networks for various agents' route-choice behavior. We perform the analysis within a dynamical system framework over a directed acyclic graph between a single origin-destination pair. We give a precise characterization of various margins of resilience of the network with respect to the topology, `pre-disturbance' equilibrium, and agents' local route-choice behavior. We show that the cooperative route choice behavior is maximally resilient in this setting. We also setup a simple convex optimization problem to find the most resilient `pre-disturbance' equilibrium for the network and determine link-wise tolls that yield such an equilibrium. Finally, we extend the analysis to link-wise outflow functions that accommodate the possibility of cascaded failures and study the effect of such phenomena on the margins of resilience of the network.",munther dahleh,Educational institutions,2014.0,10.1109/MED.2014.6961439,22nd Mediterranean Conference on Control and Automation,Dahleh2014,False,,IEEE,Not available,Plenary talk: Resilience and risk in networked systems,d54786112c97b8c2b879ee53c7b69094,https://ieeexplore.ieee.org/document/6961439/
3611,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of the eta-Nash equilibria (eta-NEs), of the two-user linear deterministic interference channel with noisy channel-output feedback are characterized, with eta &gt; 0 arbitrarily small. The price of anarchy is the ratio between the sum-rate capacity and the smallest sum-rate at an eta-NE. Alternatively, the price of stability is the ratio between the sumrate capacity and the biggest sum-rate at an eta-NE. Some of the main conclusions of this work are the following: (a) When both transmitter-receiver pairs are in the low-interference regime, the PoA can be made arbitrarily close to one as eta approaches zero, subject to a particular condition. More specifically, there are scenarios in which even the worst eta-NE (in terms of sumrate) is arbitrarily close to the Pareto boundary of the capacity region. (b) The use of feedback plays a fundamental role on increasing the PoA in some interference regimes. This is basically because in these regimes, the use of feedback increases the sumcapacity, whereas the smallest sum-rate at an eta-NE remains the same as in the case without feedback. (c) The PoS is equal to one in all the interference regimes. This implies that there always exists an eta-NE in the Pareto boundary of the capacity region. The conclusions of this work reveal the relevance of jointly using equilibrium selection methods and channel-output feedback for reducing the effect of anarchical behavior of the network components in the eta-NE sum-rate of the interference channel.",victor quintero,,2017.0,,European Wireless 2017; 23th European Wireless Conference,Quintero2017,False,,IEEE,Not available,On the Efficiency of Nash Equilibria in the Interference Channel with Noisy Feedback,febabe0d38c6a9daca1d77c0d3e31318,
3612,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of the eta-Nash equilibria (eta-NEs), of the two-user linear deterministic interference channel with noisy channel-output feedback are characterized, with eta &gt; 0 arbitrarily small. The price of anarchy is the ratio between the sum-rate capacity and the smallest sum-rate at an eta-NE. Alternatively, the price of stability is the ratio between the sumrate capacity and the biggest sum-rate at an eta-NE. Some of the main conclusions of this work are the following: (a) When both transmitter-receiver pairs are in the low-interference regime, the PoA can be made arbitrarily close to one as eta approaches zero, subject to a particular condition. More specifically, there are scenarios in which even the worst eta-NE (in terms of sumrate) is arbitrarily close to the Pareto boundary of the capacity region. (b) The use of feedback plays a fundamental role on increasing the PoA in some interference regimes. This is basically because in these regimes, the use of feedback increases the sumcapacity, whereas the smallest sum-rate at an eta-NE remains the same as in the case without feedback. (c) The PoS is equal to one in all the interference regimes. This implies that there always exists an eta-NE in the Pareto boundary of the capacity region. The conclusions of this work reveal the relevance of jointly using equilibrium selection methods and channel-output feedback for reducing the effect of anarchical behavior of the network components in the eta-NE sum-rate of the interference channel.",samir perlaza,,2017.0,,European Wireless 2017; 23th European Wireless Conference,Quintero2017,False,,IEEE,Not available,On the Efficiency of Nash Equilibria in the Interference Channel with Noisy Feedback,febabe0d38c6a9daca1d77c0d3e31318,
3613,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of the eta-Nash equilibria (eta-NEs), of the two-user linear deterministic interference channel with noisy channel-output feedback are characterized, with eta &gt; 0 arbitrarily small. The price of anarchy is the ratio between the sum-rate capacity and the smallest sum-rate at an eta-NE. Alternatively, the price of stability is the ratio between the sumrate capacity and the biggest sum-rate at an eta-NE. Some of the main conclusions of this work are the following: (a) When both transmitter-receiver pairs are in the low-interference regime, the PoA can be made arbitrarily close to one as eta approaches zero, subject to a particular condition. More specifically, there are scenarios in which even the worst eta-NE (in terms of sumrate) is arbitrarily close to the Pareto boundary of the capacity region. (b) The use of feedback plays a fundamental role on increasing the PoA in some interference regimes. This is basically because in these regimes, the use of feedback increases the sumcapacity, whereas the smallest sum-rate at an eta-NE remains the same as in the case without feedback. (c) The PoS is equal to one in all the interference regimes. This implies that there always exists an eta-NE in the Pareto boundary of the capacity region. The conclusions of this work reveal the relevance of jointly using equilibrium selection methods and channel-output feedback for reducing the effect of anarchical behavior of the network components in the eta-NE sum-rate of the interference channel.",jean-marie gorce,,2017.0,,European Wireless 2017; 23th European Wireless Conference,Quintero2017,False,,IEEE,Not available,On the Efficiency of Nash Equilibria in the Interference Channel with Noisy Feedback,febabe0d38c6a9daca1d77c0d3e31318,
3614,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",m. goemans,Convergence,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
3615,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",m. goemans,Routing,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
3616,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",m. goemans,Cost function,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
3617,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
3618,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",m. goemans,Steady-state,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
3619,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",m. goemans,Polynomials,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
3620,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",m. goemans,Delay,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
3621,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",m. goemans,Performance analysis,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
3622,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",m. goemans,Control systems,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
3623,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",m. goemans,Nash equilibrium,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
3624,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",m. goemans,Computer science,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
3625,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",vahab mirrokni,Convergence,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
3626,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",vahab mirrokni,Routing,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
3627,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",vahab mirrokni,Cost function,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
3628,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
3629,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
3630,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",vahab mirrokni,Steady-state,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
3631,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",vahab mirrokni,Polynomials,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
3632,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",vahab mirrokni,Delay,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
3633,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",vahab mirrokni,Performance analysis,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
3634,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",vahab mirrokni,Control systems,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
3635,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",vahab mirrokni,Nash equilibrium,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
3636,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",vahab mirrokni,Computer science,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
3637,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",a. vetta,Convergence,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
3638,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",a. vetta,Routing,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
3639,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",a. vetta,Cost function,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
3640,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
3641,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",a. vetta,Steady-state,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
3642,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",a. vetta,Polynomials,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
3643,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",a. vetta,Delay,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
3644,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",a. vetta,Performance analysis,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
3645,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",a. vetta,Control systems,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
3646,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",a. vetta,Nash equilibrium,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
3647,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",a. vetta,Computer science,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
3648,"We study a single server model with no queue and exponential services times, in which service is only provided during a certain time interval. A number of customers wish to obtain this service and can choose their arrival time. A customer that finds a busy server leaves without being served. We model this scenario as a non-cooperative game in which the customers wish to maximize their probability of obtaining service. We characterize the Nash equilibrium and the price of anarchy, which is defined as the ratio between the optimal and equilibrium social utility. In particular, the equilibrium arrival distribution has an atom at zero, a period with no arrival and is continuous on some interval until the closing time. We further generalize our analysis to take into account uncertainty regarding the population size, i.e. a game with a random number of customers. In the special case where the population size follows a Poisson distribution, we show that the continuous part of the distribution is uniform, which is not the case in general. Finally, we show that the price of anarchy is not monotone with respect to the population size; but rather uni-modal with values close to one for small and large populations.",liron ravner,Servers,2014.0,,"2014 7th International Conference on NETwork Games, COntrol and OPtimization (NetGCoop)",Ravner2014,False,,IEEE,Not available,Equilibrium and socially optimal arrivals to a single server loss system,dbb596e13a10cf149f4fa320d9cc1114,https://ieeexplore.ieee.org/document/7943402/
3649,"We study a single server model with no queue and exponential services times, in which service is only provided during a certain time interval. A number of customers wish to obtain this service and can choose their arrival time. A customer that finds a busy server leaves without being served. We model this scenario as a non-cooperative game in which the customers wish to maximize their probability of obtaining service. We characterize the Nash equilibrium and the price of anarchy, which is defined as the ratio between the optimal and equilibrium social utility. In particular, the equilibrium arrival distribution has an atom at zero, a period with no arrival and is continuous on some interval until the closing time. We further generalize our analysis to take into account uncertainty regarding the population size, i.e. a game with a random number of customers. In the special case where the population size follows a Poisson distribution, we show that the continuous part of the distribution is uniform, which is not the case in general. Finally, we show that the price of anarchy is not monotone with respect to the population size; but rather uni-modal with values close to one for small and large populations.",liron ravner,Games,2014.0,,"2014 7th International Conference on NETwork Games, COntrol and OPtimization (NetGCoop)",Ravner2014,False,,IEEE,Not available,Equilibrium and socially optimal arrivals to a single server loss system,dbb596e13a10cf149f4fa320d9cc1114,https://ieeexplore.ieee.org/document/7943402/
3650,"We study a single server model with no queue and exponential services times, in which service is only provided during a certain time interval. A number of customers wish to obtain this service and can choose their arrival time. A customer that finds a busy server leaves without being served. We model this scenario as a non-cooperative game in which the customers wish to maximize their probability of obtaining service. We characterize the Nash equilibrium and the price of anarchy, which is defined as the ratio between the optimal and equilibrium social utility. In particular, the equilibrium arrival distribution has an atom at zero, a period with no arrival and is continuous on some interval until the closing time. We further generalize our analysis to take into account uncertainty regarding the population size, i.e. a game with a random number of customers. In the special case where the population size follows a Poisson distribution, we show that the continuous part of the distribution is uniform, which is not the case in general. Finally, we show that the price of anarchy is not monotone with respect to the population size; but rather uni-modal with values close to one for small and large populations.",liron ravner,Sociology,2014.0,,"2014 7th International Conference on NETwork Games, COntrol and OPtimization (NetGCoop)",Ravner2014,False,,IEEE,Not available,Equilibrium and socially optimal arrivals to a single server loss system,dbb596e13a10cf149f4fa320d9cc1114,https://ieeexplore.ieee.org/document/7943402/
3651,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
3652,"We study a single server model with no queue and exponential services times, in which service is only provided during a certain time interval. A number of customers wish to obtain this service and can choose their arrival time. A customer that finds a busy server leaves without being served. We model this scenario as a non-cooperative game in which the customers wish to maximize their probability of obtaining service. We characterize the Nash equilibrium and the price of anarchy, which is defined as the ratio between the optimal and equilibrium social utility. In particular, the equilibrium arrival distribution has an atom at zero, a period with no arrival and is continuous on some interval until the closing time. We further generalize our analysis to take into account uncertainty regarding the population size, i.e. a game with a random number of customers. In the special case where the population size follows a Poisson distribution, we show that the continuous part of the distribution is uniform, which is not the case in general. Finally, we show that the price of anarchy is not monotone with respect to the population size; but rather uni-modal with values close to one for small and large populations.",liron ravner,Statistics,2014.0,,"2014 7th International Conference on NETwork Games, COntrol and OPtimization (NetGCoop)",Ravner2014,False,,IEEE,Not available,Equilibrium and socially optimal arrivals to a single server loss system,dbb596e13a10cf149f4fa320d9cc1114,https://ieeexplore.ieee.org/document/7943402/
3653,"We study a single server model with no queue and exponential services times, in which service is only provided during a certain time interval. A number of customers wish to obtain this service and can choose their arrival time. A customer that finds a busy server leaves without being served. We model this scenario as a non-cooperative game in which the customers wish to maximize their probability of obtaining service. We characterize the Nash equilibrium and the price of anarchy, which is defined as the ratio between the optimal and equilibrium social utility. In particular, the equilibrium arrival distribution has an atom at zero, a period with no arrival and is continuous on some interval until the closing time. We further generalize our analysis to take into account uncertainty regarding the population size, i.e. a game with a random number of customers. In the special case where the population size follows a Poisson distribution, we show that the continuous part of the distribution is uniform, which is not the case in general. Finally, we show that the price of anarchy is not monotone with respect to the population size; but rather uni-modal with values close to one for small and large populations.",liron ravner,Analytical models,2014.0,,"2014 7th International Conference on NETwork Games, COntrol and OPtimization (NetGCoop)",Ravner2014,False,,IEEE,Not available,Equilibrium and socially optimal arrivals to a single server loss system,dbb596e13a10cf149f4fa320d9cc1114,https://ieeexplore.ieee.org/document/7943402/
3654,"We study a single server model with no queue and exponential services times, in which service is only provided during a certain time interval. A number of customers wish to obtain this service and can choose their arrival time. A customer that finds a busy server leaves without being served. We model this scenario as a non-cooperative game in which the customers wish to maximize their probability of obtaining service. We characterize the Nash equilibrium and the price of anarchy, which is defined as the ratio between the optimal and equilibrium social utility. In particular, the equilibrium arrival distribution has an atom at zero, a period with no arrival and is continuous on some interval until the closing time. We further generalize our analysis to take into account uncertainty regarding the population size, i.e. a game with a random number of customers. In the special case where the population size follows a Poisson distribution, we show that the continuous part of the distribution is uniform, which is not the case in general. Finally, we show that the price of anarchy is not monotone with respect to the population size; but rather uni-modal with values close to one for small and large populations.",liron ravner,Nash equilibrium,2014.0,,"2014 7th International Conference on NETwork Games, COntrol and OPtimization (NetGCoop)",Ravner2014,False,,IEEE,Not available,Equilibrium and socially optimal arrivals to a single server loss system,dbb596e13a10cf149f4fa320d9cc1114,https://ieeexplore.ieee.org/document/7943402/
3655,"We study a single server model with no queue and exponential services times, in which service is only provided during a certain time interval. A number of customers wish to obtain this service and can choose their arrival time. A customer that finds a busy server leaves without being served. We model this scenario as a non-cooperative game in which the customers wish to maximize their probability of obtaining service. We characterize the Nash equilibrium and the price of anarchy, which is defined as the ratio between the optimal and equilibrium social utility. In particular, the equilibrium arrival distribution has an atom at zero, a period with no arrival and is continuous on some interval until the closing time. We further generalize our analysis to take into account uncertainty regarding the population size, i.e. a game with a random number of customers. In the special case where the population size follows a Poisson distribution, we show that the continuous part of the distribution is uniform, which is not the case in general. Finally, we show that the price of anarchy is not monotone with respect to the population size; but rather uni-modal with values close to one for small and large populations.",liron ravner,Optimization,2014.0,,"2014 7th International Conference on NETwork Games, COntrol and OPtimization (NetGCoop)",Ravner2014,False,,IEEE,Not available,Equilibrium and socially optimal arrivals to a single server loss system,dbb596e13a10cf149f4fa320d9cc1114,https://ieeexplore.ieee.org/document/7943402/
3656,"We study a single server model with no queue and exponential services times, in which service is only provided during a certain time interval. A number of customers wish to obtain this service and can choose their arrival time. A customer that finds a busy server leaves without being served. We model this scenario as a non-cooperative game in which the customers wish to maximize their probability of obtaining service. We characterize the Nash equilibrium and the price of anarchy, which is defined as the ratio between the optimal and equilibrium social utility. In particular, the equilibrium arrival distribution has an atom at zero, a period with no arrival and is continuous on some interval until the closing time. We further generalize our analysis to take into account uncertainty regarding the population size, i.e. a game with a random number of customers. In the special case where the population size follows a Poisson distribution, we show that the continuous part of the distribution is uniform, which is not the case in general. Finally, we show that the price of anarchy is not monotone with respect to the population size; but rather uni-modal with values close to one for small and large populations.",moshe haviv,Servers,2014.0,,"2014 7th International Conference on NETwork Games, COntrol and OPtimization (NetGCoop)",Ravner2014,False,,IEEE,Not available,Equilibrium and socially optimal arrivals to a single server loss system,dbb596e13a10cf149f4fa320d9cc1114,https://ieeexplore.ieee.org/document/7943402/
3657,"We study a single server model with no queue and exponential services times, in which service is only provided during a certain time interval. A number of customers wish to obtain this service and can choose their arrival time. A customer that finds a busy server leaves without being served. We model this scenario as a non-cooperative game in which the customers wish to maximize their probability of obtaining service. We characterize the Nash equilibrium and the price of anarchy, which is defined as the ratio between the optimal and equilibrium social utility. In particular, the equilibrium arrival distribution has an atom at zero, a period with no arrival and is continuous on some interval until the closing time. We further generalize our analysis to take into account uncertainty regarding the population size, i.e. a game with a random number of customers. In the special case where the population size follows a Poisson distribution, we show that the continuous part of the distribution is uniform, which is not the case in general. Finally, we show that the price of anarchy is not monotone with respect to the population size; but rather uni-modal with values close to one for small and large populations.",moshe haviv,Games,2014.0,,"2014 7th International Conference on NETwork Games, COntrol and OPtimization (NetGCoop)",Ravner2014,False,,IEEE,Not available,Equilibrium and socially optimal arrivals to a single server loss system,dbb596e13a10cf149f4fa320d9cc1114,https://ieeexplore.ieee.org/document/7943402/
3658,"We study a single server model with no queue and exponential services times, in which service is only provided during a certain time interval. A number of customers wish to obtain this service and can choose their arrival time. A customer that finds a busy server leaves without being served. We model this scenario as a non-cooperative game in which the customers wish to maximize their probability of obtaining service. We characterize the Nash equilibrium and the price of anarchy, which is defined as the ratio between the optimal and equilibrium social utility. In particular, the equilibrium arrival distribution has an atom at zero, a period with no arrival and is continuous on some interval until the closing time. We further generalize our analysis to take into account uncertainty regarding the population size, i.e. a game with a random number of customers. In the special case where the population size follows a Poisson distribution, we show that the continuous part of the distribution is uniform, which is not the case in general. Finally, we show that the price of anarchy is not monotone with respect to the population size; but rather uni-modal with values close to one for small and large populations.",moshe haviv,Sociology,2014.0,,"2014 7th International Conference on NETwork Games, COntrol and OPtimization (NetGCoop)",Ravner2014,False,,IEEE,Not available,Equilibrium and socially optimal arrivals to a single server loss system,dbb596e13a10cf149f4fa320d9cc1114,https://ieeexplore.ieee.org/document/7943402/
3659,"We study a single server model with no queue and exponential services times, in which service is only provided during a certain time interval. A number of customers wish to obtain this service and can choose their arrival time. A customer that finds a busy server leaves without being served. We model this scenario as a non-cooperative game in which the customers wish to maximize their probability of obtaining service. We characterize the Nash equilibrium and the price of anarchy, which is defined as the ratio between the optimal and equilibrium social utility. In particular, the equilibrium arrival distribution has an atom at zero, a period with no arrival and is continuous on some interval until the closing time. We further generalize our analysis to take into account uncertainty regarding the population size, i.e. a game with a random number of customers. In the special case where the population size follows a Poisson distribution, we show that the continuous part of the distribution is uniform, which is not the case in general. Finally, we show that the price of anarchy is not monotone with respect to the population size; but rather uni-modal with values close to one for small and large populations.",moshe haviv,Statistics,2014.0,,"2014 7th International Conference on NETwork Games, COntrol and OPtimization (NetGCoop)",Ravner2014,False,,IEEE,Not available,Equilibrium and socially optimal arrivals to a single server loss system,dbb596e13a10cf149f4fa320d9cc1114,https://ieeexplore.ieee.org/document/7943402/
3660,"We study a single server model with no queue and exponential services times, in which service is only provided during a certain time interval. A number of customers wish to obtain this service and can choose their arrival time. A customer that finds a busy server leaves without being served. We model this scenario as a non-cooperative game in which the customers wish to maximize their probability of obtaining service. We characterize the Nash equilibrium and the price of anarchy, which is defined as the ratio between the optimal and equilibrium social utility. In particular, the equilibrium arrival distribution has an atom at zero, a period with no arrival and is continuous on some interval until the closing time. We further generalize our analysis to take into account uncertainty regarding the population size, i.e. a game with a random number of customers. In the special case where the population size follows a Poisson distribution, we show that the continuous part of the distribution is uniform, which is not the case in general. Finally, we show that the price of anarchy is not monotone with respect to the population size; but rather uni-modal with values close to one for small and large populations.",moshe haviv,Analytical models,2014.0,,"2014 7th International Conference on NETwork Games, COntrol and OPtimization (NetGCoop)",Ravner2014,False,,IEEE,Not available,Equilibrium and socially optimal arrivals to a single server loss system,dbb596e13a10cf149f4fa320d9cc1114,https://ieeexplore.ieee.org/document/7943402/
3661,"We study a single server model with no queue and exponential services times, in which service is only provided during a certain time interval. A number of customers wish to obtain this service and can choose their arrival time. A customer that finds a busy server leaves without being served. We model this scenario as a non-cooperative game in which the customers wish to maximize their probability of obtaining service. We characterize the Nash equilibrium and the price of anarchy, which is defined as the ratio between the optimal and equilibrium social utility. In particular, the equilibrium arrival distribution has an atom at zero, a period with no arrival and is continuous on some interval until the closing time. We further generalize our analysis to take into account uncertainty regarding the population size, i.e. a game with a random number of customers. In the special case where the population size follows a Poisson distribution, we show that the continuous part of the distribution is uniform, which is not the case in general. Finally, we show that the price of anarchy is not monotone with respect to the population size; but rather uni-modal with values close to one for small and large populations.",moshe haviv,Nash equilibrium,2014.0,,"2014 7th International Conference on NETwork Games, COntrol and OPtimization (NetGCoop)",Ravner2014,False,,IEEE,Not available,Equilibrium and socially optimal arrivals to a single server loss system,dbb596e13a10cf149f4fa320d9cc1114,https://ieeexplore.ieee.org/document/7943402/
3662,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
3663,"We study a single server model with no queue and exponential services times, in which service is only provided during a certain time interval. A number of customers wish to obtain this service and can choose their arrival time. A customer that finds a busy server leaves without being served. We model this scenario as a non-cooperative game in which the customers wish to maximize their probability of obtaining service. We characterize the Nash equilibrium and the price of anarchy, which is defined as the ratio between the optimal and equilibrium social utility. In particular, the equilibrium arrival distribution has an atom at zero, a period with no arrival and is continuous on some interval until the closing time. We further generalize our analysis to take into account uncertainty regarding the population size, i.e. a game with a random number of customers. In the special case where the population size follows a Poisson distribution, we show that the continuous part of the distribution is uniform, which is not the case in general. Finally, we show that the price of anarchy is not monotone with respect to the population size; but rather uni-modal with values close to one for small and large populations.",moshe haviv,Optimization,2014.0,,"2014 7th International Conference on NETwork Games, COntrol and OPtimization (NetGCoop)",Ravner2014,False,,IEEE,Not available,Equilibrium and socially optimal arrivals to a single server loss system,dbb596e13a10cf149f4fa320d9cc1114,https://ieeexplore.ieee.org/document/7943402/
3664,"In this paper we consider the problem of distributed channel allocation in large networks under the frequency-selective interference channel. Performance is measured by the weighted sum of achievable rates. First we present a natural non-cooperative game theoretic formulation for this problem. It is shown that, when interference is sufficiently strong, this game has a pure price of anarchy approaching infinity with high probability, and there is an asymptotically increasing number of equilibria with the worst performance. Then we propose a novel non-cooperative M Frequency-Selective Interference Game (M-FSIG), where users limit their utility such that it is greater than zero only for their M best channels, and equal for them. We show that the M-FSIG exhibits, with high probability, an increasing number of optimal pure Nash equilibria and no bad equilibria. Consequently, the pure price of anarchy converges to one in probability in any interference regime. In order to exploit these results algorithmically we propose a modified Fictitious Play algorithm that can be implemented distributedly. We carry out simulations that show its fast convergence to the proven pure Nash equilibria.",ilai bistritz,Interference,2015.0,10.1109/ALLERTON.2015.7447154,"2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Bistritz2015,False,,IEEE,Not available,Asymptotically optimal distributed channel allocation: A competitive game-theoretic approach,e540851e38f0fb631a26e8e7c82dad36,https://ieeexplore.ieee.org/document/7447154/
3665,"In this paper we consider the problem of distributed channel allocation in large networks under the frequency-selective interference channel. Performance is measured by the weighted sum of achievable rates. First we present a natural non-cooperative game theoretic formulation for this problem. It is shown that, when interference is sufficiently strong, this game has a pure price of anarchy approaching infinity with high probability, and there is an asymptotically increasing number of equilibria with the worst performance. Then we propose a novel non-cooperative M Frequency-Selective Interference Game (M-FSIG), where users limit their utility such that it is greater than zero only for their M best channels, and equal for them. We show that the M-FSIG exhibits, with high probability, an increasing number of optimal pure Nash equilibria and no bad equilibria. Consequently, the pure price of anarchy converges to one in probability in any interference regime. In order to exploit these results algorithmically we propose a modified Fictitious Play algorithm that can be implemented distributedly. We carry out simulations that show its fast convergence to the proven pure Nash equilibria.",ilai bistritz,Games,2015.0,10.1109/ALLERTON.2015.7447154,"2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Bistritz2015,False,,IEEE,Not available,Asymptotically optimal distributed channel allocation: A competitive game-theoretic approach,e540851e38f0fb631a26e8e7c82dad36,https://ieeexplore.ieee.org/document/7447154/
3666,"In this paper we consider the problem of distributed channel allocation in large networks under the frequency-selective interference channel. Performance is measured by the weighted sum of achievable rates. First we present a natural non-cooperative game theoretic formulation for this problem. It is shown that, when interference is sufficiently strong, this game has a pure price of anarchy approaching infinity with high probability, and there is an asymptotically increasing number of equilibria with the worst performance. Then we propose a novel non-cooperative M Frequency-Selective Interference Game (M-FSIG), where users limit their utility such that it is greater than zero only for their M best channels, and equal for them. We show that the M-FSIG exhibits, with high probability, an increasing number of optimal pure Nash equilibria and no bad equilibria. Consequently, the pure price of anarchy converges to one in probability in any interference regime. In order to exploit these results algorithmically we propose a modified Fictitious Play algorithm that can be implemented distributedly. We carry out simulations that show its fast convergence to the proven pure Nash equilibria.",ilai bistritz,Channel allocation,2015.0,10.1109/ALLERTON.2015.7447154,"2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Bistritz2015,False,,IEEE,Not available,Asymptotically optimal distributed channel allocation: A competitive game-theoretic approach,e540851e38f0fb631a26e8e7c82dad36,https://ieeexplore.ieee.org/document/7447154/
3667,"In this paper we consider the problem of distributed channel allocation in large networks under the frequency-selective interference channel. Performance is measured by the weighted sum of achievable rates. First we present a natural non-cooperative game theoretic formulation for this problem. It is shown that, when interference is sufficiently strong, this game has a pure price of anarchy approaching infinity with high probability, and there is an asymptotically increasing number of equilibria with the worst performance. Then we propose a novel non-cooperative M Frequency-Selective Interference Game (M-FSIG), where users limit their utility such that it is greater than zero only for their M best channels, and equal for them. We show that the M-FSIG exhibits, with high probability, an increasing number of optimal pure Nash equilibria and no bad equilibria. Consequently, the pure price of anarchy converges to one in probability in any interference regime. In order to exploit these results algorithmically we propose a modified Fictitious Play algorithm that can be implemented distributedly. We carry out simulations that show its fast convergence to the proven pure Nash equilibria.",ilai bistritz,Receivers,2015.0,10.1109/ALLERTON.2015.7447154,"2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Bistritz2015,False,,IEEE,Not available,Asymptotically optimal distributed channel allocation: A competitive game-theoretic approach,e540851e38f0fb631a26e8e7c82dad36,https://ieeexplore.ieee.org/document/7447154/
3668,"In this paper we consider the problem of distributed channel allocation in large networks under the frequency-selective interference channel. Performance is measured by the weighted sum of achievable rates. First we present a natural non-cooperative game theoretic formulation for this problem. It is shown that, when interference is sufficiently strong, this game has a pure price of anarchy approaching infinity with high probability, and there is an asymptotically increasing number of equilibria with the worst performance. Then we propose a novel non-cooperative M Frequency-Selective Interference Game (M-FSIG), where users limit their utility such that it is greater than zero only for their M best channels, and equal for them. We show that the M-FSIG exhibits, with high probability, an increasing number of optimal pure Nash equilibria and no bad equilibria. Consequently, the pure price of anarchy converges to one in probability in any interference regime. In order to exploit these results algorithmically we propose a modified Fictitious Play algorithm that can be implemented distributedly. We carry out simulations that show its fast convergence to the proven pure Nash equilibria.",ilai bistritz,Algorithm design and analysis,2015.0,10.1109/ALLERTON.2015.7447154,"2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Bistritz2015,False,,IEEE,Not available,Asymptotically optimal distributed channel allocation: A competitive game-theoretic approach,e540851e38f0fb631a26e8e7c82dad36,https://ieeexplore.ieee.org/document/7447154/
3669,"In this paper we consider the problem of distributed channel allocation in large networks under the frequency-selective interference channel. Performance is measured by the weighted sum of achievable rates. First we present a natural non-cooperative game theoretic formulation for this problem. It is shown that, when interference is sufficiently strong, this game has a pure price of anarchy approaching infinity with high probability, and there is an asymptotically increasing number of equilibria with the worst performance. Then we propose a novel non-cooperative M Frequency-Selective Interference Game (M-FSIG), where users limit their utility such that it is greater than zero only for their M best channels, and equal for them. We show that the M-FSIG exhibits, with high probability, an increasing number of optimal pure Nash equilibria and no bad equilibria. Consequently, the pure price of anarchy converges to one in probability in any interference regime. In order to exploit these results algorithmically we propose a modified Fictitious Play algorithm that can be implemented distributedly. We carry out simulations that show its fast convergence to the proven pure Nash equilibria.",ilai bistritz,Resource management,2015.0,10.1109/ALLERTON.2015.7447154,"2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Bistritz2015,False,,IEEE,Not available,Asymptotically optimal distributed channel allocation: A competitive game-theoretic approach,e540851e38f0fb631a26e8e7c82dad36,https://ieeexplore.ieee.org/document/7447154/
3670,"In this paper we consider the problem of distributed channel allocation in large networks under the frequency-selective interference channel. Performance is measured by the weighted sum of achievable rates. First we present a natural non-cooperative game theoretic formulation for this problem. It is shown that, when interference is sufficiently strong, this game has a pure price of anarchy approaching infinity with high probability, and there is an asymptotically increasing number of equilibria with the worst performance. Then we propose a novel non-cooperative M Frequency-Selective Interference Game (M-FSIG), where users limit their utility such that it is greater than zero only for their M best channels, and equal for them. We show that the M-FSIG exhibits, with high probability, an increasing number of optimal pure Nash equilibria and no bad equilibria. Consequently, the pure price of anarchy converges to one in probability in any interference regime. In order to exploit these results algorithmically we propose a modified Fictitious Play algorithm that can be implemented distributedly. We carry out simulations that show its fast convergence to the proven pure Nash equilibria.",ilai bistritz,Transmitters,2015.0,10.1109/ALLERTON.2015.7447154,"2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Bistritz2015,False,,IEEE,Not available,Asymptotically optimal distributed channel allocation: A competitive game-theoretic approach,e540851e38f0fb631a26e8e7c82dad36,https://ieeexplore.ieee.org/document/7447154/
3671,"In this paper we consider the problem of distributed channel allocation in large networks under the frequency-selective interference channel. Performance is measured by the weighted sum of achievable rates. First we present a natural non-cooperative game theoretic formulation for this problem. It is shown that, when interference is sufficiently strong, this game has a pure price of anarchy approaching infinity with high probability, and there is an asymptotically increasing number of equilibria with the worst performance. Then we propose a novel non-cooperative M Frequency-Selective Interference Game (M-FSIG), where users limit their utility such that it is greater than zero only for their M best channels, and equal for them. We show that the M-FSIG exhibits, with high probability, an increasing number of optimal pure Nash equilibria and no bad equilibria. Consequently, the pure price of anarchy converges to one in probability in any interference regime. In order to exploit these results algorithmically we propose a modified Fictitious Play algorithm that can be implemented distributedly. We carry out simulations that show its fast convergence to the proven pure Nash equilibria.",amir leshem,Interference,2015.0,10.1109/ALLERTON.2015.7447154,"2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Bistritz2015,False,,IEEE,Not available,Asymptotically optimal distributed channel allocation: A competitive game-theoretic approach,e540851e38f0fb631a26e8e7c82dad36,https://ieeexplore.ieee.org/document/7447154/
3672,"In this paper we consider the problem of distributed channel allocation in large networks under the frequency-selective interference channel. Performance is measured by the weighted sum of achievable rates. First we present a natural non-cooperative game theoretic formulation for this problem. It is shown that, when interference is sufficiently strong, this game has a pure price of anarchy approaching infinity with high probability, and there is an asymptotically increasing number of equilibria with the worst performance. Then we propose a novel non-cooperative M Frequency-Selective Interference Game (M-FSIG), where users limit their utility such that it is greater than zero only for their M best channels, and equal for them. We show that the M-FSIG exhibits, with high probability, an increasing number of optimal pure Nash equilibria and no bad equilibria. Consequently, the pure price of anarchy converges to one in probability in any interference regime. In order to exploit these results algorithmically we propose a modified Fictitious Play algorithm that can be implemented distributedly. We carry out simulations that show its fast convergence to the proven pure Nash equilibria.",amir leshem,Games,2015.0,10.1109/ALLERTON.2015.7447154,"2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Bistritz2015,False,,IEEE,Not available,Asymptotically optimal distributed channel allocation: A competitive game-theoretic approach,e540851e38f0fb631a26e8e7c82dad36,https://ieeexplore.ieee.org/document/7447154/
3673,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
3674,"In this paper we consider the problem of distributed channel allocation in large networks under the frequency-selective interference channel. Performance is measured by the weighted sum of achievable rates. First we present a natural non-cooperative game theoretic formulation for this problem. It is shown that, when interference is sufficiently strong, this game has a pure price of anarchy approaching infinity with high probability, and there is an asymptotically increasing number of equilibria with the worst performance. Then we propose a novel non-cooperative M Frequency-Selective Interference Game (M-FSIG), where users limit their utility such that it is greater than zero only for their M best channels, and equal for them. We show that the M-FSIG exhibits, with high probability, an increasing number of optimal pure Nash equilibria and no bad equilibria. Consequently, the pure price of anarchy converges to one in probability in any interference regime. In order to exploit these results algorithmically we propose a modified Fictitious Play algorithm that can be implemented distributedly. We carry out simulations that show its fast convergence to the proven pure Nash equilibria.",amir leshem,Channel allocation,2015.0,10.1109/ALLERTON.2015.7447154,"2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Bistritz2015,False,,IEEE,Not available,Asymptotically optimal distributed channel allocation: A competitive game-theoretic approach,e540851e38f0fb631a26e8e7c82dad36,https://ieeexplore.ieee.org/document/7447154/
3675,"In this paper we consider the problem of distributed channel allocation in large networks under the frequency-selective interference channel. Performance is measured by the weighted sum of achievable rates. First we present a natural non-cooperative game theoretic formulation for this problem. It is shown that, when interference is sufficiently strong, this game has a pure price of anarchy approaching infinity with high probability, and there is an asymptotically increasing number of equilibria with the worst performance. Then we propose a novel non-cooperative M Frequency-Selective Interference Game (M-FSIG), where users limit their utility such that it is greater than zero only for their M best channels, and equal for them. We show that the M-FSIG exhibits, with high probability, an increasing number of optimal pure Nash equilibria and no bad equilibria. Consequently, the pure price of anarchy converges to one in probability in any interference regime. In order to exploit these results algorithmically we propose a modified Fictitious Play algorithm that can be implemented distributedly. We carry out simulations that show its fast convergence to the proven pure Nash equilibria.",amir leshem,Receivers,2015.0,10.1109/ALLERTON.2015.7447154,"2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Bistritz2015,False,,IEEE,Not available,Asymptotically optimal distributed channel allocation: A competitive game-theoretic approach,e540851e38f0fb631a26e8e7c82dad36,https://ieeexplore.ieee.org/document/7447154/
3676,"In this paper we consider the problem of distributed channel allocation in large networks under the frequency-selective interference channel. Performance is measured by the weighted sum of achievable rates. First we present a natural non-cooperative game theoretic formulation for this problem. It is shown that, when interference is sufficiently strong, this game has a pure price of anarchy approaching infinity with high probability, and there is an asymptotically increasing number of equilibria with the worst performance. Then we propose a novel non-cooperative M Frequency-Selective Interference Game (M-FSIG), where users limit their utility such that it is greater than zero only for their M best channels, and equal for them. We show that the M-FSIG exhibits, with high probability, an increasing number of optimal pure Nash equilibria and no bad equilibria. Consequently, the pure price of anarchy converges to one in probability in any interference regime. In order to exploit these results algorithmically we propose a modified Fictitious Play algorithm that can be implemented distributedly. We carry out simulations that show its fast convergence to the proven pure Nash equilibria.",amir leshem,Algorithm design and analysis,2015.0,10.1109/ALLERTON.2015.7447154,"2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Bistritz2015,False,,IEEE,Not available,Asymptotically optimal distributed channel allocation: A competitive game-theoretic approach,e540851e38f0fb631a26e8e7c82dad36,https://ieeexplore.ieee.org/document/7447154/
3677,"In this paper we consider the problem of distributed channel allocation in large networks under the frequency-selective interference channel. Performance is measured by the weighted sum of achievable rates. First we present a natural non-cooperative game theoretic formulation for this problem. It is shown that, when interference is sufficiently strong, this game has a pure price of anarchy approaching infinity with high probability, and there is an asymptotically increasing number of equilibria with the worst performance. Then we propose a novel non-cooperative M Frequency-Selective Interference Game (M-FSIG), where users limit their utility such that it is greater than zero only for their M best channels, and equal for them. We show that the M-FSIG exhibits, with high probability, an increasing number of optimal pure Nash equilibria and no bad equilibria. Consequently, the pure price of anarchy converges to one in probability in any interference regime. In order to exploit these results algorithmically we propose a modified Fictitious Play algorithm that can be implemented distributedly. We carry out simulations that show its fast convergence to the proven pure Nash equilibria.",amir leshem,Resource management,2015.0,10.1109/ALLERTON.2015.7447154,"2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Bistritz2015,False,,IEEE,Not available,Asymptotically optimal distributed channel allocation: A competitive game-theoretic approach,e540851e38f0fb631a26e8e7c82dad36,https://ieeexplore.ieee.org/document/7447154/
3678,"In this paper we consider the problem of distributed channel allocation in large networks under the frequency-selective interference channel. Performance is measured by the weighted sum of achievable rates. First we present a natural non-cooperative game theoretic formulation for this problem. It is shown that, when interference is sufficiently strong, this game has a pure price of anarchy approaching infinity with high probability, and there is an asymptotically increasing number of equilibria with the worst performance. Then we propose a novel non-cooperative M Frequency-Selective Interference Game (M-FSIG), where users limit their utility such that it is greater than zero only for their M best channels, and equal for them. We show that the M-FSIG exhibits, with high probability, an increasing number of optimal pure Nash equilibria and no bad equilibria. Consequently, the pure price of anarchy converges to one in probability in any interference regime. In order to exploit these results algorithmically we propose a modified Fictitious Play algorithm that can be implemented distributedly. We carry out simulations that show its fast convergence to the proven pure Nash equilibria.",amir leshem,Transmitters,2015.0,10.1109/ALLERTON.2015.7447154,"2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Bistritz2015,False,,IEEE,Not available,Asymptotically optimal distributed channel allocation: A competitive game-theoretic approach,e540851e38f0fb631a26e8e7c82dad36,https://ieeexplore.ieee.org/document/7447154/
3679,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",chandra chekuri,Nash equilibrium,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3680,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",chandra chekuri,Costs,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3681,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",chandra chekuri,Routing,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3682,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",chandra chekuri,Delay,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3683,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",chandra chekuri,Computer science,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3684,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
3685,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",chandra chekuri,Joining processes,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3686,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",chandra chekuri,Computational complexity,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3687,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",chandra chekuri,Upper bound,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3688,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",chandra chekuri,Polynomials,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3689,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",chandra chekuri,Multicast algorithms,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3690,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",julia chuzhoy,Nash equilibrium,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3691,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",julia chuzhoy,Costs,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3692,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",julia chuzhoy,Routing,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3693,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",julia chuzhoy,Delay,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3694,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",julia chuzhoy,Computer science,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3695,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
3696,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",julia chuzhoy,Joining processes,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3697,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",julia chuzhoy,Computational complexity,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3698,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",julia chuzhoy,Upper bound,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3699,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",julia chuzhoy,Polynomials,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3700,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",julia chuzhoy,Multicast algorithms,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3701,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",liane lewin-eytan,Nash equilibrium,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3702,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",liane lewin-eytan,Costs,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3703,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",liane lewin-eytan,Routing,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3704,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",liane lewin-eytan,Delay,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3705,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",liane lewin-eytan,Computer science,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3706,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
3707,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",liane lewin-eytan,Joining processes,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3708,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",liane lewin-eytan,Computational complexity,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3709,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",liane lewin-eytan,Upper bound,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3710,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",liane lewin-eytan,Polynomials,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3711,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",liane lewin-eytan,Multicast algorithms,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3712,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",joseph naor,Nash equilibrium,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3713,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",joseph naor,Costs,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3714,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",joseph naor,Routing,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3715,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",joseph naor,Delay,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3716,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",joseph naor,Computer science,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3717,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
3718,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",joseph naor,Joining processes,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3719,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",joseph naor,Computational complexity,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3720,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",joseph naor,Upper bound,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3721,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",joseph naor,Polynomials,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3722,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",joseph naor,Multicast algorithms,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3723,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",ariel orda,Nash equilibrium,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3724,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",ariel orda,Costs,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3725,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",ariel orda,Routing,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3726,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",ariel orda,Delay,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3727,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",ariel orda,Computer science,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3728,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
3729,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",ariel orda,Joining processes,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3730,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",ariel orda,Computational complexity,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3731,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",ariel orda,Upper bound,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3732,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",ariel orda,Polynomials,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3733,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",ariel orda,Multicast algorithms,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
3734,"Offloading computation to a mobile cloud is a promising solution to augment the computation capabilities of mobile devices. In this paper we consider selfish mobile devices in a dense wireless network, in which individual mobile devices can offload computations through multiple access points or through the base station to a mobile cloud so as to minimize their computation costs. We provide a game theoretical analysis of the problem, prove the existence of pure strategy Nash equilibria, and provide an efficient decentralized algorithm for computing an equilibrium. For the case when the cloud computing resources scale with the number of mobile devices we show that all improvement paths are finite. Furthermore, we provide an upper bound on the price of anarchy of the game, which serves as an upper bound on the approximation ratio of the proposed decentralized algorithms. We use simulations to evaluate the time complexity of computing Nash equilibria and to provide insights into the price of anarchy of the game under realistic scenarios. Our results show that the equilibrium cost may be close to optimal, and the convergence time is almost linear in the number of mobile devices.",sla&#x0111;ana jo&#x0161;ilo,computation offloading,,10.1109/TMC.2018.2829874,IEEE Transactions on Mobile Computing,Jo&#x0161;iloNone,False,,IEEE,Not available,Selfish Decentralized Computation Offloading for Mobile Cloud Computing in Dense Wireless Networks,0a9c0b8fbd74714739bfd0aa25fadff1,
3735,"Offloading computation to a mobile cloud is a promising solution to augment the computation capabilities of mobile devices. In this paper we consider selfish mobile devices in a dense wireless network, in which individual mobile devices can offload computations through multiple access points or through the base station to a mobile cloud so as to minimize their computation costs. We provide a game theoretical analysis of the problem, prove the existence of pure strategy Nash equilibria, and provide an efficient decentralized algorithm for computing an equilibrium. For the case when the cloud computing resources scale with the number of mobile devices we show that all improvement paths are finite. Furthermore, we provide an upper bound on the price of anarchy of the game, which serves as an upper bound on the approximation ratio of the proposed decentralized algorithms. We use simulations to evaluate the time complexity of computing Nash equilibria and to provide insights into the price of anarchy of the game under realistic scenarios. Our results show that the equilibrium cost may be close to optimal, and the convergence time is almost linear in the number of mobile devices.",sla&#x0111;ana jo&#x0161;ilo,mobile edge computing,,10.1109/TMC.2018.2829874,IEEE Transactions on Mobile Computing,Jo&#x0161;iloNone,False,,IEEE,Not available,Selfish Decentralized Computation Offloading for Mobile Cloud Computing in Dense Wireless Networks,0a9c0b8fbd74714739bfd0aa25fadff1,
3736,"Offloading computation to a mobile cloud is a promising solution to augment the computation capabilities of mobile devices. In this paper we consider selfish mobile devices in a dense wireless network, in which individual mobile devices can offload computations through multiple access points or through the base station to a mobile cloud so as to minimize their computation costs. We provide a game theoretical analysis of the problem, prove the existence of pure strategy Nash equilibria, and provide an efficient decentralized algorithm for computing an equilibrium. For the case when the cloud computing resources scale with the number of mobile devices we show that all improvement paths are finite. Furthermore, we provide an upper bound on the price of anarchy of the game, which serves as an upper bound on the approximation ratio of the proposed decentralized algorithms. We use simulations to evaluate the time complexity of computing Nash equilibria and to provide insights into the price of anarchy of the game under realistic scenarios. Our results show that the equilibrium cost may be close to optimal, and the convergence time is almost linear in the number of mobile devices.",sla&#x0111;ana jo&#x0161;ilo,Nash equilibria,,10.1109/TMC.2018.2829874,IEEE Transactions on Mobile Computing,Jo&#x0161;iloNone,False,,IEEE,Not available,Selfish Decentralized Computation Offloading for Mobile Cloud Computing in Dense Wireless Networks,0a9c0b8fbd74714739bfd0aa25fadff1,
3737,"Offloading computation to a mobile cloud is a promising solution to augment the computation capabilities of mobile devices. In this paper we consider selfish mobile devices in a dense wireless network, in which individual mobile devices can offload computations through multiple access points or through the base station to a mobile cloud so as to minimize their computation costs. We provide a game theoretical analysis of the problem, prove the existence of pure strategy Nash equilibria, and provide an efficient decentralized algorithm for computing an equilibrium. For the case when the cloud computing resources scale with the number of mobile devices we show that all improvement paths are finite. Furthermore, we provide an upper bound on the price of anarchy of the game, which serves as an upper bound on the approximation ratio of the proposed decentralized algorithms. We use simulations to evaluate the time complexity of computing Nash equilibria and to provide insights into the price of anarchy of the game under realistic scenarios. Our results show that the equilibrium cost may be close to optimal, and the convergence time is almost linear in the number of mobile devices.",sla&#x0111;ana jo&#x0161;ilo,decentralized algorithms,,10.1109/TMC.2018.2829874,IEEE Transactions on Mobile Computing,Jo&#x0161;iloNone,False,,IEEE,Not available,Selfish Decentralized Computation Offloading for Mobile Cloud Computing in Dense Wireless Networks,0a9c0b8fbd74714739bfd0aa25fadff1,
3738,"Offloading computation to a mobile cloud is a promising solution to augment the computation capabilities of mobile devices. In this paper we consider selfish mobile devices in a dense wireless network, in which individual mobile devices can offload computations through multiple access points or through the base station to a mobile cloud so as to minimize their computation costs. We provide a game theoretical analysis of the problem, prove the existence of pure strategy Nash equilibria, and provide an efficient decentralized algorithm for computing an equilibrium. For the case when the cloud computing resources scale with the number of mobile devices we show that all improvement paths are finite. Furthermore, we provide an upper bound on the price of anarchy of the game, which serves as an upper bound on the approximation ratio of the proposed decentralized algorithms. We use simulations to evaluate the time complexity of computing Nash equilibria and to provide insights into the price of anarchy of the game under realistic scenarios. Our results show that the equilibrium cost may be close to optimal, and the convergence time is almost linear in the number of mobile devices.",gyorgy dan,computation offloading,,10.1109/TMC.2018.2829874,IEEE Transactions on Mobile Computing,Jo&#x0161;iloNone,False,,IEEE,Not available,Selfish Decentralized Computation Offloading for Mobile Cloud Computing in Dense Wireless Networks,0a9c0b8fbd74714739bfd0aa25fadff1,
3739,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
3740,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
3741,"Offloading computation to a mobile cloud is a promising solution to augment the computation capabilities of mobile devices. In this paper we consider selfish mobile devices in a dense wireless network, in which individual mobile devices can offload computations through multiple access points or through the base station to a mobile cloud so as to minimize their computation costs. We provide a game theoretical analysis of the problem, prove the existence of pure strategy Nash equilibria, and provide an efficient decentralized algorithm for computing an equilibrium. For the case when the cloud computing resources scale with the number of mobile devices we show that all improvement paths are finite. Furthermore, we provide an upper bound on the price of anarchy of the game, which serves as an upper bound on the approximation ratio of the proposed decentralized algorithms. We use simulations to evaluate the time complexity of computing Nash equilibria and to provide insights into the price of anarchy of the game under realistic scenarios. Our results show that the equilibrium cost may be close to optimal, and the convergence time is almost linear in the number of mobile devices.",gyorgy dan,mobile edge computing,,10.1109/TMC.2018.2829874,IEEE Transactions on Mobile Computing,Jo&#x0161;iloNone,False,,IEEE,Not available,Selfish Decentralized Computation Offloading for Mobile Cloud Computing in Dense Wireless Networks,0a9c0b8fbd74714739bfd0aa25fadff1,
3742,"Offloading computation to a mobile cloud is a promising solution to augment the computation capabilities of mobile devices. In this paper we consider selfish mobile devices in a dense wireless network, in which individual mobile devices can offload computations through multiple access points or through the base station to a mobile cloud so as to minimize their computation costs. We provide a game theoretical analysis of the problem, prove the existence of pure strategy Nash equilibria, and provide an efficient decentralized algorithm for computing an equilibrium. For the case when the cloud computing resources scale with the number of mobile devices we show that all improvement paths are finite. Furthermore, we provide an upper bound on the price of anarchy of the game, which serves as an upper bound on the approximation ratio of the proposed decentralized algorithms. We use simulations to evaluate the time complexity of computing Nash equilibria and to provide insights into the price of anarchy of the game under realistic scenarios. Our results show that the equilibrium cost may be close to optimal, and the convergence time is almost linear in the number of mobile devices.",gyorgy dan,Nash equilibria,,10.1109/TMC.2018.2829874,IEEE Transactions on Mobile Computing,Jo&#x0161;iloNone,False,,IEEE,Not available,Selfish Decentralized Computation Offloading for Mobile Cloud Computing in Dense Wireless Networks,0a9c0b8fbd74714739bfd0aa25fadff1,
3743,"Offloading computation to a mobile cloud is a promising solution to augment the computation capabilities of mobile devices. In this paper we consider selfish mobile devices in a dense wireless network, in which individual mobile devices can offload computations through multiple access points or through the base station to a mobile cloud so as to minimize their computation costs. We provide a game theoretical analysis of the problem, prove the existence of pure strategy Nash equilibria, and provide an efficient decentralized algorithm for computing an equilibrium. For the case when the cloud computing resources scale with the number of mobile devices we show that all improvement paths are finite. Furthermore, we provide an upper bound on the price of anarchy of the game, which serves as an upper bound on the approximation ratio of the proposed decentralized algorithms. We use simulations to evaluate the time complexity of computing Nash equilibria and to provide insights into the price of anarchy of the game under realistic scenarios. Our results show that the equilibrium cost may be close to optimal, and the convergence time is almost linear in the number of mobile devices.",gyorgy dan,decentralized algorithms,,10.1109/TMC.2018.2829874,IEEE Transactions on Mobile Computing,Jo&#x0161;iloNone,False,,IEEE,Not available,Selfish Decentralized Computation Offloading for Mobile Cloud Computing in Dense Wireless Networks,0a9c0b8fbd74714739bfd0aa25fadff1,
3744,"Contention among users utilizing a single shared resource arises in multiple contexts of computing and computer communications. We consider a setup in which users can split their work between a shared resource and a private resource. Unlike the private resource, which provides guaranteed performance, the performance of the shared resource is highly dependent on the usage pattern of other users, which in turn influences a user's decision if and to what extent to make use of the shared resource. The intrinsic relation between the utility that a user perceives from the shared resource and the usage pattern followed by other users gives rise to a noncooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the ratio between the worst Nash equilibrium and the social optimum, known as the “price of anarchy,” and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the price of anarchy can be arbitrarily large. We demonstrate that, somewhat counterintuitively, exercising admission control to the shared resource may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the shared resource to a wide range of user types.",amir nahir,Analytical models,2015.0,10.1109/TNET.2014.2354572,IEEE/ACM Transactions on Networking,Nahir2015,False,,IEEE,Not available,Workload Factoring: A Game-Theoretic Perspective,759722e4368fa23983f8764c742ab847,https://ieeexplore.ieee.org/document/6901301/
3745,"Contention among users utilizing a single shared resource arises in multiple contexts of computing and computer communications. We consider a setup in which users can split their work between a shared resource and a private resource. Unlike the private resource, which provides guaranteed performance, the performance of the shared resource is highly dependent on the usage pattern of other users, which in turn influences a user's decision if and to what extent to make use of the shared resource. The intrinsic relation between the utility that a user perceives from the shared resource and the usage pattern followed by other users gives rise to a noncooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the ratio between the worst Nash equilibrium and the social optimum, known as the “price of anarchy,” and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the price of anarchy can be arbitrarily large. We demonstrate that, somewhat counterintuitively, exercising admission control to the shared resource may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the shared resource to a wide range of user types.",amir nahir,modeling,2015.0,10.1109/TNET.2014.2354572,IEEE/ACM Transactions on Networking,Nahir2015,False,,IEEE,Not available,Workload Factoring: A Game-Theoretic Perspective,759722e4368fa23983f8764c742ab847,https://ieeexplore.ieee.org/document/6901301/
3746,"Contention among users utilizing a single shared resource arises in multiple contexts of computing and computer communications. We consider a setup in which users can split their work between a shared resource and a private resource. Unlike the private resource, which provides guaranteed performance, the performance of the shared resource is highly dependent on the usage pattern of other users, which in turn influences a user's decision if and to what extent to make use of the shared resource. The intrinsic relation between the utility that a user perceives from the shared resource and the usage pattern followed by other users gives rise to a noncooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the ratio between the worst Nash equilibrium and the social optimum, known as the “price of anarchy,” and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the price of anarchy can be arbitrarily large. We demonstrate that, somewhat counterintuitively, exercising admission control to the shared resource may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the shared resource to a wide range of user types.",amir nahir,system analysis and design,2015.0,10.1109/TNET.2014.2354572,IEEE/ACM Transactions on Networking,Nahir2015,False,,IEEE,Not available,Workload Factoring: A Game-Theoretic Perspective,759722e4368fa23983f8764c742ab847,https://ieeexplore.ieee.org/document/6901301/
3747,"Contention among users utilizing a single shared resource arises in multiple contexts of computing and computer communications. We consider a setup in which users can split their work between a shared resource and a private resource. Unlike the private resource, which provides guaranteed performance, the performance of the shared resource is highly dependent on the usage pattern of other users, which in turn influences a user's decision if and to what extent to make use of the shared resource. The intrinsic relation between the utility that a user perceives from the shared resource and the usage pattern followed by other users gives rise to a noncooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the ratio between the worst Nash equilibrium and the social optimum, known as the “price of anarchy,” and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the price of anarchy can be arbitrarily large. We demonstrate that, somewhat counterintuitively, exercising admission control to the shared resource may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the shared resource to a wide range of user types.",amir nahir,system performance,2015.0,10.1109/TNET.2014.2354572,IEEE/ACM Transactions on Networking,Nahir2015,False,,IEEE,Not available,Workload Factoring: A Game-Theoretic Perspective,759722e4368fa23983f8764c742ab847,https://ieeexplore.ieee.org/document/6901301/
3748,"Contention among users utilizing a single shared resource arises in multiple contexts of computing and computer communications. We consider a setup in which users can split their work between a shared resource and a private resource. Unlike the private resource, which provides guaranteed performance, the performance of the shared resource is highly dependent on the usage pattern of other users, which in turn influences a user's decision if and to what extent to make use of the shared resource. The intrinsic relation between the utility that a user perceives from the shared resource and the usage pattern followed by other users gives rise to a noncooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the ratio between the worst Nash equilibrium and the social optimum, known as the “price of anarchy,” and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the price of anarchy can be arbitrarily large. We demonstrate that, somewhat counterintuitively, exercising admission control to the shared resource may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the shared resource to a wide range of user types.",amir nahir,systems engineering and theory,2015.0,10.1109/TNET.2014.2354572,IEEE/ACM Transactions on Networking,Nahir2015,False,,IEEE,Not available,Workload Factoring: A Game-Theoretic Perspective,759722e4368fa23983f8764c742ab847,https://ieeexplore.ieee.org/document/6901301/
3749,"Contention among users utilizing a single shared resource arises in multiple contexts of computing and computer communications. We consider a setup in which users can split their work between a shared resource and a private resource. Unlike the private resource, which provides guaranteed performance, the performance of the shared resource is highly dependent on the usage pattern of other users, which in turn influences a user's decision if and to what extent to make use of the shared resource. The intrinsic relation between the utility that a user perceives from the shared resource and the usage pattern followed by other users gives rise to a noncooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the ratio between the worst Nash equilibrium and the social optimum, known as the “price of anarchy,” and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the price of anarchy can be arbitrarily large. We demonstrate that, somewhat counterintuitively, exercising admission control to the shared resource may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the shared resource to a wide range of user types.",ariel orda,Analytical models,2015.0,10.1109/TNET.2014.2354572,IEEE/ACM Transactions on Networking,Nahir2015,False,,IEEE,Not available,Workload Factoring: A Game-Theoretic Perspective,759722e4368fa23983f8764c742ab847,https://ieeexplore.ieee.org/document/6901301/
3750,"Contention among users utilizing a single shared resource arises in multiple contexts of computing and computer communications. We consider a setup in which users can split their work between a shared resource and a private resource. Unlike the private resource, which provides guaranteed performance, the performance of the shared resource is highly dependent on the usage pattern of other users, which in turn influences a user's decision if and to what extent to make use of the shared resource. The intrinsic relation between the utility that a user perceives from the shared resource and the usage pattern followed by other users gives rise to a noncooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the ratio between the worst Nash equilibrium and the social optimum, known as the “price of anarchy,” and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the price of anarchy can be arbitrarily large. We demonstrate that, somewhat counterintuitively, exercising admission control to the shared resource may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the shared resource to a wide range of user types.",ariel orda,modeling,2015.0,10.1109/TNET.2014.2354572,IEEE/ACM Transactions on Networking,Nahir2015,False,,IEEE,Not available,Workload Factoring: A Game-Theoretic Perspective,759722e4368fa23983f8764c742ab847,https://ieeexplore.ieee.org/document/6901301/
3751,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
3752,"Contention among users utilizing a single shared resource arises in multiple contexts of computing and computer communications. We consider a setup in which users can split their work between a shared resource and a private resource. Unlike the private resource, which provides guaranteed performance, the performance of the shared resource is highly dependent on the usage pattern of other users, which in turn influences a user's decision if and to what extent to make use of the shared resource. The intrinsic relation between the utility that a user perceives from the shared resource and the usage pattern followed by other users gives rise to a noncooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the ratio between the worst Nash equilibrium and the social optimum, known as the “price of anarchy,” and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the price of anarchy can be arbitrarily large. We demonstrate that, somewhat counterintuitively, exercising admission control to the shared resource may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the shared resource to a wide range of user types.",ariel orda,system analysis and design,2015.0,10.1109/TNET.2014.2354572,IEEE/ACM Transactions on Networking,Nahir2015,False,,IEEE,Not available,Workload Factoring: A Game-Theoretic Perspective,759722e4368fa23983f8764c742ab847,https://ieeexplore.ieee.org/document/6901301/
3753,"Contention among users utilizing a single shared resource arises in multiple contexts of computing and computer communications. We consider a setup in which users can split their work between a shared resource and a private resource. Unlike the private resource, which provides guaranteed performance, the performance of the shared resource is highly dependent on the usage pattern of other users, which in turn influences a user's decision if and to what extent to make use of the shared resource. The intrinsic relation between the utility that a user perceives from the shared resource and the usage pattern followed by other users gives rise to a noncooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the ratio between the worst Nash equilibrium and the social optimum, known as the “price of anarchy,” and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the price of anarchy can be arbitrarily large. We demonstrate that, somewhat counterintuitively, exercising admission control to the shared resource may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the shared resource to a wide range of user types.",ariel orda,system performance,2015.0,10.1109/TNET.2014.2354572,IEEE/ACM Transactions on Networking,Nahir2015,False,,IEEE,Not available,Workload Factoring: A Game-Theoretic Perspective,759722e4368fa23983f8764c742ab847,https://ieeexplore.ieee.org/document/6901301/
3754,"Contention among users utilizing a single shared resource arises in multiple contexts of computing and computer communications. We consider a setup in which users can split their work between a shared resource and a private resource. Unlike the private resource, which provides guaranteed performance, the performance of the shared resource is highly dependent on the usage pattern of other users, which in turn influences a user's decision if and to what extent to make use of the shared resource. The intrinsic relation between the utility that a user perceives from the shared resource and the usage pattern followed by other users gives rise to a noncooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the ratio between the worst Nash equilibrium and the social optimum, known as the “price of anarchy,” and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the price of anarchy can be arbitrarily large. We demonstrate that, somewhat counterintuitively, exercising admission control to the shared resource may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the shared resource to a wide range of user types.",ariel orda,systems engineering and theory,2015.0,10.1109/TNET.2014.2354572,IEEE/ACM Transactions on Networking,Nahir2015,False,,IEEE,Not available,Workload Factoring: A Game-Theoretic Perspective,759722e4368fa23983f8764c742ab847,https://ieeexplore.ieee.org/document/6901301/
3755,"Contention among users utilizing a single shared resource arises in multiple contexts of computing and computer communications. We consider a setup in which users can split their work between a shared resource and a private resource. Unlike the private resource, which provides guaranteed performance, the performance of the shared resource is highly dependent on the usage pattern of other users, which in turn influences a user's decision if and to what extent to make use of the shared resource. The intrinsic relation between the utility that a user perceives from the shared resource and the usage pattern followed by other users gives rise to a noncooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the ratio between the worst Nash equilibrium and the social optimum, known as the “price of anarchy,” and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the price of anarchy can be arbitrarily large. We demonstrate that, somewhat counterintuitively, exercising admission control to the shared resource may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the shared resource to a wide range of user types.",danny raz,Analytical models,2015.0,10.1109/TNET.2014.2354572,IEEE/ACM Transactions on Networking,Nahir2015,False,,IEEE,Not available,Workload Factoring: A Game-Theoretic Perspective,759722e4368fa23983f8764c742ab847,https://ieeexplore.ieee.org/document/6901301/
3756,"Contention among users utilizing a single shared resource arises in multiple contexts of computing and computer communications. We consider a setup in which users can split their work between a shared resource and a private resource. Unlike the private resource, which provides guaranteed performance, the performance of the shared resource is highly dependent on the usage pattern of other users, which in turn influences a user's decision if and to what extent to make use of the shared resource. The intrinsic relation between the utility that a user perceives from the shared resource and the usage pattern followed by other users gives rise to a noncooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the ratio between the worst Nash equilibrium and the social optimum, known as the “price of anarchy,” and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the price of anarchy can be arbitrarily large. We demonstrate that, somewhat counterintuitively, exercising admission control to the shared resource may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the shared resource to a wide range of user types.",danny raz,modeling,2015.0,10.1109/TNET.2014.2354572,IEEE/ACM Transactions on Networking,Nahir2015,False,,IEEE,Not available,Workload Factoring: A Game-Theoretic Perspective,759722e4368fa23983f8764c742ab847,https://ieeexplore.ieee.org/document/6901301/
3757,"Contention among users utilizing a single shared resource arises in multiple contexts of computing and computer communications. We consider a setup in which users can split their work between a shared resource and a private resource. Unlike the private resource, which provides guaranteed performance, the performance of the shared resource is highly dependent on the usage pattern of other users, which in turn influences a user's decision if and to what extent to make use of the shared resource. The intrinsic relation between the utility that a user perceives from the shared resource and the usage pattern followed by other users gives rise to a noncooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the ratio between the worst Nash equilibrium and the social optimum, known as the “price of anarchy,” and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the price of anarchy can be arbitrarily large. We demonstrate that, somewhat counterintuitively, exercising admission control to the shared resource may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the shared resource to a wide range of user types.",danny raz,system analysis and design,2015.0,10.1109/TNET.2014.2354572,IEEE/ACM Transactions on Networking,Nahir2015,False,,IEEE,Not available,Workload Factoring: A Game-Theoretic Perspective,759722e4368fa23983f8764c742ab847,https://ieeexplore.ieee.org/document/6901301/
3758,"Contention among users utilizing a single shared resource arises in multiple contexts of computing and computer communications. We consider a setup in which users can split their work between a shared resource and a private resource. Unlike the private resource, which provides guaranteed performance, the performance of the shared resource is highly dependent on the usage pattern of other users, which in turn influences a user's decision if and to what extent to make use of the shared resource. The intrinsic relation between the utility that a user perceives from the shared resource and the usage pattern followed by other users gives rise to a noncooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the ratio between the worst Nash equilibrium and the social optimum, known as the “price of anarchy,” and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the price of anarchy can be arbitrarily large. We demonstrate that, somewhat counterintuitively, exercising admission control to the shared resource may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the shared resource to a wide range of user types.",danny raz,system performance,2015.0,10.1109/TNET.2014.2354572,IEEE/ACM Transactions on Networking,Nahir2015,False,,IEEE,Not available,Workload Factoring: A Game-Theoretic Perspective,759722e4368fa23983f8764c742ab847,https://ieeexplore.ieee.org/document/6901301/
3759,"Contention among users utilizing a single shared resource arises in multiple contexts of computing and computer communications. We consider a setup in which users can split their work between a shared resource and a private resource. Unlike the private resource, which provides guaranteed performance, the performance of the shared resource is highly dependent on the usage pattern of other users, which in turn influences a user's decision if and to what extent to make use of the shared resource. The intrinsic relation between the utility that a user perceives from the shared resource and the usage pattern followed by other users gives rise to a noncooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the ratio between the worst Nash equilibrium and the social optimum, known as the “price of anarchy,” and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the price of anarchy can be arbitrarily large. We demonstrate that, somewhat counterintuitively, exercising admission control to the shared resource may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the shared resource to a wide range of user types.",danny raz,systems engineering and theory,2015.0,10.1109/TNET.2014.2354572,IEEE/ACM Transactions on Networking,Nahir2015,False,,IEEE,Not available,Workload Factoring: A Game-Theoretic Perspective,759722e4368fa23983f8764c742ab847,https://ieeexplore.ieee.org/document/6901301/
3760,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",j. omic,Protection,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
3761,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",j. omic,Game theory,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
3762,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
3763,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",j. omic,IP networks,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
3764,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",j. omic,Network servers,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
3765,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",j. omic,Internet,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
3766,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",j. omic,Computer viruses,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
3767,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",j. omic,Employment,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
3768,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",j. omic,Decision making,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
3769,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",j. omic,Curing,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
3770,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",j. omic,Information security,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
3771,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",a. orda,Protection,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
3772,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",a. orda,Game theory,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
3773,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
3774,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",a. orda,IP networks,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
3775,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",a. orda,Network servers,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
3776,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",a. orda,Internet,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
3777,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",a. orda,Computer viruses,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
3778,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",a. orda,Employment,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
3779,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",a. orda,Decision making,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
3780,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",a. orda,Curing,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
3781,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",a. orda,Information security,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
3782,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",p. mieghem,Protection,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
3783,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",p. mieghem,Game theory,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
3784,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
3785,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",p. mieghem,IP networks,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
3786,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",p. mieghem,Network servers,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
3787,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",p. mieghem,Internet,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
3788,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",p. mieghem,Computer viruses,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
3789,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",p. mieghem,Employment,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
3790,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",p. mieghem,Decision making,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
3791,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",p. mieghem,Curing,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
3792,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",p. mieghem,Information security,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
3793,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",c. georgiou,Uncertainty,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
3794,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",c. georgiou,Routing,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
3795,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
3796,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",c. georgiou,Telecommunication traffic,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
3797,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",c. georgiou,Traffic control,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
3798,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",c. georgiou,Delay,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
3799,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",c. georgiou,Probability distribution,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
3800,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",c. georgiou,Polynomials,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
3801,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",c. georgiou,Costs,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
3802,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",c. georgiou,Upper bound,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
3803,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",c. georgiou,Nash equilibrium,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
3804,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",t. pavlides,Uncertainty,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
3805,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",t. pavlides,Routing,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
3806,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
3807,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",t. pavlides,Telecommunication traffic,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
3808,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",t. pavlides,Traffic control,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
3809,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",t. pavlides,Delay,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
3810,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",t. pavlides,Probability distribution,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
3811,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",t. pavlides,Polynomials,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
3812,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",t. pavlides,Costs,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
3813,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",t. pavlides,Upper bound,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
3814,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",t. pavlides,Nash equilibrium,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
3815,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",a. philippou,Uncertainty,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
3816,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",a. philippou,Routing,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
3817,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
3818,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",a. philippou,Telecommunication traffic,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
3819,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",a. philippou,Traffic control,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
3820,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",a. philippou,Delay,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
3821,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",a. philippou,Probability distribution,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
3822,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",a. philippou,Polynomials,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
3823,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",a. philippou,Costs,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
3824,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",a. philippou,Upper bound,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
3825,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",a. philippou,Nash equilibrium,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
3826,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. andrews,Wireless networks,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
3827,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. andrews,Signal to noise ratio,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
3828,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
3829,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. andrews,Game theory,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
3830,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. andrews,Distributed algorithms,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
3831,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. andrews,Approximation algorithms,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
3832,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. andrews,Nash equilibrium,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
3833,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. andrews,Background noise,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
3834,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. andrews,Linear programming,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
3835,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. andrews,Polynomials,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
3836,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. andrews,Algorithm design and analysis,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
3837,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. dinitz,Wireless networks,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
3838,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. dinitz,Signal to noise ratio,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
3839,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
3840,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. dinitz,Game theory,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
3841,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. dinitz,Distributed algorithms,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
3842,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. dinitz,Approximation algorithms,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
3843,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. dinitz,Nash equilibrium,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
3844,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. dinitz,Background noise,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
3845,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. dinitz,Linear programming,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
3846,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. dinitz,Polynomials,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
3847,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. dinitz,Algorithm design and analysis,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
3848,"Large-scale online service providers have been increasingly relying on geographically distributed cloud infrastructures for service hosting and delivery. In this context, a key challenge faced by service providers is to determine the locations where service applications should be placed such that the hosting cost is minimized while key performance requirements (e.g., response time) are ensured. Furthermore, the dynamic nature of both demand pattern and infrastructure cost favors a dynamic solution to this problem. Currently most of the existing solutions for service placement have either ignored dynamics, or provided solutions inadequate to achieve this objective. In this paper, we present a framework for dynamic service placement problems based on control- and game-theoretic models. In particular, we present a solution that optimizes the hosting cost dynamically over time according to both demand and resource price fluctuations. We further consider the case where multiple service providers compete for resources in a dynamic manner. This paper extends our previous work [1] by analyzing the outcome of the competition in terms of both price of stability and price of anarchy. Our analysis suggests that in an uncoordinated scenario where service providers behave in a selfish manner, the resulting Nash equilibrium can be arbitrarily worse than the optimal centralized solution in terms of social welfare. Based on this observation, we present a coordination mechanism that can be employed by the infrastructure provider to maximize the social welfare of the system. Finally, we demonstrate the effectiveness of our solutions using realistic simulations.",qi zhang,Cloud computing,2013.0,10.1109/JSAC.2013.SUP2.1213008,IEEE Journal on Selected Areas in Communications,Zhang2013,False,,IEEE,Not available,Dynamic Service Placement in Geographically Distributed Clouds,d2b38fd8bbcc32729c13a7a6817fcd5f,https://ieeexplore.ieee.org/document/6708556/
3849,"Large-scale online service providers have been increasingly relying on geographically distributed cloud infrastructures for service hosting and delivery. In this context, a key challenge faced by service providers is to determine the locations where service applications should be placed such that the hosting cost is minimized while key performance requirements (e.g., response time) are ensured. Furthermore, the dynamic nature of both demand pattern and infrastructure cost favors a dynamic solution to this problem. Currently most of the existing solutions for service placement have either ignored dynamics, or provided solutions inadequate to achieve this objective. In this paper, we present a framework for dynamic service placement problems based on control- and game-theoretic models. In particular, we present a solution that optimizes the hosting cost dynamically over time according to both demand and resource price fluctuations. We further consider the case where multiple service providers compete for resources in a dynamic manner. This paper extends our previous work [1] by analyzing the outcome of the competition in terms of both price of stability and price of anarchy. Our analysis suggests that in an uncoordinated scenario where service providers behave in a selfish manner, the resulting Nash equilibrium can be arbitrarily worse than the optimal centralized solution in terms of social welfare. Based on this observation, we present a coordination mechanism that can be employed by the infrastructure provider to maximize the social welfare of the system. Finally, we demonstrate the effectiveness of our solutions using realistic simulations.",qi zhang,resource management,2013.0,10.1109/JSAC.2013.SUP2.1213008,IEEE Journal on Selected Areas in Communications,Zhang2013,False,,IEEE,Not available,Dynamic Service Placement in Geographically Distributed Clouds,d2b38fd8bbcc32729c13a7a6817fcd5f,https://ieeexplore.ieee.org/document/6708556/
3850,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
3851,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
3852,"Large-scale online service providers have been increasingly relying on geographically distributed cloud infrastructures for service hosting and delivery. In this context, a key challenge faced by service providers is to determine the locations where service applications should be placed such that the hosting cost is minimized while key performance requirements (e.g., response time) are ensured. Furthermore, the dynamic nature of both demand pattern and infrastructure cost favors a dynamic solution to this problem. Currently most of the existing solutions for service placement have either ignored dynamics, or provided solutions inadequate to achieve this objective. In this paper, we present a framework for dynamic service placement problems based on control- and game-theoretic models. In particular, we present a solution that optimizes the hosting cost dynamically over time according to both demand and resource price fluctuations. We further consider the case where multiple service providers compete for resources in a dynamic manner. This paper extends our previous work [1] by analyzing the outcome of the competition in terms of both price of stability and price of anarchy. Our analysis suggests that in an uncoordinated scenario where service providers behave in a selfish manner, the resulting Nash equilibrium can be arbitrarily worse than the optimal centralized solution in terms of social welfare. Based on this observation, we present a coordination mechanism that can be employed by the infrastructure provider to maximize the social welfare of the system. Finally, we demonstrate the effectiveness of our solutions using realistic simulations.",qi zhang,model predictive control,2013.0,10.1109/JSAC.2013.SUP2.1213008,IEEE Journal on Selected Areas in Communications,Zhang2013,False,,IEEE,Not available,Dynamic Service Placement in Geographically Distributed Clouds,d2b38fd8bbcc32729c13a7a6817fcd5f,https://ieeexplore.ieee.org/document/6708556/
3853,"Large-scale online service providers have been increasingly relying on geographically distributed cloud infrastructures for service hosting and delivery. In this context, a key challenge faced by service providers is to determine the locations where service applications should be placed such that the hosting cost is minimized while key performance requirements (e.g., response time) are ensured. Furthermore, the dynamic nature of both demand pattern and infrastructure cost favors a dynamic solution to this problem. Currently most of the existing solutions for service placement have either ignored dynamics, or provided solutions inadequate to achieve this objective. In this paper, we present a framework for dynamic service placement problems based on control- and game-theoretic models. In particular, we present a solution that optimizes the hosting cost dynamically over time according to both demand and resource price fluctuations. We further consider the case where multiple service providers compete for resources in a dynamic manner. This paper extends our previous work [1] by analyzing the outcome of the competition in terms of both price of stability and price of anarchy. Our analysis suggests that in an uncoordinated scenario where service providers behave in a selfish manner, the resulting Nash equilibrium can be arbitrarily worse than the optimal centralized solution in terms of social welfare. Based on this observation, we present a coordination mechanism that can be employed by the infrastructure provider to maximize the social welfare of the system. Finally, we demonstrate the effectiveness of our solutions using realistic simulations.",quanyan zhu,Cloud computing,2013.0,10.1109/JSAC.2013.SUP2.1213008,IEEE Journal on Selected Areas in Communications,Zhang2013,False,,IEEE,Not available,Dynamic Service Placement in Geographically Distributed Clouds,d2b38fd8bbcc32729c13a7a6817fcd5f,https://ieeexplore.ieee.org/document/6708556/
3854,"Large-scale online service providers have been increasingly relying on geographically distributed cloud infrastructures for service hosting and delivery. In this context, a key challenge faced by service providers is to determine the locations where service applications should be placed such that the hosting cost is minimized while key performance requirements (e.g., response time) are ensured. Furthermore, the dynamic nature of both demand pattern and infrastructure cost favors a dynamic solution to this problem. Currently most of the existing solutions for service placement have either ignored dynamics, or provided solutions inadequate to achieve this objective. In this paper, we present a framework for dynamic service placement problems based on control- and game-theoretic models. In particular, we present a solution that optimizes the hosting cost dynamically over time according to both demand and resource price fluctuations. We further consider the case where multiple service providers compete for resources in a dynamic manner. This paper extends our previous work [1] by analyzing the outcome of the competition in terms of both price of stability and price of anarchy. Our analysis suggests that in an uncoordinated scenario where service providers behave in a selfish manner, the resulting Nash equilibrium can be arbitrarily worse than the optimal centralized solution in terms of social welfare. Based on this observation, we present a coordination mechanism that can be employed by the infrastructure provider to maximize the social welfare of the system. Finally, we demonstrate the effectiveness of our solutions using realistic simulations.",quanyan zhu,resource management,2013.0,10.1109/JSAC.2013.SUP2.1213008,IEEE Journal on Selected Areas in Communications,Zhang2013,False,,IEEE,Not available,Dynamic Service Placement in Geographically Distributed Clouds,d2b38fd8bbcc32729c13a7a6817fcd5f,https://ieeexplore.ieee.org/document/6708556/
3855,"Large-scale online service providers have been increasingly relying on geographically distributed cloud infrastructures for service hosting and delivery. In this context, a key challenge faced by service providers is to determine the locations where service applications should be placed such that the hosting cost is minimized while key performance requirements (e.g., response time) are ensured. Furthermore, the dynamic nature of both demand pattern and infrastructure cost favors a dynamic solution to this problem. Currently most of the existing solutions for service placement have either ignored dynamics, or provided solutions inadequate to achieve this objective. In this paper, we present a framework for dynamic service placement problems based on control- and game-theoretic models. In particular, we present a solution that optimizes the hosting cost dynamically over time according to both demand and resource price fluctuations. We further consider the case where multiple service providers compete for resources in a dynamic manner. This paper extends our previous work [1] by analyzing the outcome of the competition in terms of both price of stability and price of anarchy. Our analysis suggests that in an uncoordinated scenario where service providers behave in a selfish manner, the resulting Nash equilibrium can be arbitrarily worse than the optimal centralized solution in terms of social welfare. Based on this observation, we present a coordination mechanism that can be employed by the infrastructure provider to maximize the social welfare of the system. Finally, we demonstrate the effectiveness of our solutions using realistic simulations.",quanyan zhu,model predictive control,2013.0,10.1109/JSAC.2013.SUP2.1213008,IEEE Journal on Selected Areas in Communications,Zhang2013,False,,IEEE,Not available,Dynamic Service Placement in Geographically Distributed Clouds,d2b38fd8bbcc32729c13a7a6817fcd5f,https://ieeexplore.ieee.org/document/6708556/
3856,"Large-scale online service providers have been increasingly relying on geographically distributed cloud infrastructures for service hosting and delivery. In this context, a key challenge faced by service providers is to determine the locations where service applications should be placed such that the hosting cost is minimized while key performance requirements (e.g., response time) are ensured. Furthermore, the dynamic nature of both demand pattern and infrastructure cost favors a dynamic solution to this problem. Currently most of the existing solutions for service placement have either ignored dynamics, or provided solutions inadequate to achieve this objective. In this paper, we present a framework for dynamic service placement problems based on control- and game-theoretic models. In particular, we present a solution that optimizes the hosting cost dynamically over time according to both demand and resource price fluctuations. We further consider the case where multiple service providers compete for resources in a dynamic manner. This paper extends our previous work [1] by analyzing the outcome of the competition in terms of both price of stability and price of anarchy. Our analysis suggests that in an uncoordinated scenario where service providers behave in a selfish manner, the resulting Nash equilibrium can be arbitrarily worse than the optimal centralized solution in terms of social welfare. Based on this observation, we present a coordination mechanism that can be employed by the infrastructure provider to maximize the social welfare of the system. Finally, we demonstrate the effectiveness of our solutions using realistic simulations.",mohamed zhani,Cloud computing,2013.0,10.1109/JSAC.2013.SUP2.1213008,IEEE Journal on Selected Areas in Communications,Zhang2013,False,,IEEE,Not available,Dynamic Service Placement in Geographically Distributed Clouds,d2b38fd8bbcc32729c13a7a6817fcd5f,https://ieeexplore.ieee.org/document/6708556/
3857,"Large-scale online service providers have been increasingly relying on geographically distributed cloud infrastructures for service hosting and delivery. In this context, a key challenge faced by service providers is to determine the locations where service applications should be placed such that the hosting cost is minimized while key performance requirements (e.g., response time) are ensured. Furthermore, the dynamic nature of both demand pattern and infrastructure cost favors a dynamic solution to this problem. Currently most of the existing solutions for service placement have either ignored dynamics, or provided solutions inadequate to achieve this objective. In this paper, we present a framework for dynamic service placement problems based on control- and game-theoretic models. In particular, we present a solution that optimizes the hosting cost dynamically over time according to both demand and resource price fluctuations. We further consider the case where multiple service providers compete for resources in a dynamic manner. This paper extends our previous work [1] by analyzing the outcome of the competition in terms of both price of stability and price of anarchy. Our analysis suggests that in an uncoordinated scenario where service providers behave in a selfish manner, the resulting Nash equilibrium can be arbitrarily worse than the optimal centralized solution in terms of social welfare. Based on this observation, we present a coordination mechanism that can be employed by the infrastructure provider to maximize the social welfare of the system. Finally, we demonstrate the effectiveness of our solutions using realistic simulations.",mohamed zhani,resource management,2013.0,10.1109/JSAC.2013.SUP2.1213008,IEEE Journal on Selected Areas in Communications,Zhang2013,False,,IEEE,Not available,Dynamic Service Placement in Geographically Distributed Clouds,d2b38fd8bbcc32729c13a7a6817fcd5f,https://ieeexplore.ieee.org/document/6708556/
3858,"Large-scale online service providers have been increasingly relying on geographically distributed cloud infrastructures for service hosting and delivery. In this context, a key challenge faced by service providers is to determine the locations where service applications should be placed such that the hosting cost is minimized while key performance requirements (e.g., response time) are ensured. Furthermore, the dynamic nature of both demand pattern and infrastructure cost favors a dynamic solution to this problem. Currently most of the existing solutions for service placement have either ignored dynamics, or provided solutions inadequate to achieve this objective. In this paper, we present a framework for dynamic service placement problems based on control- and game-theoretic models. In particular, we present a solution that optimizes the hosting cost dynamically over time according to both demand and resource price fluctuations. We further consider the case where multiple service providers compete for resources in a dynamic manner. This paper extends our previous work [1] by analyzing the outcome of the competition in terms of both price of stability and price of anarchy. Our analysis suggests that in an uncoordinated scenario where service providers behave in a selfish manner, the resulting Nash equilibrium can be arbitrarily worse than the optimal centralized solution in terms of social welfare. Based on this observation, we present a coordination mechanism that can be employed by the infrastructure provider to maximize the social welfare of the system. Finally, we demonstrate the effectiveness of our solutions using realistic simulations.",mohamed zhani,model predictive control,2013.0,10.1109/JSAC.2013.SUP2.1213008,IEEE Journal on Selected Areas in Communications,Zhang2013,False,,IEEE,Not available,Dynamic Service Placement in Geographically Distributed Clouds,d2b38fd8bbcc32729c13a7a6817fcd5f,https://ieeexplore.ieee.org/document/6708556/
3859,"Large-scale online service providers have been increasingly relying on geographically distributed cloud infrastructures for service hosting and delivery. In this context, a key challenge faced by service providers is to determine the locations where service applications should be placed such that the hosting cost is minimized while key performance requirements (e.g., response time) are ensured. Furthermore, the dynamic nature of both demand pattern and infrastructure cost favors a dynamic solution to this problem. Currently most of the existing solutions for service placement have either ignored dynamics, or provided solutions inadequate to achieve this objective. In this paper, we present a framework for dynamic service placement problems based on control- and game-theoretic models. In particular, we present a solution that optimizes the hosting cost dynamically over time according to both demand and resource price fluctuations. We further consider the case where multiple service providers compete for resources in a dynamic manner. This paper extends our previous work [1] by analyzing the outcome of the competition in terms of both price of stability and price of anarchy. Our analysis suggests that in an uncoordinated scenario where service providers behave in a selfish manner, the resulting Nash equilibrium can be arbitrarily worse than the optimal centralized solution in terms of social welfare. Based on this observation, we present a coordination mechanism that can be employed by the infrastructure provider to maximize the social welfare of the system. Finally, we demonstrate the effectiveness of our solutions using realistic simulations.",raouf boutaba,Cloud computing,2013.0,10.1109/JSAC.2013.SUP2.1213008,IEEE Journal on Selected Areas in Communications,Zhang2013,False,,IEEE,Not available,Dynamic Service Placement in Geographically Distributed Clouds,d2b38fd8bbcc32729c13a7a6817fcd5f,https://ieeexplore.ieee.org/document/6708556/
3860,"Large-scale online service providers have been increasingly relying on geographically distributed cloud infrastructures for service hosting and delivery. In this context, a key challenge faced by service providers is to determine the locations where service applications should be placed such that the hosting cost is minimized while key performance requirements (e.g., response time) are ensured. Furthermore, the dynamic nature of both demand pattern and infrastructure cost favors a dynamic solution to this problem. Currently most of the existing solutions for service placement have either ignored dynamics, or provided solutions inadequate to achieve this objective. In this paper, we present a framework for dynamic service placement problems based on control- and game-theoretic models. In particular, we present a solution that optimizes the hosting cost dynamically over time according to both demand and resource price fluctuations. We further consider the case where multiple service providers compete for resources in a dynamic manner. This paper extends our previous work [1] by analyzing the outcome of the competition in terms of both price of stability and price of anarchy. Our analysis suggests that in an uncoordinated scenario where service providers behave in a selfish manner, the resulting Nash equilibrium can be arbitrarily worse than the optimal centralized solution in terms of social welfare. Based on this observation, we present a coordination mechanism that can be employed by the infrastructure provider to maximize the social welfare of the system. Finally, we demonstrate the effectiveness of our solutions using realistic simulations.",raouf boutaba,resource management,2013.0,10.1109/JSAC.2013.SUP2.1213008,IEEE Journal on Selected Areas in Communications,Zhang2013,False,,IEEE,Not available,Dynamic Service Placement in Geographically Distributed Clouds,d2b38fd8bbcc32729c13a7a6817fcd5f,https://ieeexplore.ieee.org/document/6708556/
3861,"Large-scale online service providers have been increasingly relying on geographically distributed cloud infrastructures for service hosting and delivery. In this context, a key challenge faced by service providers is to determine the locations where service applications should be placed such that the hosting cost is minimized while key performance requirements (e.g., response time) are ensured. Furthermore, the dynamic nature of both demand pattern and infrastructure cost favors a dynamic solution to this problem. Currently most of the existing solutions for service placement have either ignored dynamics, or provided solutions inadequate to achieve this objective. In this paper, we present a framework for dynamic service placement problems based on control- and game-theoretic models. In particular, we present a solution that optimizes the hosting cost dynamically over time according to both demand and resource price fluctuations. We further consider the case where multiple service providers compete for resources in a dynamic manner. This paper extends our previous work [1] by analyzing the outcome of the competition in terms of both price of stability and price of anarchy. Our analysis suggests that in an uncoordinated scenario where service providers behave in a selfish manner, the resulting Nash equilibrium can be arbitrarily worse than the optimal centralized solution in terms of social welfare. Based on this observation, we present a coordination mechanism that can be employed by the infrastructure provider to maximize the social welfare of the system. Finally, we demonstrate the effectiveness of our solutions using realistic simulations.",raouf boutaba,model predictive control,2013.0,10.1109/JSAC.2013.SUP2.1213008,IEEE Journal on Selected Areas in Communications,Zhang2013,False,,IEEE,Not available,Dynamic Service Placement in Geographically Distributed Clouds,d2b38fd8bbcc32729c13a7a6817fcd5f,https://ieeexplore.ieee.org/document/6708556/
3862,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
3863,"Large-scale online service providers have been increasingly relying on geographically distributed cloud infrastructures for service hosting and delivery. In this context, a key challenge faced by service providers is to determine the locations where service applications should be placed such that the hosting cost is minimized while key performance requirements (e.g., response time) are ensured. Furthermore, the dynamic nature of both demand pattern and infrastructure cost favors a dynamic solution to this problem. Currently most of the existing solutions for service placement have either ignored dynamics, or provided solutions inadequate to achieve this objective. In this paper, we present a framework for dynamic service placement problems based on control- and game-theoretic models. In particular, we present a solution that optimizes the hosting cost dynamically over time according to both demand and resource price fluctuations. We further consider the case where multiple service providers compete for resources in a dynamic manner. This paper extends our previous work [1] by analyzing the outcome of the competition in terms of both price of stability and price of anarchy. Our analysis suggests that in an uncoordinated scenario where service providers behave in a selfish manner, the resulting Nash equilibrium can be arbitrarily worse than the optimal centralized solution in terms of social welfare. Based on this observation, we present a coordination mechanism that can be employed by the infrastructure provider to maximize the social welfare of the system. Finally, we demonstrate the effectiveness of our solutions using realistic simulations.",joseph hellerstein,Cloud computing,2013.0,10.1109/JSAC.2013.SUP2.1213008,IEEE Journal on Selected Areas in Communications,Zhang2013,False,,IEEE,Not available,Dynamic Service Placement in Geographically Distributed Clouds,d2b38fd8bbcc32729c13a7a6817fcd5f,https://ieeexplore.ieee.org/document/6708556/
3864,"Large-scale online service providers have been increasingly relying on geographically distributed cloud infrastructures for service hosting and delivery. In this context, a key challenge faced by service providers is to determine the locations where service applications should be placed such that the hosting cost is minimized while key performance requirements (e.g., response time) are ensured. Furthermore, the dynamic nature of both demand pattern and infrastructure cost favors a dynamic solution to this problem. Currently most of the existing solutions for service placement have either ignored dynamics, or provided solutions inadequate to achieve this objective. In this paper, we present a framework for dynamic service placement problems based on control- and game-theoretic models. In particular, we present a solution that optimizes the hosting cost dynamically over time according to both demand and resource price fluctuations. We further consider the case where multiple service providers compete for resources in a dynamic manner. This paper extends our previous work [1] by analyzing the outcome of the competition in terms of both price of stability and price of anarchy. Our analysis suggests that in an uncoordinated scenario where service providers behave in a selfish manner, the resulting Nash equilibrium can be arbitrarily worse than the optimal centralized solution in terms of social welfare. Based on this observation, we present a coordination mechanism that can be employed by the infrastructure provider to maximize the social welfare of the system. Finally, we demonstrate the effectiveness of our solutions using realistic simulations.",joseph hellerstein,resource management,2013.0,10.1109/JSAC.2013.SUP2.1213008,IEEE Journal on Selected Areas in Communications,Zhang2013,False,,IEEE,Not available,Dynamic Service Placement in Geographically Distributed Clouds,d2b38fd8bbcc32729c13a7a6817fcd5f,https://ieeexplore.ieee.org/document/6708556/
3865,"Large-scale online service providers have been increasingly relying on geographically distributed cloud infrastructures for service hosting and delivery. In this context, a key challenge faced by service providers is to determine the locations where service applications should be placed such that the hosting cost is minimized while key performance requirements (e.g., response time) are ensured. Furthermore, the dynamic nature of both demand pattern and infrastructure cost favors a dynamic solution to this problem. Currently most of the existing solutions for service placement have either ignored dynamics, or provided solutions inadequate to achieve this objective. In this paper, we present a framework for dynamic service placement problems based on control- and game-theoretic models. In particular, we present a solution that optimizes the hosting cost dynamically over time according to both demand and resource price fluctuations. We further consider the case where multiple service providers compete for resources in a dynamic manner. This paper extends our previous work [1] by analyzing the outcome of the competition in terms of both price of stability and price of anarchy. Our analysis suggests that in an uncoordinated scenario where service providers behave in a selfish manner, the resulting Nash equilibrium can be arbitrarily worse than the optimal centralized solution in terms of social welfare. Based on this observation, we present a coordination mechanism that can be employed by the infrastructure provider to maximize the social welfare of the system. Finally, we demonstrate the effectiveness of our solutions using realistic simulations.",joseph hellerstein,model predictive control,2013.0,10.1109/JSAC.2013.SUP2.1213008,IEEE Journal on Selected Areas in Communications,Zhang2013,False,,IEEE,Not available,Dynamic Service Placement in Geographically Distributed Clouds,d2b38fd8bbcc32729c13a7a6817fcd5f,https://ieeexplore.ieee.org/document/6708556/
3866,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. nahir,Network topology,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
3867,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. nahir,Nash equilibrium,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
3868,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. nahir,Routing,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
3869,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. nahir,Interference,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
3870,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. nahir,Performance analysis,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
3871,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. nahir,Lighting control,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
3872,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. nahir,Relays,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
3873,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
3874,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. nahir,Game theory,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
3875,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. nahir,Stability,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
3876,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. nahir,Computer network reliability,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
3877,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. orda,Network topology,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
3878,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. orda,Nash equilibrium,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
3879,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. orda,Routing,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
3880,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. orda,Interference,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
3881,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. orda,Performance analysis,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
3882,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. orda,Lighting control,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
3883,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. orda,Relays,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
3884,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
3885,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. orda,Game theory,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
3886,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. orda,Stability,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
3887,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. orda,Computer network reliability,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
3888,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. freund,Network topology,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
3889,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. freund,Nash equilibrium,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
3890,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. freund,Routing,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
3891,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. freund,Interference,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
3892,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. freund,Performance analysis,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
3893,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. freund,Lighting control,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
3894,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. freund,Relays,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
3895,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
3896,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. freund,Game theory,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
3897,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. freund,Stability,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
3898,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. freund,Computer network reliability,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
3899,"Aggregating statistically diverse renewable power producers (RPPs) is an effective way to reduce the uncertainty of the RPPs. The key question is how to design a mechanism to aggregate the RPPs and distribute the payoffs among them. In this paper, a simple payoff allocation mechanism (PAM) is shown to achieve a wide range of desired properties. In particular, social efficiency, stability (in the core), and no collusion are achieved at the unique pure Nash Equilibrium (NE) of the non-cooperative game of RPPs induced by the PAM. As a result, an ideal “Price of Anarchy” of one is achieved. Moreover, a closed form expression of the unique pure NE is derived. A simulation study is conducted using the data of ten wind power producers in the PJM interconnection.",hossein khazaei,Mechanism Design,2017.0,10.1109/GlobalSIP.2017.8309116,2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP),Khazaei2017,False,,IEEE,Not available,A simple payoff allocation mechanism achieves efficiency and stability in renewable energy aggregation,6e22313d864590a3e9eae891991c37db,https://ieeexplore.ieee.org/document/8309116/
3900,"Aggregating statistically diverse renewable power producers (RPPs) is an effective way to reduce the uncertainty of the RPPs. The key question is how to design a mechanism to aggregate the RPPs and distribute the payoffs among them. In this paper, a simple payoff allocation mechanism (PAM) is shown to achieve a wide range of desired properties. In particular, social efficiency, stability (in the core), and no collusion are achieved at the unique pure Nash Equilibrium (NE) of the non-cooperative game of RPPs induced by the PAM. As a result, an ideal “Price of Anarchy” of one is achieved. Moreover, a closed form expression of the unique pure NE is derived. A simulation study is conducted using the data of ten wind power producers in the PJM interconnection.",hossein khazaei,Renewable Energy Integration,2017.0,10.1109/GlobalSIP.2017.8309116,2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP),Khazaei2017,False,,IEEE,Not available,A simple payoff allocation mechanism achieves efficiency and stability in renewable energy aggregation,6e22313d864590a3e9eae891991c37db,https://ieeexplore.ieee.org/document/8309116/
3901,"Aggregating statistically diverse renewable power producers (RPPs) is an effective way to reduce the uncertainty of the RPPs. The key question is how to design a mechanism to aggregate the RPPs and distribute the payoffs among them. In this paper, a simple payoff allocation mechanism (PAM) is shown to achieve a wide range of desired properties. In particular, social efficiency, stability (in the core), and no collusion are achieved at the unique pure Nash Equilibrium (NE) of the non-cooperative game of RPPs induced by the PAM. As a result, an ideal “Price of Anarchy” of one is achieved. Moreover, a closed form expression of the unique pure NE is derived. A simulation study is conducted using the data of ten wind power producers in the PJM interconnection.",hossein khazaei,Energy Aggregation,2017.0,10.1109/GlobalSIP.2017.8309116,2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP),Khazaei2017,False,,IEEE,Not available,A simple payoff allocation mechanism achieves efficiency and stability in renewable energy aggregation,6e22313d864590a3e9eae891991c37db,https://ieeexplore.ieee.org/document/8309116/
3902,"Aggregating statistically diverse renewable power producers (RPPs) is an effective way to reduce the uncertainty of the RPPs. The key question is how to design a mechanism to aggregate the RPPs and distribute the payoffs among them. In this paper, a simple payoff allocation mechanism (PAM) is shown to achieve a wide range of desired properties. In particular, social efficiency, stability (in the core), and no collusion are achieved at the unique pure Nash Equilibrium (NE) of the non-cooperative game of RPPs induced by the PAM. As a result, an ideal “Price of Anarchy” of one is achieved. Moreover, a closed form expression of the unique pure NE is derived. A simulation study is conducted using the data of ten wind power producers in the PJM interconnection.",yue zhao,Mechanism Design,2017.0,10.1109/GlobalSIP.2017.8309116,2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP),Khazaei2017,False,,IEEE,Not available,A simple payoff allocation mechanism achieves efficiency and stability in renewable energy aggregation,6e22313d864590a3e9eae891991c37db,https://ieeexplore.ieee.org/document/8309116/
3903,"Aggregating statistically diverse renewable power producers (RPPs) is an effective way to reduce the uncertainty of the RPPs. The key question is how to design a mechanism to aggregate the RPPs and distribute the payoffs among them. In this paper, a simple payoff allocation mechanism (PAM) is shown to achieve a wide range of desired properties. In particular, social efficiency, stability (in the core), and no collusion are achieved at the unique pure Nash Equilibrium (NE) of the non-cooperative game of RPPs induced by the PAM. As a result, an ideal “Price of Anarchy” of one is achieved. Moreover, a closed form expression of the unique pure NE is derived. A simulation study is conducted using the data of ten wind power producers in the PJM interconnection.",yue zhao,Renewable Energy Integration,2017.0,10.1109/GlobalSIP.2017.8309116,2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP),Khazaei2017,False,,IEEE,Not available,A simple payoff allocation mechanism achieves efficiency and stability in renewable energy aggregation,6e22313d864590a3e9eae891991c37db,https://ieeexplore.ieee.org/document/8309116/
3904,"Aggregating statistically diverse renewable power producers (RPPs) is an effective way to reduce the uncertainty of the RPPs. The key question is how to design a mechanism to aggregate the RPPs and distribute the payoffs among them. In this paper, a simple payoff allocation mechanism (PAM) is shown to achieve a wide range of desired properties. In particular, social efficiency, stability (in the core), and no collusion are achieved at the unique pure Nash Equilibrium (NE) of the non-cooperative game of RPPs induced by the PAM. As a result, an ideal “Price of Anarchy” of one is achieved. Moreover, a closed form expression of the unique pure NE is derived. A simulation study is conducted using the data of ten wind power producers in the PJM interconnection.",yue zhao,Energy Aggregation,2017.0,10.1109/GlobalSIP.2017.8309116,2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP),Khazaei2017,False,,IEEE,Not available,A simple payoff allocation mechanism achieves efficiency and stability in renewable energy aggregation,6e22313d864590a3e9eae891991c37db,https://ieeexplore.ieee.org/document/8309116/
3905,"Mechanism design is studied for aggregating renewable power producers (RPPs) in a two-settlement power market. Employing an indirect mechanism design framework, a payoff allocation mechanism (PAM) is derived from the competitive equilibrium (CE) of a specially formulated market with transferrable payoff. Given the designed mechanism, the strategic behaviors of the participating RPPs entail a non-cooperative game: It is proven that a unique pure Nash equilibrium (NE) exists among the RPPs, for which a closed form expression is found. Moreover, it is proven that the designed mechanism achieves a number of key desirable properties at the NE: these include efficiency (i.e., an ideal ""Price of Anarchy"" of one), stability (i.e., ""in the core"" from a coalitional game theoretic perspective), and no collusion. In addition, it is shown that a set of desirable ""ex-post"" properties are also achieved by the designed mechanism. Extensive simulations are conducted and corroborate the theoretical results.",hossein khazaei,Cost allocation,,10.1109/TPWRS.2018.2875457,IEEE Transactions on Power Systems,KhazaeiNone,False,,IEEE,Not available,Indirect Mechanism Design for Efficient and Stable Renewable Energy Aggregation,bdb68bd15592a1e330709dfc43155670,
3906,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
3907,"Mechanism design is studied for aggregating renewable power producers (RPPs) in a two-settlement power market. Employing an indirect mechanism design framework, a payoff allocation mechanism (PAM) is derived from the competitive equilibrium (CE) of a specially formulated market with transferrable payoff. Given the designed mechanism, the strategic behaviors of the participating RPPs entail a non-cooperative game: It is proven that a unique pure Nash equilibrium (NE) exists among the RPPs, for which a closed form expression is found. Moreover, it is proven that the designed mechanism achieves a number of key desirable properties at the NE: these include efficiency (i.e., an ideal ""Price of Anarchy"" of one), stability (i.e., ""in the core"" from a coalitional game theoretic perspective), and no collusion. In addition, it is shown that a set of desirable ""ex-post"" properties are also achieved by the designed mechanism. Extensive simulations are conducted and corroborate the theoretical results.",hossein khazaei,Nash equilibrium,,10.1109/TPWRS.2018.2875457,IEEE Transactions on Power Systems,KhazaeiNone,False,,IEEE,Not available,Indirect Mechanism Design for Efficient and Stable Renewable Energy Aggregation,bdb68bd15592a1e330709dfc43155670,
3908,"Mechanism design is studied for aggregating renewable power producers (RPPs) in a two-settlement power market. Employing an indirect mechanism design framework, a payoff allocation mechanism (PAM) is derived from the competitive equilibrium (CE) of a specially formulated market with transferrable payoff. Given the designed mechanism, the strategic behaviors of the participating RPPs entail a non-cooperative game: It is proven that a unique pure Nash equilibrium (NE) exists among the RPPs, for which a closed form expression is found. Moreover, it is proven that the designed mechanism achieves a number of key desirable properties at the NE: these include efficiency (i.e., an ideal ""Price of Anarchy"" of one), stability (i.e., ""in the core"" from a coalitional game theoretic perspective), and no collusion. In addition, it is shown that a set of desirable ""ex-post"" properties are also achieved by the designed mechanism. Extensive simulations are conducted and corroborate the theoretical results.",hossein khazaei,mechanism design,,10.1109/TPWRS.2018.2875457,IEEE Transactions on Power Systems,KhazaeiNone,False,,IEEE,Not available,Indirect Mechanism Design for Efficient and Stable Renewable Energy Aggregation,bdb68bd15592a1e330709dfc43155670,
3909,"Mechanism design is studied for aggregating renewable power producers (RPPs) in a two-settlement power market. Employing an indirect mechanism design framework, a payoff allocation mechanism (PAM) is derived from the competitive equilibrium (CE) of a specially formulated market with transferrable payoff. Given the designed mechanism, the strategic behaviors of the participating RPPs entail a non-cooperative game: It is proven that a unique pure Nash equilibrium (NE) exists among the RPPs, for which a closed form expression is found. Moreover, it is proven that the designed mechanism achieves a number of key desirable properties at the NE: these include efficiency (i.e., an ideal ""Price of Anarchy"" of one), stability (i.e., ""in the core"" from a coalitional game theoretic perspective), and no collusion. In addition, it is shown that a set of desirable ""ex-post"" properties are also achieved by the designed mechanism. Extensive simulations are conducted and corroborate the theoretical results.",hossein khazaei,coalitional game,,10.1109/TPWRS.2018.2875457,IEEE Transactions on Power Systems,KhazaeiNone,False,,IEEE,Not available,Indirect Mechanism Design for Efficient and Stable Renewable Energy Aggregation,bdb68bd15592a1e330709dfc43155670,
3910,"Mechanism design is studied for aggregating renewable power producers (RPPs) in a two-settlement power market. Employing an indirect mechanism design framework, a payoff allocation mechanism (PAM) is derived from the competitive equilibrium (CE) of a specially formulated market with transferrable payoff. Given the designed mechanism, the strategic behaviors of the participating RPPs entail a non-cooperative game: It is proven that a unique pure Nash equilibrium (NE) exists among the RPPs, for which a closed form expression is found. Moreover, it is proven that the designed mechanism achieves a number of key desirable properties at the NE: these include efficiency (i.e., an ideal ""Price of Anarchy"" of one), stability (i.e., ""in the core"" from a coalitional game theoretic perspective), and no collusion. In addition, it is shown that a set of desirable ""ex-post"" properties are also achieved by the designed mechanism. Extensive simulations are conducted and corroborate the theoretical results.",hossein khazaei,renewable energy,,10.1109/TPWRS.2018.2875457,IEEE Transactions on Power Systems,KhazaeiNone,False,,IEEE,Not available,Indirect Mechanism Design for Efficient and Stable Renewable Energy Aggregation,bdb68bd15592a1e330709dfc43155670,
3911,"Mechanism design is studied for aggregating renewable power producers (RPPs) in a two-settlement power market. Employing an indirect mechanism design framework, a payoff allocation mechanism (PAM) is derived from the competitive equilibrium (CE) of a specially formulated market with transferrable payoff. Given the designed mechanism, the strategic behaviors of the participating RPPs entail a non-cooperative game: It is proven that a unique pure Nash equilibrium (NE) exists among the RPPs, for which a closed form expression is found. Moreover, it is proven that the designed mechanism achieves a number of key desirable properties at the NE: these include efficiency (i.e., an ideal ""Price of Anarchy"" of one), stability (i.e., ""in the core"" from a coalitional game theoretic perspective), and no collusion. In addition, it is shown that a set of desirable ""ex-post"" properties are also achieved by the designed mechanism. Extensive simulations are conducted and corroborate the theoretical results.",hossein khazaei,electricity market,,10.1109/TPWRS.2018.2875457,IEEE Transactions on Power Systems,KhazaeiNone,False,,IEEE,Not available,Indirect Mechanism Design for Efficient and Stable Renewable Energy Aggregation,bdb68bd15592a1e330709dfc43155670,
3912,"Mechanism design is studied for aggregating renewable power producers (RPPs) in a two-settlement power market. Employing an indirect mechanism design framework, a payoff allocation mechanism (PAM) is derived from the competitive equilibrium (CE) of a specially formulated market with transferrable payoff. Given the designed mechanism, the strategic behaviors of the participating RPPs entail a non-cooperative game: It is proven that a unique pure Nash equilibrium (NE) exists among the RPPs, for which a closed form expression is found. Moreover, it is proven that the designed mechanism achieves a number of key desirable properties at the NE: these include efficiency (i.e., an ideal ""Price of Anarchy"" of one), stability (i.e., ""in the core"" from a coalitional game theoretic perspective), and no collusion. In addition, it is shown that a set of desirable ""ex-post"" properties are also achieved by the designed mechanism. Extensive simulations are conducted and corroborate the theoretical results.",yue zhao,Cost allocation,,10.1109/TPWRS.2018.2875457,IEEE Transactions on Power Systems,KhazaeiNone,False,,IEEE,Not available,Indirect Mechanism Design for Efficient and Stable Renewable Energy Aggregation,bdb68bd15592a1e330709dfc43155670,
3913,"Mechanism design is studied for aggregating renewable power producers (RPPs) in a two-settlement power market. Employing an indirect mechanism design framework, a payoff allocation mechanism (PAM) is derived from the competitive equilibrium (CE) of a specially formulated market with transferrable payoff. Given the designed mechanism, the strategic behaviors of the participating RPPs entail a non-cooperative game: It is proven that a unique pure Nash equilibrium (NE) exists among the RPPs, for which a closed form expression is found. Moreover, it is proven that the designed mechanism achieves a number of key desirable properties at the NE: these include efficiency (i.e., an ideal ""Price of Anarchy"" of one), stability (i.e., ""in the core"" from a coalitional game theoretic perspective), and no collusion. In addition, it is shown that a set of desirable ""ex-post"" properties are also achieved by the designed mechanism. Extensive simulations are conducted and corroborate the theoretical results.",yue zhao,Nash equilibrium,,10.1109/TPWRS.2018.2875457,IEEE Transactions on Power Systems,KhazaeiNone,False,,IEEE,Not available,Indirect Mechanism Design for Efficient and Stable Renewable Energy Aggregation,bdb68bd15592a1e330709dfc43155670,
3914,"Mechanism design is studied for aggregating renewable power producers (RPPs) in a two-settlement power market. Employing an indirect mechanism design framework, a payoff allocation mechanism (PAM) is derived from the competitive equilibrium (CE) of a specially formulated market with transferrable payoff. Given the designed mechanism, the strategic behaviors of the participating RPPs entail a non-cooperative game: It is proven that a unique pure Nash equilibrium (NE) exists among the RPPs, for which a closed form expression is found. Moreover, it is proven that the designed mechanism achieves a number of key desirable properties at the NE: these include efficiency (i.e., an ideal ""Price of Anarchy"" of one), stability (i.e., ""in the core"" from a coalitional game theoretic perspective), and no collusion. In addition, it is shown that a set of desirable ""ex-post"" properties are also achieved by the designed mechanism. Extensive simulations are conducted and corroborate the theoretical results.",yue zhao,mechanism design,,10.1109/TPWRS.2018.2875457,IEEE Transactions on Power Systems,KhazaeiNone,False,,IEEE,Not available,Indirect Mechanism Design for Efficient and Stable Renewable Energy Aggregation,bdb68bd15592a1e330709dfc43155670,
3915,"Mechanism design is studied for aggregating renewable power producers (RPPs) in a two-settlement power market. Employing an indirect mechanism design framework, a payoff allocation mechanism (PAM) is derived from the competitive equilibrium (CE) of a specially formulated market with transferrable payoff. Given the designed mechanism, the strategic behaviors of the participating RPPs entail a non-cooperative game: It is proven that a unique pure Nash equilibrium (NE) exists among the RPPs, for which a closed form expression is found. Moreover, it is proven that the designed mechanism achieves a number of key desirable properties at the NE: these include efficiency (i.e., an ideal ""Price of Anarchy"" of one), stability (i.e., ""in the core"" from a coalitional game theoretic perspective), and no collusion. In addition, it is shown that a set of desirable ""ex-post"" properties are also achieved by the designed mechanism. Extensive simulations are conducted and corroborate the theoretical results.",yue zhao,coalitional game,,10.1109/TPWRS.2018.2875457,IEEE Transactions on Power Systems,KhazaeiNone,False,,IEEE,Not available,Indirect Mechanism Design for Efficient and Stable Renewable Energy Aggregation,bdb68bd15592a1e330709dfc43155670,
3916,"Mechanism design is studied for aggregating renewable power producers (RPPs) in a two-settlement power market. Employing an indirect mechanism design framework, a payoff allocation mechanism (PAM) is derived from the competitive equilibrium (CE) of a specially formulated market with transferrable payoff. Given the designed mechanism, the strategic behaviors of the participating RPPs entail a non-cooperative game: It is proven that a unique pure Nash equilibrium (NE) exists among the RPPs, for which a closed form expression is found. Moreover, it is proven that the designed mechanism achieves a number of key desirable properties at the NE: these include efficiency (i.e., an ideal ""Price of Anarchy"" of one), stability (i.e., ""in the core"" from a coalitional game theoretic perspective), and no collusion. In addition, it is shown that a set of desirable ""ex-post"" properties are also achieved by the designed mechanism. Extensive simulations are conducted and corroborate the theoretical results.",yue zhao,renewable energy,,10.1109/TPWRS.2018.2875457,IEEE Transactions on Power Systems,KhazaeiNone,False,,IEEE,Not available,Indirect Mechanism Design for Efficient and Stable Renewable Energy Aggregation,bdb68bd15592a1e330709dfc43155670,
3917,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
3918,"Mechanism design is studied for aggregating renewable power producers (RPPs) in a two-settlement power market. Employing an indirect mechanism design framework, a payoff allocation mechanism (PAM) is derived from the competitive equilibrium (CE) of a specially formulated market with transferrable payoff. Given the designed mechanism, the strategic behaviors of the participating RPPs entail a non-cooperative game: It is proven that a unique pure Nash equilibrium (NE) exists among the RPPs, for which a closed form expression is found. Moreover, it is proven that the designed mechanism achieves a number of key desirable properties at the NE: these include efficiency (i.e., an ideal ""Price of Anarchy"" of one), stability (i.e., ""in the core"" from a coalitional game theoretic perspective), and no collusion. In addition, it is shown that a set of desirable ""ex-post"" properties are also achieved by the designed mechanism. Extensive simulations are conducted and corroborate the theoretical results.",yue zhao,electricity market,,10.1109/TPWRS.2018.2875457,IEEE Transactions on Power Systems,KhazaeiNone,False,,IEEE,Not available,Indirect Mechanism Design for Efficient and Stable Renewable Energy Aggregation,bdb68bd15592a1e330709dfc43155670,
3919,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",r. johari,Resource management,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
3920,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",r. johari,Computer aided software engineering,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
3921,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",r. johari,Aggregates,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
3922,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",r. johari,Internet,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
3923,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",r. johari,Environmental economics,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
3924,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",r. johari,Nash equilibrium,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
3925,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",r. johari,Peer to peer computing,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
3926,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",r. johari,Computer science,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
3927,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",r. johari,Routing,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
3928,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
3929,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",r. johari,Telecommunication traffic,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
3930,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",j.n. tsitsiklis,Resource management,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
3931,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",j.n. tsitsiklis,Computer aided software engineering,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
3932,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",j.n. tsitsiklis,Aggregates,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
3933,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",j.n. tsitsiklis,Internet,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
3934,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",j.n. tsitsiklis,Environmental economics,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
3935,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",j.n. tsitsiklis,Nash equilibrium,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
3936,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",j.n. tsitsiklis,Peer to peer computing,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
3937,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",j.n. tsitsiklis,Computer science,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
3938,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",j.n. tsitsiklis,Routing,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
3939,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
3940,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",j.n. tsitsiklis,Telecommunication traffic,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
3941,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",elliot anshelevich,Peer to peer computing,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
3942,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",elliot anshelevich,Contracts,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
3943,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",elliot anshelevich,IP networks,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
3944,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",elliot anshelevich,Internet,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
3945,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",elliot anshelevich,Stability,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
3946,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",elliot anshelevich,Game theory,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
3947,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",elliot anshelevich,Heart,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
3948,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",elliot anshelevich,Network topology,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
3949,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",elliot anshelevich,Predictive models,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
3950,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
3951,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",elliot anshelevich,Traffic control,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
3952,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",bruce shepherd,Peer to peer computing,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
3953,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",bruce shepherd,Contracts,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
3954,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",bruce shepherd,IP networks,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
3955,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",bruce shepherd,Internet,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
3956,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",bruce shepherd,Stability,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
3957,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",bruce shepherd,Game theory,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
3958,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",bruce shepherd,Heart,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
3959,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",bruce shepherd,Network topology,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
3960,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",bruce shepherd,Predictive models,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
3961,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
3962,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
3963,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",bruce shepherd,Traffic control,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
3964,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",gordon wilfong,Peer to peer computing,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
3965,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",gordon wilfong,Contracts,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
3966,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",gordon wilfong,IP networks,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
3967,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",gordon wilfong,Internet,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
3968,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",gordon wilfong,Stability,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
3969,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",gordon wilfong,Game theory,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
3970,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",gordon wilfong,Heart,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
3971,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",gordon wilfong,Network topology,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
3972,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",gordon wilfong,Predictive models,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
3973,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
3974,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",gordon wilfong,Traffic control,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
3975,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",fan bai,Wireless networks,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
3976,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",fan bai,Time division multiple access,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
3977,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",fan bai,Game theory,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
3978,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",fan bai,Frequency division multiaccess,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
3979,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",fan bai,Access protocols,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
3980,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",fan bai,Multiaccess communication,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
3981,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",fan bai,Radio transceivers,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
3982,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",fan bai,Media Access Protocol,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
3983,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",fan bai,Computer science,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
3984,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
3985,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",fan bai,Helium,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
3986,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",xinhua he,Wireless networks,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
3987,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",xinhua he,Time division multiple access,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
3988,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",xinhua he,Game theory,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
3989,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",xinhua he,Frequency division multiaccess,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
3990,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",xinhua he,Access protocols,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
3991,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",xinhua he,Multiaccess communication,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
3992,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",xinhua he,Radio transceivers,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
3993,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",xinhua he,Media Access Protocol,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
3994,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",xinhua he,Computer science,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
3995,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
3996,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",xinhua he,Helium,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
3997,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",wenjun li,Wireless networks,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
3998,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",wenjun li,Time division multiple access,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
3999,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",wenjun li,Game theory,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
4000,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",wenjun li,Frequency division multiaccess,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
4001,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",wenjun li,Access protocols,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
4002,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",wenjun li,Multiaccess communication,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
4003,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",wenjun li,Radio transceivers,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
4004,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",wenjun li,Media Access Protocol,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
4005,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",wenjun li,Computer science,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
4006,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4007,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",wenjun li,Helium,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
4008,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",hyeryung jang,CSMA,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
4009,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",hyeryung jang,distributed algorithms,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
4010,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",hyeryung jang,game theory,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
4011,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",hyeryung jang,wireless ad-hoc network,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
4012,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",hyeryung jang,stochastic approximation,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
4013,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",se-young yun,CSMA,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
4014,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",se-young yun,distributed algorithms,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
4015,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",se-young yun,game theory,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
4016,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",se-young yun,wireless ad-hoc network,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
4017,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4018,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",se-young yun,stochastic approximation,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
4019,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",jinwoo shin,CSMA,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
4020,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",jinwoo shin,distributed algorithms,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
4021,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",jinwoo shin,game theory,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
4022,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",jinwoo shin,wireless ad-hoc network,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
4023,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",jinwoo shin,stochastic approximation,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
4024,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",yung yi,CSMA,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
4025,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",yung yi,distributed algorithms,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
4026,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",yung yi,game theory,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
4027,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",yung yi,wireless ad-hoc network,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
4028,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4029,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",yung yi,stochastic approximation,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
4030,"This paper discusses a special type of multi-user communication scenario, in which users' utilities are linearly impacted by their competitors' actions. First, we explicitly characterize the Nash equilibrium and Pareto boundary of the achievable utility region. Second, the price of anarchy incurred by the non-collaborative Nash strategy is quantified. Third, to improve the performance in the non-cooperative scenarios, we investigate the properties of an alternative solution concept named conjectural equilibrium, in which individual users compensate for their lack of information by forming internal beliefs about their competitors. The global convergence of the best response and Jacobi update dynamics that achieve various conjectural equilibria is analyzed. It is shown that the Pareto boundaries of the investigated linearly coupled games can be sustained as stable conjectural equilibria if the belief functions are properly initialized. The investigated models apply to a variety of realistic applications encountered in the multiple access design, including wireless random access and flow control.",yi su,Nash equilibrium,2011.0,10.1109/TCOMM.2011.062111.090417,IEEE Transactions on Communications,Su2011,False,,IEEE,Not available,Linearly Coupled Communication Games,f0dfc5e3d6f04d4e03bb40448e923854,https://ieeexplore.ieee.org/document/5934673/
4031,"This paper discusses a special type of multi-user communication scenario, in which users' utilities are linearly impacted by their competitors' actions. First, we explicitly characterize the Nash equilibrium and Pareto boundary of the achievable utility region. Second, the price of anarchy incurred by the non-collaborative Nash strategy is quantified. Third, to improve the performance in the non-cooperative scenarios, we investigate the properties of an alternative solution concept named conjectural equilibrium, in which individual users compensate for their lack of information by forming internal beliefs about their competitors. The global convergence of the best response and Jacobi update dynamics that achieve various conjectural equilibria is analyzed. It is shown that the Pareto boundaries of the investigated linearly coupled games can be sustained as stable conjectural equilibria if the belief functions are properly initialized. The investigated models apply to a variety of realistic applications encountered in the multiple access design, including wireless random access and flow control.",yi su,Pareto-optimality,2011.0,10.1109/TCOMM.2011.062111.090417,IEEE Transactions on Communications,Su2011,False,,IEEE,Not available,Linearly Coupled Communication Games,f0dfc5e3d6f04d4e03bb40448e923854,https://ieeexplore.ieee.org/document/5934673/
4032,"This paper discusses a special type of multi-user communication scenario, in which users' utilities are linearly impacted by their competitors' actions. First, we explicitly characterize the Nash equilibrium and Pareto boundary of the achievable utility region. Second, the price of anarchy incurred by the non-collaborative Nash strategy is quantified. Third, to improve the performance in the non-cooperative scenarios, we investigate the properties of an alternative solution concept named conjectural equilibrium, in which individual users compensate for their lack of information by forming internal beliefs about their competitors. The global convergence of the best response and Jacobi update dynamics that achieve various conjectural equilibria is analyzed. It is shown that the Pareto boundaries of the investigated linearly coupled games can be sustained as stable conjectural equilibria if the belief functions are properly initialized. The investigated models apply to a variety of realistic applications encountered in the multiple access design, including wireless random access and flow control.",yi su,conjectural equilibrium,2011.0,10.1109/TCOMM.2011.062111.090417,IEEE Transactions on Communications,Su2011,False,,IEEE,Not available,Linearly Coupled Communication Games,f0dfc5e3d6f04d4e03bb40448e923854,https://ieeexplore.ieee.org/document/5934673/
4033,"This paper discusses a special type of multi-user communication scenario, in which users' utilities are linearly impacted by their competitors' actions. First, we explicitly characterize the Nash equilibrium and Pareto boundary of the achievable utility region. Second, the price of anarchy incurred by the non-collaborative Nash strategy is quantified. Third, to improve the performance in the non-cooperative scenarios, we investigate the properties of an alternative solution concept named conjectural equilibrium, in which individual users compensate for their lack of information by forming internal beliefs about their competitors. The global convergence of the best response and Jacobi update dynamics that achieve various conjectural equilibria is analyzed. It is shown that the Pareto boundaries of the investigated linearly coupled games can be sustained as stable conjectural equilibria if the belief functions are properly initialized. The investigated models apply to a variety of realistic applications encountered in the multiple access design, including wireless random access and flow control.",yi su,non-cooperative games,2011.0,10.1109/TCOMM.2011.062111.090417,IEEE Transactions on Communications,Su2011,False,,IEEE,Not available,Linearly Coupled Communication Games,f0dfc5e3d6f04d4e03bb40448e923854,https://ieeexplore.ieee.org/document/5934673/
4034,"This paper discusses a special type of multi-user communication scenario, in which users' utilities are linearly impacted by their competitors' actions. First, we explicitly characterize the Nash equilibrium and Pareto boundary of the achievable utility region. Second, the price of anarchy incurred by the non-collaborative Nash strategy is quantified. Third, to improve the performance in the non-cooperative scenarios, we investigate the properties of an alternative solution concept named conjectural equilibrium, in which individual users compensate for their lack of information by forming internal beliefs about their competitors. The global convergence of the best response and Jacobi update dynamics that achieve various conjectural equilibria is analyzed. It is shown that the Pareto boundaries of the investigated linearly coupled games can be sustained as stable conjectural equilibria if the belief functions are properly initialized. The investigated models apply to a variety of realistic applications encountered in the multiple access design, including wireless random access and flow control.",mihaela schaar,Nash equilibrium,2011.0,10.1109/TCOMM.2011.062111.090417,IEEE Transactions on Communications,Su2011,False,,IEEE,Not available,Linearly Coupled Communication Games,f0dfc5e3d6f04d4e03bb40448e923854,https://ieeexplore.ieee.org/document/5934673/
4035,"This paper discusses a special type of multi-user communication scenario, in which users' utilities are linearly impacted by their competitors' actions. First, we explicitly characterize the Nash equilibrium and Pareto boundary of the achievable utility region. Second, the price of anarchy incurred by the non-collaborative Nash strategy is quantified. Third, to improve the performance in the non-cooperative scenarios, we investigate the properties of an alternative solution concept named conjectural equilibrium, in which individual users compensate for their lack of information by forming internal beliefs about their competitors. The global convergence of the best response and Jacobi update dynamics that achieve various conjectural equilibria is analyzed. It is shown that the Pareto boundaries of the investigated linearly coupled games can be sustained as stable conjectural equilibria if the belief functions are properly initialized. The investigated models apply to a variety of realistic applications encountered in the multiple access design, including wireless random access and flow control.",mihaela schaar,Pareto-optimality,2011.0,10.1109/TCOMM.2011.062111.090417,IEEE Transactions on Communications,Su2011,False,,IEEE,Not available,Linearly Coupled Communication Games,f0dfc5e3d6f04d4e03bb40448e923854,https://ieeexplore.ieee.org/document/5934673/
4036,"This paper discusses a special type of multi-user communication scenario, in which users' utilities are linearly impacted by their competitors' actions. First, we explicitly characterize the Nash equilibrium and Pareto boundary of the achievable utility region. Second, the price of anarchy incurred by the non-collaborative Nash strategy is quantified. Third, to improve the performance in the non-cooperative scenarios, we investigate the properties of an alternative solution concept named conjectural equilibrium, in which individual users compensate for their lack of information by forming internal beliefs about their competitors. The global convergence of the best response and Jacobi update dynamics that achieve various conjectural equilibria is analyzed. It is shown that the Pareto boundaries of the investigated linearly coupled games can be sustained as stable conjectural equilibria if the belief functions are properly initialized. The investigated models apply to a variety of realistic applications encountered in the multiple access design, including wireless random access and flow control.",mihaela schaar,conjectural equilibrium,2011.0,10.1109/TCOMM.2011.062111.090417,IEEE Transactions on Communications,Su2011,False,,IEEE,Not available,Linearly Coupled Communication Games,f0dfc5e3d6f04d4e03bb40448e923854,https://ieeexplore.ieee.org/document/5934673/
4037,"This paper discusses a special type of multi-user communication scenario, in which users' utilities are linearly impacted by their competitors' actions. First, we explicitly characterize the Nash equilibrium and Pareto boundary of the achievable utility region. Second, the price of anarchy incurred by the non-collaborative Nash strategy is quantified. Third, to improve the performance in the non-cooperative scenarios, we investigate the properties of an alternative solution concept named conjectural equilibrium, in which individual users compensate for their lack of information by forming internal beliefs about their competitors. The global convergence of the best response and Jacobi update dynamics that achieve various conjectural equilibria is analyzed. It is shown that the Pareto boundaries of the investigated linearly coupled games can be sustained as stable conjectural equilibria if the belief functions are properly initialized. The investigated models apply to a variety of realistic applications encountered in the multiple access design, including wireless random access and flow control.",mihaela schaar,non-cooperative games,2011.0,10.1109/TCOMM.2011.062111.090417,IEEE Transactions on Communications,Su2011,False,,IEEE,Not available,Linearly Coupled Communication Games,f0dfc5e3d6f04d4e03bb40448e923854,https://ieeexplore.ieee.org/document/5934673/
4038,"We study a dynamic random access game with a finite number of opportunities for transmission and with energy constraints. We provide sufficient conditions for feasible strategies and for existence of Nash-Pareto solutions and show that finding Nash-Pareto policies of the dynamic random access game is equivalent to partitioning the set of time slot opportunities with constraints into a set of terminals. We further derive upper bounds for pure Nash-Pareto policies, and extend the study to non-integer energy constraints and unknown termination time, where time division multiplexing policies can be suboptimal. We show that the dynamic random access game has several strong equilibria (resilient to coalition of any size), and we compute them explicitly. We introduce the (strong) price of anarchy concept to measure the gap between the payoff under strong equilibria and the social optimum.",eitan altman,Dynamic game,2009.0,10.1109/WIOPT.2009.5291611,"2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Altman2009,False,,IEEE,Not available,A dynamic random access game with energy constraints,4eb2d71138fc92f3f433cb60a9b9bed6,https://ieeexplore.ieee.org/document/5291611/
4039,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4040,"We study a dynamic random access game with a finite number of opportunities for transmission and with energy constraints. We provide sufficient conditions for feasible strategies and for existence of Nash-Pareto solutions and show that finding Nash-Pareto policies of the dynamic random access game is equivalent to partitioning the set of time slot opportunities with constraints into a set of terminals. We further derive upper bounds for pure Nash-Pareto policies, and extend the study to non-integer energy constraints and unknown termination time, where time division multiplexing policies can be suboptimal. We show that the dynamic random access game has several strong equilibria (resilient to coalition of any size), and we compute them explicitly. We introduce the (strong) price of anarchy concept to measure the gap between the payoff under strong equilibria and the social optimum.",eitan altman,multiple access control,2009.0,10.1109/WIOPT.2009.5291611,"2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Altman2009,False,,IEEE,Not available,A dynamic random access game with energy constraints,4eb2d71138fc92f3f433cb60a9b9bed6,https://ieeexplore.ieee.org/document/5291611/
4041,"We study a dynamic random access game with a finite number of opportunities for transmission and with energy constraints. We provide sufficient conditions for feasible strategies and for existence of Nash-Pareto solutions and show that finding Nash-Pareto policies of the dynamic random access game is equivalent to partitioning the set of time slot opportunities with constraints into a set of terminals. We further derive upper bounds for pure Nash-Pareto policies, and extend the study to non-integer energy constraints and unknown termination time, where time division multiplexing policies can be suboptimal. We show that the dynamic random access game has several strong equilibria (resilient to coalition of any size), and we compute them explicitly. We introduce the (strong) price of anarchy concept to measure the gap between the payoff under strong equilibria and the social optimum.",eitan altman,strong equilibria,2009.0,10.1109/WIOPT.2009.5291611,"2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Altman2009,False,,IEEE,Not available,A dynamic random access game with energy constraints,4eb2d71138fc92f3f433cb60a9b9bed6,https://ieeexplore.ieee.org/document/5291611/
4042,"We study a dynamic random access game with a finite number of opportunities for transmission and with energy constraints. We provide sufficient conditions for feasible strategies and for existence of Nash-Pareto solutions and show that finding Nash-Pareto policies of the dynamic random access game is equivalent to partitioning the set of time slot opportunities with constraints into a set of terminals. We further derive upper bounds for pure Nash-Pareto policies, and extend the study to non-integer energy constraints and unknown termination time, where time division multiplexing policies can be suboptimal. We show that the dynamic random access game has several strong equilibria (resilient to coalition of any size), and we compute them explicitly. We introduce the (strong) price of anarchy concept to measure the gap between the payoff under strong equilibria and the social optimum.",eitan altman,TDM policy,2009.0,10.1109/WIOPT.2009.5291611,"2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Altman2009,False,,IEEE,Not available,A dynamic random access game with energy constraints,4eb2d71138fc92f3f433cb60a9b9bed6,https://ieeexplore.ieee.org/document/5291611/
4043,"We study a dynamic random access game with a finite number of opportunities for transmission and with energy constraints. We provide sufficient conditions for feasible strategies and for existence of Nash-Pareto solutions and show that finding Nash-Pareto policies of the dynamic random access game is equivalent to partitioning the set of time slot opportunities with constraints into a set of terminals. We further derive upper bounds for pure Nash-Pareto policies, and extend the study to non-integer energy constraints and unknown termination time, where time division multiplexing policies can be suboptimal. We show that the dynamic random access game has several strong equilibria (resilient to coalition of any size), and we compute them explicitly. We introduce the (strong) price of anarchy concept to measure the gap between the payoff under strong equilibria and the social optimum.",tamer basar,Dynamic game,2009.0,10.1109/WIOPT.2009.5291611,"2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Altman2009,False,,IEEE,Not available,A dynamic random access game with energy constraints,4eb2d71138fc92f3f433cb60a9b9bed6,https://ieeexplore.ieee.org/document/5291611/
4044,"We study a dynamic random access game with a finite number of opportunities for transmission and with energy constraints. We provide sufficient conditions for feasible strategies and for existence of Nash-Pareto solutions and show that finding Nash-Pareto policies of the dynamic random access game is equivalent to partitioning the set of time slot opportunities with constraints into a set of terminals. We further derive upper bounds for pure Nash-Pareto policies, and extend the study to non-integer energy constraints and unknown termination time, where time division multiplexing policies can be suboptimal. We show that the dynamic random access game has several strong equilibria (resilient to coalition of any size), and we compute them explicitly. We introduce the (strong) price of anarchy concept to measure the gap between the payoff under strong equilibria and the social optimum.",tamer basar,multiple access control,2009.0,10.1109/WIOPT.2009.5291611,"2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Altman2009,False,,IEEE,Not available,A dynamic random access game with energy constraints,4eb2d71138fc92f3f433cb60a9b9bed6,https://ieeexplore.ieee.org/document/5291611/
4045,"We study a dynamic random access game with a finite number of opportunities for transmission and with energy constraints. We provide sufficient conditions for feasible strategies and for existence of Nash-Pareto solutions and show that finding Nash-Pareto policies of the dynamic random access game is equivalent to partitioning the set of time slot opportunities with constraints into a set of terminals. We further derive upper bounds for pure Nash-Pareto policies, and extend the study to non-integer energy constraints and unknown termination time, where time division multiplexing policies can be suboptimal. We show that the dynamic random access game has several strong equilibria (resilient to coalition of any size), and we compute them explicitly. We introduce the (strong) price of anarchy concept to measure the gap between the payoff under strong equilibria and the social optimum.",tamer basar,strong equilibria,2009.0,10.1109/WIOPT.2009.5291611,"2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Altman2009,False,,IEEE,Not available,A dynamic random access game with energy constraints,4eb2d71138fc92f3f433cb60a9b9bed6,https://ieeexplore.ieee.org/document/5291611/
4046,"We study a dynamic random access game with a finite number of opportunities for transmission and with energy constraints. We provide sufficient conditions for feasible strategies and for existence of Nash-Pareto solutions and show that finding Nash-Pareto policies of the dynamic random access game is equivalent to partitioning the set of time slot opportunities with constraints into a set of terminals. We further derive upper bounds for pure Nash-Pareto policies, and extend the study to non-integer energy constraints and unknown termination time, where time division multiplexing policies can be suboptimal. We show that the dynamic random access game has several strong equilibria (resilient to coalition of any size), and we compute them explicitly. We introduce the (strong) price of anarchy concept to measure the gap between the payoff under strong equilibria and the social optimum.",tamer basar,TDM policy,2009.0,10.1109/WIOPT.2009.5291611,"2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Altman2009,False,,IEEE,Not available,A dynamic random access game with energy constraints,4eb2d71138fc92f3f433cb60a9b9bed6,https://ieeexplore.ieee.org/document/5291611/
4047,"We study a dynamic random access game with a finite number of opportunities for transmission and with energy constraints. We provide sufficient conditions for feasible strategies and for existence of Nash-Pareto solutions and show that finding Nash-Pareto policies of the dynamic random access game is equivalent to partitioning the set of time slot opportunities with constraints into a set of terminals. We further derive upper bounds for pure Nash-Pareto policies, and extend the study to non-integer energy constraints and unknown termination time, where time division multiplexing policies can be suboptimal. We show that the dynamic random access game has several strong equilibria (resilient to coalition of any size), and we compute them explicitly. We introduce the (strong) price of anarchy concept to measure the gap between the payoff under strong equilibria and the social optimum.",ishai menache,Dynamic game,2009.0,10.1109/WIOPT.2009.5291611,"2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Altman2009,False,,IEEE,Not available,A dynamic random access game with energy constraints,4eb2d71138fc92f3f433cb60a9b9bed6,https://ieeexplore.ieee.org/document/5291611/
4048,"We study a dynamic random access game with a finite number of opportunities for transmission and with energy constraints. We provide sufficient conditions for feasible strategies and for existence of Nash-Pareto solutions and show that finding Nash-Pareto policies of the dynamic random access game is equivalent to partitioning the set of time slot opportunities with constraints into a set of terminals. We further derive upper bounds for pure Nash-Pareto policies, and extend the study to non-integer energy constraints and unknown termination time, where time division multiplexing policies can be suboptimal. We show that the dynamic random access game has several strong equilibria (resilient to coalition of any size), and we compute them explicitly. We introduce the (strong) price of anarchy concept to measure the gap between the payoff under strong equilibria and the social optimum.",ishai menache,multiple access control,2009.0,10.1109/WIOPT.2009.5291611,"2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Altman2009,False,,IEEE,Not available,A dynamic random access game with energy constraints,4eb2d71138fc92f3f433cb60a9b9bed6,https://ieeexplore.ieee.org/document/5291611/
4049,"We study a dynamic random access game with a finite number of opportunities for transmission and with energy constraints. We provide sufficient conditions for feasible strategies and for existence of Nash-Pareto solutions and show that finding Nash-Pareto policies of the dynamic random access game is equivalent to partitioning the set of time slot opportunities with constraints into a set of terminals. We further derive upper bounds for pure Nash-Pareto policies, and extend the study to non-integer energy constraints and unknown termination time, where time division multiplexing policies can be suboptimal. We show that the dynamic random access game has several strong equilibria (resilient to coalition of any size), and we compute them explicitly. We introduce the (strong) price of anarchy concept to measure the gap between the payoff under strong equilibria and the social optimum.",ishai menache,strong equilibria,2009.0,10.1109/WIOPT.2009.5291611,"2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Altman2009,False,,IEEE,Not available,A dynamic random access game with energy constraints,4eb2d71138fc92f3f433cb60a9b9bed6,https://ieeexplore.ieee.org/document/5291611/
4050,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
4051,"We study a dynamic random access game with a finite number of opportunities for transmission and with energy constraints. We provide sufficient conditions for feasible strategies and for existence of Nash-Pareto solutions and show that finding Nash-Pareto policies of the dynamic random access game is equivalent to partitioning the set of time slot opportunities with constraints into a set of terminals. We further derive upper bounds for pure Nash-Pareto policies, and extend the study to non-integer energy constraints and unknown termination time, where time division multiplexing policies can be suboptimal. We show that the dynamic random access game has several strong equilibria (resilient to coalition of any size), and we compute them explicitly. We introduce the (strong) price of anarchy concept to measure the gap between the payoff under strong equilibria and the social optimum.",ishai menache,TDM policy,2009.0,10.1109/WIOPT.2009.5291611,"2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Altman2009,False,,IEEE,Not available,A dynamic random access game with energy constraints,4eb2d71138fc92f3f433cb60a9b9bed6,https://ieeexplore.ieee.org/document/5291611/
4052,"We study a dynamic random access game with a finite number of opportunities for transmission and with energy constraints. We provide sufficient conditions for feasible strategies and for existence of Nash-Pareto solutions and show that finding Nash-Pareto policies of the dynamic random access game is equivalent to partitioning the set of time slot opportunities with constraints into a set of terminals. We further derive upper bounds for pure Nash-Pareto policies, and extend the study to non-integer energy constraints and unknown termination time, where time division multiplexing policies can be suboptimal. We show that the dynamic random access game has several strong equilibria (resilient to coalition of any size), and we compute them explicitly. We introduce the (strong) price of anarchy concept to measure the gap between the payoff under strong equilibria and the social optimum.",hamidou tembine,Dynamic game,2009.0,10.1109/WIOPT.2009.5291611,"2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Altman2009,False,,IEEE,Not available,A dynamic random access game with energy constraints,4eb2d71138fc92f3f433cb60a9b9bed6,https://ieeexplore.ieee.org/document/5291611/
4053,"We study a dynamic random access game with a finite number of opportunities for transmission and with energy constraints. We provide sufficient conditions for feasible strategies and for existence of Nash-Pareto solutions and show that finding Nash-Pareto policies of the dynamic random access game is equivalent to partitioning the set of time slot opportunities with constraints into a set of terminals. We further derive upper bounds for pure Nash-Pareto policies, and extend the study to non-integer energy constraints and unknown termination time, where time division multiplexing policies can be suboptimal. We show that the dynamic random access game has several strong equilibria (resilient to coalition of any size), and we compute them explicitly. We introduce the (strong) price of anarchy concept to measure the gap between the payoff under strong equilibria and the social optimum.",hamidou tembine,multiple access control,2009.0,10.1109/WIOPT.2009.5291611,"2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Altman2009,False,,IEEE,Not available,A dynamic random access game with energy constraints,4eb2d71138fc92f3f433cb60a9b9bed6,https://ieeexplore.ieee.org/document/5291611/
4054,"We study a dynamic random access game with a finite number of opportunities for transmission and with energy constraints. We provide sufficient conditions for feasible strategies and for existence of Nash-Pareto solutions and show that finding Nash-Pareto policies of the dynamic random access game is equivalent to partitioning the set of time slot opportunities with constraints into a set of terminals. We further derive upper bounds for pure Nash-Pareto policies, and extend the study to non-integer energy constraints and unknown termination time, where time division multiplexing policies can be suboptimal. We show that the dynamic random access game has several strong equilibria (resilient to coalition of any size), and we compute them explicitly. We introduce the (strong) price of anarchy concept to measure the gap between the payoff under strong equilibria and the social optimum.",hamidou tembine,strong equilibria,2009.0,10.1109/WIOPT.2009.5291611,"2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Altman2009,False,,IEEE,Not available,A dynamic random access game with energy constraints,4eb2d71138fc92f3f433cb60a9b9bed6,https://ieeexplore.ieee.org/document/5291611/
4055,"We study a dynamic random access game with a finite number of opportunities for transmission and with energy constraints. We provide sufficient conditions for feasible strategies and for existence of Nash-Pareto solutions and show that finding Nash-Pareto policies of the dynamic random access game is equivalent to partitioning the set of time slot opportunities with constraints into a set of terminals. We further derive upper bounds for pure Nash-Pareto policies, and extend the study to non-integer energy constraints and unknown termination time, where time division multiplexing policies can be suboptimal. We show that the dynamic random access game has several strong equilibria (resilient to coalition of any size), and we compute them explicitly. We introduce the (strong) price of anarchy concept to measure the gap between the payoff under strong equilibria and the social optimum.",hamidou tembine,TDM policy,2009.0,10.1109/WIOPT.2009.5291611,"2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Altman2009,False,,IEEE,Not available,A dynamic random access game with energy constraints,4eb2d71138fc92f3f433cb60a9b9bed6,https://ieeexplore.ieee.org/document/5291611/
4056,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",v.s. kumar,Approximation algorithms,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4057,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",v.s. kumar,Game theory,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4058,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",v.s. kumar,Costs,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4059,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",v.s. kumar,Information security,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4060,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",v.s. kumar,Computer viruses,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4061,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
4062,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",v.s. kumar,Computer worms,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4063,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",v.s. kumar,Protection,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4064,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",v.s. kumar,Distributed computing,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4065,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",v.s. kumar,Sun,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4066,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",v.s. kumar,Computer networks,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4067,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",rajmohan rajaraman,Approximation algorithms,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4068,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",rajmohan rajaraman,Game theory,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4069,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",rajmohan rajaraman,Costs,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4070,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",rajmohan rajaraman,Information security,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4071,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",rajmohan rajaraman,Computer viruses,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4072,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
4073,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
4074,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",rajmohan rajaraman,Computer worms,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4075,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",rajmohan rajaraman,Protection,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4076,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",rajmohan rajaraman,Distributed computing,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4077,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",rajmohan rajaraman,Sun,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4078,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",rajmohan rajaraman,Computer networks,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4079,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",zhifeng sun,Approximation algorithms,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4080,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",zhifeng sun,Game theory,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4081,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",zhifeng sun,Costs,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4082,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",zhifeng sun,Information security,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4083,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",zhifeng sun,Computer viruses,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4084,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
4085,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",zhifeng sun,Computer worms,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4086,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",zhifeng sun,Protection,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4087,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",zhifeng sun,Distributed computing,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4088,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",zhifeng sun,Sun,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4089,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",zhifeng sun,Computer networks,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4090,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",ravi sundaram,Approximation algorithms,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4091,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",ravi sundaram,Game theory,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4092,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",ravi sundaram,Costs,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4093,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",ravi sundaram,Information security,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4094,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",ravi sundaram,Computer viruses,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4095,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
4096,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",ravi sundaram,Computer worms,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4097,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",ravi sundaram,Protection,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4098,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",ravi sundaram,Distributed computing,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4099,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",ravi sundaram,Sun,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4100,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",ravi sundaram,Computer networks,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
4101,"In this paper, we address the problem of minimizing the energy cost of positioning nodes in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a two-fold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is supermodular and that it possesses a unique Nash equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",ana moragrega,Distributed algorithms,2013.0,10.1109/TSP.2013.2259160,IEEE Transactions on Signal Processing,Moragrega2013,False,,IEEE,Not available,Supermodular Game for Power Control in TOA-Based Positioning,cdba3d719214dc4acde5c4a909b15190,https://ieeexplore.ieee.org/document/6506112/
4102,"In this paper, we address the problem of minimizing the energy cost of positioning nodes in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a two-fold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is supermodular and that it possesses a unique Nash equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",ana moragrega,game theory,2013.0,10.1109/TSP.2013.2259160,IEEE Transactions on Signal Processing,Moragrega2013,False,,IEEE,Not available,Supermodular Game for Power Control in TOA-Based Positioning,cdba3d719214dc4acde5c4a909b15190,https://ieeexplore.ieee.org/document/6506112/
4103,"In this paper, we address the problem of minimizing the energy cost of positioning nodes in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a two-fold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is supermodular and that it possesses a unique Nash equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",ana moragrega,positioning,2013.0,10.1109/TSP.2013.2259160,IEEE Transactions on Signal Processing,Moragrega2013,False,,IEEE,Not available,Supermodular Game for Power Control in TOA-Based Positioning,cdba3d719214dc4acde5c4a909b15190,https://ieeexplore.ieee.org/document/6506112/
4104,"In this paper, we address the problem of minimizing the energy cost of positioning nodes in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a two-fold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is supermodular and that it possesses a unique Nash equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",ana moragrega,supermodular games,2013.0,10.1109/TSP.2013.2259160,IEEE Transactions on Signal Processing,Moragrega2013,False,,IEEE,Not available,Supermodular Game for Power Control in TOA-Based Positioning,cdba3d719214dc4acde5c4a909b15190,https://ieeexplore.ieee.org/document/6506112/
4105,"In this paper, we address the problem of minimizing the energy cost of positioning nodes in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a two-fold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is supermodular and that it possesses a unique Nash equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",ana moragrega,wireless sensor networks,2013.0,10.1109/TSP.2013.2259160,IEEE Transactions on Signal Processing,Moragrega2013,False,,IEEE,Not available,Supermodular Game for Power Control in TOA-Based Positioning,cdba3d719214dc4acde5c4a909b15190,https://ieeexplore.ieee.org/document/6506112/
4106,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
4107,"In this paper, we address the problem of minimizing the energy cost of positioning nodes in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a two-fold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is supermodular and that it possesses a unique Nash equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",pau closas,Distributed algorithms,2013.0,10.1109/TSP.2013.2259160,IEEE Transactions on Signal Processing,Moragrega2013,False,,IEEE,Not available,Supermodular Game for Power Control in TOA-Based Positioning,cdba3d719214dc4acde5c4a909b15190,https://ieeexplore.ieee.org/document/6506112/
4108,"In this paper, we address the problem of minimizing the energy cost of positioning nodes in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a two-fold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is supermodular and that it possesses a unique Nash equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",pau closas,game theory,2013.0,10.1109/TSP.2013.2259160,IEEE Transactions on Signal Processing,Moragrega2013,False,,IEEE,Not available,Supermodular Game for Power Control in TOA-Based Positioning,cdba3d719214dc4acde5c4a909b15190,https://ieeexplore.ieee.org/document/6506112/
4109,"In this paper, we address the problem of minimizing the energy cost of positioning nodes in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a two-fold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is supermodular and that it possesses a unique Nash equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",pau closas,positioning,2013.0,10.1109/TSP.2013.2259160,IEEE Transactions on Signal Processing,Moragrega2013,False,,IEEE,Not available,Supermodular Game for Power Control in TOA-Based Positioning,cdba3d719214dc4acde5c4a909b15190,https://ieeexplore.ieee.org/document/6506112/
4110,"In this paper, we address the problem of minimizing the energy cost of positioning nodes in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a two-fold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is supermodular and that it possesses a unique Nash equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",pau closas,supermodular games,2013.0,10.1109/TSP.2013.2259160,IEEE Transactions on Signal Processing,Moragrega2013,False,,IEEE,Not available,Supermodular Game for Power Control in TOA-Based Positioning,cdba3d719214dc4acde5c4a909b15190,https://ieeexplore.ieee.org/document/6506112/
4111,"In this paper, we address the problem of minimizing the energy cost of positioning nodes in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a two-fold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is supermodular and that it possesses a unique Nash equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",pau closas,wireless sensor networks,2013.0,10.1109/TSP.2013.2259160,IEEE Transactions on Signal Processing,Moragrega2013,False,,IEEE,Not available,Supermodular Game for Power Control in TOA-Based Positioning,cdba3d719214dc4acde5c4a909b15190,https://ieeexplore.ieee.org/document/6506112/
4112,"In this paper, we address the problem of minimizing the energy cost of positioning nodes in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a two-fold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is supermodular and that it possesses a unique Nash equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",christian ibars,Distributed algorithms,2013.0,10.1109/TSP.2013.2259160,IEEE Transactions on Signal Processing,Moragrega2013,False,,IEEE,Not available,Supermodular Game for Power Control in TOA-Based Positioning,cdba3d719214dc4acde5c4a909b15190,https://ieeexplore.ieee.org/document/6506112/
4113,"In this paper, we address the problem of minimizing the energy cost of positioning nodes in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a two-fold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is supermodular and that it possesses a unique Nash equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",christian ibars,game theory,2013.0,10.1109/TSP.2013.2259160,IEEE Transactions on Signal Processing,Moragrega2013,False,,IEEE,Not available,Supermodular Game for Power Control in TOA-Based Positioning,cdba3d719214dc4acde5c4a909b15190,https://ieeexplore.ieee.org/document/6506112/
4114,"In this paper, we address the problem of minimizing the energy cost of positioning nodes in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a two-fold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is supermodular and that it possesses a unique Nash equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",christian ibars,positioning,2013.0,10.1109/TSP.2013.2259160,IEEE Transactions on Signal Processing,Moragrega2013,False,,IEEE,Not available,Supermodular Game for Power Control in TOA-Based Positioning,cdba3d719214dc4acde5c4a909b15190,https://ieeexplore.ieee.org/document/6506112/
4115,"In this paper, we address the problem of minimizing the energy cost of positioning nodes in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a two-fold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is supermodular and that it possesses a unique Nash equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",christian ibars,supermodular games,2013.0,10.1109/TSP.2013.2259160,IEEE Transactions on Signal Processing,Moragrega2013,False,,IEEE,Not available,Supermodular Game for Power Control in TOA-Based Positioning,cdba3d719214dc4acde5c4a909b15190,https://ieeexplore.ieee.org/document/6506112/
4116,"In this paper, we address the problem of minimizing the energy cost of positioning nodes in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a two-fold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is supermodular and that it possesses a unique Nash equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",christian ibars,wireless sensor networks,2013.0,10.1109/TSP.2013.2259160,IEEE Transactions on Signal Processing,Moragrega2013,False,,IEEE,Not available,Supermodular Game for Power Control in TOA-Based Positioning,cdba3d719214dc4acde5c4a909b15190,https://ieeexplore.ieee.org/document/6506112/
4117,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
4118,"This paper studies the problem of content distribution in wireless peer-to-peer networks with selfish nodes. In this problem a group of wireless nodes exchange data over a lossless broadcast channel. Each node aims to increase its own download rate and minimize its upload rate. We propose a distributed protocol that provides incentives for the nodes to participate in the content distribution. Our protocol does not require any exchange of money, reputation, etc., and hence can be easily implemented without additional infrastructure. Moreover, our protocol can be easily modified to employ network coding. Focusing on the important case in which the system contains two files that need to be distributed, we derive a closed-form expression of Nash Equilibria. We also derive the prices of anarchy, both from each node's perspective and the whole system's perspective. Furthermore, we propose a distributed mechanism where the strategy of each node is only based on the local information and show that the mechanism converges to a Nash Equilibrium. We also introduce an approach for calculating Nash Equilibria for systems that incorporate network coding when more than two files need to be distributed.",i-hong hou,Encoding,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Hou2013,False,,IEEE,Not available,A non-monetary protocol for peer-to-peer content distribution in wireless broadcast networks with network coding,6f0349238813aa9ecf23742874393812,https://ieeexplore.ieee.org/document/6576431/
4119,"This paper studies the problem of content distribution in wireless peer-to-peer networks with selfish nodes. In this problem a group of wireless nodes exchange data over a lossless broadcast channel. Each node aims to increase its own download rate and minimize its upload rate. We propose a distributed protocol that provides incentives for the nodes to participate in the content distribution. Our protocol does not require any exchange of money, reputation, etc., and hence can be easily implemented without additional infrastructure. Moreover, our protocol can be easily modified to employ network coding. Focusing on the important case in which the system contains two files that need to be distributed, we derive a closed-form expression of Nash Equilibria. We also derive the prices of anarchy, both from each node's perspective and the whole system's perspective. Furthermore, we propose a distributed mechanism where the strategy of each node is only based on the local information and show that the mechanism converges to a Nash Equilibrium. We also introduce an approach for calculating Nash Equilibria for systems that incorporate network coding when more than two files need to be distributed.",i-hong hou,Wireless communication,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Hou2013,False,,IEEE,Not available,A non-monetary protocol for peer-to-peer content distribution in wireless broadcast networks with network coding,6f0349238813aa9ecf23742874393812,https://ieeexplore.ieee.org/document/6576431/
4120,"This paper studies the problem of content distribution in wireless peer-to-peer networks with selfish nodes. In this problem a group of wireless nodes exchange data over a lossless broadcast channel. Each node aims to increase its own download rate and minimize its upload rate. We propose a distributed protocol that provides incentives for the nodes to participate in the content distribution. Our protocol does not require any exchange of money, reputation, etc., and hence can be easily implemented without additional infrastructure. Moreover, our protocol can be easily modified to employ network coding. Focusing on the important case in which the system contains two files that need to be distributed, we derive a closed-form expression of Nash Equilibria. We also derive the prices of anarchy, both from each node's perspective and the whole system's perspective. Furthermore, we propose a distributed mechanism where the strategy of each node is only based on the local information and show that the mechanism converges to a Nash Equilibrium. We also introduce an approach for calculating Nash Equilibria for systems that incorporate network coding when more than two files need to be distributed.",i-hong hou,Broadcasting,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Hou2013,False,,IEEE,Not available,A non-monetary protocol for peer-to-peer content distribution in wireless broadcast networks with network coding,6f0349238813aa9ecf23742874393812,https://ieeexplore.ieee.org/document/6576431/
4121,"This paper studies the problem of content distribution in wireless peer-to-peer networks with selfish nodes. In this problem a group of wireless nodes exchange data over a lossless broadcast channel. Each node aims to increase its own download rate and minimize its upload rate. We propose a distributed protocol that provides incentives for the nodes to participate in the content distribution. Our protocol does not require any exchange of money, reputation, etc., and hence can be easily implemented without additional infrastructure. Moreover, our protocol can be easily modified to employ network coding. Focusing on the important case in which the system contains two files that need to be distributed, we derive a closed-form expression of Nash Equilibria. We also derive the prices of anarchy, both from each node's perspective and the whole system's perspective. Furthermore, we propose a distributed mechanism where the strategy of each node is only based on the local information and show that the mechanism converges to a Nash Equilibrium. We also introduce an approach for calculating Nash Equilibria for systems that incorporate network coding when more than two files need to be distributed.",yao liu,Encoding,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Hou2013,False,,IEEE,Not available,A non-monetary protocol for peer-to-peer content distribution in wireless broadcast networks with network coding,6f0349238813aa9ecf23742874393812,https://ieeexplore.ieee.org/document/6576431/
4122,"This paper studies the problem of content distribution in wireless peer-to-peer networks with selfish nodes. In this problem a group of wireless nodes exchange data over a lossless broadcast channel. Each node aims to increase its own download rate and minimize its upload rate. We propose a distributed protocol that provides incentives for the nodes to participate in the content distribution. Our protocol does not require any exchange of money, reputation, etc., and hence can be easily implemented without additional infrastructure. Moreover, our protocol can be easily modified to employ network coding. Focusing on the important case in which the system contains two files that need to be distributed, we derive a closed-form expression of Nash Equilibria. We also derive the prices of anarchy, both from each node's perspective and the whole system's perspective. Furthermore, we propose a distributed mechanism where the strategy of each node is only based on the local information and show that the mechanism converges to a Nash Equilibrium. We also introduce an approach for calculating Nash Equilibria for systems that incorporate network coding when more than two files need to be distributed.",yao liu,Wireless communication,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Hou2013,False,,IEEE,Not available,A non-monetary protocol for peer-to-peer content distribution in wireless broadcast networks with network coding,6f0349238813aa9ecf23742874393812,https://ieeexplore.ieee.org/document/6576431/
4123,"This paper studies the problem of content distribution in wireless peer-to-peer networks with selfish nodes. In this problem a group of wireless nodes exchange data over a lossless broadcast channel. Each node aims to increase its own download rate and minimize its upload rate. We propose a distributed protocol that provides incentives for the nodes to participate in the content distribution. Our protocol does not require any exchange of money, reputation, etc., and hence can be easily implemented without additional infrastructure. Moreover, our protocol can be easily modified to employ network coding. Focusing on the important case in which the system contains two files that need to be distributed, we derive a closed-form expression of Nash Equilibria. We also derive the prices of anarchy, both from each node's perspective and the whole system's perspective. Furthermore, we propose a distributed mechanism where the strategy of each node is only based on the local information and show that the mechanism converges to a Nash Equilibrium. We also introduce an approach for calculating Nash Equilibria for systems that incorporate network coding when more than two files need to be distributed.",yao liu,Broadcasting,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Hou2013,False,,IEEE,Not available,A non-monetary protocol for peer-to-peer content distribution in wireless broadcast networks with network coding,6f0349238813aa9ecf23742874393812,https://ieeexplore.ieee.org/document/6576431/
4124,"This paper studies the problem of content distribution in wireless peer-to-peer networks with selfish nodes. In this problem a group of wireless nodes exchange data over a lossless broadcast channel. Each node aims to increase its own download rate and minimize its upload rate. We propose a distributed protocol that provides incentives for the nodes to participate in the content distribution. Our protocol does not require any exchange of money, reputation, etc., and hence can be easily implemented without additional infrastructure. Moreover, our protocol can be easily modified to employ network coding. Focusing on the important case in which the system contains two files that need to be distributed, we derive a closed-form expression of Nash Equilibria. We also derive the prices of anarchy, both from each node's perspective and the whole system's perspective. Furthermore, we propose a distributed mechanism where the strategy of each node is only based on the local information and show that the mechanism converges to a Nash Equilibrium. We also introduce an approach for calculating Nash Equilibria for systems that incorporate network coding when more than two files need to be distributed.",alex sprintson,Encoding,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Hou2013,False,,IEEE,Not available,A non-monetary protocol for peer-to-peer content distribution in wireless broadcast networks with network coding,6f0349238813aa9ecf23742874393812,https://ieeexplore.ieee.org/document/6576431/
4125,"This paper studies the problem of content distribution in wireless peer-to-peer networks with selfish nodes. In this problem a group of wireless nodes exchange data over a lossless broadcast channel. Each node aims to increase its own download rate and minimize its upload rate. We propose a distributed protocol that provides incentives for the nodes to participate in the content distribution. Our protocol does not require any exchange of money, reputation, etc., and hence can be easily implemented without additional infrastructure. Moreover, our protocol can be easily modified to employ network coding. Focusing on the important case in which the system contains two files that need to be distributed, we derive a closed-form expression of Nash Equilibria. We also derive the prices of anarchy, both from each node's perspective and the whole system's perspective. Furthermore, we propose a distributed mechanism where the strategy of each node is only based on the local information and show that the mechanism converges to a Nash Equilibrium. We also introduce an approach for calculating Nash Equilibria for systems that incorporate network coding when more than two files need to be distributed.",alex sprintson,Wireless communication,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Hou2013,False,,IEEE,Not available,A non-monetary protocol for peer-to-peer content distribution in wireless broadcast networks with network coding,6f0349238813aa9ecf23742874393812,https://ieeexplore.ieee.org/document/6576431/
4126,"This paper studies the problem of content distribution in wireless peer-to-peer networks with selfish nodes. In this problem a group of wireless nodes exchange data over a lossless broadcast channel. Each node aims to increase its own download rate and minimize its upload rate. We propose a distributed protocol that provides incentives for the nodes to participate in the content distribution. Our protocol does not require any exchange of money, reputation, etc., and hence can be easily implemented without additional infrastructure. Moreover, our protocol can be easily modified to employ network coding. Focusing on the important case in which the system contains two files that need to be distributed, we derive a closed-form expression of Nash Equilibria. We also derive the prices of anarchy, both from each node's perspective and the whole system's perspective. Furthermore, we propose a distributed mechanism where the strategy of each node is only based on the local information and show that the mechanism converges to a Nash Equilibrium. We also introduce an approach for calculating Nash Equilibria for systems that incorporate network coding when more than two files need to be distributed.",alex sprintson,Broadcasting,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Hou2013,False,,IEEE,Not available,A non-monetary protocol for peer-to-peer content distribution in wireless broadcast networks with network coding,6f0349238813aa9ecf23742874393812,https://ieeexplore.ieee.org/document/6576431/
4127,"The network function virtualization (NFV) paradigm has gained increasing interest in both academia and industry as it promises scalable and flexible network management and orchestration. In NFV networks, network services are provided as chains of different virtual network functions (VNFs), which are instantiated and executed on dedicated VNF-compliant servers. The problem of composing those chains is referred to as the service chain composition problem. In contrast to centralized solutions that suffer from scalability and privacy issues, in this paper, we leverage non-cooperative game theory to achieve a low-complexity distributed solution to the above-mentioned problem. Specifically, to account for selfish and competitive behavior of users, we formulate the service chain composition problem as an atomic weighted congestion game with unsplittable flows and player-specific cost functions. We show that the game possesses a weighted potential function and admits a Nash equilibrium (NE). We prove that the price of anarchy is upper-bounded, and also propose a distributed and privacy-preserving algorithm which provably converges toward an NE of the game in polynomial time. Finally, through extensive numerical results, we assess the performance of the proposed distributed solution to the service chain composition problem.",salvatore d'oro,Game theory,2017.0,10.1109/JSAC.2017.2659298,IEEE Journal on Selected Areas in Communications,D’Oro2017,False,,IEEE,Not available,Exploiting Congestion Games to Achieve Distributed Service Chaining in NFV Networks,517eadd90b74ef58c8b28fda2647e689,https://ieeexplore.ieee.org/document/7835234/
4128,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
4129,"The network function virtualization (NFV) paradigm has gained increasing interest in both academia and industry as it promises scalable and flexible network management and orchestration. In NFV networks, network services are provided as chains of different virtual network functions (VNFs), which are instantiated and executed on dedicated VNF-compliant servers. The problem of composing those chains is referred to as the service chain composition problem. In contrast to centralized solutions that suffer from scalability and privacy issues, in this paper, we leverage non-cooperative game theory to achieve a low-complexity distributed solution to the above-mentioned problem. Specifically, to account for selfish and competitive behavior of users, we formulate the service chain composition problem as an atomic weighted congestion game with unsplittable flows and player-specific cost functions. We show that the game possesses a weighted potential function and admits a Nash equilibrium (NE). We prove that the price of anarchy is upper-bounded, and also propose a distributed and privacy-preserving algorithm which provably converges toward an NE of the game in polynomial time. Finally, through extensive numerical results, we assess the performance of the proposed distributed solution to the service chain composition problem.",salvatore d'oro,congestion games,2017.0,10.1109/JSAC.2017.2659298,IEEE Journal on Selected Areas in Communications,D’Oro2017,False,,IEEE,Not available,Exploiting Congestion Games to Achieve Distributed Service Chaining in NFV Networks,517eadd90b74ef58c8b28fda2647e689,https://ieeexplore.ieee.org/document/7835234/
4130,"The network function virtualization (NFV) paradigm has gained increasing interest in both academia and industry as it promises scalable and flexible network management and orchestration. In NFV networks, network services are provided as chains of different virtual network functions (VNFs), which are instantiated and executed on dedicated VNF-compliant servers. The problem of composing those chains is referred to as the service chain composition problem. In contrast to centralized solutions that suffer from scalability and privacy issues, in this paper, we leverage non-cooperative game theory to achieve a low-complexity distributed solution to the above-mentioned problem. Specifically, to account for selfish and competitive behavior of users, we formulate the service chain composition problem as an atomic weighted congestion game with unsplittable flows and player-specific cost functions. We show that the game possesses a weighted potential function and admits a Nash equilibrium (NE). We prove that the price of anarchy is upper-bounded, and also propose a distributed and privacy-preserving algorithm which provably converges toward an NE of the game in polynomial time. Finally, through extensive numerical results, we assess the performance of the proposed distributed solution to the service chain composition problem.",salvatore d'oro,service chaining,2017.0,10.1109/JSAC.2017.2659298,IEEE Journal on Selected Areas in Communications,D’Oro2017,False,,IEEE,Not available,Exploiting Congestion Games to Achieve Distributed Service Chaining in NFV Networks,517eadd90b74ef58c8b28fda2647e689,https://ieeexplore.ieee.org/document/7835234/
4131,"The network function virtualization (NFV) paradigm has gained increasing interest in both academia and industry as it promises scalable and flexible network management and orchestration. In NFV networks, network services are provided as chains of different virtual network functions (VNFs), which are instantiated and executed on dedicated VNF-compliant servers. The problem of composing those chains is referred to as the service chain composition problem. In contrast to centralized solutions that suffer from scalability and privacy issues, in this paper, we leverage non-cooperative game theory to achieve a low-complexity distributed solution to the above-mentioned problem. Specifically, to account for selfish and competitive behavior of users, we formulate the service chain composition problem as an atomic weighted congestion game with unsplittable flows and player-specific cost functions. We show that the game possesses a weighted potential function and admits a Nash equilibrium (NE). We prove that the price of anarchy is upper-bounded, and also propose a distributed and privacy-preserving algorithm which provably converges toward an NE of the game in polynomial time. Finally, through extensive numerical results, we assess the performance of the proposed distributed solution to the service chain composition problem.",salvatore d'oro,network function virtualization (NFV),2017.0,10.1109/JSAC.2017.2659298,IEEE Journal on Selected Areas in Communications,D’Oro2017,False,,IEEE,Not available,Exploiting Congestion Games to Achieve Distributed Service Chaining in NFV Networks,517eadd90b74ef58c8b28fda2647e689,https://ieeexplore.ieee.org/document/7835234/
4132,"The network function virtualization (NFV) paradigm has gained increasing interest in both academia and industry as it promises scalable and flexible network management and orchestration. In NFV networks, network services are provided as chains of different virtual network functions (VNFs), which are instantiated and executed on dedicated VNF-compliant servers. The problem of composing those chains is referred to as the service chain composition problem. In contrast to centralized solutions that suffer from scalability and privacy issues, in this paper, we leverage non-cooperative game theory to achieve a low-complexity distributed solution to the above-mentioned problem. Specifically, to account for selfish and competitive behavior of users, we formulate the service chain composition problem as an atomic weighted congestion game with unsplittable flows and player-specific cost functions. We show that the game possesses a weighted potential function and admits a Nash equilibrium (NE). We prove that the price of anarchy is upper-bounded, and also propose a distributed and privacy-preserving algorithm which provably converges toward an NE of the game in polynomial time. Finally, through extensive numerical results, we assess the performance of the proposed distributed solution to the service chain composition problem.",laura galluccio,Game theory,2017.0,10.1109/JSAC.2017.2659298,IEEE Journal on Selected Areas in Communications,D’Oro2017,False,,IEEE,Not available,Exploiting Congestion Games to Achieve Distributed Service Chaining in NFV Networks,517eadd90b74ef58c8b28fda2647e689,https://ieeexplore.ieee.org/document/7835234/
4133,"The network function virtualization (NFV) paradigm has gained increasing interest in both academia and industry as it promises scalable and flexible network management and orchestration. In NFV networks, network services are provided as chains of different virtual network functions (VNFs), which are instantiated and executed on dedicated VNF-compliant servers. The problem of composing those chains is referred to as the service chain composition problem. In contrast to centralized solutions that suffer from scalability and privacy issues, in this paper, we leverage non-cooperative game theory to achieve a low-complexity distributed solution to the above-mentioned problem. Specifically, to account for selfish and competitive behavior of users, we formulate the service chain composition problem as an atomic weighted congestion game with unsplittable flows and player-specific cost functions. We show that the game possesses a weighted potential function and admits a Nash equilibrium (NE). We prove that the price of anarchy is upper-bounded, and also propose a distributed and privacy-preserving algorithm which provably converges toward an NE of the game in polynomial time. Finally, through extensive numerical results, we assess the performance of the proposed distributed solution to the service chain composition problem.",laura galluccio,congestion games,2017.0,10.1109/JSAC.2017.2659298,IEEE Journal on Selected Areas in Communications,D’Oro2017,False,,IEEE,Not available,Exploiting Congestion Games to Achieve Distributed Service Chaining in NFV Networks,517eadd90b74ef58c8b28fda2647e689,https://ieeexplore.ieee.org/document/7835234/
4134,"The network function virtualization (NFV) paradigm has gained increasing interest in both academia and industry as it promises scalable and flexible network management and orchestration. In NFV networks, network services are provided as chains of different virtual network functions (VNFs), which are instantiated and executed on dedicated VNF-compliant servers. The problem of composing those chains is referred to as the service chain composition problem. In contrast to centralized solutions that suffer from scalability and privacy issues, in this paper, we leverage non-cooperative game theory to achieve a low-complexity distributed solution to the above-mentioned problem. Specifically, to account for selfish and competitive behavior of users, we formulate the service chain composition problem as an atomic weighted congestion game with unsplittable flows and player-specific cost functions. We show that the game possesses a weighted potential function and admits a Nash equilibrium (NE). We prove that the price of anarchy is upper-bounded, and also propose a distributed and privacy-preserving algorithm which provably converges toward an NE of the game in polynomial time. Finally, through extensive numerical results, we assess the performance of the proposed distributed solution to the service chain composition problem.",laura galluccio,service chaining,2017.0,10.1109/JSAC.2017.2659298,IEEE Journal on Selected Areas in Communications,D’Oro2017,False,,IEEE,Not available,Exploiting Congestion Games to Achieve Distributed Service Chaining in NFV Networks,517eadd90b74ef58c8b28fda2647e689,https://ieeexplore.ieee.org/document/7835234/
4135,"The network function virtualization (NFV) paradigm has gained increasing interest in both academia and industry as it promises scalable and flexible network management and orchestration. In NFV networks, network services are provided as chains of different virtual network functions (VNFs), which are instantiated and executed on dedicated VNF-compliant servers. The problem of composing those chains is referred to as the service chain composition problem. In contrast to centralized solutions that suffer from scalability and privacy issues, in this paper, we leverage non-cooperative game theory to achieve a low-complexity distributed solution to the above-mentioned problem. Specifically, to account for selfish and competitive behavior of users, we formulate the service chain composition problem as an atomic weighted congestion game with unsplittable flows and player-specific cost functions. We show that the game possesses a weighted potential function and admits a Nash equilibrium (NE). We prove that the price of anarchy is upper-bounded, and also propose a distributed and privacy-preserving algorithm which provably converges toward an NE of the game in polynomial time. Finally, through extensive numerical results, we assess the performance of the proposed distributed solution to the service chain composition problem.",laura galluccio,network function virtualization (NFV),2017.0,10.1109/JSAC.2017.2659298,IEEE Journal on Selected Areas in Communications,D’Oro2017,False,,IEEE,Not available,Exploiting Congestion Games to Achieve Distributed Service Chaining in NFV Networks,517eadd90b74ef58c8b28fda2647e689,https://ieeexplore.ieee.org/document/7835234/
4136,"The network function virtualization (NFV) paradigm has gained increasing interest in both academia and industry as it promises scalable and flexible network management and orchestration. In NFV networks, network services are provided as chains of different virtual network functions (VNFs), which are instantiated and executed on dedicated VNF-compliant servers. The problem of composing those chains is referred to as the service chain composition problem. In contrast to centralized solutions that suffer from scalability and privacy issues, in this paper, we leverage non-cooperative game theory to achieve a low-complexity distributed solution to the above-mentioned problem. Specifically, to account for selfish and competitive behavior of users, we formulate the service chain composition problem as an atomic weighted congestion game with unsplittable flows and player-specific cost functions. We show that the game possesses a weighted potential function and admits a Nash equilibrium (NE). We prove that the price of anarchy is upper-bounded, and also propose a distributed and privacy-preserving algorithm which provably converges toward an NE of the game in polynomial time. Finally, through extensive numerical results, we assess the performance of the proposed distributed solution to the service chain composition problem.",sergio palazzo,Game theory,2017.0,10.1109/JSAC.2017.2659298,IEEE Journal on Selected Areas in Communications,D’Oro2017,False,,IEEE,Not available,Exploiting Congestion Games to Achieve Distributed Service Chaining in NFV Networks,517eadd90b74ef58c8b28fda2647e689,https://ieeexplore.ieee.org/document/7835234/
4137,"The network function virtualization (NFV) paradigm has gained increasing interest in both academia and industry as it promises scalable and flexible network management and orchestration. In NFV networks, network services are provided as chains of different virtual network functions (VNFs), which are instantiated and executed on dedicated VNF-compliant servers. The problem of composing those chains is referred to as the service chain composition problem. In contrast to centralized solutions that suffer from scalability and privacy issues, in this paper, we leverage non-cooperative game theory to achieve a low-complexity distributed solution to the above-mentioned problem. Specifically, to account for selfish and competitive behavior of users, we formulate the service chain composition problem as an atomic weighted congestion game with unsplittable flows and player-specific cost functions. We show that the game possesses a weighted potential function and admits a Nash equilibrium (NE). We prove that the price of anarchy is upper-bounded, and also propose a distributed and privacy-preserving algorithm which provably converges toward an NE of the game in polynomial time. Finally, through extensive numerical results, we assess the performance of the proposed distributed solution to the service chain composition problem.",sergio palazzo,congestion games,2017.0,10.1109/JSAC.2017.2659298,IEEE Journal on Selected Areas in Communications,D’Oro2017,False,,IEEE,Not available,Exploiting Congestion Games to Achieve Distributed Service Chaining in NFV Networks,517eadd90b74ef58c8b28fda2647e689,https://ieeexplore.ieee.org/document/7835234/
4138,"The network function virtualization (NFV) paradigm has gained increasing interest in both academia and industry as it promises scalable and flexible network management and orchestration. In NFV networks, network services are provided as chains of different virtual network functions (VNFs), which are instantiated and executed on dedicated VNF-compliant servers. The problem of composing those chains is referred to as the service chain composition problem. In contrast to centralized solutions that suffer from scalability and privacy issues, in this paper, we leverage non-cooperative game theory to achieve a low-complexity distributed solution to the above-mentioned problem. Specifically, to account for selfish and competitive behavior of users, we formulate the service chain composition problem as an atomic weighted congestion game with unsplittable flows and player-specific cost functions. We show that the game possesses a weighted potential function and admits a Nash equilibrium (NE). We prove that the price of anarchy is upper-bounded, and also propose a distributed and privacy-preserving algorithm which provably converges toward an NE of the game in polynomial time. Finally, through extensive numerical results, we assess the performance of the proposed distributed solution to the service chain composition problem.",sergio palazzo,service chaining,2017.0,10.1109/JSAC.2017.2659298,IEEE Journal on Selected Areas in Communications,D’Oro2017,False,,IEEE,Not available,Exploiting Congestion Games to Achieve Distributed Service Chaining in NFV Networks,517eadd90b74ef58c8b28fda2647e689,https://ieeexplore.ieee.org/document/7835234/
4139,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
4140,"The network function virtualization (NFV) paradigm has gained increasing interest in both academia and industry as it promises scalable and flexible network management and orchestration. In NFV networks, network services are provided as chains of different virtual network functions (VNFs), which are instantiated and executed on dedicated VNF-compliant servers. The problem of composing those chains is referred to as the service chain composition problem. In contrast to centralized solutions that suffer from scalability and privacy issues, in this paper, we leverage non-cooperative game theory to achieve a low-complexity distributed solution to the above-mentioned problem. Specifically, to account for selfish and competitive behavior of users, we formulate the service chain composition problem as an atomic weighted congestion game with unsplittable flows and player-specific cost functions. We show that the game possesses a weighted potential function and admits a Nash equilibrium (NE). We prove that the price of anarchy is upper-bounded, and also propose a distributed and privacy-preserving algorithm which provably converges toward an NE of the game in polynomial time. Finally, through extensive numerical results, we assess the performance of the proposed distributed solution to the service chain composition problem.",sergio palazzo,network function virtualization (NFV),2017.0,10.1109/JSAC.2017.2659298,IEEE Journal on Selected Areas in Communications,D’Oro2017,False,,IEEE,Not available,Exploiting Congestion Games to Achieve Distributed Service Chaining in NFV Networks,517eadd90b74ef58c8b28fda2647e689,https://ieeexplore.ieee.org/document/7835234/
4141,"The network function virtualization (NFV) paradigm has gained increasing interest in both academia and industry as it promises scalable and flexible network management and orchestration. In NFV networks, network services are provided as chains of different virtual network functions (VNFs), which are instantiated and executed on dedicated VNF-compliant servers. The problem of composing those chains is referred to as the service chain composition problem. In contrast to centralized solutions that suffer from scalability and privacy issues, in this paper, we leverage non-cooperative game theory to achieve a low-complexity distributed solution to the above-mentioned problem. Specifically, to account for selfish and competitive behavior of users, we formulate the service chain composition problem as an atomic weighted congestion game with unsplittable flows and player-specific cost functions. We show that the game possesses a weighted potential function and admits a Nash equilibrium (NE). We prove that the price of anarchy is upper-bounded, and also propose a distributed and privacy-preserving algorithm which provably converges toward an NE of the game in polynomial time. Finally, through extensive numerical results, we assess the performance of the proposed distributed solution to the service chain composition problem.",giovanni schembra,Game theory,2017.0,10.1109/JSAC.2017.2659298,IEEE Journal on Selected Areas in Communications,D’Oro2017,False,,IEEE,Not available,Exploiting Congestion Games to Achieve Distributed Service Chaining in NFV Networks,517eadd90b74ef58c8b28fda2647e689,https://ieeexplore.ieee.org/document/7835234/
4142,"The network function virtualization (NFV) paradigm has gained increasing interest in both academia and industry as it promises scalable and flexible network management and orchestration. In NFV networks, network services are provided as chains of different virtual network functions (VNFs), which are instantiated and executed on dedicated VNF-compliant servers. The problem of composing those chains is referred to as the service chain composition problem. In contrast to centralized solutions that suffer from scalability and privacy issues, in this paper, we leverage non-cooperative game theory to achieve a low-complexity distributed solution to the above-mentioned problem. Specifically, to account for selfish and competitive behavior of users, we formulate the service chain composition problem as an atomic weighted congestion game with unsplittable flows and player-specific cost functions. We show that the game possesses a weighted potential function and admits a Nash equilibrium (NE). We prove that the price of anarchy is upper-bounded, and also propose a distributed and privacy-preserving algorithm which provably converges toward an NE of the game in polynomial time. Finally, through extensive numerical results, we assess the performance of the proposed distributed solution to the service chain composition problem.",giovanni schembra,congestion games,2017.0,10.1109/JSAC.2017.2659298,IEEE Journal on Selected Areas in Communications,D’Oro2017,False,,IEEE,Not available,Exploiting Congestion Games to Achieve Distributed Service Chaining in NFV Networks,517eadd90b74ef58c8b28fda2647e689,https://ieeexplore.ieee.org/document/7835234/
4143,"The network function virtualization (NFV) paradigm has gained increasing interest in both academia and industry as it promises scalable and flexible network management and orchestration. In NFV networks, network services are provided as chains of different virtual network functions (VNFs), which are instantiated and executed on dedicated VNF-compliant servers. The problem of composing those chains is referred to as the service chain composition problem. In contrast to centralized solutions that suffer from scalability and privacy issues, in this paper, we leverage non-cooperative game theory to achieve a low-complexity distributed solution to the above-mentioned problem. Specifically, to account for selfish and competitive behavior of users, we formulate the service chain composition problem as an atomic weighted congestion game with unsplittable flows and player-specific cost functions. We show that the game possesses a weighted potential function and admits a Nash equilibrium (NE). We prove that the price of anarchy is upper-bounded, and also propose a distributed and privacy-preserving algorithm which provably converges toward an NE of the game in polynomial time. Finally, through extensive numerical results, we assess the performance of the proposed distributed solution to the service chain composition problem.",giovanni schembra,service chaining,2017.0,10.1109/JSAC.2017.2659298,IEEE Journal on Selected Areas in Communications,D’Oro2017,False,,IEEE,Not available,Exploiting Congestion Games to Achieve Distributed Service Chaining in NFV Networks,517eadd90b74ef58c8b28fda2647e689,https://ieeexplore.ieee.org/document/7835234/
4144,"The network function virtualization (NFV) paradigm has gained increasing interest in both academia and industry as it promises scalable and flexible network management and orchestration. In NFV networks, network services are provided as chains of different virtual network functions (VNFs), which are instantiated and executed on dedicated VNF-compliant servers. The problem of composing those chains is referred to as the service chain composition problem. In contrast to centralized solutions that suffer from scalability and privacy issues, in this paper, we leverage non-cooperative game theory to achieve a low-complexity distributed solution to the above-mentioned problem. Specifically, to account for selfish and competitive behavior of users, we formulate the service chain composition problem as an atomic weighted congestion game with unsplittable flows and player-specific cost functions. We show that the game possesses a weighted potential function and admits a Nash equilibrium (NE). We prove that the price of anarchy is upper-bounded, and also propose a distributed and privacy-preserving algorithm which provably converges toward an NE of the game in polynomial time. Finally, through extensive numerical results, we assess the performance of the proposed distributed solution to the service chain composition problem.",giovanni schembra,network function virtualization (NFV),2017.0,10.1109/JSAC.2017.2659298,IEEE Journal on Selected Areas in Communications,D’Oro2017,False,,IEEE,Not available,Exploiting Congestion Games to Achieve Distributed Service Chaining in NFV Networks,517eadd90b74ef58c8b28fda2647e689,https://ieeexplore.ieee.org/document/7835234/
4145,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",thomas carroll,Processor scheduling,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
4146,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",thomas carroll,Surface-mount technology,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
4147,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",thomas carroll,Game theory,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
4148,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",thomas carroll,Costs,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
4149,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",thomas carroll,Scheduling algorithm,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
4150,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
4151,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",thomas carroll,Routing,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
4152,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",thomas carroll,Single machine scheduling,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
4153,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",thomas carroll,Computer science,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
4154,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",thomas carroll,Decision making,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
4155,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",thomas carroll,Steady-state,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
4156,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",daniel grosu,Processor scheduling,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
4157,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",daniel grosu,Surface-mount technology,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
4158,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",daniel grosu,Game theory,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
4159,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",daniel grosu,Costs,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
4160,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",daniel grosu,Scheduling algorithm,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
4161,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
4162,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",daniel grosu,Routing,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
4163,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",daniel grosu,Single machine scheduling,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
4164,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",daniel grosu,Computer science,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
4165,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",daniel grosu,Decision making,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
4166,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",daniel grosu,Steady-state,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
4167,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",ninoslav marina,Relays,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
4168,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",ninoslav marina,Peer to peer computing,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
4169,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",ninoslav marina,Games,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
4170,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",ninoslav marina,Resource management,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
4171,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",ninoslav marina,Ad hoc networks,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
4172,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
4173,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",ninoslav marina,Upper bound,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
4174,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",ninoslav marina,Nash equilibrium,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
4175,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",gurdal arslan,Relays,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
4176,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",gurdal arslan,Peer to peer computing,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
4177,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",gurdal arslan,Games,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
4178,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",gurdal arslan,Resource management,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
4179,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",gurdal arslan,Ad hoc networks,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
4180,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",gurdal arslan,Upper bound,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
4181,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",gurdal arslan,Nash equilibrium,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
4182,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",aleksandar kavcic,Relays,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
4183,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
4184,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
4185,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",aleksandar kavcic,Peer to peer computing,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
4186,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",aleksandar kavcic,Games,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
4187,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",aleksandar kavcic,Resource management,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
4188,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",aleksandar kavcic,Ad hoc networks,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
4189,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",aleksandar kavcic,Upper bound,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
4190,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",aleksandar kavcic,Nash equilibrium,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
4191,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",huigang chen,Routing,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
4192,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",huigang chen,Nash equilibrium,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
4193,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",huigang chen,Communication system traffic control,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
4194,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",huigang chen,Traffic control,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
4195,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
4196,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",huigang chen,Educational institutions,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
4197,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",huigang chen,USA Councils,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
4198,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",huigang chen,H infinity control,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
4199,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",huigang chen,Bandwidth,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
4200,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",huigang chen,Laboratories,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
4201,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",huigang chen,Distributed algorithms,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
4202,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",john baras,Routing,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
4203,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",john baras,Nash equilibrium,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
4204,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",john baras,Communication system traffic control,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
4205,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",john baras,Traffic control,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
4206,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
4207,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",john baras,Educational institutions,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
4208,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",john baras,USA Councils,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
4209,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",john baras,H infinity control,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
4210,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",john baras,Bandwidth,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
4211,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",john baras,Laboratories,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
4212,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",john baras,Distributed algorithms,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
4213,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",wenchao xu,Games,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
4214,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",wenchao xu,Switches,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
4215,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",wenchao xu,IEEE 802.11 Standards,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
4216,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",wenchao xu,Wireless networks,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
4217,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
4218,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",wenchao xu,Indexes,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
4219,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",wenchao xu,Nash equilibrium,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
4220,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",wenchao xu,Delay,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
4221,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",cunqing hua,Games,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
4222,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",cunqing hua,Switches,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
4223,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",cunqing hua,IEEE 802.11 Standards,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
4224,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",cunqing hua,Wireless networks,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
4225,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",cunqing hua,Indexes,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
4226,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",cunqing hua,Nash equilibrium,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
4227,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",cunqing hua,Delay,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
4228,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
4229,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",aiping huang,Games,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
4230,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",aiping huang,Switches,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
4231,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",aiping huang,IEEE 802.11 Standards,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
4232,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",aiping huang,Wireless networks,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
4233,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",aiping huang,Indexes,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
4234,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",aiping huang,Nash equilibrium,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
4235,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",aiping huang,Delay,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
4236,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",seyed ahmadyan,Games,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
4237,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",seyed ahmadyan,Resource management,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
4238,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",seyed ahmadyan,Nash equilibrium,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
4239,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
4240,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",seyed ahmadyan,Approximation algorithms,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
4241,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",seyed ahmadyan,Search methods,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
4242,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",seyed ahmadyan,Economics,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
4243,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",seyed ahmadyan,Electronic mail,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
4244,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",seyed etesami,Games,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
4245,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",seyed etesami,Resource management,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
4246,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",seyed etesami,Nash equilibrium,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
4247,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",seyed etesami,Approximation algorithms,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
4248,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",seyed etesami,Search methods,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
4249,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",seyed etesami,Economics,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
4250,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4251,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",seyed etesami,Electronic mail,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
4252,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",h. poor,Games,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
4253,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",h. poor,Resource management,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
4254,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",h. poor,Nash equilibrium,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
4255,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",h. poor,Approximation algorithms,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
4256,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",h. poor,Search methods,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
4257,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",h. poor,Economics,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
4258,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",h. poor,Electronic mail,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
4259,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",mehdi soorki,5G cellular network,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
4260,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",mehdi soorki,virtual MIMO,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
4261,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4262,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",mehdi soorki,D2D relaying,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
4263,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",mehdi soorki,coalitional game,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
4264,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",mehdi soorki,mechanism design,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
4265,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",mohammad manshaei,5G cellular network,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
4266,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",mohammad manshaei,virtual MIMO,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
4267,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",mohammad manshaei,D2D relaying,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
4268,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",mohammad manshaei,coalitional game,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
4269,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",mohammad manshaei,mechanism design,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
4270,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",behrouz maham,5G cellular network,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
4271,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",behrouz maham,virtual MIMO,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
4272,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4273,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",behrouz maham,D2D relaying,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
4274,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",behrouz maham,coalitional game,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
4275,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",behrouz maham,mechanism design,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
4276,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",hossein saidi,5G cellular network,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
4277,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",hossein saidi,virtual MIMO,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
4278,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",hossein saidi,D2D relaying,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
4279,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",hossein saidi,coalitional game,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
4280,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",hossein saidi,mechanism design,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
4281,"Secondary users sharing primary users' spectrum is modeled as a graphical game. Users located in random graphs and a regular lattice are considered. Secondary users are assumed to differentiate the ``quality"" of the primary spectrum while interacting within their local neighborhood to minimize interference and congestion. The learning algorithm is also shown to be effective in punishing malicious users that violate spectrum etiquettes. An equivalence between spectrum sharing neighborhood interaction and the spin-glass model in statistical physics is established. A distributed exponential learning algorithm is used to arrive at an evolutionary stable solution to the game. Some theoretical properties of the system are studied and simulation results are presented to illustrate price of anarchy, convergence of the learning algorithm and asymptotic invariance of the system performance with respect to spectrum quality.",mahdi azarafrooz,Games,2011.0,10.1109/GLOCOM.2011.6134250,2011 IEEE Global Telecommunications Conference - GLOBECOM 2011,Azarafrooz2011,False,,IEEE,Not available,Distributed Learning in Secondary Spectrum Sharing Graphical Game,011fb578d25e9aa0ee215c044b67b2cf,https://ieeexplore.ieee.org/document/6134250/
4282,"Secondary users sharing primary users' spectrum is modeled as a graphical game. Users located in random graphs and a regular lattice are considered. Secondary users are assumed to differentiate the ``quality"" of the primary spectrum while interacting within their local neighborhood to minimize interference and congestion. The learning algorithm is also shown to be effective in punishing malicious users that violate spectrum etiquettes. An equivalence between spectrum sharing neighborhood interaction and the spin-glass model in statistical physics is established. A distributed exponential learning algorithm is used to arrive at an evolutionary stable solution to the game. Some theoretical properties of the system are studied and simulation results are presented to illustrate price of anarchy, convergence of the learning algorithm and asymptotic invariance of the system performance with respect to spectrum quality.",mahdi azarafrooz,Peer to peer computing,2011.0,10.1109/GLOCOM.2011.6134250,2011 IEEE Global Telecommunications Conference - GLOBECOM 2011,Azarafrooz2011,False,,IEEE,Not available,Distributed Learning in Secondary Spectrum Sharing Graphical Game,011fb578d25e9aa0ee215c044b67b2cf,https://ieeexplore.ieee.org/document/6134250/
4283,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4284,"Secondary users sharing primary users' spectrum is modeled as a graphical game. Users located in random graphs and a regular lattice are considered. Secondary users are assumed to differentiate the ``quality"" of the primary spectrum while interacting within their local neighborhood to minimize interference and congestion. The learning algorithm is also shown to be effective in punishing malicious users that violate spectrum etiquettes. An equivalence between spectrum sharing neighborhood interaction and the spin-glass model in statistical physics is established. A distributed exponential learning algorithm is used to arrive at an evolutionary stable solution to the game. Some theoretical properties of the system are studied and simulation results are presented to illustrate price of anarchy, convergence of the learning algorithm and asymptotic invariance of the system performance with respect to spectrum quality.",mahdi azarafrooz,Switches,2011.0,10.1109/GLOCOM.2011.6134250,2011 IEEE Global Telecommunications Conference - GLOBECOM 2011,Azarafrooz2011,False,,IEEE,Not available,Distributed Learning in Secondary Spectrum Sharing Graphical Game,011fb578d25e9aa0ee215c044b67b2cf,https://ieeexplore.ieee.org/document/6134250/
4285,"Secondary users sharing primary users' spectrum is modeled as a graphical game. Users located in random graphs and a regular lattice are considered. Secondary users are assumed to differentiate the ``quality"" of the primary spectrum while interacting within their local neighborhood to minimize interference and congestion. The learning algorithm is also shown to be effective in punishing malicious users that violate spectrum etiquettes. An equivalence between spectrum sharing neighborhood interaction and the spin-glass model in statistical physics is established. A distributed exponential learning algorithm is used to arrive at an evolutionary stable solution to the game. Some theoretical properties of the system are studied and simulation results are presented to illustrate price of anarchy, convergence of the learning algorithm and asymptotic invariance of the system performance with respect to spectrum quality.",mahdi azarafrooz,Interference,2011.0,10.1109/GLOCOM.2011.6134250,2011 IEEE Global Telecommunications Conference - GLOBECOM 2011,Azarafrooz2011,False,,IEEE,Not available,Distributed Learning in Secondary Spectrum Sharing Graphical Game,011fb578d25e9aa0ee215c044b67b2cf,https://ieeexplore.ieee.org/document/6134250/
4286,"Secondary users sharing primary users' spectrum is modeled as a graphical game. Users located in random graphs and a regular lattice are considered. Secondary users are assumed to differentiate the ``quality"" of the primary spectrum while interacting within their local neighborhood to minimize interference and congestion. The learning algorithm is also shown to be effective in punishing malicious users that violate spectrum etiquettes. An equivalence between spectrum sharing neighborhood interaction and the spin-glass model in statistical physics is established. A distributed exponential learning algorithm is used to arrive at an evolutionary stable solution to the game. Some theoretical properties of the system are studied and simulation results are presented to illustrate price of anarchy, convergence of the learning algorithm and asymptotic invariance of the system performance with respect to spectrum quality.",mahdi azarafrooz,Indexes,2011.0,10.1109/GLOCOM.2011.6134250,2011 IEEE Global Telecommunications Conference - GLOBECOM 2011,Azarafrooz2011,False,,IEEE,Not available,Distributed Learning in Secondary Spectrum Sharing Graphical Game,011fb578d25e9aa0ee215c044b67b2cf,https://ieeexplore.ieee.org/document/6134250/
4287,"Secondary users sharing primary users' spectrum is modeled as a graphical game. Users located in random graphs and a regular lattice are considered. Secondary users are assumed to differentiate the ``quality"" of the primary spectrum while interacting within their local neighborhood to minimize interference and congestion. The learning algorithm is also shown to be effective in punishing malicious users that violate spectrum etiquettes. An equivalence between spectrum sharing neighborhood interaction and the spin-glass model in statistical physics is established. A distributed exponential learning algorithm is used to arrive at an evolutionary stable solution to the game. Some theoretical properties of the system are studied and simulation results are presented to illustrate price of anarchy, convergence of the learning algorithm and asymptotic invariance of the system performance with respect to spectrum quality.",mahdi azarafrooz,IEEE Communications Society,2011.0,10.1109/GLOCOM.2011.6134250,2011 IEEE Global Telecommunications Conference - GLOBECOM 2011,Azarafrooz2011,False,,IEEE,Not available,Distributed Learning in Secondary Spectrum Sharing Graphical Game,011fb578d25e9aa0ee215c044b67b2cf,https://ieeexplore.ieee.org/document/6134250/
4288,"Secondary users sharing primary users' spectrum is modeled as a graphical game. Users located in random graphs and a regular lattice are considered. Secondary users are assumed to differentiate the ``quality"" of the primary spectrum while interacting within their local neighborhood to minimize interference and congestion. The learning algorithm is also shown to be effective in punishing malicious users that violate spectrum etiquettes. An equivalence between spectrum sharing neighborhood interaction and the spin-glass model in statistical physics is established. A distributed exponential learning algorithm is used to arrive at an evolutionary stable solution to the game. Some theoretical properties of the system are studied and simulation results are presented to illustrate price of anarchy, convergence of the learning algorithm and asymptotic invariance of the system performance with respect to spectrum quality.",mahdi azarafrooz,Nash equilibrium,2011.0,10.1109/GLOCOM.2011.6134250,2011 IEEE Global Telecommunications Conference - GLOBECOM 2011,Azarafrooz2011,False,,IEEE,Not available,Distributed Learning in Secondary Spectrum Sharing Graphical Game,011fb578d25e9aa0ee215c044b67b2cf,https://ieeexplore.ieee.org/document/6134250/
4289,"Secondary users sharing primary users' spectrum is modeled as a graphical game. Users located in random graphs and a regular lattice are considered. Secondary users are assumed to differentiate the ``quality"" of the primary spectrum while interacting within their local neighborhood to minimize interference and congestion. The learning algorithm is also shown to be effective in punishing malicious users that violate spectrum etiquettes. An equivalence between spectrum sharing neighborhood interaction and the spin-glass model in statistical physics is established. A distributed exponential learning algorithm is used to arrive at an evolutionary stable solution to the game. Some theoretical properties of the system are studied and simulation results are presented to illustrate price of anarchy, convergence of the learning algorithm and asymptotic invariance of the system performance with respect to spectrum quality.",r. chandramouli,Games,2011.0,10.1109/GLOCOM.2011.6134250,2011 IEEE Global Telecommunications Conference - GLOBECOM 2011,Azarafrooz2011,False,,IEEE,Not available,Distributed Learning in Secondary Spectrum Sharing Graphical Game,011fb578d25e9aa0ee215c044b67b2cf,https://ieeexplore.ieee.org/document/6134250/
4290,"Secondary users sharing primary users' spectrum is modeled as a graphical game. Users located in random graphs and a regular lattice are considered. Secondary users are assumed to differentiate the ``quality"" of the primary spectrum while interacting within their local neighborhood to minimize interference and congestion. The learning algorithm is also shown to be effective in punishing malicious users that violate spectrum etiquettes. An equivalence between spectrum sharing neighborhood interaction and the spin-glass model in statistical physics is established. A distributed exponential learning algorithm is used to arrive at an evolutionary stable solution to the game. Some theoretical properties of the system are studied and simulation results are presented to illustrate price of anarchy, convergence of the learning algorithm and asymptotic invariance of the system performance with respect to spectrum quality.",r. chandramouli,Peer to peer computing,2011.0,10.1109/GLOCOM.2011.6134250,2011 IEEE Global Telecommunications Conference - GLOBECOM 2011,Azarafrooz2011,False,,IEEE,Not available,Distributed Learning in Secondary Spectrum Sharing Graphical Game,011fb578d25e9aa0ee215c044b67b2cf,https://ieeexplore.ieee.org/document/6134250/
4291,"Secondary users sharing primary users' spectrum is modeled as a graphical game. Users located in random graphs and a regular lattice are considered. Secondary users are assumed to differentiate the ``quality"" of the primary spectrum while interacting within their local neighborhood to minimize interference and congestion. The learning algorithm is also shown to be effective in punishing malicious users that violate spectrum etiquettes. An equivalence between spectrum sharing neighborhood interaction and the spin-glass model in statistical physics is established. A distributed exponential learning algorithm is used to arrive at an evolutionary stable solution to the game. Some theoretical properties of the system are studied and simulation results are presented to illustrate price of anarchy, convergence of the learning algorithm and asymptotic invariance of the system performance with respect to spectrum quality.",r. chandramouli,Switches,2011.0,10.1109/GLOCOM.2011.6134250,2011 IEEE Global Telecommunications Conference - GLOBECOM 2011,Azarafrooz2011,False,,IEEE,Not available,Distributed Learning in Secondary Spectrum Sharing Graphical Game,011fb578d25e9aa0ee215c044b67b2cf,https://ieeexplore.ieee.org/document/6134250/
4292,"Secondary users sharing primary users' spectrum is modeled as a graphical game. Users located in random graphs and a regular lattice are considered. Secondary users are assumed to differentiate the ``quality"" of the primary spectrum while interacting within their local neighborhood to minimize interference and congestion. The learning algorithm is also shown to be effective in punishing malicious users that violate spectrum etiquettes. An equivalence between spectrum sharing neighborhood interaction and the spin-glass model in statistical physics is established. A distributed exponential learning algorithm is used to arrive at an evolutionary stable solution to the game. Some theoretical properties of the system are studied and simulation results are presented to illustrate price of anarchy, convergence of the learning algorithm and asymptotic invariance of the system performance with respect to spectrum quality.",r. chandramouli,Interference,2011.0,10.1109/GLOCOM.2011.6134250,2011 IEEE Global Telecommunications Conference - GLOBECOM 2011,Azarafrooz2011,False,,IEEE,Not available,Distributed Learning in Secondary Spectrum Sharing Graphical Game,011fb578d25e9aa0ee215c044b67b2cf,https://ieeexplore.ieee.org/document/6134250/
4293,"Secondary users sharing primary users' spectrum is modeled as a graphical game. Users located in random graphs and a regular lattice are considered. Secondary users are assumed to differentiate the ``quality"" of the primary spectrum while interacting within their local neighborhood to minimize interference and congestion. The learning algorithm is also shown to be effective in punishing malicious users that violate spectrum etiquettes. An equivalence between spectrum sharing neighborhood interaction and the spin-glass model in statistical physics is established. A distributed exponential learning algorithm is used to arrive at an evolutionary stable solution to the game. Some theoretical properties of the system are studied and simulation results are presented to illustrate price of anarchy, convergence of the learning algorithm and asymptotic invariance of the system performance with respect to spectrum quality.",r. chandramouli,Indexes,2011.0,10.1109/GLOCOM.2011.6134250,2011 IEEE Global Telecommunications Conference - GLOBECOM 2011,Azarafrooz2011,False,,IEEE,Not available,Distributed Learning in Secondary Spectrum Sharing Graphical Game,011fb578d25e9aa0ee215c044b67b2cf,https://ieeexplore.ieee.org/document/6134250/
4294,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
4295,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
4296,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4297,"Secondary users sharing primary users' spectrum is modeled as a graphical game. Users located in random graphs and a regular lattice are considered. Secondary users are assumed to differentiate the ``quality"" of the primary spectrum while interacting within their local neighborhood to minimize interference and congestion. The learning algorithm is also shown to be effective in punishing malicious users that violate spectrum etiquettes. An equivalence between spectrum sharing neighborhood interaction and the spin-glass model in statistical physics is established. A distributed exponential learning algorithm is used to arrive at an evolutionary stable solution to the game. Some theoretical properties of the system are studied and simulation results are presented to illustrate price of anarchy, convergence of the learning algorithm and asymptotic invariance of the system performance with respect to spectrum quality.",r. chandramouli,IEEE Communications Society,2011.0,10.1109/GLOCOM.2011.6134250,2011 IEEE Global Telecommunications Conference - GLOBECOM 2011,Azarafrooz2011,False,,IEEE,Not available,Distributed Learning in Secondary Spectrum Sharing Graphical Game,011fb578d25e9aa0ee215c044b67b2cf,https://ieeexplore.ieee.org/document/6134250/
4298,"Secondary users sharing primary users' spectrum is modeled as a graphical game. Users located in random graphs and a regular lattice are considered. Secondary users are assumed to differentiate the ``quality"" of the primary spectrum while interacting within their local neighborhood to minimize interference and congestion. The learning algorithm is also shown to be effective in punishing malicious users that violate spectrum etiquettes. An equivalence between spectrum sharing neighborhood interaction and the spin-glass model in statistical physics is established. A distributed exponential learning algorithm is used to arrive at an evolutionary stable solution to the game. Some theoretical properties of the system are studied and simulation results are presented to illustrate price of anarchy, convergence of the learning algorithm and asymptotic invariance of the system performance with respect to spectrum quality.",r. chandramouli,Nash equilibrium,2011.0,10.1109/GLOCOM.2011.6134250,2011 IEEE Global Telecommunications Conference - GLOBECOM 2011,Azarafrooz2011,False,,IEEE,Not available,Distributed Learning in Secondary Spectrum Sharing Graphical Game,011fb578d25e9aa0ee215c044b67b2cf,https://ieeexplore.ieee.org/document/6134250/
4299,"We formulate two coordination mechanisms between local and centralized electricity markets. The first one is a centralized mechanism ruled by the national market operator and formulated as a standard constrained optimization problem. The second one is a decentralized mechanism, governed by local market operators that interact with a central market operator. In both cases, conventional generators submit block quantity offers subject to inter-temporal constraints while anticipating the outcome of the market clearing(s). The decentralized coordination mechanism can be interpreted as a Stackelberg game that we formulate as a bilevel mathematical programming problem. We prove that in case of simple bids, the Stackelberg game admits a unique subgame perfect Nash equilibrium and extend this result to block quantity offers using Complementarity Theory. Through a case study we determine that the decentralized design is as efficient as the centralized one with high shares of renewables, using the Price of Anarchy as performance measure, and that imperfect information has a limited impact on the performance of the decentralized market design.",helene cadre,Games,2017.0,10.1109/EEM.2017.7981863,2017 14th International Conference on the European Energy Market (EEM),Cadre2017,False,,IEEE,Not available,On the efficiency of local electricity markets,cdf6c470b7a6dcbb5a40035d43ed02f6,https://ieeexplore.ieee.org/document/7981863/
4300,"We formulate two coordination mechanisms between local and centralized electricity markets. The first one is a centralized mechanism ruled by the national market operator and formulated as a standard constrained optimization problem. The second one is a decentralized mechanism, governed by local market operators that interact with a central market operator. In both cases, conventional generators submit block quantity offers subject to inter-temporal constraints while anticipating the outcome of the market clearing(s). The decentralized coordination mechanism can be interpreted as a Stackelberg game that we formulate as a bilevel mathematical programming problem. We prove that in case of simple bids, the Stackelberg game admits a unique subgame perfect Nash equilibrium and extend this result to block quantity offers using Complementarity Theory. Through a case study we determine that the decentralized design is as efficient as the centralized one with high shares of renewables, using the Price of Anarchy as performance measure, and that imperfect information has a limited impact on the performance of the decentralized market design.",helene cadre,Generators,2017.0,10.1109/EEM.2017.7981863,2017 14th International Conference on the European Energy Market (EEM),Cadre2017,False,,IEEE,Not available,On the efficiency of local electricity markets,cdf6c470b7a6dcbb5a40035d43ed02f6,https://ieeexplore.ieee.org/document/7981863/
4301,"We formulate two coordination mechanisms between local and centralized electricity markets. The first one is a centralized mechanism ruled by the national market operator and formulated as a standard constrained optimization problem. The second one is a decentralized mechanism, governed by local market operators that interact with a central market operator. In both cases, conventional generators submit block quantity offers subject to inter-temporal constraints while anticipating the outcome of the market clearing(s). The decentralized coordination mechanism can be interpreted as a Stackelberg game that we formulate as a bilevel mathematical programming problem. We prove that in case of simple bids, the Stackelberg game admits a unique subgame perfect Nash equilibrium and extend this result to block quantity offers using Complementarity Theory. Through a case study we determine that the decentralized design is as efficient as the centralized one with high shares of renewables, using the Price of Anarchy as performance measure, and that imperfect information has a limited impact on the performance of the decentralized market design.",helene cadre,Mathematical model,2017.0,10.1109/EEM.2017.7981863,2017 14th International Conference on the European Energy Market (EEM),Cadre2017,False,,IEEE,Not available,On the efficiency of local electricity markets,cdf6c470b7a6dcbb5a40035d43ed02f6,https://ieeexplore.ieee.org/document/7981863/
4302,"We formulate two coordination mechanisms between local and centralized electricity markets. The first one is a centralized mechanism ruled by the national market operator and formulated as a standard constrained optimization problem. The second one is a decentralized mechanism, governed by local market operators that interact with a central market operator. In both cases, conventional generators submit block quantity offers subject to inter-temporal constraints while anticipating the outcome of the market clearing(s). The decentralized coordination mechanism can be interpreted as a Stackelberg game that we formulate as a bilevel mathematical programming problem. We prove that in case of simple bids, the Stackelberg game admits a unique subgame perfect Nash equilibrium and extend this result to block quantity offers using Complementarity Theory. Through a case study we determine that the decentralized design is as efficient as the centralized one with high shares of renewables, using the Price of Anarchy as performance measure, and that imperfect information has a limited impact on the performance of the decentralized market design.",helene cadre,Electricity supply industry,2017.0,10.1109/EEM.2017.7981863,2017 14th International Conference on the European Energy Market (EEM),Cadre2017,False,,IEEE,Not available,On the efficiency of local electricity markets,cdf6c470b7a6dcbb5a40035d43ed02f6,https://ieeexplore.ieee.org/document/7981863/
4303,"We formulate two coordination mechanisms between local and centralized electricity markets. The first one is a centralized mechanism ruled by the national market operator and formulated as a standard constrained optimization problem. The second one is a decentralized mechanism, governed by local market operators that interact with a central market operator. In both cases, conventional generators submit block quantity offers subject to inter-temporal constraints while anticipating the outcome of the market clearing(s). The decentralized coordination mechanism can be interpreted as a Stackelberg game that we formulate as a bilevel mathematical programming problem. We prove that in case of simple bids, the Stackelberg game admits a unique subgame perfect Nash equilibrium and extend this result to block quantity offers using Complementarity Theory. Through a case study we determine that the decentralized design is as efficient as the centralized one with high shares of renewables, using the Price of Anarchy as performance measure, and that imperfect information has a limited impact on the performance of the decentralized market design.",helene cadre,Standards,2017.0,10.1109/EEM.2017.7981863,2017 14th International Conference on the European Energy Market (EEM),Cadre2017,False,,IEEE,Not available,On the efficiency of local electricity markets,cdf6c470b7a6dcbb5a40035d43ed02f6,https://ieeexplore.ieee.org/document/7981863/
4304,"We formulate two coordination mechanisms between local and centralized electricity markets. The first one is a centralized mechanism ruled by the national market operator and formulated as a standard constrained optimization problem. The second one is a decentralized mechanism, governed by local market operators that interact with a central market operator. In both cases, conventional generators submit block quantity offers subject to inter-temporal constraints while anticipating the outcome of the market clearing(s). The decentralized coordination mechanism can be interpreted as a Stackelberg game that we formulate as a bilevel mathematical programming problem. We prove that in case of simple bids, the Stackelberg game admits a unique subgame perfect Nash equilibrium and extend this result to block quantity offers using Complementarity Theory. Through a case study we determine that the decentralized design is as efficient as the centralized one with high shares of renewables, using the Price of Anarchy as performance measure, and that imperfect information has a limited impact on the performance of the decentralized market design.",helene cadre,Mathematical programming,2017.0,10.1109/EEM.2017.7981863,2017 14th International Conference on the European Energy Market (EEM),Cadre2017,False,,IEEE,Not available,On the efficiency of local electricity markets,cdf6c470b7a6dcbb5a40035d43ed02f6,https://ieeexplore.ieee.org/document/7981863/
4305,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",fengxiao tang,Anticoordination game,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
4306,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",fengxiao tang,channel assignment,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
4307,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4308,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",fengxiao tang,device to device (D2D),2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
4309,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",fengxiao tang,game theory,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
4310,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",fengxiao tang,partially overlapping channel (PoC),2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
4311,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",fengxiao tang,potential game,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
4312,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",fengxiao tang,unmanned aerial vehicle (UAV),2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
4313,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",zubair fadlullah,Anticoordination game,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
4314,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",zubair fadlullah,channel assignment,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
4315,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",zubair fadlullah,device to device (D2D),2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
4316,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",zubair fadlullah,game theory,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
4317,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",zubair fadlullah,partially overlapping channel (PoC),2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
4318,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4319,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",zubair fadlullah,potential game,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
4320,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",zubair fadlullah,unmanned aerial vehicle (UAV),2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
4321,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",nei kato,Anticoordination game,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
4322,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",nei kato,channel assignment,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
4323,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",nei kato,device to device (D2D),2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
4324,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",nei kato,game theory,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
4325,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",nei kato,partially overlapping channel (PoC),2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
4326,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",nei kato,potential game,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
4327,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",nei kato,unmanned aerial vehicle (UAV),2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
4328,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",fumie ono,Anticoordination game,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
4329,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4330,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",fumie ono,channel assignment,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
4331,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",fumie ono,device to device (D2D),2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
4332,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",fumie ono,game theory,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
4333,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",fumie ono,partially overlapping channel (PoC),2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
4334,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",fumie ono,potential game,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
4335,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",fumie ono,unmanned aerial vehicle (UAV),2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
4336,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",ryu miura,Anticoordination game,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
4337,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",ryu miura,channel assignment,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
4338,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",ryu miura,device to device (D2D),2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
4339,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",ryu miura,game theory,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
4340,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4341,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",ryu miura,partially overlapping channel (PoC),2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
4342,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",ryu miura,potential game,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
4343,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",ryu miura,unmanned aerial vehicle (UAV),2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
4344,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
4345,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
4346,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
4347,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
4348,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
4349,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
4350,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
4351,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4352,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
4353,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
4354,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
4355,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
4356,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
4357,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
4358,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
4359,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
4360,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
4361,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
4362,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4363,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
4364,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4365,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4366,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4367,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4368,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4369,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4370,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4371,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4372,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4373,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4374,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4375,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4376,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4377,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4378,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4379,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4380,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4381,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4382,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4383,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4384,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4385,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4386,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4387,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4388,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4389,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4390,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4391,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4392,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4393,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4394,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4395,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4396,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4397,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4398,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4399,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4400,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4401,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4402,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4403,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4404,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4405,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4406,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
4407,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4408,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4409,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4410,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4411,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4412,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4413,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4414,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4415,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4416,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4417,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4418,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4419,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4420,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4421,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4422,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4423,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4424,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4425,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4426,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4427,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4428,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4429,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4430,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4431,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4432,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4433,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4434,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4435,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4436,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4437,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4438,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4439,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4440,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4441,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4442,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4443,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4444,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4445,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4446,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4447,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4448,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4449,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4450,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4451,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4452,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4453,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4454,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4455,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4456,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4457,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4458,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4459,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4460,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4461,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4462,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4463,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4464,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4465,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4466,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4467,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4468,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4469,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4470,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4471,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4472,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4473,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4474,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4475,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4476,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4477,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4478,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4479,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4480,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4481,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4482,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4483,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
4484,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4485,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
4486,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
4487,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
4488,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
4489,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
4490,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
4491,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
4492,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4493,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4494,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4495,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4496,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4497,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4498,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4499,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4500,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4501,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4502,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4503,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4504,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4505,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4506,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4507,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4508,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4509,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4510,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4511,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4512,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4513,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4514,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4515,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4516,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4517,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
4518,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4519,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4520,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4521,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4522,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4523,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4524,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4525,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4526,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4527,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4528,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4529,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4530,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4531,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4532,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4533,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4534,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4535,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4536,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4537,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4538,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4539,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4540,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4541,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4542,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4543,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4544,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4545,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4546,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4547,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4548,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4549,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4550,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4551,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4552,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4553,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4554,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4555,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4556,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4557,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4558,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4559,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4560,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4561,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4562,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4563,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4564,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4565,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4566,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4567,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4568,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4569,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4570,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4571,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4572,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4573,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4574,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4575,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4576,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4577,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4578,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4579,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4580,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4581,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4582,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4583,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4584,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
4585,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4586,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4587,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4588,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4589,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4590,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4591,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4592,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4593,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4594,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4595,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4596,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4597,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4598,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4599,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4600,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4601,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4602,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4603,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4604,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4605,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4606,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4607,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4608,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4609,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4610,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4611,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4612,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4613,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4614,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4615,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4616,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4617,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4618,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4619,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4620,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4621,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4622,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4623,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4624,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4625,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4626,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4627,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4628,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4629,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4630,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4631,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4632,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4633,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4634,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4635,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4636,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4637,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4638,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4639,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4640,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4641,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4642,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4643,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4644,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4645,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4646,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4647,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4648,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4649,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4650,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4651,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4652,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4653,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4654,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4655,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4656,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4657,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4658,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4659,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4660,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4661,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
4662,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4663,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4664,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4665,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4666,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4667,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
4668,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
4669,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
4670,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
4671,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
4672,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
4673,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4674,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
4675,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
4676,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4677,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4678,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4679,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4680,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4681,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4682,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4683,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4684,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4685,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4686,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4687,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4688,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4689,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4690,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4691,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4692,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4693,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4694,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4695,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4696,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4697,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4698,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4699,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4700,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4701,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4702,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4703,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4704,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4705,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4706,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4707,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4708,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4709,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4710,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4711,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4712,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4713,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4714,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4715,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4716,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4717,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4718,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4719,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4720,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4721,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4722,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4723,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4724,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4725,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4726,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4727,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4728,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4729,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4730,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4731,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4732,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4733,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4734,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4735,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4736,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4737,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4738,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4739,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4740,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4741,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4742,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4743,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4744,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4745,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4746,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4747,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4748,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4749,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4750,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4751,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4752,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4753,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4754,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4755,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4756,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4757,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4758,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4759,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4760,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4761,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4762,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4763,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
4764,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
4765,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
4766,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
4767,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
4768,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
4769,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
4770,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
4771,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
4772,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
4773,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4774,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
4775,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
4776,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
4777,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
4778,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
4779,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
4780,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
4781,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
4782,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
4783,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4784,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4785,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4786,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4787,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4788,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4789,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4790,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4791,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4792,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4793,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4794,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4795,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4796,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4797,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4798,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4799,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4800,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4801,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4802,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4803,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4804,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4805,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4806,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4807,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4808,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4809,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
4810,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4811,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4812,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4813,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4814,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4815,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4816,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4817,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4818,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4819,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4820,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4821,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4822,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4823,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4824,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
4825,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4826,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4827,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4828,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4829,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4830,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4831,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4832,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4833,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4834,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4835,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4836,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4837,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4838,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4839,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4840,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4841,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4842,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4843,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4844,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4845,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4846,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4847,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4848,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4849,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4850,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4851,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4852,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4853,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4854,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4855,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4856,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4857,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4858,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4859,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4860,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4861,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4862,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4863,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4864,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4865,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4866,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4867,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4868,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4869,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4870,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4871,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4872,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4873,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4874,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4875,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4876,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4877,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4878,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4879,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
4880,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4881,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4882,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4883,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
4884,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4885,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4886,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4887,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4888,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4889,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4890,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4891,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4892,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4893,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4894,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4895,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4896,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4897,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4898,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4899,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4900,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4901,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4902,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
4903,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
4904,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
4905,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
4906,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4907,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
4908,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
4909,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
4910,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
4911,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
4912,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4913,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4914,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4915,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4916,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4917,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4918,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4919,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4920,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4921,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4922,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4923,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4924,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4925,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4926,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4927,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4928,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4929,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4930,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4931,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4932,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4933,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4934,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4935,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4936,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4937,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
4938,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4939,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4940,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4941,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4942,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4943,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4944,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4945,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4946,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4947,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4948,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4949,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4950,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4951,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4952,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4953,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4954,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4955,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4956,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4957,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4958,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4959,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4960,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4961,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4962,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4963,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4964,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4965,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4966,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4967,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4968,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4969,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4970,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4971,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4972,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4973,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4974,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4975,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4976,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4977,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4978,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4979,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4980,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4981,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4982,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4983,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4984,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4985,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4986,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4987,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4988,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4989,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4990,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4991,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4992,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4993,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4994,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
4995,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
4996,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4997,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4998,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
4999,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5000,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5001,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5002,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5003,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5004,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5005,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5006,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5007,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5008,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5009,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5010,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5011,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5012,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5013,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5014,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5015,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5016,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5017,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5018,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5019,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5020,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5021,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5022,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5023,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5024,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5025,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5026,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5027,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5028,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5029,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5030,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5031,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5032,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5033,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5034,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5035,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5036,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5037,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5038,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5039,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5040,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5041,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5042,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5043,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5044,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5045,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5046,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5047,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5048,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5049,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5050,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5051,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5052,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5053,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5054,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5055,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5056,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5057,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5058,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5059,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5060,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5061,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5062,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5063,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5064,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5065,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5066,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5067,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5068,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5069,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5070,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5071,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5072,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5073,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5074,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5075,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5076,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5077,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5078,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5079,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5080,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5081,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5082,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5083,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5084,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5085,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5086,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5087,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5088,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5089,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5090,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5091,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5092,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5093,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5094,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5095,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5096,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5097,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5098,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5099,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5100,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5101,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5102,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5103,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5104,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5105,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5106,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5107,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5108,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5109,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5110,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5111,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5112,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5113,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5114,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5115,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5116,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5117,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5118,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5119,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5120,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5121,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5122,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5123,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5124,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5125,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5126,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5127,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5128,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5129,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5130,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5131,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5132,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5133,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5134,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5135,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5136,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5137,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5138,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5139,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5140,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
5141,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
5142,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
5143,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
5144,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
5145,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
5146,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
5147,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
5148,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5149,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5150,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5151,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5152,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5153,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5154,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5155,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5156,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5157,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5158,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5159,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5160,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5161,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5162,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5163,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5164,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5165,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5166,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5167,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5168,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5169,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5170,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5171,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5172,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5173,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5174,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5175,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5176,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5177,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5178,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5179,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5180,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5181,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5182,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5183,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5184,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5185,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5186,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5187,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5188,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5189,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5190,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5191,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5192,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5193,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5194,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5195,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5196,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5197,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5198,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5199,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5200,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5201,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5202,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5203,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5204,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5205,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5206,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5207,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5208,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5209,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5210,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5211,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5212,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5213,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5214,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5215,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5216,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5217,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5218,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5219,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5220,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5221,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5222,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5223,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5224,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5225,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5226,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5227,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5228,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5229,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5230,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5231,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5232,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5233,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5234,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5235,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5236,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5237,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5238,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5239,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5240,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5241,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5242,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5243,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5244,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5245,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5246,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5247,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5248,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5249,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5250,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5251,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5252,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5253,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5254,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5255,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5256,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5257,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5258,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5259,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5260,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5261,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5262,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5263,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5264,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5265,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5266,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5267,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5268,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5269,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5270,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5271,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5272,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5273,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5274,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5275,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5276,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5277,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5278,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5279,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5280,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5281,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5282,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5283,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5284,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5285,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5286,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5287,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5288,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5289,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5290,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5291,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5292,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5293,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5294,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5295,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5296,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5297,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5298,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5299,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5300,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5301,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5302,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5303,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5304,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5305,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5306,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5307,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5308,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5309,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5310,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5311,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5312,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5313,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5314,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5315,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5316,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5317,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5318,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5319,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5320,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5321,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5322,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5323,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5324,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5325,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5326,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5327,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5328,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5329,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5330,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5331,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5332,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5333,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5334,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5335,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5336,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5337,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5338,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5339,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5340,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5341,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5342,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5343,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5344,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5345,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5346,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5347,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5348,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5349,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5350,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5351,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5352,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5353,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5354,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5355,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5356,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5357,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5358,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5359,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5360,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5361,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5362,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5363,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5364,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5365,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5366,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5367,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5368,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5369,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5370,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5371,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5372,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5373,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5374,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5375,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5376,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5377,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
5378,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
5379,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
5380,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
5381,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
5382,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
5383,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
5384,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5385,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
5386,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5387,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5388,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5389,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5390,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5391,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5392,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5393,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5394,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5395,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5396,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5397,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5398,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5399,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5400,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5401,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5402,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5403,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5404,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5405,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5406,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5407,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5408,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5409,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5410,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5411,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5412,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5413,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5414,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5415,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5416,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5417,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5418,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5419,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5420,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5421,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5422,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5423,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5424,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5425,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5426,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5427,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5428,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5429,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5430,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5431,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5432,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5433,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5434,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5435,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5436,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5437,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5438,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5439,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5440,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5441,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5442,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5443,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5444,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5445,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5446,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5447,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5448,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5449,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5450,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5451,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5452,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5453,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5454,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5455,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5456,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5457,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5458,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5459,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5460,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5461,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5462,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5463,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5464,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5465,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5466,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5467,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5468,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5469,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5470,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5471,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5472,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5473,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5474,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5475,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5476,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5477,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5478,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5479,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5480,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5481,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5482,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5483,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5484,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5485,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5486,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5487,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5488,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5489,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5490,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5491,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5492,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5493,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5494,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5495,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5496,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5497,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5498,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5499,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5500,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5501,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5502,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5503,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5504,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5505,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5506,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5507,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5508,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5509,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5510,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5511,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5512,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5513,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5514,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5515,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5516,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5517,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5518,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5519,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5520,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5521,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5522,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5523,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5524,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5525,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5526,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5527,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5528,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5529,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5530,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5531,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5532,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5533,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5534,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5535,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5536,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5537,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5538,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5539,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5540,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5541,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5542,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5543,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5544,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5545,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5546,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5547,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5548,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5549,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5550,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5551,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5552,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5553,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5554,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5555,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5556,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5557,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5558,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5559,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5560,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5561,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5562,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5563,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5564,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5565,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5566,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5567,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5568,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5569,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5570,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5571,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5572,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5573,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5574,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5575,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5576,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5577,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5578,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5579,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5580,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5581,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5582,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5583,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5584,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5585,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5586,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5587,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5588,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5589,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5590,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5591,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5592,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5593,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5594,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5595,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5596,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5597,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5598,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5599,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5600,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5601,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5602,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5603,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5604,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5605,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5606,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5607,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5608,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5609,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5610,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5611,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5612,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5613,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
5614,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
5615,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
5616,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
5617,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5618,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
5619,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
5620,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
5621,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
5622,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5623,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5624,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5625,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5626,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5627,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5628,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5629,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5630,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5631,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5632,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5633,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5634,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5635,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5636,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5637,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5638,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5639,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5640,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5641,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5642,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5643,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5644,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5645,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5646,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5647,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5648,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5649,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5650,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5651,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5652,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5653,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5654,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5655,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5656,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5657,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5658,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5659,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5660,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5661,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5662,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5663,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5664,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5665,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5666,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5667,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5668,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5669,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5670,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5671,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5672,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5673,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5674,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5675,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5676,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5677,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5678,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5679,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5680,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5681,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5682,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5683,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5684,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5685,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5686,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5687,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5688,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5689,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5690,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5691,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5692,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5693,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5694,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5695,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5696,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5697,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5698,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5699,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5700,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5701,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5702,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5703,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5704,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5705,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5706,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5707,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5708,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5709,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5710,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5711,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5712,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5713,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5714,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5715,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5716,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5717,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5718,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5719,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5720,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5721,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5722,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5723,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5724,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5725,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5726,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5727,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5728,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5729,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5730,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5731,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5732,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5733,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5734,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5735,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5736,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5737,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5738,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5739,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5740,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5741,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5742,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5743,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5744,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5745,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5746,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5747,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5748,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5749,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5750,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5751,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5752,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5753,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5754,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5755,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5756,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5757,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5758,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5759,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5760,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5761,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5762,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5763,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5764,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5765,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5766,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5767,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5768,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5769,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5770,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5771,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5772,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5773,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5774,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5775,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5776,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5777,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5778,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5779,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5780,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5781,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5782,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5783,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5784,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5785,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5786,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5787,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5788,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5789,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5790,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5791,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5792,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5793,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5794,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5795,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5796,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5797,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5798,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5799,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5800,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5801,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5802,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5803,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5804,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5805,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5806,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5807,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5808,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5809,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5810,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5811,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5812,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5813,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5814,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5815,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5816,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5817,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5818,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5819,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5820,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5821,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5822,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5823,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5824,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5825,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5826,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
5827,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5828,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5829,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5830,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5831,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5832,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5833,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5834,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5835,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5836,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5837,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5838,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5839,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5840,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5841,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5842,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5843,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5844,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5845,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5846,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5847,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5848,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
5849,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
5850,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5851,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
5852,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
5853,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
5854,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
5855,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
5856,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
5857,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
5858,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5859,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5860,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5861,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5862,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5863,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5864,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5865,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5866,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5867,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5868,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5869,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5870,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5871,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5872,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5873,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5874,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5875,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5876,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5877,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5878,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5879,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5880,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5881,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5882,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5883,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5884,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5885,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
5886,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5887,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5888,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5889,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5890,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5891,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5892,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5893,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5894,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5895,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5896,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5897,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5898,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5899,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5900,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5901,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5902,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5903,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5904,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5905,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5906,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5907,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
5908,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5909,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5910,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5911,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5912,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5913,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5914,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5915,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5916,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5917,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5918,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5919,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5920,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5921,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5922,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5923,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5924,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5925,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5926,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5927,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5928,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5929,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5930,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5931,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5932,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5933,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5934,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5935,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5936,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5937,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5938,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5939,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5940,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5941,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5942,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5943,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5944,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5945,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
5946,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5947,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5948,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5949,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5950,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5951,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5952,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5953,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5954,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5955,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5956,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
5957,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5958,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5959,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5960,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5961,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5962,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5963,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5964,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5965,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
5966,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5967,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5968,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5969,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5970,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5971,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5972,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5973,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5974,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5975,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5976,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5977,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5978,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5979,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5980,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5981,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5982,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5983,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5984,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5985,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5986,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5987,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5988,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5989,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5990,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5991,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5992,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5993,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5994,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
5995,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5996,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5997,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5998,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
5999,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6000,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6001,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6002,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6003,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6004,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6005,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6006,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6007,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6008,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6009,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6010,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6011,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6012,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6013,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6014,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6015,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6016,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6017,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6018,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6019,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6020,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6021,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6022,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6023,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6024,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6025,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6026,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6027,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6028,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6029,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6030,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6031,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6032,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6033,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6034,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6035,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6036,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6037,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6038,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6039,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6040,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6041,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6042,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6043,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6044,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6045,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6046,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6047,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6048,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6049,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6050,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6051,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6052,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6053,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6054,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6055,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6056,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6057,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6058,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6059,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6060,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6061,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6062,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6063,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6064,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6065,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6066,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6067,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6068,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6069,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6070,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6071,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6072,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6073,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6074,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6075,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6076,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6077,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6078,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6079,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6080,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6081,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6082,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6083,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6084,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6085,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6086,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
6087,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
6088,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
6089,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
6090,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
6091,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
6092,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
6093,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
6094,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6095,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6096,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6097,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6098,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6099,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6100,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6101,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6102,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6103,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6104,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6105,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6106,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6107,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6108,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6109,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6110,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6111,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6112,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6113,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6114,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6115,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6116,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6117,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6118,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6119,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6120,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6121,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6122,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6123,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6124,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6125,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6126,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6127,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6128,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6129,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6130,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6131,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6132,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6133,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6134,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6135,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6136,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6137,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6138,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6139,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6140,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6141,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6142,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6143,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6144,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6145,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6146,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6147,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6148,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6149,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6150,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6151,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6152,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6153,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6154,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6155,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6156,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6157,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6158,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6159,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6160,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6161,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6162,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6163,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6164,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6165,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6166,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6167,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6168,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6169,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6170,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6171,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6172,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6173,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6174,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6175,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6176,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6177,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6178,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6179,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6180,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6181,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6182,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
6183,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6184,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
6185,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
6186,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
6187,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
6188,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
6189,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
6190,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
6191,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
6192,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
6193,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
6194,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6195,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
6196,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
6197,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
6198,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
6199,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
6200,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
6201,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
6202,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6203,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6204,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6205,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6206,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6207,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6208,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6209,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6210,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6211,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6212,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6213,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6214,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6215,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6216,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6217,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6218,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6219,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6220,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6221,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6222,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6223,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6224,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6225,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6226,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6227,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6228,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6229,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6230,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6231,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6232,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6233,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6234,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6235,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6236,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6237,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6238,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6239,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6240,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6241,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6242,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6243,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6244,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6245,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6246,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6247,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6248,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6249,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6250,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6251,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6252,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6253,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6254,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6255,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6256,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6257,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6258,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6259,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6260,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6261,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6262,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6263,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6264,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6265,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6266,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6267,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6268,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6269,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6270,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6271,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6272,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6273,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6274,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6275,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6276,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6277,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6278,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6279,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6280,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6281,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6282,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6283,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6284,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6285,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6286,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6287,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6288,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6289,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6290,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6291,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6292,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6293,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6294,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6295,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6296,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6297,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6298,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6299,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6300,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6301,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6302,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6303,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6304,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6305,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6306,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6307,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6308,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6309,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6310,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6311,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6312,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6313,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6314,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6315,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6316,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6317,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6318,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6319,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6320,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6321,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6322,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
6323,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
6324,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
6325,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
6326,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
6327,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6328,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6329,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
6330,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
6331,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
6332,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6333,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6334,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6335,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6336,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6337,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6338,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6339,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6340,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6341,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6342,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6343,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6344,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6345,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6346,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6347,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6348,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6349,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6350,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6351,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6352,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6353,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6354,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6355,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6356,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6357,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6358,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6359,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6360,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6361,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6362,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6363,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6364,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6365,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6366,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6367,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6368,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6369,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6370,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6371,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6372,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6373,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6374,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6375,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6376,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6377,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6378,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6379,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6380,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6381,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6382,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6383,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6384,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6385,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6386,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6387,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6388,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6389,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6390,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6391,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6392,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6393,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6394,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6395,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6396,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6397,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6398,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6399,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6400,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6401,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6402,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6403,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6404,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6405,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6406,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6407,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6408,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6409,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6410,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6411,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6412,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6413,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6414,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6415,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6416,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6417,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6418,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6419,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
6420,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
6421,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
6422,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
6423,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
6424,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
6425,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
6426,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
6427,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6428,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
6429,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
6430,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
6431,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
6432,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
6433,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
6434,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
6435,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
6436,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
6437,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
6438,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
6439,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6440,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6441,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6442,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6443,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6444,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6445,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6446,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6447,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6448,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6449,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6450,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6451,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6452,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6453,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6454,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6455,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6456,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6457,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6458,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6459,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6460,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6461,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6462,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6463,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6464,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6465,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6466,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6467,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6468,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6469,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6470,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6471,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6472,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6473,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6474,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6475,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6476,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6477,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6478,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6479,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6480,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6481,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
6482,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6483,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6484,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6485,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6486,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6487,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6488,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6489,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6490,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6491,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6492,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6493,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6494,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6495,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6496,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6497,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6498,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6499,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6500,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6501,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6502,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6503,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6504,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6505,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6506,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6507,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6508,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6509,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6510,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6511,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6512,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6513,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6514,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6515,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6516,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6517,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6518,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6519,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6520,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6521,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6522,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6523,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6524,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6525,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6526,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6527,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6528,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6529,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6530,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6531,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6532,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6533,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6534,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6535,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6536,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6537,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6538,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6539,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6540,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6541,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6542,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6543,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6544,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6545,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6546,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6547,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6548,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6549,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6550,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6551,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6552,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6553,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6554,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6555,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6556,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6557,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6558,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6559,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6560,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
6561,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
6562,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6563,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
6564,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
6565,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
6566,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
6567,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
6568,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
6569,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6570,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6571,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6572,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6573,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6574,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6575,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6576,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6577,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6578,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6579,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6580,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6581,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6582,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6583,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6584,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6585,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6586,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6587,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6588,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6589,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6590,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6591,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6592,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6593,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6594,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6595,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6596,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6597,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6598,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6599,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6600,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6601,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6602,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6603,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6604,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6605,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6606,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6607,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6608,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6609,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6610,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6611,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6612,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6613,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6614,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6615,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6616,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
6617,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6618,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6619,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6620,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6621,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6622,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6623,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6624,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6625,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6626,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6627,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6628,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6629,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6630,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6631,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6632,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6633,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6634,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6635,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6636,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6637,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6638,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6639,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
6640,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6641,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6642,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6643,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6644,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6645,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6646,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6647,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6648,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6649,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6650,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6651,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6652,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6653,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6654,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6655,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
6656,"Increased variability in power generation due to large scale integration of renewable energy sources such as wind and solar power is a significant technical challenge in power systems operations and control. In addition, there is a compelling value in reducing the peak demand since it occurs only for a small fraction of time, while the power system is designed to reliably satisfy the peak demand. One promising approach to reduce variability of renewable generation and peak demand is to harness the inherent flexibility of electric power loads of consumers. Efficient control techniques are required to manage flexibility in consumer demands. Advancements in sensing, communications and computational technologies infused into the power system resulting in the cyber-physical-social electric grid, are creating opportunities for novel control solutions. In this paper, we first formulate a centralized demand side management approach. Next, we consider a decentralized approach for controlling the loads where the flexible load consumers play a non-cooperative game among each other. We show that Nash equilibria exist for this game. Our main technical result is that the demand response game in decentralized approach has the property of being a valid monotone utility game. This in turn leads to robust lower bounds on the price of anarchy (POA) for our game.",pratyush chakraborty,Games,2014.0,10.1109/SmartGridComm.2014.7007720,2014 IEEE International Conference on Smart Grid Communications (SmartGridComm),Chakraborty2014,False,,IEEE,Not available,A demand response game and its robust price of anarchy,251780ce58a1c0f564342aaae2120172,https://ieeexplore.ieee.org/document/7007720/
6657,"Increased variability in power generation due to large scale integration of renewable energy sources such as wind and solar power is a significant technical challenge in power systems operations and control. In addition, there is a compelling value in reducing the peak demand since it occurs only for a small fraction of time, while the power system is designed to reliably satisfy the peak demand. One promising approach to reduce variability of renewable generation and peak demand is to harness the inherent flexibility of electric power loads of consumers. Efficient control techniques are required to manage flexibility in consumer demands. Advancements in sensing, communications and computational technologies infused into the power system resulting in the cyber-physical-social electric grid, are creating opportunities for novel control solutions. In this paper, we first formulate a centralized demand side management approach. Next, we consider a decentralized approach for controlling the loads where the flexible load consumers play a non-cooperative game among each other. We show that Nash equilibria exist for this game. Our main technical result is that the demand response game in decentralized approach has the property of being a valid monotone utility game. This in turn leads to robust lower bounds on the price of anarchy (POA) for our game.",pratyush chakraborty,Power demand,2014.0,10.1109/SmartGridComm.2014.7007720,2014 IEEE International Conference on Smart Grid Communications (SmartGridComm),Chakraborty2014,False,,IEEE,Not available,A demand response game and its robust price of anarchy,251780ce58a1c0f564342aaae2120172,https://ieeexplore.ieee.org/document/7007720/
6658,"Increased variability in power generation due to large scale integration of renewable energy sources such as wind and solar power is a significant technical challenge in power systems operations and control. In addition, there is a compelling value in reducing the peak demand since it occurs only for a small fraction of time, while the power system is designed to reliably satisfy the peak demand. One promising approach to reduce variability of renewable generation and peak demand is to harness the inherent flexibility of electric power loads of consumers. Efficient control techniques are required to manage flexibility in consumer demands. Advancements in sensing, communications and computational technologies infused into the power system resulting in the cyber-physical-social electric grid, are creating opportunities for novel control solutions. In this paper, we first formulate a centralized demand side management approach. Next, we consider a decentralized approach for controlling the loads where the flexible load consumers play a non-cooperative game among each other. We show that Nash equilibria exist for this game. Our main technical result is that the demand response game in decentralized approach has the property of being a valid monotone utility game. This in turn leads to robust lower bounds on the price of anarchy (POA) for our game.",pratyush chakraborty,Load management,2014.0,10.1109/SmartGridComm.2014.7007720,2014 IEEE International Conference on Smart Grid Communications (SmartGridComm),Chakraborty2014,False,,IEEE,Not available,A demand response game and its robust price of anarchy,251780ce58a1c0f564342aaae2120172,https://ieeexplore.ieee.org/document/7007720/
6659,"Increased variability in power generation due to large scale integration of renewable energy sources such as wind and solar power is a significant technical challenge in power systems operations and control. In addition, there is a compelling value in reducing the peak demand since it occurs only for a small fraction of time, while the power system is designed to reliably satisfy the peak demand. One promising approach to reduce variability of renewable generation and peak demand is to harness the inherent flexibility of electric power loads of consumers. Efficient control techniques are required to manage flexibility in consumer demands. Advancements in sensing, communications and computational technologies infused into the power system resulting in the cyber-physical-social electric grid, are creating opportunities for novel control solutions. In this paper, we first formulate a centralized demand side management approach. Next, we consider a decentralized approach for controlling the loads where the flexible load consumers play a non-cooperative game among each other. We show that Nash equilibria exist for this game. Our main technical result is that the demand response game in decentralized approach has the property of being a valid monotone utility game. This in turn leads to robust lower bounds on the price of anarchy (POA) for our game.",pratyush chakraborty,Schedules,2014.0,10.1109/SmartGridComm.2014.7007720,2014 IEEE International Conference on Smart Grid Communications (SmartGridComm),Chakraborty2014,False,,IEEE,Not available,A demand response game and its robust price of anarchy,251780ce58a1c0f564342aaae2120172,https://ieeexplore.ieee.org/document/7007720/
6660,"Increased variability in power generation due to large scale integration of renewable energy sources such as wind and solar power is a significant technical challenge in power systems operations and control. In addition, there is a compelling value in reducing the peak demand since it occurs only for a small fraction of time, while the power system is designed to reliably satisfy the peak demand. One promising approach to reduce variability of renewable generation and peak demand is to harness the inherent flexibility of electric power loads of consumers. Efficient control techniques are required to manage flexibility in consumer demands. Advancements in sensing, communications and computational technologies infused into the power system resulting in the cyber-physical-social electric grid, are creating opportunities for novel control solutions. In this paper, we first formulate a centralized demand side management approach. Next, we consider a decentralized approach for controlling the loads where the flexible load consumers play a non-cooperative game among each other. We show that Nash equilibria exist for this game. Our main technical result is that the demand response game in decentralized approach has the property of being a valid monotone utility game. This in turn leads to robust lower bounds on the price of anarchy (POA) for our game.",pratyush chakraborty,Centralized control,2014.0,10.1109/SmartGridComm.2014.7007720,2014 IEEE International Conference on Smart Grid Communications (SmartGridComm),Chakraborty2014,False,,IEEE,Not available,A demand response game and its robust price of anarchy,251780ce58a1c0f564342aaae2120172,https://ieeexplore.ieee.org/document/7007720/
6661,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6662,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6663,"Increased variability in power generation due to large scale integration of renewable energy sources such as wind and solar power is a significant technical challenge in power systems operations and control. In addition, there is a compelling value in reducing the peak demand since it occurs only for a small fraction of time, while the power system is designed to reliably satisfy the peak demand. One promising approach to reduce variability of renewable generation and peak demand is to harness the inherent flexibility of electric power loads of consumers. Efficient control techniques are required to manage flexibility in consumer demands. Advancements in sensing, communications and computational technologies infused into the power system resulting in the cyber-physical-social electric grid, are creating opportunities for novel control solutions. In this paper, we first formulate a centralized demand side management approach. Next, we consider a decentralized approach for controlling the loads where the flexible load consumers play a non-cooperative game among each other. We show that Nash equilibria exist for this game. Our main technical result is that the demand response game in decentralized approach has the property of being a valid monotone utility game. This in turn leads to robust lower bounds on the price of anarchy (POA) for our game.",pratyush chakraborty,Nash equilibrium,2014.0,10.1109/SmartGridComm.2014.7007720,2014 IEEE International Conference on Smart Grid Communications (SmartGridComm),Chakraborty2014,False,,IEEE,Not available,A demand response game and its robust price of anarchy,251780ce58a1c0f564342aaae2120172,https://ieeexplore.ieee.org/document/7007720/
6664,"Increased variability in power generation due to large scale integration of renewable energy sources such as wind and solar power is a significant technical challenge in power systems operations and control. In addition, there is a compelling value in reducing the peak demand since it occurs only for a small fraction of time, while the power system is designed to reliably satisfy the peak demand. One promising approach to reduce variability of renewable generation and peak demand is to harness the inherent flexibility of electric power loads of consumers. Efficient control techniques are required to manage flexibility in consumer demands. Advancements in sensing, communications and computational technologies infused into the power system resulting in the cyber-physical-social electric grid, are creating opportunities for novel control solutions. In this paper, we first formulate a centralized demand side management approach. Next, we consider a decentralized approach for controlling the loads where the flexible load consumers play a non-cooperative game among each other. We show that Nash equilibria exist for this game. Our main technical result is that the demand response game in decentralized approach has the property of being a valid monotone utility game. This in turn leads to robust lower bounds on the price of anarchy (POA) for our game.",pramod khargonekar,Games,2014.0,10.1109/SmartGridComm.2014.7007720,2014 IEEE International Conference on Smart Grid Communications (SmartGridComm),Chakraborty2014,False,,IEEE,Not available,A demand response game and its robust price of anarchy,251780ce58a1c0f564342aaae2120172,https://ieeexplore.ieee.org/document/7007720/
6665,"Increased variability in power generation due to large scale integration of renewable energy sources such as wind and solar power is a significant technical challenge in power systems operations and control. In addition, there is a compelling value in reducing the peak demand since it occurs only for a small fraction of time, while the power system is designed to reliably satisfy the peak demand. One promising approach to reduce variability of renewable generation and peak demand is to harness the inherent flexibility of electric power loads of consumers. Efficient control techniques are required to manage flexibility in consumer demands. Advancements in sensing, communications and computational technologies infused into the power system resulting in the cyber-physical-social electric grid, are creating opportunities for novel control solutions. In this paper, we first formulate a centralized demand side management approach. Next, we consider a decentralized approach for controlling the loads where the flexible load consumers play a non-cooperative game among each other. We show that Nash equilibria exist for this game. Our main technical result is that the demand response game in decentralized approach has the property of being a valid monotone utility game. This in turn leads to robust lower bounds on the price of anarchy (POA) for our game.",pramod khargonekar,Power demand,2014.0,10.1109/SmartGridComm.2014.7007720,2014 IEEE International Conference on Smart Grid Communications (SmartGridComm),Chakraborty2014,False,,IEEE,Not available,A demand response game and its robust price of anarchy,251780ce58a1c0f564342aaae2120172,https://ieeexplore.ieee.org/document/7007720/
6666,"Increased variability in power generation due to large scale integration of renewable energy sources such as wind and solar power is a significant technical challenge in power systems operations and control. In addition, there is a compelling value in reducing the peak demand since it occurs only for a small fraction of time, while the power system is designed to reliably satisfy the peak demand. One promising approach to reduce variability of renewable generation and peak demand is to harness the inherent flexibility of electric power loads of consumers. Efficient control techniques are required to manage flexibility in consumer demands. Advancements in sensing, communications and computational technologies infused into the power system resulting in the cyber-physical-social electric grid, are creating opportunities for novel control solutions. In this paper, we first formulate a centralized demand side management approach. Next, we consider a decentralized approach for controlling the loads where the flexible load consumers play a non-cooperative game among each other. We show that Nash equilibria exist for this game. Our main technical result is that the demand response game in decentralized approach has the property of being a valid monotone utility game. This in turn leads to robust lower bounds on the price of anarchy (POA) for our game.",pramod khargonekar,Load management,2014.0,10.1109/SmartGridComm.2014.7007720,2014 IEEE International Conference on Smart Grid Communications (SmartGridComm),Chakraborty2014,False,,IEEE,Not available,A demand response game and its robust price of anarchy,251780ce58a1c0f564342aaae2120172,https://ieeexplore.ieee.org/document/7007720/
6667,"Increased variability in power generation due to large scale integration of renewable energy sources such as wind and solar power is a significant technical challenge in power systems operations and control. In addition, there is a compelling value in reducing the peak demand since it occurs only for a small fraction of time, while the power system is designed to reliably satisfy the peak demand. One promising approach to reduce variability of renewable generation and peak demand is to harness the inherent flexibility of electric power loads of consumers. Efficient control techniques are required to manage flexibility in consumer demands. Advancements in sensing, communications and computational technologies infused into the power system resulting in the cyber-physical-social electric grid, are creating opportunities for novel control solutions. In this paper, we first formulate a centralized demand side management approach. Next, we consider a decentralized approach for controlling the loads where the flexible load consumers play a non-cooperative game among each other. We show that Nash equilibria exist for this game. Our main technical result is that the demand response game in decentralized approach has the property of being a valid monotone utility game. This in turn leads to robust lower bounds on the price of anarchy (POA) for our game.",pramod khargonekar,Schedules,2014.0,10.1109/SmartGridComm.2014.7007720,2014 IEEE International Conference on Smart Grid Communications (SmartGridComm),Chakraborty2014,False,,IEEE,Not available,A demand response game and its robust price of anarchy,251780ce58a1c0f564342aaae2120172,https://ieeexplore.ieee.org/document/7007720/
6668,"Increased variability in power generation due to large scale integration of renewable energy sources such as wind and solar power is a significant technical challenge in power systems operations and control. In addition, there is a compelling value in reducing the peak demand since it occurs only for a small fraction of time, while the power system is designed to reliably satisfy the peak demand. One promising approach to reduce variability of renewable generation and peak demand is to harness the inherent flexibility of electric power loads of consumers. Efficient control techniques are required to manage flexibility in consumer demands. Advancements in sensing, communications and computational technologies infused into the power system resulting in the cyber-physical-social electric grid, are creating opportunities for novel control solutions. In this paper, we first formulate a centralized demand side management approach. Next, we consider a decentralized approach for controlling the loads where the flexible load consumers play a non-cooperative game among each other. We show that Nash equilibria exist for this game. Our main technical result is that the demand response game in decentralized approach has the property of being a valid monotone utility game. This in turn leads to robust lower bounds on the price of anarchy (POA) for our game.",pramod khargonekar,Centralized control,2014.0,10.1109/SmartGridComm.2014.7007720,2014 IEEE International Conference on Smart Grid Communications (SmartGridComm),Chakraborty2014,False,,IEEE,Not available,A demand response game and its robust price of anarchy,251780ce58a1c0f564342aaae2120172,https://ieeexplore.ieee.org/document/7007720/
6669,"Increased variability in power generation due to large scale integration of renewable energy sources such as wind and solar power is a significant technical challenge in power systems operations and control. In addition, there is a compelling value in reducing the peak demand since it occurs only for a small fraction of time, while the power system is designed to reliably satisfy the peak demand. One promising approach to reduce variability of renewable generation and peak demand is to harness the inherent flexibility of electric power loads of consumers. Efficient control techniques are required to manage flexibility in consumer demands. Advancements in sensing, communications and computational technologies infused into the power system resulting in the cyber-physical-social electric grid, are creating opportunities for novel control solutions. In this paper, we first formulate a centralized demand side management approach. Next, we consider a decentralized approach for controlling the loads where the flexible load consumers play a non-cooperative game among each other. We show that Nash equilibria exist for this game. Our main technical result is that the demand response game in decentralized approach has the property of being a valid monotone utility game. This in turn leads to robust lower bounds on the price of anarchy (POA) for our game.",pramod khargonekar,Nash equilibrium,2014.0,10.1109/SmartGridComm.2014.7007720,2014 IEEE International Conference on Smart Grid Communications (SmartGridComm),Chakraborty2014,False,,IEEE,Not available,A demand response game and its robust price of anarchy,251780ce58a1c0f564342aaae2120172,https://ieeexplore.ieee.org/document/7007720/
6670,"Investments in security technologies by strategic users is typically modeled as a public good problem, known as the Interdependent Security (IDS) game. The equilibria for such games are often inefficient, as selfish users free-ride on positive externalities of others' contributions. We present a mechanism that implements the socially optimal equilibrium in an IDS game through a message exchange process; this mechanism does not need to monitor or audit users. However, it does not necessarily guarantee voluntary participation, often a trivial condition to satisfy in many resource allocation problems, but made much harder due to the incentive to stay out and free-ride on others' investments. We discuss the role of cyber insurance in this setting.",parinaz naghizadeh,Security,2014.0,10.1109/ITA.2014.6804216,2014 Information Theory and Applications Workshop (ITA),Naghizadeh2014,False,,IEEE,Not available,Closing the price of anarchy gap in the interdependent security game,92d4d6c85c3bf830b63aad30635033a7,https://ieeexplore.ieee.org/document/6804216/
6671,"Investments in security technologies by strategic users is typically modeled as a public good problem, known as the Interdependent Security (IDS) game. The equilibria for such games are often inefficient, as selfish users free-ride on positive externalities of others' contributions. We present a mechanism that implements the socially optimal equilibrium in an IDS game through a message exchange process; this mechanism does not need to monitor or audit users. However, it does not necessarily guarantee voluntary participation, often a trivial condition to satisfy in many resource allocation problems, but made much harder due to the incentive to stay out and free-ride on others' investments. We discuss the role of cyber insurance in this setting.",parinaz naghizadeh,Investment,2014.0,10.1109/ITA.2014.6804216,2014 Information Theory and Applications Workshop (ITA),Naghizadeh2014,False,,IEEE,Not available,Closing the price of anarchy gap in the interdependent security game,92d4d6c85c3bf830b63aad30635033a7,https://ieeexplore.ieee.org/document/6804216/
6672,"Investments in security technologies by strategic users is typically modeled as a public good problem, known as the Interdependent Security (IDS) game. The equilibria for such games are often inefficient, as selfish users free-ride on positive externalities of others' contributions. We present a mechanism that implements the socially optimal equilibrium in an IDS game through a message exchange process; this mechanism does not need to monitor or audit users. However, it does not necessarily guarantee voluntary participation, often a trivial condition to satisfy in many resource allocation problems, but made much harder due to the incentive to stay out and free-ride on others' investments. We discuss the role of cyber insurance in this setting.",parinaz naghizadeh,Games,2014.0,10.1109/ITA.2014.6804216,2014 Information Theory and Applications Workshop (ITA),Naghizadeh2014,False,,IEEE,Not available,Closing the price of anarchy gap in the interdependent security game,92d4d6c85c3bf830b63aad30635033a7,https://ieeexplore.ieee.org/document/6804216/
6673,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6674,"Investments in security technologies by strategic users is typically modeled as a public good problem, known as the Interdependent Security (IDS) game. The equilibria for such games are often inefficient, as selfish users free-ride on positive externalities of others' contributions. We present a mechanism that implements the socially optimal equilibrium in an IDS game through a message exchange process; this mechanism does not need to monitor or audit users. However, it does not necessarily guarantee voluntary participation, often a trivial condition to satisfy in many resource allocation problems, but made much harder due to the incentive to stay out and free-ride on others' investments. We discuss the role of cyber insurance in this setting.",parinaz naghizadeh,Nash equilibrium,2014.0,10.1109/ITA.2014.6804216,2014 Information Theory and Applications Workshop (ITA),Naghizadeh2014,False,,IEEE,Not available,Closing the price of anarchy gap in the interdependent security game,92d4d6c85c3bf830b63aad30635033a7,https://ieeexplore.ieee.org/document/6804216/
6675,"Investments in security technologies by strategic users is typically modeled as a public good problem, known as the Interdependent Security (IDS) game. The equilibria for such games are often inefficient, as selfish users free-ride on positive externalities of others' contributions. We present a mechanism that implements the socially optimal equilibrium in an IDS game through a message exchange process; this mechanism does not need to monitor or audit users. However, it does not necessarily guarantee voluntary participation, often a trivial condition to satisfy in many resource allocation problems, but made much harder due to the incentive to stay out and free-ride on others' investments. We discuss the role of cyber insurance in this setting.",parinaz naghizadeh,Vectors,2014.0,10.1109/ITA.2014.6804216,2014 Information Theory and Applications Workshop (ITA),Naghizadeh2014,False,,IEEE,Not available,Closing the price of anarchy gap in the interdependent security game,92d4d6c85c3bf830b63aad30635033a7,https://ieeexplore.ieee.org/document/6804216/
6676,"Investments in security technologies by strategic users is typically modeled as a public good problem, known as the Interdependent Security (IDS) game. The equilibria for such games are often inefficient, as selfish users free-ride on positive externalities of others' contributions. We present a mechanism that implements the socially optimal equilibrium in an IDS game through a message exchange process; this mechanism does not need to monitor or audit users. However, it does not necessarily guarantee voluntary participation, often a trivial condition to satisfy in many resource allocation problems, but made much harder due to the incentive to stay out and free-ride on others' investments. We discuss the role of cyber insurance in this setting.",parinaz naghizadeh,Proposals,2014.0,10.1109/ITA.2014.6804216,2014 Information Theory and Applications Workshop (ITA),Naghizadeh2014,False,,IEEE,Not available,Closing the price of anarchy gap in the interdependent security game,92d4d6c85c3bf830b63aad30635033a7,https://ieeexplore.ieee.org/document/6804216/
6677,"Investments in security technologies by strategic users is typically modeled as a public good problem, known as the Interdependent Security (IDS) game. The equilibria for such games are often inefficient, as selfish users free-ride on positive externalities of others' contributions. We present a mechanism that implements the socially optimal equilibrium in an IDS game through a message exchange process; this mechanism does not need to monitor or audit users. However, it does not necessarily guarantee voluntary participation, often a trivial condition to satisfy in many resource allocation problems, but made much harder due to the incentive to stay out and free-ride on others' investments. We discuss the role of cyber insurance in this setting.",parinaz naghizadeh,Monitoring,2014.0,10.1109/ITA.2014.6804216,2014 Information Theory and Applications Workshop (ITA),Naghizadeh2014,False,,IEEE,Not available,Closing the price of anarchy gap in the interdependent security game,92d4d6c85c3bf830b63aad30635033a7,https://ieeexplore.ieee.org/document/6804216/
6678,"Investments in security technologies by strategic users is typically modeled as a public good problem, known as the Interdependent Security (IDS) game. The equilibria for such games are often inefficient, as selfish users free-ride on positive externalities of others' contributions. We present a mechanism that implements the socially optimal equilibrium in an IDS game through a message exchange process; this mechanism does not need to monitor or audit users. However, it does not necessarily guarantee voluntary participation, often a trivial condition to satisfy in many resource allocation problems, but made much harder due to the incentive to stay out and free-ride on others' investments. We discuss the role of cyber insurance in this setting.",mingyan liu,Security,2014.0,10.1109/ITA.2014.6804216,2014 Information Theory and Applications Workshop (ITA),Naghizadeh2014,False,,IEEE,Not available,Closing the price of anarchy gap in the interdependent security game,92d4d6c85c3bf830b63aad30635033a7,https://ieeexplore.ieee.org/document/6804216/
6679,"Investments in security technologies by strategic users is typically modeled as a public good problem, known as the Interdependent Security (IDS) game. The equilibria for such games are often inefficient, as selfish users free-ride on positive externalities of others' contributions. We present a mechanism that implements the socially optimal equilibrium in an IDS game through a message exchange process; this mechanism does not need to monitor or audit users. However, it does not necessarily guarantee voluntary participation, often a trivial condition to satisfy in many resource allocation problems, but made much harder due to the incentive to stay out and free-ride on others' investments. We discuss the role of cyber insurance in this setting.",mingyan liu,Investment,2014.0,10.1109/ITA.2014.6804216,2014 Information Theory and Applications Workshop (ITA),Naghizadeh2014,False,,IEEE,Not available,Closing the price of anarchy gap in the interdependent security game,92d4d6c85c3bf830b63aad30635033a7,https://ieeexplore.ieee.org/document/6804216/
6680,"Investments in security technologies by strategic users is typically modeled as a public good problem, known as the Interdependent Security (IDS) game. The equilibria for such games are often inefficient, as selfish users free-ride on positive externalities of others' contributions. We present a mechanism that implements the socially optimal equilibrium in an IDS game through a message exchange process; this mechanism does not need to monitor or audit users. However, it does not necessarily guarantee voluntary participation, often a trivial condition to satisfy in many resource allocation problems, but made much harder due to the incentive to stay out and free-ride on others' investments. We discuss the role of cyber insurance in this setting.",mingyan liu,Games,2014.0,10.1109/ITA.2014.6804216,2014 Information Theory and Applications Workshop (ITA),Naghizadeh2014,False,,IEEE,Not available,Closing the price of anarchy gap in the interdependent security game,92d4d6c85c3bf830b63aad30635033a7,https://ieeexplore.ieee.org/document/6804216/
6681,"Investments in security technologies by strategic users is typically modeled as a public good problem, known as the Interdependent Security (IDS) game. The equilibria for such games are often inefficient, as selfish users free-ride on positive externalities of others' contributions. We present a mechanism that implements the socially optimal equilibrium in an IDS game through a message exchange process; this mechanism does not need to monitor or audit users. However, it does not necessarily guarantee voluntary participation, often a trivial condition to satisfy in many resource allocation problems, but made much harder due to the incentive to stay out and free-ride on others' investments. We discuss the role of cyber insurance in this setting.",mingyan liu,Nash equilibrium,2014.0,10.1109/ITA.2014.6804216,2014 Information Theory and Applications Workshop (ITA),Naghizadeh2014,False,,IEEE,Not available,Closing the price of anarchy gap in the interdependent security game,92d4d6c85c3bf830b63aad30635033a7,https://ieeexplore.ieee.org/document/6804216/
6682,"Investments in security technologies by strategic users is typically modeled as a public good problem, known as the Interdependent Security (IDS) game. The equilibria for such games are often inefficient, as selfish users free-ride on positive externalities of others' contributions. We present a mechanism that implements the socially optimal equilibrium in an IDS game through a message exchange process; this mechanism does not need to monitor or audit users. However, it does not necessarily guarantee voluntary participation, often a trivial condition to satisfy in many resource allocation problems, but made much harder due to the incentive to stay out and free-ride on others' investments. We discuss the role of cyber insurance in this setting.",mingyan liu,Vectors,2014.0,10.1109/ITA.2014.6804216,2014 Information Theory and Applications Workshop (ITA),Naghizadeh2014,False,,IEEE,Not available,Closing the price of anarchy gap in the interdependent security game,92d4d6c85c3bf830b63aad30635033a7,https://ieeexplore.ieee.org/document/6804216/
6683,"Investments in security technologies by strategic users is typically modeled as a public good problem, known as the Interdependent Security (IDS) game. The equilibria for such games are often inefficient, as selfish users free-ride on positive externalities of others' contributions. We present a mechanism that implements the socially optimal equilibrium in an IDS game through a message exchange process; this mechanism does not need to monitor or audit users. However, it does not necessarily guarantee voluntary participation, often a trivial condition to satisfy in many resource allocation problems, but made much harder due to the incentive to stay out and free-ride on others' investments. We discuss the role of cyber insurance in this setting.",mingyan liu,Proposals,2014.0,10.1109/ITA.2014.6804216,2014 Information Theory and Applications Workshop (ITA),Naghizadeh2014,False,,IEEE,Not available,Closing the price of anarchy gap in the interdependent security game,92d4d6c85c3bf830b63aad30635033a7,https://ieeexplore.ieee.org/document/6804216/
6684,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6685,"Investments in security technologies by strategic users is typically modeled as a public good problem, known as the Interdependent Security (IDS) game. The equilibria for such games are often inefficient, as selfish users free-ride on positive externalities of others' contributions. We present a mechanism that implements the socially optimal equilibrium in an IDS game through a message exchange process; this mechanism does not need to monitor or audit users. However, it does not necessarily guarantee voluntary participation, often a trivial condition to satisfy in many resource allocation problems, but made much harder due to the incentive to stay out and free-ride on others' investments. We discuss the role of cyber insurance in this setting.",mingyan liu,Monitoring,2014.0,10.1109/ITA.2014.6804216,2014 Information Theory and Applications Workshop (ITA),Naghizadeh2014,False,,IEEE,Not available,Closing the price of anarchy gap in the interdependent security game,92d4d6c85c3bf830b63aad30635033a7,https://ieeexplore.ieee.org/document/6804216/
6686,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",lok law,Games,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
6687,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",lok law,Nash equilibrium,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
6688,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",lok law,Optimized production technology,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
6689,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",lok law,Resource management,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
6690,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",lok law,Computational modeling,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
6691,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",lok law,Computer science,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
6692,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",lok law,Erbium,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
6693,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",jianwei huang,Games,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
6694,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",jianwei huang,Nash equilibrium,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
6695,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6696,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",jianwei huang,Optimized production technology,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
6697,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",jianwei huang,Resource management,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
6698,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",jianwei huang,Computational modeling,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
6699,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",jianwei huang,Computer science,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
6700,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",jianwei huang,Erbium,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
6701,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",mingyan liu,Games,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
6702,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",mingyan liu,Nash equilibrium,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
6703,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",mingyan liu,Optimized production technology,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
6704,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",mingyan liu,Resource management,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
6705,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",mingyan liu,Computational modeling,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
6706,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6707,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",mingyan liu,Computer science,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
6708,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",mingyan liu,Erbium,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
6709,"In this paper, we consider a cognitive radio network where multiple heterogenous secondary users (SUs) compete for transmissions on idle primary channels. We model this as a singleton congestion game, where the probability for an SU to successfully access a channel decreases with the number of SUs selecting the same channel. In particular, we consider player-specific payoffs that depend not only on the shares of the channel but also on different preference constants. Such system can be modeled as a congestion game, and we study the price of anarchy (PoA) for four families of such a game: identical, player-specific symmetric, resource-specific symmetric, and asymmetric games. We characterize the worst-case PoA in terms of the number of SUs and channels, and illustrate the network scenarios under which the worse case performance is reached. We further illustrate the PoA results with two Medium Access Control (MAC) schemes: uniform MAC and slotted Aloha. For both cases, we observe that the average performance of the game equilibrium is better than the worst-case PoA. Our study sheds light on how to design stable systems with smaller efficiency loss of the equilibrium.",lok law,Cognitive radio,2012.0,10.1109/TWC.2012.083112.120371,IEEE Transactions on Wireless Communications,Law2012,False,,IEEE,Not available,Price of Anarchy for Congestion Games in Cognitive Radio Networks,d78287bf43af78c169dac2e1b5572756,https://ieeexplore.ieee.org/document/6294502/
6710,"In this paper, we consider a cognitive radio network where multiple heterogenous secondary users (SUs) compete for transmissions on idle primary channels. We model this as a singleton congestion game, where the probability for an SU to successfully access a channel decreases with the number of SUs selecting the same channel. In particular, we consider player-specific payoffs that depend not only on the shares of the channel but also on different preference constants. Such system can be modeled as a congestion game, and we study the price of anarchy (PoA) for four families of such a game: identical, player-specific symmetric, resource-specific symmetric, and asymmetric games. We characterize the worst-case PoA in terms of the number of SUs and channels, and illustrate the network scenarios under which the worse case performance is reached. We further illustrate the PoA results with two Medium Access Control (MAC) schemes: uniform MAC and slotted Aloha. For both cases, we observe that the average performance of the game equilibrium is better than the worst-case PoA. Our study sheds light on how to design stable systems with smaller efficiency loss of the equilibrium.",lok law,spectrum sharing,2012.0,10.1109/TWC.2012.083112.120371,IEEE Transactions on Wireless Communications,Law2012,False,,IEEE,Not available,Price of Anarchy for Congestion Games in Cognitive Radio Networks,d78287bf43af78c169dac2e1b5572756,https://ieeexplore.ieee.org/document/6294502/
6711,"In this paper, we consider a cognitive radio network where multiple heterogenous secondary users (SUs) compete for transmissions on idle primary channels. We model this as a singleton congestion game, where the probability for an SU to successfully access a channel decreases with the number of SUs selecting the same channel. In particular, we consider player-specific payoffs that depend not only on the shares of the channel but also on different preference constants. Such system can be modeled as a congestion game, and we study the price of anarchy (PoA) for four families of such a game: identical, player-specific symmetric, resource-specific symmetric, and asymmetric games. We characterize the worst-case PoA in terms of the number of SUs and channels, and illustrate the network scenarios under which the worse case performance is reached. We further illustrate the PoA results with two Medium Access Control (MAC) schemes: uniform MAC and slotted Aloha. For both cases, we observe that the average performance of the game equilibrium is better than the worst-case PoA. Our study sheds light on how to design stable systems with smaller efficiency loss of the equilibrium.",lok law,congestion game,2012.0,10.1109/TWC.2012.083112.120371,IEEE Transactions on Wireless Communications,Law2012,False,,IEEE,Not available,Price of Anarchy for Congestion Games in Cognitive Radio Networks,d78287bf43af78c169dac2e1b5572756,https://ieeexplore.ieee.org/document/6294502/
6712,"In this paper, we consider a cognitive radio network where multiple heterogenous secondary users (SUs) compete for transmissions on idle primary channels. We model this as a singleton congestion game, where the probability for an SU to successfully access a channel decreases with the number of SUs selecting the same channel. In particular, we consider player-specific payoffs that depend not only on the shares of the channel but also on different preference constants. Such system can be modeled as a congestion game, and we study the price of anarchy (PoA) for four families of such a game: identical, player-specific symmetric, resource-specific symmetric, and asymmetric games. We characterize the worst-case PoA in terms of the number of SUs and channels, and illustrate the network scenarios under which the worse case performance is reached. We further illustrate the PoA results with two Medium Access Control (MAC) schemes: uniform MAC and slotted Aloha. For both cases, we observe that the average performance of the game equilibrium is better than the worst-case PoA. Our study sheds light on how to design stable systems with smaller efficiency loss of the equilibrium.",lok law,price of anarchy,2012.0,10.1109/TWC.2012.083112.120371,IEEE Transactions on Wireless Communications,Law2012,False,,IEEE,Not available,Price of Anarchy for Congestion Games in Cognitive Radio Networks,d78287bf43af78c169dac2e1b5572756,https://ieeexplore.ieee.org/document/6294502/
6713,"In this paper, we consider a cognitive radio network where multiple heterogenous secondary users (SUs) compete for transmissions on idle primary channels. We model this as a singleton congestion game, where the probability for an SU to successfully access a channel decreases with the number of SUs selecting the same channel. In particular, we consider player-specific payoffs that depend not only on the shares of the channel but also on different preference constants. Such system can be modeled as a congestion game, and we study the price of anarchy (PoA) for four families of such a game: identical, player-specific symmetric, resource-specific symmetric, and asymmetric games. We characterize the worst-case PoA in terms of the number of SUs and channels, and illustrate the network scenarios under which the worse case performance is reached. We further illustrate the PoA results with two Medium Access Control (MAC) schemes: uniform MAC and slotted Aloha. For both cases, we observe that the average performance of the game equilibrium is better than the worst-case PoA. Our study sheds light on how to design stable systems with smaller efficiency loss of the equilibrium.",jianwei huang,Cognitive radio,2012.0,10.1109/TWC.2012.083112.120371,IEEE Transactions on Wireless Communications,Law2012,False,,IEEE,Not available,Price of Anarchy for Congestion Games in Cognitive Radio Networks,d78287bf43af78c169dac2e1b5572756,https://ieeexplore.ieee.org/document/6294502/
6714,"In this paper, we consider a cognitive radio network where multiple heterogenous secondary users (SUs) compete for transmissions on idle primary channels. We model this as a singleton congestion game, where the probability for an SU to successfully access a channel decreases with the number of SUs selecting the same channel. In particular, we consider player-specific payoffs that depend not only on the shares of the channel but also on different preference constants. Such system can be modeled as a congestion game, and we study the price of anarchy (PoA) for four families of such a game: identical, player-specific symmetric, resource-specific symmetric, and asymmetric games. We characterize the worst-case PoA in terms of the number of SUs and channels, and illustrate the network scenarios under which the worse case performance is reached. We further illustrate the PoA results with two Medium Access Control (MAC) schemes: uniform MAC and slotted Aloha. For both cases, we observe that the average performance of the game equilibrium is better than the worst-case PoA. Our study sheds light on how to design stable systems with smaller efficiency loss of the equilibrium.",jianwei huang,spectrum sharing,2012.0,10.1109/TWC.2012.083112.120371,IEEE Transactions on Wireless Communications,Law2012,False,,IEEE,Not available,Price of Anarchy for Congestion Games in Cognitive Radio Networks,d78287bf43af78c169dac2e1b5572756,https://ieeexplore.ieee.org/document/6294502/
6715,"In this paper, we consider a cognitive radio network where multiple heterogenous secondary users (SUs) compete for transmissions on idle primary channels. We model this as a singleton congestion game, where the probability for an SU to successfully access a channel decreases with the number of SUs selecting the same channel. In particular, we consider player-specific payoffs that depend not only on the shares of the channel but also on different preference constants. Such system can be modeled as a congestion game, and we study the price of anarchy (PoA) for four families of such a game: identical, player-specific symmetric, resource-specific symmetric, and asymmetric games. We characterize the worst-case PoA in terms of the number of SUs and channels, and illustrate the network scenarios under which the worse case performance is reached. We further illustrate the PoA results with two Medium Access Control (MAC) schemes: uniform MAC and slotted Aloha. For both cases, we observe that the average performance of the game equilibrium is better than the worst-case PoA. Our study sheds light on how to design stable systems with smaller efficiency loss of the equilibrium.",jianwei huang,congestion game,2012.0,10.1109/TWC.2012.083112.120371,IEEE Transactions on Wireless Communications,Law2012,False,,IEEE,Not available,Price of Anarchy for Congestion Games in Cognitive Radio Networks,d78287bf43af78c169dac2e1b5572756,https://ieeexplore.ieee.org/document/6294502/
6716,"In this paper, we consider a cognitive radio network where multiple heterogenous secondary users (SUs) compete for transmissions on idle primary channels. We model this as a singleton congestion game, where the probability for an SU to successfully access a channel decreases with the number of SUs selecting the same channel. In particular, we consider player-specific payoffs that depend not only on the shares of the channel but also on different preference constants. Such system can be modeled as a congestion game, and we study the price of anarchy (PoA) for four families of such a game: identical, player-specific symmetric, resource-specific symmetric, and asymmetric games. We characterize the worst-case PoA in terms of the number of SUs and channels, and illustrate the network scenarios under which the worse case performance is reached. We further illustrate the PoA results with two Medium Access Control (MAC) schemes: uniform MAC and slotted Aloha. For both cases, we observe that the average performance of the game equilibrium is better than the worst-case PoA. Our study sheds light on how to design stable systems with smaller efficiency loss of the equilibrium.",jianwei huang,price of anarchy,2012.0,10.1109/TWC.2012.083112.120371,IEEE Transactions on Wireless Communications,Law2012,False,,IEEE,Not available,Price of Anarchy for Congestion Games in Cognitive Radio Networks,d78287bf43af78c169dac2e1b5572756,https://ieeexplore.ieee.org/document/6294502/
6717,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6718,"In this paper, we consider a cognitive radio network where multiple heterogenous secondary users (SUs) compete for transmissions on idle primary channels. We model this as a singleton congestion game, where the probability for an SU to successfully access a channel decreases with the number of SUs selecting the same channel. In particular, we consider player-specific payoffs that depend not only on the shares of the channel but also on different preference constants. Such system can be modeled as a congestion game, and we study the price of anarchy (PoA) for four families of such a game: identical, player-specific symmetric, resource-specific symmetric, and asymmetric games. We characterize the worst-case PoA in terms of the number of SUs and channels, and illustrate the network scenarios under which the worse case performance is reached. We further illustrate the PoA results with two Medium Access Control (MAC) schemes: uniform MAC and slotted Aloha. For both cases, we observe that the average performance of the game equilibrium is better than the worst-case PoA. Our study sheds light on how to design stable systems with smaller efficiency loss of the equilibrium.",mingyan liu,Cognitive radio,2012.0,10.1109/TWC.2012.083112.120371,IEEE Transactions on Wireless Communications,Law2012,False,,IEEE,Not available,Price of Anarchy for Congestion Games in Cognitive Radio Networks,d78287bf43af78c169dac2e1b5572756,https://ieeexplore.ieee.org/document/6294502/
6719,"In this paper, we consider a cognitive radio network where multiple heterogenous secondary users (SUs) compete for transmissions on idle primary channels. We model this as a singleton congestion game, where the probability for an SU to successfully access a channel decreases with the number of SUs selecting the same channel. In particular, we consider player-specific payoffs that depend not only on the shares of the channel but also on different preference constants. Such system can be modeled as a congestion game, and we study the price of anarchy (PoA) for four families of such a game: identical, player-specific symmetric, resource-specific symmetric, and asymmetric games. We characterize the worst-case PoA in terms of the number of SUs and channels, and illustrate the network scenarios under which the worse case performance is reached. We further illustrate the PoA results with two Medium Access Control (MAC) schemes: uniform MAC and slotted Aloha. For both cases, we observe that the average performance of the game equilibrium is better than the worst-case PoA. Our study sheds light on how to design stable systems with smaller efficiency loss of the equilibrium.",mingyan liu,spectrum sharing,2012.0,10.1109/TWC.2012.083112.120371,IEEE Transactions on Wireless Communications,Law2012,False,,IEEE,Not available,Price of Anarchy for Congestion Games in Cognitive Radio Networks,d78287bf43af78c169dac2e1b5572756,https://ieeexplore.ieee.org/document/6294502/
6720,"In this paper, we consider a cognitive radio network where multiple heterogenous secondary users (SUs) compete for transmissions on idle primary channels. We model this as a singleton congestion game, where the probability for an SU to successfully access a channel decreases with the number of SUs selecting the same channel. In particular, we consider player-specific payoffs that depend not only on the shares of the channel but also on different preference constants. Such system can be modeled as a congestion game, and we study the price of anarchy (PoA) for four families of such a game: identical, player-specific symmetric, resource-specific symmetric, and asymmetric games. We characterize the worst-case PoA in terms of the number of SUs and channels, and illustrate the network scenarios under which the worse case performance is reached. We further illustrate the PoA results with two Medium Access Control (MAC) schemes: uniform MAC and slotted Aloha. For both cases, we observe that the average performance of the game equilibrium is better than the worst-case PoA. Our study sheds light on how to design stable systems with smaller efficiency loss of the equilibrium.",mingyan liu,congestion game,2012.0,10.1109/TWC.2012.083112.120371,IEEE Transactions on Wireless Communications,Law2012,False,,IEEE,Not available,Price of Anarchy for Congestion Games in Cognitive Radio Networks,d78287bf43af78c169dac2e1b5572756,https://ieeexplore.ieee.org/document/6294502/
6721,"In this paper, we consider a cognitive radio network where multiple heterogenous secondary users (SUs) compete for transmissions on idle primary channels. We model this as a singleton congestion game, where the probability for an SU to successfully access a channel decreases with the number of SUs selecting the same channel. In particular, we consider player-specific payoffs that depend not only on the shares of the channel but also on different preference constants. Such system can be modeled as a congestion game, and we study the price of anarchy (PoA) for four families of such a game: identical, player-specific symmetric, resource-specific symmetric, and asymmetric games. We characterize the worst-case PoA in terms of the number of SUs and channels, and illustrate the network scenarios under which the worse case performance is reached. We further illustrate the PoA results with two Medium Access Control (MAC) schemes: uniform MAC and slotted Aloha. For both cases, we observe that the average performance of the game equilibrium is better than the worst-case PoA. Our study sheds light on how to design stable systems with smaller efficiency loss of the equilibrium.",mingyan liu,price of anarchy,2012.0,10.1109/TWC.2012.083112.120371,IEEE Transactions on Wireless Communications,Law2012,False,,IEEE,Not available,Price of Anarchy for Congestion Games in Cognitive Radio Networks,d78287bf43af78c169dac2e1b5572756,https://ieeexplore.ieee.org/document/6294502/
6722,"The Price of Anarchy (PoA) is a measure for the loss of optimality due to decentralized behavior. It has been studied in many settings but, surprisingly, not in the most fundamental queueing system involving customers' decisions, namely, the single server Markovian queue. We find that the loss of efficiency in such systems is bounded by 50% in most practical cases, in which the arrival rate of the customers is significantly lower than the service rate. We also find that the loss of efficiency has an interesting behavior in two aspects: first, it sharply increases as the arrival rate comes close to the service rate; second, it becomes unbounded exactly when the arrival rate is greater than the service rate, a surprising behavior because the system is always stable. Knowing these bounds is important for the queue controller, for example when considering an investment in added service capacity.",gail gilboa-freedman,Adaptive control,2014.0,10.1109/TAC.2013.2270872,IEEE Transactions on Automatic Control,Gilboa-Freedman2014,False,,IEEE,Not available,The Price of Anarchy in the Markovian Single Server Queue,f3be4782a4e01807d8aac7e3e76fedf7,https://ieeexplore.ieee.org/document/6545289/
6723,"The Price of Anarchy (PoA) is a measure for the loss of optimality due to decentralized behavior. It has been studied in many settings but, surprisingly, not in the most fundamental queueing system involving customers' decisions, namely, the single server Markovian queue. We find that the loss of efficiency in such systems is bounded by 50% in most practical cases, in which the arrival rate of the customers is significantly lower than the service rate. We also find that the loss of efficiency has an interesting behavior in two aspects: first, it sharply increases as the arrival rate comes close to the service rate; second, it becomes unbounded exactly when the arrival rate is greater than the service rate, a surprising behavior because the system is always stable. Knowing these bounds is important for the queue controller, for example when considering an investment in added service capacity.",gail gilboa-freedman,cost function,2014.0,10.1109/TAC.2013.2270872,IEEE Transactions on Automatic Control,Gilboa-Freedman2014,False,,IEEE,Not available,The Price of Anarchy in the Markovian Single Server Queue,f3be4782a4e01807d8aac7e3e76fedf7,https://ieeexplore.ieee.org/document/6545289/
6724,"The Price of Anarchy (PoA) is a measure for the loss of optimality due to decentralized behavior. It has been studied in many settings but, surprisingly, not in the most fundamental queueing system involving customers' decisions, namely, the single server Markovian queue. We find that the loss of efficiency in such systems is bounded by 50% in most practical cases, in which the arrival rate of the customers is significantly lower than the service rate. We also find that the loss of efficiency has an interesting behavior in two aspects: first, it sharply increases as the arrival rate comes close to the service rate; second, it becomes unbounded exactly when the arrival rate is greater than the service rate, a surprising behavior because the system is always stable. Knowing these bounds is important for the queue controller, for example when considering an investment in added service capacity.",gail gilboa-freedman,numerical simulation,2014.0,10.1109/TAC.2013.2270872,IEEE Transactions on Automatic Control,Gilboa-Freedman2014,False,,IEEE,Not available,The Price of Anarchy in the Markovian Single Server Queue,f3be4782a4e01807d8aac7e3e76fedf7,https://ieeexplore.ieee.org/document/6545289/
6725,"The Price of Anarchy (PoA) is a measure for the loss of optimality due to decentralized behavior. It has been studied in many settings but, surprisingly, not in the most fundamental queueing system involving customers' decisions, namely, the single server Markovian queue. We find that the loss of efficiency in such systems is bounded by 50% in most practical cases, in which the arrival rate of the customers is significantly lower than the service rate. We also find that the loss of efficiency has an interesting behavior in two aspects: first, it sharply increases as the arrival rate comes close to the service rate; second, it becomes unbounded exactly when the arrival rate is greater than the service rate, a surprising behavior because the system is always stable. Knowing these bounds is important for the queue controller, for example when considering an investment in added service capacity.",refael hassin,Adaptive control,2014.0,10.1109/TAC.2013.2270872,IEEE Transactions on Automatic Control,Gilboa-Freedman2014,False,,IEEE,Not available,The Price of Anarchy in the Markovian Single Server Queue,f3be4782a4e01807d8aac7e3e76fedf7,https://ieeexplore.ieee.org/document/6545289/
6726,"The Price of Anarchy (PoA) is a measure for the loss of optimality due to decentralized behavior. It has been studied in many settings but, surprisingly, not in the most fundamental queueing system involving customers' decisions, namely, the single server Markovian queue. We find that the loss of efficiency in such systems is bounded by 50% in most practical cases, in which the arrival rate of the customers is significantly lower than the service rate. We also find that the loss of efficiency has an interesting behavior in two aspects: first, it sharply increases as the arrival rate comes close to the service rate; second, it becomes unbounded exactly when the arrival rate is greater than the service rate, a surprising behavior because the system is always stable. Knowing these bounds is important for the queue controller, for example when considering an investment in added service capacity.",refael hassin,cost function,2014.0,10.1109/TAC.2013.2270872,IEEE Transactions on Automatic Control,Gilboa-Freedman2014,False,,IEEE,Not available,The Price of Anarchy in the Markovian Single Server Queue,f3be4782a4e01807d8aac7e3e76fedf7,https://ieeexplore.ieee.org/document/6545289/
6727,"The Price of Anarchy (PoA) is a measure for the loss of optimality due to decentralized behavior. It has been studied in many settings but, surprisingly, not in the most fundamental queueing system involving customers' decisions, namely, the single server Markovian queue. We find that the loss of efficiency in such systems is bounded by 50% in most practical cases, in which the arrival rate of the customers is significantly lower than the service rate. We also find that the loss of efficiency has an interesting behavior in two aspects: first, it sharply increases as the arrival rate comes close to the service rate; second, it becomes unbounded exactly when the arrival rate is greater than the service rate, a surprising behavior because the system is always stable. Knowing these bounds is important for the queue controller, for example when considering an investment in added service capacity.",refael hassin,numerical simulation,2014.0,10.1109/TAC.2013.2270872,IEEE Transactions on Automatic Control,Gilboa-Freedman2014,False,,IEEE,Not available,The Price of Anarchy in the Markovian Single Server Queue,f3be4782a4e01807d8aac7e3e76fedf7,https://ieeexplore.ieee.org/document/6545289/
6728,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6729,"The Price of Anarchy (PoA) is a measure for the loss of optimality due to decentralized behavior. It has been studied in many settings but, surprisingly, not in the most fundamental queueing system involving customers' decisions, namely, the single server Markovian queue. We find that the loss of efficiency in such systems is bounded by 50% in most practical cases, in which the arrival rate of the customers is significantly lower than the service rate. We also find that the loss of efficiency has an interesting behavior in two aspects: first, it sharply increases as the arrival rate comes close to the service rate; second, it becomes unbounded exactly when the arrival rate is greater than the service rate, a surprising behavior because the system is always stable. Knowing these bounds is important for the queue controller, for example when considering an investment in added service capacity.",yoav kerner,Adaptive control,2014.0,10.1109/TAC.2013.2270872,IEEE Transactions on Automatic Control,Gilboa-Freedman2014,False,,IEEE,Not available,The Price of Anarchy in the Markovian Single Server Queue,f3be4782a4e01807d8aac7e3e76fedf7,https://ieeexplore.ieee.org/document/6545289/
6730,"The Price of Anarchy (PoA) is a measure for the loss of optimality due to decentralized behavior. It has been studied in many settings but, surprisingly, not in the most fundamental queueing system involving customers' decisions, namely, the single server Markovian queue. We find that the loss of efficiency in such systems is bounded by 50% in most practical cases, in which the arrival rate of the customers is significantly lower than the service rate. We also find that the loss of efficiency has an interesting behavior in two aspects: first, it sharply increases as the arrival rate comes close to the service rate; second, it becomes unbounded exactly when the arrival rate is greater than the service rate, a surprising behavior because the system is always stable. Knowing these bounds is important for the queue controller, for example when considering an investment in added service capacity.",yoav kerner,cost function,2014.0,10.1109/TAC.2013.2270872,IEEE Transactions on Automatic Control,Gilboa-Freedman2014,False,,IEEE,Not available,The Price of Anarchy in the Markovian Single Server Queue,f3be4782a4e01807d8aac7e3e76fedf7,https://ieeexplore.ieee.org/document/6545289/
6731,"The Price of Anarchy (PoA) is a measure for the loss of optimality due to decentralized behavior. It has been studied in many settings but, surprisingly, not in the most fundamental queueing system involving customers' decisions, namely, the single server Markovian queue. We find that the loss of efficiency in such systems is bounded by 50% in most practical cases, in which the arrival rate of the customers is significantly lower than the service rate. We also find that the loss of efficiency has an interesting behavior in two aspects: first, it sharply increases as the arrival rate comes close to the service rate; second, it becomes unbounded exactly when the arrival rate is greater than the service rate, a surprising behavior because the system is always stable. Knowing these bounds is important for the queue controller, for example when considering an investment in added service capacity.",yoav kerner,numerical simulation,2014.0,10.1109/TAC.2013.2270872,IEEE Transactions on Automatic Control,Gilboa-Freedman2014,False,,IEEE,Not available,The Price of Anarchy in the Markovian Single Server Queue,f3be4782a4e01807d8aac7e3e76fedf7,https://ieeexplore.ieee.org/document/6545289/
6732,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",prasanna chaporkar,Wireless LAN,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
6733,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",prasanna chaporkar,Nash equilibrium,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
6734,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",prasanna chaporkar,Throughput,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
6735,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",prasanna chaporkar,Communications Society,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
6736,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",prasanna chaporkar,Media Access Protocol,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
6737,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",prasanna chaporkar,H infinity control,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
6738,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",prasanna chaporkar,Time factors,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
6739,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6740,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",prasanna chaporkar,Hardware,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
6741,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",prasanna chaporkar,Modulation coding,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
6742,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",prasanna chaporkar,Propagation losses,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
6743,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",alexandre proutiere,Wireless LAN,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
6744,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",alexandre proutiere,Nash equilibrium,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
6745,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",alexandre proutiere,Throughput,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
6746,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",alexandre proutiere,Communications Society,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
6747,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",alexandre proutiere,Media Access Protocol,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
6748,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",alexandre proutiere,H infinity control,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
6749,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",alexandre proutiere,Time factors,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
6750,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6751,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",alexandre proutiere,Hardware,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
6752,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",alexandre proutiere,Modulation coding,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
6753,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",alexandre proutiere,Propagation losses,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
6754,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",bozidar radunoviae,Wireless LAN,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
6755,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",bozidar radunoviae,Nash equilibrium,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
6756,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",bozidar radunoviae,Throughput,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
6757,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",bozidar radunoviae,Communications Society,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
6758,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",bozidar radunoviae,Media Access Protocol,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
6759,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",bozidar radunoviae,H infinity control,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
6760,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",bozidar radunoviae,Time factors,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
6761,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6762,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",bozidar radunoviae,Hardware,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
6763,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",bozidar radunoviae,Modulation coding,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
6764,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",bozidar radunoviae,Propagation losses,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
6765,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pratyush chakraborty,Nash equilibrium,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
6766,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pratyush chakraborty,Decentralized control,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
6767,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pratyush chakraborty,Optimization,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
6768,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pratyush chakraborty,Games,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
6769,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pratyush chakraborty,Electric vehicles,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
6770,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pratyush chakraborty,Schedules,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
6771,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pratyush chakraborty,Equations,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
6772,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6773,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6774,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pramod khargonekar,Nash equilibrium,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
6775,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pramod khargonekar,Decentralized control,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
6776,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pramod khargonekar,Optimization,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
6777,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pramod khargonekar,Games,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
6778,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pramod khargonekar,Electric vehicles,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
6779,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pramod khargonekar,Schedules,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
6780,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pramod khargonekar,Equations,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
6781,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",jonatha anselmi,Time factors,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
6782,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",jonatha anselmi,Routing,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
6783,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",jonatha anselmi,Queueing analysis,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
6784,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6785,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",jonatha anselmi,Approximation methods,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
6786,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",jonatha anselmi,Optimization,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
6787,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",jonatha anselmi,Upper bound,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
6788,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",jonatha anselmi,Nash equilibrium,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
6789,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",bruno gaujal,Time factors,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
6790,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",bruno gaujal,Routing,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
6791,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",bruno gaujal,Queueing analysis,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
6792,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",bruno gaujal,Approximation methods,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
6793,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",bruno gaujal,Optimization,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
6794,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",bruno gaujal,Upper bound,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
6795,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6796,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",bruno gaujal,Nash equilibrium,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
6797,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",jing zhang,Optimization,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
6798,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",jing zhang,Price-of-Anarchy (PoA),2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
6799,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",jing zhang,sensitivity analysis,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
6800,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",jing zhang,traffic assignment problem,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
6801,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",jing zhang,transportation networks,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
6802,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",jing zhang,variational inequalities,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
6803,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",sepideh pourazarm,Optimization,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
6804,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",sepideh pourazarm,Price-of-Anarchy (PoA),2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
6805,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",sepideh pourazarm,sensitivity analysis,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
6806,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6807,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",sepideh pourazarm,traffic assignment problem,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
6808,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",sepideh pourazarm,transportation networks,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
6809,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",sepideh pourazarm,variational inequalities,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
6810,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",christos cassandras,Optimization,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
6811,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",christos cassandras,Price-of-Anarchy (PoA),2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
6812,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",christos cassandras,sensitivity analysis,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
6813,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",christos cassandras,traffic assignment problem,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
6814,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",christos cassandras,transportation networks,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
6815,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",christos cassandras,variational inequalities,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
6816,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",ioannis paschalidis,Optimization,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
6817,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6818,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",ioannis paschalidis,Price-of-Anarchy (PoA),2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
6819,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",ioannis paschalidis,sensitivity analysis,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
6820,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",ioannis paschalidis,traffic assignment problem,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
6821,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",ioannis paschalidis,transportation networks,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
6822,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",ioannis paschalidis,variational inequalities,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
6823,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",john musacchio,Diffserv networks,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
6824,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",john musacchio,Telecommunication traffic,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
6825,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",john musacchio,Traffic control,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
6826,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",john musacchio,Delay,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
6827,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",john musacchio,Nash equilibrium,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
6828,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6829,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",john musacchio,Costs,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
6830,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",john musacchio,Pricing,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
6831,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",john musacchio,Routing,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
6832,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",john musacchio,Environmental economics,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
6833,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",john musacchio,Degradation,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
6834,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",shuang wu,Diffserv networks,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
6835,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",shuang wu,Telecommunication traffic,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
6836,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",shuang wu,Traffic control,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
6837,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",shuang wu,Delay,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
6838,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",shuang wu,Nash equilibrium,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
6839,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6840,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",shuang wu,Costs,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
6841,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",shuang wu,Pricing,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
6842,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",shuang wu,Routing,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
6843,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",shuang wu,Environmental economics,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
6844,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",shuang wu,Degradation,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
6845,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",bo gao,Mobile computing,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
6846,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",bo gao,mobile cloud computing,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
6847,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",bo gao,energy-aware,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
6848,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",bo gao,Mobile computing,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
6849,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",bo gao,mobile cloud computing,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
6850,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6851,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",bo gao,energy-aware,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
6852,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",ligang he,Mobile computing,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
6853,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",ligang he,mobile cloud computing,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
6854,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",ligang he,energy-aware,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
6855,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",ligang he,Mobile computing,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
6856,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",ligang he,mobile cloud computing,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
6857,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",ligang he,energy-aware,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
6858,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",stephen jarvis,Mobile computing,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
6859,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",stephen jarvis,mobile cloud computing,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
6860,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",stephen jarvis,energy-aware,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
6861,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
6862,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",stephen jarvis,Mobile computing,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
6863,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",stephen jarvis,mobile cloud computing,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
6864,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",stephen jarvis,energy-aware,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
6865,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",u. ayesta,Load management,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
6866,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",u. ayesta,Routing,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
6867,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",u. ayesta,Nash equilibrium,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
6868,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",u. ayesta,Network servers,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
6869,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",u. ayesta,Web server,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
6870,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",u. ayesta,Costs,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
6871,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",u. ayesta,Communications Society,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
6872,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
6873,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",u. ayesta,Scalability,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
6874,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",u. ayesta,Computer architecture,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
6875,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",u. ayesta,Performance loss,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
6876,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",o. brun,Load management,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
6877,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",o. brun,Routing,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
6878,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",o. brun,Nash equilibrium,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
6879,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",o. brun,Network servers,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
6880,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",o. brun,Web server,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
6881,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",o. brun,Costs,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
6882,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",o. brun,Communications Society,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
6883,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6884,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
6885,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",o. brun,Scalability,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
6886,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",o. brun,Computer architecture,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
6887,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",o. brun,Performance loss,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
6888,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",b. prabhu,Load management,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
6889,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",b. prabhu,Routing,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
6890,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",b. prabhu,Nash equilibrium,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
6891,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",b. prabhu,Network servers,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
6892,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",b. prabhu,Web server,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
6893,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",b. prabhu,Costs,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
6894,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",b. prabhu,Communications Society,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
6895,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
6896,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",b. prabhu,Scalability,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
6897,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",b. prabhu,Computer architecture,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
6898,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",b. prabhu,Performance loss,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
6899,"We consider in this paper a simple model for human interactions as service providers of different resources over social networks, and study the dynamics of selfish behavior of such social entities using a game-theoretic model known as binary-preference capacitated selfish replication (CSR) game. It is known that such games have an associated ordinal potential function, and hence always admit a pure-strategy Nash equilibrium (NE). We study the price of anarchy of such games, and show that it is bounded above by 3; we further provide some instances for which the price of anarchy is at least 2. We also devise a quasi-polynomial algorithm O(n2+ln D) which can find, in a distributed manner, an allocation profile that is within a constant factor of the optimal allocation, and hence of any pure-strategy Nash equilibrium of the game, where the parameters n, and D denote, respectively, the number of players, and the diameter of the network. We further show that when the underlying network has a tree structure, every globally optimal allocation is a Nash equilibrium, which can be reached in only linear time.",seyed etesami,Capacitated selfish replication game,2015.0,10.1109/CDC.2015.7402771,2015 54th IEEE Conference on Decision and Control (CDC),Etesami2015,False,,IEEE,Not available,An approximation algorithm and price of anarchy for the binary-preference capacitated selfish replication game,c2ff2ca30f60e4aaa6132bc41aa2be69,https://ieeexplore.ieee.org/document/7402771/
6900,"We consider in this paper a simple model for human interactions as service providers of different resources over social networks, and study the dynamics of selfish behavior of such social entities using a game-theoretic model known as binary-preference capacitated selfish replication (CSR) game. It is known that such games have an associated ordinal potential function, and hence always admit a pure-strategy Nash equilibrium (NE). We study the price of anarchy of such games, and show that it is bounded above by 3; we further provide some instances for which the price of anarchy is at least 2. We also devise a quasi-polynomial algorithm O(n2+ln D) which can find, in a distributed manner, an allocation profile that is within a constant factor of the optimal allocation, and hence of any pure-strategy Nash equilibrium of the game, where the parameters n, and D denote, respectively, the number of players, and the diameter of the network. We further show that when the underlying network has a tree structure, every globally optimal allocation is a Nash equilibrium, which can be reached in only linear time.",seyed etesami,pure Nash equilibrium (NE),2015.0,10.1109/CDC.2015.7402771,2015 54th IEEE Conference on Decision and Control (CDC),Etesami2015,False,,IEEE,Not available,An approximation algorithm and price of anarchy for the binary-preference capacitated selfish replication game,c2ff2ca30f60e4aaa6132bc41aa2be69,https://ieeexplore.ieee.org/document/7402771/
6901,"We consider in this paper a simple model for human interactions as service providers of different resources over social networks, and study the dynamics of selfish behavior of such social entities using a game-theoretic model known as binary-preference capacitated selfish replication (CSR) game. It is known that such games have an associated ordinal potential function, and hence always admit a pure-strategy Nash equilibrium (NE). We study the price of anarchy of such games, and show that it is bounded above by 3; we further provide some instances for which the price of anarchy is at least 2. We also devise a quasi-polynomial algorithm O(n2+ln D) which can find, in a distributed manner, an allocation profile that is within a constant factor of the optimal allocation, and hence of any pure-strategy Nash equilibrium of the game, where the parameters n, and D denote, respectively, the number of players, and the diameter of the network. We further show that when the underlying network has a tree structure, every globally optimal allocation is a Nash equilibrium, which can be reached in only linear time.",seyed etesami,potential function,2015.0,10.1109/CDC.2015.7402771,2015 54th IEEE Conference on Decision and Control (CDC),Etesami2015,False,,IEEE,Not available,An approximation algorithm and price of anarchy for the binary-preference capacitated selfish replication game,c2ff2ca30f60e4aaa6132bc41aa2be69,https://ieeexplore.ieee.org/document/7402771/
6902,"We consider in this paper a simple model for human interactions as service providers of different resources over social networks, and study the dynamics of selfish behavior of such social entities using a game-theoretic model known as binary-preference capacitated selfish replication (CSR) game. It is known that such games have an associated ordinal potential function, and hence always admit a pure-strategy Nash equilibrium (NE). We study the price of anarchy of such games, and show that it is bounded above by 3; we further provide some instances for which the price of anarchy is at least 2. We also devise a quasi-polynomial algorithm O(n2+ln D) which can find, in a distributed manner, an allocation profile that is within a constant factor of the optimal allocation, and hence of any pure-strategy Nash equilibrium of the game, where the parameters n, and D denote, respectively, the number of players, and the diameter of the network. We further show that when the underlying network has a tree structure, every globally optimal allocation is a Nash equilibrium, which can be reached in only linear time.",seyed etesami,quasi-polynomial algorithm,2015.0,10.1109/CDC.2015.7402771,2015 54th IEEE Conference on Decision and Control (CDC),Etesami2015,False,,IEEE,Not available,An approximation algorithm and price of anarchy for the binary-preference capacitated selfish replication game,c2ff2ca30f60e4aaa6132bc41aa2be69,https://ieeexplore.ieee.org/document/7402771/
6903,"We consider in this paper a simple model for human interactions as service providers of different resources over social networks, and study the dynamics of selfish behavior of such social entities using a game-theoretic model known as binary-preference capacitated selfish replication (CSR) game. It is known that such games have an associated ordinal potential function, and hence always admit a pure-strategy Nash equilibrium (NE). We study the price of anarchy of such games, and show that it is bounded above by 3; we further provide some instances for which the price of anarchy is at least 2. We also devise a quasi-polynomial algorithm O(n2+ln D) which can find, in a distributed manner, an allocation profile that is within a constant factor of the optimal allocation, and hence of any pure-strategy Nash equilibrium of the game, where the parameters n, and D denote, respectively, the number of players, and the diameter of the network. We further show that when the underlying network has a tree structure, every globally optimal allocation is a Nash equilibrium, which can be reached in only linear time.",seyed etesami,price of anarchy,2015.0,10.1109/CDC.2015.7402771,2015 54th IEEE Conference on Decision and Control (CDC),Etesami2015,False,,IEEE,Not available,An approximation algorithm and price of anarchy for the binary-preference capacitated selfish replication game,c2ff2ca30f60e4aaa6132bc41aa2be69,https://ieeexplore.ieee.org/document/7402771/
6904,"We consider in this paper a simple model for human interactions as service providers of different resources over social networks, and study the dynamics of selfish behavior of such social entities using a game-theoretic model known as binary-preference capacitated selfish replication (CSR) game. It is known that such games have an associated ordinal potential function, and hence always admit a pure-strategy Nash equilibrium (NE). We study the price of anarchy of such games, and show that it is bounded above by 3; we further provide some instances for which the price of anarchy is at least 2. We also devise a quasi-polynomial algorithm O(n2+ln D) which can find, in a distributed manner, an allocation profile that is within a constant factor of the optimal allocation, and hence of any pure-strategy Nash equilibrium of the game, where the parameters n, and D denote, respectively, the number of players, and the diameter of the network. We further show that when the underlying network has a tree structure, every globally optimal allocation is a Nash equilibrium, which can be reached in only linear time.",seyed etesami,optimal allocation,2015.0,10.1109/CDC.2015.7402771,2015 54th IEEE Conference on Decision and Control (CDC),Etesami2015,False,,IEEE,Not available,An approximation algorithm and price of anarchy for the binary-preference capacitated selfish replication game,c2ff2ca30f60e4aaa6132bc41aa2be69,https://ieeexplore.ieee.org/document/7402771/
6905,"We consider in this paper a simple model for human interactions as service providers of different resources over social networks, and study the dynamics of selfish behavior of such social entities using a game-theoretic model known as binary-preference capacitated selfish replication (CSR) game. It is known that such games have an associated ordinal potential function, and hence always admit a pure-strategy Nash equilibrium (NE). We study the price of anarchy of such games, and show that it is bounded above by 3; we further provide some instances for which the price of anarchy is at least 2. We also devise a quasi-polynomial algorithm O(n2+ln D) which can find, in a distributed manner, an allocation profile that is within a constant factor of the optimal allocation, and hence of any pure-strategy Nash equilibrium of the game, where the parameters n, and D denote, respectively, the number of players, and the diameter of the network. We further show that when the underlying network has a tree structure, every globally optimal allocation is a Nash equilibrium, which can be reached in only linear time.",tamer ba&#x015f;ar,Capacitated selfish replication game,2015.0,10.1109/CDC.2015.7402771,2015 54th IEEE Conference on Decision and Control (CDC),Etesami2015,False,,IEEE,Not available,An approximation algorithm and price of anarchy for the binary-preference capacitated selfish replication game,c2ff2ca30f60e4aaa6132bc41aa2be69,https://ieeexplore.ieee.org/document/7402771/
6906,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
6907,"We consider in this paper a simple model for human interactions as service providers of different resources over social networks, and study the dynamics of selfish behavior of such social entities using a game-theoretic model known as binary-preference capacitated selfish replication (CSR) game. It is known that such games have an associated ordinal potential function, and hence always admit a pure-strategy Nash equilibrium (NE). We study the price of anarchy of such games, and show that it is bounded above by 3; we further provide some instances for which the price of anarchy is at least 2. We also devise a quasi-polynomial algorithm O(n2+ln D) which can find, in a distributed manner, an allocation profile that is within a constant factor of the optimal allocation, and hence of any pure-strategy Nash equilibrium of the game, where the parameters n, and D denote, respectively, the number of players, and the diameter of the network. We further show that when the underlying network has a tree structure, every globally optimal allocation is a Nash equilibrium, which can be reached in only linear time.",tamer ba&#x015f;ar,pure Nash equilibrium (NE),2015.0,10.1109/CDC.2015.7402771,2015 54th IEEE Conference on Decision and Control (CDC),Etesami2015,False,,IEEE,Not available,An approximation algorithm and price of anarchy for the binary-preference capacitated selfish replication game,c2ff2ca30f60e4aaa6132bc41aa2be69,https://ieeexplore.ieee.org/document/7402771/
6908,"We consider in this paper a simple model for human interactions as service providers of different resources over social networks, and study the dynamics of selfish behavior of such social entities using a game-theoretic model known as binary-preference capacitated selfish replication (CSR) game. It is known that such games have an associated ordinal potential function, and hence always admit a pure-strategy Nash equilibrium (NE). We study the price of anarchy of such games, and show that it is bounded above by 3; we further provide some instances for which the price of anarchy is at least 2. We also devise a quasi-polynomial algorithm O(n2+ln D) which can find, in a distributed manner, an allocation profile that is within a constant factor of the optimal allocation, and hence of any pure-strategy Nash equilibrium of the game, where the parameters n, and D denote, respectively, the number of players, and the diameter of the network. We further show that when the underlying network has a tree structure, every globally optimal allocation is a Nash equilibrium, which can be reached in only linear time.",tamer ba&#x015f;ar,potential function,2015.0,10.1109/CDC.2015.7402771,2015 54th IEEE Conference on Decision and Control (CDC),Etesami2015,False,,IEEE,Not available,An approximation algorithm and price of anarchy for the binary-preference capacitated selfish replication game,c2ff2ca30f60e4aaa6132bc41aa2be69,https://ieeexplore.ieee.org/document/7402771/
6909,"We consider in this paper a simple model for human interactions as service providers of different resources over social networks, and study the dynamics of selfish behavior of such social entities using a game-theoretic model known as binary-preference capacitated selfish replication (CSR) game. It is known that such games have an associated ordinal potential function, and hence always admit a pure-strategy Nash equilibrium (NE). We study the price of anarchy of such games, and show that it is bounded above by 3; we further provide some instances for which the price of anarchy is at least 2. We also devise a quasi-polynomial algorithm O(n2+ln D) which can find, in a distributed manner, an allocation profile that is within a constant factor of the optimal allocation, and hence of any pure-strategy Nash equilibrium of the game, where the parameters n, and D denote, respectively, the number of players, and the diameter of the network. We further show that when the underlying network has a tree structure, every globally optimal allocation is a Nash equilibrium, which can be reached in only linear time.",tamer ba&#x015f;ar,quasi-polynomial algorithm,2015.0,10.1109/CDC.2015.7402771,2015 54th IEEE Conference on Decision and Control (CDC),Etesami2015,False,,IEEE,Not available,An approximation algorithm and price of anarchy for the binary-preference capacitated selfish replication game,c2ff2ca30f60e4aaa6132bc41aa2be69,https://ieeexplore.ieee.org/document/7402771/
6910,"We consider in this paper a simple model for human interactions as service providers of different resources over social networks, and study the dynamics of selfish behavior of such social entities using a game-theoretic model known as binary-preference capacitated selfish replication (CSR) game. It is known that such games have an associated ordinal potential function, and hence always admit a pure-strategy Nash equilibrium (NE). We study the price of anarchy of such games, and show that it is bounded above by 3; we further provide some instances for which the price of anarchy is at least 2. We also devise a quasi-polynomial algorithm O(n2+ln D) which can find, in a distributed manner, an allocation profile that is within a constant factor of the optimal allocation, and hence of any pure-strategy Nash equilibrium of the game, where the parameters n, and D denote, respectively, the number of players, and the diameter of the network. We further show that when the underlying network has a tree structure, every globally optimal allocation is a Nash equilibrium, which can be reached in only linear time.",tamer ba&#x015f;ar,price of anarchy,2015.0,10.1109/CDC.2015.7402771,2015 54th IEEE Conference on Decision and Control (CDC),Etesami2015,False,,IEEE,Not available,An approximation algorithm and price of anarchy for the binary-preference capacitated selfish replication game,c2ff2ca30f60e4aaa6132bc41aa2be69,https://ieeexplore.ieee.org/document/7402771/
6911,"We consider in this paper a simple model for human interactions as service providers of different resources over social networks, and study the dynamics of selfish behavior of such social entities using a game-theoretic model known as binary-preference capacitated selfish replication (CSR) game. It is known that such games have an associated ordinal potential function, and hence always admit a pure-strategy Nash equilibrium (NE). We study the price of anarchy of such games, and show that it is bounded above by 3; we further provide some instances for which the price of anarchy is at least 2. We also devise a quasi-polynomial algorithm O(n2+ln D) which can find, in a distributed manner, an allocation profile that is within a constant factor of the optimal allocation, and hence of any pure-strategy Nash equilibrium of the game, where the parameters n, and D denote, respectively, the number of players, and the diameter of the network. We further show that when the underlying network has a tree structure, every globally optimal allocation is a Nash equilibrium, which can be reached in only linear time.",tamer ba&#x015f;ar,optimal allocation,2015.0,10.1109/CDC.2015.7402771,2015 54th IEEE Conference on Decision and Control (CDC),Etesami2015,False,,IEEE,Not available,An approximation algorithm and price of anarchy for the binary-preference capacitated selfish replication game,c2ff2ca30f60e4aaa6132bc41aa2be69,https://ieeexplore.ieee.org/document/7402771/
6912,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",jason marden,Games,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
6913,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",jason marden,Linear programming,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
6914,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",jason marden,Stability analysis,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
6915,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",jason marden,Resource management,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
6916,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",jason marden,Cost function,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
6917,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
6918,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",jason marden,Decision making,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
6919,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",jason marden,Computer architecture,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
6920,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",matthew philips,Games,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
6921,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",matthew philips,Linear programming,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
6922,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",matthew philips,Stability analysis,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
6923,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",matthew philips,Resource management,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
6924,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",matthew philips,Cost function,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
6925,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",matthew philips,Decision making,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
6926,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",matthew philips,Computer architecture,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
6927,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",jing zhang,Transportation networks,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
6928,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
6929,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",jing zhang,variational inequalities,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
6930,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",jing zhang,price of anarchy,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
6931,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",jing zhang,smart cities,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
6932,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",jing zhang,optimization,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
6933,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",sepideh pourazarm,Transportation networks,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
6934,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",sepideh pourazarm,variational inequalities,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
6935,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",sepideh pourazarm,price of anarchy,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
6936,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",sepideh pourazarm,smart cities,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
6937,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",sepideh pourazarm,optimization,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
6938,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",christos cassandras,Transportation networks,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
6939,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
6940,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",christos cassandras,variational inequalities,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
6941,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",christos cassandras,price of anarchy,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
6942,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",christos cassandras,smart cities,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
6943,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",christos cassandras,optimization,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
6944,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",ioannis paschalidis,Transportation networks,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
6945,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",ioannis paschalidis,variational inequalities,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
6946,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",ioannis paschalidis,price of anarchy,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
6947,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",ioannis paschalidis,smart cities,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
6948,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",ioannis paschalidis,optimization,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
6949,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",benjamin grimmer,Games,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
6950,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
6951,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",benjamin grimmer,Routing,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
6952,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",benjamin grimmer,Delays,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
6953,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",benjamin grimmer,Global Positioning System,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
6954,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",benjamin grimmer,Nash equilibrium,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
6955,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",benjamin grimmer,Processor scheduling,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
6956,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",benjamin grimmer,Servers,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
6957,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",sanjiv kapoor,Games,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
6958,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",sanjiv kapoor,Routing,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
6959,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",sanjiv kapoor,Delays,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
6960,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",sanjiv kapoor,Global Positioning System,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
6961,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6962,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",sanjiv kapoor,Nash equilibrium,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
6963,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",sanjiv kapoor,Processor scheduling,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
6964,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",sanjiv kapoor,Servers,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
6965,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",ninoslav marina,Relays,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
6966,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",ninoslav marina,Peer to peer computing,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
6967,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",ninoslav marina,Game theory,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
6968,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",ninoslav marina,Nash equilibrium,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
6969,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",ninoslav marina,Upper bound,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
6970,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",ninoslav marina,Information analysis,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
6971,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",ninoslav marina,Performance analysis,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
6972,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6973,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",ninoslav marina,Wireless networks,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
6974,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",ninoslav marina,Transmitters,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
6975,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",ninoslav marina,Information rates,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
6976,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",are hjorungnes,Relays,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
6977,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",are hjorungnes,Peer to peer computing,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
6978,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",are hjorungnes,Game theory,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
6979,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",are hjorungnes,Nash equilibrium,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
6980,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",are hjorungnes,Upper bound,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
6981,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",are hjorungnes,Information analysis,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
6982,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",are hjorungnes,Performance analysis,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
6983,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6984,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",are hjorungnes,Wireless networks,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
6985,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",are hjorungnes,Transmitters,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
6986,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",are hjorungnes,Information rates,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
6987,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",xuehe wang,Noncooperative congestion game,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
6988,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",xuehe wang,price of anarchy,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
6989,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",xuehe wang,price of total anarchy,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
6990,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",xuehe wang,road pricing,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
6991,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",xuehe wang,traffic networks,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
6992,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",nan xiao,Noncooperative congestion game,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
6993,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",nan xiao,price of anarchy,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
6994,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
6995,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
6996,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",nan xiao,price of total anarchy,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
6997,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",nan xiao,road pricing,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
6998,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",nan xiao,traffic networks,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
6999,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",lihua xie,Noncooperative congestion game,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
7000,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",lihua xie,price of anarchy,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
7001,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",lihua xie,price of total anarchy,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
7002,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",lihua xie,road pricing,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
7003,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",lihua xie,traffic networks,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
7004,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",emilio frazzoli,Noncooperative congestion game,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
7005,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",emilio frazzoli,price of anarchy,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
7006,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7007,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",emilio frazzoli,price of total anarchy,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
7008,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",emilio frazzoli,road pricing,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
7009,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",emilio frazzoli,traffic networks,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
7010,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",daniela rus,Noncooperative congestion game,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
7011,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",daniela rus,price of anarchy,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
7012,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",daniela rus,price of total anarchy,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
7013,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",daniela rus,road pricing,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
7014,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",daniela rus,traffic networks,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
7015,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",ehsan monsef,Nash equilibrium,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
7016,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",ehsan monsef,Global Positioning System,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
7017,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7018,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",ehsan monsef,Routing,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
7019,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",ehsan monsef,Quality of service,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
7020,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",ehsan monsef,Delays,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
7021,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",ehsan monsef,Cost function,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
7022,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",ehsan monsef,Games,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
7023,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",tricha anjali,Nash equilibrium,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
7024,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",tricha anjali,Global Positioning System,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
7025,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",tricha anjali,Routing,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
7026,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",tricha anjali,Quality of service,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
7027,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",tricha anjali,Delays,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
7028,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7029,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",tricha anjali,Cost function,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
7030,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",tricha anjali,Games,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
7031,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",sanjiv kapoor,Nash equilibrium,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
7032,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",sanjiv kapoor,Global Positioning System,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
7033,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",sanjiv kapoor,Routing,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
7034,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",sanjiv kapoor,Quality of service,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
7035,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",sanjiv kapoor,Delays,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
7036,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",sanjiv kapoor,Cost function,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
7037,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",sanjiv kapoor,Games,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
7038,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",matthew zyskowski,Cost Density-Shaping Games,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
7039,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7040,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",matthew zyskowski,Cost Cumulant Control,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
7041,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",matthew zyskowski,Price of Anarchy,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
7042,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",matthew zyskowski,Variance of Anarchy,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
7043,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",matthew zyskowski,Telecommunications,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
7044,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",matthew zyskowski,Stochastic Differential Games,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
7045,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",matthew zyskowski,Team Optimization,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
7046,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",quanyan zhu,Cost Density-Shaping Games,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
7047,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",quanyan zhu,Cost Cumulant Control,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
7048,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",quanyan zhu,Price of Anarchy,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
7049,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",quanyan zhu,Variance of Anarchy,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
7050,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7051,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",quanyan zhu,Telecommunications,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
7052,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",quanyan zhu,Stochastic Differential Games,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
7053,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",quanyan zhu,Team Optimization,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
7054,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",lok law,Cognitive radio,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7055,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",lok law,Nash equilibrium,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7056,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",lok law,Media Access Protocol,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7057,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",lok law,Resource management,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7058,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",lok law,Computer science,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7059,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",lok law,Information analysis,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7060,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",lok law,Closed-form solution,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7061,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7062,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",lok law,Monitoring,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7063,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",lok law,Interference,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7064,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",lok law,Frequency,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7065,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",jianwei huang,Cognitive radio,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7066,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",jianwei huang,Nash equilibrium,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7067,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",jianwei huang,Media Access Protocol,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7068,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",jianwei huang,Resource management,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7069,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",jianwei huang,Computer science,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7070,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",jianwei huang,Information analysis,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7071,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",jianwei huang,Closed-form solution,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7072,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7073,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",jianwei huang,Monitoring,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7074,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",jianwei huang,Interference,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7075,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",jianwei huang,Frequency,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7076,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",mingyan liu,Cognitive radio,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7077,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",mingyan liu,Nash equilibrium,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7078,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",mingyan liu,Media Access Protocol,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7079,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",mingyan liu,Resource management,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7080,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",mingyan liu,Computer science,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7081,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",mingyan liu,Information analysis,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7082,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",mingyan liu,Closed-form solution,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7083,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7084,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",mingyan liu,Monitoring,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7085,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",mingyan liu,Interference,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7086,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",mingyan liu,Frequency,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7087,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",shuo-yen li,Cognitive radio,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7088,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",shuo-yen li,Nash equilibrium,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7089,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",shuo-yen li,Media Access Protocol,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7090,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",shuo-yen li,Resource management,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7091,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",shuo-yen li,Computer science,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7092,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",shuo-yen li,Information analysis,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7093,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",shuo-yen li,Closed-form solution,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7094,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7095,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",shuo-yen li,Monitoring,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7096,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",shuo-yen li,Interference,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7097,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",shuo-yen li,Frequency,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
7098,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",daniel lazar,Roads,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
7099,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",daniel lazar,Cost function,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
7100,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",daniel lazar,Routing,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
7101,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",daniel lazar,Delays,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
7102,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",daniel lazar,Automobiles,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
7103,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",daniel lazar,Cruise control,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
7104,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",samuel coogan,Roads,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
7105,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7106,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7107,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",samuel coogan,Cost function,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
7108,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",samuel coogan,Routing,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
7109,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",samuel coogan,Delays,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
7110,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",samuel coogan,Automobiles,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
7111,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",samuel coogan,Cruise control,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
7112,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",ramtin pedarsani,Roads,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
7113,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",ramtin pedarsani,Cost function,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
7114,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",ramtin pedarsani,Routing,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
7115,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",ramtin pedarsani,Delays,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
7116,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",ramtin pedarsani,Automobiles,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
7117,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7118,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",ramtin pedarsani,Cruise control,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
7119,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",amir-hamed mohsenian-rad,Network coding,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7120,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",amir-hamed mohsenian-rad,Upper bound,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7121,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",amir-hamed mohsenian-rad,Communications Society,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7122,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",amir-hamed mohsenian-rad,Design engineering,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7123,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",amir-hamed mohsenian-rad,Electronic mail,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7124,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",amir-hamed mohsenian-rad,Wireless networks,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7125,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",amir-hamed mohsenian-rad,Encoding,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7126,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",amir-hamed mohsenian-rad,Unicast,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7127,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",amir-hamed mohsenian-rad,Decoding,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7128,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7129,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",amir-hamed mohsenian-rad,Nash equilibrium,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7130,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",jianwei huang,Network coding,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7131,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",jianwei huang,Upper bound,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7132,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",jianwei huang,Communications Society,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7133,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",jianwei huang,Design engineering,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7134,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",jianwei huang,Electronic mail,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7135,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",jianwei huang,Wireless networks,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7136,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",jianwei huang,Encoding,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7137,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",jianwei huang,Unicast,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7138,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",jianwei huang,Decoding,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7139,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7140,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",jianwei huang,Nash equilibrium,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7141,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",vincent wong,Network coding,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7142,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",vincent wong,Upper bound,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7143,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",vincent wong,Communications Society,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7144,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",vincent wong,Design engineering,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7145,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",vincent wong,Electronic mail,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7146,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",vincent wong,Wireless networks,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7147,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",vincent wong,Encoding,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7148,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",vincent wong,Unicast,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7149,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",vincent wong,Decoding,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7150,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7151,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",vincent wong,Nash equilibrium,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7152,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",robert schober,Network coding,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7153,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",robert schober,Upper bound,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7154,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",robert schober,Communications Society,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7155,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",robert schober,Design engineering,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7156,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",robert schober,Electronic mail,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7157,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",robert schober,Wireless networks,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7158,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",robert schober,Encoding,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7159,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",robert schober,Unicast,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7160,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",robert schober,Decoding,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7161,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7162,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",robert schober,Nash equilibrium,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7163,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
7164,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
7165,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
7166,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
7167,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
7168,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
7169,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
7170,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
7171,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
7172,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7173,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
7174,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
7175,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
7176,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
7177,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
7178,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
7179,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
7180,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
7181,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
7182,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7183,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7184,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7185,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7186,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7187,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7188,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7189,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7190,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7191,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7192,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7193,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7194,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7195,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7196,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7197,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7198,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7199,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7200,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7201,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7202,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7203,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7204,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7205,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7206,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7207,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7208,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7209,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
7210,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
7211,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
7212,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
7213,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
7214,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
7215,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
7216,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7217,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7218,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
7219,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
7220,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
7221,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
7222,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
7223,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
7224,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
7225,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7226,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7227,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7228,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7229,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7230,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7231,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7232,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7233,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7234,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7235,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7236,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7237,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7238,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7239,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7240,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7241,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7242,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7243,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7244,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7245,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7246,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7247,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7248,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7249,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7250,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7251,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7252,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7253,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7254,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7255,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7256,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7257,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7258,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7259,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7260,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7261,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7262,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7263,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7264,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7265,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7266,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7267,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7268,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7269,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7270,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7271,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7272,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7273,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7274,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7275,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7276,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7277,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7278,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7279,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7280,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7281,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7282,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7283,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7284,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7285,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7286,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7287,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7288,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7289,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7290,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7291,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7292,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7293,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7294,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7295,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7296,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7297,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7298,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7299,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7300,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7301,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7302,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
7303,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
7304,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
7305,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7306,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
7307,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
7308,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
7309,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
7310,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
7311,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7312,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7313,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7314,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7315,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7316,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7317,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7318,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7319,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7320,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7321,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7322,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7323,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7324,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7325,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7326,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7327,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7328,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7329,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7330,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7331,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7332,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7333,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7334,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7335,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7336,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7337,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7338,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7339,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7340,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7341,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7342,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7343,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7344,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7345,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7346,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7347,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7348,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7349,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7350,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7351,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7352,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7353,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7354,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7355,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7356,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7357,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7358,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7359,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7360,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7361,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7362,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7363,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7364,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7365,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7366,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7367,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7368,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7369,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7370,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7371,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7372,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7373,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7374,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7375,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7376,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7377,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7378,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7379,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7380,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7381,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7382,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7383,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7384,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7385,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7386,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7387,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7388,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7389,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7390,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7391,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7392,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7393,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7394,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7395,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7396,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7397,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7398,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7399,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
7400,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
7401,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
7402,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
7403,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
7404,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
7405,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7406,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
7407,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
7408,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
7409,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
7410,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
7411,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
7412,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
7413,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
7414,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
7415,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
7416,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7417,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
7418,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
7419,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7420,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7421,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7422,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7423,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7424,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7425,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7426,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7427,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7428,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7429,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7430,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7431,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7432,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7433,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7434,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7435,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7436,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7437,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7438,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7439,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7440,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7441,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7442,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7443,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7444,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7445,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7446,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
7447,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
7448,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
7449,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
7450,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7451,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
7452,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
7453,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
7454,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
7455,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
7456,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
7457,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
7458,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
7459,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
7460,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
7461,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7462,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7463,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7464,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7465,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7466,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7467,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7468,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7469,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7470,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7471,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7472,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7473,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7474,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7475,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7476,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7477,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7478,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7479,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7480,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7481,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7482,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7483,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7484,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7485,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7486,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7487,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7488,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7489,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7490,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7491,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7492,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7493,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7494,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7495,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7496,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7497,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7498,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7499,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7500,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7501,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7502,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7503,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7504,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7505,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7506,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7507,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7508,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7509,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7510,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7511,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7512,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7513,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7514,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7515,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
7516,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7517,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7518,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7519,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7520,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7521,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7522,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7523,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7524,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7525,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7526,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7527,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7528,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7529,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7530,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7531,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7532,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7533,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7534,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7535,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7536,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7537,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
7538,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7539,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
7540,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
7541,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
7542,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
7543,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
7544,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
7545,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
7546,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
7547,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7548,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7549,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
7550,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7551,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7552,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7553,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7554,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7555,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7556,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7557,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7558,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7559,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7560,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7561,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7562,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7563,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7564,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7565,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7566,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7567,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7568,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7569,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7570,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7571,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7572,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7573,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7574,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7575,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
7576,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7577,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7578,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7579,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7580,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7581,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7582,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7583,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7584,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7585,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7586,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7587,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7588,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7589,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7590,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7591,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7592,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7593,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7594,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7595,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7596,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7597,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7598,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7599,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7600,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7601,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7602,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7603,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7604,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7605,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7606,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7607,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7608,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7609,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7610,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7611,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7612,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7613,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7614,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7615,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7616,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7617,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7618,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7619,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7620,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7621,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7622,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7623,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7624,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7625,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7626,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7627,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7628,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7629,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7630,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7631,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7632,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7633,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7634,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7635,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7636,"This note focuses on the design of cost-sharing rules to optimize the efficiency of the resulting equilibria in cost-sharing games with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst-case guarantees on the performance of the (worst or best) equilibria. Our first result characterizes the cost-sharing design that optimizes the price of anarchy, followed by the price of stability. This optimal cost-sharing rule is precisely the Shapley value cost-sharing rule. Our second result characterizes the cost-sharing design that optimizes the price of stability, followed by the price of anarchy. This optimal cost-sharing rule is precisely the marginal contribution cost-sharing rule. This analysis highlights a fundamental tradeoff between the price of anarchy and price of stability in the considered class of games. That is, given the optimality of both the Shapley value and marginal cost distribution rules in each of their respective domains, it is impossible to improve either the price of anarchy or price of stability without degrading its counterpart.",matthew phillips,Distributed control,2018.0,10.1109/TAC.2017.2765299,IEEE Transactions on Automatic Control,Phillips2018,False,,IEEE,Not available,Design Tradeoffs in Concave Cost-Sharing Games,307d2a94c902970607eb2e463edd6415,https://ieeexplore.ieee.org/document/8078240/
7637,"This note focuses on the design of cost-sharing rules to optimize the efficiency of the resulting equilibria in cost-sharing games with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst-case guarantees on the performance of the (worst or best) equilibria. Our first result characterizes the cost-sharing design that optimizes the price of anarchy, followed by the price of stability. This optimal cost-sharing rule is precisely the Shapley value cost-sharing rule. Our second result characterizes the cost-sharing design that optimizes the price of stability, followed by the price of anarchy. This optimal cost-sharing rule is precisely the marginal contribution cost-sharing rule. This analysis highlights a fundamental tradeoff between the price of anarchy and price of stability in the considered class of games. That is, given the optimality of both the Shapley value and marginal cost distribution rules in each of their respective domains, it is impossible to improve either the price of anarchy or price of stability without degrading its counterpart.",matthew phillips,game theory,2018.0,10.1109/TAC.2017.2765299,IEEE Transactions on Automatic Control,Phillips2018,False,,IEEE,Not available,Design Tradeoffs in Concave Cost-Sharing Games,307d2a94c902970607eb2e463edd6415,https://ieeexplore.ieee.org/document/8078240/
7638,"This note focuses on the design of cost-sharing rules to optimize the efficiency of the resulting equilibria in cost-sharing games with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst-case guarantees on the performance of the (worst or best) equilibria. Our first result characterizes the cost-sharing design that optimizes the price of anarchy, followed by the price of stability. This optimal cost-sharing rule is precisely the Shapley value cost-sharing rule. Our second result characterizes the cost-sharing design that optimizes the price of stability, followed by the price of anarchy. This optimal cost-sharing rule is precisely the marginal contribution cost-sharing rule. This analysis highlights a fundamental tradeoff between the price of anarchy and price of stability in the considered class of games. That is, given the optimality of both the Shapley value and marginal cost distribution rules in each of their respective domains, it is impossible to improve either the price of anarchy or price of stability without degrading its counterpart.",matthew phillips,multiagent systems,2018.0,10.1109/TAC.2017.2765299,IEEE Transactions on Automatic Control,Phillips2018,False,,IEEE,Not available,Design Tradeoffs in Concave Cost-Sharing Games,307d2a94c902970607eb2e463edd6415,https://ieeexplore.ieee.org/document/8078240/
7639,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7640,"This note focuses on the design of cost-sharing rules to optimize the efficiency of the resulting equilibria in cost-sharing games with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst-case guarantees on the performance of the (worst or best) equilibria. Our first result characterizes the cost-sharing design that optimizes the price of anarchy, followed by the price of stability. This optimal cost-sharing rule is precisely the Shapley value cost-sharing rule. Our second result characterizes the cost-sharing design that optimizes the price of stability, followed by the price of anarchy. This optimal cost-sharing rule is precisely the marginal contribution cost-sharing rule. This analysis highlights a fundamental tradeoff between the price of anarchy and price of stability in the considered class of games. That is, given the optimality of both the Shapley value and marginal cost distribution rules in each of their respective domains, it is impossible to improve either the price of anarchy or price of stability without degrading its counterpart.",matthew phillips,networked control systems,2018.0,10.1109/TAC.2017.2765299,IEEE Transactions on Automatic Control,Phillips2018,False,,IEEE,Not available,Design Tradeoffs in Concave Cost-Sharing Games,307d2a94c902970607eb2e463edd6415,https://ieeexplore.ieee.org/document/8078240/
7641,"This note focuses on the design of cost-sharing rules to optimize the efficiency of the resulting equilibria in cost-sharing games with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst-case guarantees on the performance of the (worst or best) equilibria. Our first result characterizes the cost-sharing design that optimizes the price of anarchy, followed by the price of stability. This optimal cost-sharing rule is precisely the Shapley value cost-sharing rule. Our second result characterizes the cost-sharing design that optimizes the price of stability, followed by the price of anarchy. This optimal cost-sharing rule is precisely the marginal contribution cost-sharing rule. This analysis highlights a fundamental tradeoff between the price of anarchy and price of stability in the considered class of games. That is, given the optimality of both the Shapley value and marginal cost distribution rules in each of their respective domains, it is impossible to improve either the price of anarchy or price of stability without degrading its counterpart.",jason marden,Distributed control,2018.0,10.1109/TAC.2017.2765299,IEEE Transactions on Automatic Control,Phillips2018,False,,IEEE,Not available,Design Tradeoffs in Concave Cost-Sharing Games,307d2a94c902970607eb2e463edd6415,https://ieeexplore.ieee.org/document/8078240/
7642,"This note focuses on the design of cost-sharing rules to optimize the efficiency of the resulting equilibria in cost-sharing games with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst-case guarantees on the performance of the (worst or best) equilibria. Our first result characterizes the cost-sharing design that optimizes the price of anarchy, followed by the price of stability. This optimal cost-sharing rule is precisely the Shapley value cost-sharing rule. Our second result characterizes the cost-sharing design that optimizes the price of stability, followed by the price of anarchy. This optimal cost-sharing rule is precisely the marginal contribution cost-sharing rule. This analysis highlights a fundamental tradeoff between the price of anarchy and price of stability in the considered class of games. That is, given the optimality of both the Shapley value and marginal cost distribution rules in each of their respective domains, it is impossible to improve either the price of anarchy or price of stability without degrading its counterpart.",jason marden,game theory,2018.0,10.1109/TAC.2017.2765299,IEEE Transactions on Automatic Control,Phillips2018,False,,IEEE,Not available,Design Tradeoffs in Concave Cost-Sharing Games,307d2a94c902970607eb2e463edd6415,https://ieeexplore.ieee.org/document/8078240/
7643,"This note focuses on the design of cost-sharing rules to optimize the efficiency of the resulting equilibria in cost-sharing games with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst-case guarantees on the performance of the (worst or best) equilibria. Our first result characterizes the cost-sharing design that optimizes the price of anarchy, followed by the price of stability. This optimal cost-sharing rule is precisely the Shapley value cost-sharing rule. Our second result characterizes the cost-sharing design that optimizes the price of stability, followed by the price of anarchy. This optimal cost-sharing rule is precisely the marginal contribution cost-sharing rule. This analysis highlights a fundamental tradeoff between the price of anarchy and price of stability in the considered class of games. That is, given the optimality of both the Shapley value and marginal cost distribution rules in each of their respective domains, it is impossible to improve either the price of anarchy or price of stability without degrading its counterpart.",jason marden,multiagent systems,2018.0,10.1109/TAC.2017.2765299,IEEE Transactions on Automatic Control,Phillips2018,False,,IEEE,Not available,Design Tradeoffs in Concave Cost-Sharing Games,307d2a94c902970607eb2e463edd6415,https://ieeexplore.ieee.org/document/8078240/
7644,"This note focuses on the design of cost-sharing rules to optimize the efficiency of the resulting equilibria in cost-sharing games with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst-case guarantees on the performance of the (worst or best) equilibria. Our first result characterizes the cost-sharing design that optimizes the price of anarchy, followed by the price of stability. This optimal cost-sharing rule is precisely the Shapley value cost-sharing rule. Our second result characterizes the cost-sharing design that optimizes the price of stability, followed by the price of anarchy. This optimal cost-sharing rule is precisely the marginal contribution cost-sharing rule. This analysis highlights a fundamental tradeoff between the price of anarchy and price of stability in the considered class of games. That is, given the optimality of both the Shapley value and marginal cost distribution rules in each of their respective domains, it is impossible to improve either the price of anarchy or price of stability without degrading its counterpart.",jason marden,networked control systems,2018.0,10.1109/TAC.2017.2765299,IEEE Transactions on Automatic Control,Phillips2018,False,,IEEE,Not available,Design Tradeoffs in Concave Cost-Sharing Games,307d2a94c902970607eb2e463edd6415,https://ieeexplore.ieee.org/document/8078240/
7645,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
7646,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
7647,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
7648,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
7649,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
7650,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7651,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
7652,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
7653,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
7654,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",shay kutten,Peer to peer computing,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
7655,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",shay kutten,Games,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
7656,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",shay kutten,Electronic mail,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
7657,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",shay kutten,Conferences,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
7658,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",shay kutten,Information systems,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
7659,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",shay kutten,Electronic commerce,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
7660,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",shay kutten,Europe,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
7661,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
7662,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7663,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",ron lavi,Peer to peer computing,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
7664,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",ron lavi,Games,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
7665,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",ron lavi,Electronic mail,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
7666,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",ron lavi,Conferences,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
7667,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",ron lavi,Information systems,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
7668,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",ron lavi,Electronic commerce,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
7669,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",ron lavi,Europe,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
7670,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",amitabh trehan,Peer to peer computing,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
7671,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",amitabh trehan,Games,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
7672,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",amitabh trehan,Electronic mail,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
7673,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7674,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",amitabh trehan,Conferences,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
7675,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",amitabh trehan,Information systems,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
7676,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",amitabh trehan,Electronic commerce,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
7677,"Summary form only given. A traditional distributed system is often designed by some central manufacturer and owned by some central owner. However, increasingly, more modern distributed systems are composed of components, each owned by a different owner. Moreover, such systems are formed rather distributively, by people teaming up to pool their resources together. For example, many Peer to Peer (P2P) networks are composed of nodes belonging to different persons, who would like to gain by cooperation. In this paper, we consider ways by which people make distributed decisions regarding this composition of such systems, attempting to realize high values. We initiate the evaluation of those ways, by the quality of the resulting systems. We concentrate on settings in which a node can increase its utility by connecting to other nodes. However, the node must also pay a cost that increases with the size of the system. The right balance is achieved by the right size group of nodes. We address this issue using game theory, and refer to games in such settings as European Union grant games (based on the competition for the commission's grants) . For such a game, we study its price of anarchy (and also the strong price of anarchy) - the ratio between the average (over the system's components) value of the optimal possible system, and the average value for the system formed in the worst equilibrium. We formulate and analyze three intuitive games and show how simple changes in the protocol can improve the price of anarchy drastically. In particular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibility of appealing a rejection from a system. We show that the latter property is especially important if there are some pre-existing constraints regarding who may collaborate (or communicate) with whom.",amitabh trehan,Europe,2012.0,10.1109/INFCOMW.2012.6193482,2012 Proceedings IEEE INFOCOM Workshops,Kutten2012,False,,IEEE,Not available,Composition games for distributed systems: The EU grant games (abstract),885125f0db66e85ffa3d0bfcba501df5,https://ieeexplore.ieee.org/document/6193482/
7678,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",daniel lazar,Roads,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
7679,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",daniel lazar,Cost function,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
7680,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",daniel lazar,Routing,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
7681,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",daniel lazar,Delays,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
7682,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",daniel lazar,Automobiles,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
7683,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",daniel lazar,Cruise control,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
7684,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7685,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",samuel coogan,Roads,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
7686,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",samuel coogan,Cost function,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
7687,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",samuel coogan,Routing,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
7688,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",samuel coogan,Delays,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
7689,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",samuel coogan,Automobiles,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
7690,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",samuel coogan,Cruise control,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
7691,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",ramtin pedarsani,Roads,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
7692,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",ramtin pedarsani,Cost function,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
7693,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",ramtin pedarsani,Routing,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
7694,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",ramtin pedarsani,Delays,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
7695,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7696,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",ramtin pedarsani,Automobiles,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
7697,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",ramtin pedarsani,Cruise control,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
7698,"This paper studies the performance of a wireless network when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We define the utility of each node as a weighted difference between a performance metric and some transmission costs. We consider expected goodput and expected delay as the performance metrics. The relative preference of nodes for their performance metrics and the transmission costs is represented by a tradeoff factor. We first consider a scenario in which nodes can be priced for the channel access. We relate the tradeoff factor to some pricing mechanism and compute the symmetric Nash equilibria of the game in closed form as a function of the price factor. We show that simple pricing mechanisms can be used to maximize system efficiency. In particular, we show that for a specific value of price factor, the selfish behavior of the nodes can be used to achieve the same performance as social optima at equilibrium. In the case without pricing where the dis-utility coincides with the transmission energy costs, we analyze the Price of Anarchy for these games. For the game with goodput based utility, we show that the Price of Anarchy is infinite at the tradeoff factor that achieves the global optimal goodput. For the game with delay based utility, we bound the Price of Anarchy and study the effect of the tradeoff factor.",manjesh hanawal,Game Theory,2012.0,10.1109/JSAC.2012.121207,IEEE Journal on Selected Areas in Communications,Hanawal2012,False,,IEEE,Not available,Stochastic Geometry Based Medium Access Games in Wireless Ad Hoc Networks,a8150a029cf597501477ef5918f2db7d,https://ieeexplore.ieee.org/document/6354273/
7699,"This paper studies the performance of a wireless network when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We define the utility of each node as a weighted difference between a performance metric and some transmission costs. We consider expected goodput and expected delay as the performance metrics. The relative preference of nodes for their performance metrics and the transmission costs is represented by a tradeoff factor. We first consider a scenario in which nodes can be priced for the channel access. We relate the tradeoff factor to some pricing mechanism and compute the symmetric Nash equilibria of the game in closed form as a function of the price factor. We show that simple pricing mechanisms can be used to maximize system efficiency. In particular, we show that for a specific value of price factor, the selfish behavior of the nodes can be used to achieve the same performance as social optima at equilibrium. In the case without pricing where the dis-utility coincides with the transmission energy costs, we analyze the Price of Anarchy for these games. For the game with goodput based utility, we show that the Price of Anarchy is infinite at the tradeoff factor that achieves the global optimal goodput. For the game with delay based utility, we bound the Price of Anarchy and study the effect of the tradeoff factor.",manjesh hanawal,Mobile Ad hoc Networks (MANETs),2012.0,10.1109/JSAC.2012.121207,IEEE Journal on Selected Areas in Communications,Hanawal2012,False,,IEEE,Not available,Stochastic Geometry Based Medium Access Games in Wireless Ad Hoc Networks,a8150a029cf597501477ef5918f2db7d,https://ieeexplore.ieee.org/document/6354273/
7700,"This paper studies the performance of a wireless network when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We define the utility of each node as a weighted difference between a performance metric and some transmission costs. We consider expected goodput and expected delay as the performance metrics. The relative preference of nodes for their performance metrics and the transmission costs is represented by a tradeoff factor. We first consider a scenario in which nodes can be priced for the channel access. We relate the tradeoff factor to some pricing mechanism and compute the symmetric Nash equilibria of the game in closed form as a function of the price factor. We show that simple pricing mechanisms can be used to maximize system efficiency. In particular, we show that for a specific value of price factor, the selfish behavior of the nodes can be used to achieve the same performance as social optima at equilibrium. In the case without pricing where the dis-utility coincides with the transmission energy costs, we analyze the Price of Anarchy for these games. For the game with goodput based utility, we show that the Price of Anarchy is infinite at the tradeoff factor that achieves the global optimal goodput. For the game with delay based utility, we bound the Price of Anarchy and study the effect of the tradeoff factor.",manjesh hanawal,Pricing,2012.0,10.1109/JSAC.2012.121207,IEEE Journal on Selected Areas in Communications,Hanawal2012,False,,IEEE,Not available,Stochastic Geometry Based Medium Access Games in Wireless Ad Hoc Networks,a8150a029cf597501477ef5918f2db7d,https://ieeexplore.ieee.org/document/6354273/
7701,"This paper studies the performance of a wireless network when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We define the utility of each node as a weighted difference between a performance metric and some transmission costs. We consider expected goodput and expected delay as the performance metrics. The relative preference of nodes for their performance metrics and the transmission costs is represented by a tradeoff factor. We first consider a scenario in which nodes can be priced for the channel access. We relate the tradeoff factor to some pricing mechanism and compute the symmetric Nash equilibria of the game in closed form as a function of the price factor. We show that simple pricing mechanisms can be used to maximize system efficiency. In particular, we show that for a specific value of price factor, the selfish behavior of the nodes can be used to achieve the same performance as social optima at equilibrium. In the case without pricing where the dis-utility coincides with the transmission energy costs, we analyze the Price of Anarchy for these games. For the game with goodput based utility, we show that the Price of Anarchy is infinite at the tradeoff factor that achieves the global optimal goodput. For the game with delay based utility, we bound the Price of Anarchy and study the effect of the tradeoff factor.",manjesh hanawal,Medium Access Control,2012.0,10.1109/JSAC.2012.121207,IEEE Journal on Selected Areas in Communications,Hanawal2012,False,,IEEE,Not available,Stochastic Geometry Based Medium Access Games in Wireless Ad Hoc Networks,a8150a029cf597501477ef5918f2db7d,https://ieeexplore.ieee.org/document/6354273/
7702,"This paper studies the performance of a wireless network when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We define the utility of each node as a weighted difference between a performance metric and some transmission costs. We consider expected goodput and expected delay as the performance metrics. The relative preference of nodes for their performance metrics and the transmission costs is represented by a tradeoff factor. We first consider a scenario in which nodes can be priced for the channel access. We relate the tradeoff factor to some pricing mechanism and compute the symmetric Nash equilibria of the game in closed form as a function of the price factor. We show that simple pricing mechanisms can be used to maximize system efficiency. In particular, we show that for a specific value of price factor, the selfish behavior of the nodes can be used to achieve the same performance as social optima at equilibrium. In the case without pricing where the dis-utility coincides with the transmission energy costs, we analyze the Price of Anarchy for these games. For the game with goodput based utility, we show that the Price of Anarchy is infinite at the tradeoff factor that achieves the global optimal goodput. For the game with delay based utility, we bound the Price of Anarchy and study the effect of the tradeoff factor.",manjesh hanawal,Stochastic Geometry,2012.0,10.1109/JSAC.2012.121207,IEEE Journal on Selected Areas in Communications,Hanawal2012,False,,IEEE,Not available,Stochastic Geometry Based Medium Access Games in Wireless Ad Hoc Networks,a8150a029cf597501477ef5918f2db7d,https://ieeexplore.ieee.org/document/6354273/
7703,"This paper studies the performance of a wireless network when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We define the utility of each node as a weighted difference between a performance metric and some transmission costs. We consider expected goodput and expected delay as the performance metrics. The relative preference of nodes for their performance metrics and the transmission costs is represented by a tradeoff factor. We first consider a scenario in which nodes can be priced for the channel access. We relate the tradeoff factor to some pricing mechanism and compute the symmetric Nash equilibria of the game in closed form as a function of the price factor. We show that simple pricing mechanisms can be used to maximize system efficiency. In particular, we show that for a specific value of price factor, the selfish behavior of the nodes can be used to achieve the same performance as social optima at equilibrium. In the case without pricing where the dis-utility coincides with the transmission energy costs, we analyze the Price of Anarchy for these games. For the game with goodput based utility, we show that the Price of Anarchy is infinite at the tradeoff factor that achieves the global optimal goodput. For the game with delay based utility, we bound the Price of Anarchy and study the effect of the tradeoff factor.",manjesh hanawal,Replicator Dynamics,2012.0,10.1109/JSAC.2012.121207,IEEE Journal on Selected Areas in Communications,Hanawal2012,False,,IEEE,Not available,Stochastic Geometry Based Medium Access Games in Wireless Ad Hoc Networks,a8150a029cf597501477ef5918f2db7d,https://ieeexplore.ieee.org/document/6354273/
7704,"This paper studies the performance of a wireless network when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We define the utility of each node as a weighted difference between a performance metric and some transmission costs. We consider expected goodput and expected delay as the performance metrics. The relative preference of nodes for their performance metrics and the transmission costs is represented by a tradeoff factor. We first consider a scenario in which nodes can be priced for the channel access. We relate the tradeoff factor to some pricing mechanism and compute the symmetric Nash equilibria of the game in closed form as a function of the price factor. We show that simple pricing mechanisms can be used to maximize system efficiency. In particular, we show that for a specific value of price factor, the selfish behavior of the nodes can be used to achieve the same performance as social optima at equilibrium. In the case without pricing where the dis-utility coincides with the transmission energy costs, we analyze the Price of Anarchy for these games. For the game with goodput based utility, we show that the Price of Anarchy is infinite at the tradeoff factor that achieves the global optimal goodput. For the game with delay based utility, we bound the Price of Anarchy and study the effect of the tradeoff factor.",eitan altman,Game Theory,2012.0,10.1109/JSAC.2012.121207,IEEE Journal on Selected Areas in Communications,Hanawal2012,False,,IEEE,Not available,Stochastic Geometry Based Medium Access Games in Wireless Ad Hoc Networks,a8150a029cf597501477ef5918f2db7d,https://ieeexplore.ieee.org/document/6354273/
7705,"This paper studies the performance of a wireless network when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We define the utility of each node as a weighted difference between a performance metric and some transmission costs. We consider expected goodput and expected delay as the performance metrics. The relative preference of nodes for their performance metrics and the transmission costs is represented by a tradeoff factor. We first consider a scenario in which nodes can be priced for the channel access. We relate the tradeoff factor to some pricing mechanism and compute the symmetric Nash equilibria of the game in closed form as a function of the price factor. We show that simple pricing mechanisms can be used to maximize system efficiency. In particular, we show that for a specific value of price factor, the selfish behavior of the nodes can be used to achieve the same performance as social optima at equilibrium. In the case without pricing where the dis-utility coincides with the transmission energy costs, we analyze the Price of Anarchy for these games. For the game with goodput based utility, we show that the Price of Anarchy is infinite at the tradeoff factor that achieves the global optimal goodput. For the game with delay based utility, we bound the Price of Anarchy and study the effect of the tradeoff factor.",eitan altman,Mobile Ad hoc Networks (MANETs),2012.0,10.1109/JSAC.2012.121207,IEEE Journal on Selected Areas in Communications,Hanawal2012,False,,IEEE,Not available,Stochastic Geometry Based Medium Access Games in Wireless Ad Hoc Networks,a8150a029cf597501477ef5918f2db7d,https://ieeexplore.ieee.org/document/6354273/
7706,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7707,"This paper studies the performance of a wireless network when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We define the utility of each node as a weighted difference between a performance metric and some transmission costs. We consider expected goodput and expected delay as the performance metrics. The relative preference of nodes for their performance metrics and the transmission costs is represented by a tradeoff factor. We first consider a scenario in which nodes can be priced for the channel access. We relate the tradeoff factor to some pricing mechanism and compute the symmetric Nash equilibria of the game in closed form as a function of the price factor. We show that simple pricing mechanisms can be used to maximize system efficiency. In particular, we show that for a specific value of price factor, the selfish behavior of the nodes can be used to achieve the same performance as social optima at equilibrium. In the case without pricing where the dis-utility coincides with the transmission energy costs, we analyze the Price of Anarchy for these games. For the game with goodput based utility, we show that the Price of Anarchy is infinite at the tradeoff factor that achieves the global optimal goodput. For the game with delay based utility, we bound the Price of Anarchy and study the effect of the tradeoff factor.",eitan altman,Pricing,2012.0,10.1109/JSAC.2012.121207,IEEE Journal on Selected Areas in Communications,Hanawal2012,False,,IEEE,Not available,Stochastic Geometry Based Medium Access Games in Wireless Ad Hoc Networks,a8150a029cf597501477ef5918f2db7d,https://ieeexplore.ieee.org/document/6354273/
7708,"This paper studies the performance of a wireless network when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We define the utility of each node as a weighted difference between a performance metric and some transmission costs. We consider expected goodput and expected delay as the performance metrics. The relative preference of nodes for their performance metrics and the transmission costs is represented by a tradeoff factor. We first consider a scenario in which nodes can be priced for the channel access. We relate the tradeoff factor to some pricing mechanism and compute the symmetric Nash equilibria of the game in closed form as a function of the price factor. We show that simple pricing mechanisms can be used to maximize system efficiency. In particular, we show that for a specific value of price factor, the selfish behavior of the nodes can be used to achieve the same performance as social optima at equilibrium. In the case without pricing where the dis-utility coincides with the transmission energy costs, we analyze the Price of Anarchy for these games. For the game with goodput based utility, we show that the Price of Anarchy is infinite at the tradeoff factor that achieves the global optimal goodput. For the game with delay based utility, we bound the Price of Anarchy and study the effect of the tradeoff factor.",eitan altman,Medium Access Control,2012.0,10.1109/JSAC.2012.121207,IEEE Journal on Selected Areas in Communications,Hanawal2012,False,,IEEE,Not available,Stochastic Geometry Based Medium Access Games in Wireless Ad Hoc Networks,a8150a029cf597501477ef5918f2db7d,https://ieeexplore.ieee.org/document/6354273/
7709,"This paper studies the performance of a wireless network when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We define the utility of each node as a weighted difference between a performance metric and some transmission costs. We consider expected goodput and expected delay as the performance metrics. The relative preference of nodes for their performance metrics and the transmission costs is represented by a tradeoff factor. We first consider a scenario in which nodes can be priced for the channel access. We relate the tradeoff factor to some pricing mechanism and compute the symmetric Nash equilibria of the game in closed form as a function of the price factor. We show that simple pricing mechanisms can be used to maximize system efficiency. In particular, we show that for a specific value of price factor, the selfish behavior of the nodes can be used to achieve the same performance as social optima at equilibrium. In the case without pricing where the dis-utility coincides with the transmission energy costs, we analyze the Price of Anarchy for these games. For the game with goodput based utility, we show that the Price of Anarchy is infinite at the tradeoff factor that achieves the global optimal goodput. For the game with delay based utility, we bound the Price of Anarchy and study the effect of the tradeoff factor.",eitan altman,Stochastic Geometry,2012.0,10.1109/JSAC.2012.121207,IEEE Journal on Selected Areas in Communications,Hanawal2012,False,,IEEE,Not available,Stochastic Geometry Based Medium Access Games in Wireless Ad Hoc Networks,a8150a029cf597501477ef5918f2db7d,https://ieeexplore.ieee.org/document/6354273/
7710,"This paper studies the performance of a wireless network when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We define the utility of each node as a weighted difference between a performance metric and some transmission costs. We consider expected goodput and expected delay as the performance metrics. The relative preference of nodes for their performance metrics and the transmission costs is represented by a tradeoff factor. We first consider a scenario in which nodes can be priced for the channel access. We relate the tradeoff factor to some pricing mechanism and compute the symmetric Nash equilibria of the game in closed form as a function of the price factor. We show that simple pricing mechanisms can be used to maximize system efficiency. In particular, we show that for a specific value of price factor, the selfish behavior of the nodes can be used to achieve the same performance as social optima at equilibrium. In the case without pricing where the dis-utility coincides with the transmission energy costs, we analyze the Price of Anarchy for these games. For the game with goodput based utility, we show that the Price of Anarchy is infinite at the tradeoff factor that achieves the global optimal goodput. For the game with delay based utility, we bound the Price of Anarchy and study the effect of the tradeoff factor.",eitan altman,Replicator Dynamics,2012.0,10.1109/JSAC.2012.121207,IEEE Journal on Selected Areas in Communications,Hanawal2012,False,,IEEE,Not available,Stochastic Geometry Based Medium Access Games in Wireless Ad Hoc Networks,a8150a029cf597501477ef5918f2db7d,https://ieeexplore.ieee.org/document/6354273/
7711,"This paper studies the performance of a wireless network when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We define the utility of each node as a weighted difference between a performance metric and some transmission costs. We consider expected goodput and expected delay as the performance metrics. The relative preference of nodes for their performance metrics and the transmission costs is represented by a tradeoff factor. We first consider a scenario in which nodes can be priced for the channel access. We relate the tradeoff factor to some pricing mechanism and compute the symmetric Nash equilibria of the game in closed form as a function of the price factor. We show that simple pricing mechanisms can be used to maximize system efficiency. In particular, we show that for a specific value of price factor, the selfish behavior of the nodes can be used to achieve the same performance as social optima at equilibrium. In the case without pricing where the dis-utility coincides with the transmission energy costs, we analyze the Price of Anarchy for these games. For the game with goodput based utility, we show that the Price of Anarchy is infinite at the tradeoff factor that achieves the global optimal goodput. For the game with delay based utility, we bound the Price of Anarchy and study the effect of the tradeoff factor.",francois baccelli,Game Theory,2012.0,10.1109/JSAC.2012.121207,IEEE Journal on Selected Areas in Communications,Hanawal2012,False,,IEEE,Not available,Stochastic Geometry Based Medium Access Games in Wireless Ad Hoc Networks,a8150a029cf597501477ef5918f2db7d,https://ieeexplore.ieee.org/document/6354273/
7712,"This paper studies the performance of a wireless network when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We define the utility of each node as a weighted difference between a performance metric and some transmission costs. We consider expected goodput and expected delay as the performance metrics. The relative preference of nodes for their performance metrics and the transmission costs is represented by a tradeoff factor. We first consider a scenario in which nodes can be priced for the channel access. We relate the tradeoff factor to some pricing mechanism and compute the symmetric Nash equilibria of the game in closed form as a function of the price factor. We show that simple pricing mechanisms can be used to maximize system efficiency. In particular, we show that for a specific value of price factor, the selfish behavior of the nodes can be used to achieve the same performance as social optima at equilibrium. In the case without pricing where the dis-utility coincides with the transmission energy costs, we analyze the Price of Anarchy for these games. For the game with goodput based utility, we show that the Price of Anarchy is infinite at the tradeoff factor that achieves the global optimal goodput. For the game with delay based utility, we bound the Price of Anarchy and study the effect of the tradeoff factor.",francois baccelli,Mobile Ad hoc Networks (MANETs),2012.0,10.1109/JSAC.2012.121207,IEEE Journal on Selected Areas in Communications,Hanawal2012,False,,IEEE,Not available,Stochastic Geometry Based Medium Access Games in Wireless Ad Hoc Networks,a8150a029cf597501477ef5918f2db7d,https://ieeexplore.ieee.org/document/6354273/
7713,"This paper studies the performance of a wireless network when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We define the utility of each node as a weighted difference between a performance metric and some transmission costs. We consider expected goodput and expected delay as the performance metrics. The relative preference of nodes for their performance metrics and the transmission costs is represented by a tradeoff factor. We first consider a scenario in which nodes can be priced for the channel access. We relate the tradeoff factor to some pricing mechanism and compute the symmetric Nash equilibria of the game in closed form as a function of the price factor. We show that simple pricing mechanisms can be used to maximize system efficiency. In particular, we show that for a specific value of price factor, the selfish behavior of the nodes can be used to achieve the same performance as social optima at equilibrium. In the case without pricing where the dis-utility coincides with the transmission energy costs, we analyze the Price of Anarchy for these games. For the game with goodput based utility, we show that the Price of Anarchy is infinite at the tradeoff factor that achieves the global optimal goodput. For the game with delay based utility, we bound the Price of Anarchy and study the effect of the tradeoff factor.",francois baccelli,Pricing,2012.0,10.1109/JSAC.2012.121207,IEEE Journal on Selected Areas in Communications,Hanawal2012,False,,IEEE,Not available,Stochastic Geometry Based Medium Access Games in Wireless Ad Hoc Networks,a8150a029cf597501477ef5918f2db7d,https://ieeexplore.ieee.org/document/6354273/
7714,"This paper studies the performance of a wireless network when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We define the utility of each node as a weighted difference between a performance metric and some transmission costs. We consider expected goodput and expected delay as the performance metrics. The relative preference of nodes for their performance metrics and the transmission costs is represented by a tradeoff factor. We first consider a scenario in which nodes can be priced for the channel access. We relate the tradeoff factor to some pricing mechanism and compute the symmetric Nash equilibria of the game in closed form as a function of the price factor. We show that simple pricing mechanisms can be used to maximize system efficiency. In particular, we show that for a specific value of price factor, the selfish behavior of the nodes can be used to achieve the same performance as social optima at equilibrium. In the case without pricing where the dis-utility coincides with the transmission energy costs, we analyze the Price of Anarchy for these games. For the game with goodput based utility, we show that the Price of Anarchy is infinite at the tradeoff factor that achieves the global optimal goodput. For the game with delay based utility, we bound the Price of Anarchy and study the effect of the tradeoff factor.",francois baccelli,Medium Access Control,2012.0,10.1109/JSAC.2012.121207,IEEE Journal on Selected Areas in Communications,Hanawal2012,False,,IEEE,Not available,Stochastic Geometry Based Medium Access Games in Wireless Ad Hoc Networks,a8150a029cf597501477ef5918f2db7d,https://ieeexplore.ieee.org/document/6354273/
7715,"This paper studies the performance of a wireless network when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We define the utility of each node as a weighted difference between a performance metric and some transmission costs. We consider expected goodput and expected delay as the performance metrics. The relative preference of nodes for their performance metrics and the transmission costs is represented by a tradeoff factor. We first consider a scenario in which nodes can be priced for the channel access. We relate the tradeoff factor to some pricing mechanism and compute the symmetric Nash equilibria of the game in closed form as a function of the price factor. We show that simple pricing mechanisms can be used to maximize system efficiency. In particular, we show that for a specific value of price factor, the selfish behavior of the nodes can be used to achieve the same performance as social optima at equilibrium. In the case without pricing where the dis-utility coincides with the transmission energy costs, we analyze the Price of Anarchy for these games. For the game with goodput based utility, we show that the Price of Anarchy is infinite at the tradeoff factor that achieves the global optimal goodput. For the game with delay based utility, we bound the Price of Anarchy and study the effect of the tradeoff factor.",francois baccelli,Stochastic Geometry,2012.0,10.1109/JSAC.2012.121207,IEEE Journal on Selected Areas in Communications,Hanawal2012,False,,IEEE,Not available,Stochastic Geometry Based Medium Access Games in Wireless Ad Hoc Networks,a8150a029cf597501477ef5918f2db7d,https://ieeexplore.ieee.org/document/6354273/
7716,"This paper studies the performance of a wireless network when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We define the utility of each node as a weighted difference between a performance metric and some transmission costs. We consider expected goodput and expected delay as the performance metrics. The relative preference of nodes for their performance metrics and the transmission costs is represented by a tradeoff factor. We first consider a scenario in which nodes can be priced for the channel access. We relate the tradeoff factor to some pricing mechanism and compute the symmetric Nash equilibria of the game in closed form as a function of the price factor. We show that simple pricing mechanisms can be used to maximize system efficiency. In particular, we show that for a specific value of price factor, the selfish behavior of the nodes can be used to achieve the same performance as social optima at equilibrium. In the case without pricing where the dis-utility coincides with the transmission energy costs, we analyze the Price of Anarchy for these games. For the game with goodput based utility, we show that the Price of Anarchy is infinite at the tradeoff factor that achieves the global optimal goodput. For the game with delay based utility, we bound the Price of Anarchy and study the effect of the tradeoff factor.",francois baccelli,Replicator Dynamics,2012.0,10.1109/JSAC.2012.121207,IEEE Journal on Selected Areas in Communications,Hanawal2012,False,,IEEE,Not available,Stochastic Geometry Based Medium Access Games in Wireless Ad Hoc Networks,a8150a029cf597501477ef5918f2db7d,https://ieeexplore.ieee.org/document/6354273/
7717,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7718,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",y. xi,Pricing,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
7719,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",y. xi,Routing,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
7720,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",y. xi,Spread spectrum communication,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
7721,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",y. xi,Relays,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
7722,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",y. xi,Peer to peer computing,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
7723,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",y. xi,Telecommunication traffic,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
7724,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",y. xi,Cost function,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
7725,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",y. xi,Network topology,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
7726,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",y. xi,Communications Society,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
7727,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",y. xi,USA Councils,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
7728,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7729,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",e. yeh,Pricing,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
7730,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",e. yeh,Routing,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
7731,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",e. yeh,Spread spectrum communication,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
7732,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",e. yeh,Relays,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
7733,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",e. yeh,Peer to peer computing,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
7734,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",e. yeh,Telecommunication traffic,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
7735,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",e. yeh,Cost function,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
7736,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",e. yeh,Network topology,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
7737,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",e. yeh,Communications Society,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
7738,"We study pricing games in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. Each node (1) makes a bid to each of its customers, specifying a charging function and a proposed traffic share, and (2) allocates its received traffic to its service providers. A node aims to maximize its profit from forwarding traffic. We show that the socially optimal routing can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its bids. Inefficient equilibria arise in oligopolies due to the monopolistic pricing power of a superior relay. It results in finite price of anarchy if marginal cost functions are concave, but unbounded price of anarchy when they are convex. Pricing games of general topology suffer from the intrinsic multi-hop network structure, which gives rise to infinite price of anarchy.",e. yeh,USA Councils,2008.0,10.1109/INFOCOM.2008.205,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Xi2008,False,,IEEE,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-Hop Relay Networks",9fb6a6b9db3d20fd2fdce0a22432751c,https://ieeexplore.ieee.org/document/4509800/
7739,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7740,"This paper studies the performance of Mobile Ad hoc Networks (MANETs) when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We consider goodput and delay as the performance metric that each node is interested in optimizing taking into account the transmission energy costs. We introduce a pricing scheme based on the transmission energy requirements and compute the symmetric Nash equilibria of the game in closed form. It is shown that by appropriately pricing the nodes, the selfish behavior of the nodes can be used to achieve the social optimum at equilibrium. The price of anarchy is then analyzed for these games. For the game with delay based utility, we bound the price of anarchy and study the effect of the price factor. For the game with goodput based utility, it is shown that price of anarchy is infinite at the price factor that achieves the global optima.",m.k. hanawal,Game Theory,2012.0,10.1109/INFCOM.2012.6195554,2012 Proceedings IEEE INFOCOM,Hanawal2012,False,,IEEE,Not available,Stochastic geometry based medium access games,d91dc35b4e99845860d323b3bc42cb30,https://ieeexplore.ieee.org/document/6195554/
7741,"This paper studies the performance of Mobile Ad hoc Networks (MANETs) when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We consider goodput and delay as the performance metric that each node is interested in optimizing taking into account the transmission energy costs. We introduce a pricing scheme based on the transmission energy requirements and compute the symmetric Nash equilibria of the game in closed form. It is shown that by appropriately pricing the nodes, the selfish behavior of the nodes can be used to achieve the social optimum at equilibrium. The price of anarchy is then analyzed for these games. For the game with delay based utility, we bound the price of anarchy and study the effect of the price factor. For the game with goodput based utility, it is shown that price of anarchy is infinite at the price factor that achieves the global optima.",m.k. hanawal,Mobile Ad hoc Networks (MANETs),2012.0,10.1109/INFCOM.2012.6195554,2012 Proceedings IEEE INFOCOM,Hanawal2012,False,,IEEE,Not available,Stochastic geometry based medium access games,d91dc35b4e99845860d323b3bc42cb30,https://ieeexplore.ieee.org/document/6195554/
7742,"This paper studies the performance of Mobile Ad hoc Networks (MANETs) when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We consider goodput and delay as the performance metric that each node is interested in optimizing taking into account the transmission energy costs. We introduce a pricing scheme based on the transmission energy requirements and compute the symmetric Nash equilibria of the game in closed form. It is shown that by appropriately pricing the nodes, the selfish behavior of the nodes can be used to achieve the social optimum at equilibrium. The price of anarchy is then analyzed for these games. For the game with delay based utility, we bound the price of anarchy and study the effect of the price factor. For the game with goodput based utility, it is shown that price of anarchy is infinite at the price factor that achieves the global optima.",m.k. hanawal,Pricing,2012.0,10.1109/INFCOM.2012.6195554,2012 Proceedings IEEE INFOCOM,Hanawal2012,False,,IEEE,Not available,Stochastic geometry based medium access games,d91dc35b4e99845860d323b3bc42cb30,https://ieeexplore.ieee.org/document/6195554/
7743,"This paper studies the performance of Mobile Ad hoc Networks (MANETs) when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We consider goodput and delay as the performance metric that each node is interested in optimizing taking into account the transmission energy costs. We introduce a pricing scheme based on the transmission energy requirements and compute the symmetric Nash equilibria of the game in closed form. It is shown that by appropriately pricing the nodes, the selfish behavior of the nodes can be used to achieve the social optimum at equilibrium. The price of anarchy is then analyzed for these games. For the game with delay based utility, we bound the price of anarchy and study the effect of the price factor. For the game with goodput based utility, it is shown that price of anarchy is infinite at the price factor that achieves the global optima.",m.k. hanawal,Medium Access Control,2012.0,10.1109/INFCOM.2012.6195554,2012 Proceedings IEEE INFOCOM,Hanawal2012,False,,IEEE,Not available,Stochastic geometry based medium access games,d91dc35b4e99845860d323b3bc42cb30,https://ieeexplore.ieee.org/document/6195554/
7744,"This paper studies the performance of Mobile Ad hoc Networks (MANETs) when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We consider goodput and delay as the performance metric that each node is interested in optimizing taking into account the transmission energy costs. We introduce a pricing scheme based on the transmission energy requirements and compute the symmetric Nash equilibria of the game in closed form. It is shown that by appropriately pricing the nodes, the selfish behavior of the nodes can be used to achieve the social optimum at equilibrium. The price of anarchy is then analyzed for these games. For the game with delay based utility, we bound the price of anarchy and study the effect of the price factor. For the game with goodput based utility, it is shown that price of anarchy is infinite at the price factor that achieves the global optima.",m.k. hanawal,Stochastic Geometry,2012.0,10.1109/INFCOM.2012.6195554,2012 Proceedings IEEE INFOCOM,Hanawal2012,False,,IEEE,Not available,Stochastic geometry based medium access games,d91dc35b4e99845860d323b3bc42cb30,https://ieeexplore.ieee.org/document/6195554/
7745,"This paper studies the performance of Mobile Ad hoc Networks (MANETs) when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We consider goodput and delay as the performance metric that each node is interested in optimizing taking into account the transmission energy costs. We introduce a pricing scheme based on the transmission energy requirements and compute the symmetric Nash equilibria of the game in closed form. It is shown that by appropriately pricing the nodes, the selfish behavior of the nodes can be used to achieve the social optimum at equilibrium. The price of anarchy is then analyzed for these games. For the game with delay based utility, we bound the price of anarchy and study the effect of the price factor. For the game with goodput based utility, it is shown that price of anarchy is infinite at the price factor that achieves the global optima.",e. altman,Game Theory,2012.0,10.1109/INFCOM.2012.6195554,2012 Proceedings IEEE INFOCOM,Hanawal2012,False,,IEEE,Not available,Stochastic geometry based medium access games,d91dc35b4e99845860d323b3bc42cb30,https://ieeexplore.ieee.org/document/6195554/
7746,"This paper studies the performance of Mobile Ad hoc Networks (MANETs) when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We consider goodput and delay as the performance metric that each node is interested in optimizing taking into account the transmission energy costs. We introduce a pricing scheme based on the transmission energy requirements and compute the symmetric Nash equilibria of the game in closed form. It is shown that by appropriately pricing the nodes, the selfish behavior of the nodes can be used to achieve the social optimum at equilibrium. The price of anarchy is then analyzed for these games. For the game with delay based utility, we bound the price of anarchy and study the effect of the price factor. For the game with goodput based utility, it is shown that price of anarchy is infinite at the price factor that achieves the global optima.",e. altman,Mobile Ad hoc Networks (MANETs),2012.0,10.1109/INFCOM.2012.6195554,2012 Proceedings IEEE INFOCOM,Hanawal2012,False,,IEEE,Not available,Stochastic geometry based medium access games,d91dc35b4e99845860d323b3bc42cb30,https://ieeexplore.ieee.org/document/6195554/
7747,"This paper studies the performance of Mobile Ad hoc Networks (MANETs) when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We consider goodput and delay as the performance metric that each node is interested in optimizing taking into account the transmission energy costs. We introduce a pricing scheme based on the transmission energy requirements and compute the symmetric Nash equilibria of the game in closed form. It is shown that by appropriately pricing the nodes, the selfish behavior of the nodes can be used to achieve the social optimum at equilibrium. The price of anarchy is then analyzed for these games. For the game with delay based utility, we bound the price of anarchy and study the effect of the price factor. For the game with goodput based utility, it is shown that price of anarchy is infinite at the price factor that achieves the global optima.",e. altman,Pricing,2012.0,10.1109/INFCOM.2012.6195554,2012 Proceedings IEEE INFOCOM,Hanawal2012,False,,IEEE,Not available,Stochastic geometry based medium access games,d91dc35b4e99845860d323b3bc42cb30,https://ieeexplore.ieee.org/document/6195554/
7748,"This paper studies the performance of Mobile Ad hoc Networks (MANETs) when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We consider goodput and delay as the performance metric that each node is interested in optimizing taking into account the transmission energy costs. We introduce a pricing scheme based on the transmission energy requirements and compute the symmetric Nash equilibria of the game in closed form. It is shown that by appropriately pricing the nodes, the selfish behavior of the nodes can be used to achieve the social optimum at equilibrium. The price of anarchy is then analyzed for these games. For the game with delay based utility, we bound the price of anarchy and study the effect of the price factor. For the game with goodput based utility, it is shown that price of anarchy is infinite at the price factor that achieves the global optima.",e. altman,Medium Access Control,2012.0,10.1109/INFCOM.2012.6195554,2012 Proceedings IEEE INFOCOM,Hanawal2012,False,,IEEE,Not available,Stochastic geometry based medium access games,d91dc35b4e99845860d323b3bc42cb30,https://ieeexplore.ieee.org/document/6195554/
7749,"This paper studies the performance of Mobile Ad hoc Networks (MANETs) when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We consider goodput and delay as the performance metric that each node is interested in optimizing taking into account the transmission energy costs. We introduce a pricing scheme based on the transmission energy requirements and compute the symmetric Nash equilibria of the game in closed form. It is shown that by appropriately pricing the nodes, the selfish behavior of the nodes can be used to achieve the social optimum at equilibrium. The price of anarchy is then analyzed for these games. For the game with delay based utility, we bound the price of anarchy and study the effect of the price factor. For the game with goodput based utility, it is shown that price of anarchy is infinite at the price factor that achieves the global optima.",e. altman,Stochastic Geometry,2012.0,10.1109/INFCOM.2012.6195554,2012 Proceedings IEEE INFOCOM,Hanawal2012,False,,IEEE,Not available,Stochastic geometry based medium access games,d91dc35b4e99845860d323b3bc42cb30,https://ieeexplore.ieee.org/document/6195554/
7750,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7751,"This paper studies the performance of Mobile Ad hoc Networks (MANETs) when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We consider goodput and delay as the performance metric that each node is interested in optimizing taking into account the transmission energy costs. We introduce a pricing scheme based on the transmission energy requirements and compute the symmetric Nash equilibria of the game in closed form. It is shown that by appropriately pricing the nodes, the selfish behavior of the nodes can be used to achieve the social optimum at equilibrium. The price of anarchy is then analyzed for these games. For the game with delay based utility, we bound the price of anarchy and study the effect of the price factor. For the game with goodput based utility, it is shown that price of anarchy is infinite at the price factor that achieves the global optima.",f. baccelli,Game Theory,2012.0,10.1109/INFCOM.2012.6195554,2012 Proceedings IEEE INFOCOM,Hanawal2012,False,,IEEE,Not available,Stochastic geometry based medium access games,d91dc35b4e99845860d323b3bc42cb30,https://ieeexplore.ieee.org/document/6195554/
7752,"This paper studies the performance of Mobile Ad hoc Networks (MANETs) when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We consider goodput and delay as the performance metric that each node is interested in optimizing taking into account the transmission energy costs. We introduce a pricing scheme based on the transmission energy requirements and compute the symmetric Nash equilibria of the game in closed form. It is shown that by appropriately pricing the nodes, the selfish behavior of the nodes can be used to achieve the social optimum at equilibrium. The price of anarchy is then analyzed for these games. For the game with delay based utility, we bound the price of anarchy and study the effect of the price factor. For the game with goodput based utility, it is shown that price of anarchy is infinite at the price factor that achieves the global optima.",f. baccelli,Mobile Ad hoc Networks (MANETs),2012.0,10.1109/INFCOM.2012.6195554,2012 Proceedings IEEE INFOCOM,Hanawal2012,False,,IEEE,Not available,Stochastic geometry based medium access games,d91dc35b4e99845860d323b3bc42cb30,https://ieeexplore.ieee.org/document/6195554/
7753,"This paper studies the performance of Mobile Ad hoc Networks (MANETs) when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We consider goodput and delay as the performance metric that each node is interested in optimizing taking into account the transmission energy costs. We introduce a pricing scheme based on the transmission energy requirements and compute the symmetric Nash equilibria of the game in closed form. It is shown that by appropriately pricing the nodes, the selfish behavior of the nodes can be used to achieve the social optimum at equilibrium. The price of anarchy is then analyzed for these games. For the game with delay based utility, we bound the price of anarchy and study the effect of the price factor. For the game with goodput based utility, it is shown that price of anarchy is infinite at the price factor that achieves the global optima.",f. baccelli,Pricing,2012.0,10.1109/INFCOM.2012.6195554,2012 Proceedings IEEE INFOCOM,Hanawal2012,False,,IEEE,Not available,Stochastic geometry based medium access games,d91dc35b4e99845860d323b3bc42cb30,https://ieeexplore.ieee.org/document/6195554/
7754,"This paper studies the performance of Mobile Ad hoc Networks (MANETs) when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We consider goodput and delay as the performance metric that each node is interested in optimizing taking into account the transmission energy costs. We introduce a pricing scheme based on the transmission energy requirements and compute the symmetric Nash equilibria of the game in closed form. It is shown that by appropriately pricing the nodes, the selfish behavior of the nodes can be used to achieve the social optimum at equilibrium. The price of anarchy is then analyzed for these games. For the game with delay based utility, we bound the price of anarchy and study the effect of the price factor. For the game with goodput based utility, it is shown that price of anarchy is infinite at the price factor that achieves the global optima.",f. baccelli,Medium Access Control,2012.0,10.1109/INFCOM.2012.6195554,2012 Proceedings IEEE INFOCOM,Hanawal2012,False,,IEEE,Not available,Stochastic geometry based medium access games,d91dc35b4e99845860d323b3bc42cb30,https://ieeexplore.ieee.org/document/6195554/
7755,"This paper studies the performance of Mobile Ad hoc Networks (MANETs) when the nodes, that form a Poisson point process, selfishly choose their Medium Access Probability (MAP). We consider goodput and delay as the performance metric that each node is interested in optimizing taking into account the transmission energy costs. We introduce a pricing scheme based on the transmission energy requirements and compute the symmetric Nash equilibria of the game in closed form. It is shown that by appropriately pricing the nodes, the selfish behavior of the nodes can be used to achieve the social optimum at equilibrium. The price of anarchy is then analyzed for these games. For the game with delay based utility, we bound the price of anarchy and study the effect of the price factor. For the game with goodput based utility, it is shown that price of anarchy is infinite at the price factor that achieves the global optima.",f. baccelli,Stochastic Geometry,2012.0,10.1109/INFCOM.2012.6195554,2012 Proceedings IEEE INFOCOM,Hanawal2012,False,,IEEE,Not available,Stochastic geometry based medium access games,d91dc35b4e99845860d323b3bc42cb30,https://ieeexplore.ieee.org/document/6195554/
7756,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",evangelos bampas,Bottleneck games,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
7757,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",evangelos bampas,multifiber optical networks,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
7758,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",evangelos bampas,noncooperative games,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
7759,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",evangelos bampas,path multicoloring,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
7760,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",evangelos bampas,price of anarchy,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
7761,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7762,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",evangelos bampas,selfish wavelength assignment,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
7763,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",aris pagourtzis,Bottleneck games,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
7764,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",aris pagourtzis,multifiber optical networks,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
7765,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",aris pagourtzis,noncooperative games,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
7766,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",aris pagourtzis,path multicoloring,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
7767,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",aris pagourtzis,price of anarchy,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
7768,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",aris pagourtzis,selfish wavelength assignment,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
7769,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",george pierrakos,Bottleneck games,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
7770,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",george pierrakos,multifiber optical networks,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
7771,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",george pierrakos,noncooperative games,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
7772,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
7773,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7774,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",george pierrakos,path multicoloring,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
7775,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",george pierrakos,price of anarchy,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
7776,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",george pierrakos,selfish wavelength assignment,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
7777,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",katerina potika,Bottleneck games,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
7778,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",katerina potika,multifiber optical networks,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
7779,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",katerina potika,noncooperative games,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
7780,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",katerina potika,path multicoloring,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
7781,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",katerina potika,price of anarchy,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
7782,"We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.",katerina potika,selfish wavelength assignment,2012.0,10.1109/TNET.2011.2173948,IEEE/ACM Transactions on Networking,Bampas2012,False,,IEEE,Not available,On a Noncooperative Model for Wavelength Assignment in Multifiber Optical Networks,5dc1e47fde379b53e18ed56b7f02f9a3,https://ieeexplore.ieee.org/document/6072290/
7783,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",jason marden,Games,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
7784,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7785,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",jason marden,Linear programming,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
7786,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",jason marden,Stability analysis,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
7787,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",jason marden,Resource management,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
7788,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",jason marden,Cost function,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
7789,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",jason marden,Decision making,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
7790,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",jason marden,Computer architecture,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
7791,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",matthew philips,Games,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
7792,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",matthew philips,Linear programming,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
7793,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",matthew philips,Stability analysis,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
7794,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",matthew philips,Resource management,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
7795,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7796,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",matthew philips,Cost function,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
7797,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",matthew philips,Decision making,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
7798,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",matthew philips,Computer architecture,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
7799,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",john musacchio,Diffserv networks,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
7800,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",john musacchio,Telecommunication traffic,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
7801,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",john musacchio,Traffic control,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
7802,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",john musacchio,Delay,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
7803,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",john musacchio,Nash equilibrium,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
7804,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",john musacchio,Costs,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
7805,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",john musacchio,Pricing,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
7806,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7807,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",john musacchio,Routing,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
7808,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",john musacchio,Environmental economics,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
7809,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",john musacchio,Degradation,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
7810,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",shuang wu,Diffserv networks,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
7811,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",shuang wu,Telecommunication traffic,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
7812,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",shuang wu,Traffic control,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
7813,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",shuang wu,Delay,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
7814,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",shuang wu,Nash equilibrium,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
7815,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",shuang wu,Costs,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
7816,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",shuang wu,Pricing,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
7817,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7818,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",shuang wu,Routing,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
7819,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",shuang wu,Environmental economics,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
7820,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",shuang wu,Degradation,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
7821,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",prasanna chaporkar,Wireless LAN,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
7822,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",prasanna chaporkar,Nash equilibrium,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
7823,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",prasanna chaporkar,Throughput,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
7824,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",prasanna chaporkar,Communications Society,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
7825,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",prasanna chaporkar,Media Access Protocol,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
7826,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",prasanna chaporkar,H infinity control,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
7827,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",prasanna chaporkar,Time factors,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
7828,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
7829,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",prasanna chaporkar,Hardware,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
7830,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",prasanna chaporkar,Modulation coding,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
7831,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",prasanna chaporkar,Propagation losses,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
7832,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",alexandre proutiere,Wireless LAN,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
7833,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",alexandre proutiere,Nash equilibrium,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
7834,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",alexandre proutiere,Throughput,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
7835,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",alexandre proutiere,Communications Society,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
7836,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",alexandre proutiere,Media Access Protocol,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
7837,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",alexandre proutiere,H infinity control,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
7838,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",alexandre proutiere,Time factors,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
7839,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
7840,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",alexandre proutiere,Hardware,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
7841,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",alexandre proutiere,Modulation coding,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
7842,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",alexandre proutiere,Propagation losses,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
7843,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",bozidar radunoviae,Wireless LAN,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
7844,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",bozidar radunoviae,Nash equilibrium,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
7845,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",bozidar radunoviae,Throughput,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
7846,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",bozidar radunoviae,Communications Society,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
7847,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",bozidar radunoviae,Media Access Protocol,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
7848,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",bozidar radunoviae,H infinity control,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
7849,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",bozidar radunoviae,Time factors,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
7850,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
7851,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",bozidar radunoviae,Hardware,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
7852,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",bozidar radunoviae,Modulation coding,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
7853,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",bozidar radunoviae,Propagation losses,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
7854,"Recent results have shown that selfish users do not have an incentive to participate in intersession network coding in a static noncooperative game setting. Because of this, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 20%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be improved to 36%. We design a grim-trigger strategy that encourages users to cooperate and participate in the intersession network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We resolve the conflict of interest among the users through a bargaining process and obtain tight upper bounds for the price-of-anarchy that are valid for any possible bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve these upper bounds, as confirmed through simulation studies. The coexistence of multiple selfish network coding sessions as well as the coexistence of selfish network coding and routing sessions are also investigated. Our results represent a first step toward designing practical intersession network coding schemes that achieve reasonable performance for selfish users.",hamed mohsenian-rad,Min-max bargaining solution,2014.0,10.1109/TNET.2013.2271038,IEEE/ACM Transactions on Networking,Mohsenian-Rad2014,False,,IEEE,Not available,Repeated Intersession Network Coding Games: Efficiency and Min-Max Bargaining Solution,0769f49a69f3d7e0c6d89d0918096dfd,https://ieeexplore.ieee.org/document/6565417/
7855,"Recent results have shown that selfish users do not have an incentive to participate in intersession network coding in a static noncooperative game setting. Because of this, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 20%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be improved to 36%. We design a grim-trigger strategy that encourages users to cooperate and participate in the intersession network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We resolve the conflict of interest among the users through a bargaining process and obtain tight upper bounds for the price-of-anarchy that are valid for any possible bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve these upper bounds, as confirmed through simulation studies. The coexistence of multiple selfish network coding sessions as well as the coexistence of selfish network coding and routing sessions are also investigated. Our results represent a first step toward designing practical intersession network coding schemes that achieve reasonable performance for selfish users.",hamed mohsenian-rad,network coding,2014.0,10.1109/TNET.2013.2271038,IEEE/ACM Transactions on Networking,Mohsenian-Rad2014,False,,IEEE,Not available,Repeated Intersession Network Coding Games: Efficiency and Min-Max Bargaining Solution,0769f49a69f3d7e0c6d89d0918096dfd,https://ieeexplore.ieee.org/document/6565417/
7856,"Recent results have shown that selfish users do not have an incentive to participate in intersession network coding in a static noncooperative game setting. Because of this, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 20%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be improved to 36%. We design a grim-trigger strategy that encourages users to cooperate and participate in the intersession network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We resolve the conflict of interest among the users through a bargaining process and obtain tight upper bounds for the price-of-anarchy that are valid for any possible bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve these upper bounds, as confirmed through simulation studies. The coexistence of multiple selfish network coding sessions as well as the coexistence of selfish network coding and routing sessions are also investigated. Our results represent a first step toward designing practical intersession network coding schemes that achieve reasonable performance for selfish users.",hamed mohsenian-rad,repeated game theory,2014.0,10.1109/TNET.2013.2271038,IEEE/ACM Transactions on Networking,Mohsenian-Rad2014,False,,IEEE,Not available,Repeated Intersession Network Coding Games: Efficiency and Min-Max Bargaining Solution,0769f49a69f3d7e0c6d89d0918096dfd,https://ieeexplore.ieee.org/document/6565417/
7857,"Recent results have shown that selfish users do not have an incentive to participate in intersession network coding in a static noncooperative game setting. Because of this, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 20%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be improved to 36%. We design a grim-trigger strategy that encourages users to cooperate and participate in the intersession network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We resolve the conflict of interest among the users through a bargaining process and obtain tight upper bounds for the price-of-anarchy that are valid for any possible bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve these upper bounds, as confirmed through simulation studies. The coexistence of multiple selfish network coding sessions as well as the coexistence of selfish network coding and routing sessions are also investigated. Our results represent a first step toward designing practical intersession network coding schemes that achieve reasonable performance for selfish users.",hamed mohsenian-rad,resource management,2014.0,10.1109/TNET.2013.2271038,IEEE/ACM Transactions on Networking,Mohsenian-Rad2014,False,,IEEE,Not available,Repeated Intersession Network Coding Games: Efficiency and Min-Max Bargaining Solution,0769f49a69f3d7e0c6d89d0918096dfd,https://ieeexplore.ieee.org/document/6565417/
7858,"Recent results have shown that selfish users do not have an incentive to participate in intersession network coding in a static noncooperative game setting. Because of this, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 20%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be improved to 36%. We design a grim-trigger strategy that encourages users to cooperate and participate in the intersession network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We resolve the conflict of interest among the users through a bargaining process and obtain tight upper bounds for the price-of-anarchy that are valid for any possible bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve these upper bounds, as confirmed through simulation studies. The coexistence of multiple selfish network coding sessions as well as the coexistence of selfish network coding and routing sessions are also investigated. Our results represent a first step toward designing practical intersession network coding schemes that achieve reasonable performance for selfish users.",jianwei huang,Min-max bargaining solution,2014.0,10.1109/TNET.2013.2271038,IEEE/ACM Transactions on Networking,Mohsenian-Rad2014,False,,IEEE,Not available,Repeated Intersession Network Coding Games: Efficiency and Min-Max Bargaining Solution,0769f49a69f3d7e0c6d89d0918096dfd,https://ieeexplore.ieee.org/document/6565417/
7859,"Recent results have shown that selfish users do not have an incentive to participate in intersession network coding in a static noncooperative game setting. Because of this, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 20%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be improved to 36%. We design a grim-trigger strategy that encourages users to cooperate and participate in the intersession network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We resolve the conflict of interest among the users through a bargaining process and obtain tight upper bounds for the price-of-anarchy that are valid for any possible bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve these upper bounds, as confirmed through simulation studies. The coexistence of multiple selfish network coding sessions as well as the coexistence of selfish network coding and routing sessions are also investigated. Our results represent a first step toward designing practical intersession network coding schemes that achieve reasonable performance for selfish users.",jianwei huang,network coding,2014.0,10.1109/TNET.2013.2271038,IEEE/ACM Transactions on Networking,Mohsenian-Rad2014,False,,IEEE,Not available,Repeated Intersession Network Coding Games: Efficiency and Min-Max Bargaining Solution,0769f49a69f3d7e0c6d89d0918096dfd,https://ieeexplore.ieee.org/document/6565417/
7860,"Recent results have shown that selfish users do not have an incentive to participate in intersession network coding in a static noncooperative game setting. Because of this, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 20%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be improved to 36%. We design a grim-trigger strategy that encourages users to cooperate and participate in the intersession network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We resolve the conflict of interest among the users through a bargaining process and obtain tight upper bounds for the price-of-anarchy that are valid for any possible bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve these upper bounds, as confirmed through simulation studies. The coexistence of multiple selfish network coding sessions as well as the coexistence of selfish network coding and routing sessions are also investigated. Our results represent a first step toward designing practical intersession network coding schemes that achieve reasonable performance for selfish users.",jianwei huang,repeated game theory,2014.0,10.1109/TNET.2013.2271038,IEEE/ACM Transactions on Networking,Mohsenian-Rad2014,False,,IEEE,Not available,Repeated Intersession Network Coding Games: Efficiency and Min-Max Bargaining Solution,0769f49a69f3d7e0c6d89d0918096dfd,https://ieeexplore.ieee.org/document/6565417/
7861,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
7862,"Recent results have shown that selfish users do not have an incentive to participate in intersession network coding in a static noncooperative game setting. Because of this, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 20%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be improved to 36%. We design a grim-trigger strategy that encourages users to cooperate and participate in the intersession network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We resolve the conflict of interest among the users through a bargaining process and obtain tight upper bounds for the price-of-anarchy that are valid for any possible bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve these upper bounds, as confirmed through simulation studies. The coexistence of multiple selfish network coding sessions as well as the coexistence of selfish network coding and routing sessions are also investigated. Our results represent a first step toward designing practical intersession network coding schemes that achieve reasonable performance for selfish users.",jianwei huang,resource management,2014.0,10.1109/TNET.2013.2271038,IEEE/ACM Transactions on Networking,Mohsenian-Rad2014,False,,IEEE,Not available,Repeated Intersession Network Coding Games: Efficiency and Min-Max Bargaining Solution,0769f49a69f3d7e0c6d89d0918096dfd,https://ieeexplore.ieee.org/document/6565417/
7863,"Recent results have shown that selfish users do not have an incentive to participate in intersession network coding in a static noncooperative game setting. Because of this, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 20%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be improved to 36%. We design a grim-trigger strategy that encourages users to cooperate and participate in the intersession network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We resolve the conflict of interest among the users through a bargaining process and obtain tight upper bounds for the price-of-anarchy that are valid for any possible bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve these upper bounds, as confirmed through simulation studies. The coexistence of multiple selfish network coding sessions as well as the coexistence of selfish network coding and routing sessions are also investigated. Our results represent a first step toward designing practical intersession network coding schemes that achieve reasonable performance for selfish users.",vincent wong,Min-max bargaining solution,2014.0,10.1109/TNET.2013.2271038,IEEE/ACM Transactions on Networking,Mohsenian-Rad2014,False,,IEEE,Not available,Repeated Intersession Network Coding Games: Efficiency and Min-Max Bargaining Solution,0769f49a69f3d7e0c6d89d0918096dfd,https://ieeexplore.ieee.org/document/6565417/
7864,"Recent results have shown that selfish users do not have an incentive to participate in intersession network coding in a static noncooperative game setting. Because of this, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 20%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be improved to 36%. We design a grim-trigger strategy that encourages users to cooperate and participate in the intersession network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We resolve the conflict of interest among the users through a bargaining process and obtain tight upper bounds for the price-of-anarchy that are valid for any possible bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve these upper bounds, as confirmed through simulation studies. The coexistence of multiple selfish network coding sessions as well as the coexistence of selfish network coding and routing sessions are also investigated. Our results represent a first step toward designing practical intersession network coding schemes that achieve reasonable performance for selfish users.",vincent wong,network coding,2014.0,10.1109/TNET.2013.2271038,IEEE/ACM Transactions on Networking,Mohsenian-Rad2014,False,,IEEE,Not available,Repeated Intersession Network Coding Games: Efficiency and Min-Max Bargaining Solution,0769f49a69f3d7e0c6d89d0918096dfd,https://ieeexplore.ieee.org/document/6565417/
7865,"Recent results have shown that selfish users do not have an incentive to participate in intersession network coding in a static noncooperative game setting. Because of this, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 20%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be improved to 36%. We design a grim-trigger strategy that encourages users to cooperate and participate in the intersession network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We resolve the conflict of interest among the users through a bargaining process and obtain tight upper bounds for the price-of-anarchy that are valid for any possible bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve these upper bounds, as confirmed through simulation studies. The coexistence of multiple selfish network coding sessions as well as the coexistence of selfish network coding and routing sessions are also investigated. Our results represent a first step toward designing practical intersession network coding schemes that achieve reasonable performance for selfish users.",vincent wong,repeated game theory,2014.0,10.1109/TNET.2013.2271038,IEEE/ACM Transactions on Networking,Mohsenian-Rad2014,False,,IEEE,Not available,Repeated Intersession Network Coding Games: Efficiency and Min-Max Bargaining Solution,0769f49a69f3d7e0c6d89d0918096dfd,https://ieeexplore.ieee.org/document/6565417/
7866,"Recent results have shown that selfish users do not have an incentive to participate in intersession network coding in a static noncooperative game setting. Because of this, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 20%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be improved to 36%. We design a grim-trigger strategy that encourages users to cooperate and participate in the intersession network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We resolve the conflict of interest among the users through a bargaining process and obtain tight upper bounds for the price-of-anarchy that are valid for any possible bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve these upper bounds, as confirmed through simulation studies. The coexistence of multiple selfish network coding sessions as well as the coexistence of selfish network coding and routing sessions are also investigated. Our results represent a first step toward designing practical intersession network coding schemes that achieve reasonable performance for selfish users.",vincent wong,resource management,2014.0,10.1109/TNET.2013.2271038,IEEE/ACM Transactions on Networking,Mohsenian-Rad2014,False,,IEEE,Not available,Repeated Intersession Network Coding Games: Efficiency and Min-Max Bargaining Solution,0769f49a69f3d7e0c6d89d0918096dfd,https://ieeexplore.ieee.org/document/6565417/
7867,"Recent results have shown that selfish users do not have an incentive to participate in intersession network coding in a static noncooperative game setting. Because of this, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 20%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be improved to 36%. We design a grim-trigger strategy that encourages users to cooperate and participate in the intersession network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We resolve the conflict of interest among the users through a bargaining process and obtain tight upper bounds for the price-of-anarchy that are valid for any possible bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve these upper bounds, as confirmed through simulation studies. The coexistence of multiple selfish network coding sessions as well as the coexistence of selfish network coding and routing sessions are also investigated. Our results represent a first step toward designing practical intersession network coding schemes that achieve reasonable performance for selfish users.",robert schober,Min-max bargaining solution,2014.0,10.1109/TNET.2013.2271038,IEEE/ACM Transactions on Networking,Mohsenian-Rad2014,False,,IEEE,Not available,Repeated Intersession Network Coding Games: Efficiency and Min-Max Bargaining Solution,0769f49a69f3d7e0c6d89d0918096dfd,https://ieeexplore.ieee.org/document/6565417/
7868,"Recent results have shown that selfish users do not have an incentive to participate in intersession network coding in a static noncooperative game setting. Because of this, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 20%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be improved to 36%. We design a grim-trigger strategy that encourages users to cooperate and participate in the intersession network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We resolve the conflict of interest among the users through a bargaining process and obtain tight upper bounds for the price-of-anarchy that are valid for any possible bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve these upper bounds, as confirmed through simulation studies. The coexistence of multiple selfish network coding sessions as well as the coexistence of selfish network coding and routing sessions are also investigated. Our results represent a first step toward designing practical intersession network coding schemes that achieve reasonable performance for selfish users.",robert schober,network coding,2014.0,10.1109/TNET.2013.2271038,IEEE/ACM Transactions on Networking,Mohsenian-Rad2014,False,,IEEE,Not available,Repeated Intersession Network Coding Games: Efficiency and Min-Max Bargaining Solution,0769f49a69f3d7e0c6d89d0918096dfd,https://ieeexplore.ieee.org/document/6565417/
7869,"Recent results have shown that selfish users do not have an incentive to participate in intersession network coding in a static noncooperative game setting. Because of this, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 20%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be improved to 36%. We design a grim-trigger strategy that encourages users to cooperate and participate in the intersession network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We resolve the conflict of interest among the users through a bargaining process and obtain tight upper bounds for the price-of-anarchy that are valid for any possible bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve these upper bounds, as confirmed through simulation studies. The coexistence of multiple selfish network coding sessions as well as the coexistence of selfish network coding and routing sessions are also investigated. Our results represent a first step toward designing practical intersession network coding schemes that achieve reasonable performance for selfish users.",robert schober,repeated game theory,2014.0,10.1109/TNET.2013.2271038,IEEE/ACM Transactions on Networking,Mohsenian-Rad2014,False,,IEEE,Not available,Repeated Intersession Network Coding Games: Efficiency and Min-Max Bargaining Solution,0769f49a69f3d7e0c6d89d0918096dfd,https://ieeexplore.ieee.org/document/6565417/
7870,"Recent results have shown that selfish users do not have an incentive to participate in intersession network coding in a static noncooperative game setting. Because of this, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 20%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be improved to 36%. We design a grim-trigger strategy that encourages users to cooperate and participate in the intersession network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We resolve the conflict of interest among the users through a bargaining process and obtain tight upper bounds for the price-of-anarchy that are valid for any possible bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve these upper bounds, as confirmed through simulation studies. The coexistence of multiple selfish network coding sessions as well as the coexistence of selfish network coding and routing sessions are also investigated. Our results represent a first step toward designing practical intersession network coding schemes that achieve reasonable performance for selfish users.",robert schober,resource management,2014.0,10.1109/TNET.2013.2271038,IEEE/ACM Transactions on Networking,Mohsenian-Rad2014,False,,IEEE,Not available,Repeated Intersession Network Coding Games: Efficiency and Min-Max Bargaining Solution,0769f49a69f3d7e0c6d89d0918096dfd,https://ieeexplore.ieee.org/document/6565417/
7871,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",m.x. goemans,Mobile ad hoc networks,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
7872,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
7873,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",m.x. goemans,Nash equilibrium,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
7874,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",m.x. goemans,price of anarchy,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
7875,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",m.x. goemans,third-generation (3G) wireless networks,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
7876,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",m.x. goemans,unified architecture,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
7877,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",li li,Mobile ad hoc networks,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
7878,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",li li,Nash equilibrium,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
7879,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",li li,price of anarchy,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
7880,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",li li,third-generation (3G) wireless networks,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
7881,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",li li,unified architecture,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
7882,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",v.s. mirrokni,Mobile ad hoc networks,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
7883,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
7884,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
7885,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",v.s. mirrokni,Nash equilibrium,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
7886,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",v.s. mirrokni,price of anarchy,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
7887,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",v.s. mirrokni,third-generation (3G) wireless networks,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
7888,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",v.s. mirrokni,unified architecture,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
7889,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",m. thottan,Mobile ad hoc networks,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
7890,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",m. thottan,Nash equilibrium,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
7891,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",m. thottan,price of anarchy,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
7892,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",m. thottan,third-generation (3G) wireless networks,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
7893,"In third-generation (3G) wireless data networks, repeated requests for popular data items can exacerbate the already scarce wireless spectrum. In this paper, we propose an architectural and protocol framework that allows 3G service providers to host efficient content distribution services. We offload the spectrum intensive task of content distribution to an ad hoc network. Less mobile users (resident subscribers) are provided incentives to cache popular data items, while mobile users (transit subscribers) access this data from resident subscribers through the ad hoc network. Since the participants of this data distribution network act as selfish agents, they may collude to maximize their individual payoff. Our proposed protocol discourages potential collusion scenarios. In this architecture, the goal (social function) of the 3G service provider is to have the selfishly motivated resident subscribers service as many data requests as possible. However, the choice of which set of items to cache is left to the individual user. The caching activity among the different users can be modeled as a market sharing game. In this work, we study the Nash equilibria of market sharing games and the performance of such equilibria in terms of a social function. These games are a special case of congestion games that have been studied in the economics literature. In particular, pure strategy Nash equilibria for this set of games exist. We give a polynomial-time algorithm to find a pure strategy Nash equilibrium for a special case, while it is NP-hard to do so in the general case. As for the performance of Nash equilibria, we show that the price of anarchy-the worst case ratio between the social function at any Nash equilibrium and at the social optimum-can be upper bounded by a factor of 2. When the popularity follows a Zipf distribution, the price of anarchy is bounded by 1.45 in the special case where caching any item has a positive reward for all players. We prove that the selfish behavior of computationally bounded agents converges to an approximate Nash equilibrium in a finite number of improvements. Furthermore, we prove that, after each agent computes its response function once using a constant factor approximation algorithm, the outcome of the game is within a factor of O(logn) of the optimal social value, where n is the number of agents. Our simulation scenarios show that the price of anarchy is 30% better than that of the worst case analysis and that the system quickly (1 or 2 steps) converges to a Nash equilibrium.",m. thottan,unified architecture,2006.0,10.1109/JSAC.2006.872884,IEEE Journal on Selected Areas in Communications,Goemans2006,False,,IEEE,Not available,Market sharing games applied to content distribution in ad hoc networks,3b85fe84d381e831de5533eb1e5faf44,https://ieeexplore.ieee.org/document/1626428/
7894,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",j. doncel,Servers,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
7895,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
7896,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",j. doncel,Routing,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
7897,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",j. doncel,Games,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
7898,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",j. doncel,Nash equilibrium,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
7899,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",j. doncel,Vectors,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
7900,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",j. doncel,Optimization,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
7901,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",j. doncel,Computer architecture,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
7902,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",u. ayesta,Servers,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
7903,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",u. ayesta,Routing,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
7904,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",u. ayesta,Games,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
7905,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",u. ayesta,Nash equilibrium,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
7906,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
7907,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",u. ayesta,Vectors,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
7908,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",u. ayesta,Optimization,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
7909,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",u. ayesta,Computer architecture,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
7910,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",o. brun,Servers,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
7911,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",o. brun,Routing,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
7912,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",o. brun,Games,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
7913,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",o. brun,Nash equilibrium,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
7914,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",o. brun,Vectors,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
7915,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",o. brun,Optimization,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
7916,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",o. brun,Computer architecture,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
7917,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
7918,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",b.j. prabhu,Servers,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
7919,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",b.j. prabhu,Routing,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
7920,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",b.j. prabhu,Games,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
7921,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",b.j. prabhu,Nash equilibrium,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
7922,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",b.j. prabhu,Vectors,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
7923,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",b.j. prabhu,Optimization,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
7924,"Price of Anarchy is an oft-used worst-case measure of the inefficiency of non-cooperative decentralized architectures. In practice, though, the worst-case scenario may occur rarely, if at all. For non-cooperative decentralized load-balancing in server farms, we show that the Price of Anarchy is an overly pessimistic measure that does not reflect the performance obtained in most instances of the problem. In the case of two classes of servers, we show that non-cooperative load-balancing provides a close-to-optimal solution in most cases, and that the worst-case performance given by the Price of Anarchy occurs only in a very specific setting, namely, when the slower servers are infinitely more numerous and infinitely slower than the faster ones. We explicitly characterize the worst-case traffic conditions for the efficiency of non-cooperative load-balancing schemes, and show that, contrary to a common belief, the worst inefficiency is in general not achieved in heavy-traffic or close to saturation conditions.",b.j. prabhu,Computer architecture,2013.0,,2013 IFIP Networking Conference,Doncel2013,False,,IEEE,Not available,On the efficiency of non-cooperative load balancing,2beca193692e057472060fa806266079,https://ieeexplore.ieee.org/document/6663492/
7925,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",amir-hamed mohsenian-rad,Network coding,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7926,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",amir-hamed mohsenian-rad,Upper bound,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7927,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",amir-hamed mohsenian-rad,Communications Society,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7928,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
7929,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",amir-hamed mohsenian-rad,Design engineering,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7930,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",amir-hamed mohsenian-rad,Electronic mail,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7931,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",amir-hamed mohsenian-rad,Wireless networks,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7932,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",amir-hamed mohsenian-rad,Encoding,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7933,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",amir-hamed mohsenian-rad,Unicast,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7934,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",amir-hamed mohsenian-rad,Decoding,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7935,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",amir-hamed mohsenian-rad,Nash equilibrium,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7936,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",jianwei huang,Network coding,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7937,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",jianwei huang,Upper bound,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7938,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",jianwei huang,Communications Society,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7939,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
7940,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",jianwei huang,Design engineering,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7941,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",jianwei huang,Electronic mail,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7942,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",jianwei huang,Wireless networks,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7943,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",jianwei huang,Encoding,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7944,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",jianwei huang,Unicast,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7945,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",jianwei huang,Decoding,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7946,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",jianwei huang,Nash equilibrium,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7947,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",vincent wong,Network coding,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7948,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",vincent wong,Upper bound,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7949,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",vincent wong,Communications Society,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7950,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
7951,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",vincent wong,Design engineering,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7952,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",vincent wong,Electronic mail,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7953,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",vincent wong,Wireless networks,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7954,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",vincent wong,Encoding,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7955,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",vincent wong,Unicast,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7956,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",vincent wong,Decoding,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7957,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",vincent wong,Nash equilibrium,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7958,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",robert schober,Network coding,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7959,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",robert schober,Upper bound,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7960,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",robert schober,Communications Society,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7961,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
7962,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",robert schober,Design engineering,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7963,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",robert schober,Electronic mail,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7964,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",robert schober,Wireless networks,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7965,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",robert schober,Encoding,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7966,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",robert schober,Unicast,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7967,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",robert schober,Decoding,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7968,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",robert schober,Nash equilibrium,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
7969,"We will present recent work on the resilience and risk of failure emerging in cyber-physical infrastructures such as smart transportation systems and the smart grid. In the first part of the talk, we present results on the volatility and risk of failure associated with real-time response in the future smart grid. Real-time demand response has been postulated as the solution to the intermittency problem created by renewable generation. The proposed market architecture is simple, namely, consumers react directly to spot market prices in order to fulfill their demands. This mechanism creates a closed loop system between price and demand that has implications on efficiency, demand and price volatility, and risk of demand spikes. In this talk, we first present an analysis of this closed loop system for homogeneous consumers and highlight the tradeoffs between market efficiency and demand and price volatility. Then, we present an abstracted framework to analyze the tradeoffs between efficiency and risk for heterogeneous consumers in the presence of shiftable demands. In this context, we expand the market mechanism to study the impact of coordination on such a tradeoff. We show that although the non-cooperative load-shifting scheme leads to an efficiency loss (otherwise known as the price of anarchy), the scheme has a smaller tail probability of the aggregate unshiftable demand distribution than cooperative schemes. This tail distribution is important as it corresponds to rare and undesirable demand spikes. Such instances highlight the role of the market mechanisms in striking a balance between efficiency and risk in real-time markets. In the second part of the talk, we present results on the robustness (resilience) properticlosedes of transportation networks for various agents' route-choice behavior. We perform the analysis within a dynamical system framework over a directed acyclic graph between a single origin-destination pair. We give a precise characterization of various margins of resilience of the network with respect to the topology, `pre-disturbance' equilibrium, and agents' local route-choice behavior. We show that the cooperative route choice behavior is maximally resilient in this setting. We also setup a simple convex optimization problem to find the most resilient `pre-disturbance' equilibrium for the network and determine link-wise tolls that yield such an equilibrium. Finally, we extend the analysis to link-wise outflow functions that accommodate the possibility of cascaded failures and study the effect of such phenomena on the margins of resilience of the network.",munther dahleh,Resilience,2014.0,10.1109/MED.2014.6961439,22nd Mediterranean Conference on Control and Automation,Dahleh2014,False,,IEEE,Not available,Plenary talk: Resilience and risk in networked systems,d54786112c97b8c2b879ee53c7b69094,https://ieeexplore.ieee.org/document/6961439/
7970,"We will present recent work on the resilience and risk of failure emerging in cyber-physical infrastructures such as smart transportation systems and the smart grid. In the first part of the talk, we present results on the volatility and risk of failure associated with real-time response in the future smart grid. Real-time demand response has been postulated as the solution to the intermittency problem created by renewable generation. The proposed market architecture is simple, namely, consumers react directly to spot market prices in order to fulfill their demands. This mechanism creates a closed loop system between price and demand that has implications on efficiency, demand and price volatility, and risk of demand spikes. In this talk, we first present an analysis of this closed loop system for homogeneous consumers and highlight the tradeoffs between market efficiency and demand and price volatility. Then, we present an abstracted framework to analyze the tradeoffs between efficiency and risk for heterogeneous consumers in the presence of shiftable demands. In this context, we expand the market mechanism to study the impact of coordination on such a tradeoff. We show that although the non-cooperative load-shifting scheme leads to an efficiency loss (otherwise known as the price of anarchy), the scheme has a smaller tail probability of the aggregate unshiftable demand distribution than cooperative schemes. This tail distribution is important as it corresponds to rare and undesirable demand spikes. Such instances highlight the role of the market mechanisms in striking a balance between efficiency and risk in real-time markets. In the second part of the talk, we present results on the robustness (resilience) properticlosedes of transportation networks for various agents' route-choice behavior. We perform the analysis within a dynamical system framework over a directed acyclic graph between a single origin-destination pair. We give a precise characterization of various margins of resilience of the network with respect to the topology, `pre-disturbance' equilibrium, and agents' local route-choice behavior. We show that the cooperative route choice behavior is maximally resilient in this setting. We also setup a simple convex optimization problem to find the most resilient `pre-disturbance' equilibrium for the network and determine link-wise tolls that yield such an equilibrium. Finally, we extend the analysis to link-wise outflow functions that accommodate the possibility of cascaded failures and study the effect of such phenomena on the margins of resilience of the network.",munther dahleh,Real-time systems,2014.0,10.1109/MED.2014.6961439,22nd Mediterranean Conference on Control and Automation,Dahleh2014,False,,IEEE,Not available,Plenary talk: Resilience and risk in networked systems,d54786112c97b8c2b879ee53c7b69094,https://ieeexplore.ieee.org/document/6961439/
7971,"We will present recent work on the resilience and risk of failure emerging in cyber-physical infrastructures such as smart transportation systems and the smart grid. In the first part of the talk, we present results on the volatility and risk of failure associated with real-time response in the future smart grid. Real-time demand response has been postulated as the solution to the intermittency problem created by renewable generation. The proposed market architecture is simple, namely, consumers react directly to spot market prices in order to fulfill their demands. This mechanism creates a closed loop system between price and demand that has implications on efficiency, demand and price volatility, and risk of demand spikes. In this talk, we first present an analysis of this closed loop system for homogeneous consumers and highlight the tradeoffs between market efficiency and demand and price volatility. Then, we present an abstracted framework to analyze the tradeoffs between efficiency and risk for heterogeneous consumers in the presence of shiftable demands. In this context, we expand the market mechanism to study the impact of coordination on such a tradeoff. We show that although the non-cooperative load-shifting scheme leads to an efficiency loss (otherwise known as the price of anarchy), the scheme has a smaller tail probability of the aggregate unshiftable demand distribution than cooperative schemes. This tail distribution is important as it corresponds to rare and undesirable demand spikes. Such instances highlight the role of the market mechanisms in striking a balance between efficiency and risk in real-time markets. In the second part of the talk, we present results on the robustness (resilience) properticlosedes of transportation networks for various agents' route-choice behavior. We perform the analysis within a dynamical system framework over a directed acyclic graph between a single origin-destination pair. We give a precise characterization of various margins of resilience of the network with respect to the topology, `pre-disturbance' equilibrium, and agents' local route-choice behavior. We show that the cooperative route choice behavior is maximally resilient in this setting. We also setup a simple convex optimization problem to find the most resilient `pre-disturbance' equilibrium for the network and determine link-wise tolls that yield such an equilibrium. Finally, we extend the analysis to link-wise outflow functions that accommodate the possibility of cascaded failures and study the effect of such phenomena on the margins of resilience of the network.",munther dahleh,Transportation,2014.0,10.1109/MED.2014.6961439,22nd Mediterranean Conference on Control and Automation,Dahleh2014,False,,IEEE,Not available,Plenary talk: Resilience and risk in networked systems,d54786112c97b8c2b879ee53c7b69094,https://ieeexplore.ieee.org/document/6961439/
7972,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
7973,"We will present recent work on the resilience and risk of failure emerging in cyber-physical infrastructures such as smart transportation systems and the smart grid. In the first part of the talk, we present results on the volatility and risk of failure associated with real-time response in the future smart grid. Real-time demand response has been postulated as the solution to the intermittency problem created by renewable generation. The proposed market architecture is simple, namely, consumers react directly to spot market prices in order to fulfill their demands. This mechanism creates a closed loop system between price and demand that has implications on efficiency, demand and price volatility, and risk of demand spikes. In this talk, we first present an analysis of this closed loop system for homogeneous consumers and highlight the tradeoffs between market efficiency and demand and price volatility. Then, we present an abstracted framework to analyze the tradeoffs between efficiency and risk for heterogeneous consumers in the presence of shiftable demands. In this context, we expand the market mechanism to study the impact of coordination on such a tradeoff. We show that although the non-cooperative load-shifting scheme leads to an efficiency loss (otherwise known as the price of anarchy), the scheme has a smaller tail probability of the aggregate unshiftable demand distribution than cooperative schemes. This tail distribution is important as it corresponds to rare and undesirable demand spikes. Such instances highlight the role of the market mechanisms in striking a balance between efficiency and risk in real-time markets. In the second part of the talk, we present results on the robustness (resilience) properticlosedes of transportation networks for various agents' route-choice behavior. We perform the analysis within a dynamical system framework over a directed acyclic graph between a single origin-destination pair. We give a precise characterization of various margins of resilience of the network with respect to the topology, `pre-disturbance' equilibrium, and agents' local route-choice behavior. We show that the cooperative route choice behavior is maximally resilient in this setting. We also setup a simple convex optimization problem to find the most resilient `pre-disturbance' equilibrium for the network and determine link-wise tolls that yield such an equilibrium. Finally, we extend the analysis to link-wise outflow functions that accommodate the possibility of cascaded failures and study the effect of such phenomena on the margins of resilience of the network.",munther dahleh,Smart grids,2014.0,10.1109/MED.2014.6961439,22nd Mediterranean Conference on Control and Automation,Dahleh2014,False,,IEEE,Not available,Plenary talk: Resilience and risk in networked systems,d54786112c97b8c2b879ee53c7b69094,https://ieeexplore.ieee.org/document/6961439/
7974,"We will present recent work on the resilience and risk of failure emerging in cyber-physical infrastructures such as smart transportation systems and the smart grid. In the first part of the talk, we present results on the volatility and risk of failure associated with real-time response in the future smart grid. Real-time demand response has been postulated as the solution to the intermittency problem created by renewable generation. The proposed market architecture is simple, namely, consumers react directly to spot market prices in order to fulfill their demands. This mechanism creates a closed loop system between price and demand that has implications on efficiency, demand and price volatility, and risk of demand spikes. In this talk, we first present an analysis of this closed loop system for homogeneous consumers and highlight the tradeoffs between market efficiency and demand and price volatility. Then, we present an abstracted framework to analyze the tradeoffs between efficiency and risk for heterogeneous consumers in the presence of shiftable demands. In this context, we expand the market mechanism to study the impact of coordination on such a tradeoff. We show that although the non-cooperative load-shifting scheme leads to an efficiency loss (otherwise known as the price of anarchy), the scheme has a smaller tail probability of the aggregate unshiftable demand distribution than cooperative schemes. This tail distribution is important as it corresponds to rare and undesirable demand spikes. Such instances highlight the role of the market mechanisms in striking a balance between efficiency and risk in real-time markets. In the second part of the talk, we present results on the robustness (resilience) properticlosedes of transportation networks for various agents' route-choice behavior. We perform the analysis within a dynamical system framework over a directed acyclic graph between a single origin-destination pair. We give a precise characterization of various margins of resilience of the network with respect to the topology, `pre-disturbance' equilibrium, and agents' local route-choice behavior. We show that the cooperative route choice behavior is maximally resilient in this setting. We also setup a simple convex optimization problem to find the most resilient `pre-disturbance' equilibrium for the network and determine link-wise tolls that yield such an equilibrium. Finally, we extend the analysis to link-wise outflow functions that accommodate the possibility of cascaded failures and study the effect of such phenomena on the margins of resilience of the network.",munther dahleh,Closed loop systems,2014.0,10.1109/MED.2014.6961439,22nd Mediterranean Conference on Control and Automation,Dahleh2014,False,,IEEE,Not available,Plenary talk: Resilience and risk in networked systems,d54786112c97b8c2b879ee53c7b69094,https://ieeexplore.ieee.org/document/6961439/
7975,"We will present recent work on the resilience and risk of failure emerging in cyber-physical infrastructures such as smart transportation systems and the smart grid. In the first part of the talk, we present results on the volatility and risk of failure associated with real-time response in the future smart grid. Real-time demand response has been postulated as the solution to the intermittency problem created by renewable generation. The proposed market architecture is simple, namely, consumers react directly to spot market prices in order to fulfill their demands. This mechanism creates a closed loop system between price and demand that has implications on efficiency, demand and price volatility, and risk of demand spikes. In this talk, we first present an analysis of this closed loop system for homogeneous consumers and highlight the tradeoffs between market efficiency and demand and price volatility. Then, we present an abstracted framework to analyze the tradeoffs between efficiency and risk for heterogeneous consumers in the presence of shiftable demands. In this context, we expand the market mechanism to study the impact of coordination on such a tradeoff. We show that although the non-cooperative load-shifting scheme leads to an efficiency loss (otherwise known as the price of anarchy), the scheme has a smaller tail probability of the aggregate unshiftable demand distribution than cooperative schemes. This tail distribution is important as it corresponds to rare and undesirable demand spikes. Such instances highlight the role of the market mechanisms in striking a balance between efficiency and risk in real-time markets. In the second part of the talk, we present results on the robustness (resilience) properticlosedes of transportation networks for various agents' route-choice behavior. We perform the analysis within a dynamical system framework over a directed acyclic graph between a single origin-destination pair. We give a precise characterization of various margins of resilience of the network with respect to the topology, `pre-disturbance' equilibrium, and agents' local route-choice behavior. We show that the cooperative route choice behavior is maximally resilient in this setting. We also setup a simple convex optimization problem to find the most resilient `pre-disturbance' equilibrium for the network and determine link-wise tolls that yield such an equilibrium. Finally, we extend the analysis to link-wise outflow functions that accommodate the possibility of cascaded failures and study the effect of such phenomena on the margins of resilience of the network.",munther dahleh,Automation,2014.0,10.1109/MED.2014.6961439,22nd Mediterranean Conference on Control and Automation,Dahleh2014,False,,IEEE,Not available,Plenary talk: Resilience and risk in networked systems,d54786112c97b8c2b879ee53c7b69094,https://ieeexplore.ieee.org/document/6961439/
7976,"We will present recent work on the resilience and risk of failure emerging in cyber-physical infrastructures such as smart transportation systems and the smart grid. In the first part of the talk, we present results on the volatility and risk of failure associated with real-time response in the future smart grid. Real-time demand response has been postulated as the solution to the intermittency problem created by renewable generation. The proposed market architecture is simple, namely, consumers react directly to spot market prices in order to fulfill their demands. This mechanism creates a closed loop system between price and demand that has implications on efficiency, demand and price volatility, and risk of demand spikes. In this talk, we first present an analysis of this closed loop system for homogeneous consumers and highlight the tradeoffs between market efficiency and demand and price volatility. Then, we present an abstracted framework to analyze the tradeoffs between efficiency and risk for heterogeneous consumers in the presence of shiftable demands. In this context, we expand the market mechanism to study the impact of coordination on such a tradeoff. We show that although the non-cooperative load-shifting scheme leads to an efficiency loss (otherwise known as the price of anarchy), the scheme has a smaller tail probability of the aggregate unshiftable demand distribution than cooperative schemes. This tail distribution is important as it corresponds to rare and undesirable demand spikes. Such instances highlight the role of the market mechanisms in striking a balance between efficiency and risk in real-time markets. In the second part of the talk, we present results on the robustness (resilience) properticlosedes of transportation networks for various agents' route-choice behavior. We perform the analysis within a dynamical system framework over a directed acyclic graph between a single origin-destination pair. We give a precise characterization of various margins of resilience of the network with respect to the topology, `pre-disturbance' equilibrium, and agents' local route-choice behavior. We show that the cooperative route choice behavior is maximally resilient in this setting. We also setup a simple convex optimization problem to find the most resilient `pre-disturbance' equilibrium for the network and determine link-wise tolls that yield such an equilibrium. Finally, we extend the analysis to link-wise outflow functions that accommodate the possibility of cascaded failures and study the effect of such phenomena on the margins of resilience of the network.",munther dahleh,Educational institutions,2014.0,10.1109/MED.2014.6961439,22nd Mediterranean Conference on Control and Automation,Dahleh2014,False,,IEEE,Not available,Plenary talk: Resilience and risk in networked systems,d54786112c97b8c2b879ee53c7b69094,https://ieeexplore.ieee.org/document/6961439/
7977,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",jonatha anselmi,Time factors,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
7978,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",jonatha anselmi,Routing,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
7979,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",jonatha anselmi,Queueing analysis,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
7980,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",jonatha anselmi,Approximation methods,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
7981,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",jonatha anselmi,Optimization,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
7982,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",jonatha anselmi,Upper bound,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
7983,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
7984,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",jonatha anselmi,Nash equilibrium,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
7985,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",bruno gaujal,Time factors,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
7986,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",bruno gaujal,Routing,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
7987,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",bruno gaujal,Queueing analysis,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
7988,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",bruno gaujal,Approximation methods,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
7989,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",bruno gaujal,Optimization,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
7990,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",bruno gaujal,Upper bound,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
7991,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",bruno gaujal,Nash equilibrium,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
7992,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of the eta-Nash equilibria (eta-NEs), of the two-user linear deterministic interference channel with noisy channel-output feedback are characterized, with eta &gt; 0 arbitrarily small. The price of anarchy is the ratio between the sum-rate capacity and the smallest sum-rate at an eta-NE. Alternatively, the price of stability is the ratio between the sumrate capacity and the biggest sum-rate at an eta-NE. Some of the main conclusions of this work are the following: (a) When both transmitter-receiver pairs are in the low-interference regime, the PoA can be made arbitrarily close to one as eta approaches zero, subject to a particular condition. More specifically, there are scenarios in which even the worst eta-NE (in terms of sumrate) is arbitrarily close to the Pareto boundary of the capacity region. (b) The use of feedback plays a fundamental role on increasing the PoA in some interference regimes. This is basically because in these regimes, the use of feedback increases the sumcapacity, whereas the smallest sum-rate at an eta-NE remains the same as in the case without feedback. (c) The PoS is equal to one in all the interference regimes. This implies that there always exists an eta-NE in the Pareto boundary of the capacity region. The conclusions of this work reveal the relevance of jointly using equilibrium selection methods and channel-output feedback for reducing the effect of anarchical behavior of the network components in the eta-NE sum-rate of the interference channel.",victor quintero,,2017.0,,European Wireless 2017; 23th European Wireless Conference,Quintero2017,False,,IEEE,Not available,On the Efficiency of Nash Equilibria in the Interference Channel with Noisy Feedback,febabe0d38c6a9daca1d77c0d3e31318,
7993,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of the eta-Nash equilibria (eta-NEs), of the two-user linear deterministic interference channel with noisy channel-output feedback are characterized, with eta &gt; 0 arbitrarily small. The price of anarchy is the ratio between the sum-rate capacity and the smallest sum-rate at an eta-NE. Alternatively, the price of stability is the ratio between the sumrate capacity and the biggest sum-rate at an eta-NE. Some of the main conclusions of this work are the following: (a) When both transmitter-receiver pairs are in the low-interference regime, the PoA can be made arbitrarily close to one as eta approaches zero, subject to a particular condition. More specifically, there are scenarios in which even the worst eta-NE (in terms of sumrate) is arbitrarily close to the Pareto boundary of the capacity region. (b) The use of feedback plays a fundamental role on increasing the PoA in some interference regimes. This is basically because in these regimes, the use of feedback increases the sumcapacity, whereas the smallest sum-rate at an eta-NE remains the same as in the case without feedback. (c) The PoS is equal to one in all the interference regimes. This implies that there always exists an eta-NE in the Pareto boundary of the capacity region. The conclusions of this work reveal the relevance of jointly using equilibrium selection methods and channel-output feedback for reducing the effect of anarchical behavior of the network components in the eta-NE sum-rate of the interference channel.",samir perlaza,,2017.0,,European Wireless 2017; 23th European Wireless Conference,Quintero2017,False,,IEEE,Not available,On the Efficiency of Nash Equilibria in the Interference Channel with Noisy Feedback,febabe0d38c6a9daca1d77c0d3e31318,
7994,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
7995,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
7996,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of the eta-Nash equilibria (eta-NEs), of the two-user linear deterministic interference channel with noisy channel-output feedback are characterized, with eta &gt; 0 arbitrarily small. The price of anarchy is the ratio between the sum-rate capacity and the smallest sum-rate at an eta-NE. Alternatively, the price of stability is the ratio between the sumrate capacity and the biggest sum-rate at an eta-NE. Some of the main conclusions of this work are the following: (a) When both transmitter-receiver pairs are in the low-interference regime, the PoA can be made arbitrarily close to one as eta approaches zero, subject to a particular condition. More specifically, there are scenarios in which even the worst eta-NE (in terms of sumrate) is arbitrarily close to the Pareto boundary of the capacity region. (b) The use of feedback plays a fundamental role on increasing the PoA in some interference regimes. This is basically because in these regimes, the use of feedback increases the sumcapacity, whereas the smallest sum-rate at an eta-NE remains the same as in the case without feedback. (c) The PoS is equal to one in all the interference regimes. This implies that there always exists an eta-NE in the Pareto boundary of the capacity region. The conclusions of this work reveal the relevance of jointly using equilibrium selection methods and channel-output feedback for reducing the effect of anarchical behavior of the network components in the eta-NE sum-rate of the interference channel.",jean-marie gorce,,2017.0,,European Wireless 2017; 23th European Wireless Conference,Quintero2017,False,,IEEE,Not available,On the Efficiency of Nash Equilibria in the Interference Channel with Noisy Feedback,febabe0d38c6a9daca1d77c0d3e31318,
7997,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7998,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
7999,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
8000,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
8001,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
8002,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
8003,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
8004,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
8005,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
8006,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
8007,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
8008,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
8009,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
8010,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
8011,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
8012,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
8013,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
8014,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
8015,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
8016,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
8017,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
8018,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
8019,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",libin jiang,Pricing,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
8020,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",libin jiang,Bandwidth,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
8021,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",libin jiang,Traffic control,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
8022,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",libin jiang,Routing,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
8023,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",libin jiang,Telecommunication traffic,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
8024,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",libin jiang,Cost function,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
8025,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",libin jiang,Delay,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
8026,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",libin jiang,Computer science,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
8027,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",libin jiang,Communication networks,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
8028,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
8029,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",libin jiang,Cultural differences,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
8030,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",shyam parekh,Pricing,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
8031,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",shyam parekh,Bandwidth,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
8032,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",shyam parekh,Traffic control,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
8033,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",shyam parekh,Routing,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
8034,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",shyam parekh,Telecommunication traffic,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
8035,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",shyam parekh,Cost function,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
8036,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",shyam parekh,Delay,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
8037,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",shyam parekh,Computer science,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
8038,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",shyam parekh,Communication networks,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
8039,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8040,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",shyam parekh,Cultural differences,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
8041,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",jean walrand,Pricing,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
8042,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",jean walrand,Bandwidth,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
8043,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",jean walrand,Traffic control,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
8044,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",jean walrand,Routing,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
8045,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",jean walrand,Telecommunication traffic,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
8046,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",jean walrand,Cost function,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
8047,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",jean walrand,Delay,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
8048,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",jean walrand,Computer science,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
8049,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",jean walrand,Communication networks,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
8050,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8051,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",jean walrand,Cultural differences,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
8052,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",praneeth tota,Games,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
8053,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",praneeth tota,Resource management,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
8054,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",praneeth tota,Economics,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
8055,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",praneeth tota,Nash equilibrium,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
8056,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",praneeth tota,Gain measurement,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
8057,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",praneeth tota,Computer science,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
8058,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",praneeth tota,Loss measurement,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
8059,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",sanjiv kapoor,Games,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
8060,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",sanjiv kapoor,Resource management,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
8061,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8062,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",sanjiv kapoor,Economics,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
8063,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",sanjiv kapoor,Nash equilibrium,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
8064,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",sanjiv kapoor,Gain measurement,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
8065,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",sanjiv kapoor,Computer science,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
8066,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",sanjiv kapoor,Loss measurement,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
8067,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",benjamin grimmer,Games,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
8068,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",benjamin grimmer,Resource management,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
8069,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",benjamin grimmer,Economics,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
8070,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",benjamin grimmer,Nash equilibrium,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
8071,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",benjamin grimmer,Gain measurement,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
8072,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8073,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",benjamin grimmer,Computer science,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
8074,"In this paper we consider the economic efficiency of multi-tiered resource allocation bidding systems where allocations are based on monetary bids leading to a competitive congestion game model. We consider resources that are priced and proportionally divided among the users. This paper focuses on two aspects: (i) the impact of wealth and (ii) the inefficiency of Nash equilibrium. Motivated by the recent debate on Net-Neutrality we consider the impact of two distinct categories of players, one with higher endowment than the other. We define Wealth impact factor (WIF) as the measure of disparity of pay-offs between the rich and the poor when the game is at NE. Surprisingly, improving WIF requires quadratic effort by the poor players. which shows the disparity between the rich and the poor when considering multiple tiers of service. We also consider the inefficiency of Nash equilibrium that arises in resource allocation. The inefficiency of utilities achieved in Nash equilibrium, measured by the price of anarchy, has been shown to be at least 3/4 by Johari and Tsitsiklis. Since the effective utilities of the players depends on the payments, we define the social objective as a function of pay-offs and express the price of anarchy in terms of a measure that we term as the economic efficiency factor (ECF). We show show that this inefficiency can be as large as n, the number of players for linear utilities. Interestingly, for strictly concave utilities the ECF is shown to be bounded, based on the behavior of the derivatives of the utility functions.",benjamin grimmer,Loss measurement,2017.0,10.1109/ALLERTON.2017.8262807,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Tota2017,False,,IEEE,Not available,Economic inefficiency in resource allocation games,e8f06497cfa7cb5c6911b52e23d30300,https://ieeexplore.ieee.org/document/8262807/
8075,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8076,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8077,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8078,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8079,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8080,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8081,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8082,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8083,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8084,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8085,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8086,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8087,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8088,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8089,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8090,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8091,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8092,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8093,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8094,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8095,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8096,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8097,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8098,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8099,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8100,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8101,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8102,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8103,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8104,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8105,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
8106,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8107,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8108,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8109,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8110,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8111,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8112,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8113,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8114,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8115,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8116,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8117,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8118,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8119,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8120,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8121,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8122,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8123,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8124,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8125,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8126,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8127,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8128,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8129,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8130,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8131,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",m. goemans,Convergence,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
8132,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",m. goemans,Routing,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
8133,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",m. goemans,Cost function,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
8134,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",m. goemans,Steady-state,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
8135,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",m. goemans,Polynomials,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
8136,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",m. goemans,Delay,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
8137,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",m. goemans,Performance analysis,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
8138,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",m. goemans,Control systems,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
8139,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8140,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",m. goemans,Nash equilibrium,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
8141,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",m. goemans,Computer science,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
8142,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",vahab mirrokni,Convergence,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
8143,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",vahab mirrokni,Routing,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
8144,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",vahab mirrokni,Cost function,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
8145,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",vahab mirrokni,Steady-state,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
8146,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",vahab mirrokni,Polynomials,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
8147,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",vahab mirrokni,Delay,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
8148,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",vahab mirrokni,Performance analysis,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
8149,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",vahab mirrokni,Control systems,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
8150,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8151,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",vahab mirrokni,Nash equilibrium,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
8152,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",vahab mirrokni,Computer science,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
8153,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",a. vetta,Convergence,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
8154,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",a. vetta,Routing,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
8155,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",a. vetta,Cost function,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
8156,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",a. vetta,Steady-state,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
8157,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",a. vetta,Polynomials,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
8158,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",a. vetta,Delay,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
8159,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",a. vetta,Performance analysis,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
8160,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",a. vetta,Control systems,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
8161,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8162,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",a. vetta,Nash equilibrium,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
8163,"We introduce the concept of a sink equilibrium. A sink equilibrium is a strongly connected component with no outgoing arcs in the strategy profile graph associated with a game. The strategy profile graph has a vertex set induced by the set of pure strategy profiles; its arc set corresponds to transitions between strategy profiles that occur with nonzero probability. (Here our focus will just be on the special case in which the strategy profile graph is actually a best response graph; that is, its arc set corresponds exactly to best response moves that result from myopic or greedy behaviour). We argue that there is a natural convergence process to sink equilibria in games where agents use pure strategies. This leads to an alternative measure of the social cost of a lack of coordination, the price of sinking, which measures the worst case ratio between the value of a sink equilibrium and the value of the socially optimal solution. We define the value of a sink equilibrium to be the expected social value of the steady state distribution induced by a random walk on that sink. We illustrate the value of this measure in three ways. Firstly, we show that it may more accurately reflects the inefficiency of uncoordinated solutions in competitive games when the use of pure strategies is the norm. In particular, we give an example (a valid-utility game) in which the game converges to solutions which are a factor n worse than socially optimal. The price of sinking is indeed n, but the price of anarchy is close to 1. Secondly, sink equilibria always exist. Thus, even in games in which pure strategy Nash equilibria (PSNE) do not exist, we can still calculate the price of sinking. Thirdly, we show that bounding the price of sinking can have important implications for the speed of convergence to socially good solutions in games where the agents make best response moves in a random order. We present two examples to illustrate our ideas. (i) Unsplittable selfish routing (and weighted congestion games):we prove that the price of sinking for the weighted unsplittable flow version of the selfish routing problem (for bounded-degree polynomial latency functions) is at most O(2/sup 2d/ d/sup 2d + 3/). In comparison, we give instances of these games without any PSNE. Moreover, our proof technique implies fast convergence to socially good (approximate) solutions. This is in contrast to the negative result of Fabrikant, Papadimitriou, and Talwar (2004) showing the existence of exponentially long best-response paths. (ii) Valid-utility games: we show that for valid-utility games the price of sinking is at most n+1; thus the worst case price of sinking in a valid-utility game is between it and n+1. We use our proof to show fast convergence to constant factor approximate solutions in basic-utility games. In addition, we present a hardness result which shows that, in general, there might be states that are exponentially far from any sink equilibrium in valid-utility games. We prove this by showing that the problem of finding a sink equilibrium (or a PSNE) in valid-utility games is PLS-complete.",a. vetta,Computer science,2005.0,10.1109/SFCS.2005.68,46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05),Goemans2005,False,,IEEE,Not available,Sink equilibria and convergence,e6d170a2fb40c0a5124eff92298f7436,https://ieeexplore.ieee.org/document/1530709/
8164,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
8165,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
8166,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
8167,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
8168,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
8169,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
8170,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
8171,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
8172,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8173,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
8174,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
8175,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
8176,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
8177,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
8178,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
8179,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
8180,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
8181,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
8182,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
8183,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8184,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
8185,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
8186,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
8187,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
8188,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
8189,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
8190,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
8191,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
8192,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
8193,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
8194,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8195,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
8196,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
8197,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
8198,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
8199,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
8200,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
8201,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
8202,"This paper proposes to empower capacityand coverage-centric fiber-wireless (FiWi) enhanced 4G LongTerm Evolution Advanced (LTE-A) heterogeneous networks (HetNets) with computationand storage-centric mobile cloud computing to cope with the unprecedented growth of mobile data traffic. Minimizing energy consumption and maximizing revenue while offloading mobile data in such highly converged and hierarchical networks is not trivial, where multiple players (ίe., cloud service providers, macrocell and small cells, users) with multiple objectives coexist. This paper proposes a mobile data offloading framework using a noncooperative multi-level game-theoretic approach from an end-to-end perspective in the envisioned network. More specifically, we design three-level Stackelberg games, in which a single-leader multi-follower game, a multi-leader multi-follower game, and a single-leader multi-follower game are modeled in the introduced network such that individual players selfishly optimize their local payoff functions and collectively solve the large complex network-wide optimization problem. Further, we develop distributed mobile data offloading algorithms to reduce the complexity of the hierarchical games and to achieve a unique Nash equilibrium condition in each subgame. Simulation results show that by reaching the Nash equilibrium condition, the proposed solution helps minimize energy consumption, interference price, and processing cost, while maximizing revenues of the players in the envisioned network. In addition, the efficiency of the equilibria in terms of price of anarchy and price of stability is quantified for the best/worst case of the Nash equilibrium.",bhaskar rimai,Fiber-wireless (FiWi),2017.0,10.1364/JOCN.9.000601,IEEE/OSA Journal of Optical Communications and Networking,Rimai2017,False,,IEEE,Not available,Mobile data offloading in FiWi enhanced LTE-A heterogeneous networks,9e1d53a3b64be142024910ca68ac89e4,
8203,"This paper proposes to empower capacityand coverage-centric fiber-wireless (FiWi) enhanced 4G LongTerm Evolution Advanced (LTE-A) heterogeneous networks (HetNets) with computationand storage-centric mobile cloud computing to cope with the unprecedented growth of mobile data traffic. Minimizing energy consumption and maximizing revenue while offloading mobile data in such highly converged and hierarchical networks is not trivial, where multiple players (ίe., cloud service providers, macrocell and small cells, users) with multiple objectives coexist. This paper proposes a mobile data offloading framework using a noncooperative multi-level game-theoretic approach from an end-to-end perspective in the envisioned network. More specifically, we design three-level Stackelberg games, in which a single-leader multi-follower game, a multi-leader multi-follower game, and a single-leader multi-follower game are modeled in the introduced network such that individual players selfishly optimize their local payoff functions and collectively solve the large complex network-wide optimization problem. Further, we develop distributed mobile data offloading algorithms to reduce the complexity of the hierarchical games and to achieve a unique Nash equilibrium condition in each subgame. Simulation results show that by reaching the Nash equilibrium condition, the proposed solution helps minimize energy consumption, interference price, and processing cost, while maximizing revenues of the players in the envisioned network. In addition, the efficiency of the equilibria in terms of price of anarchy and price of stability is quantified for the best/worst case of the Nash equilibrium.",bhaskar rimai,Game theory,2017.0,10.1364/JOCN.9.000601,IEEE/OSA Journal of Optical Communications and Networking,Rimai2017,False,,IEEE,Not available,Mobile data offloading in FiWi enhanced LTE-A heterogeneous networks,9e1d53a3b64be142024910ca68ac89e4,
8204,"This paper proposes to empower capacityand coverage-centric fiber-wireless (FiWi) enhanced 4G LongTerm Evolution Advanced (LTE-A) heterogeneous networks (HetNets) with computationand storage-centric mobile cloud computing to cope with the unprecedented growth of mobile data traffic. Minimizing energy consumption and maximizing revenue while offloading mobile data in such highly converged and hierarchical networks is not trivial, where multiple players (ίe., cloud service providers, macrocell and small cells, users) with multiple objectives coexist. This paper proposes a mobile data offloading framework using a noncooperative multi-level game-theoretic approach from an end-to-end perspective in the envisioned network. More specifically, we design three-level Stackelberg games, in which a single-leader multi-follower game, a multi-leader multi-follower game, and a single-leader multi-follower game are modeled in the introduced network such that individual players selfishly optimize their local payoff functions and collectively solve the large complex network-wide optimization problem. Further, we develop distributed mobile data offloading algorithms to reduce the complexity of the hierarchical games and to achieve a unique Nash equilibrium condition in each subgame. Simulation results show that by reaching the Nash equilibrium condition, the proposed solution helps minimize energy consumption, interference price, and processing cost, while maximizing revenues of the players in the envisioned network. In addition, the efficiency of the equilibria in terms of price of anarchy and price of stability is quantified for the best/worst case of the Nash equilibrium.",bhaskar rimai,Heterogeneous networks,2017.0,10.1364/JOCN.9.000601,IEEE/OSA Journal of Optical Communications and Networking,Rimai2017,False,,IEEE,Not available,Mobile data offloading in FiWi enhanced LTE-A heterogeneous networks,9e1d53a3b64be142024910ca68ac89e4,
8205,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8206,"This paper proposes to empower capacityand coverage-centric fiber-wireless (FiWi) enhanced 4G LongTerm Evolution Advanced (LTE-A) heterogeneous networks (HetNets) with computationand storage-centric mobile cloud computing to cope with the unprecedented growth of mobile data traffic. Minimizing energy consumption and maximizing revenue while offloading mobile data in such highly converged and hierarchical networks is not trivial, where multiple players (ίe., cloud service providers, macrocell and small cells, users) with multiple objectives coexist. This paper proposes a mobile data offloading framework using a noncooperative multi-level game-theoretic approach from an end-to-end perspective in the envisioned network. More specifically, we design three-level Stackelberg games, in which a single-leader multi-follower game, a multi-leader multi-follower game, and a single-leader multi-follower game are modeled in the introduced network such that individual players selfishly optimize their local payoff functions and collectively solve the large complex network-wide optimization problem. Further, we develop distributed mobile data offloading algorithms to reduce the complexity of the hierarchical games and to achieve a unique Nash equilibrium condition in each subgame. Simulation results show that by reaching the Nash equilibrium condition, the proposed solution helps minimize energy consumption, interference price, and processing cost, while maximizing revenues of the players in the envisioned network. In addition, the efficiency of the equilibria in terms of price of anarchy and price of stability is quantified for the best/worst case of the Nash equilibrium.",bhaskar rimai,Mobile cloud computing (MCC),2017.0,10.1364/JOCN.9.000601,IEEE/OSA Journal of Optical Communications and Networking,Rimai2017,False,,IEEE,Not available,Mobile data offloading in FiWi enhanced LTE-A heterogeneous networks,9e1d53a3b64be142024910ca68ac89e4,
8207,"This paper proposes to empower capacityand coverage-centric fiber-wireless (FiWi) enhanced 4G LongTerm Evolution Advanced (LTE-A) heterogeneous networks (HetNets) with computationand storage-centric mobile cloud computing to cope with the unprecedented growth of mobile data traffic. Minimizing energy consumption and maximizing revenue while offloading mobile data in such highly converged and hierarchical networks is not trivial, where multiple players (ίe., cloud service providers, macrocell and small cells, users) with multiple objectives coexist. This paper proposes a mobile data offloading framework using a noncooperative multi-level game-theoretic approach from an end-to-end perspective in the envisioned network. More specifically, we design three-level Stackelberg games, in which a single-leader multi-follower game, a multi-leader multi-follower game, and a single-leader multi-follower game are modeled in the introduced network such that individual players selfishly optimize their local payoff functions and collectively solve the large complex network-wide optimization problem. Further, we develop distributed mobile data offloading algorithms to reduce the complexity of the hierarchical games and to achieve a unique Nash equilibrium condition in each subgame. Simulation results show that by reaching the Nash equilibrium condition, the proposed solution helps minimize energy consumption, interference price, and processing cost, while maximizing revenues of the players in the envisioned network. In addition, the efficiency of the equilibria in terms of price of anarchy and price of stability is quantified for the best/worst case of the Nash equilibrium.",bhaskar rimai,Mobile data offloading,2017.0,10.1364/JOCN.9.000601,IEEE/OSA Journal of Optical Communications and Networking,Rimai2017,False,,IEEE,Not available,Mobile data offloading in FiWi enhanced LTE-A heterogeneous networks,9e1d53a3b64be142024910ca68ac89e4,
8208,"This paper proposes to empower capacityand coverage-centric fiber-wireless (FiWi) enhanced 4G LongTerm Evolution Advanced (LTE-A) heterogeneous networks (HetNets) with computationand storage-centric mobile cloud computing to cope with the unprecedented growth of mobile data traffic. Minimizing energy consumption and maximizing revenue while offloading mobile data in such highly converged and hierarchical networks is not trivial, where multiple players (ίe., cloud service providers, macrocell and small cells, users) with multiple objectives coexist. This paper proposes a mobile data offloading framework using a noncooperative multi-level game-theoretic approach from an end-to-end perspective in the envisioned network. More specifically, we design three-level Stackelberg games, in which a single-leader multi-follower game, a multi-leader multi-follower game, and a single-leader multi-follower game are modeled in the introduced network such that individual players selfishly optimize their local payoff functions and collectively solve the large complex network-wide optimization problem. Further, we develop distributed mobile data offloading algorithms to reduce the complexity of the hierarchical games and to achieve a unique Nash equilibrium condition in each subgame. Simulation results show that by reaching the Nash equilibrium condition, the proposed solution helps minimize energy consumption, interference price, and processing cost, while maximizing revenues of the players in the envisioned network. In addition, the efficiency of the equilibria in terms of price of anarchy and price of stability is quantified for the best/worst case of the Nash equilibrium.",bhaskar rimai,Nash equilibrium,2017.0,10.1364/JOCN.9.000601,IEEE/OSA Journal of Optical Communications and Networking,Rimai2017,False,,IEEE,Not available,Mobile data offloading in FiWi enhanced LTE-A heterogeneous networks,9e1d53a3b64be142024910ca68ac89e4,
8209,"This paper proposes to empower capacityand coverage-centric fiber-wireless (FiWi) enhanced 4G LongTerm Evolution Advanced (LTE-A) heterogeneous networks (HetNets) with computationand storage-centric mobile cloud computing to cope with the unprecedented growth of mobile data traffic. Minimizing energy consumption and maximizing revenue while offloading mobile data in such highly converged and hierarchical networks is not trivial, where multiple players (ίe., cloud service providers, macrocell and small cells, users) with multiple objectives coexist. This paper proposes a mobile data offloading framework using a noncooperative multi-level game-theoretic approach from an end-to-end perspective in the envisioned network. More specifically, we design three-level Stackelberg games, in which a single-leader multi-follower game, a multi-leader multi-follower game, and a single-leader multi-follower game are modeled in the introduced network such that individual players selfishly optimize their local payoff functions and collectively solve the large complex network-wide optimization problem. Further, we develop distributed mobile data offloading algorithms to reduce the complexity of the hierarchical games and to achieve a unique Nash equilibrium condition in each subgame. Simulation results show that by reaching the Nash equilibrium condition, the proposed solution helps minimize energy consumption, interference price, and processing cost, while maximizing revenues of the players in the envisioned network. In addition, the efficiency of the equilibria in terms of price of anarchy and price of stability is quantified for the best/worst case of the Nash equilibrium.",bhaskar rimai,Passive optical networks (PONs),2017.0,10.1364/JOCN.9.000601,IEEE/OSA Journal of Optical Communications and Networking,Rimai2017,False,,IEEE,Not available,Mobile data offloading in FiWi enhanced LTE-A heterogeneous networks,9e1d53a3b64be142024910ca68ac89e4,
8210,"This paper proposes to empower capacityand coverage-centric fiber-wireless (FiWi) enhanced 4G LongTerm Evolution Advanced (LTE-A) heterogeneous networks (HetNets) with computationand storage-centric mobile cloud computing to cope with the unprecedented growth of mobile data traffic. Minimizing energy consumption and maximizing revenue while offloading mobile data in such highly converged and hierarchical networks is not trivial, where multiple players (ίe., cloud service providers, macrocell and small cells, users) with multiple objectives coexist. This paper proposes a mobile data offloading framework using a noncooperative multi-level game-theoretic approach from an end-to-end perspective in the envisioned network. More specifically, we design three-level Stackelberg games, in which a single-leader multi-follower game, a multi-leader multi-follower game, and a single-leader multi-follower game are modeled in the introduced network such that individual players selfishly optimize their local payoff functions and collectively solve the large complex network-wide optimization problem. Further, we develop distributed mobile data offloading algorithms to reduce the complexity of the hierarchical games and to achieve a unique Nash equilibrium condition in each subgame. Simulation results show that by reaching the Nash equilibrium condition, the proposed solution helps minimize energy consumption, interference price, and processing cost, while maximizing revenues of the players in the envisioned network. In addition, the efficiency of the equilibria in terms of price of anarchy and price of stability is quantified for the best/worst case of the Nash equilibrium.",bhaskar rimai,Price of anarchy (PoA),2017.0,10.1364/JOCN.9.000601,IEEE/OSA Journal of Optical Communications and Networking,Rimai2017,False,,IEEE,Not available,Mobile data offloading in FiWi enhanced LTE-A heterogeneous networks,9e1d53a3b64be142024910ca68ac89e4,
8211,"This paper proposes to empower capacityand coverage-centric fiber-wireless (FiWi) enhanced 4G LongTerm Evolution Advanced (LTE-A) heterogeneous networks (HetNets) with computationand storage-centric mobile cloud computing to cope with the unprecedented growth of mobile data traffic. Minimizing energy consumption and maximizing revenue while offloading mobile data in such highly converged and hierarchical networks is not trivial, where multiple players (ίe., cloud service providers, macrocell and small cells, users) with multiple objectives coexist. This paper proposes a mobile data offloading framework using a noncooperative multi-level game-theoretic approach from an end-to-end perspective in the envisioned network. More specifically, we design three-level Stackelberg games, in which a single-leader multi-follower game, a multi-leader multi-follower game, and a single-leader multi-follower game are modeled in the introduced network such that individual players selfishly optimize their local payoff functions and collectively solve the large complex network-wide optimization problem. Further, we develop distributed mobile data offloading algorithms to reduce the complexity of the hierarchical games and to achieve a unique Nash equilibrium condition in each subgame. Simulation results show that by reaching the Nash equilibrium condition, the proposed solution helps minimize energy consumption, interference price, and processing cost, while maximizing revenues of the players in the envisioned network. In addition, the efficiency of the equilibria in terms of price of anarchy and price of stability is quantified for the best/worst case of the Nash equilibrium.",martin maier,Fiber-wireless (FiWi),2017.0,10.1364/JOCN.9.000601,IEEE/OSA Journal of Optical Communications and Networking,Rimai2017,False,,IEEE,Not available,Mobile data offloading in FiWi enhanced LTE-A heterogeneous networks,9e1d53a3b64be142024910ca68ac89e4,
8212,"This paper proposes to empower capacityand coverage-centric fiber-wireless (FiWi) enhanced 4G LongTerm Evolution Advanced (LTE-A) heterogeneous networks (HetNets) with computationand storage-centric mobile cloud computing to cope with the unprecedented growth of mobile data traffic. Minimizing energy consumption and maximizing revenue while offloading mobile data in such highly converged and hierarchical networks is not trivial, where multiple players (ίe., cloud service providers, macrocell and small cells, users) with multiple objectives coexist. This paper proposes a mobile data offloading framework using a noncooperative multi-level game-theoretic approach from an end-to-end perspective in the envisioned network. More specifically, we design three-level Stackelberg games, in which a single-leader multi-follower game, a multi-leader multi-follower game, and a single-leader multi-follower game are modeled in the introduced network such that individual players selfishly optimize their local payoff functions and collectively solve the large complex network-wide optimization problem. Further, we develop distributed mobile data offloading algorithms to reduce the complexity of the hierarchical games and to achieve a unique Nash equilibrium condition in each subgame. Simulation results show that by reaching the Nash equilibrium condition, the proposed solution helps minimize energy consumption, interference price, and processing cost, while maximizing revenues of the players in the envisioned network. In addition, the efficiency of the equilibria in terms of price of anarchy and price of stability is quantified for the best/worst case of the Nash equilibrium.",martin maier,Game theory,2017.0,10.1364/JOCN.9.000601,IEEE/OSA Journal of Optical Communications and Networking,Rimai2017,False,,IEEE,Not available,Mobile data offloading in FiWi enhanced LTE-A heterogeneous networks,9e1d53a3b64be142024910ca68ac89e4,
8213,"This paper proposes to empower capacityand coverage-centric fiber-wireless (FiWi) enhanced 4G LongTerm Evolution Advanced (LTE-A) heterogeneous networks (HetNets) with computationand storage-centric mobile cloud computing to cope with the unprecedented growth of mobile data traffic. Minimizing energy consumption and maximizing revenue while offloading mobile data in such highly converged and hierarchical networks is not trivial, where multiple players (ίe., cloud service providers, macrocell and small cells, users) with multiple objectives coexist. This paper proposes a mobile data offloading framework using a noncooperative multi-level game-theoretic approach from an end-to-end perspective in the envisioned network. More specifically, we design three-level Stackelberg games, in which a single-leader multi-follower game, a multi-leader multi-follower game, and a single-leader multi-follower game are modeled in the introduced network such that individual players selfishly optimize their local payoff functions and collectively solve the large complex network-wide optimization problem. Further, we develop distributed mobile data offloading algorithms to reduce the complexity of the hierarchical games and to achieve a unique Nash equilibrium condition in each subgame. Simulation results show that by reaching the Nash equilibrium condition, the proposed solution helps minimize energy consumption, interference price, and processing cost, while maximizing revenues of the players in the envisioned network. In addition, the efficiency of the equilibria in terms of price of anarchy and price of stability is quantified for the best/worst case of the Nash equilibrium.",martin maier,Heterogeneous networks,2017.0,10.1364/JOCN.9.000601,IEEE/OSA Journal of Optical Communications and Networking,Rimai2017,False,,IEEE,Not available,Mobile data offloading in FiWi enhanced LTE-A heterogeneous networks,9e1d53a3b64be142024910ca68ac89e4,
8214,"This paper proposes to empower capacityand coverage-centric fiber-wireless (FiWi) enhanced 4G LongTerm Evolution Advanced (LTE-A) heterogeneous networks (HetNets) with computationand storage-centric mobile cloud computing to cope with the unprecedented growth of mobile data traffic. Minimizing energy consumption and maximizing revenue while offloading mobile data in such highly converged and hierarchical networks is not trivial, where multiple players (ίe., cloud service providers, macrocell and small cells, users) with multiple objectives coexist. This paper proposes a mobile data offloading framework using a noncooperative multi-level game-theoretic approach from an end-to-end perspective in the envisioned network. More specifically, we design three-level Stackelberg games, in which a single-leader multi-follower game, a multi-leader multi-follower game, and a single-leader multi-follower game are modeled in the introduced network such that individual players selfishly optimize their local payoff functions and collectively solve the large complex network-wide optimization problem. Further, we develop distributed mobile data offloading algorithms to reduce the complexity of the hierarchical games and to achieve a unique Nash equilibrium condition in each subgame. Simulation results show that by reaching the Nash equilibrium condition, the proposed solution helps minimize energy consumption, interference price, and processing cost, while maximizing revenues of the players in the envisioned network. In addition, the efficiency of the equilibria in terms of price of anarchy and price of stability is quantified for the best/worst case of the Nash equilibrium.",martin maier,Mobile cloud computing (MCC),2017.0,10.1364/JOCN.9.000601,IEEE/OSA Journal of Optical Communications and Networking,Rimai2017,False,,IEEE,Not available,Mobile data offloading in FiWi enhanced LTE-A heterogeneous networks,9e1d53a3b64be142024910ca68ac89e4,
8215,"This paper proposes to empower capacityand coverage-centric fiber-wireless (FiWi) enhanced 4G LongTerm Evolution Advanced (LTE-A) heterogeneous networks (HetNets) with computationand storage-centric mobile cloud computing to cope with the unprecedented growth of mobile data traffic. Minimizing energy consumption and maximizing revenue while offloading mobile data in such highly converged and hierarchical networks is not trivial, where multiple players (ίe., cloud service providers, macrocell and small cells, users) with multiple objectives coexist. This paper proposes a mobile data offloading framework using a noncooperative multi-level game-theoretic approach from an end-to-end perspective in the envisioned network. More specifically, we design three-level Stackelberg games, in which a single-leader multi-follower game, a multi-leader multi-follower game, and a single-leader multi-follower game are modeled in the introduced network such that individual players selfishly optimize their local payoff functions and collectively solve the large complex network-wide optimization problem. Further, we develop distributed mobile data offloading algorithms to reduce the complexity of the hierarchical games and to achieve a unique Nash equilibrium condition in each subgame. Simulation results show that by reaching the Nash equilibrium condition, the proposed solution helps minimize energy consumption, interference price, and processing cost, while maximizing revenues of the players in the envisioned network. In addition, the efficiency of the equilibria in terms of price of anarchy and price of stability is quantified for the best/worst case of the Nash equilibrium.",martin maier,Mobile data offloading,2017.0,10.1364/JOCN.9.000601,IEEE/OSA Journal of Optical Communications and Networking,Rimai2017,False,,IEEE,Not available,Mobile data offloading in FiWi enhanced LTE-A heterogeneous networks,9e1d53a3b64be142024910ca68ac89e4,
8216,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
8217,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8218,"This paper proposes to empower capacityand coverage-centric fiber-wireless (FiWi) enhanced 4G LongTerm Evolution Advanced (LTE-A) heterogeneous networks (HetNets) with computationand storage-centric mobile cloud computing to cope with the unprecedented growth of mobile data traffic. Minimizing energy consumption and maximizing revenue while offloading mobile data in such highly converged and hierarchical networks is not trivial, where multiple players (ίe., cloud service providers, macrocell and small cells, users) with multiple objectives coexist. This paper proposes a mobile data offloading framework using a noncooperative multi-level game-theoretic approach from an end-to-end perspective in the envisioned network. More specifically, we design three-level Stackelberg games, in which a single-leader multi-follower game, a multi-leader multi-follower game, and a single-leader multi-follower game are modeled in the introduced network such that individual players selfishly optimize their local payoff functions and collectively solve the large complex network-wide optimization problem. Further, we develop distributed mobile data offloading algorithms to reduce the complexity of the hierarchical games and to achieve a unique Nash equilibrium condition in each subgame. Simulation results show that by reaching the Nash equilibrium condition, the proposed solution helps minimize energy consumption, interference price, and processing cost, while maximizing revenues of the players in the envisioned network. In addition, the efficiency of the equilibria in terms of price of anarchy and price of stability is quantified for the best/worst case of the Nash equilibrium.",martin maier,Nash equilibrium,2017.0,10.1364/JOCN.9.000601,IEEE/OSA Journal of Optical Communications and Networking,Rimai2017,False,,IEEE,Not available,Mobile data offloading in FiWi enhanced LTE-A heterogeneous networks,9e1d53a3b64be142024910ca68ac89e4,
8219,"This paper proposes to empower capacityand coverage-centric fiber-wireless (FiWi) enhanced 4G LongTerm Evolution Advanced (LTE-A) heterogeneous networks (HetNets) with computationand storage-centric mobile cloud computing to cope with the unprecedented growth of mobile data traffic. Minimizing energy consumption and maximizing revenue while offloading mobile data in such highly converged and hierarchical networks is not trivial, where multiple players (ίe., cloud service providers, macrocell and small cells, users) with multiple objectives coexist. This paper proposes a mobile data offloading framework using a noncooperative multi-level game-theoretic approach from an end-to-end perspective in the envisioned network. More specifically, we design three-level Stackelberg games, in which a single-leader multi-follower game, a multi-leader multi-follower game, and a single-leader multi-follower game are modeled in the introduced network such that individual players selfishly optimize their local payoff functions and collectively solve the large complex network-wide optimization problem. Further, we develop distributed mobile data offloading algorithms to reduce the complexity of the hierarchical games and to achieve a unique Nash equilibrium condition in each subgame. Simulation results show that by reaching the Nash equilibrium condition, the proposed solution helps minimize energy consumption, interference price, and processing cost, while maximizing revenues of the players in the envisioned network. In addition, the efficiency of the equilibria in terms of price of anarchy and price of stability is quantified for the best/worst case of the Nash equilibrium.",martin maier,Passive optical networks (PONs),2017.0,10.1364/JOCN.9.000601,IEEE/OSA Journal of Optical Communications and Networking,Rimai2017,False,,IEEE,Not available,Mobile data offloading in FiWi enhanced LTE-A heterogeneous networks,9e1d53a3b64be142024910ca68ac89e4,
8220,"This paper proposes to empower capacityand coverage-centric fiber-wireless (FiWi) enhanced 4G LongTerm Evolution Advanced (LTE-A) heterogeneous networks (HetNets) with computationand storage-centric mobile cloud computing to cope with the unprecedented growth of mobile data traffic. Minimizing energy consumption and maximizing revenue while offloading mobile data in such highly converged and hierarchical networks is not trivial, where multiple players (ίe., cloud service providers, macrocell and small cells, users) with multiple objectives coexist. This paper proposes a mobile data offloading framework using a noncooperative multi-level game-theoretic approach from an end-to-end perspective in the envisioned network. More specifically, we design three-level Stackelberg games, in which a single-leader multi-follower game, a multi-leader multi-follower game, and a single-leader multi-follower game are modeled in the introduced network such that individual players selfishly optimize their local payoff functions and collectively solve the large complex network-wide optimization problem. Further, we develop distributed mobile data offloading algorithms to reduce the complexity of the hierarchical games and to achieve a unique Nash equilibrium condition in each subgame. Simulation results show that by reaching the Nash equilibrium condition, the proposed solution helps minimize energy consumption, interference price, and processing cost, while maximizing revenues of the players in the envisioned network. In addition, the efficiency of the equilibria in terms of price of anarchy and price of stability is quantified for the best/worst case of the Nash equilibrium.",martin maier,Price of anarchy (PoA),2017.0,10.1364/JOCN.9.000601,IEEE/OSA Journal of Optical Communications and Networking,Rimai2017,False,,IEEE,Not available,Mobile data offloading in FiWi enhanced LTE-A heterogeneous networks,9e1d53a3b64be142024910ca68ac89e4,
8221,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",salvatore d'oro,Network slicing,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
8222,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",salvatore d'oro,5G,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
8223,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",salvatore d'oro,congestion games,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
8224,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",salvatore d'oro,game theory,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
8225,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",salvatore d'oro,distributed algorithms.,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
8226,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",francesco restuccia,Network slicing,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
8227,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",francesco restuccia,5G,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
8228,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8229,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",francesco restuccia,congestion games,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
8230,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",francesco restuccia,game theory,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
8231,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",francesco restuccia,distributed algorithms.,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
8232,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",tommaso melodia,Network slicing,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
8233,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",tommaso melodia,5G,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
8234,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",tommaso melodia,congestion games,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
8235,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",tommaso melodia,game theory,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
8236,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",tommaso melodia,distributed algorithms.,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
8237,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",sergio palazzo,Network slicing,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
8238,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",sergio palazzo,5G,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
8239,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8240,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",sergio palazzo,congestion games,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
8241,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",sergio palazzo,game theory,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
8242,"Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.",sergio palazzo,distributed algorithms.,,10.1109/TNET.2018.2878965,IEEE/ACM Transactions on Networking,D'OroNone,False,,IEEE,Not available,Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results,cab1a1e5d4e24b0e0cd252c8362140fa,
8243,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",maria-florina balcan,Games,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
8244,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",maria-florina balcan,Couplings,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
8245,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",maria-florina balcan,Vectors,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
8246,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",maria-florina balcan,Convergence,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
8247,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",maria-florina balcan,Delay,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
8248,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",maria-florina balcan,Nash equilibrium,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
8249,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",maria-florina balcan,Internet,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
8250,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8251,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",florin constantin,Games,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
8252,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",florin constantin,Couplings,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
8253,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",florin constantin,Vectors,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
8254,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",florin constantin,Convergence,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
8255,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",florin constantin,Delay,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
8256,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",florin constantin,Nash equilibrium,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
8257,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",florin constantin,Internet,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
8258,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",georgios piliouras,Games,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
8259,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",georgios piliouras,Couplings,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
8260,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",georgios piliouras,Vectors,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
8261,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8262,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",georgios piliouras,Convergence,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
8263,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",georgios piliouras,Delay,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
8264,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",georgios piliouras,Nash equilibrium,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
8265,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",georgios piliouras,Internet,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
8266,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",jeff shamma,Games,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
8267,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",jeff shamma,Couplings,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
8268,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",jeff shamma,Vectors,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
8269,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",jeff shamma,Convergence,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
8270,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",jeff shamma,Delay,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
8271,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",jeff shamma,Nash equilibrium,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
8272,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8273,"Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel game-theoretic construct, that we call game-coupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ,μ)-smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.",jeff shamma,Internet,2011.0,10.1109/CDC.2011.6161365,2011 50th IEEE Conference on Decision and Control and European Control Conference,Balcan2011,False,,IEEE,Not available,Game couplings: Learning dynamics and applications,7ced317be8fe1e811b54919c98105e85,https://ieeexplore.ieee.org/document/6161365/
8274,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",majed haddad,Heterogeneous network,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8275,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",majed haddad,macro cell,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8276,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",majed haddad,small cell,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8277,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",majed haddad,WiFi,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8278,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",majed haddad,network selection,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8279,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",majed haddad,dynamic offset,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8280,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",majed haddad,traffic steering,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8281,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",majed haddad,channel distribution information,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8282,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",majed haddad,channel state information,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8283,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8284,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",majed haddad,game theory,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8285,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",majed haddad,price of anarchy.,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8286,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",piotr wiecek,Heterogeneous network,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8287,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",piotr wiecek,macro cell,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8288,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",piotr wiecek,small cell,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8289,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",piotr wiecek,WiFi,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8290,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",piotr wiecek,network selection,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8291,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",piotr wiecek,dynamic offset,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8292,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",piotr wiecek,traffic steering,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8293,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",piotr wiecek,channel distribution information,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8294,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8295,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",piotr wiecek,channel state information,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8296,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",piotr wiecek,game theory,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8297,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",piotr wiecek,price of anarchy.,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8298,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",habib sidi,Heterogeneous network,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8299,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",habib sidi,macro cell,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8300,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",habib sidi,small cell,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8301,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",habib sidi,WiFi,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8302,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",habib sidi,network selection,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8303,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",habib sidi,dynamic offset,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8304,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",habib sidi,traffic steering,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8305,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
8306,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",habib sidi,channel distribution information,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8307,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",habib sidi,channel state information,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8308,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",habib sidi,game theory,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8309,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",habib sidi,price of anarchy.,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8310,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",eitan altman,Heterogeneous network,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8311,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",eitan altman,macro cell,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8312,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",eitan altman,small cell,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8313,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",eitan altman,WiFi,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8314,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",eitan altman,network selection,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8315,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",eitan altman,dynamic offset,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8316,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
8317,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",eitan altman,traffic steering,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8318,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",eitan altman,channel distribution information,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8319,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",eitan altman,channel state information,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8320,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",eitan altman,game theory,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8321,"Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60 percent of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n<sup>4</sup>) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1 even for a low number of users, and remains bounded above by the non-cooperative model.",eitan altman,price of anarchy.,2016.0,10.1109/TMC.2015.2492560,IEEE Transactions on Mobile Computing,Haddad2016,False,,IEEE,Not available,An Automated Dynamic Offset for Network Selection in Heterogeneous Networks,71c21b32cad24b45d13a857fc428ec7f,https://ieeexplore.ieee.org/document/7302065/
8322,"We study a single server model with no queue and exponential services times, in which service is only provided during a certain time interval. A number of customers wish to obtain this service and can choose their arrival time. A customer that finds a busy server leaves without being served. We model this scenario as a non-cooperative game in which the customers wish to maximize their probability of obtaining service. We characterize the Nash equilibrium and the price of anarchy, which is defined as the ratio between the optimal and equilibrium social utility. In particular, the equilibrium arrival distribution has an atom at zero, a period with no arrival and is continuous on some interval until the closing time. We further generalize our analysis to take into account uncertainty regarding the population size, i.e. a game with a random number of customers. In the special case where the population size follows a Poisson distribution, we show that the continuous part of the distribution is uniform, which is not the case in general. Finally, we show that the price of anarchy is not monotone with respect to the population size; but rather uni-modal with values close to one for small and large populations.",liron ravner,Servers,2014.0,,"2014 7th International Conference on NETwork Games, COntrol and OPtimization (NetGCoop)",Ravner2014,False,,IEEE,Not available,Equilibrium and socially optimal arrivals to a single server loss system,dbb596e13a10cf149f4fa320d9cc1114,https://ieeexplore.ieee.org/document/7943402/
8323,"We study a single server model with no queue and exponential services times, in which service is only provided during a certain time interval. A number of customers wish to obtain this service and can choose their arrival time. A customer that finds a busy server leaves without being served. We model this scenario as a non-cooperative game in which the customers wish to maximize their probability of obtaining service. We characterize the Nash equilibrium and the price of anarchy, which is defined as the ratio between the optimal and equilibrium social utility. In particular, the equilibrium arrival distribution has an atom at zero, a period with no arrival and is continuous on some interval until the closing time. We further generalize our analysis to take into account uncertainty regarding the population size, i.e. a game with a random number of customers. In the special case where the population size follows a Poisson distribution, we show that the continuous part of the distribution is uniform, which is not the case in general. Finally, we show that the price of anarchy is not monotone with respect to the population size; but rather uni-modal with values close to one for small and large populations.",liron ravner,Games,2014.0,,"2014 7th International Conference on NETwork Games, COntrol and OPtimization (NetGCoop)",Ravner2014,False,,IEEE,Not available,Equilibrium and socially optimal arrivals to a single server loss system,dbb596e13a10cf149f4fa320d9cc1114,https://ieeexplore.ieee.org/document/7943402/
8324,"We study a single server model with no queue and exponential services times, in which service is only provided during a certain time interval. A number of customers wish to obtain this service and can choose their arrival time. A customer that finds a busy server leaves without being served. We model this scenario as a non-cooperative game in which the customers wish to maximize their probability of obtaining service. We characterize the Nash equilibrium and the price of anarchy, which is defined as the ratio between the optimal and equilibrium social utility. In particular, the equilibrium arrival distribution has an atom at zero, a period with no arrival and is continuous on some interval until the closing time. We further generalize our analysis to take into account uncertainty regarding the population size, i.e. a game with a random number of customers. In the special case where the population size follows a Poisson distribution, we show that the continuous part of the distribution is uniform, which is not the case in general. Finally, we show that the price of anarchy is not monotone with respect to the population size; but rather uni-modal with values close to one for small and large populations.",liron ravner,Sociology,2014.0,,"2014 7th International Conference on NETwork Games, COntrol and OPtimization (NetGCoop)",Ravner2014,False,,IEEE,Not available,Equilibrium and socially optimal arrivals to a single server loss system,dbb596e13a10cf149f4fa320d9cc1114,https://ieeexplore.ieee.org/document/7943402/
8325,"We study a single server model with no queue and exponential services times, in which service is only provided during a certain time interval. A number of customers wish to obtain this service and can choose their arrival time. A customer that finds a busy server leaves without being served. We model this scenario as a non-cooperative game in which the customers wish to maximize their probability of obtaining service. We characterize the Nash equilibrium and the price of anarchy, which is defined as the ratio between the optimal and equilibrium social utility. In particular, the equilibrium arrival distribution has an atom at zero, a period with no arrival and is continuous on some interval until the closing time. We further generalize our analysis to take into account uncertainty regarding the population size, i.e. a game with a random number of customers. In the special case where the population size follows a Poisson distribution, we show that the continuous part of the distribution is uniform, which is not the case in general. Finally, we show that the price of anarchy is not monotone with respect to the population size; but rather uni-modal with values close to one for small and large populations.",liron ravner,Statistics,2014.0,,"2014 7th International Conference on NETwork Games, COntrol and OPtimization (NetGCoop)",Ravner2014,False,,IEEE,Not available,Equilibrium and socially optimal arrivals to a single server loss system,dbb596e13a10cf149f4fa320d9cc1114,https://ieeexplore.ieee.org/document/7943402/
8326,"We study a single server model with no queue and exponential services times, in which service is only provided during a certain time interval. A number of customers wish to obtain this service and can choose their arrival time. A customer that finds a busy server leaves without being served. We model this scenario as a non-cooperative game in which the customers wish to maximize their probability of obtaining service. We characterize the Nash equilibrium and the price of anarchy, which is defined as the ratio between the optimal and equilibrium social utility. In particular, the equilibrium arrival distribution has an atom at zero, a period with no arrival and is continuous on some interval until the closing time. We further generalize our analysis to take into account uncertainty regarding the population size, i.e. a game with a random number of customers. In the special case where the population size follows a Poisson distribution, we show that the continuous part of the distribution is uniform, which is not the case in general. Finally, we show that the price of anarchy is not monotone with respect to the population size; but rather uni-modal with values close to one for small and large populations.",liron ravner,Analytical models,2014.0,,"2014 7th International Conference on NETwork Games, COntrol and OPtimization (NetGCoop)",Ravner2014,False,,IEEE,Not available,Equilibrium and socially optimal arrivals to a single server loss system,dbb596e13a10cf149f4fa320d9cc1114,https://ieeexplore.ieee.org/document/7943402/
8327,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
8328,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
8329,"We study a single server model with no queue and exponential services times, in which service is only provided during a certain time interval. A number of customers wish to obtain this service and can choose their arrival time. A customer that finds a busy server leaves without being served. We model this scenario as a non-cooperative game in which the customers wish to maximize their probability of obtaining service. We characterize the Nash equilibrium and the price of anarchy, which is defined as the ratio between the optimal and equilibrium social utility. In particular, the equilibrium arrival distribution has an atom at zero, a period with no arrival and is continuous on some interval until the closing time. We further generalize our analysis to take into account uncertainty regarding the population size, i.e. a game with a random number of customers. In the special case where the population size follows a Poisson distribution, we show that the continuous part of the distribution is uniform, which is not the case in general. Finally, we show that the price of anarchy is not monotone with respect to the population size; but rather uni-modal with values close to one for small and large populations.",liron ravner,Nash equilibrium,2014.0,,"2014 7th International Conference on NETwork Games, COntrol and OPtimization (NetGCoop)",Ravner2014,False,,IEEE,Not available,Equilibrium and socially optimal arrivals to a single server loss system,dbb596e13a10cf149f4fa320d9cc1114,https://ieeexplore.ieee.org/document/7943402/
8330,"We study a single server model with no queue and exponential services times, in which service is only provided during a certain time interval. A number of customers wish to obtain this service and can choose their arrival time. A customer that finds a busy server leaves without being served. We model this scenario as a non-cooperative game in which the customers wish to maximize their probability of obtaining service. We characterize the Nash equilibrium and the price of anarchy, which is defined as the ratio between the optimal and equilibrium social utility. In particular, the equilibrium arrival distribution has an atom at zero, a period with no arrival and is continuous on some interval until the closing time. We further generalize our analysis to take into account uncertainty regarding the population size, i.e. a game with a random number of customers. In the special case where the population size follows a Poisson distribution, we show that the continuous part of the distribution is uniform, which is not the case in general. Finally, we show that the price of anarchy is not monotone with respect to the population size; but rather uni-modal with values close to one for small and large populations.",liron ravner,Optimization,2014.0,,"2014 7th International Conference on NETwork Games, COntrol and OPtimization (NetGCoop)",Ravner2014,False,,IEEE,Not available,Equilibrium and socially optimal arrivals to a single server loss system,dbb596e13a10cf149f4fa320d9cc1114,https://ieeexplore.ieee.org/document/7943402/
8331,"We study a single server model with no queue and exponential services times, in which service is only provided during a certain time interval. A number of customers wish to obtain this service and can choose their arrival time. A customer that finds a busy server leaves without being served. We model this scenario as a non-cooperative game in which the customers wish to maximize their probability of obtaining service. We characterize the Nash equilibrium and the price of anarchy, which is defined as the ratio between the optimal and equilibrium social utility. In particular, the equilibrium arrival distribution has an atom at zero, a period with no arrival and is continuous on some interval until the closing time. We further generalize our analysis to take into account uncertainty regarding the population size, i.e. a game with a random number of customers. In the special case where the population size follows a Poisson distribution, we show that the continuous part of the distribution is uniform, which is not the case in general. Finally, we show that the price of anarchy is not monotone with respect to the population size; but rather uni-modal with values close to one for small and large populations.",moshe haviv,Servers,2014.0,,"2014 7th International Conference on NETwork Games, COntrol and OPtimization (NetGCoop)",Ravner2014,False,,IEEE,Not available,Equilibrium and socially optimal arrivals to a single server loss system,dbb596e13a10cf149f4fa320d9cc1114,https://ieeexplore.ieee.org/document/7943402/
8332,"We study a single server model with no queue and exponential services times, in which service is only provided during a certain time interval. A number of customers wish to obtain this service and can choose their arrival time. A customer that finds a busy server leaves without being served. We model this scenario as a non-cooperative game in which the customers wish to maximize their probability of obtaining service. We characterize the Nash equilibrium and the price of anarchy, which is defined as the ratio between the optimal and equilibrium social utility. In particular, the equilibrium arrival distribution has an atom at zero, a period with no arrival and is continuous on some interval until the closing time. We further generalize our analysis to take into account uncertainty regarding the population size, i.e. a game with a random number of customers. In the special case where the population size follows a Poisson distribution, we show that the continuous part of the distribution is uniform, which is not the case in general. Finally, we show that the price of anarchy is not monotone with respect to the population size; but rather uni-modal with values close to one for small and large populations.",moshe haviv,Games,2014.0,,"2014 7th International Conference on NETwork Games, COntrol and OPtimization (NetGCoop)",Ravner2014,False,,IEEE,Not available,Equilibrium and socially optimal arrivals to a single server loss system,dbb596e13a10cf149f4fa320d9cc1114,https://ieeexplore.ieee.org/document/7943402/
8333,"We study a single server model with no queue and exponential services times, in which service is only provided during a certain time interval. A number of customers wish to obtain this service and can choose their arrival time. A customer that finds a busy server leaves without being served. We model this scenario as a non-cooperative game in which the customers wish to maximize their probability of obtaining service. We characterize the Nash equilibrium and the price of anarchy, which is defined as the ratio between the optimal and equilibrium social utility. In particular, the equilibrium arrival distribution has an atom at zero, a period with no arrival and is continuous on some interval until the closing time. We further generalize our analysis to take into account uncertainty regarding the population size, i.e. a game with a random number of customers. In the special case where the population size follows a Poisson distribution, we show that the continuous part of the distribution is uniform, which is not the case in general. Finally, we show that the price of anarchy is not monotone with respect to the population size; but rather uni-modal with values close to one for small and large populations.",moshe haviv,Sociology,2014.0,,"2014 7th International Conference on NETwork Games, COntrol and OPtimization (NetGCoop)",Ravner2014,False,,IEEE,Not available,Equilibrium and socially optimal arrivals to a single server loss system,dbb596e13a10cf149f4fa320d9cc1114,https://ieeexplore.ieee.org/document/7943402/
8334,"We study a single server model with no queue and exponential services times, in which service is only provided during a certain time interval. A number of customers wish to obtain this service and can choose their arrival time. A customer that finds a busy server leaves without being served. We model this scenario as a non-cooperative game in which the customers wish to maximize their probability of obtaining service. We characterize the Nash equilibrium and the price of anarchy, which is defined as the ratio between the optimal and equilibrium social utility. In particular, the equilibrium arrival distribution has an atom at zero, a period with no arrival and is continuous on some interval until the closing time. We further generalize our analysis to take into account uncertainty regarding the population size, i.e. a game with a random number of customers. In the special case where the population size follows a Poisson distribution, we show that the continuous part of the distribution is uniform, which is not the case in general. Finally, we show that the price of anarchy is not monotone with respect to the population size; but rather uni-modal with values close to one for small and large populations.",moshe haviv,Statistics,2014.0,,"2014 7th International Conference on NETwork Games, COntrol and OPtimization (NetGCoop)",Ravner2014,False,,IEEE,Not available,Equilibrium and socially optimal arrivals to a single server loss system,dbb596e13a10cf149f4fa320d9cc1114,https://ieeexplore.ieee.org/document/7943402/
8335,"We study a single server model with no queue and exponential services times, in which service is only provided during a certain time interval. A number of customers wish to obtain this service and can choose their arrival time. A customer that finds a busy server leaves without being served. We model this scenario as a non-cooperative game in which the customers wish to maximize their probability of obtaining service. We characterize the Nash equilibrium and the price of anarchy, which is defined as the ratio between the optimal and equilibrium social utility. In particular, the equilibrium arrival distribution has an atom at zero, a period with no arrival and is continuous on some interval until the closing time. We further generalize our analysis to take into account uncertainty regarding the population size, i.e. a game with a random number of customers. In the special case where the population size follows a Poisson distribution, we show that the continuous part of the distribution is uniform, which is not the case in general. Finally, we show that the price of anarchy is not monotone with respect to the population size; but rather uni-modal with values close to one for small and large populations.",moshe haviv,Analytical models,2014.0,,"2014 7th International Conference on NETwork Games, COntrol and OPtimization (NetGCoop)",Ravner2014,False,,IEEE,Not available,Equilibrium and socially optimal arrivals to a single server loss system,dbb596e13a10cf149f4fa320d9cc1114,https://ieeexplore.ieee.org/document/7943402/
8336,"We study a single server model with no queue and exponential services times, in which service is only provided during a certain time interval. A number of customers wish to obtain this service and can choose their arrival time. A customer that finds a busy server leaves without being served. We model this scenario as a non-cooperative game in which the customers wish to maximize their probability of obtaining service. We characterize the Nash equilibrium and the price of anarchy, which is defined as the ratio between the optimal and equilibrium social utility. In particular, the equilibrium arrival distribution has an atom at zero, a period with no arrival and is continuous on some interval until the closing time. We further generalize our analysis to take into account uncertainty regarding the population size, i.e. a game with a random number of customers. In the special case where the population size follows a Poisson distribution, we show that the continuous part of the distribution is uniform, which is not the case in general. Finally, we show that the price of anarchy is not monotone with respect to the population size; but rather uni-modal with values close to one for small and large populations.",moshe haviv,Nash equilibrium,2014.0,,"2014 7th International Conference on NETwork Games, COntrol and OPtimization (NetGCoop)",Ravner2014,False,,IEEE,Not available,Equilibrium and socially optimal arrivals to a single server loss system,dbb596e13a10cf149f4fa320d9cc1114,https://ieeexplore.ieee.org/document/7943402/
8337,"We study a single server model with no queue and exponential services times, in which service is only provided during a certain time interval. A number of customers wish to obtain this service and can choose their arrival time. A customer that finds a busy server leaves without being served. We model this scenario as a non-cooperative game in which the customers wish to maximize their probability of obtaining service. We characterize the Nash equilibrium and the price of anarchy, which is defined as the ratio between the optimal and equilibrium social utility. In particular, the equilibrium arrival distribution has an atom at zero, a period with no arrival and is continuous on some interval until the closing time. We further generalize our analysis to take into account uncertainty regarding the population size, i.e. a game with a random number of customers. In the special case where the population size follows a Poisson distribution, we show that the continuous part of the distribution is uniform, which is not the case in general. Finally, we show that the price of anarchy is not monotone with respect to the population size; but rather uni-modal with values close to one for small and large populations.",moshe haviv,Optimization,2014.0,,"2014 7th International Conference on NETwork Games, COntrol and OPtimization (NetGCoop)",Ravner2014,False,,IEEE,Not available,Equilibrium and socially optimal arrivals to a single server loss system,dbb596e13a10cf149f4fa320d9cc1114,https://ieeexplore.ieee.org/document/7943402/
8338,"We investigate the behavior of a large number of selfish users that are able to switch dynamically between multiple wireless access-points (possibly belonging to different standards) by introducing an iterated non-cooperative game. Users start out completely uneducated and naive but, by using a fixed set of strategies to process a broadcasted training signal, they quickly evolve and converge to an evolutionarily stable equilibrium. Then, in order to measure efficiency in this steady state, we adapt the notion of the price of anarchy to our setting and we obtain an explicit analytic estimate for it by using methods from statistical physics (namely the theory of replicas). Surprisingly, we find that the price of anarchy does not depend on the specifics of the wireless nodes (e.g., spectral efficiency) but only on the number of strategies per user and a particular combination of the number of nodes, the number of users and the size of the training signal. Finally, we map this game to the well-studied minority game, generalizing its analysis to an arbitrary number of choices.",panayotis mertikopoulos,Wireless networks,2008.0,10.1109/JSAC.2008.080913,IEEE Journal on Selected Areas in Communications,Mertikopoulos2008,False,,IEEE,Not available,Correlated Anarchy in Overlapping Wireless Networks,540321518afa99c49e61ed19b69c5f19,https://ieeexplore.ieee.org/document/4604741/
8339,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
8340,"We investigate the behavior of a large number of selfish users that are able to switch dynamically between multiple wireless access-points (possibly belonging to different standards) by introducing an iterated non-cooperative game. Users start out completely uneducated and naive but, by using a fixed set of strategies to process a broadcasted training signal, they quickly evolve and converge to an evolutionarily stable equilibrium. Then, in order to measure efficiency in this steady state, we adapt the notion of the price of anarchy to our setting and we obtain an explicit analytic estimate for it by using methods from statistical physics (namely the theory of replicas). Surprisingly, we find that the price of anarchy does not depend on the specifics of the wireless nodes (e.g., spectral efficiency) but only on the number of strategies per user and a particular combination of the number of nodes, the number of users and the size of the training signal. Finally, we map this game to the well-studied minority game, generalizing its analysis to an arbitrary number of choices.",panayotis mertikopoulos,Nash equilibrium,2008.0,10.1109/JSAC.2008.080913,IEEE Journal on Selected Areas in Communications,Mertikopoulos2008,False,,IEEE,Not available,Correlated Anarchy in Overlapping Wireless Networks,540321518afa99c49e61ed19b69c5f19,https://ieeexplore.ieee.org/document/4604741/
8341,"We investigate the behavior of a large number of selfish users that are able to switch dynamically between multiple wireless access-points (possibly belonging to different standards) by introducing an iterated non-cooperative game. Users start out completely uneducated and naive but, by using a fixed set of strategies to process a broadcasted training signal, they quickly evolve and converge to an evolutionarily stable equilibrium. Then, in order to measure efficiency in this steady state, we adapt the notion of the price of anarchy to our setting and we obtain an explicit analytic estimate for it by using methods from statistical physics (namely the theory of replicas). Surprisingly, we find that the price of anarchy does not depend on the specifics of the wireless nodes (e.g., spectral efficiency) but only on the number of strategies per user and a particular combination of the number of nodes, the number of users and the size of the training signal. Finally, we map this game to the well-studied minority game, generalizing its analysis to an arbitrary number of choices.",panayotis mertikopoulos,correlated equilibrium,2008.0,10.1109/JSAC.2008.080913,IEEE Journal on Selected Areas in Communications,Mertikopoulos2008,False,,IEEE,Not available,Correlated Anarchy in Overlapping Wireless Networks,540321518afa99c49e61ed19b69c5f19,https://ieeexplore.ieee.org/document/4604741/
8342,"We investigate the behavior of a large number of selfish users that are able to switch dynamically between multiple wireless access-points (possibly belonging to different standards) by introducing an iterated non-cooperative game. Users start out completely uneducated and naive but, by using a fixed set of strategies to process a broadcasted training signal, they quickly evolve and converge to an evolutionarily stable equilibrium. Then, in order to measure efficiency in this steady state, we adapt the notion of the price of anarchy to our setting and we obtain an explicit analytic estimate for it by using methods from statistical physics (namely the theory of replicas). Surprisingly, we find that the price of anarchy does not depend on the specifics of the wireless nodes (e.g., spectral efficiency) but only on the number of strategies per user and a particular combination of the number of nodes, the number of users and the size of the training signal. Finally, we map this game to the well-studied minority game, generalizing its analysis to an arbitrary number of choices.",panayotis mertikopoulos,price of anarchy,2008.0,10.1109/JSAC.2008.080913,IEEE Journal on Selected Areas in Communications,Mertikopoulos2008,False,,IEEE,Not available,Correlated Anarchy in Overlapping Wireless Networks,540321518afa99c49e61ed19b69c5f19,https://ieeexplore.ieee.org/document/4604741/
8343,"We investigate the behavior of a large number of selfish users that are able to switch dynamically between multiple wireless access-points (possibly belonging to different standards) by introducing an iterated non-cooperative game. Users start out completely uneducated and naive but, by using a fixed set of strategies to process a broadcasted training signal, they quickly evolve and converge to an evolutionarily stable equilibrium. Then, in order to measure efficiency in this steady state, we adapt the notion of the price of anarchy to our setting and we obtain an explicit analytic estimate for it by using methods from statistical physics (namely the theory of replicas). Surprisingly, we find that the price of anarchy does not depend on the specifics of the wireless nodes (e.g., spectral efficiency) but only on the number of strategies per user and a particular combination of the number of nodes, the number of users and the size of the training signal. Finally, we map this game to the well-studied minority game, generalizing its analysis to an arbitrary number of choices.",panayotis mertikopoulos,evolutionary games,2008.0,10.1109/JSAC.2008.080913,IEEE Journal on Selected Areas in Communications,Mertikopoulos2008,False,,IEEE,Not available,Correlated Anarchy in Overlapping Wireless Networks,540321518afa99c49e61ed19b69c5f19,https://ieeexplore.ieee.org/document/4604741/
8344,"We investigate the behavior of a large number of selfish users that are able to switch dynamically between multiple wireless access-points (possibly belonging to different standards) by introducing an iterated non-cooperative game. Users start out completely uneducated and naive but, by using a fixed set of strategies to process a broadcasted training signal, they quickly evolve and converge to an evolutionarily stable equilibrium. Then, in order to measure efficiency in this steady state, we adapt the notion of the price of anarchy to our setting and we obtain an explicit analytic estimate for it by using methods from statistical physics (namely the theory of replicas). Surprisingly, we find that the price of anarchy does not depend on the specifics of the wireless nodes (e.g., spectral efficiency) but only on the number of strategies per user and a particular combination of the number of nodes, the number of users and the size of the training signal. Finally, we map this game to the well-studied minority game, generalizing its analysis to an arbitrary number of choices.",panayotis mertikopoulos,replicas,2008.0,10.1109/JSAC.2008.080913,IEEE Journal on Selected Areas in Communications,Mertikopoulos2008,False,,IEEE,Not available,Correlated Anarchy in Overlapping Wireless Networks,540321518afa99c49e61ed19b69c5f19,https://ieeexplore.ieee.org/document/4604741/
8345,"We investigate the behavior of a large number of selfish users that are able to switch dynamically between multiple wireless access-points (possibly belonging to different standards) by introducing an iterated non-cooperative game. Users start out completely uneducated and naive but, by using a fixed set of strategies to process a broadcasted training signal, they quickly evolve and converge to an evolutionarily stable equilibrium. Then, in order to measure efficiency in this steady state, we adapt the notion of the price of anarchy to our setting and we obtain an explicit analytic estimate for it by using methods from statistical physics (namely the theory of replicas). Surprisingly, we find that the price of anarchy does not depend on the specifics of the wireless nodes (e.g., spectral efficiency) but only on the number of strategies per user and a particular combination of the number of nodes, the number of users and the size of the training signal. Finally, we map this game to the well-studied minority game, generalizing its analysis to an arbitrary number of choices.",aris moustakas,Wireless networks,2008.0,10.1109/JSAC.2008.080913,IEEE Journal on Selected Areas in Communications,Mertikopoulos2008,False,,IEEE,Not available,Correlated Anarchy in Overlapping Wireless Networks,540321518afa99c49e61ed19b69c5f19,https://ieeexplore.ieee.org/document/4604741/
8346,"We investigate the behavior of a large number of selfish users that are able to switch dynamically between multiple wireless access-points (possibly belonging to different standards) by introducing an iterated non-cooperative game. Users start out completely uneducated and naive but, by using a fixed set of strategies to process a broadcasted training signal, they quickly evolve and converge to an evolutionarily stable equilibrium. Then, in order to measure efficiency in this steady state, we adapt the notion of the price of anarchy to our setting and we obtain an explicit analytic estimate for it by using methods from statistical physics (namely the theory of replicas). Surprisingly, we find that the price of anarchy does not depend on the specifics of the wireless nodes (e.g., spectral efficiency) but only on the number of strategies per user and a particular combination of the number of nodes, the number of users and the size of the training signal. Finally, we map this game to the well-studied minority game, generalizing its analysis to an arbitrary number of choices.",aris moustakas,Nash equilibrium,2008.0,10.1109/JSAC.2008.080913,IEEE Journal on Selected Areas in Communications,Mertikopoulos2008,False,,IEEE,Not available,Correlated Anarchy in Overlapping Wireless Networks,540321518afa99c49e61ed19b69c5f19,https://ieeexplore.ieee.org/document/4604741/
8347,"We investigate the behavior of a large number of selfish users that are able to switch dynamically between multiple wireless access-points (possibly belonging to different standards) by introducing an iterated non-cooperative game. Users start out completely uneducated and naive but, by using a fixed set of strategies to process a broadcasted training signal, they quickly evolve and converge to an evolutionarily stable equilibrium. Then, in order to measure efficiency in this steady state, we adapt the notion of the price of anarchy to our setting and we obtain an explicit analytic estimate for it by using methods from statistical physics (namely the theory of replicas). Surprisingly, we find that the price of anarchy does not depend on the specifics of the wireless nodes (e.g., spectral efficiency) but only on the number of strategies per user and a particular combination of the number of nodes, the number of users and the size of the training signal. Finally, we map this game to the well-studied minority game, generalizing its analysis to an arbitrary number of choices.",aris moustakas,correlated equilibrium,2008.0,10.1109/JSAC.2008.080913,IEEE Journal on Selected Areas in Communications,Mertikopoulos2008,False,,IEEE,Not available,Correlated Anarchy in Overlapping Wireless Networks,540321518afa99c49e61ed19b69c5f19,https://ieeexplore.ieee.org/document/4604741/
8348,"We investigate the behavior of a large number of selfish users that are able to switch dynamically between multiple wireless access-points (possibly belonging to different standards) by introducing an iterated non-cooperative game. Users start out completely uneducated and naive but, by using a fixed set of strategies to process a broadcasted training signal, they quickly evolve and converge to an evolutionarily stable equilibrium. Then, in order to measure efficiency in this steady state, we adapt the notion of the price of anarchy to our setting and we obtain an explicit analytic estimate for it by using methods from statistical physics (namely the theory of replicas). Surprisingly, we find that the price of anarchy does not depend on the specifics of the wireless nodes (e.g., spectral efficiency) but only on the number of strategies per user and a particular combination of the number of nodes, the number of users and the size of the training signal. Finally, we map this game to the well-studied minority game, generalizing its analysis to an arbitrary number of choices.",aris moustakas,price of anarchy,2008.0,10.1109/JSAC.2008.080913,IEEE Journal on Selected Areas in Communications,Mertikopoulos2008,False,,IEEE,Not available,Correlated Anarchy in Overlapping Wireless Networks,540321518afa99c49e61ed19b69c5f19,https://ieeexplore.ieee.org/document/4604741/
8349,"We investigate the behavior of a large number of selfish users that are able to switch dynamically between multiple wireless access-points (possibly belonging to different standards) by introducing an iterated non-cooperative game. Users start out completely uneducated and naive but, by using a fixed set of strategies to process a broadcasted training signal, they quickly evolve and converge to an evolutionarily stable equilibrium. Then, in order to measure efficiency in this steady state, we adapt the notion of the price of anarchy to our setting and we obtain an explicit analytic estimate for it by using methods from statistical physics (namely the theory of replicas). Surprisingly, we find that the price of anarchy does not depend on the specifics of the wireless nodes (e.g., spectral efficiency) but only on the number of strategies per user and a particular combination of the number of nodes, the number of users and the size of the training signal. Finally, we map this game to the well-studied minority game, generalizing its analysis to an arbitrary number of choices.",aris moustakas,evolutionary games,2008.0,10.1109/JSAC.2008.080913,IEEE Journal on Selected Areas in Communications,Mertikopoulos2008,False,,IEEE,Not available,Correlated Anarchy in Overlapping Wireless Networks,540321518afa99c49e61ed19b69c5f19,https://ieeexplore.ieee.org/document/4604741/
8350,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
8351,"We investigate the behavior of a large number of selfish users that are able to switch dynamically between multiple wireless access-points (possibly belonging to different standards) by introducing an iterated non-cooperative game. Users start out completely uneducated and naive but, by using a fixed set of strategies to process a broadcasted training signal, they quickly evolve and converge to an evolutionarily stable equilibrium. Then, in order to measure efficiency in this steady state, we adapt the notion of the price of anarchy to our setting and we obtain an explicit analytic estimate for it by using methods from statistical physics (namely the theory of replicas). Surprisingly, we find that the price of anarchy does not depend on the specifics of the wireless nodes (e.g., spectral efficiency) but only on the number of strategies per user and a particular combination of the number of nodes, the number of users and the size of the training signal. Finally, we map this game to the well-studied minority game, generalizing its analysis to an arbitrary number of choices.",aris moustakas,replicas,2008.0,10.1109/JSAC.2008.080913,IEEE Journal on Selected Areas in Communications,Mertikopoulos2008,False,,IEEE,Not available,Correlated Anarchy in Overlapping Wireless Networks,540321518afa99c49e61ed19b69c5f19,https://ieeexplore.ieee.org/document/4604741/
8352,"In peer-to-peer storage systems, peers replicate each others' data in order to increase availability. If the matching is done centrally, the algorithm can optimize data availability in an equitable manner for all participants. However, if matching is decentralized, the peers' selfishness can greatly alter the results, leading to performance inequities that can render the system unreliable and thus ultimately unusable. We analyze the problem using both theoretical approaches (complexity analysis for the centralized system, game theory for the decentralized one) and simulation. We prove that the problem of optimizing availability in a centralized system is NP-hard. In decentralized settings, we show that the rational behavior of selfish peers will be to replicate only with similarly-available peers. Compared to the socially-optimal solution, highly available peers have their data availability increased at the expense of decreased data availability for less available peers. The price of anarchy is high: unbounded in one model, and linear with the number of time slots in the second model. We also propose centralized and decentralized heuristics that, according to our experiments, converge fast in the average case. The high price of anarchy means that a completely decentralized system could be too hostile for peers with low availability, who could never achieve satisfying replication parameters. Moreover, we experimentally show that even explicit consideration and exploitation of diurnal patterns of peer availability has a small effect on the data availability-except when the system has truly global scope. Yet a fully centralized system is infeasible, not only because of problems in information gathering, but also the complexity of optimizing availability. The solution to this dilemma is to create system-wide cooperation rules that allow a decentralized algorithm, but also limit the selfishness of the participants.",krzysztof rzadca,price of anarchy,2010.0,10.1109/ICDCS.2010.67,2010 IEEE 30th International Conference on Distributed Computing Systems,Rzadca2010,False,,IEEE,Not available,Replica Placement in P2P Storage: Complexity and Game Theoretic Analyses,460329b9e0ca072aecab540d5529a23f,https://ieeexplore.ieee.org/document/5541690/
8353,"In peer-to-peer storage systems, peers replicate each others' data in order to increase availability. If the matching is done centrally, the algorithm can optimize data availability in an equitable manner for all participants. However, if matching is decentralized, the peers' selfishness can greatly alter the results, leading to performance inequities that can render the system unreliable and thus ultimately unusable. We analyze the problem using both theoretical approaches (complexity analysis for the centralized system, game theory for the decentralized one) and simulation. We prove that the problem of optimizing availability in a centralized system is NP-hard. In decentralized settings, we show that the rational behavior of selfish peers will be to replicate only with similarly-available peers. Compared to the socially-optimal solution, highly available peers have their data availability increased at the expense of decreased data availability for less available peers. The price of anarchy is high: unbounded in one model, and linear with the number of time slots in the second model. We also propose centralized and decentralized heuristics that, according to our experiments, converge fast in the average case. The high price of anarchy means that a completely decentralized system could be too hostile for peers with low availability, who could never achieve satisfying replication parameters. Moreover, we experimentally show that even explicit consideration and exploitation of diurnal patterns of peer availability has a small effect on the data availability-except when the system has truly global scope. Yet a fully centralized system is infeasible, not only because of problems in information gathering, but also the complexity of optimizing availability. The solution to this dilemma is to create system-wide cooperation rules that allow a decentralized algorithm, but also limit the selfishness of the participants.",krzysztof rzadca,equitable optimization,2010.0,10.1109/ICDCS.2010.67,2010 IEEE 30th International Conference on Distributed Computing Systems,Rzadca2010,False,,IEEE,Not available,Replica Placement in P2P Storage: Complexity and Game Theoretic Analyses,460329b9e0ca072aecab540d5529a23f,https://ieeexplore.ieee.org/document/5541690/
8354,"In peer-to-peer storage systems, peers replicate each others' data in order to increase availability. If the matching is done centrally, the algorithm can optimize data availability in an equitable manner for all participants. However, if matching is decentralized, the peers' selfishness can greatly alter the results, leading to performance inequities that can render the system unreliable and thus ultimately unusable. We analyze the problem using both theoretical approaches (complexity analysis for the centralized system, game theory for the decentralized one) and simulation. We prove that the problem of optimizing availability in a centralized system is NP-hard. In decentralized settings, we show that the rational behavior of selfish peers will be to replicate only with similarly-available peers. Compared to the socially-optimal solution, highly available peers have their data availability increased at the expense of decreased data availability for less available peers. The price of anarchy is high: unbounded in one model, and linear with the number of time slots in the second model. We also propose centralized and decentralized heuristics that, according to our experiments, converge fast in the average case. The high price of anarchy means that a completely decentralized system could be too hostile for peers with low availability, who could never achieve satisfying replication parameters. Moreover, we experimentally show that even explicit consideration and exploitation of diurnal patterns of peer availability has a small effect on the data availability-except when the system has truly global scope. Yet a fully centralized system is infeasible, not only because of problems in information gathering, but also the complexity of optimizing availability. The solution to this dilemma is to create system-wide cooperation rules that allow a decentralized algorithm, but also limit the selfishness of the participants.",krzysztof rzadca,distributed storage,2010.0,10.1109/ICDCS.2010.67,2010 IEEE 30th International Conference on Distributed Computing Systems,Rzadca2010,False,,IEEE,Not available,Replica Placement in P2P Storage: Complexity and Game Theoretic Analyses,460329b9e0ca072aecab540d5529a23f,https://ieeexplore.ieee.org/document/5541690/
8355,"In peer-to-peer storage systems, peers replicate each others' data in order to increase availability. If the matching is done centrally, the algorithm can optimize data availability in an equitable manner for all participants. However, if matching is decentralized, the peers' selfishness can greatly alter the results, leading to performance inequities that can render the system unreliable and thus ultimately unusable. We analyze the problem using both theoretical approaches (complexity analysis for the centralized system, game theory for the decentralized one) and simulation. We prove that the problem of optimizing availability in a centralized system is NP-hard. In decentralized settings, we show that the rational behavior of selfish peers will be to replicate only with similarly-available peers. Compared to the socially-optimal solution, highly available peers have their data availability increased at the expense of decreased data availability for less available peers. The price of anarchy is high: unbounded in one model, and linear with the number of time slots in the second model. We also propose centralized and decentralized heuristics that, according to our experiments, converge fast in the average case. The high price of anarchy means that a completely decentralized system could be too hostile for peers with low availability, who could never achieve satisfying replication parameters. Moreover, we experimentally show that even explicit consideration and exploitation of diurnal patterns of peer availability has a small effect on the data availability-except when the system has truly global scope. Yet a fully centralized system is infeasible, not only because of problems in information gathering, but also the complexity of optimizing availability. The solution to this dilemma is to create system-wide cooperation rules that allow a decentralized algorithm, but also limit the selfishness of the participants.",anwitaman datta,price of anarchy,2010.0,10.1109/ICDCS.2010.67,2010 IEEE 30th International Conference on Distributed Computing Systems,Rzadca2010,False,,IEEE,Not available,Replica Placement in P2P Storage: Complexity and Game Theoretic Analyses,460329b9e0ca072aecab540d5529a23f,https://ieeexplore.ieee.org/document/5541690/
8356,"In peer-to-peer storage systems, peers replicate each others' data in order to increase availability. If the matching is done centrally, the algorithm can optimize data availability in an equitable manner for all participants. However, if matching is decentralized, the peers' selfishness can greatly alter the results, leading to performance inequities that can render the system unreliable and thus ultimately unusable. We analyze the problem using both theoretical approaches (complexity analysis for the centralized system, game theory for the decentralized one) and simulation. We prove that the problem of optimizing availability in a centralized system is NP-hard. In decentralized settings, we show that the rational behavior of selfish peers will be to replicate only with similarly-available peers. Compared to the socially-optimal solution, highly available peers have their data availability increased at the expense of decreased data availability for less available peers. The price of anarchy is high: unbounded in one model, and linear with the number of time slots in the second model. We also propose centralized and decentralized heuristics that, according to our experiments, converge fast in the average case. The high price of anarchy means that a completely decentralized system could be too hostile for peers with low availability, who could never achieve satisfying replication parameters. Moreover, we experimentally show that even explicit consideration and exploitation of diurnal patterns of peer availability has a small effect on the data availability-except when the system has truly global scope. Yet a fully centralized system is infeasible, not only because of problems in information gathering, but also the complexity of optimizing availability. The solution to this dilemma is to create system-wide cooperation rules that allow a decentralized algorithm, but also limit the selfishness of the participants.",anwitaman datta,equitable optimization,2010.0,10.1109/ICDCS.2010.67,2010 IEEE 30th International Conference on Distributed Computing Systems,Rzadca2010,False,,IEEE,Not available,Replica Placement in P2P Storage: Complexity and Game Theoretic Analyses,460329b9e0ca072aecab540d5529a23f,https://ieeexplore.ieee.org/document/5541690/
8357,"In peer-to-peer storage systems, peers replicate each others' data in order to increase availability. If the matching is done centrally, the algorithm can optimize data availability in an equitable manner for all participants. However, if matching is decentralized, the peers' selfishness can greatly alter the results, leading to performance inequities that can render the system unreliable and thus ultimately unusable. We analyze the problem using both theoretical approaches (complexity analysis for the centralized system, game theory for the decentralized one) and simulation. We prove that the problem of optimizing availability in a centralized system is NP-hard. In decentralized settings, we show that the rational behavior of selfish peers will be to replicate only with similarly-available peers. Compared to the socially-optimal solution, highly available peers have their data availability increased at the expense of decreased data availability for less available peers. The price of anarchy is high: unbounded in one model, and linear with the number of time slots in the second model. We also propose centralized and decentralized heuristics that, according to our experiments, converge fast in the average case. The high price of anarchy means that a completely decentralized system could be too hostile for peers with low availability, who could never achieve satisfying replication parameters. Moreover, we experimentally show that even explicit consideration and exploitation of diurnal patterns of peer availability has a small effect on the data availability-except when the system has truly global scope. Yet a fully centralized system is infeasible, not only because of problems in information gathering, but also the complexity of optimizing availability. The solution to this dilemma is to create system-wide cooperation rules that allow a decentralized algorithm, but also limit the selfishness of the participants.",anwitaman datta,distributed storage,2010.0,10.1109/ICDCS.2010.67,2010 IEEE 30th International Conference on Distributed Computing Systems,Rzadca2010,False,,IEEE,Not available,Replica Placement in P2P Storage: Complexity and Game Theoretic Analyses,460329b9e0ca072aecab540d5529a23f,https://ieeexplore.ieee.org/document/5541690/
8358,"In peer-to-peer storage systems, peers replicate each others' data in order to increase availability. If the matching is done centrally, the algorithm can optimize data availability in an equitable manner for all participants. However, if matching is decentralized, the peers' selfishness can greatly alter the results, leading to performance inequities that can render the system unreliable and thus ultimately unusable. We analyze the problem using both theoretical approaches (complexity analysis for the centralized system, game theory for the decentralized one) and simulation. We prove that the problem of optimizing availability in a centralized system is NP-hard. In decentralized settings, we show that the rational behavior of selfish peers will be to replicate only with similarly-available peers. Compared to the socially-optimal solution, highly available peers have their data availability increased at the expense of decreased data availability for less available peers. The price of anarchy is high: unbounded in one model, and linear with the number of time slots in the second model. We also propose centralized and decentralized heuristics that, according to our experiments, converge fast in the average case. The high price of anarchy means that a completely decentralized system could be too hostile for peers with low availability, who could never achieve satisfying replication parameters. Moreover, we experimentally show that even explicit consideration and exploitation of diurnal patterns of peer availability has a small effect on the data availability-except when the system has truly global scope. Yet a fully centralized system is infeasible, not only because of problems in information gathering, but also the complexity of optimizing availability. The solution to this dilemma is to create system-wide cooperation rules that allow a decentralized algorithm, but also limit the selfishness of the participants.",sonja buchegger,price of anarchy,2010.0,10.1109/ICDCS.2010.67,2010 IEEE 30th International Conference on Distributed Computing Systems,Rzadca2010,False,,IEEE,Not available,Replica Placement in P2P Storage: Complexity and Game Theoretic Analyses,460329b9e0ca072aecab540d5529a23f,https://ieeexplore.ieee.org/document/5541690/
8359,"In peer-to-peer storage systems, peers replicate each others' data in order to increase availability. If the matching is done centrally, the algorithm can optimize data availability in an equitable manner for all participants. However, if matching is decentralized, the peers' selfishness can greatly alter the results, leading to performance inequities that can render the system unreliable and thus ultimately unusable. We analyze the problem using both theoretical approaches (complexity analysis for the centralized system, game theory for the decentralized one) and simulation. We prove that the problem of optimizing availability in a centralized system is NP-hard. In decentralized settings, we show that the rational behavior of selfish peers will be to replicate only with similarly-available peers. Compared to the socially-optimal solution, highly available peers have their data availability increased at the expense of decreased data availability for less available peers. The price of anarchy is high: unbounded in one model, and linear with the number of time slots in the second model. We also propose centralized and decentralized heuristics that, according to our experiments, converge fast in the average case. The high price of anarchy means that a completely decentralized system could be too hostile for peers with low availability, who could never achieve satisfying replication parameters. Moreover, we experimentally show that even explicit consideration and exploitation of diurnal patterns of peer availability has a small effect on the data availability-except when the system has truly global scope. Yet a fully centralized system is infeasible, not only because of problems in information gathering, but also the complexity of optimizing availability. The solution to this dilemma is to create system-wide cooperation rules that allow a decentralized algorithm, but also limit the selfishness of the participants.",sonja buchegger,equitable optimization,2010.0,10.1109/ICDCS.2010.67,2010 IEEE 30th International Conference on Distributed Computing Systems,Rzadca2010,False,,IEEE,Not available,Replica Placement in P2P Storage: Complexity and Game Theoretic Analyses,460329b9e0ca072aecab540d5529a23f,https://ieeexplore.ieee.org/document/5541690/
8360,"In peer-to-peer storage systems, peers replicate each others' data in order to increase availability. If the matching is done centrally, the algorithm can optimize data availability in an equitable manner for all participants. However, if matching is decentralized, the peers' selfishness can greatly alter the results, leading to performance inequities that can render the system unreliable and thus ultimately unusable. We analyze the problem using both theoretical approaches (complexity analysis for the centralized system, game theory for the decentralized one) and simulation. We prove that the problem of optimizing availability in a centralized system is NP-hard. In decentralized settings, we show that the rational behavior of selfish peers will be to replicate only with similarly-available peers. Compared to the socially-optimal solution, highly available peers have their data availability increased at the expense of decreased data availability for less available peers. The price of anarchy is high: unbounded in one model, and linear with the number of time slots in the second model. We also propose centralized and decentralized heuristics that, according to our experiments, converge fast in the average case. The high price of anarchy means that a completely decentralized system could be too hostile for peers with low availability, who could never achieve satisfying replication parameters. Moreover, we experimentally show that even explicit consideration and exploitation of diurnal patterns of peer availability has a small effect on the data availability-except when the system has truly global scope. Yet a fully centralized system is infeasible, not only because of problems in information gathering, but also the complexity of optimizing availability. The solution to this dilemma is to create system-wide cooperation rules that allow a decentralized algorithm, but also limit the selfishness of the participants.",sonja buchegger,distributed storage,2010.0,10.1109/ICDCS.2010.67,2010 IEEE 30th International Conference on Distributed Computing Systems,Rzadca2010,False,,IEEE,Not available,Replica Placement in P2P Storage: Complexity and Game Theoretic Analyses,460329b9e0ca072aecab540d5529a23f,https://ieeexplore.ieee.org/document/5541690/
8361,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
8362,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8363,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8364,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8365,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8366,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8367,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8368,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8369,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8370,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8371,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8372,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
8373,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8374,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8375,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8376,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8377,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8378,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8379,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8380,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8381,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8382,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8383,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
8384,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8385,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8386,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8387,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
8388,"We study a network security game where strategic players choose their investments in security. Since a player's investment can reduce the propagation of computer viruses, a key feature of the game is the positive externality exerted by the investment. With selfish players, unfortunately, the overall network security can be far from optimum. The contributions of this paper are as follows. 1) We first characterize the price of anarchy (POA) in the strategic-form game under an “Effective-investment” model and a “Bad-traffic” model, and give insight on how the POA depends on individual players' cost functions and their mutual influence. We also introduce the concept of “weighted POA” to bound the region of payoff vectors. 2) In a repeated game, players have more incentive to cooperate for their long term interests. We consider the socially best outcome that can be supported by the repeated game, as compared to the social optimum. 3) Next, we compare the benefits of improving security technology and improving incentives, and show that improving technology alone may not offset the price of anarchy. 4) Finally, we characterize the performance of correlated equilibrium (CE). Although the paper focuses on network security, many results are generally applicable to games with positive externalities .",libin jiang,Correlated equilibrium (CE),2011.0,10.1109/TNET.2010.2071397,IEEE/ACM Transactions on Networking,Jiang2011,False,,IEEE,Not available,How Bad Are Selfish Investments in Network Security?,b998a0b4a2948c4632b037e584709110,https://ieeexplore.ieee.org/document/5575384/
8389,"We study a network security game where strategic players choose their investments in security. Since a player's investment can reduce the propagation of computer viruses, a key feature of the game is the positive externality exerted by the investment. With selfish players, unfortunately, the overall network security can be far from optimum. The contributions of this paper are as follows. 1) We first characterize the price of anarchy (POA) in the strategic-form game under an “Effective-investment” model and a “Bad-traffic” model, and give insight on how the POA depends on individual players' cost functions and their mutual influence. We also introduce the concept of “weighted POA” to bound the region of payoff vectors. 2) In a repeated game, players have more incentive to cooperate for their long term interests. We consider the socially best outcome that can be supported by the repeated game, as compared to the social optimum. 3) Next, we compare the benefits of improving security technology and improving incentives, and show that improving technology alone may not offset the price of anarchy. 4) Finally, we characterize the performance of correlated equilibrium (CE). Although the paper focuses on network security, many results are generally applicable to games with positive externalities .",libin jiang,game theory,2011.0,10.1109/TNET.2010.2071397,IEEE/ACM Transactions on Networking,Jiang2011,False,,IEEE,Not available,How Bad Are Selfish Investments in Network Security?,b998a0b4a2948c4632b037e584709110,https://ieeexplore.ieee.org/document/5575384/
8390,"We study a network security game where strategic players choose their investments in security. Since a player's investment can reduce the propagation of computer viruses, a key feature of the game is the positive externality exerted by the investment. With selfish players, unfortunately, the overall network security can be far from optimum. The contributions of this paper are as follows. 1) We first characterize the price of anarchy (POA) in the strategic-form game under an “Effective-investment” model and a “Bad-traffic” model, and give insight on how the POA depends on individual players' cost functions and their mutual influence. We also introduce the concept of “weighted POA” to bound the region of payoff vectors. 2) In a repeated game, players have more incentive to cooperate for their long term interests. We consider the socially best outcome that can be supported by the repeated game, as compared to the social optimum. 3) Next, we compare the benefits of improving security technology and improving incentives, and show that improving technology alone may not offset the price of anarchy. 4) Finally, we characterize the performance of correlated equilibrium (CE). Although the paper focuses on network security, many results are generally applicable to games with positive externalities .",libin jiang,network security,2011.0,10.1109/TNET.2010.2071397,IEEE/ACM Transactions on Networking,Jiang2011,False,,IEEE,Not available,How Bad Are Selfish Investments in Network Security?,b998a0b4a2948c4632b037e584709110,https://ieeexplore.ieee.org/document/5575384/
8391,"We study a network security game where strategic players choose their investments in security. Since a player's investment can reduce the propagation of computer viruses, a key feature of the game is the positive externality exerted by the investment. With selfish players, unfortunately, the overall network security can be far from optimum. The contributions of this paper are as follows. 1) We first characterize the price of anarchy (POA) in the strategic-form game under an “Effective-investment” model and a “Bad-traffic” model, and give insight on how the POA depends on individual players' cost functions and their mutual influence. We also introduce the concept of “weighted POA” to bound the region of payoff vectors. 2) In a repeated game, players have more incentive to cooperate for their long term interests. We consider the socially best outcome that can be supported by the repeated game, as compared to the social optimum. 3) Next, we compare the benefits of improving security technology and improving incentives, and show that improving technology alone may not offset the price of anarchy. 4) Finally, we characterize the performance of correlated equilibrium (CE). Although the paper focuses on network security, many results are generally applicable to games with positive externalities .",libin jiang,positive externality,2011.0,10.1109/TNET.2010.2071397,IEEE/ACM Transactions on Networking,Jiang2011,False,,IEEE,Not available,How Bad Are Selfish Investments in Network Security?,b998a0b4a2948c4632b037e584709110,https://ieeexplore.ieee.org/document/5575384/
8392,"We study a network security game where strategic players choose their investments in security. Since a player's investment can reduce the propagation of computer viruses, a key feature of the game is the positive externality exerted by the investment. With selfish players, unfortunately, the overall network security can be far from optimum. The contributions of this paper are as follows. 1) We first characterize the price of anarchy (POA) in the strategic-form game under an “Effective-investment” model and a “Bad-traffic” model, and give insight on how the POA depends on individual players' cost functions and their mutual influence. We also introduce the concept of “weighted POA” to bound the region of payoff vectors. 2) In a repeated game, players have more incentive to cooperate for their long term interests. We consider the socially best outcome that can be supported by the repeated game, as compared to the social optimum. 3) Next, we compare the benefits of improving security technology and improving incentives, and show that improving technology alone may not offset the price of anarchy. 4) Finally, we characterize the performance of correlated equilibrium (CE). Although the paper focuses on network security, many results are generally applicable to games with positive externalities .",libin jiang,price of anarchy (POA),2011.0,10.1109/TNET.2010.2071397,IEEE/ACM Transactions on Networking,Jiang2011,False,,IEEE,Not available,How Bad Are Selfish Investments in Network Security?,b998a0b4a2948c4632b037e584709110,https://ieeexplore.ieee.org/document/5575384/
8393,"We study a network security game where strategic players choose their investments in security. Since a player's investment can reduce the propagation of computer viruses, a key feature of the game is the positive externality exerted by the investment. With selfish players, unfortunately, the overall network security can be far from optimum. The contributions of this paper are as follows. 1) We first characterize the price of anarchy (POA) in the strategic-form game under an “Effective-investment” model and a “Bad-traffic” model, and give insight on how the POA depends on individual players' cost functions and their mutual influence. We also introduce the concept of “weighted POA” to bound the region of payoff vectors. 2) In a repeated game, players have more incentive to cooperate for their long term interests. We consider the socially best outcome that can be supported by the repeated game, as compared to the social optimum. 3) Next, we compare the benefits of improving security technology and improving incentives, and show that improving technology alone may not offset the price of anarchy. 4) Finally, we characterize the performance of correlated equilibrium (CE). Although the paper focuses on network security, many results are generally applicable to games with positive externalities .",libin jiang,repeated game,2011.0,10.1109/TNET.2010.2071397,IEEE/ACM Transactions on Networking,Jiang2011,False,,IEEE,Not available,How Bad Are Selfish Investments in Network Security?,b998a0b4a2948c4632b037e584709110,https://ieeexplore.ieee.org/document/5575384/
8394,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
8395,"We study a network security game where strategic players choose their investments in security. Since a player's investment can reduce the propagation of computer viruses, a key feature of the game is the positive externality exerted by the investment. With selfish players, unfortunately, the overall network security can be far from optimum. The contributions of this paper are as follows. 1) We first characterize the price of anarchy (POA) in the strategic-form game under an “Effective-investment” model and a “Bad-traffic” model, and give insight on how the POA depends on individual players' cost functions and their mutual influence. We also introduce the concept of “weighted POA” to bound the region of payoff vectors. 2) In a repeated game, players have more incentive to cooperate for their long term interests. We consider the socially best outcome that can be supported by the repeated game, as compared to the social optimum. 3) Next, we compare the benefits of improving security technology and improving incentives, and show that improving technology alone may not offset the price of anarchy. 4) Finally, we characterize the performance of correlated equilibrium (CE). Although the paper focuses on network security, many results are generally applicable to games with positive externalities .",venkat anantharam,Correlated equilibrium (CE),2011.0,10.1109/TNET.2010.2071397,IEEE/ACM Transactions on Networking,Jiang2011,False,,IEEE,Not available,How Bad Are Selfish Investments in Network Security?,b998a0b4a2948c4632b037e584709110,https://ieeexplore.ieee.org/document/5575384/
8396,"We study a network security game where strategic players choose their investments in security. Since a player's investment can reduce the propagation of computer viruses, a key feature of the game is the positive externality exerted by the investment. With selfish players, unfortunately, the overall network security can be far from optimum. The contributions of this paper are as follows. 1) We first characterize the price of anarchy (POA) in the strategic-form game under an “Effective-investment” model and a “Bad-traffic” model, and give insight on how the POA depends on individual players' cost functions and their mutual influence. We also introduce the concept of “weighted POA” to bound the region of payoff vectors. 2) In a repeated game, players have more incentive to cooperate for their long term interests. We consider the socially best outcome that can be supported by the repeated game, as compared to the social optimum. 3) Next, we compare the benefits of improving security technology and improving incentives, and show that improving technology alone may not offset the price of anarchy. 4) Finally, we characterize the performance of correlated equilibrium (CE). Although the paper focuses on network security, many results are generally applicable to games with positive externalities .",venkat anantharam,game theory,2011.0,10.1109/TNET.2010.2071397,IEEE/ACM Transactions on Networking,Jiang2011,False,,IEEE,Not available,How Bad Are Selfish Investments in Network Security?,b998a0b4a2948c4632b037e584709110,https://ieeexplore.ieee.org/document/5575384/
8397,"We study a network security game where strategic players choose their investments in security. Since a player's investment can reduce the propagation of computer viruses, a key feature of the game is the positive externality exerted by the investment. With selfish players, unfortunately, the overall network security can be far from optimum. The contributions of this paper are as follows. 1) We first characterize the price of anarchy (POA) in the strategic-form game under an “Effective-investment” model and a “Bad-traffic” model, and give insight on how the POA depends on individual players' cost functions and their mutual influence. We also introduce the concept of “weighted POA” to bound the region of payoff vectors. 2) In a repeated game, players have more incentive to cooperate for their long term interests. We consider the socially best outcome that can be supported by the repeated game, as compared to the social optimum. 3) Next, we compare the benefits of improving security technology and improving incentives, and show that improving technology alone may not offset the price of anarchy. 4) Finally, we characterize the performance of correlated equilibrium (CE). Although the paper focuses on network security, many results are generally applicable to games with positive externalities .",venkat anantharam,network security,2011.0,10.1109/TNET.2010.2071397,IEEE/ACM Transactions on Networking,Jiang2011,False,,IEEE,Not available,How Bad Are Selfish Investments in Network Security?,b998a0b4a2948c4632b037e584709110,https://ieeexplore.ieee.org/document/5575384/
8398,"We study a network security game where strategic players choose their investments in security. Since a player's investment can reduce the propagation of computer viruses, a key feature of the game is the positive externality exerted by the investment. With selfish players, unfortunately, the overall network security can be far from optimum. The contributions of this paper are as follows. 1) We first characterize the price of anarchy (POA) in the strategic-form game under an “Effective-investment” model and a “Bad-traffic” model, and give insight on how the POA depends on individual players' cost functions and their mutual influence. We also introduce the concept of “weighted POA” to bound the region of payoff vectors. 2) In a repeated game, players have more incentive to cooperate for their long term interests. We consider the socially best outcome that can be supported by the repeated game, as compared to the social optimum. 3) Next, we compare the benefits of improving security technology and improving incentives, and show that improving technology alone may not offset the price of anarchy. 4) Finally, we characterize the performance of correlated equilibrium (CE). Although the paper focuses on network security, many results are generally applicable to games with positive externalities .",venkat anantharam,positive externality,2011.0,10.1109/TNET.2010.2071397,IEEE/ACM Transactions on Networking,Jiang2011,False,,IEEE,Not available,How Bad Are Selfish Investments in Network Security?,b998a0b4a2948c4632b037e584709110,https://ieeexplore.ieee.org/document/5575384/
8399,"We study a network security game where strategic players choose their investments in security. Since a player's investment can reduce the propagation of computer viruses, a key feature of the game is the positive externality exerted by the investment. With selfish players, unfortunately, the overall network security can be far from optimum. The contributions of this paper are as follows. 1) We first characterize the price of anarchy (POA) in the strategic-form game under an “Effective-investment” model and a “Bad-traffic” model, and give insight on how the POA depends on individual players' cost functions and their mutual influence. We also introduce the concept of “weighted POA” to bound the region of payoff vectors. 2) In a repeated game, players have more incentive to cooperate for their long term interests. We consider the socially best outcome that can be supported by the repeated game, as compared to the social optimum. 3) Next, we compare the benefits of improving security technology and improving incentives, and show that improving technology alone may not offset the price of anarchy. 4) Finally, we characterize the performance of correlated equilibrium (CE). Although the paper focuses on network security, many results are generally applicable to games with positive externalities .",venkat anantharam,price of anarchy (POA),2011.0,10.1109/TNET.2010.2071397,IEEE/ACM Transactions on Networking,Jiang2011,False,,IEEE,Not available,How Bad Are Selfish Investments in Network Security?,b998a0b4a2948c4632b037e584709110,https://ieeexplore.ieee.org/document/5575384/
8400,"We study a network security game where strategic players choose their investments in security. Since a player's investment can reduce the propagation of computer viruses, a key feature of the game is the positive externality exerted by the investment. With selfish players, unfortunately, the overall network security can be far from optimum. The contributions of this paper are as follows. 1) We first characterize the price of anarchy (POA) in the strategic-form game under an “Effective-investment” model and a “Bad-traffic” model, and give insight on how the POA depends on individual players' cost functions and their mutual influence. We also introduce the concept of “weighted POA” to bound the region of payoff vectors. 2) In a repeated game, players have more incentive to cooperate for their long term interests. We consider the socially best outcome that can be supported by the repeated game, as compared to the social optimum. 3) Next, we compare the benefits of improving security technology and improving incentives, and show that improving technology alone may not offset the price of anarchy. 4) Finally, we characterize the performance of correlated equilibrium (CE). Although the paper focuses on network security, many results are generally applicable to games with positive externalities .",venkat anantharam,repeated game,2011.0,10.1109/TNET.2010.2071397,IEEE/ACM Transactions on Networking,Jiang2011,False,,IEEE,Not available,How Bad Are Selfish Investments in Network Security?,b998a0b4a2948c4632b037e584709110,https://ieeexplore.ieee.org/document/5575384/
8401,"We study a network security game where strategic players choose their investments in security. Since a player's investment can reduce the propagation of computer viruses, a key feature of the game is the positive externality exerted by the investment. With selfish players, unfortunately, the overall network security can be far from optimum. The contributions of this paper are as follows. 1) We first characterize the price of anarchy (POA) in the strategic-form game under an “Effective-investment” model and a “Bad-traffic” model, and give insight on how the POA depends on individual players' cost functions and their mutual influence. We also introduce the concept of “weighted POA” to bound the region of payoff vectors. 2) In a repeated game, players have more incentive to cooperate for their long term interests. We consider the socially best outcome that can be supported by the repeated game, as compared to the social optimum. 3) Next, we compare the benefits of improving security technology and improving incentives, and show that improving technology alone may not offset the price of anarchy. 4) Finally, we characterize the performance of correlated equilibrium (CE). Although the paper focuses on network security, many results are generally applicable to games with positive externalities .",jean walrand,Correlated equilibrium (CE),2011.0,10.1109/TNET.2010.2071397,IEEE/ACM Transactions on Networking,Jiang2011,False,,IEEE,Not available,How Bad Are Selfish Investments in Network Security?,b998a0b4a2948c4632b037e584709110,https://ieeexplore.ieee.org/document/5575384/
8402,"We study a network security game where strategic players choose their investments in security. Since a player's investment can reduce the propagation of computer viruses, a key feature of the game is the positive externality exerted by the investment. With selfish players, unfortunately, the overall network security can be far from optimum. The contributions of this paper are as follows. 1) We first characterize the price of anarchy (POA) in the strategic-form game under an “Effective-investment” model and a “Bad-traffic” model, and give insight on how the POA depends on individual players' cost functions and their mutual influence. We also introduce the concept of “weighted POA” to bound the region of payoff vectors. 2) In a repeated game, players have more incentive to cooperate for their long term interests. We consider the socially best outcome that can be supported by the repeated game, as compared to the social optimum. 3) Next, we compare the benefits of improving security technology and improving incentives, and show that improving technology alone may not offset the price of anarchy. 4) Finally, we characterize the performance of correlated equilibrium (CE). Although the paper focuses on network security, many results are generally applicable to games with positive externalities .",jean walrand,game theory,2011.0,10.1109/TNET.2010.2071397,IEEE/ACM Transactions on Networking,Jiang2011,False,,IEEE,Not available,How Bad Are Selfish Investments in Network Security?,b998a0b4a2948c4632b037e584709110,https://ieeexplore.ieee.org/document/5575384/
8403,"We study a network security game where strategic players choose their investments in security. Since a player's investment can reduce the propagation of computer viruses, a key feature of the game is the positive externality exerted by the investment. With selfish players, unfortunately, the overall network security can be far from optimum. The contributions of this paper are as follows. 1) We first characterize the price of anarchy (POA) in the strategic-form game under an “Effective-investment” model and a “Bad-traffic” model, and give insight on how the POA depends on individual players' cost functions and their mutual influence. We also introduce the concept of “weighted POA” to bound the region of payoff vectors. 2) In a repeated game, players have more incentive to cooperate for their long term interests. We consider the socially best outcome that can be supported by the repeated game, as compared to the social optimum. 3) Next, we compare the benefits of improving security technology and improving incentives, and show that improving technology alone may not offset the price of anarchy. 4) Finally, we characterize the performance of correlated equilibrium (CE). Although the paper focuses on network security, many results are generally applicable to games with positive externalities .",jean walrand,network security,2011.0,10.1109/TNET.2010.2071397,IEEE/ACM Transactions on Networking,Jiang2011,False,,IEEE,Not available,How Bad Are Selfish Investments in Network Security?,b998a0b4a2948c4632b037e584709110,https://ieeexplore.ieee.org/document/5575384/
8404,"We study a network security game where strategic players choose their investments in security. Since a player's investment can reduce the propagation of computer viruses, a key feature of the game is the positive externality exerted by the investment. With selfish players, unfortunately, the overall network security can be far from optimum. The contributions of this paper are as follows. 1) We first characterize the price of anarchy (POA) in the strategic-form game under an “Effective-investment” model and a “Bad-traffic” model, and give insight on how the POA depends on individual players' cost functions and their mutual influence. We also introduce the concept of “weighted POA” to bound the region of payoff vectors. 2) In a repeated game, players have more incentive to cooperate for their long term interests. We consider the socially best outcome that can be supported by the repeated game, as compared to the social optimum. 3) Next, we compare the benefits of improving security technology and improving incentives, and show that improving technology alone may not offset the price of anarchy. 4) Finally, we characterize the performance of correlated equilibrium (CE). Although the paper focuses on network security, many results are generally applicable to games with positive externalities .",jean walrand,positive externality,2011.0,10.1109/TNET.2010.2071397,IEEE/ACM Transactions on Networking,Jiang2011,False,,IEEE,Not available,How Bad Are Selfish Investments in Network Security?,b998a0b4a2948c4632b037e584709110,https://ieeexplore.ieee.org/document/5575384/
8405,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
8406,"We study a network security game where strategic players choose their investments in security. Since a player's investment can reduce the propagation of computer viruses, a key feature of the game is the positive externality exerted by the investment. With selfish players, unfortunately, the overall network security can be far from optimum. The contributions of this paper are as follows. 1) We first characterize the price of anarchy (POA) in the strategic-form game under an “Effective-investment” model and a “Bad-traffic” model, and give insight on how the POA depends on individual players' cost functions and their mutual influence. We also introduce the concept of “weighted POA” to bound the region of payoff vectors. 2) In a repeated game, players have more incentive to cooperate for their long term interests. We consider the socially best outcome that can be supported by the repeated game, as compared to the social optimum. 3) Next, we compare the benefits of improving security technology and improving incentives, and show that improving technology alone may not offset the price of anarchy. 4) Finally, we characterize the performance of correlated equilibrium (CE). Although the paper focuses on network security, many results are generally applicable to games with positive externalities .",jean walrand,price of anarchy (POA),2011.0,10.1109/TNET.2010.2071397,IEEE/ACM Transactions on Networking,Jiang2011,False,,IEEE,Not available,How Bad Are Selfish Investments in Network Security?,b998a0b4a2948c4632b037e584709110,https://ieeexplore.ieee.org/document/5575384/
8407,"We study a network security game where strategic players choose their investments in security. Since a player's investment can reduce the propagation of computer viruses, a key feature of the game is the positive externality exerted by the investment. With selfish players, unfortunately, the overall network security can be far from optimum. The contributions of this paper are as follows. 1) We first characterize the price of anarchy (POA) in the strategic-form game under an “Effective-investment” model and a “Bad-traffic” model, and give insight on how the POA depends on individual players' cost functions and their mutual influence. We also introduce the concept of “weighted POA” to bound the region of payoff vectors. 2) In a repeated game, players have more incentive to cooperate for their long term interests. We consider the socially best outcome that can be supported by the repeated game, as compared to the social optimum. 3) Next, we compare the benefits of improving security technology and improving incentives, and show that improving technology alone may not offset the price of anarchy. 4) Finally, we characterize the performance of correlated equilibrium (CE). Although the paper focuses on network security, many results are generally applicable to games with positive externalities .",jean walrand,repeated game,2011.0,10.1109/TNET.2010.2071397,IEEE/ACM Transactions on Networking,Jiang2011,False,,IEEE,Not available,How Bad Are Selfish Investments in Network Security?,b998a0b4a2948c4632b037e584709110,https://ieeexplore.ieee.org/document/5575384/
8408,"In this paper we consider the problem of distributed channel allocation in large networks under the frequency-selective interference channel. Performance is measured by the weighted sum of achievable rates. First we present a natural non-cooperative game theoretic formulation for this problem. It is shown that, when interference is sufficiently strong, this game has a pure price of anarchy approaching infinity with high probability, and there is an asymptotically increasing number of equilibria with the worst performance. Then we propose a novel non-cooperative M Frequency-Selective Interference Game (M-FSIG), where users limit their utility such that it is greater than zero only for their M best channels, and equal for them. We show that the M-FSIG exhibits, with high probability, an increasing number of optimal pure Nash equilibria and no bad equilibria. Consequently, the pure price of anarchy converges to one in probability in any interference regime. In order to exploit these results algorithmically we propose a modified Fictitious Play algorithm that can be implemented distributedly. We carry out simulations that show its fast convergence to the proven pure Nash equilibria.",ilai bistritz,Interference,2015.0,10.1109/ALLERTON.2015.7447154,"2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Bistritz2015,False,,IEEE,Not available,Asymptotically optimal distributed channel allocation: A competitive game-theoretic approach,e540851e38f0fb631a26e8e7c82dad36,https://ieeexplore.ieee.org/document/7447154/
8409,"In this paper we consider the problem of distributed channel allocation in large networks under the frequency-selective interference channel. Performance is measured by the weighted sum of achievable rates. First we present a natural non-cooperative game theoretic formulation for this problem. It is shown that, when interference is sufficiently strong, this game has a pure price of anarchy approaching infinity with high probability, and there is an asymptotically increasing number of equilibria with the worst performance. Then we propose a novel non-cooperative M Frequency-Selective Interference Game (M-FSIG), where users limit their utility such that it is greater than zero only for their M best channels, and equal for them. We show that the M-FSIG exhibits, with high probability, an increasing number of optimal pure Nash equilibria and no bad equilibria. Consequently, the pure price of anarchy converges to one in probability in any interference regime. In order to exploit these results algorithmically we propose a modified Fictitious Play algorithm that can be implemented distributedly. We carry out simulations that show its fast convergence to the proven pure Nash equilibria.",ilai bistritz,Games,2015.0,10.1109/ALLERTON.2015.7447154,"2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Bistritz2015,False,,IEEE,Not available,Asymptotically optimal distributed channel allocation: A competitive game-theoretic approach,e540851e38f0fb631a26e8e7c82dad36,https://ieeexplore.ieee.org/document/7447154/
8410,"In this paper we consider the problem of distributed channel allocation in large networks under the frequency-selective interference channel. Performance is measured by the weighted sum of achievable rates. First we present a natural non-cooperative game theoretic formulation for this problem. It is shown that, when interference is sufficiently strong, this game has a pure price of anarchy approaching infinity with high probability, and there is an asymptotically increasing number of equilibria with the worst performance. Then we propose a novel non-cooperative M Frequency-Selective Interference Game (M-FSIG), where users limit their utility such that it is greater than zero only for their M best channels, and equal for them. We show that the M-FSIG exhibits, with high probability, an increasing number of optimal pure Nash equilibria and no bad equilibria. Consequently, the pure price of anarchy converges to one in probability in any interference regime. In order to exploit these results algorithmically we propose a modified Fictitious Play algorithm that can be implemented distributedly. We carry out simulations that show its fast convergence to the proven pure Nash equilibria.",ilai bistritz,Channel allocation,2015.0,10.1109/ALLERTON.2015.7447154,"2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Bistritz2015,False,,IEEE,Not available,Asymptotically optimal distributed channel allocation: A competitive game-theoretic approach,e540851e38f0fb631a26e8e7c82dad36,https://ieeexplore.ieee.org/document/7447154/
8411,"In this paper we consider the problem of distributed channel allocation in large networks under the frequency-selective interference channel. Performance is measured by the weighted sum of achievable rates. First we present a natural non-cooperative game theoretic formulation for this problem. It is shown that, when interference is sufficiently strong, this game has a pure price of anarchy approaching infinity with high probability, and there is an asymptotically increasing number of equilibria with the worst performance. Then we propose a novel non-cooperative M Frequency-Selective Interference Game (M-FSIG), where users limit their utility such that it is greater than zero only for their M best channels, and equal for them. We show that the M-FSIG exhibits, with high probability, an increasing number of optimal pure Nash equilibria and no bad equilibria. Consequently, the pure price of anarchy converges to one in probability in any interference regime. In order to exploit these results algorithmically we propose a modified Fictitious Play algorithm that can be implemented distributedly. We carry out simulations that show its fast convergence to the proven pure Nash equilibria.",ilai bistritz,Receivers,2015.0,10.1109/ALLERTON.2015.7447154,"2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Bistritz2015,False,,IEEE,Not available,Asymptotically optimal distributed channel allocation: A competitive game-theoretic approach,e540851e38f0fb631a26e8e7c82dad36,https://ieeexplore.ieee.org/document/7447154/
8412,"In this paper we consider the problem of distributed channel allocation in large networks under the frequency-selective interference channel. Performance is measured by the weighted sum of achievable rates. First we present a natural non-cooperative game theoretic formulation for this problem. It is shown that, when interference is sufficiently strong, this game has a pure price of anarchy approaching infinity with high probability, and there is an asymptotically increasing number of equilibria with the worst performance. Then we propose a novel non-cooperative M Frequency-Selective Interference Game (M-FSIG), where users limit their utility such that it is greater than zero only for their M best channels, and equal for them. We show that the M-FSIG exhibits, with high probability, an increasing number of optimal pure Nash equilibria and no bad equilibria. Consequently, the pure price of anarchy converges to one in probability in any interference regime. In order to exploit these results algorithmically we propose a modified Fictitious Play algorithm that can be implemented distributedly. We carry out simulations that show its fast convergence to the proven pure Nash equilibria.",ilai bistritz,Algorithm design and analysis,2015.0,10.1109/ALLERTON.2015.7447154,"2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Bistritz2015,False,,IEEE,Not available,Asymptotically optimal distributed channel allocation: A competitive game-theoretic approach,e540851e38f0fb631a26e8e7c82dad36,https://ieeexplore.ieee.org/document/7447154/
8413,"In this paper we consider the problem of distributed channel allocation in large networks under the frequency-selective interference channel. Performance is measured by the weighted sum of achievable rates. First we present a natural non-cooperative game theoretic formulation for this problem. It is shown that, when interference is sufficiently strong, this game has a pure price of anarchy approaching infinity with high probability, and there is an asymptotically increasing number of equilibria with the worst performance. Then we propose a novel non-cooperative M Frequency-Selective Interference Game (M-FSIG), where users limit their utility such that it is greater than zero only for their M best channels, and equal for them. We show that the M-FSIG exhibits, with high probability, an increasing number of optimal pure Nash equilibria and no bad equilibria. Consequently, the pure price of anarchy converges to one in probability in any interference regime. In order to exploit these results algorithmically we propose a modified Fictitious Play algorithm that can be implemented distributedly. We carry out simulations that show its fast convergence to the proven pure Nash equilibria.",ilai bistritz,Resource management,2015.0,10.1109/ALLERTON.2015.7447154,"2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Bistritz2015,False,,IEEE,Not available,Asymptotically optimal distributed channel allocation: A competitive game-theoretic approach,e540851e38f0fb631a26e8e7c82dad36,https://ieeexplore.ieee.org/document/7447154/
8414,"In this paper we consider the problem of distributed channel allocation in large networks under the frequency-selective interference channel. Performance is measured by the weighted sum of achievable rates. First we present a natural non-cooperative game theoretic formulation for this problem. It is shown that, when interference is sufficiently strong, this game has a pure price of anarchy approaching infinity with high probability, and there is an asymptotically increasing number of equilibria with the worst performance. Then we propose a novel non-cooperative M Frequency-Selective Interference Game (M-FSIG), where users limit their utility such that it is greater than zero only for their M best channels, and equal for them. We show that the M-FSIG exhibits, with high probability, an increasing number of optimal pure Nash equilibria and no bad equilibria. Consequently, the pure price of anarchy converges to one in probability in any interference regime. In order to exploit these results algorithmically we propose a modified Fictitious Play algorithm that can be implemented distributedly. We carry out simulations that show its fast convergence to the proven pure Nash equilibria.",ilai bistritz,Transmitters,2015.0,10.1109/ALLERTON.2015.7447154,"2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Bistritz2015,False,,IEEE,Not available,Asymptotically optimal distributed channel allocation: A competitive game-theoretic approach,e540851e38f0fb631a26e8e7c82dad36,https://ieeexplore.ieee.org/document/7447154/
8415,"In this paper we consider the problem of distributed channel allocation in large networks under the frequency-selective interference channel. Performance is measured by the weighted sum of achievable rates. First we present a natural non-cooperative game theoretic formulation for this problem. It is shown that, when interference is sufficiently strong, this game has a pure price of anarchy approaching infinity with high probability, and there is an asymptotically increasing number of equilibria with the worst performance. Then we propose a novel non-cooperative M Frequency-Selective Interference Game (M-FSIG), where users limit their utility such that it is greater than zero only for their M best channels, and equal for them. We show that the M-FSIG exhibits, with high probability, an increasing number of optimal pure Nash equilibria and no bad equilibria. Consequently, the pure price of anarchy converges to one in probability in any interference regime. In order to exploit these results algorithmically we propose a modified Fictitious Play algorithm that can be implemented distributedly. We carry out simulations that show its fast convergence to the proven pure Nash equilibria.",amir leshem,Interference,2015.0,10.1109/ALLERTON.2015.7447154,"2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Bistritz2015,False,,IEEE,Not available,Asymptotically optimal distributed channel allocation: A competitive game-theoretic approach,e540851e38f0fb631a26e8e7c82dad36,https://ieeexplore.ieee.org/document/7447154/
8416,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
8417,"In this paper we consider the problem of distributed channel allocation in large networks under the frequency-selective interference channel. Performance is measured by the weighted sum of achievable rates. First we present a natural non-cooperative game theoretic formulation for this problem. It is shown that, when interference is sufficiently strong, this game has a pure price of anarchy approaching infinity with high probability, and there is an asymptotically increasing number of equilibria with the worst performance. Then we propose a novel non-cooperative M Frequency-Selective Interference Game (M-FSIG), where users limit their utility such that it is greater than zero only for their M best channels, and equal for them. We show that the M-FSIG exhibits, with high probability, an increasing number of optimal pure Nash equilibria and no bad equilibria. Consequently, the pure price of anarchy converges to one in probability in any interference regime. In order to exploit these results algorithmically we propose a modified Fictitious Play algorithm that can be implemented distributedly. We carry out simulations that show its fast convergence to the proven pure Nash equilibria.",amir leshem,Games,2015.0,10.1109/ALLERTON.2015.7447154,"2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Bistritz2015,False,,IEEE,Not available,Asymptotically optimal distributed channel allocation: A competitive game-theoretic approach,e540851e38f0fb631a26e8e7c82dad36,https://ieeexplore.ieee.org/document/7447154/
8418,"In this paper we consider the problem of distributed channel allocation in large networks under the frequency-selective interference channel. Performance is measured by the weighted sum of achievable rates. First we present a natural non-cooperative game theoretic formulation for this problem. It is shown that, when interference is sufficiently strong, this game has a pure price of anarchy approaching infinity with high probability, and there is an asymptotically increasing number of equilibria with the worst performance. Then we propose a novel non-cooperative M Frequency-Selective Interference Game (M-FSIG), where users limit their utility such that it is greater than zero only for their M best channels, and equal for them. We show that the M-FSIG exhibits, with high probability, an increasing number of optimal pure Nash equilibria and no bad equilibria. Consequently, the pure price of anarchy converges to one in probability in any interference regime. In order to exploit these results algorithmically we propose a modified Fictitious Play algorithm that can be implemented distributedly. We carry out simulations that show its fast convergence to the proven pure Nash equilibria.",amir leshem,Channel allocation,2015.0,10.1109/ALLERTON.2015.7447154,"2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Bistritz2015,False,,IEEE,Not available,Asymptotically optimal distributed channel allocation: A competitive game-theoretic approach,e540851e38f0fb631a26e8e7c82dad36,https://ieeexplore.ieee.org/document/7447154/
8419,"In this paper we consider the problem of distributed channel allocation in large networks under the frequency-selective interference channel. Performance is measured by the weighted sum of achievable rates. First we present a natural non-cooperative game theoretic formulation for this problem. It is shown that, when interference is sufficiently strong, this game has a pure price of anarchy approaching infinity with high probability, and there is an asymptotically increasing number of equilibria with the worst performance. Then we propose a novel non-cooperative M Frequency-Selective Interference Game (M-FSIG), where users limit their utility such that it is greater than zero only for their M best channels, and equal for them. We show that the M-FSIG exhibits, with high probability, an increasing number of optimal pure Nash equilibria and no bad equilibria. Consequently, the pure price of anarchy converges to one in probability in any interference regime. In order to exploit these results algorithmically we propose a modified Fictitious Play algorithm that can be implemented distributedly. We carry out simulations that show its fast convergence to the proven pure Nash equilibria.",amir leshem,Receivers,2015.0,10.1109/ALLERTON.2015.7447154,"2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Bistritz2015,False,,IEEE,Not available,Asymptotically optimal distributed channel allocation: A competitive game-theoretic approach,e540851e38f0fb631a26e8e7c82dad36,https://ieeexplore.ieee.org/document/7447154/
8420,"In this paper we consider the problem of distributed channel allocation in large networks under the frequency-selective interference channel. Performance is measured by the weighted sum of achievable rates. First we present a natural non-cooperative game theoretic formulation for this problem. It is shown that, when interference is sufficiently strong, this game has a pure price of anarchy approaching infinity with high probability, and there is an asymptotically increasing number of equilibria with the worst performance. Then we propose a novel non-cooperative M Frequency-Selective Interference Game (M-FSIG), where users limit their utility such that it is greater than zero only for their M best channels, and equal for them. We show that the M-FSIG exhibits, with high probability, an increasing number of optimal pure Nash equilibria and no bad equilibria. Consequently, the pure price of anarchy converges to one in probability in any interference regime. In order to exploit these results algorithmically we propose a modified Fictitious Play algorithm that can be implemented distributedly. We carry out simulations that show its fast convergence to the proven pure Nash equilibria.",amir leshem,Algorithm design and analysis,2015.0,10.1109/ALLERTON.2015.7447154,"2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Bistritz2015,False,,IEEE,Not available,Asymptotically optimal distributed channel allocation: A competitive game-theoretic approach,e540851e38f0fb631a26e8e7c82dad36,https://ieeexplore.ieee.org/document/7447154/
8421,"In this paper we consider the problem of distributed channel allocation in large networks under the frequency-selective interference channel. Performance is measured by the weighted sum of achievable rates. First we present a natural non-cooperative game theoretic formulation for this problem. It is shown that, when interference is sufficiently strong, this game has a pure price of anarchy approaching infinity with high probability, and there is an asymptotically increasing number of equilibria with the worst performance. Then we propose a novel non-cooperative M Frequency-Selective Interference Game (M-FSIG), where users limit their utility such that it is greater than zero only for their M best channels, and equal for them. We show that the M-FSIG exhibits, with high probability, an increasing number of optimal pure Nash equilibria and no bad equilibria. Consequently, the pure price of anarchy converges to one in probability in any interference regime. In order to exploit these results algorithmically we propose a modified Fictitious Play algorithm that can be implemented distributedly. We carry out simulations that show its fast convergence to the proven pure Nash equilibria.",amir leshem,Resource management,2015.0,10.1109/ALLERTON.2015.7447154,"2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Bistritz2015,False,,IEEE,Not available,Asymptotically optimal distributed channel allocation: A competitive game-theoretic approach,e540851e38f0fb631a26e8e7c82dad36,https://ieeexplore.ieee.org/document/7447154/
8422,"In this paper we consider the problem of distributed channel allocation in large networks under the frequency-selective interference channel. Performance is measured by the weighted sum of achievable rates. First we present a natural non-cooperative game theoretic formulation for this problem. It is shown that, when interference is sufficiently strong, this game has a pure price of anarchy approaching infinity with high probability, and there is an asymptotically increasing number of equilibria with the worst performance. Then we propose a novel non-cooperative M Frequency-Selective Interference Game (M-FSIG), where users limit their utility such that it is greater than zero only for their M best channels, and equal for them. We show that the M-FSIG exhibits, with high probability, an increasing number of optimal pure Nash equilibria and no bad equilibria. Consequently, the pure price of anarchy converges to one in probability in any interference regime. In order to exploit these results algorithmically we propose a modified Fictitious Play algorithm that can be implemented distributedly. We carry out simulations that show its fast convergence to the proven pure Nash equilibria.",amir leshem,Transmitters,2015.0,10.1109/ALLERTON.2015.7447154,"2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Bistritz2015,False,,IEEE,Not available,Asymptotically optimal distributed channel allocation: A competitive game-theoretic approach,e540851e38f0fb631a26e8e7c82dad36,https://ieeexplore.ieee.org/document/7447154/
8423,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",chandra chekuri,Nash equilibrium,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8424,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",chandra chekuri,Costs,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8425,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",chandra chekuri,Routing,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8426,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",chandra chekuri,Delay,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8427,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
8428,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",chandra chekuri,Computer science,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8429,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",chandra chekuri,Joining processes,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8430,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",chandra chekuri,Computational complexity,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8431,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",chandra chekuri,Upper bound,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8432,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",chandra chekuri,Polynomials,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8433,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",chandra chekuri,Multicast algorithms,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8434,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",julia chuzhoy,Nash equilibrium,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8435,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",julia chuzhoy,Costs,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8436,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",julia chuzhoy,Routing,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8437,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",julia chuzhoy,Delay,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8438,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
8439,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
8440,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",julia chuzhoy,Computer science,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8441,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",julia chuzhoy,Joining processes,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8442,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",julia chuzhoy,Computational complexity,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8443,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",julia chuzhoy,Upper bound,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8444,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",julia chuzhoy,Polynomials,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8445,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",julia chuzhoy,Multicast algorithms,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8446,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",liane lewin-eytan,Nash equilibrium,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8447,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",liane lewin-eytan,Costs,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8448,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",liane lewin-eytan,Routing,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8449,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",liane lewin-eytan,Delay,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8450,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
8451,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",liane lewin-eytan,Computer science,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8452,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",liane lewin-eytan,Joining processes,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8453,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",liane lewin-eytan,Computational complexity,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8454,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",liane lewin-eytan,Upper bound,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8455,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",liane lewin-eytan,Polynomials,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8456,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",liane lewin-eytan,Multicast algorithms,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8457,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",joseph naor,Nash equilibrium,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8458,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",joseph naor,Costs,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8459,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",joseph naor,Routing,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8460,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",joseph naor,Delay,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8461,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8462,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",joseph naor,Computer science,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8463,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",joseph naor,Joining processes,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8464,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",joseph naor,Computational complexity,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8465,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",joseph naor,Upper bound,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8466,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",joseph naor,Polynomials,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8467,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",joseph naor,Multicast algorithms,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8468,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",ariel orda,Nash equilibrium,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8469,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",ariel orda,Costs,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8470,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",ariel orda,Routing,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8471,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",ariel orda,Delay,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8472,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8473,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",ariel orda,Computer science,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8474,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",ariel orda,Joining processes,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8475,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",ariel orda,Computational complexity,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8476,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",ariel orda,Upper bound,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8477,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",ariel orda,Polynomials,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8478,"We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog&lt;sup&gt;2&lt;/sup&gt; n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.",ariel orda,Multicast algorithms,2007.0,10.1109/JSAC.2007.070813,IEEE Journal on Selected Areas in Communications,Chekuri2007,False,,IEEE,Not available,Non-Cooperative Multicast and Facility Location Games,a660e22c3265139cc21ddb63df35d4a0,https://ieeexplore.ieee.org/document/4278419/
8479,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",u. ayesta,Load management,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
8480,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",u. ayesta,Routing,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
8481,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",u. ayesta,Nash equilibrium,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
8482,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",u. ayesta,Network servers,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
8483,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8484,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",u. ayesta,Web server,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
8485,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",u. ayesta,Costs,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
8486,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",u. ayesta,Communications Society,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
8487,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",u. ayesta,Scalability,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
8488,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",u. ayesta,Computer architecture,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
8489,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",u. ayesta,Performance loss,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
8490,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",o. brun,Load management,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
8491,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",o. brun,Routing,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
8492,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",o. brun,Nash equilibrium,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
8493,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",o. brun,Network servers,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
8494,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8495,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",o. brun,Web server,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
8496,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",o. brun,Costs,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
8497,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",o. brun,Communications Society,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
8498,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",o. brun,Scalability,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
8499,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",o. brun,Computer architecture,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
8500,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",o. brun,Performance loss,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
8501,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",b. prabhu,Load management,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
8502,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",b. prabhu,Routing,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
8503,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",b. prabhu,Nash equilibrium,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
8504,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",b. prabhu,Network servers,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
8505,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8506,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",b. prabhu,Web server,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
8507,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",b. prabhu,Costs,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
8508,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",b. prabhu,Communications Society,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
8509,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",b. prabhu,Scalability,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
8510,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",b. prabhu,Computer architecture,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
8511,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",b. prabhu,Performance loss,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
8512,"Offloading computation to a mobile cloud is a promising solution to augment the computation capabilities of mobile devices. In this paper we consider selfish mobile devices in a dense wireless network, in which individual mobile devices can offload computations through multiple access points or through the base station to a mobile cloud so as to minimize their computation costs. We provide a game theoretical analysis of the problem, prove the existence of pure strategy Nash equilibria, and provide an efficient decentralized algorithm for computing an equilibrium. For the case when the cloud computing resources scale with the number of mobile devices we show that all improvement paths are finite. Furthermore, we provide an upper bound on the price of anarchy of the game, which serves as an upper bound on the approximation ratio of the proposed decentralized algorithms. We use simulations to evaluate the time complexity of computing Nash equilibria and to provide insights into the price of anarchy of the game under realistic scenarios. Our results show that the equilibrium cost may be close to optimal, and the convergence time is almost linear in the number of mobile devices.",sla&#x0111;ana jo&#x0161;ilo,computation offloading,,10.1109/TMC.2018.2829874,IEEE Transactions on Mobile Computing,Jo&#x0161;iloNone,False,,IEEE,Not available,Selfish Decentralized Computation Offloading for Mobile Cloud Computing in Dense Wireless Networks,0a9c0b8fbd74714739bfd0aa25fadff1,
8513,"Offloading computation to a mobile cloud is a promising solution to augment the computation capabilities of mobile devices. In this paper we consider selfish mobile devices in a dense wireless network, in which individual mobile devices can offload computations through multiple access points or through the base station to a mobile cloud so as to minimize their computation costs. We provide a game theoretical analysis of the problem, prove the existence of pure strategy Nash equilibria, and provide an efficient decentralized algorithm for computing an equilibrium. For the case when the cloud computing resources scale with the number of mobile devices we show that all improvement paths are finite. Furthermore, we provide an upper bound on the price of anarchy of the game, which serves as an upper bound on the approximation ratio of the proposed decentralized algorithms. We use simulations to evaluate the time complexity of computing Nash equilibria and to provide insights into the price of anarchy of the game under realistic scenarios. Our results show that the equilibrium cost may be close to optimal, and the convergence time is almost linear in the number of mobile devices.",sla&#x0111;ana jo&#x0161;ilo,mobile edge computing,,10.1109/TMC.2018.2829874,IEEE Transactions on Mobile Computing,Jo&#x0161;iloNone,False,,IEEE,Not available,Selfish Decentralized Computation Offloading for Mobile Cloud Computing in Dense Wireless Networks,0a9c0b8fbd74714739bfd0aa25fadff1,
8514,"Offloading computation to a mobile cloud is a promising solution to augment the computation capabilities of mobile devices. In this paper we consider selfish mobile devices in a dense wireless network, in which individual mobile devices can offload computations through multiple access points or through the base station to a mobile cloud so as to minimize their computation costs. We provide a game theoretical analysis of the problem, prove the existence of pure strategy Nash equilibria, and provide an efficient decentralized algorithm for computing an equilibrium. For the case when the cloud computing resources scale with the number of mobile devices we show that all improvement paths are finite. Furthermore, we provide an upper bound on the price of anarchy of the game, which serves as an upper bound on the approximation ratio of the proposed decentralized algorithms. We use simulations to evaluate the time complexity of computing Nash equilibria and to provide insights into the price of anarchy of the game under realistic scenarios. Our results show that the equilibrium cost may be close to optimal, and the convergence time is almost linear in the number of mobile devices.",sla&#x0111;ana jo&#x0161;ilo,Nash equilibria,,10.1109/TMC.2018.2829874,IEEE Transactions on Mobile Computing,Jo&#x0161;iloNone,False,,IEEE,Not available,Selfish Decentralized Computation Offloading for Mobile Cloud Computing in Dense Wireless Networks,0a9c0b8fbd74714739bfd0aa25fadff1,
8515,"Offloading computation to a mobile cloud is a promising solution to augment the computation capabilities of mobile devices. In this paper we consider selfish mobile devices in a dense wireless network, in which individual mobile devices can offload computations through multiple access points or through the base station to a mobile cloud so as to minimize their computation costs. We provide a game theoretical analysis of the problem, prove the existence of pure strategy Nash equilibria, and provide an efficient decentralized algorithm for computing an equilibrium. For the case when the cloud computing resources scale with the number of mobile devices we show that all improvement paths are finite. Furthermore, we provide an upper bound on the price of anarchy of the game, which serves as an upper bound on the approximation ratio of the proposed decentralized algorithms. We use simulations to evaluate the time complexity of computing Nash equilibria and to provide insights into the price of anarchy of the game under realistic scenarios. Our results show that the equilibrium cost may be close to optimal, and the convergence time is almost linear in the number of mobile devices.",sla&#x0111;ana jo&#x0161;ilo,decentralized algorithms,,10.1109/TMC.2018.2829874,IEEE Transactions on Mobile Computing,Jo&#x0161;iloNone,False,,IEEE,Not available,Selfish Decentralized Computation Offloading for Mobile Cloud Computing in Dense Wireless Networks,0a9c0b8fbd74714739bfd0aa25fadff1,
8516,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8517,"Offloading computation to a mobile cloud is a promising solution to augment the computation capabilities of mobile devices. In this paper we consider selfish mobile devices in a dense wireless network, in which individual mobile devices can offload computations through multiple access points or through the base station to a mobile cloud so as to minimize their computation costs. We provide a game theoretical analysis of the problem, prove the existence of pure strategy Nash equilibria, and provide an efficient decentralized algorithm for computing an equilibrium. For the case when the cloud computing resources scale with the number of mobile devices we show that all improvement paths are finite. Furthermore, we provide an upper bound on the price of anarchy of the game, which serves as an upper bound on the approximation ratio of the proposed decentralized algorithms. We use simulations to evaluate the time complexity of computing Nash equilibria and to provide insights into the price of anarchy of the game under realistic scenarios. Our results show that the equilibrium cost may be close to optimal, and the convergence time is almost linear in the number of mobile devices.",gyorgy dan,computation offloading,,10.1109/TMC.2018.2829874,IEEE Transactions on Mobile Computing,Jo&#x0161;iloNone,False,,IEEE,Not available,Selfish Decentralized Computation Offloading for Mobile Cloud Computing in Dense Wireless Networks,0a9c0b8fbd74714739bfd0aa25fadff1,
8518,"Offloading computation to a mobile cloud is a promising solution to augment the computation capabilities of mobile devices. In this paper we consider selfish mobile devices in a dense wireless network, in which individual mobile devices can offload computations through multiple access points or through the base station to a mobile cloud so as to minimize their computation costs. We provide a game theoretical analysis of the problem, prove the existence of pure strategy Nash equilibria, and provide an efficient decentralized algorithm for computing an equilibrium. For the case when the cloud computing resources scale with the number of mobile devices we show that all improvement paths are finite. Furthermore, we provide an upper bound on the price of anarchy of the game, which serves as an upper bound on the approximation ratio of the proposed decentralized algorithms. We use simulations to evaluate the time complexity of computing Nash equilibria and to provide insights into the price of anarchy of the game under realistic scenarios. Our results show that the equilibrium cost may be close to optimal, and the convergence time is almost linear in the number of mobile devices.",gyorgy dan,mobile edge computing,,10.1109/TMC.2018.2829874,IEEE Transactions on Mobile Computing,Jo&#x0161;iloNone,False,,IEEE,Not available,Selfish Decentralized Computation Offloading for Mobile Cloud Computing in Dense Wireless Networks,0a9c0b8fbd74714739bfd0aa25fadff1,
8519,"Offloading computation to a mobile cloud is a promising solution to augment the computation capabilities of mobile devices. In this paper we consider selfish mobile devices in a dense wireless network, in which individual mobile devices can offload computations through multiple access points or through the base station to a mobile cloud so as to minimize their computation costs. We provide a game theoretical analysis of the problem, prove the existence of pure strategy Nash equilibria, and provide an efficient decentralized algorithm for computing an equilibrium. For the case when the cloud computing resources scale with the number of mobile devices we show that all improvement paths are finite. Furthermore, we provide an upper bound on the price of anarchy of the game, which serves as an upper bound on the approximation ratio of the proposed decentralized algorithms. We use simulations to evaluate the time complexity of computing Nash equilibria and to provide insights into the price of anarchy of the game under realistic scenarios. Our results show that the equilibrium cost may be close to optimal, and the convergence time is almost linear in the number of mobile devices.",gyorgy dan,Nash equilibria,,10.1109/TMC.2018.2829874,IEEE Transactions on Mobile Computing,Jo&#x0161;iloNone,False,,IEEE,Not available,Selfish Decentralized Computation Offloading for Mobile Cloud Computing in Dense Wireless Networks,0a9c0b8fbd74714739bfd0aa25fadff1,
8520,"Offloading computation to a mobile cloud is a promising solution to augment the computation capabilities of mobile devices. In this paper we consider selfish mobile devices in a dense wireless network, in which individual mobile devices can offload computations through multiple access points or through the base station to a mobile cloud so as to minimize their computation costs. We provide a game theoretical analysis of the problem, prove the existence of pure strategy Nash equilibria, and provide an efficient decentralized algorithm for computing an equilibrium. For the case when the cloud computing resources scale with the number of mobile devices we show that all improvement paths are finite. Furthermore, we provide an upper bound on the price of anarchy of the game, which serves as an upper bound on the approximation ratio of the proposed decentralized algorithms. We use simulations to evaluate the time complexity of computing Nash equilibria and to provide insights into the price of anarchy of the game under realistic scenarios. Our results show that the equilibrium cost may be close to optimal, and the convergence time is almost linear in the number of mobile devices.",gyorgy dan,decentralized algorithms,,10.1109/TMC.2018.2829874,IEEE Transactions on Mobile Computing,Jo&#x0161;iloNone,False,,IEEE,Not available,Selfish Decentralized Computation Offloading for Mobile Cloud Computing in Dense Wireless Networks,0a9c0b8fbd74714739bfd0aa25fadff1,
8521,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The degradation in performance due to the lack of regulation is measured by the Price of Anarchy (POA), which is defined as the ratio between the cost of the worst possible Wardrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Toward establishing this result, we first characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. Next, we show that the Wardrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt;; 1 and determine near-tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy.",aditya ramamoorthy,Distributed source coding,2012.0,10.1109/TIT.2012.2184660,IEEE Transactions on Information Theory,Ramamoorthy2012,False,,IEEE,Not available,Selfish Distributed Compression Over Networks: Correlation Induces Anarchy,047e59363aaf2dc243cdd1e6c38419be,https://ieeexplore.ieee.org/document/6142086/
8522,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The degradation in performance due to the lack of regulation is measured by the Price of Anarchy (POA), which is defined as the ratio between the cost of the worst possible Wardrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Toward establishing this result, we first characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. Next, we show that the Wardrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt;; 1 and determine near-tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy.",aditya ramamoorthy,game theory,2012.0,10.1109/TIT.2012.2184660,IEEE Transactions on Information Theory,Ramamoorthy2012,False,,IEEE,Not available,Selfish Distributed Compression Over Networks: Correlation Induces Anarchy,047e59363aaf2dc243cdd1e6c38419be,https://ieeexplore.ieee.org/document/6142086/
8523,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The degradation in performance due to the lack of regulation is measured by the Price of Anarchy (POA), which is defined as the ratio between the cost of the worst possible Wardrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Toward establishing this result, we first characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. Next, we show that the Wardrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt;; 1 and determine near-tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy.",aditya ramamoorthy,multicast,2012.0,10.1109/TIT.2012.2184660,IEEE Transactions on Information Theory,Ramamoorthy2012,False,,IEEE,Not available,Selfish Distributed Compression Over Networks: Correlation Induces Anarchy,047e59363aaf2dc243cdd1e6c38419be,https://ieeexplore.ieee.org/document/6142086/
8524,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The degradation in performance due to the lack of regulation is measured by the Price of Anarchy (POA), which is defined as the ratio between the cost of the worst possible Wardrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Toward establishing this result, we first characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. Next, we show that the Wardrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt;; 1 and determine near-tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy.",aditya ramamoorthy,network coding,2012.0,10.1109/TIT.2012.2184660,IEEE Transactions on Information Theory,Ramamoorthy2012,False,,IEEE,Not available,Selfish Distributed Compression Over Networks: Correlation Induces Anarchy,047e59363aaf2dc243cdd1e6c38419be,https://ieeexplore.ieee.org/document/6142086/
8525,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The degradation in performance due to the lack of regulation is measured by the Price of Anarchy (POA), which is defined as the ratio between the cost of the worst possible Wardrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Toward establishing this result, we first characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. Next, we show that the Wardrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt;; 1 and determine near-tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy.",aditya ramamoorthy,selfish behavior,2012.0,10.1109/TIT.2012.2184660,IEEE Transactions on Information Theory,Ramamoorthy2012,False,,IEEE,Not available,Selfish Distributed Compression Over Networks: Correlation Induces Anarchy,047e59363aaf2dc243cdd1e6c38419be,https://ieeexplore.ieee.org/document/6142086/
8526,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The degradation in performance due to the lack of regulation is measured by the Price of Anarchy (POA), which is defined as the ratio between the cost of the worst possible Wardrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Toward establishing this result, we first characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. Next, we show that the Wardrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt;; 1 and determine near-tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy.",vwani roychowdhury,Distributed source coding,2012.0,10.1109/TIT.2012.2184660,IEEE Transactions on Information Theory,Ramamoorthy2012,False,,IEEE,Not available,Selfish Distributed Compression Over Networks: Correlation Induces Anarchy,047e59363aaf2dc243cdd1e6c38419be,https://ieeexplore.ieee.org/document/6142086/
8527,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8528,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The degradation in performance due to the lack of regulation is measured by the Price of Anarchy (POA), which is defined as the ratio between the cost of the worst possible Wardrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Toward establishing this result, we first characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. Next, we show that the Wardrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt;; 1 and determine near-tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy.",vwani roychowdhury,game theory,2012.0,10.1109/TIT.2012.2184660,IEEE Transactions on Information Theory,Ramamoorthy2012,False,,IEEE,Not available,Selfish Distributed Compression Over Networks: Correlation Induces Anarchy,047e59363aaf2dc243cdd1e6c38419be,https://ieeexplore.ieee.org/document/6142086/
8529,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The degradation in performance due to the lack of regulation is measured by the Price of Anarchy (POA), which is defined as the ratio between the cost of the worst possible Wardrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Toward establishing this result, we first characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. Next, we show that the Wardrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt;; 1 and determine near-tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy.",vwani roychowdhury,multicast,2012.0,10.1109/TIT.2012.2184660,IEEE Transactions on Information Theory,Ramamoorthy2012,False,,IEEE,Not available,Selfish Distributed Compression Over Networks: Correlation Induces Anarchy,047e59363aaf2dc243cdd1e6c38419be,https://ieeexplore.ieee.org/document/6142086/
8530,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The degradation in performance due to the lack of regulation is measured by the Price of Anarchy (POA), which is defined as the ratio between the cost of the worst possible Wardrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Toward establishing this result, we first characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. Next, we show that the Wardrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt;; 1 and determine near-tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy.",vwani roychowdhury,network coding,2012.0,10.1109/TIT.2012.2184660,IEEE Transactions on Information Theory,Ramamoorthy2012,False,,IEEE,Not available,Selfish Distributed Compression Over Networks: Correlation Induces Anarchy,047e59363aaf2dc243cdd1e6c38419be,https://ieeexplore.ieee.org/document/6142086/
8531,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The degradation in performance due to the lack of regulation is measured by the Price of Anarchy (POA), which is defined as the ratio between the cost of the worst possible Wardrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Toward establishing this result, we first characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. Next, we show that the Wardrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt;; 1 and determine near-tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy.",vwani roychowdhury,selfish behavior,2012.0,10.1109/TIT.2012.2184660,IEEE Transactions on Information Theory,Ramamoorthy2012,False,,IEEE,Not available,Selfish Distributed Compression Over Networks: Correlation Induces Anarchy,047e59363aaf2dc243cdd1e6c38419be,https://ieeexplore.ieee.org/document/6142086/
8532,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The degradation in performance due to the lack of regulation is measured by the Price of Anarchy (POA), which is defined as the ratio between the cost of the worst possible Wardrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Toward establishing this result, we first characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. Next, we show that the Wardrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt;; 1 and determine near-tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy.",sudhir singh,Distributed source coding,2012.0,10.1109/TIT.2012.2184660,IEEE Transactions on Information Theory,Ramamoorthy2012,False,,IEEE,Not available,Selfish Distributed Compression Over Networks: Correlation Induces Anarchy,047e59363aaf2dc243cdd1e6c38419be,https://ieeexplore.ieee.org/document/6142086/
8533,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The degradation in performance due to the lack of regulation is measured by the Price of Anarchy (POA), which is defined as the ratio between the cost of the worst possible Wardrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Toward establishing this result, we first characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. Next, we show that the Wardrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt;; 1 and determine near-tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy.",sudhir singh,game theory,2012.0,10.1109/TIT.2012.2184660,IEEE Transactions on Information Theory,Ramamoorthy2012,False,,IEEE,Not available,Selfish Distributed Compression Over Networks: Correlation Induces Anarchy,047e59363aaf2dc243cdd1e6c38419be,https://ieeexplore.ieee.org/document/6142086/
8534,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The degradation in performance due to the lack of regulation is measured by the Price of Anarchy (POA), which is defined as the ratio between the cost of the worst possible Wardrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Toward establishing this result, we first characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. Next, we show that the Wardrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt;; 1 and determine near-tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy.",sudhir singh,multicast,2012.0,10.1109/TIT.2012.2184660,IEEE Transactions on Information Theory,Ramamoorthy2012,False,,IEEE,Not available,Selfish Distributed Compression Over Networks: Correlation Induces Anarchy,047e59363aaf2dc243cdd1e6c38419be,https://ieeexplore.ieee.org/document/6142086/
8535,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The degradation in performance due to the lack of regulation is measured by the Price of Anarchy (POA), which is defined as the ratio between the cost of the worst possible Wardrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Toward establishing this result, we first characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. Next, we show that the Wardrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt;; 1 and determine near-tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy.",sudhir singh,network coding,2012.0,10.1109/TIT.2012.2184660,IEEE Transactions on Information Theory,Ramamoorthy2012,False,,IEEE,Not available,Selfish Distributed Compression Over Networks: Correlation Induces Anarchy,047e59363aaf2dc243cdd1e6c38419be,https://ieeexplore.ieee.org/document/6142086/
8536,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The degradation in performance due to the lack of regulation is measured by the Price of Anarchy (POA), which is defined as the ratio between the cost of the worst possible Wardrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Toward establishing this result, we first characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. Next, we show that the Wardrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt;; 1 and determine near-tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy.",sudhir singh,selfish behavior,2012.0,10.1109/TIT.2012.2184660,IEEE Transactions on Information Theory,Ramamoorthy2012,False,,IEEE,Not available,Selfish Distributed Compression Over Networks: Correlation Induces Anarchy,047e59363aaf2dc243cdd1e6c38419be,https://ieeexplore.ieee.org/document/6142086/
8537,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",a. kesselman,Energy efficiency,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
8538,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8539,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",a. kesselman,Ad hoc networks,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
8540,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",a. kesselman,Multimedia communication,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
8541,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",a. kesselman,Mobile ad hoc networks,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
8542,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",a. kesselman,Delay,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
8543,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",a. kesselman,Costs,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
8544,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",a. kesselman,Power system modeling,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
8545,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",a. kesselman,System performance,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
8546,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",a. kesselman,Broadcasting,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
8547,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",a. kesselman,Degradation,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
8548,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",d. kowalski,Energy efficiency,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
8549,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
8550,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8551,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",d. kowalski,Ad hoc networks,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
8552,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",d. kowalski,Multimedia communication,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
8553,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",d. kowalski,Mobile ad hoc networks,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
8554,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",d. kowalski,Delay,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
8555,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",d. kowalski,Costs,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
8556,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",d. kowalski,Power system modeling,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
8557,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",d. kowalski,System performance,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
8558,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",d. kowalski,Broadcasting,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
8559,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",d. kowalski,Degradation,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
8560,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",m. segal,Energy efficiency,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
8561,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8562,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",m. segal,Ad hoc networks,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
8563,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",m. segal,Multimedia communication,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
8564,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",m. segal,Mobile ad hoc networks,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
8565,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",m. segal,Delay,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
8566,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",m. segal,Costs,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
8567,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",m. segal,Power system modeling,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
8568,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",m. segal,System performance,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
8569,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",m. segal,Broadcasting,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
8570,"We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.",m. segal,Degradation,2005.0,10.1109/ICC.2005.1494993,"IEEE International Conference on Communications, 2005. ICC 2005. 2005",Kesselman2005,False,,IEEE,Not available,Energy efficient connectivity in ad hoc networks from user's and designer's perspective,259b194b57e060a37482997cd9c788bb,https://ieeexplore.ieee.org/document/1494993/
8571,"We consider in this paper a simple model for human interactions as service providers of different resources over social networks, and study the dynamics of selfish behavior of such social entities using a game-theoretic model known as binary-preference capacitated selfish replication (CSR) game. It is known that such games have an associated ordinal potential function, and hence always admit a pure-strategy Nash equilibrium (NE). We study the price of anarchy of such games, and show that it is bounded above by 3; we further provide some instances for which the price of anarchy is at least 2. We also devise a quasi-polynomial algorithm O(n2+ln D) which can find, in a distributed manner, an allocation profile that is within a constant factor of the optimal allocation, and hence of any pure-strategy Nash equilibrium of the game, where the parameters n, and D denote, respectively, the number of players, and the diameter of the network. We further show that when the underlying network has a tree structure, every globally optimal allocation is a Nash equilibrium, which can be reached in only linear time.",seyed etesami,Capacitated selfish replication game,2015.0,10.1109/CDC.2015.7402771,2015 54th IEEE Conference on Decision and Control (CDC),Etesami2015,False,,IEEE,Not available,An approximation algorithm and price of anarchy for the binary-preference capacitated selfish replication game,c2ff2ca30f60e4aaa6132bc41aa2be69,https://ieeexplore.ieee.org/document/7402771/
8572,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8573,"We consider in this paper a simple model for human interactions as service providers of different resources over social networks, and study the dynamics of selfish behavior of such social entities using a game-theoretic model known as binary-preference capacitated selfish replication (CSR) game. It is known that such games have an associated ordinal potential function, and hence always admit a pure-strategy Nash equilibrium (NE). We study the price of anarchy of such games, and show that it is bounded above by 3; we further provide some instances for which the price of anarchy is at least 2. We also devise a quasi-polynomial algorithm O(n2+ln D) which can find, in a distributed manner, an allocation profile that is within a constant factor of the optimal allocation, and hence of any pure-strategy Nash equilibrium of the game, where the parameters n, and D denote, respectively, the number of players, and the diameter of the network. We further show that when the underlying network has a tree structure, every globally optimal allocation is a Nash equilibrium, which can be reached in only linear time.",seyed etesami,pure Nash equilibrium (NE),2015.0,10.1109/CDC.2015.7402771,2015 54th IEEE Conference on Decision and Control (CDC),Etesami2015,False,,IEEE,Not available,An approximation algorithm and price of anarchy for the binary-preference capacitated selfish replication game,c2ff2ca30f60e4aaa6132bc41aa2be69,https://ieeexplore.ieee.org/document/7402771/
8574,"We consider in this paper a simple model for human interactions as service providers of different resources over social networks, and study the dynamics of selfish behavior of such social entities using a game-theoretic model known as binary-preference capacitated selfish replication (CSR) game. It is known that such games have an associated ordinal potential function, and hence always admit a pure-strategy Nash equilibrium (NE). We study the price of anarchy of such games, and show that it is bounded above by 3; we further provide some instances for which the price of anarchy is at least 2. We also devise a quasi-polynomial algorithm O(n2+ln D) which can find, in a distributed manner, an allocation profile that is within a constant factor of the optimal allocation, and hence of any pure-strategy Nash equilibrium of the game, where the parameters n, and D denote, respectively, the number of players, and the diameter of the network. We further show that when the underlying network has a tree structure, every globally optimal allocation is a Nash equilibrium, which can be reached in only linear time.",seyed etesami,potential function,2015.0,10.1109/CDC.2015.7402771,2015 54th IEEE Conference on Decision and Control (CDC),Etesami2015,False,,IEEE,Not available,An approximation algorithm and price of anarchy for the binary-preference capacitated selfish replication game,c2ff2ca30f60e4aaa6132bc41aa2be69,https://ieeexplore.ieee.org/document/7402771/
8575,"We consider in this paper a simple model for human interactions as service providers of different resources over social networks, and study the dynamics of selfish behavior of such social entities using a game-theoretic model known as binary-preference capacitated selfish replication (CSR) game. It is known that such games have an associated ordinal potential function, and hence always admit a pure-strategy Nash equilibrium (NE). We study the price of anarchy of such games, and show that it is bounded above by 3; we further provide some instances for which the price of anarchy is at least 2. We also devise a quasi-polynomial algorithm O(n2+ln D) which can find, in a distributed manner, an allocation profile that is within a constant factor of the optimal allocation, and hence of any pure-strategy Nash equilibrium of the game, where the parameters n, and D denote, respectively, the number of players, and the diameter of the network. We further show that when the underlying network has a tree structure, every globally optimal allocation is a Nash equilibrium, which can be reached in only linear time.",seyed etesami,quasi-polynomial algorithm,2015.0,10.1109/CDC.2015.7402771,2015 54th IEEE Conference on Decision and Control (CDC),Etesami2015,False,,IEEE,Not available,An approximation algorithm and price of anarchy for the binary-preference capacitated selfish replication game,c2ff2ca30f60e4aaa6132bc41aa2be69,https://ieeexplore.ieee.org/document/7402771/
8576,"We consider in this paper a simple model for human interactions as service providers of different resources over social networks, and study the dynamics of selfish behavior of such social entities using a game-theoretic model known as binary-preference capacitated selfish replication (CSR) game. It is known that such games have an associated ordinal potential function, and hence always admit a pure-strategy Nash equilibrium (NE). We study the price of anarchy of such games, and show that it is bounded above by 3; we further provide some instances for which the price of anarchy is at least 2. We also devise a quasi-polynomial algorithm O(n2+ln D) which can find, in a distributed manner, an allocation profile that is within a constant factor of the optimal allocation, and hence of any pure-strategy Nash equilibrium of the game, where the parameters n, and D denote, respectively, the number of players, and the diameter of the network. We further show that when the underlying network has a tree structure, every globally optimal allocation is a Nash equilibrium, which can be reached in only linear time.",seyed etesami,price of anarchy,2015.0,10.1109/CDC.2015.7402771,2015 54th IEEE Conference on Decision and Control (CDC),Etesami2015,False,,IEEE,Not available,An approximation algorithm and price of anarchy for the binary-preference capacitated selfish replication game,c2ff2ca30f60e4aaa6132bc41aa2be69,https://ieeexplore.ieee.org/document/7402771/
8577,"We consider in this paper a simple model for human interactions as service providers of different resources over social networks, and study the dynamics of selfish behavior of such social entities using a game-theoretic model known as binary-preference capacitated selfish replication (CSR) game. It is known that such games have an associated ordinal potential function, and hence always admit a pure-strategy Nash equilibrium (NE). We study the price of anarchy of such games, and show that it is bounded above by 3; we further provide some instances for which the price of anarchy is at least 2. We also devise a quasi-polynomial algorithm O(n2+ln D) which can find, in a distributed manner, an allocation profile that is within a constant factor of the optimal allocation, and hence of any pure-strategy Nash equilibrium of the game, where the parameters n, and D denote, respectively, the number of players, and the diameter of the network. We further show that when the underlying network has a tree structure, every globally optimal allocation is a Nash equilibrium, which can be reached in only linear time.",seyed etesami,optimal allocation,2015.0,10.1109/CDC.2015.7402771,2015 54th IEEE Conference on Decision and Control (CDC),Etesami2015,False,,IEEE,Not available,An approximation algorithm and price of anarchy for the binary-preference capacitated selfish replication game,c2ff2ca30f60e4aaa6132bc41aa2be69,https://ieeexplore.ieee.org/document/7402771/
8578,"We consider in this paper a simple model for human interactions as service providers of different resources over social networks, and study the dynamics of selfish behavior of such social entities using a game-theoretic model known as binary-preference capacitated selfish replication (CSR) game. It is known that such games have an associated ordinal potential function, and hence always admit a pure-strategy Nash equilibrium (NE). We study the price of anarchy of such games, and show that it is bounded above by 3; we further provide some instances for which the price of anarchy is at least 2. We also devise a quasi-polynomial algorithm O(n2+ln D) which can find, in a distributed manner, an allocation profile that is within a constant factor of the optimal allocation, and hence of any pure-strategy Nash equilibrium of the game, where the parameters n, and D denote, respectively, the number of players, and the diameter of the network. We further show that when the underlying network has a tree structure, every globally optimal allocation is a Nash equilibrium, which can be reached in only linear time.",tamer ba&#x015f;ar,Capacitated selfish replication game,2015.0,10.1109/CDC.2015.7402771,2015 54th IEEE Conference on Decision and Control (CDC),Etesami2015,False,,IEEE,Not available,An approximation algorithm and price of anarchy for the binary-preference capacitated selfish replication game,c2ff2ca30f60e4aaa6132bc41aa2be69,https://ieeexplore.ieee.org/document/7402771/
8579,"We consider in this paper a simple model for human interactions as service providers of different resources over social networks, and study the dynamics of selfish behavior of such social entities using a game-theoretic model known as binary-preference capacitated selfish replication (CSR) game. It is known that such games have an associated ordinal potential function, and hence always admit a pure-strategy Nash equilibrium (NE). We study the price of anarchy of such games, and show that it is bounded above by 3; we further provide some instances for which the price of anarchy is at least 2. We also devise a quasi-polynomial algorithm O(n2+ln D) which can find, in a distributed manner, an allocation profile that is within a constant factor of the optimal allocation, and hence of any pure-strategy Nash equilibrium of the game, where the parameters n, and D denote, respectively, the number of players, and the diameter of the network. We further show that when the underlying network has a tree structure, every globally optimal allocation is a Nash equilibrium, which can be reached in only linear time.",tamer ba&#x015f;ar,pure Nash equilibrium (NE),2015.0,10.1109/CDC.2015.7402771,2015 54th IEEE Conference on Decision and Control (CDC),Etesami2015,False,,IEEE,Not available,An approximation algorithm and price of anarchy for the binary-preference capacitated selfish replication game,c2ff2ca30f60e4aaa6132bc41aa2be69,https://ieeexplore.ieee.org/document/7402771/
8580,"We consider in this paper a simple model for human interactions as service providers of different resources over social networks, and study the dynamics of selfish behavior of such social entities using a game-theoretic model known as binary-preference capacitated selfish replication (CSR) game. It is known that such games have an associated ordinal potential function, and hence always admit a pure-strategy Nash equilibrium (NE). We study the price of anarchy of such games, and show that it is bounded above by 3; we further provide some instances for which the price of anarchy is at least 2. We also devise a quasi-polynomial algorithm O(n2+ln D) which can find, in a distributed manner, an allocation profile that is within a constant factor of the optimal allocation, and hence of any pure-strategy Nash equilibrium of the game, where the parameters n, and D denote, respectively, the number of players, and the diameter of the network. We further show that when the underlying network has a tree structure, every globally optimal allocation is a Nash equilibrium, which can be reached in only linear time.",tamer ba&#x015f;ar,potential function,2015.0,10.1109/CDC.2015.7402771,2015 54th IEEE Conference on Decision and Control (CDC),Etesami2015,False,,IEEE,Not available,An approximation algorithm and price of anarchy for the binary-preference capacitated selfish replication game,c2ff2ca30f60e4aaa6132bc41aa2be69,https://ieeexplore.ieee.org/document/7402771/
8581,"We consider in this paper a simple model for human interactions as service providers of different resources over social networks, and study the dynamics of selfish behavior of such social entities using a game-theoretic model known as binary-preference capacitated selfish replication (CSR) game. It is known that such games have an associated ordinal potential function, and hence always admit a pure-strategy Nash equilibrium (NE). We study the price of anarchy of such games, and show that it is bounded above by 3; we further provide some instances for which the price of anarchy is at least 2. We also devise a quasi-polynomial algorithm O(n2+ln D) which can find, in a distributed manner, an allocation profile that is within a constant factor of the optimal allocation, and hence of any pure-strategy Nash equilibrium of the game, where the parameters n, and D denote, respectively, the number of players, and the diameter of the network. We further show that when the underlying network has a tree structure, every globally optimal allocation is a Nash equilibrium, which can be reached in only linear time.",tamer ba&#x015f;ar,quasi-polynomial algorithm,2015.0,10.1109/CDC.2015.7402771,2015 54th IEEE Conference on Decision and Control (CDC),Etesami2015,False,,IEEE,Not available,An approximation algorithm and price of anarchy for the binary-preference capacitated selfish replication game,c2ff2ca30f60e4aaa6132bc41aa2be69,https://ieeexplore.ieee.org/document/7402771/
8582,"We consider in this paper a simple model for human interactions as service providers of different resources over social networks, and study the dynamics of selfish behavior of such social entities using a game-theoretic model known as binary-preference capacitated selfish replication (CSR) game. It is known that such games have an associated ordinal potential function, and hence always admit a pure-strategy Nash equilibrium (NE). We study the price of anarchy of such games, and show that it is bounded above by 3; we further provide some instances for which the price of anarchy is at least 2. We also devise a quasi-polynomial algorithm O(n2+ln D) which can find, in a distributed manner, an allocation profile that is within a constant factor of the optimal allocation, and hence of any pure-strategy Nash equilibrium of the game, where the parameters n, and D denote, respectively, the number of players, and the diameter of the network. We further show that when the underlying network has a tree structure, every globally optimal allocation is a Nash equilibrium, which can be reached in only linear time.",tamer ba&#x015f;ar,price of anarchy,2015.0,10.1109/CDC.2015.7402771,2015 54th IEEE Conference on Decision and Control (CDC),Etesami2015,False,,IEEE,Not available,An approximation algorithm and price of anarchy for the binary-preference capacitated selfish replication game,c2ff2ca30f60e4aaa6132bc41aa2be69,https://ieeexplore.ieee.org/document/7402771/
8583,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8584,"We consider in this paper a simple model for human interactions as service providers of different resources over social networks, and study the dynamics of selfish behavior of such social entities using a game-theoretic model known as binary-preference capacitated selfish replication (CSR) game. It is known that such games have an associated ordinal potential function, and hence always admit a pure-strategy Nash equilibrium (NE). We study the price of anarchy of such games, and show that it is bounded above by 3; we further provide some instances for which the price of anarchy is at least 2. We also devise a quasi-polynomial algorithm O(n2+ln D) which can find, in a distributed manner, an allocation profile that is within a constant factor of the optimal allocation, and hence of any pure-strategy Nash equilibrium of the game, where the parameters n, and D denote, respectively, the number of players, and the diameter of the network. We further show that when the underlying network has a tree structure, every globally optimal allocation is a Nash equilibrium, which can be reached in only linear time.",tamer ba&#x015f;ar,optimal allocation,2015.0,10.1109/CDC.2015.7402771,2015 54th IEEE Conference on Decision and Control (CDC),Etesami2015,False,,IEEE,Not available,An approximation algorithm and price of anarchy for the binary-preference capacitated selfish replication game,c2ff2ca30f60e4aaa6132bc41aa2be69,https://ieeexplore.ieee.org/document/7402771/
8585,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",a. ramamoorthy,Network coding,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
8586,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",a. ramamoorthy,Cost function,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
8587,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",a. ramamoorthy,Source coding,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
8588,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",a. ramamoorthy,Lagrangian functions,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
8589,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",a. ramamoorthy,Entropy,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
8590,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",a. ramamoorthy,Communications Society,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
8591,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",a. ramamoorthy,Nash equilibrium,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
8592,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",a. ramamoorthy,Degradation,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
8593,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",a. ramamoorthy,Upper bound,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
8594,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8595,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",a. ramamoorthy,Large-scale systems,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
8596,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",v. roychowdhury,Network coding,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
8597,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",v. roychowdhury,Cost function,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
8598,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",v. roychowdhury,Source coding,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
8599,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",v. roychowdhury,Lagrangian functions,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
8600,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",v. roychowdhury,Entropy,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
8601,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",v. roychowdhury,Communications Society,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
8602,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",v. roychowdhury,Nash equilibrium,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
8603,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",v. roychowdhury,Degradation,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
8604,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",v. roychowdhury,Upper bound,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
8605,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8606,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",v. roychowdhury,Large-scale systems,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
8607,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",s. singh,Network coding,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
8608,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",s. singh,Cost function,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
8609,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",s. singh,Source coding,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
8610,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",s. singh,Lagrangian functions,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
8611,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",s. singh,Entropy,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
8612,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",s. singh,Communications Society,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
8613,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",s. singh,Nash equilibrium,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
8614,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",s. singh,Degradation,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
8615,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",s. singh,Upper bound,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
8616,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8617,"We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. This can be considered as the network generalization of the classical distributed source coding (Slepian-Wolf) problem. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The solution concept that we adopt for this game is the popular local Nash equilibrium (Waldrop equilibrium) adapted for the scenario with multiple sources. The degradation in performance due to the lack of regulation is measured by the price of anarchy (POA), which is defined as the ratio between the cost of the worst possible Waldrop equilibrium and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result we make several contributions. We characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. This result is a key technical contribution of this paper and is of independent interest as well. Next, we show that the Waldrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA &amp;gt; 1 and determine near- tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy. Finally, all the techniques and results in this paper will naturally extend to a large class of network information flow problems where the Slepian-Wolf polytope is replaced by any contra-polymatroid (or more generally polymatroid-like set), leading to a nice class of succinct multi-player games and allow the investigation of other practical and meaningful scenarios beyond network coding as well.",s. singh,Large-scale systems,2009.0,10.1109/INFCOM.2009.5062277,IEEE INFOCOM 2009,Ramamoorthy2009,False,,IEEE,Not available,Selfish Distributed Compression over Networks,be2c0c9132c670ef33c6fb3a4d7a2205,https://ieeexplore.ieee.org/document/5062277/
8618,"Contention among users utilizing a single shared resource arises in multiple contexts of computing and computer communications. We consider a setup in which users can split their work between a shared resource and a private resource. Unlike the private resource, which provides guaranteed performance, the performance of the shared resource is highly dependent on the usage pattern of other users, which in turn influences a user's decision if and to what extent to make use of the shared resource. The intrinsic relation between the utility that a user perceives from the shared resource and the usage pattern followed by other users gives rise to a noncooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the ratio between the worst Nash equilibrium and the social optimum, known as the “price of anarchy,” and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the price of anarchy can be arbitrarily large. We demonstrate that, somewhat counterintuitively, exercising admission control to the shared resource may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the shared resource to a wide range of user types.",amir nahir,Analytical models,2015.0,10.1109/TNET.2014.2354572,IEEE/ACM Transactions on Networking,Nahir2015,False,,IEEE,Not available,Workload Factoring: A Game-Theoretic Perspective,759722e4368fa23983f8764c742ab847,https://ieeexplore.ieee.org/document/6901301/
8619,"Contention among users utilizing a single shared resource arises in multiple contexts of computing and computer communications. We consider a setup in which users can split their work between a shared resource and a private resource. Unlike the private resource, which provides guaranteed performance, the performance of the shared resource is highly dependent on the usage pattern of other users, which in turn influences a user's decision if and to what extent to make use of the shared resource. The intrinsic relation between the utility that a user perceives from the shared resource and the usage pattern followed by other users gives rise to a noncooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the ratio between the worst Nash equilibrium and the social optimum, known as the “price of anarchy,” and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the price of anarchy can be arbitrarily large. We demonstrate that, somewhat counterintuitively, exercising admission control to the shared resource may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the shared resource to a wide range of user types.",amir nahir,modeling,2015.0,10.1109/TNET.2014.2354572,IEEE/ACM Transactions on Networking,Nahir2015,False,,IEEE,Not available,Workload Factoring: A Game-Theoretic Perspective,759722e4368fa23983f8764c742ab847,https://ieeexplore.ieee.org/document/6901301/
8620,"Contention among users utilizing a single shared resource arises in multiple contexts of computing and computer communications. We consider a setup in which users can split their work between a shared resource and a private resource. Unlike the private resource, which provides guaranteed performance, the performance of the shared resource is highly dependent on the usage pattern of other users, which in turn influences a user's decision if and to what extent to make use of the shared resource. The intrinsic relation between the utility that a user perceives from the shared resource and the usage pattern followed by other users gives rise to a noncooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the ratio between the worst Nash equilibrium and the social optimum, known as the “price of anarchy,” and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the price of anarchy can be arbitrarily large. We demonstrate that, somewhat counterintuitively, exercising admission control to the shared resource may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the shared resource to a wide range of user types.",amir nahir,system analysis and design,2015.0,10.1109/TNET.2014.2354572,IEEE/ACM Transactions on Networking,Nahir2015,False,,IEEE,Not available,Workload Factoring: A Game-Theoretic Perspective,759722e4368fa23983f8764c742ab847,https://ieeexplore.ieee.org/document/6901301/
8621,"Contention among users utilizing a single shared resource arises in multiple contexts of computing and computer communications. We consider a setup in which users can split their work between a shared resource and a private resource. Unlike the private resource, which provides guaranteed performance, the performance of the shared resource is highly dependent on the usage pattern of other users, which in turn influences a user's decision if and to what extent to make use of the shared resource. The intrinsic relation between the utility that a user perceives from the shared resource and the usage pattern followed by other users gives rise to a noncooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the ratio between the worst Nash equilibrium and the social optimum, known as the “price of anarchy,” and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the price of anarchy can be arbitrarily large. We demonstrate that, somewhat counterintuitively, exercising admission control to the shared resource may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the shared resource to a wide range of user types.",amir nahir,system performance,2015.0,10.1109/TNET.2014.2354572,IEEE/ACM Transactions on Networking,Nahir2015,False,,IEEE,Not available,Workload Factoring: A Game-Theoretic Perspective,759722e4368fa23983f8764c742ab847,https://ieeexplore.ieee.org/document/6901301/
8622,"Contention among users utilizing a single shared resource arises in multiple contexts of computing and computer communications. We consider a setup in which users can split their work between a shared resource and a private resource. Unlike the private resource, which provides guaranteed performance, the performance of the shared resource is highly dependent on the usage pattern of other users, which in turn influences a user's decision if and to what extent to make use of the shared resource. The intrinsic relation between the utility that a user perceives from the shared resource and the usage pattern followed by other users gives rise to a noncooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the ratio between the worst Nash equilibrium and the social optimum, known as the “price of anarchy,” and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the price of anarchy can be arbitrarily large. We demonstrate that, somewhat counterintuitively, exercising admission control to the shared resource may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the shared resource to a wide range of user types.",amir nahir,systems engineering and theory,2015.0,10.1109/TNET.2014.2354572,IEEE/ACM Transactions on Networking,Nahir2015,False,,IEEE,Not available,Workload Factoring: A Game-Theoretic Perspective,759722e4368fa23983f8764c742ab847,https://ieeexplore.ieee.org/document/6901301/
8623,"Contention among users utilizing a single shared resource arises in multiple contexts of computing and computer communications. We consider a setup in which users can split their work between a shared resource and a private resource. Unlike the private resource, which provides guaranteed performance, the performance of the shared resource is highly dependent on the usage pattern of other users, which in turn influences a user's decision if and to what extent to make use of the shared resource. The intrinsic relation between the utility that a user perceives from the shared resource and the usage pattern followed by other users gives rise to a noncooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the ratio between the worst Nash equilibrium and the social optimum, known as the “price of anarchy,” and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the price of anarchy can be arbitrarily large. We demonstrate that, somewhat counterintuitively, exercising admission control to the shared resource may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the shared resource to a wide range of user types.",ariel orda,Analytical models,2015.0,10.1109/TNET.2014.2354572,IEEE/ACM Transactions on Networking,Nahir2015,False,,IEEE,Not available,Workload Factoring: A Game-Theoretic Perspective,759722e4368fa23983f8764c742ab847,https://ieeexplore.ieee.org/document/6901301/
8624,"Contention among users utilizing a single shared resource arises in multiple contexts of computing and computer communications. We consider a setup in which users can split their work between a shared resource and a private resource. Unlike the private resource, which provides guaranteed performance, the performance of the shared resource is highly dependent on the usage pattern of other users, which in turn influences a user's decision if and to what extent to make use of the shared resource. The intrinsic relation between the utility that a user perceives from the shared resource and the usage pattern followed by other users gives rise to a noncooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the ratio between the worst Nash equilibrium and the social optimum, known as the “price of anarchy,” and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the price of anarchy can be arbitrarily large. We demonstrate that, somewhat counterintuitively, exercising admission control to the shared resource may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the shared resource to a wide range of user types.",ariel orda,modeling,2015.0,10.1109/TNET.2014.2354572,IEEE/ACM Transactions on Networking,Nahir2015,False,,IEEE,Not available,Workload Factoring: A Game-Theoretic Perspective,759722e4368fa23983f8764c742ab847,https://ieeexplore.ieee.org/document/6901301/
8625,"Contention among users utilizing a single shared resource arises in multiple contexts of computing and computer communications. We consider a setup in which users can split their work between a shared resource and a private resource. Unlike the private resource, which provides guaranteed performance, the performance of the shared resource is highly dependent on the usage pattern of other users, which in turn influences a user's decision if and to what extent to make use of the shared resource. The intrinsic relation between the utility that a user perceives from the shared resource and the usage pattern followed by other users gives rise to a noncooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the ratio between the worst Nash equilibrium and the social optimum, known as the “price of anarchy,” and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the price of anarchy can be arbitrarily large. We demonstrate that, somewhat counterintuitively, exercising admission control to the shared resource may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the shared resource to a wide range of user types.",ariel orda,system analysis and design,2015.0,10.1109/TNET.2014.2354572,IEEE/ACM Transactions on Networking,Nahir2015,False,,IEEE,Not available,Workload Factoring: A Game-Theoretic Perspective,759722e4368fa23983f8764c742ab847,https://ieeexplore.ieee.org/document/6901301/
8626,"Contention among users utilizing a single shared resource arises in multiple contexts of computing and computer communications. We consider a setup in which users can split their work between a shared resource and a private resource. Unlike the private resource, which provides guaranteed performance, the performance of the shared resource is highly dependent on the usage pattern of other users, which in turn influences a user's decision if and to what extent to make use of the shared resource. The intrinsic relation between the utility that a user perceives from the shared resource and the usage pattern followed by other users gives rise to a noncooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the ratio between the worst Nash equilibrium and the social optimum, known as the “price of anarchy,” and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the price of anarchy can be arbitrarily large. We demonstrate that, somewhat counterintuitively, exercising admission control to the shared resource may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the shared resource to a wide range of user types.",ariel orda,system performance,2015.0,10.1109/TNET.2014.2354572,IEEE/ACM Transactions on Networking,Nahir2015,False,,IEEE,Not available,Workload Factoring: A Game-Theoretic Perspective,759722e4368fa23983f8764c742ab847,https://ieeexplore.ieee.org/document/6901301/
8627,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8628,"Contention among users utilizing a single shared resource arises in multiple contexts of computing and computer communications. We consider a setup in which users can split their work between a shared resource and a private resource. Unlike the private resource, which provides guaranteed performance, the performance of the shared resource is highly dependent on the usage pattern of other users, which in turn influences a user's decision if and to what extent to make use of the shared resource. The intrinsic relation between the utility that a user perceives from the shared resource and the usage pattern followed by other users gives rise to a noncooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the ratio between the worst Nash equilibrium and the social optimum, known as the “price of anarchy,” and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the price of anarchy can be arbitrarily large. We demonstrate that, somewhat counterintuitively, exercising admission control to the shared resource may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the shared resource to a wide range of user types.",ariel orda,systems engineering and theory,2015.0,10.1109/TNET.2014.2354572,IEEE/ACM Transactions on Networking,Nahir2015,False,,IEEE,Not available,Workload Factoring: A Game-Theoretic Perspective,759722e4368fa23983f8764c742ab847,https://ieeexplore.ieee.org/document/6901301/
8629,"Contention among users utilizing a single shared resource arises in multiple contexts of computing and computer communications. We consider a setup in which users can split their work between a shared resource and a private resource. Unlike the private resource, which provides guaranteed performance, the performance of the shared resource is highly dependent on the usage pattern of other users, which in turn influences a user's decision if and to what extent to make use of the shared resource. The intrinsic relation between the utility that a user perceives from the shared resource and the usage pattern followed by other users gives rise to a noncooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the ratio between the worst Nash equilibrium and the social optimum, known as the “price of anarchy,” and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the price of anarchy can be arbitrarily large. We demonstrate that, somewhat counterintuitively, exercising admission control to the shared resource may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the shared resource to a wide range of user types.",danny raz,Analytical models,2015.0,10.1109/TNET.2014.2354572,IEEE/ACM Transactions on Networking,Nahir2015,False,,IEEE,Not available,Workload Factoring: A Game-Theoretic Perspective,759722e4368fa23983f8764c742ab847,https://ieeexplore.ieee.org/document/6901301/
8630,"Contention among users utilizing a single shared resource arises in multiple contexts of computing and computer communications. We consider a setup in which users can split their work between a shared resource and a private resource. Unlike the private resource, which provides guaranteed performance, the performance of the shared resource is highly dependent on the usage pattern of other users, which in turn influences a user's decision if and to what extent to make use of the shared resource. The intrinsic relation between the utility that a user perceives from the shared resource and the usage pattern followed by other users gives rise to a noncooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the ratio between the worst Nash equilibrium and the social optimum, known as the “price of anarchy,” and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the price of anarchy can be arbitrarily large. We demonstrate that, somewhat counterintuitively, exercising admission control to the shared resource may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the shared resource to a wide range of user types.",danny raz,modeling,2015.0,10.1109/TNET.2014.2354572,IEEE/ACM Transactions on Networking,Nahir2015,False,,IEEE,Not available,Workload Factoring: A Game-Theoretic Perspective,759722e4368fa23983f8764c742ab847,https://ieeexplore.ieee.org/document/6901301/
8631,"Contention among users utilizing a single shared resource arises in multiple contexts of computing and computer communications. We consider a setup in which users can split their work between a shared resource and a private resource. Unlike the private resource, which provides guaranteed performance, the performance of the shared resource is highly dependent on the usage pattern of other users, which in turn influences a user's decision if and to what extent to make use of the shared resource. The intrinsic relation between the utility that a user perceives from the shared resource and the usage pattern followed by other users gives rise to a noncooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the ratio between the worst Nash equilibrium and the social optimum, known as the “price of anarchy,” and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the price of anarchy can be arbitrarily large. We demonstrate that, somewhat counterintuitively, exercising admission control to the shared resource may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the shared resource to a wide range of user types.",danny raz,system analysis and design,2015.0,10.1109/TNET.2014.2354572,IEEE/ACM Transactions on Networking,Nahir2015,False,,IEEE,Not available,Workload Factoring: A Game-Theoretic Perspective,759722e4368fa23983f8764c742ab847,https://ieeexplore.ieee.org/document/6901301/
8632,"Contention among users utilizing a single shared resource arises in multiple contexts of computing and computer communications. We consider a setup in which users can split their work between a shared resource and a private resource. Unlike the private resource, which provides guaranteed performance, the performance of the shared resource is highly dependent on the usage pattern of other users, which in turn influences a user's decision if and to what extent to make use of the shared resource. The intrinsic relation between the utility that a user perceives from the shared resource and the usage pattern followed by other users gives rise to a noncooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the ratio between the worst Nash equilibrium and the social optimum, known as the “price of anarchy,” and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the price of anarchy can be arbitrarily large. We demonstrate that, somewhat counterintuitively, exercising admission control to the shared resource may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the shared resource to a wide range of user types.",danny raz,system performance,2015.0,10.1109/TNET.2014.2354572,IEEE/ACM Transactions on Networking,Nahir2015,False,,IEEE,Not available,Workload Factoring: A Game-Theoretic Perspective,759722e4368fa23983f8764c742ab847,https://ieeexplore.ieee.org/document/6901301/
8633,"Contention among users utilizing a single shared resource arises in multiple contexts of computing and computer communications. We consider a setup in which users can split their work between a shared resource and a private resource. Unlike the private resource, which provides guaranteed performance, the performance of the shared resource is highly dependent on the usage pattern of other users, which in turn influences a user's decision if and to what extent to make use of the shared resource. The intrinsic relation between the utility that a user perceives from the shared resource and the usage pattern followed by other users gives rise to a noncooperative game, which we model and investigate. We show that the considered game admits a Nash equilibrium. Moreover, we show that this equilibrium is unique. We investigate the ratio between the worst Nash equilibrium and the social optimum, known as the “price of anarchy,” and show that, while in some cases of interest the Nash equilibrium coincides with a social optimum, in other cases the price of anarchy can be arbitrarily large. We demonstrate that, somewhat counterintuitively, exercising admission control to the shared resource may deteriorate its performance. Furthermore, we demonstrate that certain (heavy) users may “scare off” other, potentially large, communities of users. Accordingly, we propose a resource allocation scheme that addresses this problem and opens the shared resource to a wide range of user types.",danny raz,systems engineering and theory,2015.0,10.1109/TNET.2014.2354572,IEEE/ACM Transactions on Networking,Nahir2015,False,,IEEE,Not available,Workload Factoring: A Game-Theoretic Perspective,759722e4368fa23983f8764c742ab847,https://ieeexplore.ieee.org/document/6901301/
8634,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",j. omic,Protection,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
8635,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",j. omic,Game theory,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
8636,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",j. omic,IP networks,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
8637,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",j. omic,Network servers,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
8638,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8639,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",j. omic,Internet,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
8640,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",j. omic,Computer viruses,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
8641,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",j. omic,Employment,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
8642,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",j. omic,Decision making,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
8643,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",j. omic,Curing,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
8644,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",j. omic,Information security,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
8645,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",a. orda,Protection,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
8646,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",a. orda,Game theory,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
8647,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",a. orda,IP networks,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
8648,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",a. orda,Network servers,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
8649,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8650,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",a. orda,Internet,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
8651,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",a. orda,Computer viruses,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
8652,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",a. orda,Employment,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
8653,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",a. orda,Decision making,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
8654,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",a. orda,Curing,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
8655,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",a. orda,Information security,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
8656,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",p. mieghem,Protection,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
8657,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",p. mieghem,Game theory,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
8658,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",p. mieghem,IP networks,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
8659,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",p. mieghem,Network servers,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
8660,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
8661,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
8662,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8663,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",p. mieghem,Internet,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
8664,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",p. mieghem,Computer viruses,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
8665,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",p. mieghem,Employment,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
8666,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",p. mieghem,Decision making,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
8667,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",p. mieghem,Curing,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
8668,"Security breaches and attacks are critical problems in today's networking. A key-point is that the security of each host depends not only on the protection strategies it chooses to adopt but also on those chosen by other hosts in the network. The spread of Internet worms and viruses is only one example. This class of problems has two aspects. First, it deals with epidemic processes, and as such calls for the employment of epidemic theory. Second, the distributed and autonomous nature of decision-making in major classes of networks (e.g., P2P, ad- hoc, and most notably the Internet) call for the employment of game theoretical approaches. Accordingly, we propose a unified framework that combines the N-intertwined, SIS epidemic model with a noncooperative game model. We determine the existence of a Nash equilibrium of the respective game and characterize its properties. We show that its quality, in terms of overall network security, largely depends on the underlying topology. We then provide a bound on the level of system inefficiency due to the noncooperative behavior, namely, the ""price of anarchy"" of the game. We observe that the price of anarchy may be prohibitively high, hence we propose a scheme for steering users towards socially efficient behavior.",p. mieghem,Information security,2009.0,10.1109/INFCOM.2009.5062065,IEEE INFOCOM 2009,Omic2009,False,,IEEE,Not available,Protecting Against Network Infections: A Game Theoretic Perspective,febd48f3f91d65816d9049fc9907068c,https://ieeexplore.ieee.org/document/5062065/
8669,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",joshua davis,social networks,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8670,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",joshua davis,game theory,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8671,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",joshua davis,price of anarchy,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8672,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",joshua davis,Nash equilibria,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8673,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8674,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",joshua davis,coordination games,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8675,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",zachary goldman,social networks,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8676,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",zachary goldman,game theory,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8677,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",zachary goldman,price of anarchy,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8678,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",zachary goldman,Nash equilibria,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8679,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",zachary goldman,coordination games,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8680,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",jacob hilty,social networks,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8681,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",jacob hilty,game theory,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8682,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",jacob hilty,price of anarchy,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8683,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",jacob hilty,Nash equilibria,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8684,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8685,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",jacob hilty,coordination games,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8686,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",elizabeth koch,social networks,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8687,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",elizabeth koch,game theory,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8688,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",elizabeth koch,price of anarchy,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8689,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",elizabeth koch,Nash equilibria,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8690,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",elizabeth koch,coordination games,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8691,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",david liben-nowell,social networks,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8692,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",david liben-nowell,game theory,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8693,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",david liben-nowell,price of anarchy,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8694,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",david liben-nowell,Nash equilibria,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8695,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8696,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",david liben-nowell,coordination games,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8697,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",alexa sharp,social networks,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8698,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",alexa sharp,game theory,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8699,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",alexa sharp,price of anarchy,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8700,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",alexa sharp,Nash equilibria,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8701,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",alexa sharp,coordination games,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8702,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",tom wexler,social networks,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8703,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",tom wexler,game theory,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8704,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",tom wexler,price of anarchy,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8705,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",tom wexler,Nash equilibria,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8706,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8707,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",tom wexler,coordination games,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8708,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",emma zhou,social networks,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8709,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",emma zhou,game theory,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8710,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",emma zhou,price of anarchy,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8711,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",emma zhou,Nash equilibria,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8712,"Social networks are the substrate upon which we make and evaluate many of our daily decisions: our costs and benefits depend on whether-or how many of, or which of-our friends are willing to go to that restaurant, choose that cellular provider, already own that gaming platform. Much of the research on the ""diffusion of innovation"", for example, takes a game theoretic perspective on strategic decisions made by people embedded in a social context. Indeed, multiplayer games played on social networks, where the network's nodes correspond to the game's players, have proven to be fruitful models of many natural scenarios involving strategic interaction. In this paper, we embark on a mathematical and general exploration of the relationship between 2-person strategic interactions (a ""base game"") and a ""networked"" version of that same game. We formulate a generic mechanism for superimposing a symmetric 2-player base game M on a social network G: each node of G chooses a single strategy from M and simultaneously plays that strategy against each of its neighbors in G, receiving as its payoff the sum of the payoffs from playing M against each neighbor. We denote the networked game that results by M oplus G. We are broadly interested in the relationship between properties of M and of M oplus G: how does the character of strategic interaction change when it is embedded in a social network? We focus on two particular properties: the (pure) price of anarchy and the existence of pure Nash equilibria. We show tight results on the relationship between the price of anarchy in M and MoplusG in coordination games. We also show that, with some exceptions when G is bipartite, the existence or absence of pure Nash equilibria (and even the guaranteed convergence of best-response dynamics) in M and M oplus G are not entailed in either direction. Taken together, these results suggest that the process of superimposing M on a graph is a nontrivial operation that can have rich, but bounded, effects on the strategic environment.",emma zhou,coordination games,2009.0,10.1109/CSE.2009.45,2009 International Conference on Computational Science and Engineering,Davis2009,False,,IEEE,Not available,Equilibria and Efficiency Loss in Games on Networks,bf8404009522bc985fb288bb15733390,https://ieeexplore.ieee.org/document/5283899/
8713,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",benjamin grimmer,Games,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
8714,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",benjamin grimmer,Routing,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
8715,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",benjamin grimmer,Delays,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
8716,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",benjamin grimmer,Global Positioning System,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
8717,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8718,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",benjamin grimmer,Nash equilibrium,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
8719,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",benjamin grimmer,Processor scheduling,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
8720,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",benjamin grimmer,Servers,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
8721,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",sanjiv kapoor,Games,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
8722,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",sanjiv kapoor,Routing,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
8723,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",sanjiv kapoor,Delays,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
8724,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",sanjiv kapoor,Global Positioning System,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
8725,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",sanjiv kapoor,Nash equilibrium,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
8726,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",sanjiv kapoor,Processor scheduling,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
8727,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",sanjiv kapoor,Servers,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
8728,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8729,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",quanyan zhu,AWGN,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
8730,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",quanyan zhu,Game theory,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
8731,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",quanyan zhu,Communication networks,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
8732,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",quanyan zhu,Wireless networks,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
8733,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",quanyan zhu,Multiaccess communication,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
8734,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",quanyan zhu,Stability,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
8735,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",quanyan zhu,Biological system modeling,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
8736,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",quanyan zhu,Environmental factors,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
8737,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",quanyan zhu,Throughput,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
8738,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",quanyan zhu,Power control,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
8739,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8740,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",hamidou tembine,AWGN,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
8741,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",hamidou tembine,Game theory,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
8742,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",hamidou tembine,Communication networks,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
8743,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",hamidou tembine,Wireless networks,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
8744,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",hamidou tembine,Multiaccess communication,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
8745,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",hamidou tembine,Stability,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
8746,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",hamidou tembine,Biological system modeling,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
8747,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",hamidou tembine,Environmental factors,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
8748,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",hamidou tembine,Throughput,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
8749,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",hamidou tembine,Power control,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
8750,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8751,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",tamer basar,AWGN,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
8752,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",tamer basar,Game theory,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
8753,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",tamer basar,Communication networks,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
8754,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",tamer basar,Wireless networks,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
8755,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",tamer basar,Multiaccess communication,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
8756,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",tamer basar,Stability,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
8757,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",tamer basar,Biological system modeling,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
8758,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",tamer basar,Environmental factors,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
8759,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",tamer basar,Throughput,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
8760,"In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong equilibria. We use the concepts of price of anarchy and strong price of anarchy to study the performance of the system. The paper also addresses how to select one specific equilibrium solution using the concepts of normalized equilibrium and evolutionary stable strategies. We examine the long-run behavior of these strategies under several classes of evolutionary game dynamics such as Brown-von Neumann-Nash dynamics, and replicator dynamics.",tamer basar,Power control,2009.0,10.1109/GAMENETS.2009.5137426,2009 International Conference on Game Theory for Networks,Zhu2009,False,,IEEE,Not available,A constrained evolutionary Gaussian multiple access channel game,659fa54d49fe5c474e28119a1eeb94f9,https://ieeexplore.ieee.org/document/5137426/
8761,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8762,"We address the parallel machines scheduling problems when selling to a selfish customer population with heterogeneous time utility functions. The manufacturer, owning parallel machines resource, has some independent objective. Because of customers' selfishness, anarchistic competition would worsen the manufacturer's performance, and then, cause “Price of Anarchy”. On the other hand, the optimization of the manufacturer's objective would also deteriorate some customers' waiting costs greatly (and then, will harm seller himself in long term). In this paper, noncooperative game is used to model above multi-person multi-objective problem in parallel machine environment. Price of Anarchy is analyzed. To balance each participant's performance, a coordination mechanism which could generate an efficient schedule is provided by choosing payment to motivate all selfish customers to act as the manufacturer wishes. Numerical experiments on proposed coordination mechanism are given at last.",changjun wang,parallel machine scheduling,2012.0,10.1109/ICSMC.2012.6378064,"2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC)",Wang2012,False,,IEEE,Not available,Parallel machines scheduling in the presence of heterogeneous selfish customers,8d5a830abada4b29bf7cbabe5e5517e5,https://ieeexplore.ieee.org/document/6378064/
8763,"We address the parallel machines scheduling problems when selling to a selfish customer population with heterogeneous time utility functions. The manufacturer, owning parallel machines resource, has some independent objective. Because of customers' selfishness, anarchistic competition would worsen the manufacturer's performance, and then, cause “Price of Anarchy”. On the other hand, the optimization of the manufacturer's objective would also deteriorate some customers' waiting costs greatly (and then, will harm seller himself in long term). In this paper, noncooperative game is used to model above multi-person multi-objective problem in parallel machine environment. Price of Anarchy is analyzed. To balance each participant's performance, a coordination mechanism which could generate an efficient schedule is provided by choosing payment to motivate all selfish customers to act as the manufacturer wishes. Numerical experiments on proposed coordination mechanism are given at last.",changjun wang,noncooperative game,2012.0,10.1109/ICSMC.2012.6378064,"2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC)",Wang2012,False,,IEEE,Not available,Parallel machines scheduling in the presence of heterogeneous selfish customers,8d5a830abada4b29bf7cbabe5e5517e5,https://ieeexplore.ieee.org/document/6378064/
8764,"We address the parallel machines scheduling problems when selling to a selfish customer population with heterogeneous time utility functions. The manufacturer, owning parallel machines resource, has some independent objective. Because of customers' selfishness, anarchistic competition would worsen the manufacturer's performance, and then, cause “Price of Anarchy”. On the other hand, the optimization of the manufacturer's objective would also deteriorate some customers' waiting costs greatly (and then, will harm seller himself in long term). In this paper, noncooperative game is used to model above multi-person multi-objective problem in parallel machine environment. Price of Anarchy is analyzed. To balance each participant's performance, a coordination mechanism which could generate an efficient schedule is provided by choosing payment to motivate all selfish customers to act as the manufacturer wishes. Numerical experiments on proposed coordination mechanism are given at last.",changjun wang,heterogeneous customers,2012.0,10.1109/ICSMC.2012.6378064,"2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC)",Wang2012,False,,IEEE,Not available,Parallel machines scheduling in the presence of heterogeneous selfish customers,8d5a830abada4b29bf7cbabe5e5517e5,https://ieeexplore.ieee.org/document/6378064/
8765,"We address the parallel machines scheduling problems when selling to a selfish customer population with heterogeneous time utility functions. The manufacturer, owning parallel machines resource, has some independent objective. Because of customers' selfishness, anarchistic competition would worsen the manufacturer's performance, and then, cause “Price of Anarchy”. On the other hand, the optimization of the manufacturer's objective would also deteriorate some customers' waiting costs greatly (and then, will harm seller himself in long term). In this paper, noncooperative game is used to model above multi-person multi-objective problem in parallel machine environment. Price of Anarchy is analyzed. To balance each participant's performance, a coordination mechanism which could generate an efficient schedule is provided by choosing payment to motivate all selfish customers to act as the manufacturer wishes. Numerical experiments on proposed coordination mechanism are given at last.",changjun wang,price of anachy,2012.0,10.1109/ICSMC.2012.6378064,"2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC)",Wang2012,False,,IEEE,Not available,Parallel machines scheduling in the presence of heterogeneous selfish customers,8d5a830abada4b29bf7cbabe5e5517e5,https://ieeexplore.ieee.org/document/6378064/
8766,"We address the parallel machines scheduling problems when selling to a selfish customer population with heterogeneous time utility functions. The manufacturer, owning parallel machines resource, has some independent objective. Because of customers' selfishness, anarchistic competition would worsen the manufacturer's performance, and then, cause “Price of Anarchy”. On the other hand, the optimization of the manufacturer's objective would also deteriorate some customers' waiting costs greatly (and then, will harm seller himself in long term). In this paper, noncooperative game is used to model above multi-person multi-objective problem in parallel machine environment. Price of Anarchy is analyzed. To balance each participant's performance, a coordination mechanism which could generate an efficient schedule is provided by choosing payment to motivate all selfish customers to act as the manufacturer wishes. Numerical experiments on proposed coordination mechanism are given at last.",dayang lei,parallel machine scheduling,2012.0,10.1109/ICSMC.2012.6378064,"2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC)",Wang2012,False,,IEEE,Not available,Parallel machines scheduling in the presence of heterogeneous selfish customers,8d5a830abada4b29bf7cbabe5e5517e5,https://ieeexplore.ieee.org/document/6378064/
8767,"We address the parallel machines scheduling problems when selling to a selfish customer population with heterogeneous time utility functions. The manufacturer, owning parallel machines resource, has some independent objective. Because of customers' selfishness, anarchistic competition would worsen the manufacturer's performance, and then, cause “Price of Anarchy”. On the other hand, the optimization of the manufacturer's objective would also deteriorate some customers' waiting costs greatly (and then, will harm seller himself in long term). In this paper, noncooperative game is used to model above multi-person multi-objective problem in parallel machine environment. Price of Anarchy is analyzed. To balance each participant's performance, a coordination mechanism which could generate an efficient schedule is provided by choosing payment to motivate all selfish customers to act as the manufacturer wishes. Numerical experiments on proposed coordination mechanism are given at last.",dayang lei,noncooperative game,2012.0,10.1109/ICSMC.2012.6378064,"2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC)",Wang2012,False,,IEEE,Not available,Parallel machines scheduling in the presence of heterogeneous selfish customers,8d5a830abada4b29bf7cbabe5e5517e5,https://ieeexplore.ieee.org/document/6378064/
8768,"We address the parallel machines scheduling problems when selling to a selfish customer population with heterogeneous time utility functions. The manufacturer, owning parallel machines resource, has some independent objective. Because of customers' selfishness, anarchistic competition would worsen the manufacturer's performance, and then, cause “Price of Anarchy”. On the other hand, the optimization of the manufacturer's objective would also deteriorate some customers' waiting costs greatly (and then, will harm seller himself in long term). In this paper, noncooperative game is used to model above multi-person multi-objective problem in parallel machine environment. Price of Anarchy is analyzed. To balance each participant's performance, a coordination mechanism which could generate an efficient schedule is provided by choosing payment to motivate all selfish customers to act as the manufacturer wishes. Numerical experiments on proposed coordination mechanism are given at last.",dayang lei,heterogeneous customers,2012.0,10.1109/ICSMC.2012.6378064,"2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC)",Wang2012,False,,IEEE,Not available,Parallel machines scheduling in the presence of heterogeneous selfish customers,8d5a830abada4b29bf7cbabe5e5517e5,https://ieeexplore.ieee.org/document/6378064/
8769,"We address the parallel machines scheduling problems when selling to a selfish customer population with heterogeneous time utility functions. The manufacturer, owning parallel machines resource, has some independent objective. Because of customers' selfishness, anarchistic competition would worsen the manufacturer's performance, and then, cause “Price of Anarchy”. On the other hand, the optimization of the manufacturer's objective would also deteriorate some customers' waiting costs greatly (and then, will harm seller himself in long term). In this paper, noncooperative game is used to model above multi-person multi-objective problem in parallel machine environment. Price of Anarchy is analyzed. To balance each participant's performance, a coordination mechanism which could generate an efficient schedule is provided by choosing payment to motivate all selfish customers to act as the manufacturer wishes. Numerical experiments on proposed coordination mechanism are given at last.",dayang lei,price of anachy,2012.0,10.1109/ICSMC.2012.6378064,"2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC)",Wang2012,False,,IEEE,Not available,Parallel machines scheduling in the presence of heterogeneous selfish customers,8d5a830abada4b29bf7cbabe5e5517e5,https://ieeexplore.ieee.org/document/6378064/
8770,"We address the parallel machines scheduling problems when selling to a selfish customer population with heterogeneous time utility functions. The manufacturer, owning parallel machines resource, has some independent objective. Because of customers' selfishness, anarchistic competition would worsen the manufacturer's performance, and then, cause “Price of Anarchy”. On the other hand, the optimization of the manufacturer's objective would also deteriorate some customers' waiting costs greatly (and then, will harm seller himself in long term). In this paper, noncooperative game is used to model above multi-person multi-objective problem in parallel machine environment. Price of Anarchy is analyzed. To balance each participant's performance, a coordination mechanism which could generate an efficient schedule is provided by choosing payment to motivate all selfish customers to act as the manufacturer wishes. Numerical experiments on proposed coordination mechanism are given at last.",yongji jia,parallel machine scheduling,2012.0,10.1109/ICSMC.2012.6378064,"2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC)",Wang2012,False,,IEEE,Not available,Parallel machines scheduling in the presence of heterogeneous selfish customers,8d5a830abada4b29bf7cbabe5e5517e5,https://ieeexplore.ieee.org/document/6378064/
8771,"We address the parallel machines scheduling problems when selling to a selfish customer population with heterogeneous time utility functions. The manufacturer, owning parallel machines resource, has some independent objective. Because of customers' selfishness, anarchistic competition would worsen the manufacturer's performance, and then, cause “Price of Anarchy”. On the other hand, the optimization of the manufacturer's objective would also deteriorate some customers' waiting costs greatly (and then, will harm seller himself in long term). In this paper, noncooperative game is used to model above multi-person multi-objective problem in parallel machine environment. Price of Anarchy is analyzed. To balance each participant's performance, a coordination mechanism which could generate an efficient schedule is provided by choosing payment to motivate all selfish customers to act as the manufacturer wishes. Numerical experiments on proposed coordination mechanism are given at last.",yongji jia,noncooperative game,2012.0,10.1109/ICSMC.2012.6378064,"2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC)",Wang2012,False,,IEEE,Not available,Parallel machines scheduling in the presence of heterogeneous selfish customers,8d5a830abada4b29bf7cbabe5e5517e5,https://ieeexplore.ieee.org/document/6378064/
8772,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
8773,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8774,"We address the parallel machines scheduling problems when selling to a selfish customer population with heterogeneous time utility functions. The manufacturer, owning parallel machines resource, has some independent objective. Because of customers' selfishness, anarchistic competition would worsen the manufacturer's performance, and then, cause “Price of Anarchy”. On the other hand, the optimization of the manufacturer's objective would also deteriorate some customers' waiting costs greatly (and then, will harm seller himself in long term). In this paper, noncooperative game is used to model above multi-person multi-objective problem in parallel machine environment. Price of Anarchy is analyzed. To balance each participant's performance, a coordination mechanism which could generate an efficient schedule is provided by choosing payment to motivate all selfish customers to act as the manufacturer wishes. Numerical experiments on proposed coordination mechanism are given at last.",yongji jia,heterogeneous customers,2012.0,10.1109/ICSMC.2012.6378064,"2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC)",Wang2012,False,,IEEE,Not available,Parallel machines scheduling in the presence of heterogeneous selfish customers,8d5a830abada4b29bf7cbabe5e5517e5,https://ieeexplore.ieee.org/document/6378064/
8775,"We address the parallel machines scheduling problems when selling to a selfish customer population with heterogeneous time utility functions. The manufacturer, owning parallel machines resource, has some independent objective. Because of customers' selfishness, anarchistic competition would worsen the manufacturer's performance, and then, cause “Price of Anarchy”. On the other hand, the optimization of the manufacturer's objective would also deteriorate some customers' waiting costs greatly (and then, will harm seller himself in long term). In this paper, noncooperative game is used to model above multi-person multi-objective problem in parallel machine environment. Price of Anarchy is analyzed. To balance each participant's performance, a coordination mechanism which could generate an efficient schedule is provided by choosing payment to motivate all selfish customers to act as the manufacturer wishes. Numerical experiments on proposed coordination mechanism are given at last.",yongji jia,price of anachy,2012.0,10.1109/ICSMC.2012.6378064,"2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC)",Wang2012,False,,IEEE,Not available,Parallel machines scheduling in the presence of heterogeneous selfish customers,8d5a830abada4b29bf7cbabe5e5517e5,https://ieeexplore.ieee.org/document/6378064/
8776,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",c. georgiou,Uncertainty,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
8777,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",c. georgiou,Routing,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
8778,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",c. georgiou,Telecommunication traffic,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
8779,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",c. georgiou,Traffic control,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
8780,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",c. georgiou,Delay,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
8781,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",c. georgiou,Probability distribution,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
8782,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",c. georgiou,Polynomials,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
8783,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",c. georgiou,Costs,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
8784,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8785,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",c. georgiou,Upper bound,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
8786,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",c. georgiou,Nash equilibrium,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
8787,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",t. pavlides,Uncertainty,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
8788,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",t. pavlides,Routing,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
8789,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",t. pavlides,Telecommunication traffic,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
8790,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",t. pavlides,Traffic control,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
8791,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",t. pavlides,Delay,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
8792,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",t. pavlides,Probability distribution,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
8793,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",t. pavlides,Polynomials,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
8794,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",t. pavlides,Costs,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
8795,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8796,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",t. pavlides,Upper bound,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
8797,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",t. pavlides,Nash equilibrium,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
8798,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",a. philippou,Uncertainty,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
8799,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",a. philippou,Routing,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
8800,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",a. philippou,Telecommunication traffic,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
8801,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",a. philippou,Traffic control,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
8802,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",a. philippou,Delay,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
8803,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",a. philippou,Probability distribution,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
8804,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",a. philippou,Polynomials,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
8805,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",a. philippou,Costs,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
8806,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8807,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",a. philippou,Upper bound,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
8808,"We study the problem of selfish routing in the presence of incomplete network information. Our model consists of a number of users who wish to route their traffic on a network of m parallel links with the objective of minimizing their latency. However, in doing so, they face the challenge of lack of precise information on the capacity of the network links. This uncertainty is modelled via a set of probability distributions over all the possibilities, one for each user. The resulting model is an amalgamation of the KP-model of (E. Koutsoupias and C. H. Papadimitriou, 1999) and the congestion games with user-specific functions of (I. Milchtaich, 1996). We embark on a study of Nash equilibria and the price of anarchy in this new model. In particular, we propose polynomial-time algorithms for computing some special cases of pure Nash equilibria and we show that negative results of (I. Milchtaich, 1996), for the non-existence of pure Nash equilibria in the case of three users, do not apply to our model. Consequently, we propose an interesting open problem in this area, that of the existence of pure Nash equilibria in the general case of our model. Furthermore, we consider appropriate notions for the social cost and the price of anarchy and obtain upper bounds for the latter. With respect to fully mixed Nash equilibria, we propose a method to compute them and show that when they exist they are unique. Finally we prove that the fully mixed Nash equilibrium maximizes the social welfare",a. philippou,Nash equilibrium,2006.0,10.1109/IPDPS.2006.1639342,Proceedings 20th IEEE International Parallel & Distributed Processing Symposium,Georgiou2006,False,,IEEE,Not available,Network uncertainty in selfish routing,04fb10907772b76d7b5a46777afa496d,https://ieeexplore.ieee.org/document/1639342/
8809,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",matthew zyskowski,Cost Density-Shaping Games,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
8810,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",matthew zyskowski,Cost Cumulant Control,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
8811,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",matthew zyskowski,Price of Anarchy,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
8812,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",matthew zyskowski,Variance of Anarchy,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
8813,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",matthew zyskowski,Telecommunications,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
8814,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",matthew zyskowski,Stochastic Differential Games,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
8815,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",matthew zyskowski,Team Optimization,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
8816,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",quanyan zhu,Cost Density-Shaping Games,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
8817,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8818,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",quanyan zhu,Cost Cumulant Control,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
8819,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",quanyan zhu,Price of Anarchy,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
8820,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",quanyan zhu,Variance of Anarchy,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
8821,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",quanyan zhu,Telecommunications,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
8822,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",quanyan zhu,Stochastic Differential Games,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
8823,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",quanyan zhu,Team Optimization,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
8824,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",baudelio baez,Optical Networks,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
8825,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",baudelio baez,Wavelength Converter Allocation,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
8826,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",baudelio baez,Cooperative Routing,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
8827,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",baudelio baez,Selfish Routing,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
8828,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8829,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",baudelio baez,Anarchy Price,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
8830,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",baudelio baez,Multi-objective Optimization,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
8831,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",baudelio baez,Evolutionary Algorithms,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
8832,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",jose colbes,Optical Networks,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
8833,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",jose colbes,Wavelength Converter Allocation,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
8834,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",jose colbes,Cooperative Routing,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
8835,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",jose colbes,Selfish Routing,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
8836,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",jose colbes,Anarchy Price,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
8837,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",jose colbes,Multi-objective Optimization,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
8838,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",jose colbes,Evolutionary Algorithms,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
8839,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8840,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",diego pinto-roa,Optical Networks,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
8841,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",diego pinto-roa,Wavelength Converter Allocation,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
8842,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",diego pinto-roa,Cooperative Routing,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
8843,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",diego pinto-roa,Selfish Routing,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
8844,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",diego pinto-roa,Anarchy Price,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
8845,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",diego pinto-roa,Multi-objective Optimization,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
8846,"The performence of centralized and distributed routing in wavelength converter allocation problem are studied in this work. The distributed routing is based on selfish routing in which each connection tries to improve its blocking probability. In counterpart, in centralized management, the routing of connexions are calculated by cooperative approach to improve the overall blocking probability of system. In the cooperative context, it is proposed a pure evolutionary algorithm which calculates simultaneously the converters allocation and traffic load flows. For selfish routing, an evolutionary algorithm calculates the converters allocation while the traffic load flow assignment that maximizes the benefit of each connection is accomplished by simulations. Both approaches are compared using Pareto Anarchy Price measure which is a proposal of this work. Experimental results indicate that, when the traffic load increased the Pareto Anarchy Price improves, and paradoxically, the quality of solutions gets worse.",diego pinto-roa,Evolutionary Algorithms,2014.0,10.1109/CLEI.2014.6965133,2014 XL Latin American Computing Conference (CLEI),Báez2014,False,,IEEE,Not available,Cooperative versus selfish routing in WDM networks a study in multi-objective context,6ad14fcbd3f50e1fb7e3d5a724dc7ada,https://ieeexplore.ieee.org/document/6965133/
8847,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",lok law,Cognitive radio,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8848,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",lok law,Nash equilibrium,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8849,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",lok law,Media Access Protocol,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8850,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8851,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",lok law,Resource management,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8852,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",lok law,Computer science,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8853,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",lok law,Information analysis,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8854,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",lok law,Closed-form solution,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8855,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",lok law,Monitoring,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8856,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",lok law,Interference,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8857,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",lok law,Frequency,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8858,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",jianwei huang,Cognitive radio,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8859,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",jianwei huang,Nash equilibrium,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8860,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",jianwei huang,Media Access Protocol,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8861,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8862,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",jianwei huang,Resource management,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8863,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",jianwei huang,Computer science,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8864,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",jianwei huang,Information analysis,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8865,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",jianwei huang,Closed-form solution,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8866,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",jianwei huang,Monitoring,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8867,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",jianwei huang,Interference,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8868,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",jianwei huang,Frequency,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8869,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",mingyan liu,Cognitive radio,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8870,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",mingyan liu,Nash equilibrium,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8871,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",mingyan liu,Media Access Protocol,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8872,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8873,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",mingyan liu,Resource management,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8874,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",mingyan liu,Computer science,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8875,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",mingyan liu,Information analysis,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8876,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",mingyan liu,Closed-form solution,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8877,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",mingyan liu,Monitoring,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8878,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",mingyan liu,Interference,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8879,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",mingyan liu,Frequency,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8880,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",shuo-yen li,Cognitive radio,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8881,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",shuo-yen li,Nash equilibrium,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8882,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",shuo-yen li,Media Access Protocol,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8883,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
8884,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8885,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",shuo-yen li,Resource management,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8886,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",shuo-yen li,Computer science,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8887,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",shuo-yen li,Information analysis,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8888,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",shuo-yen li,Closed-form solution,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8889,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",shuo-yen li,Monitoring,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8890,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",shuo-yen li,Interference,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8891,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",shuo-yen li,Frequency,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
8892,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. andrews,Wireless networks,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
8893,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. andrews,Signal to noise ratio,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
8894,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. andrews,Game theory,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
8895,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8896,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. andrews,Distributed algorithms,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
8897,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. andrews,Approximation algorithms,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
8898,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. andrews,Nash equilibrium,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
8899,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. andrews,Background noise,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
8900,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. andrews,Linear programming,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
8901,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. andrews,Polynomials,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
8902,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. andrews,Algorithm design and analysis,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
8903,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. dinitz,Wireless networks,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
8904,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. dinitz,Signal to noise ratio,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
8905,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. dinitz,Game theory,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
8906,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8907,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. dinitz,Distributed algorithms,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
8908,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. dinitz,Approximation algorithms,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
8909,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. dinitz,Nash equilibrium,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
8910,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. dinitz,Background noise,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
8911,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. dinitz,Linear programming,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
8912,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. dinitz,Polynomials,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
8913,"In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.",m. dinitz,Algorithm design and analysis,2009.0,10.1109/INFCOM.2009.5062048,IEEE INFOCOM 2009,Andrews2009,False,,IEEE,Not available,Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory,a014c4975e6712ee1c429b8c1aa02eeb,https://ieeexplore.ieee.org/document/5062048/
8914,"Introduction of differentiated services on the Internet has failed primarily due to many economic impediments. We focus on the provider competition aspect, and develop a multi-class queueing network game framework to study it. Each network service provider is modeled as a single-server multi-class queue. Providers post prices for various service classes. Traffic is elastic and there are multiple types of it, each traffic-type is sensitive to a different degree to Quality of Service (QoS). Arriving users choose a provider and a class for service. We study the pricing and service competition between the providers in a game-theoretic setting. We provide sufficient conditions for the existence of Nash equilibrium in the Bertrand (pricing) game between the multi-class queueing service providers. We also characterize the inefficiency (price of anarchy) due to strategic DiffServ pricing.",parijat dube,DiffServ,2010.0,10.1109/ITC.2010.5608737,2010 22nd International Teletraffic Congress (lTC 22),Dube2010,False,,IEEE,Not available,DiffServ pricing games in multi-class queueing network models,bd7fdc8eb97936de5aa44a37eaa0c381,https://ieeexplore.ieee.org/document/5608737/
8915,"Introduction of differentiated services on the Internet has failed primarily due to many economic impediments. We focus on the provider competition aspect, and develop a multi-class queueing network game framework to study it. Each network service provider is modeled as a single-server multi-class queue. Providers post prices for various service classes. Traffic is elastic and there are multiple types of it, each traffic-type is sensitive to a different degree to Quality of Service (QoS). Arriving users choose a provider and a class for service. We study the pricing and service competition between the providers in a game-theoretic setting. We provide sufficient conditions for the existence of Nash equilibrium in the Bertrand (pricing) game between the multi-class queueing service providers. We also characterize the inefficiency (price of anarchy) due to strategic DiffServ pricing.",parijat dube,Queueing networks,2010.0,10.1109/ITC.2010.5608737,2010 22nd International Teletraffic Congress (lTC 22),Dube2010,False,,IEEE,Not available,DiffServ pricing games in multi-class queueing network models,bd7fdc8eb97936de5aa44a37eaa0c381,https://ieeexplore.ieee.org/document/5608737/
8916,"Introduction of differentiated services on the Internet has failed primarily due to many economic impediments. We focus on the provider competition aspect, and develop a multi-class queueing network game framework to study it. Each network service provider is modeled as a single-server multi-class queue. Providers post prices for various service classes. Traffic is elastic and there are multiple types of it, each traffic-type is sensitive to a different degree to Quality of Service (QoS). Arriving users choose a provider and a class for service. We study the pricing and service competition between the providers in a game-theoretic setting. We provide sufficient conditions for the existence of Nash equilibrium in the Bertrand (pricing) game between the multi-class queueing service providers. We also characterize the inefficiency (price of anarchy) due to strategic DiffServ pricing.",parijat dube,Bertrand game,2010.0,10.1109/ITC.2010.5608737,2010 22nd International Teletraffic Congress (lTC 22),Dube2010,False,,IEEE,Not available,DiffServ pricing games in multi-class queueing network models,bd7fdc8eb97936de5aa44a37eaa0c381,https://ieeexplore.ieee.org/document/5608737/
8917,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8918,"Introduction of differentiated services on the Internet has failed primarily due to many economic impediments. We focus on the provider competition aspect, and develop a multi-class queueing network game framework to study it. Each network service provider is modeled as a single-server multi-class queue. Providers post prices for various service classes. Traffic is elastic and there are multiple types of it, each traffic-type is sensitive to a different degree to Quality of Service (QoS). Arriving users choose a provider and a class for service. We study the pricing and service competition between the providers in a game-theoretic setting. We provide sufficient conditions for the existence of Nash equilibrium in the Bertrand (pricing) game between the multi-class queueing service providers. We also characterize the inefficiency (price of anarchy) due to strategic DiffServ pricing.",parijat dube,Nash equilibrium,2010.0,10.1109/ITC.2010.5608737,2010 22nd International Teletraffic Congress (lTC 22),Dube2010,False,,IEEE,Not available,DiffServ pricing games in multi-class queueing network models,bd7fdc8eb97936de5aa44a37eaa0c381,https://ieeexplore.ieee.org/document/5608737/
8919,"Introduction of differentiated services on the Internet has failed primarily due to many economic impediments. We focus on the provider competition aspect, and develop a multi-class queueing network game framework to study it. Each network service provider is modeled as a single-server multi-class queue. Providers post prices for various service classes. Traffic is elastic and there are multiple types of it, each traffic-type is sensitive to a different degree to Quality of Service (QoS). Arriving users choose a provider and a class for service. We study the pricing and service competition between the providers in a game-theoretic setting. We provide sufficient conditions for the existence of Nash equilibrium in the Bertrand (pricing) game between the multi-class queueing service providers. We also characterize the inefficiency (price of anarchy) due to strategic DiffServ pricing.",parijat dube,Price of Anarchy,2010.0,10.1109/ITC.2010.5608737,2010 22nd International Teletraffic Congress (lTC 22),Dube2010,False,,IEEE,Not available,DiffServ pricing games in multi-class queueing network models,bd7fdc8eb97936de5aa44a37eaa0c381,https://ieeexplore.ieee.org/document/5608737/
8920,"Introduction of differentiated services on the Internet has failed primarily due to many economic impediments. We focus on the provider competition aspect, and develop a multi-class queueing network game framework to study it. Each network service provider is modeled as a single-server multi-class queue. Providers post prices for various service classes. Traffic is elastic and there are multiple types of it, each traffic-type is sensitive to a different degree to Quality of Service (QoS). Arriving users choose a provider and a class for service. We study the pricing and service competition between the providers in a game-theoretic setting. We provide sufficient conditions for the existence of Nash equilibrium in the Bertrand (pricing) game between the multi-class queueing service providers. We also characterize the inefficiency (price of anarchy) due to strategic DiffServ pricing.",rahul jain,DiffServ,2010.0,10.1109/ITC.2010.5608737,2010 22nd International Teletraffic Congress (lTC 22),Dube2010,False,,IEEE,Not available,DiffServ pricing games in multi-class queueing network models,bd7fdc8eb97936de5aa44a37eaa0c381,https://ieeexplore.ieee.org/document/5608737/
8921,"Introduction of differentiated services on the Internet has failed primarily due to many economic impediments. We focus on the provider competition aspect, and develop a multi-class queueing network game framework to study it. Each network service provider is modeled as a single-server multi-class queue. Providers post prices for various service classes. Traffic is elastic and there are multiple types of it, each traffic-type is sensitive to a different degree to Quality of Service (QoS). Arriving users choose a provider and a class for service. We study the pricing and service competition between the providers in a game-theoretic setting. We provide sufficient conditions for the existence of Nash equilibrium in the Bertrand (pricing) game between the multi-class queueing service providers. We also characterize the inefficiency (price of anarchy) due to strategic DiffServ pricing.",rahul jain,Queueing networks,2010.0,10.1109/ITC.2010.5608737,2010 22nd International Teletraffic Congress (lTC 22),Dube2010,False,,IEEE,Not available,DiffServ pricing games in multi-class queueing network models,bd7fdc8eb97936de5aa44a37eaa0c381,https://ieeexplore.ieee.org/document/5608737/
8922,"Introduction of differentiated services on the Internet has failed primarily due to many economic impediments. We focus on the provider competition aspect, and develop a multi-class queueing network game framework to study it. Each network service provider is modeled as a single-server multi-class queue. Providers post prices for various service classes. Traffic is elastic and there are multiple types of it, each traffic-type is sensitive to a different degree to Quality of Service (QoS). Arriving users choose a provider and a class for service. We study the pricing and service competition between the providers in a game-theoretic setting. We provide sufficient conditions for the existence of Nash equilibrium in the Bertrand (pricing) game between the multi-class queueing service providers. We also characterize the inefficiency (price of anarchy) due to strategic DiffServ pricing.",rahul jain,Bertrand game,2010.0,10.1109/ITC.2010.5608737,2010 22nd International Teletraffic Congress (lTC 22),Dube2010,False,,IEEE,Not available,DiffServ pricing games in multi-class queueing network models,bd7fdc8eb97936de5aa44a37eaa0c381,https://ieeexplore.ieee.org/document/5608737/
8923,"Introduction of differentiated services on the Internet has failed primarily due to many economic impediments. We focus on the provider competition aspect, and develop a multi-class queueing network game framework to study it. Each network service provider is modeled as a single-server multi-class queue. Providers post prices for various service classes. Traffic is elastic and there are multiple types of it, each traffic-type is sensitive to a different degree to Quality of Service (QoS). Arriving users choose a provider and a class for service. We study the pricing and service competition between the providers in a game-theoretic setting. We provide sufficient conditions for the existence of Nash equilibrium in the Bertrand (pricing) game between the multi-class queueing service providers. We also characterize the inefficiency (price of anarchy) due to strategic DiffServ pricing.",rahul jain,Nash equilibrium,2010.0,10.1109/ITC.2010.5608737,2010 22nd International Teletraffic Congress (lTC 22),Dube2010,False,,IEEE,Not available,DiffServ pricing games in multi-class queueing network models,bd7fdc8eb97936de5aa44a37eaa0c381,https://ieeexplore.ieee.org/document/5608737/
8924,"Introduction of differentiated services on the Internet has failed primarily due to many economic impediments. We focus on the provider competition aspect, and develop a multi-class queueing network game framework to study it. Each network service provider is modeled as a single-server multi-class queue. Providers post prices for various service classes. Traffic is elastic and there are multiple types of it, each traffic-type is sensitive to a different degree to Quality of Service (QoS). Arriving users choose a provider and a class for service. We study the pricing and service competition between the providers in a game-theoretic setting. We provide sufficient conditions for the existence of Nash equilibrium in the Bertrand (pricing) game between the multi-class queueing service providers. We also characterize the inefficiency (price of anarchy) due to strategic DiffServ pricing.",rahul jain,Price of Anarchy,2010.0,10.1109/ITC.2010.5608737,2010 22nd International Teletraffic Congress (lTC 22),Dube2010,False,,IEEE,Not available,DiffServ pricing games in multi-class queueing network models,bd7fdc8eb97936de5aa44a37eaa0c381,https://ieeexplore.ieee.org/document/5608737/
8925,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pratyush chakraborty,Nash equilibrium,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
8926,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pratyush chakraborty,Decentralized control,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
8927,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pratyush chakraborty,Optimization,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
8928,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8929,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pratyush chakraborty,Games,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
8930,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pratyush chakraborty,Electric vehicles,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
8931,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pratyush chakraborty,Schedules,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
8932,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pratyush chakraborty,Equations,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
8933,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pramod khargonekar,Nash equilibrium,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
8934,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pramod khargonekar,Decentralized control,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
8935,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pramod khargonekar,Optimization,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
8936,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pramod khargonekar,Games,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
8937,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pramod khargonekar,Electric vehicles,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
8938,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pramod khargonekar,Schedules,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
8939,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8940,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pramod khargonekar,Equations,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
8941,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",vladimir fux,Vehicles,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
8942,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",vladimir fux,Games,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
8943,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",vladimir fux,Roads,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
8944,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",vladimir fux,Pricing,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
8945,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",vladimir fux,Bandwidth,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
8946,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",vladimir fux,Wireless networks,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
8947,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",vladimir fux,Equations,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
8948,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",patrick maille,Vehicles,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
8949,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",patrick maille,Games,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
8950,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8951,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",patrick maille,Roads,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
8952,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",patrick maille,Pricing,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
8953,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",patrick maille,Bandwidth,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
8954,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",patrick maille,Wireless networks,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
8955,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",patrick maille,Equations,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
8956,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",matteo cesana,Vehicles,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
8957,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",matteo cesana,Games,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
8958,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",matteo cesana,Roads,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
8959,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",matteo cesana,Pricing,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
8960,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",matteo cesana,Bandwidth,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
8961,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8962,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",matteo cesana,Wireless networks,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
8963,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",matteo cesana,Equations,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
8964,"Several works have recently suggested to model the problem of coordinating the charging needs of a fleet of electric vehicles as a game, and have proposed distributed algorithms to coordinate the vehicles towards a Nash equilibrium of such game. However, Nash equilibria have been shown to posses desirable system-level properties only in simplified cases. In this letter, we use the concept of price of anarchy (PoA) to analyze the inefficiency of Nash equilibria when compared to the social optimum solution. More precisely, we show that: 1) for linear price functions depending on all the charging instants, the PoA converges to one as the population of vehicles grows; 2) for price functions that depend only on the instantaneous demand, the PoA converges to one if the price function takes the form of a positive pure monomial; and 3) for general classes of price functions, the asymptotic PoA can be bounded. For finite populations, we additionally provide a bound on the PoA as a function of the number vehicles in the system. We support the theoretical findings by means of numerical simulations.",dario paccagnan,Game theory,2018.0,10.1109/LCSYS.2018.2845674,IEEE Control Systems Letters,Paccagnan2018,False,,IEEE,Not available,On the Efficiency of Nash Equilibria in Aggregative Charging Games,7a18e44e1af260dc8d75edee6a2b0880,https://ieeexplore.ieee.org/document/8375654/
8965,"Several works have recently suggested to model the problem of coordinating the charging needs of a fleet of electric vehicles as a game, and have proposed distributed algorithms to coordinate the vehicles towards a Nash equilibrium of such game. However, Nash equilibria have been shown to posses desirable system-level properties only in simplified cases. In this letter, we use the concept of price of anarchy (PoA) to analyze the inefficiency of Nash equilibria when compared to the social optimum solution. More precisely, we show that: 1) for linear price functions depending on all the charging instants, the PoA converges to one as the population of vehicles grows; 2) for price functions that depend only on the instantaneous demand, the PoA converges to one if the price function takes the form of a positive pure monomial; and 3) for general classes of price functions, the asymptotic PoA can be bounded. For finite populations, we additionally provide a bound on the PoA as a function of the number vehicles in the system. We support the theoretical findings by means of numerical simulations.",dario paccagnan,optimization,2018.0,10.1109/LCSYS.2018.2845674,IEEE Control Systems Letters,Paccagnan2018,False,,IEEE,Not available,On the Efficiency of Nash Equilibria in Aggregative Charging Games,7a18e44e1af260dc8d75edee6a2b0880,https://ieeexplore.ieee.org/document/8375654/
8966,"Several works have recently suggested to model the problem of coordinating the charging needs of a fleet of electric vehicles as a game, and have proposed distributed algorithms to coordinate the vehicles towards a Nash equilibrium of such game. However, Nash equilibria have been shown to posses desirable system-level properties only in simplified cases. In this letter, we use the concept of price of anarchy (PoA) to analyze the inefficiency of Nash equilibria when compared to the social optimum solution. More precisely, we show that: 1) for linear price functions depending on all the charging instants, the PoA converges to one as the population of vehicles grows; 2) for price functions that depend only on the instantaneous demand, the PoA converges to one if the price function takes the form of a positive pure monomial; and 3) for general classes of price functions, the asymptotic PoA can be bounded. For finite populations, we additionally provide a bound on the PoA as a function of the number vehicles in the system. We support the theoretical findings by means of numerical simulations.",dario paccagnan,large-scale systems,2018.0,10.1109/LCSYS.2018.2845674,IEEE Control Systems Letters,Paccagnan2018,False,,IEEE,Not available,On the Efficiency of Nash Equilibria in Aggregative Charging Games,7a18e44e1af260dc8d75edee6a2b0880,https://ieeexplore.ieee.org/document/8375654/
8967,"Several works have recently suggested to model the problem of coordinating the charging needs of a fleet of electric vehicles as a game, and have proposed distributed algorithms to coordinate the vehicles towards a Nash equilibrium of such game. However, Nash equilibria have been shown to posses desirable system-level properties only in simplified cases. In this letter, we use the concept of price of anarchy (PoA) to analyze the inefficiency of Nash equilibria when compared to the social optimum solution. More precisely, we show that: 1) for linear price functions depending on all the charging instants, the PoA converges to one as the population of vehicles grows; 2) for price functions that depend only on the instantaneous demand, the PoA converges to one if the price function takes the form of a positive pure monomial; and 3) for general classes of price functions, the asymptotic PoA can be bounded. For finite populations, we additionally provide a bound on the PoA as a function of the number vehicles in the system. We support the theoretical findings by means of numerical simulations.",francesca parise,Game theory,2018.0,10.1109/LCSYS.2018.2845674,IEEE Control Systems Letters,Paccagnan2018,False,,IEEE,Not available,On the Efficiency of Nash Equilibria in Aggregative Charging Games,7a18e44e1af260dc8d75edee6a2b0880,https://ieeexplore.ieee.org/document/8375654/
8968,"Several works have recently suggested to model the problem of coordinating the charging needs of a fleet of electric vehicles as a game, and have proposed distributed algorithms to coordinate the vehicles towards a Nash equilibrium of such game. However, Nash equilibria have been shown to posses desirable system-level properties only in simplified cases. In this letter, we use the concept of price of anarchy (PoA) to analyze the inefficiency of Nash equilibria when compared to the social optimum solution. More precisely, we show that: 1) for linear price functions depending on all the charging instants, the PoA converges to one as the population of vehicles grows; 2) for price functions that depend only on the instantaneous demand, the PoA converges to one if the price function takes the form of a positive pure monomial; and 3) for general classes of price functions, the asymptotic PoA can be bounded. For finite populations, we additionally provide a bound on the PoA as a function of the number vehicles in the system. We support the theoretical findings by means of numerical simulations.",francesca parise,optimization,2018.0,10.1109/LCSYS.2018.2845674,IEEE Control Systems Letters,Paccagnan2018,False,,IEEE,Not available,On the Efficiency of Nash Equilibria in Aggregative Charging Games,7a18e44e1af260dc8d75edee6a2b0880,https://ieeexplore.ieee.org/document/8375654/
8969,"Several works have recently suggested to model the problem of coordinating the charging needs of a fleet of electric vehicles as a game, and have proposed distributed algorithms to coordinate the vehicles towards a Nash equilibrium of such game. However, Nash equilibria have been shown to posses desirable system-level properties only in simplified cases. In this letter, we use the concept of price of anarchy (PoA) to analyze the inefficiency of Nash equilibria when compared to the social optimum solution. More precisely, we show that: 1) for linear price functions depending on all the charging instants, the PoA converges to one as the population of vehicles grows; 2) for price functions that depend only on the instantaneous demand, the PoA converges to one if the price function takes the form of a positive pure monomial; and 3) for general classes of price functions, the asymptotic PoA can be bounded. For finite populations, we additionally provide a bound on the PoA as a function of the number vehicles in the system. We support the theoretical findings by means of numerical simulations.",francesca parise,large-scale systems,2018.0,10.1109/LCSYS.2018.2845674,IEEE Control Systems Letters,Paccagnan2018,False,,IEEE,Not available,On the Efficiency of Nash Equilibria in Aggregative Charging Games,7a18e44e1af260dc8d75edee6a2b0880,https://ieeexplore.ieee.org/document/8375654/
8970,"Several works have recently suggested to model the problem of coordinating the charging needs of a fleet of electric vehicles as a game, and have proposed distributed algorithms to coordinate the vehicles towards a Nash equilibrium of such game. However, Nash equilibria have been shown to posses desirable system-level properties only in simplified cases. In this letter, we use the concept of price of anarchy (PoA) to analyze the inefficiency of Nash equilibria when compared to the social optimum solution. More precisely, we show that: 1) for linear price functions depending on all the charging instants, the PoA converges to one as the population of vehicles grows; 2) for price functions that depend only on the instantaneous demand, the PoA converges to one if the price function takes the form of a positive pure monomial; and 3) for general classes of price functions, the asymptotic PoA can be bounded. For finite populations, we additionally provide a bound on the PoA as a function of the number vehicles in the system. We support the theoretical findings by means of numerical simulations.",john lygeros,Game theory,2018.0,10.1109/LCSYS.2018.2845674,IEEE Control Systems Letters,Paccagnan2018,False,,IEEE,Not available,On the Efficiency of Nash Equilibria in Aggregative Charging Games,7a18e44e1af260dc8d75edee6a2b0880,https://ieeexplore.ieee.org/document/8375654/
8971,"Several works have recently suggested to model the problem of coordinating the charging needs of a fleet of electric vehicles as a game, and have proposed distributed algorithms to coordinate the vehicles towards a Nash equilibrium of such game. However, Nash equilibria have been shown to posses desirable system-level properties only in simplified cases. In this letter, we use the concept of price of anarchy (PoA) to analyze the inefficiency of Nash equilibria when compared to the social optimum solution. More precisely, we show that: 1) for linear price functions depending on all the charging instants, the PoA converges to one as the population of vehicles grows; 2) for price functions that depend only on the instantaneous demand, the PoA converges to one if the price function takes the form of a positive pure monomial; and 3) for general classes of price functions, the asymptotic PoA can be bounded. For finite populations, we additionally provide a bound on the PoA as a function of the number vehicles in the system. We support the theoretical findings by means of numerical simulations.",john lygeros,optimization,2018.0,10.1109/LCSYS.2018.2845674,IEEE Control Systems Letters,Paccagnan2018,False,,IEEE,Not available,On the Efficiency of Nash Equilibria in Aggregative Charging Games,7a18e44e1af260dc8d75edee6a2b0880,https://ieeexplore.ieee.org/document/8375654/
8972,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8973,"Several works have recently suggested to model the problem of coordinating the charging needs of a fleet of electric vehicles as a game, and have proposed distributed algorithms to coordinate the vehicles towards a Nash equilibrium of such game. However, Nash equilibria have been shown to posses desirable system-level properties only in simplified cases. In this letter, we use the concept of price of anarchy (PoA) to analyze the inefficiency of Nash equilibria when compared to the social optimum solution. More precisely, we show that: 1) for linear price functions depending on all the charging instants, the PoA converges to one as the population of vehicles grows; 2) for price functions that depend only on the instantaneous demand, the PoA converges to one if the price function takes the form of a positive pure monomial; and 3) for general classes of price functions, the asymptotic PoA can be bounded. For finite populations, we additionally provide a bound on the PoA as a function of the number vehicles in the system. We support the theoretical findings by means of numerical simulations.",john lygeros,large-scale systems,2018.0,10.1109/LCSYS.2018.2845674,IEEE Control Systems Letters,Paccagnan2018,False,,IEEE,Not available,On the Efficiency of Nash Equilibria in Aggregative Charging Games,7a18e44e1af260dc8d75edee6a2b0880,https://ieeexplore.ieee.org/document/8375654/
8974,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
8975,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
8976,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
8977,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
8978,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
8979,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
8980,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
8981,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
8982,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
8983,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8984,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
8985,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
8986,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
8987,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
8988,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
8989,"Allowing selfish agents to acquire and exploit system information has both positive and negative effects on the overall performance of resource allocation systems. The positive effect results from reduction in the uncertainty inherently present in large-scale systems. The negative effect, which can be mitigated through congestion pricing, is due to agent selfishness. However, current research, concentrated around the notion of “Price of Anarchy”, is mostly concerned with the negative effect. This paper evaluates systemic risks/benefits of selfish agent ability to acquire and exploit dynamic system information in a specific case of selfish routing in a large-scale, random, loss network. Our analysis indicates that the beneficial effect of this ability dominates in a case of high system uncertainty - low load, while the negative effect dominates in a case of low system uncertainty - high load. In the intermediate cases while the beneficial effect still dominates in the “normal” operating mode, the negative effect manifests itself in a risk of cascading overload driving the system to an emergent metastable, i.e., persistent, congested mode. Future research should consider resource allocation models with elastic selfish users and evaluate effect of the congestion pricing.",v. marbukh,selfish agents,2012.0,10.1109/NOMS.2012.6211986,2012 IEEE Network Operations and Management Symposium,Marbukh2012,False,,IEEE,Not available,Systemic risks/benefits of selfish network operations &amp; management in dynamic environment,40489152c1d5cdc0c00098a85c1cae3c,https://ieeexplore.ieee.org/document/6211986/
8990,"Allowing selfish agents to acquire and exploit system information has both positive and negative effects on the overall performance of resource allocation systems. The positive effect results from reduction in the uncertainty inherently present in large-scale systems. The negative effect, which can be mitigated through congestion pricing, is due to agent selfishness. However, current research, concentrated around the notion of “Price of Anarchy”, is mostly concerned with the negative effect. This paper evaluates systemic risks/benefits of selfish agent ability to acquire and exploit dynamic system information in a specific case of selfish routing in a large-scale, random, loss network. Our analysis indicates that the beneficial effect of this ability dominates in a case of high system uncertainty - low load, while the negative effect dominates in a case of low system uncertainty - high load. In the intermediate cases while the beneficial effect still dominates in the “normal” operating mode, the negative effect manifests itself in a risk of cascading overload driving the system to an emergent metastable, i.e., persistent, congested mode. Future research should consider resource allocation models with elastic selfish users and evaluate effect of the congestion pricing.",v. marbukh,information availability,2012.0,10.1109/NOMS.2012.6211986,2012 IEEE Network Operations and Management Symposium,Marbukh2012,False,,IEEE,Not available,Systemic risks/benefits of selfish network operations &amp; management in dynamic environment,40489152c1d5cdc0c00098a85c1cae3c,https://ieeexplore.ieee.org/document/6211986/
8991,"Allowing selfish agents to acquire and exploit system information has both positive and negative effects on the overall performance of resource allocation systems. The positive effect results from reduction in the uncertainty inherently present in large-scale systems. The negative effect, which can be mitigated through congestion pricing, is due to agent selfishness. However, current research, concentrated around the notion of “Price of Anarchy”, is mostly concerned with the negative effect. This paper evaluates systemic risks/benefits of selfish agent ability to acquire and exploit dynamic system information in a specific case of selfish routing in a large-scale, random, loss network. Our analysis indicates that the beneficial effect of this ability dominates in a case of high system uncertainty - low load, while the negative effect dominates in a case of low system uncertainty - high load. In the intermediate cases while the beneficial effect still dominates in the “normal” operating mode, the negative effect manifests itself in a risk of cascading overload driving the system to an emergent metastable, i.e., persistent, congested mode. Future research should consider resource allocation models with elastic selfish users and evaluate effect of the congestion pricing.",v. marbukh,systemic risk,2012.0,10.1109/NOMS.2012.6211986,2012 IEEE Network Operations and Management Symposium,Marbukh2012,False,,IEEE,Not available,Systemic risks/benefits of selfish network operations &amp; management in dynamic environment,40489152c1d5cdc0c00098a85c1cae3c,https://ieeexplore.ieee.org/document/6211986/
8992,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",chi chau,Routing,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
8993,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",chi chau,Monopoly,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
8994,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
8995,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
8996,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",chi chau,Pricing,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
8997,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",chi chau,Multiprotocol label switching,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
8998,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",chi chau,IP networks,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
8999,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",chi chau,Delay,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
9000,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",chi chau,Web and internet services,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
9001,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",chi chau,Control systems,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
9002,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",chi chau,Communication system traffic control,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
9003,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",chi chau,Upper bound,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
9004,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",kwang sim,Routing,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
9005,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",kwang sim,Monopoly,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
9006,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
9007,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",kwang sim,Pricing,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
9008,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",kwang sim,Multiprotocol label switching,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
9009,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",kwang sim,IP networks,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
9010,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",kwang sim,Delay,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
9011,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",kwang sim,Web and internet services,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
9012,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",kwang sim,Control systems,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
9013,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",kwang sim,Communication system traffic control,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
9014,"Using the price of anarchy (PA) and the price of monopoly (PM), the impact of selfish behaviors of noncooperative users and profit seeking operators respectively are studied. Although PA characterizes the impact of complete deregulation, and PM characterizes the impact of complete regulation, this paper shows that they are related as primal and dual ratios of two correlated optimization problems. An approach to derive bounds of both these ratios is proposed, and numerical bounds of both prices are derived in simple affine settings.",kwang sim,Upper bound,2003.0,10.1109/LCOMM.2003.817324,IEEE Communications Letters,Chau2003,False,,IEEE,Not available,Analyzing the impact of selfish behaviors of Internet users and operators,88f676bb851976dd2f35537e71547567,https://ieeexplore.ieee.org/document/1232510/
9015,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Pricing,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
9016,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Routing,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
9017,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9018,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Relays,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
9019,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Telecommunication traffic,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
9020,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Spread spectrum communication,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
9021,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Network topology,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
9022,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Oligopoly,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
9023,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Costs,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
9024,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Traffic control,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
9025,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Communication networks,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
9026,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Pricing,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
9027,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Routing,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
9028,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9029,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Relays,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
9030,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Telecommunication traffic,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
9031,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Spread spectrum communication,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
9032,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Network topology,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
9033,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Oligopoly,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
9034,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Costs,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
9035,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Traffic control,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
9036,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Communication networks,2009.0,10.1109/ALLERTON.2009.5394772,"2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in relay networks",5cda6d8da94117c98261ff17c541f41e,https://ieeexplore.ieee.org/document/5394772/
9037,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",tobias harks,Stability,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
9038,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",tobias harks,Resource management,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
9039,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9040,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",tobias harks,Cost function,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
9041,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",tobias harks,Nash equilibrium,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
9042,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",tobias harks,Pricing,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
9043,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",tobias harks,Aggregates,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
9044,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",tobias harks,Polynomials,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
9045,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",tobias harks,Transport protocols,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
9046,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",tobias harks,Delay,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
9047,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",tobias harks,Roads,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
9048,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",konstantin miller,Stability,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
9049,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",konstantin miller,Resource management,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
9050,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9051,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",konstantin miller,Cost function,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
9052,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",konstantin miller,Nash equilibrium,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
9053,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",konstantin miller,Pricing,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
9054,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",konstantin miller,Aggregates,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
9055,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",konstantin miller,Polynomials,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
9056,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",konstantin miller,Transport protocols,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
9057,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",konstantin miller,Delay,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
9058,"We study resource allocation games, where users send data along paths and links in the network charge a price equal to marginal cost. When users are price taking, it is known that there exist distributed dynamics that converge towards a fully efficient Nash equilibrium. When users are price anticipating, however, a Nash equilibrium does not maximize total utility in general. In this paper, we explore the inefficiency of Nash equilibria for general networks and semi-convex marginal cost functions. While it is known that for m ges 2 users and convex marginal cost functions, no efficiency guarantee is possible, we prove that an additional differentiability assumption on marginal cost functions implies a bounded efficiency loss of 2/(2 m + 1). For polynomial marginal cost functions with nonnegative coefficients, we precisely characterize the price of anarchy. We also prove that the efficiency of Nash equilibria significantly improves if all users have the same strategy space and the same utility function. We propose a class of distributed dynamics and prove that whenever a game admits a potential function, these dynamics globally converge to a Nash equilibrium. Finally, we show that in general the only class of marginal cost functions that guarantees the existence of a potential function are affine linear functions.",konstantin miller,Roads,2009.0,10.1109/GAMENETS.2009.5137425,2009 International Conference on Game Theory for Networks,Harks2009,False,,IEEE,Not available,Efficiency and stability of Nash equilibria in resource allocation games,810b7c10f8663675065da671ceb1b703,https://ieeexplore.ieee.org/document/5137425/
9059,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",pavan nuggehalli,Pricing,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
9060,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",pavan nuggehalli,Media Access Protocol,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
9061,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9062,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",pavan nuggehalli,Resource management,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
9063,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",pavan nuggehalli,Throughput,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
9064,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",pavan nuggehalli,Springs,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
9065,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",pavan nuggehalli,Wireless networks,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
9066,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",pavan nuggehalli,Nash equilibrium,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
9067,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",pavan nuggehalli,Access protocols,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
9068,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",pavan nuggehalli,Quality of service,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
9069,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",pavan nuggehalli,Costs,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
9070,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",jennifer price,Pricing,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
9071,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",jennifer price,Media Access Protocol,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
9072,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9073,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",jennifer price,Resource management,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
9074,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",jennifer price,Throughput,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
9075,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",jennifer price,Springs,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
9076,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",jennifer price,Wireless networks,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
9077,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",jennifer price,Nash equilibrium,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
9078,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",jennifer price,Access protocols,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
9079,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",jennifer price,Quality of service,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
9080,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",jennifer price,Costs,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
9081,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",tara javidi,Pricing,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
9082,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",tara javidi,Media Access Protocol,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
9083,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9084,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",tara javidi,Resource management,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
9085,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",tara javidi,Throughput,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
9086,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",tara javidi,Springs,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
9087,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",tara javidi,Wireless networks,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
9088,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",tara javidi,Nash equilibrium,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
9089,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",tara javidi,Access protocols,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
9090,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",tara javidi,Quality of service,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
9091,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",tara javidi,Costs,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
9092,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",hamed mohsenian-rad,Inter-session network coding,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
9093,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",hamed mohsenian-rad,butterfly network,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
9094,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9095,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",hamed mohsenian-rad,game theory,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
9096,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",hamed mohsenian-rad,Nash equilibrium,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
9097,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",hamed mohsenian-rad,price-of-anarchy,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
9098,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",hamed mohsenian-rad,efficiency bound,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
9099,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",jianwei huang,Inter-session network coding,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
9100,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",jianwei huang,butterfly network,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
9101,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",jianwei huang,game theory,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
9102,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",jianwei huang,Nash equilibrium,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
9103,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",jianwei huang,price-of-anarchy,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
9104,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",jianwei huang,efficiency bound,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
9105,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
9106,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9107,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",vincent wong,Inter-session network coding,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
9108,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",vincent wong,butterfly network,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
9109,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",vincent wong,game theory,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
9110,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",vincent wong,Nash equilibrium,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
9111,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",vincent wong,price-of-anarchy,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
9112,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",vincent wong,efficiency bound,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
9113,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",sidharth jaggi,Inter-session network coding,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
9114,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",sidharth jaggi,butterfly network,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
9115,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",sidharth jaggi,game theory,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
9116,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",sidharth jaggi,Nash equilibrium,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
9117,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9118,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",sidharth jaggi,price-of-anarchy,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
9119,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",sidharth jaggi,efficiency bound,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
9120,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",robert schober,Inter-session network coding,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
9121,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",robert schober,butterfly network,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
9122,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",robert schober,game theory,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
9123,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",robert schober,Nash equilibrium,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
9124,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",robert schober,price-of-anarchy,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
9125,"We analyze inter-session network coding in a wired network using game theory. We assume that users are selfish and act as strategic players to maximize their own utility, which leads to a resource allocation game among users. In particular, we study a butterfly network, where a bottleneck link is shared by network coding and routing flows. We assume that network coding is performed using pairwise XOR operations. We prove the existence of Nash equilibrium for a wide range of utility functions. We also show that the number of Nash equilibria can be large (even infinite) for certain choices of parameters. This is in sharp contrast to a similar game setting with traditional packet forwarding, where the Nash equilibrium is always unique. We characterize the worst-case efficiency bound, i.e., the Price-of-Anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a discriminatory pricing scheme which charges encoded and forwarded packets differently, we can improve the PoA in comparison with the case where a single pricing scheme is used. However, even when a discriminatory pricing scheme is used, the PoA is still worse than for the case when network coding is not applied. This implies that, although inter-session network coding can improve performance compared to routing, it is much more sensitive to users' strategic behavior.",robert schober,efficiency bound,2013.0,10.1109/TCOMM.2013.021413.110555,IEEE Transactions on Communications,Mohsenian-Rad2013,False,,IEEE,Not available,Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,54461e66c944fa2ce390a4d1f4c84519,https://ieeexplore.ieee.org/document/6466332/
9126,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",xuehe wang,Noncooperative congestion game,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
9127,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",xuehe wang,price of anarchy,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
9128,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9129,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",xuehe wang,price of total anarchy,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
9130,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",xuehe wang,road pricing,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
9131,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",xuehe wang,traffic networks,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
9132,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",nan xiao,Noncooperative congestion game,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
9133,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",nan xiao,price of anarchy,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
9134,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",nan xiao,price of total anarchy,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
9135,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",nan xiao,road pricing,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
9136,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",nan xiao,traffic networks,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
9137,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",lihua xie,Noncooperative congestion game,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
9138,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",lihua xie,price of anarchy,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
9139,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9140,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",lihua xie,price of total anarchy,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
9141,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",lihua xie,road pricing,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
9142,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",lihua xie,traffic networks,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
9143,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",emilio frazzoli,Noncooperative congestion game,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
9144,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",emilio frazzoli,price of anarchy,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
9145,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",emilio frazzoli,price of total anarchy,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
9146,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",emilio frazzoli,road pricing,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
9147,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",emilio frazzoli,traffic networks,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
9148,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",daniela rus,Noncooperative congestion game,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
9149,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",daniela rus,price of anarchy,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
9150,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9151,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",daniela rus,price of total anarchy,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
9152,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",daniela rus,road pricing,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
9153,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",daniela rus,traffic networks,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
9154,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Pricing,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
9155,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Routing,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
9156,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Spread spectrum communication,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
9157,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Relays,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
9158,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Telecommunication traffic,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
9159,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Oligopoly,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
9160,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Network topology,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
9161,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9162,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Costs,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
9163,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Conferences,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
9164,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",yufang xi,Computer networks,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
9165,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Pricing,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
9166,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Routing,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
9167,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Spread spectrum communication,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
9168,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Relays,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
9169,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Telecommunication traffic,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
9170,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Oligopoly,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
9171,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Network topology,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
9172,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9173,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Costs,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
9174,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Conferences,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
9175,"We study multi-hop relay networks where pricing is used to provide incentives for forwarding traffic. In these networks, nodes price their services strategically to maximize its profit from forwarding traffic, and allocate their received traffic to service providers to minimize the amount paid. In the resulting pricing game, we show that the socially optimal network routing can always be induced by an equilibrium. However, inefficient equilibria also exist. In particular, we show that inefficiencies stem from the intrinsic multi-hop network structure and can give rise to an infinite price of anarchy. This phenomenon is a fundamental issue for multi-hop networks, which persists even when the source has elastic demand.",edmund yeh,Computer networks,2009.0,10.1109/CAMSAP.2009.5413297,2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),Xi2009,False,,IEEE,Not available,"Pricing, competition, and routing in multi-hop networks",453f490a0e502f7d0b77802d8787ec23,https://ieeexplore.ieee.org/document/5413297/
9176,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",paul dutting,mechanism design,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
9177,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",paul dutting,posted prices,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
9178,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",paul dutting,price of anarchy,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
9179,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",paul dutting,prophet inequalities,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
9180,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",paul dutting,smoothness,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
9181,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",michal feldman,mechanism design,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
9182,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",michal feldman,posted prices,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
9183,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9184,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",michal feldman,price of anarchy,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
9185,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",michal feldman,prophet inequalities,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
9186,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",michal feldman,smoothness,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
9187,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",thomas kesselheim,mechanism design,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
9188,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",thomas kesselheim,posted prices,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
9189,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",thomas kesselheim,price of anarchy,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
9190,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",thomas kesselheim,prophet inequalities,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
9191,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",thomas kesselheim,smoothness,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
9192,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",brendan lucier,mechanism design,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
9193,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",brendan lucier,posted prices,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
9194,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9195,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",brendan lucier,price of anarchy,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
9196,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",brendan lucier,prophet inequalities,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
9197,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",brendan lucier,smoothness,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
9198,"This paper focuses on the design of local agent objective functions for resource allocation problems with separable, convex, and increasing system level objective functions. We employ two well-known measures to characterize the quality of local utility functions: Price of Anarchy (PoA) and Price of Stability (PoS), which provide a measure the best and worst Nash equilibrium, respectively. Our main results characterize the tradeoff between optimizing the PoA and optimizing the PoS; we show that if optimal PoA (resp. PoS) is achieved, there is a limitation on the achievable PoS (resp. PoA). Further, we show that the Shapley value objective function is the unique rule which optimizes PoA followed by PoS, and the marginal contribution rule is the unique rule which optimizes PoS followed by PoA. Lastly, we show that relaxation in the objective of optimizing PoA impacts the attainable PoS guarantees.",emily jensen,Games,2018.0,10.23919/ACC.2018.8431131,2018 Annual American Control Conference (ACC),Jensen2018,False,,IEEE,Not available,Optimal Utility Design in Convex Distributed Welfare Games,f69f7610c53e7b970ab060b2b2581fa1,https://ieeexplore.ieee.org/document/8431131/
9199,"This paper focuses on the design of local agent objective functions for resource allocation problems with separable, convex, and increasing system level objective functions. We employ two well-known measures to characterize the quality of local utility functions: Price of Anarchy (PoA) and Price of Stability (PoS), which provide a measure the best and worst Nash equilibrium, respectively. Our main results characterize the tradeoff between optimizing the PoA and optimizing the PoS; we show that if optimal PoA (resp. PoS) is achieved, there is a limitation on the achievable PoS (resp. PoA). Further, we show that the Shapley value objective function is the unique rule which optimizes PoA followed by PoS, and the marginal contribution rule is the unique rule which optimizes PoS followed by PoA. Lastly, we show that relaxation in the objective of optimizing PoA impacts the attainable PoS guarantees.",emily jensen,Resource management,2018.0,10.23919/ACC.2018.8431131,2018 Annual American Control Conference (ACC),Jensen2018,False,,IEEE,Not available,Optimal Utility Design in Convex Distributed Welfare Games,f69f7610c53e7b970ab060b2b2581fa1,https://ieeexplore.ieee.org/document/8431131/
9200,"This paper focuses on the design of local agent objective functions for resource allocation problems with separable, convex, and increasing system level objective functions. We employ two well-known measures to characterize the quality of local utility functions: Price of Anarchy (PoA) and Price of Stability (PoS), which provide a measure the best and worst Nash equilibrium, respectively. Our main results characterize the tradeoff between optimizing the PoA and optimizing the PoS; we show that if optimal PoA (resp. PoS) is achieved, there is a limitation on the achievable PoS (resp. PoA). Further, we show that the Shapley value objective function is the unique rule which optimizes PoA followed by PoS, and the marginal contribution rule is the unique rule which optimizes PoS followed by PoA. Lastly, we show that relaxation in the objective of optimizing PoA impacts the attainable PoS guarantees.",emily jensen,Linear programming,2018.0,10.23919/ACC.2018.8431131,2018 Annual American Control Conference (ACC),Jensen2018,False,,IEEE,Not available,Optimal Utility Design in Convex Distributed Welfare Games,f69f7610c53e7b970ab060b2b2581fa1,https://ieeexplore.ieee.org/document/8431131/
9201,"This paper focuses on the design of local agent objective functions for resource allocation problems with separable, convex, and increasing system level objective functions. We employ two well-known measures to characterize the quality of local utility functions: Price of Anarchy (PoA) and Price of Stability (PoS), which provide a measure the best and worst Nash equilibrium, respectively. Our main results characterize the tradeoff between optimizing the PoA and optimizing the PoS; we show that if optimal PoA (resp. PoS) is achieved, there is a limitation on the achievable PoS (resp. PoA). Further, we show that the Shapley value objective function is the unique rule which optimizes PoA followed by PoS, and the marginal contribution rule is the unique rule which optimizes PoS followed by PoA. Lastly, we show that relaxation in the objective of optimizing PoA impacts the attainable PoS guarantees.",emily jensen,Nash equilibrium,2018.0,10.23919/ACC.2018.8431131,2018 Annual American Control Conference (ACC),Jensen2018,False,,IEEE,Not available,Optimal Utility Design in Convex Distributed Welfare Games,f69f7610c53e7b970ab060b2b2581fa1,https://ieeexplore.ieee.org/document/8431131/
9202,"This paper focuses on the design of local agent objective functions for resource allocation problems with separable, convex, and increasing system level objective functions. We employ two well-known measures to characterize the quality of local utility functions: Price of Anarchy (PoA) and Price of Stability (PoS), which provide a measure the best and worst Nash equilibrium, respectively. Our main results characterize the tradeoff between optimizing the PoA and optimizing the PoS; we show that if optimal PoA (resp. PoS) is achieved, there is a limitation on the achievable PoS (resp. PoA). Further, we show that the Shapley value objective function is the unique rule which optimizes PoA followed by PoS, and the marginal contribution rule is the unique rule which optimizes PoS followed by PoA. Lastly, we show that relaxation in the objective of optimizing PoA impacts the attainable PoS guarantees.",emily jensen,Transportation,2018.0,10.23919/ACC.2018.8431131,2018 Annual American Control Conference (ACC),Jensen2018,False,,IEEE,Not available,Optimal Utility Design in Convex Distributed Welfare Games,f69f7610c53e7b970ab060b2b2581fa1,https://ieeexplore.ieee.org/document/8431131/
9203,"This paper focuses on the design of local agent objective functions for resource allocation problems with separable, convex, and increasing system level objective functions. We employ two well-known measures to characterize the quality of local utility functions: Price of Anarchy (PoA) and Price of Stability (PoS), which provide a measure the best and worst Nash equilibrium, respectively. Our main results characterize the tradeoff between optimizing the PoA and optimizing the PoS; we show that if optimal PoA (resp. PoS) is achieved, there is a limitation on the achievable PoS (resp. PoA). Further, we show that the Shapley value objective function is the unique rule which optimizes PoA followed by PoS, and the marginal contribution rule is the unique rule which optimizes PoS followed by PoA. Lastly, we show that relaxation in the objective of optimizing PoA impacts the attainable PoS guarantees.",emily jensen,Measurement,2018.0,10.23919/ACC.2018.8431131,2018 Annual American Control Conference (ACC),Jensen2018,False,,IEEE,Not available,Optimal Utility Design in Convex Distributed Welfare Games,f69f7610c53e7b970ab060b2b2581fa1,https://ieeexplore.ieee.org/document/8431131/
9204,"This paper focuses on the design of local agent objective functions for resource allocation problems with separable, convex, and increasing system level objective functions. We employ two well-known measures to characterize the quality of local utility functions: Price of Anarchy (PoA) and Price of Stability (PoS), which provide a measure the best and worst Nash equilibrium, respectively. Our main results characterize the tradeoff between optimizing the PoA and optimizing the PoS; we show that if optimal PoA (resp. PoS) is achieved, there is a limitation on the achievable PoS (resp. PoA). Further, we show that the Shapley value objective function is the unique rule which optimizes PoA followed by PoS, and the marginal contribution rule is the unique rule which optimizes PoS followed by PoA. Lastly, we show that relaxation in the objective of optimizing PoA impacts the attainable PoS guarantees.",emily jensen,Task analysis,2018.0,10.23919/ACC.2018.8431131,2018 Annual American Control Conference (ACC),Jensen2018,False,,IEEE,Not available,Optimal Utility Design in Convex Distributed Welfare Games,f69f7610c53e7b970ab060b2b2581fa1,https://ieeexplore.ieee.org/document/8431131/
9205,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9206,"This paper focuses on the design of local agent objective functions for resource allocation problems with separable, convex, and increasing system level objective functions. We employ two well-known measures to characterize the quality of local utility functions: Price of Anarchy (PoA) and Price of Stability (PoS), which provide a measure the best and worst Nash equilibrium, respectively. Our main results characterize the tradeoff between optimizing the PoA and optimizing the PoS; we show that if optimal PoA (resp. PoS) is achieved, there is a limitation on the achievable PoS (resp. PoA). Further, we show that the Shapley value objective function is the unique rule which optimizes PoA followed by PoS, and the marginal contribution rule is the unique rule which optimizes PoS followed by PoA. Lastly, we show that relaxation in the objective of optimizing PoA impacts the attainable PoS guarantees.",jason marden,Games,2018.0,10.23919/ACC.2018.8431131,2018 Annual American Control Conference (ACC),Jensen2018,False,,IEEE,Not available,Optimal Utility Design in Convex Distributed Welfare Games,f69f7610c53e7b970ab060b2b2581fa1,https://ieeexplore.ieee.org/document/8431131/
9207,"This paper focuses on the design of local agent objective functions for resource allocation problems with separable, convex, and increasing system level objective functions. We employ two well-known measures to characterize the quality of local utility functions: Price of Anarchy (PoA) and Price of Stability (PoS), which provide a measure the best and worst Nash equilibrium, respectively. Our main results characterize the tradeoff between optimizing the PoA and optimizing the PoS; we show that if optimal PoA (resp. PoS) is achieved, there is a limitation on the achievable PoS (resp. PoA). Further, we show that the Shapley value objective function is the unique rule which optimizes PoA followed by PoS, and the marginal contribution rule is the unique rule which optimizes PoS followed by PoA. Lastly, we show that relaxation in the objective of optimizing PoA impacts the attainable PoS guarantees.",jason marden,Resource management,2018.0,10.23919/ACC.2018.8431131,2018 Annual American Control Conference (ACC),Jensen2018,False,,IEEE,Not available,Optimal Utility Design in Convex Distributed Welfare Games,f69f7610c53e7b970ab060b2b2581fa1,https://ieeexplore.ieee.org/document/8431131/
9208,"This paper focuses on the design of local agent objective functions for resource allocation problems with separable, convex, and increasing system level objective functions. We employ two well-known measures to characterize the quality of local utility functions: Price of Anarchy (PoA) and Price of Stability (PoS), which provide a measure the best and worst Nash equilibrium, respectively. Our main results characterize the tradeoff between optimizing the PoA and optimizing the PoS; we show that if optimal PoA (resp. PoS) is achieved, there is a limitation on the achievable PoS (resp. PoA). Further, we show that the Shapley value objective function is the unique rule which optimizes PoA followed by PoS, and the marginal contribution rule is the unique rule which optimizes PoS followed by PoA. Lastly, we show that relaxation in the objective of optimizing PoA impacts the attainable PoS guarantees.",jason marden,Linear programming,2018.0,10.23919/ACC.2018.8431131,2018 Annual American Control Conference (ACC),Jensen2018,False,,IEEE,Not available,Optimal Utility Design in Convex Distributed Welfare Games,f69f7610c53e7b970ab060b2b2581fa1,https://ieeexplore.ieee.org/document/8431131/
9209,"This paper focuses on the design of local agent objective functions for resource allocation problems with separable, convex, and increasing system level objective functions. We employ two well-known measures to characterize the quality of local utility functions: Price of Anarchy (PoA) and Price of Stability (PoS), which provide a measure the best and worst Nash equilibrium, respectively. Our main results characterize the tradeoff between optimizing the PoA and optimizing the PoS; we show that if optimal PoA (resp. PoS) is achieved, there is a limitation on the achievable PoS (resp. PoA). Further, we show that the Shapley value objective function is the unique rule which optimizes PoA followed by PoS, and the marginal contribution rule is the unique rule which optimizes PoS followed by PoA. Lastly, we show that relaxation in the objective of optimizing PoA impacts the attainable PoS guarantees.",jason marden,Nash equilibrium,2018.0,10.23919/ACC.2018.8431131,2018 Annual American Control Conference (ACC),Jensen2018,False,,IEEE,Not available,Optimal Utility Design in Convex Distributed Welfare Games,f69f7610c53e7b970ab060b2b2581fa1,https://ieeexplore.ieee.org/document/8431131/
9210,"This paper focuses on the design of local agent objective functions for resource allocation problems with separable, convex, and increasing system level objective functions. We employ two well-known measures to characterize the quality of local utility functions: Price of Anarchy (PoA) and Price of Stability (PoS), which provide a measure the best and worst Nash equilibrium, respectively. Our main results characterize the tradeoff between optimizing the PoA and optimizing the PoS; we show that if optimal PoA (resp. PoS) is achieved, there is a limitation on the achievable PoS (resp. PoA). Further, we show that the Shapley value objective function is the unique rule which optimizes PoA followed by PoS, and the marginal contribution rule is the unique rule which optimizes PoS followed by PoA. Lastly, we show that relaxation in the objective of optimizing PoA impacts the attainable PoS guarantees.",jason marden,Transportation,2018.0,10.23919/ACC.2018.8431131,2018 Annual American Control Conference (ACC),Jensen2018,False,,IEEE,Not available,Optimal Utility Design in Convex Distributed Welfare Games,f69f7610c53e7b970ab060b2b2581fa1,https://ieeexplore.ieee.org/document/8431131/
9211,"This paper focuses on the design of local agent objective functions for resource allocation problems with separable, convex, and increasing system level objective functions. We employ two well-known measures to characterize the quality of local utility functions: Price of Anarchy (PoA) and Price of Stability (PoS), which provide a measure the best and worst Nash equilibrium, respectively. Our main results characterize the tradeoff between optimizing the PoA and optimizing the PoS; we show that if optimal PoA (resp. PoS) is achieved, there is a limitation on the achievable PoS (resp. PoA). Further, we show that the Shapley value objective function is the unique rule which optimizes PoA followed by PoS, and the marginal contribution rule is the unique rule which optimizes PoS followed by PoA. Lastly, we show that relaxation in the objective of optimizing PoA impacts the attainable PoS guarantees.",jason marden,Measurement,2018.0,10.23919/ACC.2018.8431131,2018 Annual American Control Conference (ACC),Jensen2018,False,,IEEE,Not available,Optimal Utility Design in Convex Distributed Welfare Games,f69f7610c53e7b970ab060b2b2581fa1,https://ieeexplore.ieee.org/document/8431131/
9212,"This paper focuses on the design of local agent objective functions for resource allocation problems with separable, convex, and increasing system level objective functions. We employ two well-known measures to characterize the quality of local utility functions: Price of Anarchy (PoA) and Price of Stability (PoS), which provide a measure the best and worst Nash equilibrium, respectively. Our main results characterize the tradeoff between optimizing the PoA and optimizing the PoS; we show that if optimal PoA (resp. PoS) is achieved, there is a limitation on the achievable PoS (resp. PoA). Further, we show that the Shapley value objective function is the unique rule which optimizes PoA followed by PoS, and the marginal contribution rule is the unique rule which optimizes PoS followed by PoA. Lastly, we show that relaxation in the objective of optimizing PoA impacts the attainable PoS guarantees.",jason marden,Task analysis,2018.0,10.23919/ACC.2018.8431131,2018 Annual American Control Conference (ACC),Jensen2018,False,,IEEE,Not available,Optimal Utility Design in Convex Distributed Welfare Games,f69f7610c53e7b970ab060b2b2581fa1,https://ieeexplore.ieee.org/document/8431131/
9213,"In this letter, uncertainty in users' network selection is modeled by a Markov chain. In the presence of such uncertainty, the price competition game of wireless local area network (WLAN) service providers (SPs) is analyzed and the existence of Bayesian Nash equilibrium is proved. Using the price of anarchy as a metric of efficiency for social welfare maximization, it is shown that an increase in competition does not result in significant losses in efficiency. Compared to a monopoly, an unregulated duopoly of WLAN SPs is recommended as it results in a more equitable distribution of surplus amongst the SPs and the users.",abhinav kumar,Price competition,2013.0,10.1109/LCOMM.2013.020513.122647,IEEE Communications Letters,Kumar2013,False,,IEEE,Not available,WLAN Service Providers' Price Competition with Uncertainty in User Demand,0b320243d4678b542414fbd9dd2aeab1,https://ieeexplore.ieee.org/document/6459501/
9214,"In this letter, uncertainty in users' network selection is modeled by a Markov chain. In the presence of such uncertainty, the price competition game of wireless local area network (WLAN) service providers (SPs) is analyzed and the existence of Bayesian Nash equilibrium is proved. Using the price of anarchy as a metric of efficiency for social welfare maximization, it is shown that an increase in competition does not result in significant losses in efficiency. Compared to a monopoly, an unregulated duopoly of WLAN SPs is recommended as it results in a more equitable distribution of surplus amongst the SPs and the users.",abhinav kumar,price of anarchy (PoA),2013.0,10.1109/LCOMM.2013.020513.122647,IEEE Communications Letters,Kumar2013,False,,IEEE,Not available,WLAN Service Providers' Price Competition with Uncertainty in User Demand,0b320243d4678b542414fbd9dd2aeab1,https://ieeexplore.ieee.org/document/6459501/
9215,"In this letter, uncertainty in users' network selection is modeled by a Markov chain. In the presence of such uncertainty, the price competition game of wireless local area network (WLAN) service providers (SPs) is analyzed and the existence of Bayesian Nash equilibrium is proved. Using the price of anarchy as a metric of efficiency for social welfare maximization, it is shown that an increase in competition does not result in significant losses in efficiency. Compared to a monopoly, an unregulated duopoly of WLAN SPs is recommended as it results in a more equitable distribution of surplus amongst the SPs and the users.",abhinav kumar,service provider (SP),2013.0,10.1109/LCOMM.2013.020513.122647,IEEE Communications Letters,Kumar2013,False,,IEEE,Not available,WLAN Service Providers' Price Competition with Uncertainty in User Demand,0b320243d4678b542414fbd9dd2aeab1,https://ieeexplore.ieee.org/document/6459501/
9216,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
9217,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9218,"In this letter, uncertainty in users' network selection is modeled by a Markov chain. In the presence of such uncertainty, the price competition game of wireless local area network (WLAN) service providers (SPs) is analyzed and the existence of Bayesian Nash equilibrium is proved. Using the price of anarchy as a metric of efficiency for social welfare maximization, it is shown that an increase in competition does not result in significant losses in efficiency. Compared to a monopoly, an unregulated duopoly of WLAN SPs is recommended as it results in a more equitable distribution of surplus amongst the SPs and the users.",abhinav kumar,wireless local area network (WLAN),2013.0,10.1109/LCOMM.2013.020513.122647,IEEE Communications Letters,Kumar2013,False,,IEEE,Not available,WLAN Service Providers' Price Competition with Uncertainty in User Demand,0b320243d4678b542414fbd9dd2aeab1,https://ieeexplore.ieee.org/document/6459501/
9219,"In this letter, uncertainty in users' network selection is modeled by a Markov chain. In the presence of such uncertainty, the price competition game of wireless local area network (WLAN) service providers (SPs) is analyzed and the existence of Bayesian Nash equilibrium is proved. Using the price of anarchy as a metric of efficiency for social welfare maximization, it is shown that an increase in competition does not result in significant losses in efficiency. Compared to a monopoly, an unregulated duopoly of WLAN SPs is recommended as it results in a more equitable distribution of surplus amongst the SPs and the users.",ranjan mallik,Price competition,2013.0,10.1109/LCOMM.2013.020513.122647,IEEE Communications Letters,Kumar2013,False,,IEEE,Not available,WLAN Service Providers' Price Competition with Uncertainty in User Demand,0b320243d4678b542414fbd9dd2aeab1,https://ieeexplore.ieee.org/document/6459501/
9220,"In this letter, uncertainty in users' network selection is modeled by a Markov chain. In the presence of such uncertainty, the price competition game of wireless local area network (WLAN) service providers (SPs) is analyzed and the existence of Bayesian Nash equilibrium is proved. Using the price of anarchy as a metric of efficiency for social welfare maximization, it is shown that an increase in competition does not result in significant losses in efficiency. Compared to a monopoly, an unregulated duopoly of WLAN SPs is recommended as it results in a more equitable distribution of surplus amongst the SPs and the users.",ranjan mallik,price of anarchy (PoA),2013.0,10.1109/LCOMM.2013.020513.122647,IEEE Communications Letters,Kumar2013,False,,IEEE,Not available,WLAN Service Providers' Price Competition with Uncertainty in User Demand,0b320243d4678b542414fbd9dd2aeab1,https://ieeexplore.ieee.org/document/6459501/
9221,"In this letter, uncertainty in users' network selection is modeled by a Markov chain. In the presence of such uncertainty, the price competition game of wireless local area network (WLAN) service providers (SPs) is analyzed and the existence of Bayesian Nash equilibrium is proved. Using the price of anarchy as a metric of efficiency for social welfare maximization, it is shown that an increase in competition does not result in significant losses in efficiency. Compared to a monopoly, an unregulated duopoly of WLAN SPs is recommended as it results in a more equitable distribution of surplus amongst the SPs and the users.",ranjan mallik,service provider (SP),2013.0,10.1109/LCOMM.2013.020513.122647,IEEE Communications Letters,Kumar2013,False,,IEEE,Not available,WLAN Service Providers' Price Competition with Uncertainty in User Demand,0b320243d4678b542414fbd9dd2aeab1,https://ieeexplore.ieee.org/document/6459501/
9222,"In this letter, uncertainty in users' network selection is modeled by a Markov chain. In the presence of such uncertainty, the price competition game of wireless local area network (WLAN) service providers (SPs) is analyzed and the existence of Bayesian Nash equilibrium is proved. Using the price of anarchy as a metric of efficiency for social welfare maximization, it is shown that an increase in competition does not result in significant losses in efficiency. Compared to a monopoly, an unregulated duopoly of WLAN SPs is recommended as it results in a more equitable distribution of surplus amongst the SPs and the users.",ranjan mallik,wireless local area network (WLAN),2013.0,10.1109/LCOMM.2013.020513.122647,IEEE Communications Letters,Kumar2013,False,,IEEE,Not available,WLAN Service Providers' Price Competition with Uncertainty in User Demand,0b320243d4678b542414fbd9dd2aeab1,https://ieeexplore.ieee.org/document/6459501/
9223,"In this letter, uncertainty in users' network selection is modeled by a Markov chain. In the presence of such uncertainty, the price competition game of wireless local area network (WLAN) service providers (SPs) is analyzed and the existence of Bayesian Nash equilibrium is proved. Using the price of anarchy as a metric of efficiency for social welfare maximization, it is shown that an increase in competition does not result in significant losses in efficiency. Compared to a monopoly, an unregulated duopoly of WLAN SPs is recommended as it results in a more equitable distribution of surplus amongst the SPs and the users.",robert schober,Price competition,2013.0,10.1109/LCOMM.2013.020513.122647,IEEE Communications Letters,Kumar2013,False,,IEEE,Not available,WLAN Service Providers' Price Competition with Uncertainty in User Demand,0b320243d4678b542414fbd9dd2aeab1,https://ieeexplore.ieee.org/document/6459501/
9224,"In this letter, uncertainty in users' network selection is modeled by a Markov chain. In the presence of such uncertainty, the price competition game of wireless local area network (WLAN) service providers (SPs) is analyzed and the existence of Bayesian Nash equilibrium is proved. Using the price of anarchy as a metric of efficiency for social welfare maximization, it is shown that an increase in competition does not result in significant losses in efficiency. Compared to a monopoly, an unregulated duopoly of WLAN SPs is recommended as it results in a more equitable distribution of surplus amongst the SPs and the users.",robert schober,price of anarchy (PoA),2013.0,10.1109/LCOMM.2013.020513.122647,IEEE Communications Letters,Kumar2013,False,,IEEE,Not available,WLAN Service Providers' Price Competition with Uncertainty in User Demand,0b320243d4678b542414fbd9dd2aeab1,https://ieeexplore.ieee.org/document/6459501/
9225,"In this letter, uncertainty in users' network selection is modeled by a Markov chain. In the presence of such uncertainty, the price competition game of wireless local area network (WLAN) service providers (SPs) is analyzed and the existence of Bayesian Nash equilibrium is proved. Using the price of anarchy as a metric of efficiency for social welfare maximization, it is shown that an increase in competition does not result in significant losses in efficiency. Compared to a monopoly, an unregulated duopoly of WLAN SPs is recommended as it results in a more equitable distribution of surplus amongst the SPs and the users.",robert schober,service provider (SP),2013.0,10.1109/LCOMM.2013.020513.122647,IEEE Communications Letters,Kumar2013,False,,IEEE,Not available,WLAN Service Providers' Price Competition with Uncertainty in User Demand,0b320243d4678b542414fbd9dd2aeab1,https://ieeexplore.ieee.org/document/6459501/
9226,"In this letter, uncertainty in users' network selection is modeled by a Markov chain. In the presence of such uncertainty, the price competition game of wireless local area network (WLAN) service providers (SPs) is analyzed and the existence of Bayesian Nash equilibrium is proved. Using the price of anarchy as a metric of efficiency for social welfare maximization, it is shown that an increase in competition does not result in significant losses in efficiency. Compared to a monopoly, an unregulated duopoly of WLAN SPs is recommended as it results in a more equitable distribution of surplus amongst the SPs and the users.",robert schober,wireless local area network (WLAN),2013.0,10.1109/LCOMM.2013.020513.122647,IEEE Communications Letters,Kumar2013,False,,IEEE,Not available,WLAN Service Providers' Price Competition with Uncertainty in User Demand,0b320243d4678b542414fbd9dd2aeab1,https://ieeexplore.ieee.org/document/6459501/
9227,"It is important to analyze the efficiency of resource allocation with game theory in congested networks in which the users are selfish. The results are often obtained from a one-shot game, while in reality, the transmission is frequent and occurs more than once. We develop a repeated inter-session network coding game that is based on a novel Average cost share (ACS) pricing mechanism. The users choose repeated transmission rates and transmission modes between network coding and routing to maximize their own payoffs. The Price of anarchy (PoA) is adopted to analyze the efficiency of the resource allocation. Through considering different strategies for the multiusers at the next stage, we find that network coding can improve the efficiency of resource allocation in the congested networks. We discuss trigger strategies that keep players from routing at new stages.",gang wang,,2015.0,10.1049/cje.2015.04.029,Chinese Journal of Electronics,Wang2015,False,,IEEE,Not available,Repeated Inter-Session Network Coding Games with an Average Cost Share Pricing Mechanism in Congested Networks,442279055fd3df3879d3c32d929db4cf,
9228,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9229,"It is important to analyze the efficiency of resource allocation with game theory in congested networks in which the users are selfish. The results are often obtained from a one-shot game, while in reality, the transmission is frequent and occurs more than once. We develop a repeated inter-session network coding game that is based on a novel Average cost share (ACS) pricing mechanism. The users choose repeated transmission rates and transmission modes between network coding and routing to maximize their own payoffs. The Price of anarchy (PoA) is adopted to analyze the efficiency of the resource allocation. Through considering different strategies for the multiusers at the next stage, we find that network coding can improve the efficiency of resource allocation in the congested networks. We discuss trigger strategies that keep players from routing at new stages.",jie leng,,2015.0,10.1049/cje.2015.04.029,Chinese Journal of Electronics,Wang2015,False,,IEEE,Not available,Repeated Inter-Session Network Coding Games with an Average Cost Share Pricing Mechanism in Congested Networks,442279055fd3df3879d3c32d929db4cf,
9230,"It is important to analyze the efficiency of resource allocation with game theory in congested networks in which the users are selfish. The results are often obtained from a one-shot game, while in reality, the transmission is frequent and occurs more than once. We develop a repeated inter-session network coding game that is based on a novel Average cost share (ACS) pricing mechanism. The users choose repeated transmission rates and transmission modes between network coding and routing to maximize their own payoffs. The Price of anarchy (PoA) is adopted to analyze the efficiency of the resource allocation. Through considering different strategies for the multiusers at the next stage, we find that network coding can improve the efficiency of resource allocation in the congested networks. We discuss trigger strategies that keep players from routing at new stages.",cangzhou yuan,,2015.0,10.1049/cje.2015.04.029,Chinese Journal of Electronics,Wang2015,False,,IEEE,Not available,Repeated Inter-Session Network Coding Games with an Average Cost Share Pricing Mechanism in Congested Networks,442279055fd3df3879d3c32d929db4cf,
9231,"Large-scale online service providers have been increasingly relying on geographically distributed cloud infrastructures for service hosting and delivery. In this context, a key challenge faced by service providers is to determine the locations where service applications should be placed such that the hosting cost is minimized while key performance requirements (e.g., response time) are ensured. Furthermore, the dynamic nature of both demand pattern and infrastructure cost favors a dynamic solution to this problem. Currently most of the existing solutions for service placement have either ignored dynamics, or provided solutions inadequate to achieve this objective. In this paper, we present a framework for dynamic service placement problems based on control- and game-theoretic models. In particular, we present a solution that optimizes the hosting cost dynamically over time according to both demand and resource price fluctuations. We further consider the case where multiple service providers compete for resources in a dynamic manner. This paper extends our previous work [1] by analyzing the outcome of the competition in terms of both price of stability and price of anarchy. Our analysis suggests that in an uncoordinated scenario where service providers behave in a selfish manner, the resulting Nash equilibrium can be arbitrarily worse than the optimal centralized solution in terms of social welfare. Based on this observation, we present a coordination mechanism that can be employed by the infrastructure provider to maximize the social welfare of the system. Finally, we demonstrate the effectiveness of our solutions using realistic simulations.",qi zhang,Cloud computing,2013.0,10.1109/JSAC.2013.SUP2.1213008,IEEE Journal on Selected Areas in Communications,Zhang2013,False,,IEEE,Not available,Dynamic Service Placement in Geographically Distributed Clouds,d2b38fd8bbcc32729c13a7a6817fcd5f,https://ieeexplore.ieee.org/document/6708556/
9232,"Large-scale online service providers have been increasingly relying on geographically distributed cloud infrastructures for service hosting and delivery. In this context, a key challenge faced by service providers is to determine the locations where service applications should be placed such that the hosting cost is minimized while key performance requirements (e.g., response time) are ensured. Furthermore, the dynamic nature of both demand pattern and infrastructure cost favors a dynamic solution to this problem. Currently most of the existing solutions for service placement have either ignored dynamics, or provided solutions inadequate to achieve this objective. In this paper, we present a framework for dynamic service placement problems based on control- and game-theoretic models. In particular, we present a solution that optimizes the hosting cost dynamically over time according to both demand and resource price fluctuations. We further consider the case where multiple service providers compete for resources in a dynamic manner. This paper extends our previous work [1] by analyzing the outcome of the competition in terms of both price of stability and price of anarchy. Our analysis suggests that in an uncoordinated scenario where service providers behave in a selfish manner, the resulting Nash equilibrium can be arbitrarily worse than the optimal centralized solution in terms of social welfare. Based on this observation, we present a coordination mechanism that can be employed by the infrastructure provider to maximize the social welfare of the system. Finally, we demonstrate the effectiveness of our solutions using realistic simulations.",qi zhang,resource management,2013.0,10.1109/JSAC.2013.SUP2.1213008,IEEE Journal on Selected Areas in Communications,Zhang2013,False,,IEEE,Not available,Dynamic Service Placement in Geographically Distributed Clouds,d2b38fd8bbcc32729c13a7a6817fcd5f,https://ieeexplore.ieee.org/document/6708556/
9233,"Large-scale online service providers have been increasingly relying on geographically distributed cloud infrastructures for service hosting and delivery. In this context, a key challenge faced by service providers is to determine the locations where service applications should be placed such that the hosting cost is minimized while key performance requirements (e.g., response time) are ensured. Furthermore, the dynamic nature of both demand pattern and infrastructure cost favors a dynamic solution to this problem. Currently most of the existing solutions for service placement have either ignored dynamics, or provided solutions inadequate to achieve this objective. In this paper, we present a framework for dynamic service placement problems based on control- and game-theoretic models. In particular, we present a solution that optimizes the hosting cost dynamically over time according to both demand and resource price fluctuations. We further consider the case where multiple service providers compete for resources in a dynamic manner. This paper extends our previous work [1] by analyzing the outcome of the competition in terms of both price of stability and price of anarchy. Our analysis suggests that in an uncoordinated scenario where service providers behave in a selfish manner, the resulting Nash equilibrium can be arbitrarily worse than the optimal centralized solution in terms of social welfare. Based on this observation, we present a coordination mechanism that can be employed by the infrastructure provider to maximize the social welfare of the system. Finally, we demonstrate the effectiveness of our solutions using realistic simulations.",qi zhang,model predictive control,2013.0,10.1109/JSAC.2013.SUP2.1213008,IEEE Journal on Selected Areas in Communications,Zhang2013,False,,IEEE,Not available,Dynamic Service Placement in Geographically Distributed Clouds,d2b38fd8bbcc32729c13a7a6817fcd5f,https://ieeexplore.ieee.org/document/6708556/
9234,"Large-scale online service providers have been increasingly relying on geographically distributed cloud infrastructures for service hosting and delivery. In this context, a key challenge faced by service providers is to determine the locations where service applications should be placed such that the hosting cost is minimized while key performance requirements (e.g., response time) are ensured. Furthermore, the dynamic nature of both demand pattern and infrastructure cost favors a dynamic solution to this problem. Currently most of the existing solutions for service placement have either ignored dynamics, or provided solutions inadequate to achieve this objective. In this paper, we present a framework for dynamic service placement problems based on control- and game-theoretic models. In particular, we present a solution that optimizes the hosting cost dynamically over time according to both demand and resource price fluctuations. We further consider the case where multiple service providers compete for resources in a dynamic manner. This paper extends our previous work [1] by analyzing the outcome of the competition in terms of both price of stability and price of anarchy. Our analysis suggests that in an uncoordinated scenario where service providers behave in a selfish manner, the resulting Nash equilibrium can be arbitrarily worse than the optimal centralized solution in terms of social welfare. Based on this observation, we present a coordination mechanism that can be employed by the infrastructure provider to maximize the social welfare of the system. Finally, we demonstrate the effectiveness of our solutions using realistic simulations.",quanyan zhu,Cloud computing,2013.0,10.1109/JSAC.2013.SUP2.1213008,IEEE Journal on Selected Areas in Communications,Zhang2013,False,,IEEE,Not available,Dynamic Service Placement in Geographically Distributed Clouds,d2b38fd8bbcc32729c13a7a6817fcd5f,https://ieeexplore.ieee.org/document/6708556/
9235,"Large-scale online service providers have been increasingly relying on geographically distributed cloud infrastructures for service hosting and delivery. In this context, a key challenge faced by service providers is to determine the locations where service applications should be placed such that the hosting cost is minimized while key performance requirements (e.g., response time) are ensured. Furthermore, the dynamic nature of both demand pattern and infrastructure cost favors a dynamic solution to this problem. Currently most of the existing solutions for service placement have either ignored dynamics, or provided solutions inadequate to achieve this objective. In this paper, we present a framework for dynamic service placement problems based on control- and game-theoretic models. In particular, we present a solution that optimizes the hosting cost dynamically over time according to both demand and resource price fluctuations. We further consider the case where multiple service providers compete for resources in a dynamic manner. This paper extends our previous work [1] by analyzing the outcome of the competition in terms of both price of stability and price of anarchy. Our analysis suggests that in an uncoordinated scenario where service providers behave in a selfish manner, the resulting Nash equilibrium can be arbitrarily worse than the optimal centralized solution in terms of social welfare. Based on this observation, we present a coordination mechanism that can be employed by the infrastructure provider to maximize the social welfare of the system. Finally, we demonstrate the effectiveness of our solutions using realistic simulations.",quanyan zhu,resource management,2013.0,10.1109/JSAC.2013.SUP2.1213008,IEEE Journal on Selected Areas in Communications,Zhang2013,False,,IEEE,Not available,Dynamic Service Placement in Geographically Distributed Clouds,d2b38fd8bbcc32729c13a7a6817fcd5f,https://ieeexplore.ieee.org/document/6708556/
9236,"Large-scale online service providers have been increasingly relying on geographically distributed cloud infrastructures for service hosting and delivery. In this context, a key challenge faced by service providers is to determine the locations where service applications should be placed such that the hosting cost is minimized while key performance requirements (e.g., response time) are ensured. Furthermore, the dynamic nature of both demand pattern and infrastructure cost favors a dynamic solution to this problem. Currently most of the existing solutions for service placement have either ignored dynamics, or provided solutions inadequate to achieve this objective. In this paper, we present a framework for dynamic service placement problems based on control- and game-theoretic models. In particular, we present a solution that optimizes the hosting cost dynamically over time according to both demand and resource price fluctuations. We further consider the case where multiple service providers compete for resources in a dynamic manner. This paper extends our previous work [1] by analyzing the outcome of the competition in terms of both price of stability and price of anarchy. Our analysis suggests that in an uncoordinated scenario where service providers behave in a selfish manner, the resulting Nash equilibrium can be arbitrarily worse than the optimal centralized solution in terms of social welfare. Based on this observation, we present a coordination mechanism that can be employed by the infrastructure provider to maximize the social welfare of the system. Finally, we demonstrate the effectiveness of our solutions using realistic simulations.",quanyan zhu,model predictive control,2013.0,10.1109/JSAC.2013.SUP2.1213008,IEEE Journal on Selected Areas in Communications,Zhang2013,False,,IEEE,Not available,Dynamic Service Placement in Geographically Distributed Clouds,d2b38fd8bbcc32729c13a7a6817fcd5f,https://ieeexplore.ieee.org/document/6708556/
9237,"Large-scale online service providers have been increasingly relying on geographically distributed cloud infrastructures for service hosting and delivery. In this context, a key challenge faced by service providers is to determine the locations where service applications should be placed such that the hosting cost is minimized while key performance requirements (e.g., response time) are ensured. Furthermore, the dynamic nature of both demand pattern and infrastructure cost favors a dynamic solution to this problem. Currently most of the existing solutions for service placement have either ignored dynamics, or provided solutions inadequate to achieve this objective. In this paper, we present a framework for dynamic service placement problems based on control- and game-theoretic models. In particular, we present a solution that optimizes the hosting cost dynamically over time according to both demand and resource price fluctuations. We further consider the case where multiple service providers compete for resources in a dynamic manner. This paper extends our previous work [1] by analyzing the outcome of the competition in terms of both price of stability and price of anarchy. Our analysis suggests that in an uncoordinated scenario where service providers behave in a selfish manner, the resulting Nash equilibrium can be arbitrarily worse than the optimal centralized solution in terms of social welfare. Based on this observation, we present a coordination mechanism that can be employed by the infrastructure provider to maximize the social welfare of the system. Finally, we demonstrate the effectiveness of our solutions using realistic simulations.",mohamed zhani,Cloud computing,2013.0,10.1109/JSAC.2013.SUP2.1213008,IEEE Journal on Selected Areas in Communications,Zhang2013,False,,IEEE,Not available,Dynamic Service Placement in Geographically Distributed Clouds,d2b38fd8bbcc32729c13a7a6817fcd5f,https://ieeexplore.ieee.org/document/6708556/
9238,"Large-scale online service providers have been increasingly relying on geographically distributed cloud infrastructures for service hosting and delivery. In this context, a key challenge faced by service providers is to determine the locations where service applications should be placed such that the hosting cost is minimized while key performance requirements (e.g., response time) are ensured. Furthermore, the dynamic nature of both demand pattern and infrastructure cost favors a dynamic solution to this problem. Currently most of the existing solutions for service placement have either ignored dynamics, or provided solutions inadequate to achieve this objective. In this paper, we present a framework for dynamic service placement problems based on control- and game-theoretic models. In particular, we present a solution that optimizes the hosting cost dynamically over time according to both demand and resource price fluctuations. We further consider the case where multiple service providers compete for resources in a dynamic manner. This paper extends our previous work [1] by analyzing the outcome of the competition in terms of both price of stability and price of anarchy. Our analysis suggests that in an uncoordinated scenario where service providers behave in a selfish manner, the resulting Nash equilibrium can be arbitrarily worse than the optimal centralized solution in terms of social welfare. Based on this observation, we present a coordination mechanism that can be employed by the infrastructure provider to maximize the social welfare of the system. Finally, we demonstrate the effectiveness of our solutions using realistic simulations.",mohamed zhani,resource management,2013.0,10.1109/JSAC.2013.SUP2.1213008,IEEE Journal on Selected Areas in Communications,Zhang2013,False,,IEEE,Not available,Dynamic Service Placement in Geographically Distributed Clouds,d2b38fd8bbcc32729c13a7a6817fcd5f,https://ieeexplore.ieee.org/document/6708556/
9239,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
9240,"Large-scale online service providers have been increasingly relying on geographically distributed cloud infrastructures for service hosting and delivery. In this context, a key challenge faced by service providers is to determine the locations where service applications should be placed such that the hosting cost is minimized while key performance requirements (e.g., response time) are ensured. Furthermore, the dynamic nature of both demand pattern and infrastructure cost favors a dynamic solution to this problem. Currently most of the existing solutions for service placement have either ignored dynamics, or provided solutions inadequate to achieve this objective. In this paper, we present a framework for dynamic service placement problems based on control- and game-theoretic models. In particular, we present a solution that optimizes the hosting cost dynamically over time according to both demand and resource price fluctuations. We further consider the case where multiple service providers compete for resources in a dynamic manner. This paper extends our previous work [1] by analyzing the outcome of the competition in terms of both price of stability and price of anarchy. Our analysis suggests that in an uncoordinated scenario where service providers behave in a selfish manner, the resulting Nash equilibrium can be arbitrarily worse than the optimal centralized solution in terms of social welfare. Based on this observation, we present a coordination mechanism that can be employed by the infrastructure provider to maximize the social welfare of the system. Finally, we demonstrate the effectiveness of our solutions using realistic simulations.",mohamed zhani,model predictive control,2013.0,10.1109/JSAC.2013.SUP2.1213008,IEEE Journal on Selected Areas in Communications,Zhang2013,False,,IEEE,Not available,Dynamic Service Placement in Geographically Distributed Clouds,d2b38fd8bbcc32729c13a7a6817fcd5f,https://ieeexplore.ieee.org/document/6708556/
9241,"Large-scale online service providers have been increasingly relying on geographically distributed cloud infrastructures for service hosting and delivery. In this context, a key challenge faced by service providers is to determine the locations where service applications should be placed such that the hosting cost is minimized while key performance requirements (e.g., response time) are ensured. Furthermore, the dynamic nature of both demand pattern and infrastructure cost favors a dynamic solution to this problem. Currently most of the existing solutions for service placement have either ignored dynamics, or provided solutions inadequate to achieve this objective. In this paper, we present a framework for dynamic service placement problems based on control- and game-theoretic models. In particular, we present a solution that optimizes the hosting cost dynamically over time according to both demand and resource price fluctuations. We further consider the case where multiple service providers compete for resources in a dynamic manner. This paper extends our previous work [1] by analyzing the outcome of the competition in terms of both price of stability and price of anarchy. Our analysis suggests that in an uncoordinated scenario where service providers behave in a selfish manner, the resulting Nash equilibrium can be arbitrarily worse than the optimal centralized solution in terms of social welfare. Based on this observation, we present a coordination mechanism that can be employed by the infrastructure provider to maximize the social welfare of the system. Finally, we demonstrate the effectiveness of our solutions using realistic simulations.",raouf boutaba,Cloud computing,2013.0,10.1109/JSAC.2013.SUP2.1213008,IEEE Journal on Selected Areas in Communications,Zhang2013,False,,IEEE,Not available,Dynamic Service Placement in Geographically Distributed Clouds,d2b38fd8bbcc32729c13a7a6817fcd5f,https://ieeexplore.ieee.org/document/6708556/
9242,"Large-scale online service providers have been increasingly relying on geographically distributed cloud infrastructures for service hosting and delivery. In this context, a key challenge faced by service providers is to determine the locations where service applications should be placed such that the hosting cost is minimized while key performance requirements (e.g., response time) are ensured. Furthermore, the dynamic nature of both demand pattern and infrastructure cost favors a dynamic solution to this problem. Currently most of the existing solutions for service placement have either ignored dynamics, or provided solutions inadequate to achieve this objective. In this paper, we present a framework for dynamic service placement problems based on control- and game-theoretic models. In particular, we present a solution that optimizes the hosting cost dynamically over time according to both demand and resource price fluctuations. We further consider the case where multiple service providers compete for resources in a dynamic manner. This paper extends our previous work [1] by analyzing the outcome of the competition in terms of both price of stability and price of anarchy. Our analysis suggests that in an uncoordinated scenario where service providers behave in a selfish manner, the resulting Nash equilibrium can be arbitrarily worse than the optimal centralized solution in terms of social welfare. Based on this observation, we present a coordination mechanism that can be employed by the infrastructure provider to maximize the social welfare of the system. Finally, we demonstrate the effectiveness of our solutions using realistic simulations.",raouf boutaba,resource management,2013.0,10.1109/JSAC.2013.SUP2.1213008,IEEE Journal on Selected Areas in Communications,Zhang2013,False,,IEEE,Not available,Dynamic Service Placement in Geographically Distributed Clouds,d2b38fd8bbcc32729c13a7a6817fcd5f,https://ieeexplore.ieee.org/document/6708556/
9243,"Large-scale online service providers have been increasingly relying on geographically distributed cloud infrastructures for service hosting and delivery. In this context, a key challenge faced by service providers is to determine the locations where service applications should be placed such that the hosting cost is minimized while key performance requirements (e.g., response time) are ensured. Furthermore, the dynamic nature of both demand pattern and infrastructure cost favors a dynamic solution to this problem. Currently most of the existing solutions for service placement have either ignored dynamics, or provided solutions inadequate to achieve this objective. In this paper, we present a framework for dynamic service placement problems based on control- and game-theoretic models. In particular, we present a solution that optimizes the hosting cost dynamically over time according to both demand and resource price fluctuations. We further consider the case where multiple service providers compete for resources in a dynamic manner. This paper extends our previous work [1] by analyzing the outcome of the competition in terms of both price of stability and price of anarchy. Our analysis suggests that in an uncoordinated scenario where service providers behave in a selfish manner, the resulting Nash equilibrium can be arbitrarily worse than the optimal centralized solution in terms of social welfare. Based on this observation, we present a coordination mechanism that can be employed by the infrastructure provider to maximize the social welfare of the system. Finally, we demonstrate the effectiveness of our solutions using realistic simulations.",raouf boutaba,model predictive control,2013.0,10.1109/JSAC.2013.SUP2.1213008,IEEE Journal on Selected Areas in Communications,Zhang2013,False,,IEEE,Not available,Dynamic Service Placement in Geographically Distributed Clouds,d2b38fd8bbcc32729c13a7a6817fcd5f,https://ieeexplore.ieee.org/document/6708556/
9244,"Large-scale online service providers have been increasingly relying on geographically distributed cloud infrastructures for service hosting and delivery. In this context, a key challenge faced by service providers is to determine the locations where service applications should be placed such that the hosting cost is minimized while key performance requirements (e.g., response time) are ensured. Furthermore, the dynamic nature of both demand pattern and infrastructure cost favors a dynamic solution to this problem. Currently most of the existing solutions for service placement have either ignored dynamics, or provided solutions inadequate to achieve this objective. In this paper, we present a framework for dynamic service placement problems based on control- and game-theoretic models. In particular, we present a solution that optimizes the hosting cost dynamically over time according to both demand and resource price fluctuations. We further consider the case where multiple service providers compete for resources in a dynamic manner. This paper extends our previous work [1] by analyzing the outcome of the competition in terms of both price of stability and price of anarchy. Our analysis suggests that in an uncoordinated scenario where service providers behave in a selfish manner, the resulting Nash equilibrium can be arbitrarily worse than the optimal centralized solution in terms of social welfare. Based on this observation, we present a coordination mechanism that can be employed by the infrastructure provider to maximize the social welfare of the system. Finally, we demonstrate the effectiveness of our solutions using realistic simulations.",joseph hellerstein,Cloud computing,2013.0,10.1109/JSAC.2013.SUP2.1213008,IEEE Journal on Selected Areas in Communications,Zhang2013,False,,IEEE,Not available,Dynamic Service Placement in Geographically Distributed Clouds,d2b38fd8bbcc32729c13a7a6817fcd5f,https://ieeexplore.ieee.org/document/6708556/
9245,"Large-scale online service providers have been increasingly relying on geographically distributed cloud infrastructures for service hosting and delivery. In this context, a key challenge faced by service providers is to determine the locations where service applications should be placed such that the hosting cost is minimized while key performance requirements (e.g., response time) are ensured. Furthermore, the dynamic nature of both demand pattern and infrastructure cost favors a dynamic solution to this problem. Currently most of the existing solutions for service placement have either ignored dynamics, or provided solutions inadequate to achieve this objective. In this paper, we present a framework for dynamic service placement problems based on control- and game-theoretic models. In particular, we present a solution that optimizes the hosting cost dynamically over time according to both demand and resource price fluctuations. We further consider the case where multiple service providers compete for resources in a dynamic manner. This paper extends our previous work [1] by analyzing the outcome of the competition in terms of both price of stability and price of anarchy. Our analysis suggests that in an uncoordinated scenario where service providers behave in a selfish manner, the resulting Nash equilibrium can be arbitrarily worse than the optimal centralized solution in terms of social welfare. Based on this observation, we present a coordination mechanism that can be employed by the infrastructure provider to maximize the social welfare of the system. Finally, we demonstrate the effectiveness of our solutions using realistic simulations.",joseph hellerstein,resource management,2013.0,10.1109/JSAC.2013.SUP2.1213008,IEEE Journal on Selected Areas in Communications,Zhang2013,False,,IEEE,Not available,Dynamic Service Placement in Geographically Distributed Clouds,d2b38fd8bbcc32729c13a7a6817fcd5f,https://ieeexplore.ieee.org/document/6708556/
9246,"Large-scale online service providers have been increasingly relying on geographically distributed cloud infrastructures for service hosting and delivery. In this context, a key challenge faced by service providers is to determine the locations where service applications should be placed such that the hosting cost is minimized while key performance requirements (e.g., response time) are ensured. Furthermore, the dynamic nature of both demand pattern and infrastructure cost favors a dynamic solution to this problem. Currently most of the existing solutions for service placement have either ignored dynamics, or provided solutions inadequate to achieve this objective. In this paper, we present a framework for dynamic service placement problems based on control- and game-theoretic models. In particular, we present a solution that optimizes the hosting cost dynamically over time according to both demand and resource price fluctuations. We further consider the case where multiple service providers compete for resources in a dynamic manner. This paper extends our previous work [1] by analyzing the outcome of the competition in terms of both price of stability and price of anarchy. Our analysis suggests that in an uncoordinated scenario where service providers behave in a selfish manner, the resulting Nash equilibrium can be arbitrarily worse than the optimal centralized solution in terms of social welfare. Based on this observation, we present a coordination mechanism that can be employed by the infrastructure provider to maximize the social welfare of the system. Finally, we demonstrate the effectiveness of our solutions using realistic simulations.",joseph hellerstein,model predictive control,2013.0,10.1109/JSAC.2013.SUP2.1213008,IEEE Journal on Selected Areas in Communications,Zhang2013,False,,IEEE,Not available,Dynamic Service Placement in Geographically Distributed Clouds,d2b38fd8bbcc32729c13a7a6817fcd5f,https://ieeexplore.ieee.org/document/6708556/
9247,"In the context of networking, research has focused on non-cooperative games, where the selfish agents cannot reach a binding agreement on the way they would share the infrastructure. Many approaches have been proposed for mitigating the typically inefficient operating points. However, in a growing number of networking scenarios, selfish agents are able to communicate and reach an agreement. Hence, the degradation of performance should be considered at an operating point of a cooperative game. Accordingly, our goal is to lay foundations for the application of the cooperative game theory to fundamental problems in networking. We explain our choice of the Nash bargaining scheme (NBS) as the solution concept, and introduce the price of selfishness (PoS), which considers the degradation of performance at the worst NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we consider agents with identical performance objectives. We show that, while the price of anarchy (PoA) here can be large, through bargaining, all agents, and the system, strictly improve their performance. Interestingly, in a two-agent system or when all the agents have identical demands, we establish that they reach social optimality. We then consider agents with different performance objectives and demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures are unsuitable. Accordingly, we introduce the price of heterogeneity (PoH), as an extension of the PoA. We establish an upper bound on the PoH and indicate its further motivation for bargaining. Finally, we discuss network design guidelines that follow from our findings.",gideon blocq,Atomic splittable routing games,2016.0,10.1109/TNET.2016.2530308,IEEE/ACM Transactions on Networking,Blocq2016,False,,IEEE,Not available,How Good is Bargained Routing?,63d7a448b60ccf3342f9ef03180869c2,https://ieeexplore.ieee.org/document/7423806/
9248,"In the context of networking, research has focused on non-cooperative games, where the selfish agents cannot reach a binding agreement on the way they would share the infrastructure. Many approaches have been proposed for mitigating the typically inefficient operating points. However, in a growing number of networking scenarios, selfish agents are able to communicate and reach an agreement. Hence, the degradation of performance should be considered at an operating point of a cooperative game. Accordingly, our goal is to lay foundations for the application of the cooperative game theory to fundamental problems in networking. We explain our choice of the Nash bargaining scheme (NBS) as the solution concept, and introduce the price of selfishness (PoS), which considers the degradation of performance at the worst NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we consider agents with identical performance objectives. We show that, while the price of anarchy (PoA) here can be large, through bargaining, all agents, and the system, strictly improve their performance. Interestingly, in a two-agent system or when all the agents have identical demands, we establish that they reach social optimality. We then consider agents with different performance objectives and demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures are unsuitable. Accordingly, we introduce the price of heterogeneity (PoH), as an extension of the PoA. We establish an upper bound on the PoH and indicate its further motivation for bargaining. Finally, we discuss network design guidelines that follow from our findings.",gideon blocq,parallel links,2016.0,10.1109/TNET.2016.2530308,IEEE/ACM Transactions on Networking,Blocq2016,False,,IEEE,Not available,How Good is Bargained Routing?,63d7a448b60ccf3342f9ef03180869c2,https://ieeexplore.ieee.org/document/7423806/
9249,"In the context of networking, research has focused on non-cooperative games, where the selfish agents cannot reach a binding agreement on the way they would share the infrastructure. Many approaches have been proposed for mitigating the typically inefficient operating points. However, in a growing number of networking scenarios, selfish agents are able to communicate and reach an agreement. Hence, the degradation of performance should be considered at an operating point of a cooperative game. Accordingly, our goal is to lay foundations for the application of the cooperative game theory to fundamental problems in networking. We explain our choice of the Nash bargaining scheme (NBS) as the solution concept, and introduce the price of selfishness (PoS), which considers the degradation of performance at the worst NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we consider agents with identical performance objectives. We show that, while the price of anarchy (PoA) here can be large, through bargaining, all agents, and the system, strictly improve their performance. Interestingly, in a two-agent system or when all the agents have identical demands, we establish that they reach social optimality. We then consider agents with different performance objectives and demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures are unsuitable. Accordingly, we introduce the price of heterogeneity (PoH), as an extension of the PoA. We establish an upper bound on the PoH and indicate its further motivation for bargaining. Finally, we discuss network design guidelines that follow from our findings.",gideon blocq,load balancing games,2016.0,10.1109/TNET.2016.2530308,IEEE/ACM Transactions on Networking,Blocq2016,False,,IEEE,Not available,How Good is Bargained Routing?,63d7a448b60ccf3342f9ef03180869c2,https://ieeexplore.ieee.org/document/7423806/
9250,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
9251,"In the context of networking, research has focused on non-cooperative games, where the selfish agents cannot reach a binding agreement on the way they would share the infrastructure. Many approaches have been proposed for mitigating the typically inefficient operating points. However, in a growing number of networking scenarios, selfish agents are able to communicate and reach an agreement. Hence, the degradation of performance should be considered at an operating point of a cooperative game. Accordingly, our goal is to lay foundations for the application of the cooperative game theory to fundamental problems in networking. We explain our choice of the Nash bargaining scheme (NBS) as the solution concept, and introduce the price of selfishness (PoS), which considers the degradation of performance at the worst NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we consider agents with identical performance objectives. We show that, while the price of anarchy (PoA) here can be large, through bargaining, all agents, and the system, strictly improve their performance. Interestingly, in a two-agent system or when all the agents have identical demands, we establish that they reach social optimality. We then consider agents with different performance objectives and demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures are unsuitable. Accordingly, we introduce the price of heterogeneity (PoH), as an extension of the PoA. We establish an upper bound on the PoH and indicate its further motivation for bargaining. Finally, we discuss network design guidelines that follow from our findings.",gideon blocq,Nash bargaining solution,2016.0,10.1109/TNET.2016.2530308,IEEE/ACM Transactions on Networking,Blocq2016,False,,IEEE,Not available,How Good is Bargained Routing?,63d7a448b60ccf3342f9ef03180869c2,https://ieeexplore.ieee.org/document/7423806/
9252,"In the context of networking, research has focused on non-cooperative games, where the selfish agents cannot reach a binding agreement on the way they would share the infrastructure. Many approaches have been proposed for mitigating the typically inefficient operating points. However, in a growing number of networking scenarios, selfish agents are able to communicate and reach an agreement. Hence, the degradation of performance should be considered at an operating point of a cooperative game. Accordingly, our goal is to lay foundations for the application of the cooperative game theory to fundamental problems in networking. We explain our choice of the Nash bargaining scheme (NBS) as the solution concept, and introduce the price of selfishness (PoS), which considers the degradation of performance at the worst NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we consider agents with identical performance objectives. We show that, while the price of anarchy (PoA) here can be large, through bargaining, all agents, and the system, strictly improve their performance. Interestingly, in a two-agent system or when all the agents have identical demands, we establish that they reach social optimality. We then consider agents with different performance objectives and demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures are unsuitable. Accordingly, we introduce the price of heterogeneity (PoH), as an extension of the PoA. We establish an upper bound on the PoH and indicate its further motivation for bargaining. Finally, we discuss network design guidelines that follow from our findings.",gideon blocq,price of selfishness,2016.0,10.1109/TNET.2016.2530308,IEEE/ACM Transactions on Networking,Blocq2016,False,,IEEE,Not available,How Good is Bargained Routing?,63d7a448b60ccf3342f9ef03180869c2,https://ieeexplore.ieee.org/document/7423806/
9253,"In the context of networking, research has focused on non-cooperative games, where the selfish agents cannot reach a binding agreement on the way they would share the infrastructure. Many approaches have been proposed for mitigating the typically inefficient operating points. However, in a growing number of networking scenarios, selfish agents are able to communicate and reach an agreement. Hence, the degradation of performance should be considered at an operating point of a cooperative game. Accordingly, our goal is to lay foundations for the application of the cooperative game theory to fundamental problems in networking. We explain our choice of the Nash bargaining scheme (NBS) as the solution concept, and introduce the price of selfishness (PoS), which considers the degradation of performance at the worst NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we consider agents with identical performance objectives. We show that, while the price of anarchy (PoA) here can be large, through bargaining, all agents, and the system, strictly improve their performance. Interestingly, in a two-agent system or when all the agents have identical demands, we establish that they reach social optimality. We then consider agents with different performance objectives and demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures are unsuitable. Accordingly, we introduce the price of heterogeneity (PoH), as an extension of the PoA. We establish an upper bound on the PoH and indicate its further motivation for bargaining. Finally, we discuss network design guidelines that follow from our findings.",gideon blocq,price of anarchy,2016.0,10.1109/TNET.2016.2530308,IEEE/ACM Transactions on Networking,Blocq2016,False,,IEEE,Not available,How Good is Bargained Routing?,63d7a448b60ccf3342f9ef03180869c2,https://ieeexplore.ieee.org/document/7423806/
9254,"In the context of networking, research has focused on non-cooperative games, where the selfish agents cannot reach a binding agreement on the way they would share the infrastructure. Many approaches have been proposed for mitigating the typically inefficient operating points. However, in a growing number of networking scenarios, selfish agents are able to communicate and reach an agreement. Hence, the degradation of performance should be considered at an operating point of a cooperative game. Accordingly, our goal is to lay foundations for the application of the cooperative game theory to fundamental problems in networking. We explain our choice of the Nash bargaining scheme (NBS) as the solution concept, and introduce the price of selfishness (PoS), which considers the degradation of performance at the worst NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we consider agents with identical performance objectives. We show that, while the price of anarchy (PoA) here can be large, through bargaining, all agents, and the system, strictly improve their performance. Interestingly, in a two-agent system or when all the agents have identical demands, we establish that they reach social optimality. We then consider agents with different performance objectives and demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures are unsuitable. Accordingly, we introduce the price of heterogeneity (PoH), as an extension of the PoA. We establish an upper bound on the PoH and indicate its further motivation for bargaining. Finally, we discuss network design guidelines that follow from our findings.",gideon blocq,price of heterogeneity,2016.0,10.1109/TNET.2016.2530308,IEEE/ACM Transactions on Networking,Blocq2016,False,,IEEE,Not available,How Good is Bargained Routing?,63d7a448b60ccf3342f9ef03180869c2,https://ieeexplore.ieee.org/document/7423806/
9255,"In the context of networking, research has focused on non-cooperative games, where the selfish agents cannot reach a binding agreement on the way they would share the infrastructure. Many approaches have been proposed for mitigating the typically inefficient operating points. However, in a growing number of networking scenarios, selfish agents are able to communicate and reach an agreement. Hence, the degradation of performance should be considered at an operating point of a cooperative game. Accordingly, our goal is to lay foundations for the application of the cooperative game theory to fundamental problems in networking. We explain our choice of the Nash bargaining scheme (NBS) as the solution concept, and introduce the price of selfishness (PoS), which considers the degradation of performance at the worst NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we consider agents with identical performance objectives. We show that, while the price of anarchy (PoA) here can be large, through bargaining, all agents, and the system, strictly improve their performance. Interestingly, in a two-agent system or when all the agents have identical demands, we establish that they reach social optimality. We then consider agents with different performance objectives and demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures are unsuitable. Accordingly, we introduce the price of heterogeneity (PoH), as an extension of the PoA. We establish an upper bound on the PoH and indicate its further motivation for bargaining. Finally, we discuss network design guidelines that follow from our findings.",ariel orda,Atomic splittable routing games,2016.0,10.1109/TNET.2016.2530308,IEEE/ACM Transactions on Networking,Blocq2016,False,,IEEE,Not available,How Good is Bargained Routing?,63d7a448b60ccf3342f9ef03180869c2,https://ieeexplore.ieee.org/document/7423806/
9256,"In the context of networking, research has focused on non-cooperative games, where the selfish agents cannot reach a binding agreement on the way they would share the infrastructure. Many approaches have been proposed for mitigating the typically inefficient operating points. However, in a growing number of networking scenarios, selfish agents are able to communicate and reach an agreement. Hence, the degradation of performance should be considered at an operating point of a cooperative game. Accordingly, our goal is to lay foundations for the application of the cooperative game theory to fundamental problems in networking. We explain our choice of the Nash bargaining scheme (NBS) as the solution concept, and introduce the price of selfishness (PoS), which considers the degradation of performance at the worst NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we consider agents with identical performance objectives. We show that, while the price of anarchy (PoA) here can be large, through bargaining, all agents, and the system, strictly improve their performance. Interestingly, in a two-agent system or when all the agents have identical demands, we establish that they reach social optimality. We then consider agents with different performance objectives and demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures are unsuitable. Accordingly, we introduce the price of heterogeneity (PoH), as an extension of the PoA. We establish an upper bound on the PoH and indicate its further motivation for bargaining. Finally, we discuss network design guidelines that follow from our findings.",ariel orda,parallel links,2016.0,10.1109/TNET.2016.2530308,IEEE/ACM Transactions on Networking,Blocq2016,False,,IEEE,Not available,How Good is Bargained Routing?,63d7a448b60ccf3342f9ef03180869c2,https://ieeexplore.ieee.org/document/7423806/
9257,"In the context of networking, research has focused on non-cooperative games, where the selfish agents cannot reach a binding agreement on the way they would share the infrastructure. Many approaches have been proposed for mitigating the typically inefficient operating points. However, in a growing number of networking scenarios, selfish agents are able to communicate and reach an agreement. Hence, the degradation of performance should be considered at an operating point of a cooperative game. Accordingly, our goal is to lay foundations for the application of the cooperative game theory to fundamental problems in networking. We explain our choice of the Nash bargaining scheme (NBS) as the solution concept, and introduce the price of selfishness (PoS), which considers the degradation of performance at the worst NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we consider agents with identical performance objectives. We show that, while the price of anarchy (PoA) here can be large, through bargaining, all agents, and the system, strictly improve their performance. Interestingly, in a two-agent system or when all the agents have identical demands, we establish that they reach social optimality. We then consider agents with different performance objectives and demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures are unsuitable. Accordingly, we introduce the price of heterogeneity (PoH), as an extension of the PoA. We establish an upper bound on the PoH and indicate its further motivation for bargaining. Finally, we discuss network design guidelines that follow from our findings.",ariel orda,load balancing games,2016.0,10.1109/TNET.2016.2530308,IEEE/ACM Transactions on Networking,Blocq2016,False,,IEEE,Not available,How Good is Bargained Routing?,63d7a448b60ccf3342f9ef03180869c2,https://ieeexplore.ieee.org/document/7423806/
9258,"In the context of networking, research has focused on non-cooperative games, where the selfish agents cannot reach a binding agreement on the way they would share the infrastructure. Many approaches have been proposed for mitigating the typically inefficient operating points. However, in a growing number of networking scenarios, selfish agents are able to communicate and reach an agreement. Hence, the degradation of performance should be considered at an operating point of a cooperative game. Accordingly, our goal is to lay foundations for the application of the cooperative game theory to fundamental problems in networking. We explain our choice of the Nash bargaining scheme (NBS) as the solution concept, and introduce the price of selfishness (PoS), which considers the degradation of performance at the worst NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we consider agents with identical performance objectives. We show that, while the price of anarchy (PoA) here can be large, through bargaining, all agents, and the system, strictly improve their performance. Interestingly, in a two-agent system or when all the agents have identical demands, we establish that they reach social optimality. We then consider agents with different performance objectives and demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures are unsuitable. Accordingly, we introduce the price of heterogeneity (PoH), as an extension of the PoA. We establish an upper bound on the PoH and indicate its further motivation for bargaining. Finally, we discuss network design guidelines that follow from our findings.",ariel orda,Nash bargaining solution,2016.0,10.1109/TNET.2016.2530308,IEEE/ACM Transactions on Networking,Blocq2016,False,,IEEE,Not available,How Good is Bargained Routing?,63d7a448b60ccf3342f9ef03180869c2,https://ieeexplore.ieee.org/document/7423806/
9259,"In the context of networking, research has focused on non-cooperative games, where the selfish agents cannot reach a binding agreement on the way they would share the infrastructure. Many approaches have been proposed for mitigating the typically inefficient operating points. However, in a growing number of networking scenarios, selfish agents are able to communicate and reach an agreement. Hence, the degradation of performance should be considered at an operating point of a cooperative game. Accordingly, our goal is to lay foundations for the application of the cooperative game theory to fundamental problems in networking. We explain our choice of the Nash bargaining scheme (NBS) as the solution concept, and introduce the price of selfishness (PoS), which considers the degradation of performance at the worst NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we consider agents with identical performance objectives. We show that, while the price of anarchy (PoA) here can be large, through bargaining, all agents, and the system, strictly improve their performance. Interestingly, in a two-agent system or when all the agents have identical demands, we establish that they reach social optimality. We then consider agents with different performance objectives and demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures are unsuitable. Accordingly, we introduce the price of heterogeneity (PoH), as an extension of the PoA. We establish an upper bound on the PoH and indicate its further motivation for bargaining. Finally, we discuss network design guidelines that follow from our findings.",ariel orda,price of selfishness,2016.0,10.1109/TNET.2016.2530308,IEEE/ACM Transactions on Networking,Blocq2016,False,,IEEE,Not available,How Good is Bargained Routing?,63d7a448b60ccf3342f9ef03180869c2,https://ieeexplore.ieee.org/document/7423806/
9260,"In the context of networking, research has focused on non-cooperative games, where the selfish agents cannot reach a binding agreement on the way they would share the infrastructure. Many approaches have been proposed for mitigating the typically inefficient operating points. However, in a growing number of networking scenarios, selfish agents are able to communicate and reach an agreement. Hence, the degradation of performance should be considered at an operating point of a cooperative game. Accordingly, our goal is to lay foundations for the application of the cooperative game theory to fundamental problems in networking. We explain our choice of the Nash bargaining scheme (NBS) as the solution concept, and introduce the price of selfishness (PoS), which considers the degradation of performance at the worst NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we consider agents with identical performance objectives. We show that, while the price of anarchy (PoA) here can be large, through bargaining, all agents, and the system, strictly improve their performance. Interestingly, in a two-agent system or when all the agents have identical demands, we establish that they reach social optimality. We then consider agents with different performance objectives and demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures are unsuitable. Accordingly, we introduce the price of heterogeneity (PoH), as an extension of the PoA. We establish an upper bound on the PoH and indicate its further motivation for bargaining. Finally, we discuss network design guidelines that follow from our findings.",ariel orda,price of anarchy,2016.0,10.1109/TNET.2016.2530308,IEEE/ACM Transactions on Networking,Blocq2016,False,,IEEE,Not available,How Good is Bargained Routing?,63d7a448b60ccf3342f9ef03180869c2,https://ieeexplore.ieee.org/document/7423806/
9261,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
9262,"In the context of networking, research has focused on non-cooperative games, where the selfish agents cannot reach a binding agreement on the way they would share the infrastructure. Many approaches have been proposed for mitigating the typically inefficient operating points. However, in a growing number of networking scenarios, selfish agents are able to communicate and reach an agreement. Hence, the degradation of performance should be considered at an operating point of a cooperative game. Accordingly, our goal is to lay foundations for the application of the cooperative game theory to fundamental problems in networking. We explain our choice of the Nash bargaining scheme (NBS) as the solution concept, and introduce the price of selfishness (PoS), which considers the degradation of performance at the worst NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we consider agents with identical performance objectives. We show that, while the price of anarchy (PoA) here can be large, through bargaining, all agents, and the system, strictly improve their performance. Interestingly, in a two-agent system or when all the agents have identical demands, we establish that they reach social optimality. We then consider agents with different performance objectives and demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures are unsuitable. Accordingly, we introduce the price of heterogeneity (PoH), as an extension of the PoA. We establish an upper bound on the PoH and indicate its further motivation for bargaining. Finally, we discuss network design guidelines that follow from our findings.",ariel orda,price of heterogeneity,2016.0,10.1109/TNET.2016.2530308,IEEE/ACM Transactions on Networking,Blocq2016,False,,IEEE,Not available,How Good is Bargained Routing?,63d7a448b60ccf3342f9ef03180869c2,https://ieeexplore.ieee.org/document/7423806/
9263,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. nahir,Network topology,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
9264,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. nahir,Nash equilibrium,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
9265,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. nahir,Routing,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
9266,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. nahir,Interference,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
9267,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. nahir,Performance analysis,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
9268,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. nahir,Lighting control,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
9269,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. nahir,Relays,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
9270,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. nahir,Game theory,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
9271,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. nahir,Stability,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
9272,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
9273,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. nahir,Computer network reliability,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
9274,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. orda,Network topology,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
9275,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. orda,Nash equilibrium,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
9276,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. orda,Routing,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
9277,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. orda,Interference,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
9278,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. orda,Performance analysis,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
9279,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. orda,Lighting control,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
9280,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. orda,Relays,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
9281,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. orda,Game theory,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
9282,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. orda,Stability,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
9283,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
9284,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. orda,Computer network reliability,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
9285,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. freund,Network topology,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
9286,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. freund,Nash equilibrium,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
9287,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. freund,Routing,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
9288,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. freund,Interference,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
9289,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. freund,Performance analysis,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
9290,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. freund,Lighting control,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
9291,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. freund,Relays,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
9292,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. freund,Game theory,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
9293,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. freund,Stability,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
9294,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
9295,"We study the performance of non-cooperative networks in light of three major topology design and control considerations, namely the price of establishing a link, path delay, and path proneness to congestion or interference, the latter being modeled through the ""relaying extent"" of the nodes. We analyze these considerations and the tradeoffs between them from a game theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by non-cooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (""social"") agent with the ability to impose the initial configuration on the system.",a. freund,Computer network reliability,2009.0,10.1109/INFCOM.2009.5062080,IEEE INFOCOM 2009,Nahir2009,False,,IEEE,Not available,Topology Design and Control: A Game-Theoretic Perspective,71dcc658f58bc93ffbdfc720e0df03c0,https://ieeexplore.ieee.org/document/5062080/
9296,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",paulin jacquot,Games,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
9297,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",paulin jacquot,Energy consumption,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
9298,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",paulin jacquot,Standards,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
9299,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",paulin jacquot,Smart grids,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
9300,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",paulin jacquot,Load management,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
9301,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",paulin jacquot,Noise measurement,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
9302,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",olivier beaude,Games,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
9303,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",olivier beaude,Energy consumption,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
9304,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",olivier beaude,Standards,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
9305,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
9306,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",olivier beaude,Smart grids,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
9307,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",olivier beaude,Load management,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
9308,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",olivier beaude,Noise measurement,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
9309,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",stephane gaubert,Games,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
9310,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",stephane gaubert,Energy consumption,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
9311,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",stephane gaubert,Standards,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
9312,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",stephane gaubert,Smart grids,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
9313,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",stephane gaubert,Load management,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
9314,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",stephane gaubert,Noise measurement,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
9315,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",nadia oudjane,Games,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
9316,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
9317,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",nadia oudjane,Energy consumption,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
9318,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",nadia oudjane,Standards,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
9319,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",nadia oudjane,Smart grids,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
9320,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",nadia oudjane,Load management,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
9321,"In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can value this discomfort at a varying level that we take as a parameter. This work analyses Demand Response as a game theoretic environment. We study the equilibria of the game between consumers with preferences within two different dynamic pricing mechanisms, respectively the daily proportional mechanism introduced by Mohsenian-Rad et al, and an hourly proportional mechanism. We give new results about equilibria as functions of the preference level in the case of quadratic system costs and prove that, whatever the preference level, system costs are smaller with the hourly mechanism. We simulate the Demand Response environment using real consumption data from PecanStreet database. While the Price of Anarchy remains always close to one up to 10<sup>-3</sup>with the hourly mechanism, it can be more than 10% bigger with the daily mechanism.",nadia oudjane,Noise measurement,2017.0,10.1109/SmartGridComm.2017.8340690,2017 IEEE International Conference on Smart Grid Communications (SmartGridComm),Jacquot2017,False,,IEEE,Not available,Demand response in the smart grid: The impact of consumers temporal preferences,e57bbd6fe5b28f96ccd58c8caf21a961,https://ieeexplore.ieee.org/document/8340690/
9322,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",youwen yi,Macrocell networks,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
9323,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",youwen yi,Throughput,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
9324,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",youwen yi,Games,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
9325,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",youwen yi,Noise measurement,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
9326,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",youwen yi,Radio frequency,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
9327,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
9328,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
9329,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",youwen yi,Wireless communication,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
9330,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",youwen yi,Ultrafast electronics,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
9331,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",jin zhang,Macrocell networks,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
9332,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",jin zhang,Throughput,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
9333,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",jin zhang,Games,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
9334,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",jin zhang,Noise measurement,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
9335,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",jin zhang,Radio frequency,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
9336,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",jin zhang,Wireless communication,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
9337,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",jin zhang,Ultrafast electronics,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
9338,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",qian zhang,Macrocell networks,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
9339,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
9340,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",qian zhang,Throughput,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
9341,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",qian zhang,Games,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
9342,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",qian zhang,Noise measurement,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
9343,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",qian zhang,Radio frequency,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
9344,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",qian zhang,Wireless communication,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
9345,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",qian zhang,Ultrafast electronics,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
9346,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",tao jiang,Macrocell networks,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
9347,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",tao jiang,Throughput,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
9348,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",tao jiang,Games,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
9349,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",tao jiang,Noise measurement,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
9350,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
9351,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",tao jiang,Radio frequency,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
9352,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",tao jiang,Wireless communication,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
9353,"The concept of femtocell that operates in licensed spectrum to provide home coverage has attracted interest in the wireless industry due to high spatial reuse, and extensive deployments of femtocells is expected in the future. In this paper, we consider the scenario that a femtocell service provider (FSP) expects to rent spectrum from the coexisting macrocell service provider (MSP) to serve its end users. In addition to the spectrum leasing payment, the FSP may allow hybrid access of macrocell users to improve the utilities of itself and MSP, which are defined as the sum of data traffic and payment/revenue. We propose the spectrum leasing framework taking hybrid access into consideration. The whole procedure is modeled as a three-stage Stackelberg game, where MSP and FSP determine the spectrum leasing ratio, spectrum leasing price and open access ratio sequentially to maximize their utilities, and the existence of the Nash Equilibrium of the sequential game is analyzed. We characterize the equilibrium, in terms of access price, spectrum acquisition of FSP, the open access ratio, and price of anarchy via simulation. Numerical results show that both MSP and FSP can benefit from spectrum leasing, and hybrid access of femtocell can further improve their utilities, which provide sufficient incentive for their cooperation.",tao jiang,Ultrafast electronics,2012.0,10.1109/INFCOM.2012.6195482,2012 Proceedings IEEE INFOCOM,Yi2012,False,,IEEE,Not available,Spectrum leasing to femto service provider with hybrid access,d861ef0d42077a0b56f1f0d7be8ae813,https://ieeexplore.ieee.org/document/6195482/
9354,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",sangwoo moon,Games,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
9355,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",sangwoo moon,Sociology,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
9356,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",sangwoo moon,Statistics,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
9357,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",sangwoo moon,Heuristic algorithms,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
9358,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",sangwoo moon,Optimization,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
9359,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",sangwoo moon,Mobile communication,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
9360,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",sangwoo moon,Delays,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
9361,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
9362,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",yung yi,Games,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
9363,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",yung yi,Sociology,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
9364,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",yung yi,Statistics,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
9365,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",yung yi,Heuristic algorithms,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
9366,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",yung yi,Optimization,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
9367,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",yung yi,Mobile communication,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
9368,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",yung yi,Delays,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
9369,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",hongseok kim,Games,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
9370,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",hongseok kim,Sociology,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
9371,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",hongseok kim,Statistics,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
9372,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
9373,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",hongseok kim,Heuristic algorithms,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
9374,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",hongseok kim,Optimization,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
9375,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",hongseok kim,Mobile communication,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
9376,"In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).",hongseok kim,Delays,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Moon2013,False,,IEEE,Not available,Energy-efficient user association in cellular networks: A population game approach,1ef57101f134b35d2919b023a68b58e0,https://ieeexplore.ieee.org/document/6576459/
9377,"Game theoretic models have been widely employed in many networking contexts. Research to date has mainly focused on non-cooperative networking games, where the selfish agents cannot reach a binding agreement on the way they would share the network infrastructure and the operating points are the Nash equilibria. These are typically inefficient, as manifested by large values of the Price of Anarchy (PoA). Many approaches have been proposed for mitigating this problem, however under the standing assumption of a non-cooperative game. In a growing number of networking scenarios it is possible for the selfish agents to communicate and reach an agreement, i.e., play a cooperative game. Therefore, the degradation of performance should be considered at an operating point that is a cooperative game solution. Accordingly, our goal is to lay foundations for the application of cooperative game theory to fundamental problems in networking. We explain our choice of the Nash Bargaining Scheme (NBS) as the solution concept, and we introduce the Price of Selfishness (PoS), which considers the degradation of performance at an NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we study the classical scenario of agents that consider the same performance objectives. While the PoA here can be very large, we establish that, under plausible assumptions, the PoS attains its minimum value, i.e., through bargaining, the selfish agents reach social optimality. We then extend our study to consider the “heterogeneous” case, where agents may consider vastly different performance objectives. We demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures may now be unsuitable. Accordingly, we introduce the Price of Heterogeneity (PoH), as a proper extension of the PoA. We establish an upper-bound on the PoH for a general class of heterogeneous performance objectives, and indicate that it provides incentives for bargaining also in this general case. We discuss network design guidelines that follow from our findings.",gideon blocq,Games,2012.0,10.1109/INFCOM.2012.6195636,2012 Proceedings IEEE INFOCOM,Blocq2012,False,,IEEE,Not available,How good is bargained routing?,b9b57e7e44e105b7977be0bad1fbd0c0,https://ieeexplore.ieee.org/document/6195636/
9378,"Game theoretic models have been widely employed in many networking contexts. Research to date has mainly focused on non-cooperative networking games, where the selfish agents cannot reach a binding agreement on the way they would share the network infrastructure and the operating points are the Nash equilibria. These are typically inefficient, as manifested by large values of the Price of Anarchy (PoA). Many approaches have been proposed for mitigating this problem, however under the standing assumption of a non-cooperative game. In a growing number of networking scenarios it is possible for the selfish agents to communicate and reach an agreement, i.e., play a cooperative game. Therefore, the degradation of performance should be considered at an operating point that is a cooperative game solution. Accordingly, our goal is to lay foundations for the application of cooperative game theory to fundamental problems in networking. We explain our choice of the Nash Bargaining Scheme (NBS) as the solution concept, and we introduce the Price of Selfishness (PoS), which considers the degradation of performance at an NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we study the classical scenario of agents that consider the same performance objectives. While the PoA here can be very large, we establish that, under plausible assumptions, the PoS attains its minimum value, i.e., through bargaining, the selfish agents reach social optimality. We then extend our study to consider the “heterogeneous” case, where agents may consider vastly different performance objectives. We demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures may now be unsuitable. Accordingly, we introduce the Price of Heterogeneity (PoH), as a proper extension of the PoA. We establish an upper-bound on the PoH for a general class of heterogeneous performance objectives, and indicate that it provides incentives for bargaining also in this general case. We discuss network design guidelines that follow from our findings.",gideon blocq,Routing,2012.0,10.1109/INFCOM.2012.6195636,2012 Proceedings IEEE INFOCOM,Blocq2012,False,,IEEE,Not available,How good is bargained routing?,b9b57e7e44e105b7977be0bad1fbd0c0,https://ieeexplore.ieee.org/document/6195636/
9379,"Game theoretic models have been widely employed in many networking contexts. Research to date has mainly focused on non-cooperative networking games, where the selfish agents cannot reach a binding agreement on the way they would share the network infrastructure and the operating points are the Nash equilibria. These are typically inefficient, as manifested by large values of the Price of Anarchy (PoA). Many approaches have been proposed for mitigating this problem, however under the standing assumption of a non-cooperative game. In a growing number of networking scenarios it is possible for the selfish agents to communicate and reach an agreement, i.e., play a cooperative game. Therefore, the degradation of performance should be considered at an operating point that is a cooperative game solution. Accordingly, our goal is to lay foundations for the application of cooperative game theory to fundamental problems in networking. We explain our choice of the Nash Bargaining Scheme (NBS) as the solution concept, and we introduce the Price of Selfishness (PoS), which considers the degradation of performance at an NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we study the classical scenario of agents that consider the same performance objectives. While the PoA here can be very large, we establish that, under plausible assumptions, the PoS attains its minimum value, i.e., through bargaining, the selfish agents reach social optimality. We then extend our study to consider the “heterogeneous” case, where agents may consider vastly different performance objectives. We demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures may now be unsuitable. Accordingly, we introduce the Price of Heterogeneity (PoH), as a proper extension of the PoA. We establish an upper-bound on the PoH for a general class of heterogeneous performance objectives, and indicate that it provides incentives for bargaining also in this general case. We discuss network design guidelines that follow from our findings.",gideon blocq,Vectors,2012.0,10.1109/INFCOM.2012.6195636,2012 Proceedings IEEE INFOCOM,Blocq2012,False,,IEEE,Not available,How good is bargained routing?,b9b57e7e44e105b7977be0bad1fbd0c0,https://ieeexplore.ieee.org/document/6195636/
9380,"Game theoretic models have been widely employed in many networking contexts. Research to date has mainly focused on non-cooperative networking games, where the selfish agents cannot reach a binding agreement on the way they would share the network infrastructure and the operating points are the Nash equilibria. These are typically inefficient, as manifested by large values of the Price of Anarchy (PoA). Many approaches have been proposed for mitigating this problem, however under the standing assumption of a non-cooperative game. In a growing number of networking scenarios it is possible for the selfish agents to communicate and reach an agreement, i.e., play a cooperative game. Therefore, the degradation of performance should be considered at an operating point that is a cooperative game solution. Accordingly, our goal is to lay foundations for the application of cooperative game theory to fundamental problems in networking. We explain our choice of the Nash Bargaining Scheme (NBS) as the solution concept, and we introduce the Price of Selfishness (PoS), which considers the degradation of performance at an NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we study the classical scenario of agents that consider the same performance objectives. While the PoA here can be very large, we establish that, under plausible assumptions, the PoS attains its minimum value, i.e., through bargaining, the selfish agents reach social optimality. We then extend our study to consider the “heterogeneous” case, where agents may consider vastly different performance objectives. We demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures may now be unsuitable. Accordingly, we introduce the Price of Heterogeneity (PoH), as a proper extension of the PoA. We establish an upper-bound on the PoH for a general class of heterogeneous performance objectives, and indicate that it provides incentives for bargaining also in this general case. We discuss network design guidelines that follow from our findings.",gideon blocq,NIST,2012.0,10.1109/INFCOM.2012.6195636,2012 Proceedings IEEE INFOCOM,Blocq2012,False,,IEEE,Not available,How good is bargained routing?,b9b57e7e44e105b7977be0bad1fbd0c0,https://ieeexplore.ieee.org/document/6195636/
9381,"Game theoretic models have been widely employed in many networking contexts. Research to date has mainly focused on non-cooperative networking games, where the selfish agents cannot reach a binding agreement on the way they would share the network infrastructure and the operating points are the Nash equilibria. These are typically inefficient, as manifested by large values of the Price of Anarchy (PoA). Many approaches have been proposed for mitigating this problem, however under the standing assumption of a non-cooperative game. In a growing number of networking scenarios it is possible for the selfish agents to communicate and reach an agreement, i.e., play a cooperative game. Therefore, the degradation of performance should be considered at an operating point that is a cooperative game solution. Accordingly, our goal is to lay foundations for the application of cooperative game theory to fundamental problems in networking. We explain our choice of the Nash Bargaining Scheme (NBS) as the solution concept, and we introduce the Price of Selfishness (PoS), which considers the degradation of performance at an NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we study the classical scenario of agents that consider the same performance objectives. While the PoA here can be very large, we establish that, under plausible assumptions, the PoS attains its minimum value, i.e., through bargaining, the selfish agents reach social optimality. We then extend our study to consider the “heterogeneous” case, where agents may consider vastly different performance objectives. We demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures may now be unsuitable. Accordingly, we introduce the Price of Heterogeneity (PoH), as a proper extension of the PoA. We establish an upper-bound on the PoH for a general class of heterogeneous performance objectives, and indicate that it provides incentives for bargaining also in this general case. We discuss network design guidelines that follow from our findings.",gideon blocq,Cost function,2012.0,10.1109/INFCOM.2012.6195636,2012 Proceedings IEEE INFOCOM,Blocq2012,False,,IEEE,Not available,How good is bargained routing?,b9b57e7e44e105b7977be0bad1fbd0c0,https://ieeexplore.ieee.org/document/6195636/
9382,"Game theoretic models have been widely employed in many networking contexts. Research to date has mainly focused on non-cooperative networking games, where the selfish agents cannot reach a binding agreement on the way they would share the network infrastructure and the operating points are the Nash equilibria. These are typically inefficient, as manifested by large values of the Price of Anarchy (PoA). Many approaches have been proposed for mitigating this problem, however under the standing assumption of a non-cooperative game. In a growing number of networking scenarios it is possible for the selfish agents to communicate and reach an agreement, i.e., play a cooperative game. Therefore, the degradation of performance should be considered at an operating point that is a cooperative game solution. Accordingly, our goal is to lay foundations for the application of cooperative game theory to fundamental problems in networking. We explain our choice of the Nash Bargaining Scheme (NBS) as the solution concept, and we introduce the Price of Selfishness (PoS), which considers the degradation of performance at an NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we study the classical scenario of agents that consider the same performance objectives. While the PoA here can be very large, we establish that, under plausible assumptions, the PoS attains its minimum value, i.e., through bargaining, the selfish agents reach social optimality. We then extend our study to consider the “heterogeneous” case, where agents may consider vastly different performance objectives. We demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures may now be unsuitable. Accordingly, we introduce the Price of Heterogeneity (PoH), as a proper extension of the PoA. We establish an upper-bound on the PoH for a general class of heterogeneous performance objectives, and indicate that it provides incentives for bargaining also in this general case. We discuss network design guidelines that follow from our findings.",gideon blocq,Delay,2012.0,10.1109/INFCOM.2012.6195636,2012 Proceedings IEEE INFOCOM,Blocq2012,False,,IEEE,Not available,How good is bargained routing?,b9b57e7e44e105b7977be0bad1fbd0c0,https://ieeexplore.ieee.org/document/6195636/
9383,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
9384,"Game theoretic models have been widely employed in many networking contexts. Research to date has mainly focused on non-cooperative networking games, where the selfish agents cannot reach a binding agreement on the way they would share the network infrastructure and the operating points are the Nash equilibria. These are typically inefficient, as manifested by large values of the Price of Anarchy (PoA). Many approaches have been proposed for mitigating this problem, however under the standing assumption of a non-cooperative game. In a growing number of networking scenarios it is possible for the selfish agents to communicate and reach an agreement, i.e., play a cooperative game. Therefore, the degradation of performance should be considered at an operating point that is a cooperative game solution. Accordingly, our goal is to lay foundations for the application of cooperative game theory to fundamental problems in networking. We explain our choice of the Nash Bargaining Scheme (NBS) as the solution concept, and we introduce the Price of Selfishness (PoS), which considers the degradation of performance at an NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we study the classical scenario of agents that consider the same performance objectives. While the PoA here can be very large, we establish that, under plausible assumptions, the PoS attains its minimum value, i.e., through bargaining, the selfish agents reach social optimality. We then extend our study to consider the “heterogeneous” case, where agents may consider vastly different performance objectives. We demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures may now be unsuitable. Accordingly, we introduce the Price of Heterogeneity (PoH), as a proper extension of the PoA. We establish an upper-bound on the PoH for a general class of heterogeneous performance objectives, and indicate that it provides incentives for bargaining also in this general case. We discuss network design guidelines that follow from our findings.",gideon blocq,Nash equilibrium,2012.0,10.1109/INFCOM.2012.6195636,2012 Proceedings IEEE INFOCOM,Blocq2012,False,,IEEE,Not available,How good is bargained routing?,b9b57e7e44e105b7977be0bad1fbd0c0,https://ieeexplore.ieee.org/document/6195636/
9385,"Game theoretic models have been widely employed in many networking contexts. Research to date has mainly focused on non-cooperative networking games, where the selfish agents cannot reach a binding agreement on the way they would share the network infrastructure and the operating points are the Nash equilibria. These are typically inefficient, as manifested by large values of the Price of Anarchy (PoA). Many approaches have been proposed for mitigating this problem, however under the standing assumption of a non-cooperative game. In a growing number of networking scenarios it is possible for the selfish agents to communicate and reach an agreement, i.e., play a cooperative game. Therefore, the degradation of performance should be considered at an operating point that is a cooperative game solution. Accordingly, our goal is to lay foundations for the application of cooperative game theory to fundamental problems in networking. We explain our choice of the Nash Bargaining Scheme (NBS) as the solution concept, and we introduce the Price of Selfishness (PoS), which considers the degradation of performance at an NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we study the classical scenario of agents that consider the same performance objectives. While the PoA here can be very large, we establish that, under plausible assumptions, the PoS attains its minimum value, i.e., through bargaining, the selfish agents reach social optimality. We then extend our study to consider the “heterogeneous” case, where agents may consider vastly different performance objectives. We demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures may now be unsuitable. Accordingly, we introduce the Price of Heterogeneity (PoH), as a proper extension of the PoA. We establish an upper-bound on the PoH for a general class of heterogeneous performance objectives, and indicate that it provides incentives for bargaining also in this general case. We discuss network design guidelines that follow from our findings.",ariel orda,Games,2012.0,10.1109/INFCOM.2012.6195636,2012 Proceedings IEEE INFOCOM,Blocq2012,False,,IEEE,Not available,How good is bargained routing?,b9b57e7e44e105b7977be0bad1fbd0c0,https://ieeexplore.ieee.org/document/6195636/
9386,"Game theoretic models have been widely employed in many networking contexts. Research to date has mainly focused on non-cooperative networking games, where the selfish agents cannot reach a binding agreement on the way they would share the network infrastructure and the operating points are the Nash equilibria. These are typically inefficient, as manifested by large values of the Price of Anarchy (PoA). Many approaches have been proposed for mitigating this problem, however under the standing assumption of a non-cooperative game. In a growing number of networking scenarios it is possible for the selfish agents to communicate and reach an agreement, i.e., play a cooperative game. Therefore, the degradation of performance should be considered at an operating point that is a cooperative game solution. Accordingly, our goal is to lay foundations for the application of cooperative game theory to fundamental problems in networking. We explain our choice of the Nash Bargaining Scheme (NBS) as the solution concept, and we introduce the Price of Selfishness (PoS), which considers the degradation of performance at an NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we study the classical scenario of agents that consider the same performance objectives. While the PoA here can be very large, we establish that, under plausible assumptions, the PoS attains its minimum value, i.e., through bargaining, the selfish agents reach social optimality. We then extend our study to consider the “heterogeneous” case, where agents may consider vastly different performance objectives. We demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures may now be unsuitable. Accordingly, we introduce the Price of Heterogeneity (PoH), as a proper extension of the PoA. We establish an upper-bound on the PoH for a general class of heterogeneous performance objectives, and indicate that it provides incentives for bargaining also in this general case. We discuss network design guidelines that follow from our findings.",ariel orda,Routing,2012.0,10.1109/INFCOM.2012.6195636,2012 Proceedings IEEE INFOCOM,Blocq2012,False,,IEEE,Not available,How good is bargained routing?,b9b57e7e44e105b7977be0bad1fbd0c0,https://ieeexplore.ieee.org/document/6195636/
9387,"Game theoretic models have been widely employed in many networking contexts. Research to date has mainly focused on non-cooperative networking games, where the selfish agents cannot reach a binding agreement on the way they would share the network infrastructure and the operating points are the Nash equilibria. These are typically inefficient, as manifested by large values of the Price of Anarchy (PoA). Many approaches have been proposed for mitigating this problem, however under the standing assumption of a non-cooperative game. In a growing number of networking scenarios it is possible for the selfish agents to communicate and reach an agreement, i.e., play a cooperative game. Therefore, the degradation of performance should be considered at an operating point that is a cooperative game solution. Accordingly, our goal is to lay foundations for the application of cooperative game theory to fundamental problems in networking. We explain our choice of the Nash Bargaining Scheme (NBS) as the solution concept, and we introduce the Price of Selfishness (PoS), which considers the degradation of performance at an NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we study the classical scenario of agents that consider the same performance objectives. While the PoA here can be very large, we establish that, under plausible assumptions, the PoS attains its minimum value, i.e., through bargaining, the selfish agents reach social optimality. We then extend our study to consider the “heterogeneous” case, where agents may consider vastly different performance objectives. We demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures may now be unsuitable. Accordingly, we introduce the Price of Heterogeneity (PoH), as a proper extension of the PoA. We establish an upper-bound on the PoH for a general class of heterogeneous performance objectives, and indicate that it provides incentives for bargaining also in this general case. We discuss network design guidelines that follow from our findings.",ariel orda,Vectors,2012.0,10.1109/INFCOM.2012.6195636,2012 Proceedings IEEE INFOCOM,Blocq2012,False,,IEEE,Not available,How good is bargained routing?,b9b57e7e44e105b7977be0bad1fbd0c0,https://ieeexplore.ieee.org/document/6195636/
9388,"Game theoretic models have been widely employed in many networking contexts. Research to date has mainly focused on non-cooperative networking games, where the selfish agents cannot reach a binding agreement on the way they would share the network infrastructure and the operating points are the Nash equilibria. These are typically inefficient, as manifested by large values of the Price of Anarchy (PoA). Many approaches have been proposed for mitigating this problem, however under the standing assumption of a non-cooperative game. In a growing number of networking scenarios it is possible for the selfish agents to communicate and reach an agreement, i.e., play a cooperative game. Therefore, the degradation of performance should be considered at an operating point that is a cooperative game solution. Accordingly, our goal is to lay foundations for the application of cooperative game theory to fundamental problems in networking. We explain our choice of the Nash Bargaining Scheme (NBS) as the solution concept, and we introduce the Price of Selfishness (PoS), which considers the degradation of performance at an NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we study the classical scenario of agents that consider the same performance objectives. While the PoA here can be very large, we establish that, under plausible assumptions, the PoS attains its minimum value, i.e., through bargaining, the selfish agents reach social optimality. We then extend our study to consider the “heterogeneous” case, where agents may consider vastly different performance objectives. We demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures may now be unsuitable. Accordingly, we introduce the Price of Heterogeneity (PoH), as a proper extension of the PoA. We establish an upper-bound on the PoH for a general class of heterogeneous performance objectives, and indicate that it provides incentives for bargaining also in this general case. We discuss network design guidelines that follow from our findings.",ariel orda,NIST,2012.0,10.1109/INFCOM.2012.6195636,2012 Proceedings IEEE INFOCOM,Blocq2012,False,,IEEE,Not available,How good is bargained routing?,b9b57e7e44e105b7977be0bad1fbd0c0,https://ieeexplore.ieee.org/document/6195636/
9389,"Game theoretic models have been widely employed in many networking contexts. Research to date has mainly focused on non-cooperative networking games, where the selfish agents cannot reach a binding agreement on the way they would share the network infrastructure and the operating points are the Nash equilibria. These are typically inefficient, as manifested by large values of the Price of Anarchy (PoA). Many approaches have been proposed for mitigating this problem, however under the standing assumption of a non-cooperative game. In a growing number of networking scenarios it is possible for the selfish agents to communicate and reach an agreement, i.e., play a cooperative game. Therefore, the degradation of performance should be considered at an operating point that is a cooperative game solution. Accordingly, our goal is to lay foundations for the application of cooperative game theory to fundamental problems in networking. We explain our choice of the Nash Bargaining Scheme (NBS) as the solution concept, and we introduce the Price of Selfishness (PoS), which considers the degradation of performance at an NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we study the classical scenario of agents that consider the same performance objectives. While the PoA here can be very large, we establish that, under plausible assumptions, the PoS attains its minimum value, i.e., through bargaining, the selfish agents reach social optimality. We then extend our study to consider the “heterogeneous” case, where agents may consider vastly different performance objectives. We demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures may now be unsuitable. Accordingly, we introduce the Price of Heterogeneity (PoH), as a proper extension of the PoA. We establish an upper-bound on the PoH for a general class of heterogeneous performance objectives, and indicate that it provides incentives for bargaining also in this general case. We discuss network design guidelines that follow from our findings.",ariel orda,Cost function,2012.0,10.1109/INFCOM.2012.6195636,2012 Proceedings IEEE INFOCOM,Blocq2012,False,,IEEE,Not available,How good is bargained routing?,b9b57e7e44e105b7977be0bad1fbd0c0,https://ieeexplore.ieee.org/document/6195636/
9390,"Game theoretic models have been widely employed in many networking contexts. Research to date has mainly focused on non-cooperative networking games, where the selfish agents cannot reach a binding agreement on the way they would share the network infrastructure and the operating points are the Nash equilibria. These are typically inefficient, as manifested by large values of the Price of Anarchy (PoA). Many approaches have been proposed for mitigating this problem, however under the standing assumption of a non-cooperative game. In a growing number of networking scenarios it is possible for the selfish agents to communicate and reach an agreement, i.e., play a cooperative game. Therefore, the degradation of performance should be considered at an operating point that is a cooperative game solution. Accordingly, our goal is to lay foundations for the application of cooperative game theory to fundamental problems in networking. We explain our choice of the Nash Bargaining Scheme (NBS) as the solution concept, and we introduce the Price of Selfishness (PoS), which considers the degradation of performance at an NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we study the classical scenario of agents that consider the same performance objectives. While the PoA here can be very large, we establish that, under plausible assumptions, the PoS attains its minimum value, i.e., through bargaining, the selfish agents reach social optimality. We then extend our study to consider the “heterogeneous” case, where agents may consider vastly different performance objectives. We demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures may now be unsuitable. Accordingly, we introduce the Price of Heterogeneity (PoH), as a proper extension of the PoA. We establish an upper-bound on the PoH for a general class of heterogeneous performance objectives, and indicate that it provides incentives for bargaining also in this general case. We discuss network design guidelines that follow from our findings.",ariel orda,Delay,2012.0,10.1109/INFCOM.2012.6195636,2012 Proceedings IEEE INFOCOM,Blocq2012,False,,IEEE,Not available,How good is bargained routing?,b9b57e7e44e105b7977be0bad1fbd0c0,https://ieeexplore.ieee.org/document/6195636/
9391,"Game theoretic models have been widely employed in many networking contexts. Research to date has mainly focused on non-cooperative networking games, where the selfish agents cannot reach a binding agreement on the way they would share the network infrastructure and the operating points are the Nash equilibria. These are typically inefficient, as manifested by large values of the Price of Anarchy (PoA). Many approaches have been proposed for mitigating this problem, however under the standing assumption of a non-cooperative game. In a growing number of networking scenarios it is possible for the selfish agents to communicate and reach an agreement, i.e., play a cooperative game. Therefore, the degradation of performance should be considered at an operating point that is a cooperative game solution. Accordingly, our goal is to lay foundations for the application of cooperative game theory to fundamental problems in networking. We explain our choice of the Nash Bargaining Scheme (NBS) as the solution concept, and we introduce the Price of Selfishness (PoS), which considers the degradation of performance at an NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we study the classical scenario of agents that consider the same performance objectives. While the PoA here can be very large, we establish that, under plausible assumptions, the PoS attains its minimum value, i.e., through bargaining, the selfish agents reach social optimality. We then extend our study to consider the “heterogeneous” case, where agents may consider vastly different performance objectives. We demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures may now be unsuitable. Accordingly, we introduce the Price of Heterogeneity (PoH), as a proper extension of the PoA. We establish an upper-bound on the PoH for a general class of heterogeneous performance objectives, and indicate that it provides incentives for bargaining also in this general case. We discuss network design guidelines that follow from our findings.",ariel orda,Nash equilibrium,2012.0,10.1109/INFCOM.2012.6195636,2012 Proceedings IEEE INFOCOM,Blocq2012,False,,IEEE,Not available,How good is bargained routing?,b9b57e7e44e105b7977be0bad1fbd0c0,https://ieeexplore.ieee.org/document/6195636/
9392,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",lingjie duan,Pricing,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
9393,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",lingjie duan,Investments,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
9394,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
9395,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",lingjie duan,Costs,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
9396,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",lingjie duan,Resource management,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
9397,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",lingjie duan,Environmental economics,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
9398,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",lingjie duan,Frequency division multiplexing,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
9399,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",lingjie duan,Communications Society,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
9400,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",lingjie duan,Engineering management,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
9401,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",lingjie duan,Government,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
9402,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",lingjie duan,Area measurement,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
9403,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",jianwei huang,Pricing,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
9404,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",jianwei huang,Investments,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
9405,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
9406,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",jianwei huang,Costs,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
9407,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",jianwei huang,Resource management,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
9408,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",jianwei huang,Environmental economics,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
9409,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",jianwei huang,Frequency division multiplexing,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
9410,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",jianwei huang,Communications Society,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
9411,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",jianwei huang,Engineering management,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
9412,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",jianwei huang,Government,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
9413,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",jianwei huang,Area measurement,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
9414,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",biying shou,Pricing,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
9415,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",biying shou,Investments,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
9416,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
9417,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",biying shou,Costs,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
9418,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",biying shou,Resource management,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
9419,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",biying shou,Environmental economics,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
9420,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",biying shou,Frequency division multiplexing,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
9421,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",biying shou,Communications Society,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
9422,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",biying shou,Engineering management,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
9423,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",biying shou,Government,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
9424,"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.",biying shou,Area measurement,2010.0,10.1109/DYSPAN.2010.5457903,2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN),Duan2010,False,,IEEE,Not available,Competition with Dynamic Spectrum Leasing,733767fd7859106c3774dc1f0a5a5a1c,https://ieeexplore.ieee.org/document/5457903/
9425,"We study the performance of noncooperative networks in light of three major topology design considerations, namely the price of establishing a link, path delay, and path proneness to congestion, the latter being modeled through the “relaying extent” of the nodes. We analyze these considerations and the tradeoffs between them from a game-theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. For the latter case, we indicate, by simulations, that practical scenarios tend to admit a Nash equilibrium. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by noncooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (“social”) agent with the ability to impose the initial configuration on the system.",amir nahir,Communication networks,2014.0,10.1109/TNET.2013.2254125,IEEE/ACM Transactions on Networking,Nahir2014,False,,IEEE,Not available,Topology Design of Communication Networks: A Game-Theoretic Perspective,034b94ff5f5e55fcb748e8600a316ad2,https://ieeexplore.ieee.org/document/6495502/
9426,"We study the performance of noncooperative networks in light of three major topology design considerations, namely the price of establishing a link, path delay, and path proneness to congestion, the latter being modeled through the “relaying extent” of the nodes. We analyze these considerations and the tradeoffs between them from a game-theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. For the latter case, we indicate, by simulations, that practical scenarios tend to admit a Nash equilibrium. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by noncooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (“social”) agent with the ability to impose the initial configuration on the system.",amir nahir,game theory,2014.0,10.1109/TNET.2013.2254125,IEEE/ACM Transactions on Networking,Nahir2014,False,,IEEE,Not available,Topology Design of Communication Networks: A Game-Theoretic Perspective,034b94ff5f5e55fcb748e8600a316ad2,https://ieeexplore.ieee.org/document/6495502/
9427,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
9428,"We study the performance of noncooperative networks in light of three major topology design considerations, namely the price of establishing a link, path delay, and path proneness to congestion, the latter being modeled through the “relaying extent” of the nodes. We analyze these considerations and the tradeoffs between them from a game-theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. For the latter case, we indicate, by simulations, that practical scenarios tend to admit a Nash equilibrium. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by noncooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (“social”) agent with the ability to impose the initial configuration on the system.",ariel orda,Communication networks,2014.0,10.1109/TNET.2013.2254125,IEEE/ACM Transactions on Networking,Nahir2014,False,,IEEE,Not available,Topology Design of Communication Networks: A Game-Theoretic Perspective,034b94ff5f5e55fcb748e8600a316ad2,https://ieeexplore.ieee.org/document/6495502/
9429,"We study the performance of noncooperative networks in light of three major topology design considerations, namely the price of establishing a link, path delay, and path proneness to congestion, the latter being modeled through the “relaying extent” of the nodes. We analyze these considerations and the tradeoffs between them from a game-theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. For the latter case, we indicate, by simulations, that practical scenarios tend to admit a Nash equilibrium. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by noncooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (“social”) agent with the ability to impose the initial configuration on the system.",ariel orda,game theory,2014.0,10.1109/TNET.2013.2254125,IEEE/ACM Transactions on Networking,Nahir2014,False,,IEEE,Not available,Topology Design of Communication Networks: A Game-Theoretic Perspective,034b94ff5f5e55fcb748e8600a316ad2,https://ieeexplore.ieee.org/document/6495502/
9430,"We study the performance of noncooperative networks in light of three major topology design considerations, namely the price of establishing a link, path delay, and path proneness to congestion, the latter being modeled through the “relaying extent” of the nodes. We analyze these considerations and the tradeoffs between them from a game-theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. For the latter case, we indicate, by simulations, that practical scenarios tend to admit a Nash equilibrium. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by noncooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (“social”) agent with the ability to impose the initial configuration on the system.",ari freund,Communication networks,2014.0,10.1109/TNET.2013.2254125,IEEE/ACM Transactions on Networking,Nahir2014,False,,IEEE,Not available,Topology Design of Communication Networks: A Game-Theoretic Perspective,034b94ff5f5e55fcb748e8600a316ad2,https://ieeexplore.ieee.org/document/6495502/
9431,"We study the performance of noncooperative networks in light of three major topology design considerations, namely the price of establishing a link, path delay, and path proneness to congestion, the latter being modeled through the “relaying extent” of the nodes. We analyze these considerations and the tradeoffs between them from a game-theoretic perspective, where each network element attempts to optimize its individual performance. We show that for all considered cases but one, the existence of a Nash equilibrium point is guaranteed. For the latter case, we indicate, by simulations, that practical scenarios tend to admit a Nash equilibrium. In addition, we demonstrate that the price of anarchy, i.e., the performance penalty incurred by noncooperative behavior, may be prohibitively large; yet, we also show that such games usually admit at least one Nash equilibrium that is system-wide optimal, i.e., their price of stability is 1. This finding suggests that a major improvement can be achieved by providing a central (“social”) agent with the ability to impose the initial configuration on the system.",ari freund,game theory,2014.0,10.1109/TNET.2013.2254125,IEEE/ACM Transactions on Networking,Nahir2014,False,,IEEE,Not available,Topology Design of Communication Networks: A Game-Theoretic Perspective,034b94ff5f5e55fcb748e8600a316ad2,https://ieeexplore.ieee.org/document/6495502/
9432,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",a. mohsenian-rad,Network coding,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9433,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",a. mohsenian-rad,Pricing,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9434,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",a. mohsenian-rad,Resource management,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9435,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",a. mohsenian-rad,Nash equilibrium,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9436,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",a. mohsenian-rad,Game theory,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9437,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",a. mohsenian-rad,Routing,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9438,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
9439,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
9440,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",a. mohsenian-rad,Communications Society,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9441,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",a. mohsenian-rad,Electronic mail,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9442,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",a. mohsenian-rad,Wireless networks,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9443,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",a. mohsenian-rad,Encoding,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9444,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",j. huang,Network coding,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9445,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",j. huang,Pricing,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9446,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",j. huang,Resource management,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9447,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",j. huang,Nash equilibrium,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9448,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",j. huang,Game theory,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9449,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",j. huang,Routing,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9450,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
9451,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",j. huang,Communications Society,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9452,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",j. huang,Electronic mail,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9453,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",j. huang,Wireless networks,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9454,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",j. huang,Encoding,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9455,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",v. wong,Network coding,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9456,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",v. wong,Pricing,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9457,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",v. wong,Resource management,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9458,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",v. wong,Nash equilibrium,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9459,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",v. wong,Game theory,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9460,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",v. wong,Routing,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9461,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
9462,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",v. wong,Communications Society,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9463,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",v. wong,Electronic mail,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9464,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",v. wong,Wireless networks,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9465,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",v. wong,Encoding,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9466,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",s. jaggi,Network coding,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9467,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",s. jaggi,Pricing,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9468,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",s. jaggi,Resource management,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9469,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",s. jaggi,Nash equilibrium,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9470,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",s. jaggi,Game theory,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9471,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",s. jaggi,Routing,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9472,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
9473,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",s. jaggi,Communications Society,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9474,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",s. jaggi,Electronic mail,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9475,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",s. jaggi,Wireless networks,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9476,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",s. jaggi,Encoding,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9477,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",r. schober,Network coding,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9478,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",r. schober,Pricing,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9479,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",r. schober,Resource management,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9480,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",r. schober,Nash equilibrium,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9481,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",r. schober,Game theory,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9482,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",r. schober,Routing,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9483,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
9484,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",r. schober,Communications Society,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9485,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",r. schober,Electronic mail,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9486,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",r. schober,Wireless networks,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9487,"A common assumption in the network coding literature is that the users are cooperative and will not pursue their own interests. However, this assumption can be violated in practice. In this paper, we analyze inter-session network coding in a wired network, assuming that the users are selfish and act as strategic players to maximize their own utility. We prove the existence of Nash equilibria for a wide range of utility functions. The number of Nash equilibria can be large (even infinite) under certain conditions, which is in sharp contrast to a similar game setting with traditional packet forwarding. We then characterize the worst-case efficiency bounds, i.e., the price-of-anarchy (PoA), compared to an optimal and cooperative network design. We show that by using a novel discriminatory pricing scheme that charges encoded and forwarded packets differently, we can improve PoA in comparison with the case where a single pricing scheme is being used. However, PoA is still worse than the case when network coding is not applied. This implies that inter-session network coding is more sensitive to strategic behavior. For example, for the case where only two network coding flows share a single bottleneck link, the efficiency at certain Nash equilibria can be as low as 48%. These results generalize the well-known result of guaranteed 67% efficiency bounds shown by Johari and Tsitsiklis for traditional packet forwarding networks.",r. schober,Encoding,2009.0,10.1109/ICC.2009.5198609,2009 IEEE International Conference on Communications,Mohsenian-Rad2009,False,,IEEE,Not available,A Game-Theoretic Analysis of Inter-Session Network Coding,f12c2cee1a2ba6aa1d43adb18ff6ba39,https://ieeexplore.ieee.org/document/5198609/
9488,"This paper systematically explores the efficiency of uncoordinated parking space allocation in urban environments with two types of parking facilities. Drivers decide whether to go for inexpensive but limited on-street parking spots or for expensive yet overdimensioned parking lots, incurring an additional cruising cost when they decide for on-street parking spots but fail to actually acquire one. Their decisions are made under perfect knowledge of the total parking supply and costs and different levels of information about the parking demand, i.e., complete/probabilistic information and uncertainty. We take a game-theoretic approach and analyze the parking-space allocation process in each case as resource selection game instances. We derive their equilibria, compute the related price-of-anarchy (PoA) values, and study the impact of pricing on them. It is shown that, under typical pricing policies on the two types of parking facilities, drivers tend to overcompete for the on-street parking space, giving rise to redundant cruising cost. However, this inefficiency can be alleviated through systematic manipulation of the information that is announced to the drivers. In particular, counterintuitive less-is-more effects emerge regarding the way that information availability modulates the resulting efficiency of the process, which underpin general competitive service provision settings.",evangelia kokolaki,Intelligent transportation,2013.0,10.1109/TVT.2013.2269015,IEEE Transactions on Vehicular Technology,Kokolaki2013,False,,IEEE,Not available,Leveraging Information in Parking Assistance Systems,44a9a7938c886c516d9f166e35b8e133,https://ieeexplore.ieee.org/document/6542023/
9489,"This paper systematically explores the efficiency of uncoordinated parking space allocation in urban environments with two types of parking facilities. Drivers decide whether to go for inexpensive but limited on-street parking spots or for expensive yet overdimensioned parking lots, incurring an additional cruising cost when they decide for on-street parking spots but fail to actually acquire one. Their decisions are made under perfect knowledge of the total parking supply and costs and different levels of information about the parking demand, i.e., complete/probabilistic information and uncertainty. We take a game-theoretic approach and analyze the parking-space allocation process in each case as resource selection game instances. We derive their equilibria, compute the related price-of-anarchy (PoA) values, and study the impact of pricing on them. It is shown that, under typical pricing policies on the two types of parking facilities, drivers tend to overcompete for the on-street parking space, giving rise to redundant cruising cost. However, this inefficiency can be alleviated through systematic manipulation of the information that is announced to the drivers. In particular, counterintuitive less-is-more effects emerge regarding the way that information availability modulates the resulting efficiency of the process, which underpin general competitive service provision settings.",evangelia kokolaki,parking games,2013.0,10.1109/TVT.2013.2269015,IEEE Transactions on Vehicular Technology,Kokolaki2013,False,,IEEE,Not available,Leveraging Information in Parking Assistance Systems,44a9a7938c886c516d9f166e35b8e133,https://ieeexplore.ieee.org/document/6542023/
9490,"This paper systematically explores the efficiency of uncoordinated parking space allocation in urban environments with two types of parking facilities. Drivers decide whether to go for inexpensive but limited on-street parking spots or for expensive yet overdimensioned parking lots, incurring an additional cruising cost when they decide for on-street parking spots but fail to actually acquire one. Their decisions are made under perfect knowledge of the total parking supply and costs and different levels of information about the parking demand, i.e., complete/probabilistic information and uncertainty. We take a game-theoretic approach and analyze the parking-space allocation process in each case as resource selection game instances. We derive their equilibria, compute the related price-of-anarchy (PoA) values, and study the impact of pricing on them. It is shown that, under typical pricing policies on the two types of parking facilities, drivers tend to overcompete for the on-street parking space, giving rise to redundant cruising cost. However, this inefficiency can be alleviated through systematic manipulation of the information that is announced to the drivers. In particular, counterintuitive less-is-more effects emerge regarding the way that information availability modulates the resulting efficiency of the process, which underpin general competitive service provision settings.",evangelia kokolaki,uncertainty,2013.0,10.1109/TVT.2013.2269015,IEEE Transactions on Vehicular Technology,Kokolaki2013,False,,IEEE,Not available,Leveraging Information in Parking Assistance Systems,44a9a7938c886c516d9f166e35b8e133,https://ieeexplore.ieee.org/document/6542023/
9491,"This paper systematically explores the efficiency of uncoordinated parking space allocation in urban environments with two types of parking facilities. Drivers decide whether to go for inexpensive but limited on-street parking spots or for expensive yet overdimensioned parking lots, incurring an additional cruising cost when they decide for on-street parking spots but fail to actually acquire one. Their decisions are made under perfect knowledge of the total parking supply and costs and different levels of information about the parking demand, i.e., complete/probabilistic information and uncertainty. We take a game-theoretic approach and analyze the parking-space allocation process in each case as resource selection game instances. We derive their equilibria, compute the related price-of-anarchy (PoA) values, and study the impact of pricing on them. It is shown that, under typical pricing policies on the two types of parking facilities, drivers tend to overcompete for the on-street parking space, giving rise to redundant cruising cost. However, this inefficiency can be alleviated through systematic manipulation of the information that is announced to the drivers. In particular, counterintuitive less-is-more effects emerge regarding the way that information availability modulates the resulting efficiency of the process, which underpin general competitive service provision settings.",evangelia kokolaki,vehicular ad hoc networks (VANETs),2013.0,10.1109/TVT.2013.2269015,IEEE Transactions on Vehicular Technology,Kokolaki2013,False,,IEEE,Not available,Leveraging Information in Parking Assistance Systems,44a9a7938c886c516d9f166e35b8e133,https://ieeexplore.ieee.org/document/6542023/
9492,"This paper systematically explores the efficiency of uncoordinated parking space allocation in urban environments with two types of parking facilities. Drivers decide whether to go for inexpensive but limited on-street parking spots or for expensive yet overdimensioned parking lots, incurring an additional cruising cost when they decide for on-street parking spots but fail to actually acquire one. Their decisions are made under perfect knowledge of the total parking supply and costs and different levels of information about the parking demand, i.e., complete/probabilistic information and uncertainty. We take a game-theoretic approach and analyze the parking-space allocation process in each case as resource selection game instances. We derive their equilibria, compute the related price-of-anarchy (PoA) values, and study the impact of pricing on them. It is shown that, under typical pricing policies on the two types of parking facilities, drivers tend to overcompete for the on-street parking space, giving rise to redundant cruising cost. However, this inefficiency can be alleviated through systematic manipulation of the information that is announced to the drivers. In particular, counterintuitive less-is-more effects emerge regarding the way that information availability modulates the resulting efficiency of the process, which underpin general competitive service provision settings.",merkouris karaliopoulos,Intelligent transportation,2013.0,10.1109/TVT.2013.2269015,IEEE Transactions on Vehicular Technology,Kokolaki2013,False,,IEEE,Not available,Leveraging Information in Parking Assistance Systems,44a9a7938c886c516d9f166e35b8e133,https://ieeexplore.ieee.org/document/6542023/
9493,"This paper systematically explores the efficiency of uncoordinated parking space allocation in urban environments with two types of parking facilities. Drivers decide whether to go for inexpensive but limited on-street parking spots or for expensive yet overdimensioned parking lots, incurring an additional cruising cost when they decide for on-street parking spots but fail to actually acquire one. Their decisions are made under perfect knowledge of the total parking supply and costs and different levels of information about the parking demand, i.e., complete/probabilistic information and uncertainty. We take a game-theoretic approach and analyze the parking-space allocation process in each case as resource selection game instances. We derive their equilibria, compute the related price-of-anarchy (PoA) values, and study the impact of pricing on them. It is shown that, under typical pricing policies on the two types of parking facilities, drivers tend to overcompete for the on-street parking space, giving rise to redundant cruising cost. However, this inefficiency can be alleviated through systematic manipulation of the information that is announced to the drivers. In particular, counterintuitive less-is-more effects emerge regarding the way that information availability modulates the resulting efficiency of the process, which underpin general competitive service provision settings.",merkouris karaliopoulos,parking games,2013.0,10.1109/TVT.2013.2269015,IEEE Transactions on Vehicular Technology,Kokolaki2013,False,,IEEE,Not available,Leveraging Information in Parking Assistance Systems,44a9a7938c886c516d9f166e35b8e133,https://ieeexplore.ieee.org/document/6542023/
9494,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
9495,"This paper systematically explores the efficiency of uncoordinated parking space allocation in urban environments with two types of parking facilities. Drivers decide whether to go for inexpensive but limited on-street parking spots or for expensive yet overdimensioned parking lots, incurring an additional cruising cost when they decide for on-street parking spots but fail to actually acquire one. Their decisions are made under perfect knowledge of the total parking supply and costs and different levels of information about the parking demand, i.e., complete/probabilistic information and uncertainty. We take a game-theoretic approach and analyze the parking-space allocation process in each case as resource selection game instances. We derive their equilibria, compute the related price-of-anarchy (PoA) values, and study the impact of pricing on them. It is shown that, under typical pricing policies on the two types of parking facilities, drivers tend to overcompete for the on-street parking space, giving rise to redundant cruising cost. However, this inefficiency can be alleviated through systematic manipulation of the information that is announced to the drivers. In particular, counterintuitive less-is-more effects emerge regarding the way that information availability modulates the resulting efficiency of the process, which underpin general competitive service provision settings.",merkouris karaliopoulos,uncertainty,2013.0,10.1109/TVT.2013.2269015,IEEE Transactions on Vehicular Technology,Kokolaki2013,False,,IEEE,Not available,Leveraging Information in Parking Assistance Systems,44a9a7938c886c516d9f166e35b8e133,https://ieeexplore.ieee.org/document/6542023/
9496,"This paper systematically explores the efficiency of uncoordinated parking space allocation in urban environments with two types of parking facilities. Drivers decide whether to go for inexpensive but limited on-street parking spots or for expensive yet overdimensioned parking lots, incurring an additional cruising cost when they decide for on-street parking spots but fail to actually acquire one. Their decisions are made under perfect knowledge of the total parking supply and costs and different levels of information about the parking demand, i.e., complete/probabilistic information and uncertainty. We take a game-theoretic approach and analyze the parking-space allocation process in each case as resource selection game instances. We derive their equilibria, compute the related price-of-anarchy (PoA) values, and study the impact of pricing on them. It is shown that, under typical pricing policies on the two types of parking facilities, drivers tend to overcompete for the on-street parking space, giving rise to redundant cruising cost. However, this inefficiency can be alleviated through systematic manipulation of the information that is announced to the drivers. In particular, counterintuitive less-is-more effects emerge regarding the way that information availability modulates the resulting efficiency of the process, which underpin general competitive service provision settings.",merkouris karaliopoulos,vehicular ad hoc networks (VANETs),2013.0,10.1109/TVT.2013.2269015,IEEE Transactions on Vehicular Technology,Kokolaki2013,False,,IEEE,Not available,Leveraging Information in Parking Assistance Systems,44a9a7938c886c516d9f166e35b8e133,https://ieeexplore.ieee.org/document/6542023/
9497,"This paper systematically explores the efficiency of uncoordinated parking space allocation in urban environments with two types of parking facilities. Drivers decide whether to go for inexpensive but limited on-street parking spots or for expensive yet overdimensioned parking lots, incurring an additional cruising cost when they decide for on-street parking spots but fail to actually acquire one. Their decisions are made under perfect knowledge of the total parking supply and costs and different levels of information about the parking demand, i.e., complete/probabilistic information and uncertainty. We take a game-theoretic approach and analyze the parking-space allocation process in each case as resource selection game instances. We derive their equilibria, compute the related price-of-anarchy (PoA) values, and study the impact of pricing on them. It is shown that, under typical pricing policies on the two types of parking facilities, drivers tend to overcompete for the on-street parking space, giving rise to redundant cruising cost. However, this inefficiency can be alleviated through systematic manipulation of the information that is announced to the drivers. In particular, counterintuitive less-is-more effects emerge regarding the way that information availability modulates the resulting efficiency of the process, which underpin general competitive service provision settings.",ioannis stavrakakis,Intelligent transportation,2013.0,10.1109/TVT.2013.2269015,IEEE Transactions on Vehicular Technology,Kokolaki2013,False,,IEEE,Not available,Leveraging Information in Parking Assistance Systems,44a9a7938c886c516d9f166e35b8e133,https://ieeexplore.ieee.org/document/6542023/
9498,"This paper systematically explores the efficiency of uncoordinated parking space allocation in urban environments with two types of parking facilities. Drivers decide whether to go for inexpensive but limited on-street parking spots or for expensive yet overdimensioned parking lots, incurring an additional cruising cost when they decide for on-street parking spots but fail to actually acquire one. Their decisions are made under perfect knowledge of the total parking supply and costs and different levels of information about the parking demand, i.e., complete/probabilistic information and uncertainty. We take a game-theoretic approach and analyze the parking-space allocation process in each case as resource selection game instances. We derive their equilibria, compute the related price-of-anarchy (PoA) values, and study the impact of pricing on them. It is shown that, under typical pricing policies on the two types of parking facilities, drivers tend to overcompete for the on-street parking space, giving rise to redundant cruising cost. However, this inefficiency can be alleviated through systematic manipulation of the information that is announced to the drivers. In particular, counterintuitive less-is-more effects emerge regarding the way that information availability modulates the resulting efficiency of the process, which underpin general competitive service provision settings.",ioannis stavrakakis,parking games,2013.0,10.1109/TVT.2013.2269015,IEEE Transactions on Vehicular Technology,Kokolaki2013,False,,IEEE,Not available,Leveraging Information in Parking Assistance Systems,44a9a7938c886c516d9f166e35b8e133,https://ieeexplore.ieee.org/document/6542023/
9499,"This paper systematically explores the efficiency of uncoordinated parking space allocation in urban environments with two types of parking facilities. Drivers decide whether to go for inexpensive but limited on-street parking spots or for expensive yet overdimensioned parking lots, incurring an additional cruising cost when they decide for on-street parking spots but fail to actually acquire one. Their decisions are made under perfect knowledge of the total parking supply and costs and different levels of information about the parking demand, i.e., complete/probabilistic information and uncertainty. We take a game-theoretic approach and analyze the parking-space allocation process in each case as resource selection game instances. We derive their equilibria, compute the related price-of-anarchy (PoA) values, and study the impact of pricing on them. It is shown that, under typical pricing policies on the two types of parking facilities, drivers tend to overcompete for the on-street parking space, giving rise to redundant cruising cost. However, this inefficiency can be alleviated through systematic manipulation of the information that is announced to the drivers. In particular, counterintuitive less-is-more effects emerge regarding the way that information availability modulates the resulting efficiency of the process, which underpin general competitive service provision settings.",ioannis stavrakakis,uncertainty,2013.0,10.1109/TVT.2013.2269015,IEEE Transactions on Vehicular Technology,Kokolaki2013,False,,IEEE,Not available,Leveraging Information in Parking Assistance Systems,44a9a7938c886c516d9f166e35b8e133,https://ieeexplore.ieee.org/document/6542023/
9500,"This paper systematically explores the efficiency of uncoordinated parking space allocation in urban environments with two types of parking facilities. Drivers decide whether to go for inexpensive but limited on-street parking spots or for expensive yet overdimensioned parking lots, incurring an additional cruising cost when they decide for on-street parking spots but fail to actually acquire one. Their decisions are made under perfect knowledge of the total parking supply and costs and different levels of information about the parking demand, i.e., complete/probabilistic information and uncertainty. We take a game-theoretic approach and analyze the parking-space allocation process in each case as resource selection game instances. We derive their equilibria, compute the related price-of-anarchy (PoA) values, and study the impact of pricing on them. It is shown that, under typical pricing policies on the two types of parking facilities, drivers tend to overcompete for the on-street parking space, giving rise to redundant cruising cost. However, this inefficiency can be alleviated through systematic manipulation of the information that is announced to the drivers. In particular, counterintuitive less-is-more effects emerge regarding the way that information availability modulates the resulting efficiency of the process, which underpin general competitive service provision settings.",ioannis stavrakakis,vehicular ad hoc networks (VANETs),2013.0,10.1109/TVT.2013.2269015,IEEE Transactions on Vehicular Technology,Kokolaki2013,False,,IEEE,Not available,Leveraging Information in Parking Assistance Systems,44a9a7938c886c516d9f166e35b8e133,https://ieeexplore.ieee.org/document/6542023/
9501,"In self-organized wireless network, such as ad hoc network, sensor network or mesh network, nodes are independent individuals which have different benefit; Therefore, selfish nodes refuse to forward packets for other nodes in order to save energy which causes the network fault. At the same time, some nodes may be malicious, whose aim is to damage the network. In this paper, we analyze the cooperation stimulation and security in self-organized wireless networks under a game theoretic framework. We first analyze a four node wireless network in which nodes share the channel by relaying for others during its idle periods in order to help the other nodes, each node has to use a part of its available channel capacity. And then, the fault tolerance and security problem is modeled as a non-cooperative game in which each player maximizes its own utility function. The goal of the game is to maximize the utility function in the giving condition in order to get better network efficiency. At last, for characterizing the efficiency of Nash equilibria, we analyze the so called price of anarchy, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Our results show that the players can get the biggest payoff if they obey cooperation strategy.",jing chen,Game theory,2009.0,10.1109/MINES.2009.113,2009 International Conference on Multimedia Information Networking and Security,Chen2009,False,,IEEE,Not available,Fault Tolerance and Security in Forwarding Packets Using Game Theory,22012ee60dafefdbdfe2deb9566ef4eb,https://ieeexplore.ieee.org/document/5370999/
9502,"In self-organized wireless network, such as ad hoc network, sensor network or mesh network, nodes are independent individuals which have different benefit; Therefore, selfish nodes refuse to forward packets for other nodes in order to save energy which causes the network fault. At the same time, some nodes may be malicious, whose aim is to damage the network. In this paper, we analyze the cooperation stimulation and security in self-organized wireless networks under a game theoretic framework. We first analyze a four node wireless network in which nodes share the channel by relaying for others during its idle periods in order to help the other nodes, each node has to use a part of its available channel capacity. And then, the fault tolerance and security problem is modeled as a non-cooperative game in which each player maximizes its own utility function. The goal of the game is to maximize the utility function in the giving condition in order to get better network efficiency. At last, for characterizing the efficiency of Nash equilibria, we analyze the so called price of anarchy, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Our results show that the players can get the biggest payoff if they obey cooperation strategy.",jing chen,Fault Tolerance,2009.0,10.1109/MINES.2009.113,2009 International Conference on Multimedia Information Networking and Security,Chen2009,False,,IEEE,Not available,Fault Tolerance and Security in Forwarding Packets Using Game Theory,22012ee60dafefdbdfe2deb9566ef4eb,https://ieeexplore.ieee.org/document/5370999/
9503,"In self-organized wireless network, such as ad hoc network, sensor network or mesh network, nodes are independent individuals which have different benefit; Therefore, selfish nodes refuse to forward packets for other nodes in order to save energy which causes the network fault. At the same time, some nodes may be malicious, whose aim is to damage the network. In this paper, we analyze the cooperation stimulation and security in self-organized wireless networks under a game theoretic framework. We first analyze a four node wireless network in which nodes share the channel by relaying for others during its idle periods in order to help the other nodes, each node has to use a part of its available channel capacity. And then, the fault tolerance and security problem is modeled as a non-cooperative game in which each player maximizes its own utility function. The goal of the game is to maximize the utility function in the giving condition in order to get better network efficiency. At last, for characterizing the efficiency of Nash equilibria, we analyze the so called price of anarchy, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Our results show that the players can get the biggest payoff if they obey cooperation strategy.",jing chen,Security,2009.0,10.1109/MINES.2009.113,2009 International Conference on Multimedia Information Networking and Security,Chen2009,False,,IEEE,Not available,Fault Tolerance and Security in Forwarding Packets Using Game Theory,22012ee60dafefdbdfe2deb9566ef4eb,https://ieeexplore.ieee.org/document/5370999/
9504,"In self-organized wireless network, such as ad hoc network, sensor network or mesh network, nodes are independent individuals which have different benefit; Therefore, selfish nodes refuse to forward packets for other nodes in order to save energy which causes the network fault. At the same time, some nodes may be malicious, whose aim is to damage the network. In this paper, we analyze the cooperation stimulation and security in self-organized wireless networks under a game theoretic framework. We first analyze a four node wireless network in which nodes share the channel by relaying for others during its idle periods in order to help the other nodes, each node has to use a part of its available channel capacity. And then, the fault tolerance and security problem is modeled as a non-cooperative game in which each player maximizes its own utility function. The goal of the game is to maximize the utility function in the giving condition in order to get better network efficiency. At last, for characterizing the efficiency of Nash equilibria, we analyze the so called price of anarchy, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Our results show that the players can get the biggest payoff if they obey cooperation strategy.",ruiying du,Game theory,2009.0,10.1109/MINES.2009.113,2009 International Conference on Multimedia Information Networking and Security,Chen2009,False,,IEEE,Not available,Fault Tolerance and Security in Forwarding Packets Using Game Theory,22012ee60dafefdbdfe2deb9566ef4eb,https://ieeexplore.ieee.org/document/5370999/
9505,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
9506,"In self-organized wireless network, such as ad hoc network, sensor network or mesh network, nodes are independent individuals which have different benefit; Therefore, selfish nodes refuse to forward packets for other nodes in order to save energy which causes the network fault. At the same time, some nodes may be malicious, whose aim is to damage the network. In this paper, we analyze the cooperation stimulation and security in self-organized wireless networks under a game theoretic framework. We first analyze a four node wireless network in which nodes share the channel by relaying for others during its idle periods in order to help the other nodes, each node has to use a part of its available channel capacity. And then, the fault tolerance and security problem is modeled as a non-cooperative game in which each player maximizes its own utility function. The goal of the game is to maximize the utility function in the giving condition in order to get better network efficiency. At last, for characterizing the efficiency of Nash equilibria, we analyze the so called price of anarchy, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Our results show that the players can get the biggest payoff if they obey cooperation strategy.",ruiying du,Fault Tolerance,2009.0,10.1109/MINES.2009.113,2009 International Conference on Multimedia Information Networking and Security,Chen2009,False,,IEEE,Not available,Fault Tolerance and Security in Forwarding Packets Using Game Theory,22012ee60dafefdbdfe2deb9566ef4eb,https://ieeexplore.ieee.org/document/5370999/
9507,"In self-organized wireless network, such as ad hoc network, sensor network or mesh network, nodes are independent individuals which have different benefit; Therefore, selfish nodes refuse to forward packets for other nodes in order to save energy which causes the network fault. At the same time, some nodes may be malicious, whose aim is to damage the network. In this paper, we analyze the cooperation stimulation and security in self-organized wireless networks under a game theoretic framework. We first analyze a four node wireless network in which nodes share the channel by relaying for others during its idle periods in order to help the other nodes, each node has to use a part of its available channel capacity. And then, the fault tolerance and security problem is modeled as a non-cooperative game in which each player maximizes its own utility function. The goal of the game is to maximize the utility function in the giving condition in order to get better network efficiency. At last, for characterizing the efficiency of Nash equilibria, we analyze the so called price of anarchy, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Our results show that the players can get the biggest payoff if they obey cooperation strategy.",ruiying du,Security,2009.0,10.1109/MINES.2009.113,2009 International Conference on Multimedia Information Networking and Security,Chen2009,False,,IEEE,Not available,Fault Tolerance and Security in Forwarding Packets Using Game Theory,22012ee60dafefdbdfe2deb9566ef4eb,https://ieeexplore.ieee.org/document/5370999/
9508,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
9509,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
9510,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
9511,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
9512,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
9513,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
9514,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
9515,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
9516,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
9517,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
9518,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
9519,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",danilo ardagna,Cloud computing,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
9520,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",danilo ardagna,Game Theory,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
9521,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",danilo ardagna,resource allocation,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
9522,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",danilo ardagna,performance attributes,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
9523,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",danilo ardagna,client/server,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
9524,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",danilo ardagna,distributed applications,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
9525,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",danilo ardagna,quality concepts,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
9526,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",barbara panicucci,Cloud computing,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
9527,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
9528,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",barbara panicucci,Game Theory,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
9529,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",barbara panicucci,resource allocation,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
9530,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",barbara panicucci,performance attributes,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
9531,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",barbara panicucci,client/server,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
9532,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",barbara panicucci,distributed applications,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
9533,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",barbara panicucci,quality concepts,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
9534,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",mauro passacantando,Cloud computing,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
9535,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",mauro passacantando,Game Theory,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
9536,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",mauro passacantando,resource allocation,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
9537,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",mauro passacantando,performance attributes,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
9538,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
9539,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",mauro passacantando,client/server,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
9540,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",mauro passacantando,distributed applications,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
9541,"In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper, we take the perspective of Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (SLA) contracts with the end users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper, we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics, and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.",mauro passacantando,quality concepts,2013.0,10.1109/TSC.2012.14,IEEE Transactions on Services Computing,Ardagna2013,False,,IEEE,Not available,Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems,6c32667f9fe9699ab0192c12a6140363,https://ieeexplore.ieee.org/document/6185529/
9542,"In this paper, we study a sequential dynamic routing game on a line where the decision of a user is spatio-temporal control. Each user ships its demand over time on a shared resource. We address the case where only one user arrives at each time epoch. The state of a player evolves according to whether he decides to transmit or not. We provide explicit expressions of the equilibrium of such systems and compare them to the global optimum case. In particular, we compute the price of anarchy of such schemes and identify a Braess-type paradox in the context of sequential routing game.",majed haddad,Sequential routing game,2012.0,10.1109/ICCITechnol.2012.6285812,2012 International Conference on Communications and Information Technology (ICCIT),Haddad2012,False,,IEEE,Not available,Sequential routing game on the line: Transmit or relay?,f51da9a75fad1b45600d9c90f2e3465d,https://ieeexplore.ieee.org/document/6285812/
9543,"In this paper, we study a sequential dynamic routing game on a line where the decision of a user is spatio-temporal control. Each user ships its demand over time on a shared resource. We address the case where only one user arrives at each time epoch. The state of a player evolves according to whether he decides to transmit or not. We provide explicit expressions of the equilibrium of such systems and compare them to the global optimum case. In particular, we compute the price of anarchy of such schemes and identify a Braess-type paradox in the context of sequential routing game.",majed haddad,Nash equilibrium,2012.0,10.1109/ICCITechnol.2012.6285812,2012 International Conference on Communications and Information Technology (ICCIT),Haddad2012,False,,IEEE,Not available,Sequential routing game on the line: Transmit or relay?,f51da9a75fad1b45600d9c90f2e3465d,https://ieeexplore.ieee.org/document/6285812/
9544,"In this paper, we study a sequential dynamic routing game on a line where the decision of a user is spatio-temporal control. Each user ships its demand over time on a shared resource. We address the case where only one user arrives at each time epoch. The state of a player evolves according to whether he decides to transmit or not. We provide explicit expressions of the equilibrium of such systems and compare them to the global optimum case. In particular, we compute the price of anarchy of such schemes and identify a Braess-type paradox in the context of sequential routing game.",majed haddad,Price of anarchy,2012.0,10.1109/ICCITechnol.2012.6285812,2012 International Conference on Communications and Information Technology (ICCIT),Haddad2012,False,,IEEE,Not available,Sequential routing game on the line: Transmit or relay?,f51da9a75fad1b45600d9c90f2e3465d,https://ieeexplore.ieee.org/document/6285812/
9545,"In this paper, we study a sequential dynamic routing game on a line where the decision of a user is spatio-temporal control. Each user ships its demand over time on a shared resource. We address the case where only one user arrives at each time epoch. The state of a player evolves according to whether he decides to transmit or not. We provide explicit expressions of the equilibrium of such systems and compare them to the global optimum case. In particular, we compute the price of anarchy of such schemes and identify a Braess-type paradox in the context of sequential routing game.",majed haddad,Braess-type paradox,2012.0,10.1109/ICCITechnol.2012.6285812,2012 International Conference on Communications and Information Technology (ICCIT),Haddad2012,False,,IEEE,Not available,Sequential routing game on the line: Transmit or relay?,f51da9a75fad1b45600d9c90f2e3465d,https://ieeexplore.ieee.org/document/6285812/
9546,"In this paper, we study a sequential dynamic routing game on a line where the decision of a user is spatio-temporal control. Each user ships its demand over time on a shared resource. We address the case where only one user arrives at each time epoch. The state of a player evolves according to whether he decides to transmit or not. We provide explicit expressions of the equilibrium of such systems and compare them to the global optimum case. In particular, we compute the price of anarchy of such schemes and identify a Braess-type paradox in the context of sequential routing game.",eitan altman,Sequential routing game,2012.0,10.1109/ICCITechnol.2012.6285812,2012 International Conference on Communications and Information Technology (ICCIT),Haddad2012,False,,IEEE,Not available,Sequential routing game on the line: Transmit or relay?,f51da9a75fad1b45600d9c90f2e3465d,https://ieeexplore.ieee.org/document/6285812/
9547,"In this paper, we study a sequential dynamic routing game on a line where the decision of a user is spatio-temporal control. Each user ships its demand over time on a shared resource. We address the case where only one user arrives at each time epoch. The state of a player evolves according to whether he decides to transmit or not. We provide explicit expressions of the equilibrium of such systems and compare them to the global optimum case. In particular, we compute the price of anarchy of such schemes and identify a Braess-type paradox in the context of sequential routing game.",eitan altman,Nash equilibrium,2012.0,10.1109/ICCITechnol.2012.6285812,2012 International Conference on Communications and Information Technology (ICCIT),Haddad2012,False,,IEEE,Not available,Sequential routing game on the line: Transmit or relay?,f51da9a75fad1b45600d9c90f2e3465d,https://ieeexplore.ieee.org/document/6285812/
9548,"In this paper, we study a sequential dynamic routing game on a line where the decision of a user is spatio-temporal control. Each user ships its demand over time on a shared resource. We address the case where only one user arrives at each time epoch. The state of a player evolves according to whether he decides to transmit or not. We provide explicit expressions of the equilibrium of such systems and compare them to the global optimum case. In particular, we compute the price of anarchy of such schemes and identify a Braess-type paradox in the context of sequential routing game.",eitan altman,Price of anarchy,2012.0,10.1109/ICCITechnol.2012.6285812,2012 International Conference on Communications and Information Technology (ICCIT),Haddad2012,False,,IEEE,Not available,Sequential routing game on the line: Transmit or relay?,f51da9a75fad1b45600d9c90f2e3465d,https://ieeexplore.ieee.org/document/6285812/
9549,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
9550,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
9551,"In this paper, we study a sequential dynamic routing game on a line where the decision of a user is spatio-temporal control. Each user ships its demand over time on a shared resource. We address the case where only one user arrives at each time epoch. The state of a player evolves according to whether he decides to transmit or not. We provide explicit expressions of the equilibrium of such systems and compare them to the global optimum case. In particular, we compute the price of anarchy of such schemes and identify a Braess-type paradox in the context of sequential routing game.",eitan altman,Braess-type paradox,2012.0,10.1109/ICCITechnol.2012.6285812,2012 International Conference on Communications and Information Technology (ICCIT),Haddad2012,False,,IEEE,Not available,Sequential routing game on the line: Transmit or relay?,f51da9a75fad1b45600d9c90f2e3465d,https://ieeexplore.ieee.org/document/6285812/
9552,"In this paper, we study a sequential dynamic routing game on a line where the decision of a user is spatio-temporal control. Each user ships its demand over time on a shared resource. We address the case where only one user arrives at each time epoch. The state of a player evolves according to whether he decides to transmit or not. We provide explicit expressions of the equilibrium of such systems and compare them to the global optimum case. In particular, we compute the price of anarchy of such schemes and identify a Braess-type paradox in the context of sequential routing game.",julien gaillard,Sequential routing game,2012.0,10.1109/ICCITechnol.2012.6285812,2012 International Conference on Communications and Information Technology (ICCIT),Haddad2012,False,,IEEE,Not available,Sequential routing game on the line: Transmit or relay?,f51da9a75fad1b45600d9c90f2e3465d,https://ieeexplore.ieee.org/document/6285812/
9553,"In this paper, we study a sequential dynamic routing game on a line where the decision of a user is spatio-temporal control. Each user ships its demand over time on a shared resource. We address the case where only one user arrives at each time epoch. The state of a player evolves according to whether he decides to transmit or not. We provide explicit expressions of the equilibrium of such systems and compare them to the global optimum case. In particular, we compute the price of anarchy of such schemes and identify a Braess-type paradox in the context of sequential routing game.",julien gaillard,Nash equilibrium,2012.0,10.1109/ICCITechnol.2012.6285812,2012 International Conference on Communications and Information Technology (ICCIT),Haddad2012,False,,IEEE,Not available,Sequential routing game on the line: Transmit or relay?,f51da9a75fad1b45600d9c90f2e3465d,https://ieeexplore.ieee.org/document/6285812/
9554,"In this paper, we study a sequential dynamic routing game on a line where the decision of a user is spatio-temporal control. Each user ships its demand over time on a shared resource. We address the case where only one user arrives at each time epoch. The state of a player evolves according to whether he decides to transmit or not. We provide explicit expressions of the equilibrium of such systems and compare them to the global optimum case. In particular, we compute the price of anarchy of such schemes and identify a Braess-type paradox in the context of sequential routing game.",julien gaillard,Price of anarchy,2012.0,10.1109/ICCITechnol.2012.6285812,2012 International Conference on Communications and Information Technology (ICCIT),Haddad2012,False,,IEEE,Not available,Sequential routing game on the line: Transmit or relay?,f51da9a75fad1b45600d9c90f2e3465d,https://ieeexplore.ieee.org/document/6285812/
9555,"In this paper, we study a sequential dynamic routing game on a line where the decision of a user is spatio-temporal control. Each user ships its demand over time on a shared resource. We address the case where only one user arrives at each time epoch. The state of a player evolves according to whether he decides to transmit or not. We provide explicit expressions of the equilibrium of such systems and compare them to the global optimum case. In particular, we compute the price of anarchy of such schemes and identify a Braess-type paradox in the context of sequential routing game.",julien gaillard,Braess-type paradox,2012.0,10.1109/ICCITechnol.2012.6285812,2012 International Conference on Communications and Information Technology (ICCIT),Haddad2012,False,,IEEE,Not available,Sequential routing game on the line: Transmit or relay?,f51da9a75fad1b45600d9c90f2e3465d,https://ieeexplore.ieee.org/document/6285812/
9556,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",sidi ezzahidi,Relays,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
9557,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",sidi ezzahidi,Games,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
9558,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",sidi ezzahidi,Nash equilibrium,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
9559,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",sidi ezzahidi,Approximation algorithms,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
9560,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",sidi ezzahidi,Delays,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
9561,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
9562,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",sidi ezzahidi,Routing,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
9563,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",sidi ezzahidi,Algebra,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
9564,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",essaid sabir,Relays,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
9565,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",essaid sabir,Games,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
9566,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",essaid sabir,Nash equilibrium,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
9567,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",essaid sabir,Approximation algorithms,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
9568,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",essaid sabir,Delays,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
9569,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",essaid sabir,Routing,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
9570,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",essaid sabir,Algebra,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
9571,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",el-houssine bouyakhf,Relays,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
9572,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
9573,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",el-houssine bouyakhf,Games,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
9574,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",el-houssine bouyakhf,Nash equilibrium,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
9575,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",el-houssine bouyakhf,Approximation algorithms,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
9576,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",el-houssine bouyakhf,Delays,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
9577,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",el-houssine bouyakhf,Routing,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
9578,"This paper introduces a new incentive mechanism for content caching in Delay Tolerant Network (DTN) aiming to improve the performance under relays energy cost. We model this distributed network problem as non-cooperative game, we focus on the source-relay interaction to investigate how far data transmission could be sustained. For instance, due to a limited capacity storage and battery lifetime the relay could abstain from cooperation. Thus implementing such a mechanism is crucial, the source offers the relay some positive reward in order for this latter to accept caching and forwarding the content to the final destination. However, the relay may either accept or reject this offer, depending on the reward value and the expected energy consumption due to this operation. Next, we exhibit some sufficient conditions ensuring existence of Nash equilibria for this game. Further, we discuss their efficiency using the concept of price of anarchy. Moreover, we propose two fully distributed algorithms to reach the equilibria (both for pure and mixed equilibria). We validate our proposal using extensive numerical examples and numerous simulation runs, and draw some conclusions and insightful remarks.",el-houssine bouyakhf,Algebra,2016.0,10.1109/NOMS.2016.7502916,NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,Ezzahidi2016,False,,IEEE,Not available,A reward-based incentive mechanism for file caching in delay tolerant networks,5297db06cc7760229ae6538a08acb4f8,https://ieeexplore.ieee.org/document/7502916/
9579,"Aggregating statistically diverse renewable power producers (RPPs) is an effective way to reduce the uncertainty of the RPPs. The key question is how to design a mechanism to aggregate the RPPs and distribute the payoffs among them. In this paper, a simple payoff allocation mechanism (PAM) is shown to achieve a wide range of desired properties. In particular, social efficiency, stability (in the core), and no collusion are achieved at the unique pure Nash Equilibrium (NE) of the non-cooperative game of RPPs induced by the PAM. As a result, an ideal “Price of Anarchy” of one is achieved. Moreover, a closed form expression of the unique pure NE is derived. A simulation study is conducted using the data of ten wind power producers in the PJM interconnection.",hossein khazaei,Mechanism Design,2017.0,10.1109/GlobalSIP.2017.8309116,2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP),Khazaei2017,False,,IEEE,Not available,A simple payoff allocation mechanism achieves efficiency and stability in renewable energy aggregation,6e22313d864590a3e9eae891991c37db,https://ieeexplore.ieee.org/document/8309116/
9580,"Aggregating statistically diverse renewable power producers (RPPs) is an effective way to reduce the uncertainty of the RPPs. The key question is how to design a mechanism to aggregate the RPPs and distribute the payoffs among them. In this paper, a simple payoff allocation mechanism (PAM) is shown to achieve a wide range of desired properties. In particular, social efficiency, stability (in the core), and no collusion are achieved at the unique pure Nash Equilibrium (NE) of the non-cooperative game of RPPs induced by the PAM. As a result, an ideal “Price of Anarchy” of one is achieved. Moreover, a closed form expression of the unique pure NE is derived. A simulation study is conducted using the data of ten wind power producers in the PJM interconnection.",hossein khazaei,Renewable Energy Integration,2017.0,10.1109/GlobalSIP.2017.8309116,2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP),Khazaei2017,False,,IEEE,Not available,A simple payoff allocation mechanism achieves efficiency and stability in renewable energy aggregation,6e22313d864590a3e9eae891991c37db,https://ieeexplore.ieee.org/document/8309116/
9581,"Aggregating statistically diverse renewable power producers (RPPs) is an effective way to reduce the uncertainty of the RPPs. The key question is how to design a mechanism to aggregate the RPPs and distribute the payoffs among them. In this paper, a simple payoff allocation mechanism (PAM) is shown to achieve a wide range of desired properties. In particular, social efficiency, stability (in the core), and no collusion are achieved at the unique pure Nash Equilibrium (NE) of the non-cooperative game of RPPs induced by the PAM. As a result, an ideal “Price of Anarchy” of one is achieved. Moreover, a closed form expression of the unique pure NE is derived. A simulation study is conducted using the data of ten wind power producers in the PJM interconnection.",hossein khazaei,Energy Aggregation,2017.0,10.1109/GlobalSIP.2017.8309116,2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP),Khazaei2017,False,,IEEE,Not available,A simple payoff allocation mechanism achieves efficiency and stability in renewable energy aggregation,6e22313d864590a3e9eae891991c37db,https://ieeexplore.ieee.org/document/8309116/
9582,"Aggregating statistically diverse renewable power producers (RPPs) is an effective way to reduce the uncertainty of the RPPs. The key question is how to design a mechanism to aggregate the RPPs and distribute the payoffs among them. In this paper, a simple payoff allocation mechanism (PAM) is shown to achieve a wide range of desired properties. In particular, social efficiency, stability (in the core), and no collusion are achieved at the unique pure Nash Equilibrium (NE) of the non-cooperative game of RPPs induced by the PAM. As a result, an ideal “Price of Anarchy” of one is achieved. Moreover, a closed form expression of the unique pure NE is derived. A simulation study is conducted using the data of ten wind power producers in the PJM interconnection.",yue zhao,Mechanism Design,2017.0,10.1109/GlobalSIP.2017.8309116,2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP),Khazaei2017,False,,IEEE,Not available,A simple payoff allocation mechanism achieves efficiency and stability in renewable energy aggregation,6e22313d864590a3e9eae891991c37db,https://ieeexplore.ieee.org/document/8309116/
9583,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
9584,"Aggregating statistically diverse renewable power producers (RPPs) is an effective way to reduce the uncertainty of the RPPs. The key question is how to design a mechanism to aggregate the RPPs and distribute the payoffs among them. In this paper, a simple payoff allocation mechanism (PAM) is shown to achieve a wide range of desired properties. In particular, social efficiency, stability (in the core), and no collusion are achieved at the unique pure Nash Equilibrium (NE) of the non-cooperative game of RPPs induced by the PAM. As a result, an ideal “Price of Anarchy” of one is achieved. Moreover, a closed form expression of the unique pure NE is derived. A simulation study is conducted using the data of ten wind power producers in the PJM interconnection.",yue zhao,Renewable Energy Integration,2017.0,10.1109/GlobalSIP.2017.8309116,2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP),Khazaei2017,False,,IEEE,Not available,A simple payoff allocation mechanism achieves efficiency and stability in renewable energy aggregation,6e22313d864590a3e9eae891991c37db,https://ieeexplore.ieee.org/document/8309116/
9585,"Aggregating statistically diverse renewable power producers (RPPs) is an effective way to reduce the uncertainty of the RPPs. The key question is how to design a mechanism to aggregate the RPPs and distribute the payoffs among them. In this paper, a simple payoff allocation mechanism (PAM) is shown to achieve a wide range of desired properties. In particular, social efficiency, stability (in the core), and no collusion are achieved at the unique pure Nash Equilibrium (NE) of the non-cooperative game of RPPs induced by the PAM. As a result, an ideal “Price of Anarchy” of one is achieved. Moreover, a closed form expression of the unique pure NE is derived. A simulation study is conducted using the data of ten wind power producers in the PJM interconnection.",yue zhao,Energy Aggregation,2017.0,10.1109/GlobalSIP.2017.8309116,2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP),Khazaei2017,False,,IEEE,Not available,A simple payoff allocation mechanism achieves efficiency and stability in renewable energy aggregation,6e22313d864590a3e9eae891991c37db,https://ieeexplore.ieee.org/document/8309116/
9586,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
9587,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
9588,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
9589,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
9590,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
9591,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
9592,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
9593,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
9594,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
9595,"We analyze a four node wireless network in which the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here we analyze the so called price of anarchy, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Our results show that there is a big possibility for improvement of the sum rate at the Nash equilibrium if the players are ldquoencouragedrdquo to cooperate or to choose a strategy (power policy) that is not selfish. The network operator, therefore, can design a mechanism in which both players maximize their own utilities but also the sum rate at the Nash equilibrium is much closer to the optimal sum rate.",ninoslav marina,Cooperative communications,2008.0,10.1109/EW.2008.4623877,2008 14th European Wireless Conference,Marina2008,False,,IEEE,Not available,Game theoretic analysis of a cooperative communication system,e5690a93b0e30f892b1cabc344ec64b3,https://ieeexplore.ieee.org/document/4623877/
9596,"We analyze a four node wireless network in which the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here we analyze the so called price of anarchy, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Our results show that there is a big possibility for improvement of the sum rate at the Nash equilibrium if the players are ldquoencouragedrdquo to cooperate or to choose a strategy (power policy) that is not selfish. The network operator, therefore, can design a mechanism in which both players maximize their own utilities but also the sum rate at the Nash equilibrium is much closer to the optimal sum rate.",ninoslav marina,relay channels,2008.0,10.1109/EW.2008.4623877,2008 14th European Wireless Conference,Marina2008,False,,IEEE,Not available,Game theoretic analysis of a cooperative communication system,e5690a93b0e30f892b1cabc344ec64b3,https://ieeexplore.ieee.org/document/4623877/
9597,"We analyze a four node wireless network in which the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here we analyze the so called price of anarchy, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Our results show that there is a big possibility for improvement of the sum rate at the Nash equilibrium if the players are ldquoencouragedrdquo to cooperate or to choose a strategy (power policy) that is not selfish. The network operator, therefore, can design a mechanism in which both players maximize their own utilities but also the sum rate at the Nash equilibrium is much closer to the optimal sum rate.",ninoslav marina,ad-hoc networks,2008.0,10.1109/EW.2008.4623877,2008 14th European Wireless Conference,Marina2008,False,,IEEE,Not available,Game theoretic analysis of a cooperative communication system,e5690a93b0e30f892b1cabc344ec64b3,https://ieeexplore.ieee.org/document/4623877/
9598,"We analyze a four node wireless network in which the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here we analyze the so called price of anarchy, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Our results show that there is a big possibility for improvement of the sum rate at the Nash equilibrium if the players are ldquoencouragedrdquo to cooperate or to choose a strategy (power policy) that is not selfish. The network operator, therefore, can design a mechanism in which both players maximize their own utilities but also the sum rate at the Nash equilibrium is much closer to the optimal sum rate.",ninoslav marina,game theory,2008.0,10.1109/EW.2008.4623877,2008 14th European Wireless Conference,Marina2008,False,,IEEE,Not available,Game theoretic analysis of a cooperative communication system,e5690a93b0e30f892b1cabc344ec64b3,https://ieeexplore.ieee.org/document/4623877/
9599,"We analyze a four node wireless network in which the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here we analyze the so called price of anarchy, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Our results show that there is a big possibility for improvement of the sum rate at the Nash equilibrium if the players are ldquoencouragedrdquo to cooperate or to choose a strategy (power policy) that is not selfish. The network operator, therefore, can design a mechanism in which both players maximize their own utilities but also the sum rate at the Nash equilibrium is much closer to the optimal sum rate.",ninoslav marina,Nash equilibrium,2008.0,10.1109/EW.2008.4623877,2008 14th European Wireless Conference,Marina2008,False,,IEEE,Not available,Game theoretic analysis of a cooperative communication system,e5690a93b0e30f892b1cabc344ec64b3,https://ieeexplore.ieee.org/document/4623877/
9600,"We analyze a four node wireless network in which the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here we analyze the so called price of anarchy, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Our results show that there is a big possibility for improvement of the sum rate at the Nash equilibrium if the players are ldquoencouragedrdquo to cooperate or to choose a strategy (power policy) that is not selfish. The network operator, therefore, can design a mechanism in which both players maximize their own utilities but also the sum rate at the Nash equilibrium is much closer to the optimal sum rate.",ninoslav marina,price of anarchy,2008.0,10.1109/EW.2008.4623877,2008 14th European Wireless Conference,Marina2008,False,,IEEE,Not available,Game theoretic analysis of a cooperative communication system,e5690a93b0e30f892b1cabc344ec64b3,https://ieeexplore.ieee.org/document/4623877/
9601,"In this paper, a class of non-cooperative games termed resource contention games is studied, modeled through multi-class Stochastic Flow Models (SFMs). We contrast the solutions between system-centric and user-centric optimization in this game setting, and illustrate the gap between the two solutions, which is commonly referred to as the “price of anarchy.”",christos cassandras,Games,2010.0,10.1109/EEEI.2010.5661913,2010 IEEE 26-th Convention of Electrical and Electronics Engineers in Israel,Cassandras2010,False,,IEEE,Not available,A Stochastic Hybrid Systems view at a class of non-cooperative games,270ecdf0f9a96ac464976a90b236c964,https://ieeexplore.ieee.org/document/5661913/
9602,"In this paper, a class of non-cooperative games termed resource contention games is studied, modeled through multi-class Stochastic Flow Models (SFMs). We contrast the solutions between system-centric and user-centric optimization in this game setting, and illustrate the gap between the two solutions, which is commonly referred to as the “price of anarchy.”",christos cassandras,Stochastic processes,2010.0,10.1109/EEEI.2010.5661913,2010 IEEE 26-th Convention of Electrical and Electronics Engineers in Israel,Cassandras2010,False,,IEEE,Not available,A Stochastic Hybrid Systems view at a class of non-cooperative games,270ecdf0f9a96ac464976a90b236c964,https://ieeexplore.ieee.org/document/5661913/
9603,"In this paper, a class of non-cooperative games termed resource contention games is studied, modeled through multi-class Stochastic Flow Models (SFMs). We contrast the solutions between system-centric and user-centric optimization in this game setting, and illustrate the gap between the two solutions, which is commonly referred to as the “price of anarchy.”",christos cassandras,Optimization,2010.0,10.1109/EEEI.2010.5661913,2010 IEEE 26-th Convention of Electrical and Electronics Engineers in Israel,Cassandras2010,False,,IEEE,Not available,A Stochastic Hybrid Systems view at a class of non-cooperative games,270ecdf0f9a96ac464976a90b236c964,https://ieeexplore.ieee.org/document/5661913/
9604,"In this paper, a class of non-cooperative games termed resource contention games is studied, modeled through multi-class Stochastic Flow Models (SFMs). We contrast the solutions between system-centric and user-centric optimization in this game setting, and illustrate the gap between the two solutions, which is commonly referred to as the “price of anarchy.”",christos cassandras,Analytical models,2010.0,10.1109/EEEI.2010.5661913,2010 IEEE 26-th Convention of Electrical and Electronics Engineers in Israel,Cassandras2010,False,,IEEE,Not available,A Stochastic Hybrid Systems view at a class of non-cooperative games,270ecdf0f9a96ac464976a90b236c964,https://ieeexplore.ieee.org/document/5661913/
9605,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
9606,"In this paper, a class of non-cooperative games termed resource contention games is studied, modeled through multi-class Stochastic Flow Models (SFMs). We contrast the solutions between system-centric and user-centric optimization in this game setting, and illustrate the gap between the two solutions, which is commonly referred to as the “price of anarchy.”",christos cassandras,Measurement,2010.0,10.1109/EEEI.2010.5661913,2010 IEEE 26-th Convention of Electrical and Electronics Engineers in Israel,Cassandras2010,False,,IEEE,Not available,A Stochastic Hybrid Systems view at a class of non-cooperative games,270ecdf0f9a96ac464976a90b236c964,https://ieeexplore.ieee.org/document/5661913/
9607,"In this paper, a class of non-cooperative games termed resource contention games is studied, modeled through multi-class Stochastic Flow Models (SFMs). We contrast the solutions between system-centric and user-centric optimization in this game setting, and illustrate the gap between the two solutions, which is commonly referred to as the “price of anarchy.”",christos cassandras,Lot sizing,2010.0,10.1109/EEEI.2010.5661913,2010 IEEE 26-th Convention of Electrical and Electronics Engineers in Israel,Cassandras2010,False,,IEEE,Not available,A Stochastic Hybrid Systems view at a class of non-cooperative games,270ecdf0f9a96ac464976a90b236c964,https://ieeexplore.ieee.org/document/5661913/
9608,"In this paper, a class of non-cooperative games termed resource contention games is studied, modeled through multi-class Stochastic Flow Models (SFMs). We contrast the solutions between system-centric and user-centric optimization in this game setting, and illustrate the gap between the two solutions, which is commonly referred to as the “price of anarchy.”",chen yao,Games,2010.0,10.1109/EEEI.2010.5661913,2010 IEEE 26-th Convention of Electrical and Electronics Engineers in Israel,Cassandras2010,False,,IEEE,Not available,A Stochastic Hybrid Systems view at a class of non-cooperative games,270ecdf0f9a96ac464976a90b236c964,https://ieeexplore.ieee.org/document/5661913/
9609,"In this paper, a class of non-cooperative games termed resource contention games is studied, modeled through multi-class Stochastic Flow Models (SFMs). We contrast the solutions between system-centric and user-centric optimization in this game setting, and illustrate the gap between the two solutions, which is commonly referred to as the “price of anarchy.”",chen yao,Stochastic processes,2010.0,10.1109/EEEI.2010.5661913,2010 IEEE 26-th Convention of Electrical and Electronics Engineers in Israel,Cassandras2010,False,,IEEE,Not available,A Stochastic Hybrid Systems view at a class of non-cooperative games,270ecdf0f9a96ac464976a90b236c964,https://ieeexplore.ieee.org/document/5661913/
9610,"In this paper, a class of non-cooperative games termed resource contention games is studied, modeled through multi-class Stochastic Flow Models (SFMs). We contrast the solutions between system-centric and user-centric optimization in this game setting, and illustrate the gap between the two solutions, which is commonly referred to as the “price of anarchy.”",chen yao,Optimization,2010.0,10.1109/EEEI.2010.5661913,2010 IEEE 26-th Convention of Electrical and Electronics Engineers in Israel,Cassandras2010,False,,IEEE,Not available,A Stochastic Hybrid Systems view at a class of non-cooperative games,270ecdf0f9a96ac464976a90b236c964,https://ieeexplore.ieee.org/document/5661913/
9611,"In this paper, a class of non-cooperative games termed resource contention games is studied, modeled through multi-class Stochastic Flow Models (SFMs). We contrast the solutions between system-centric and user-centric optimization in this game setting, and illustrate the gap between the two solutions, which is commonly referred to as the “price of anarchy.”",chen yao,Analytical models,2010.0,10.1109/EEEI.2010.5661913,2010 IEEE 26-th Convention of Electrical and Electronics Engineers in Israel,Cassandras2010,False,,IEEE,Not available,A Stochastic Hybrid Systems view at a class of non-cooperative games,270ecdf0f9a96ac464976a90b236c964,https://ieeexplore.ieee.org/document/5661913/
9612,"In this paper, a class of non-cooperative games termed resource contention games is studied, modeled through multi-class Stochastic Flow Models (SFMs). We contrast the solutions between system-centric and user-centric optimization in this game setting, and illustrate the gap between the two solutions, which is commonly referred to as the “price of anarchy.”",chen yao,Measurement,2010.0,10.1109/EEEI.2010.5661913,2010 IEEE 26-th Convention of Electrical and Electronics Engineers in Israel,Cassandras2010,False,,IEEE,Not available,A Stochastic Hybrid Systems view at a class of non-cooperative games,270ecdf0f9a96ac464976a90b236c964,https://ieeexplore.ieee.org/document/5661913/
9613,"In this paper, a class of non-cooperative games termed resource contention games is studied, modeled through multi-class Stochastic Flow Models (SFMs). We contrast the solutions between system-centric and user-centric optimization in this game setting, and illustrate the gap between the two solutions, which is commonly referred to as the “price of anarchy.”",chen yao,Lot sizing,2010.0,10.1109/EEEI.2010.5661913,2010 IEEE 26-th Convention of Electrical and Electronics Engineers in Israel,Cassandras2010,False,,IEEE,Not available,A Stochastic Hybrid Systems view at a class of non-cooperative games,270ecdf0f9a96ac464976a90b236c964,https://ieeexplore.ieee.org/document/5661913/
9614,"Mechanism design is studied for aggregating renewable power producers (RPPs) in a two-settlement power market. Employing an indirect mechanism design framework, a payoff allocation mechanism (PAM) is derived from the competitive equilibrium (CE) of a specially formulated market with transferrable payoff. Given the designed mechanism, the strategic behaviors of the participating RPPs entail a non-cooperative game: It is proven that a unique pure Nash equilibrium (NE) exists among the RPPs, for which a closed form expression is found. Moreover, it is proven that the designed mechanism achieves a number of key desirable properties at the NE: these include efficiency (i.e., an ideal ""Price of Anarchy"" of one), stability (i.e., ""in the core"" from a coalitional game theoretic perspective), and no collusion. In addition, it is shown that a set of desirable ""ex-post"" properties are also achieved by the designed mechanism. Extensive simulations are conducted and corroborate the theoretical results.",hossein khazaei,Cost allocation,,10.1109/TPWRS.2018.2875457,IEEE Transactions on Power Systems,KhazaeiNone,False,,IEEE,Not available,Indirect Mechanism Design for Efficient and Stable Renewable Energy Aggregation,bdb68bd15592a1e330709dfc43155670,
9615,"Mechanism design is studied for aggregating renewable power producers (RPPs) in a two-settlement power market. Employing an indirect mechanism design framework, a payoff allocation mechanism (PAM) is derived from the competitive equilibrium (CE) of a specially formulated market with transferrable payoff. Given the designed mechanism, the strategic behaviors of the participating RPPs entail a non-cooperative game: It is proven that a unique pure Nash equilibrium (NE) exists among the RPPs, for which a closed form expression is found. Moreover, it is proven that the designed mechanism achieves a number of key desirable properties at the NE: these include efficiency (i.e., an ideal ""Price of Anarchy"" of one), stability (i.e., ""in the core"" from a coalitional game theoretic perspective), and no collusion. In addition, it is shown that a set of desirable ""ex-post"" properties are also achieved by the designed mechanism. Extensive simulations are conducted and corroborate the theoretical results.",hossein khazaei,Nash equilibrium,,10.1109/TPWRS.2018.2875457,IEEE Transactions on Power Systems,KhazaeiNone,False,,IEEE,Not available,Indirect Mechanism Design for Efficient and Stable Renewable Energy Aggregation,bdb68bd15592a1e330709dfc43155670,
9616,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
9617,"Mechanism design is studied for aggregating renewable power producers (RPPs) in a two-settlement power market. Employing an indirect mechanism design framework, a payoff allocation mechanism (PAM) is derived from the competitive equilibrium (CE) of a specially formulated market with transferrable payoff. Given the designed mechanism, the strategic behaviors of the participating RPPs entail a non-cooperative game: It is proven that a unique pure Nash equilibrium (NE) exists among the RPPs, for which a closed form expression is found. Moreover, it is proven that the designed mechanism achieves a number of key desirable properties at the NE: these include efficiency (i.e., an ideal ""Price of Anarchy"" of one), stability (i.e., ""in the core"" from a coalitional game theoretic perspective), and no collusion. In addition, it is shown that a set of desirable ""ex-post"" properties are also achieved by the designed mechanism. Extensive simulations are conducted and corroborate the theoretical results.",hossein khazaei,mechanism design,,10.1109/TPWRS.2018.2875457,IEEE Transactions on Power Systems,KhazaeiNone,False,,IEEE,Not available,Indirect Mechanism Design for Efficient and Stable Renewable Energy Aggregation,bdb68bd15592a1e330709dfc43155670,
9618,"Mechanism design is studied for aggregating renewable power producers (RPPs) in a two-settlement power market. Employing an indirect mechanism design framework, a payoff allocation mechanism (PAM) is derived from the competitive equilibrium (CE) of a specially formulated market with transferrable payoff. Given the designed mechanism, the strategic behaviors of the participating RPPs entail a non-cooperative game: It is proven that a unique pure Nash equilibrium (NE) exists among the RPPs, for which a closed form expression is found. Moreover, it is proven that the designed mechanism achieves a number of key desirable properties at the NE: these include efficiency (i.e., an ideal ""Price of Anarchy"" of one), stability (i.e., ""in the core"" from a coalitional game theoretic perspective), and no collusion. In addition, it is shown that a set of desirable ""ex-post"" properties are also achieved by the designed mechanism. Extensive simulations are conducted and corroborate the theoretical results.",hossein khazaei,coalitional game,,10.1109/TPWRS.2018.2875457,IEEE Transactions on Power Systems,KhazaeiNone,False,,IEEE,Not available,Indirect Mechanism Design for Efficient and Stable Renewable Energy Aggregation,bdb68bd15592a1e330709dfc43155670,
9619,"Mechanism design is studied for aggregating renewable power producers (RPPs) in a two-settlement power market. Employing an indirect mechanism design framework, a payoff allocation mechanism (PAM) is derived from the competitive equilibrium (CE) of a specially formulated market with transferrable payoff. Given the designed mechanism, the strategic behaviors of the participating RPPs entail a non-cooperative game: It is proven that a unique pure Nash equilibrium (NE) exists among the RPPs, for which a closed form expression is found. Moreover, it is proven that the designed mechanism achieves a number of key desirable properties at the NE: these include efficiency (i.e., an ideal ""Price of Anarchy"" of one), stability (i.e., ""in the core"" from a coalitional game theoretic perspective), and no collusion. In addition, it is shown that a set of desirable ""ex-post"" properties are also achieved by the designed mechanism. Extensive simulations are conducted and corroborate the theoretical results.",hossein khazaei,renewable energy,,10.1109/TPWRS.2018.2875457,IEEE Transactions on Power Systems,KhazaeiNone,False,,IEEE,Not available,Indirect Mechanism Design for Efficient and Stable Renewable Energy Aggregation,bdb68bd15592a1e330709dfc43155670,
9620,"Mechanism design is studied for aggregating renewable power producers (RPPs) in a two-settlement power market. Employing an indirect mechanism design framework, a payoff allocation mechanism (PAM) is derived from the competitive equilibrium (CE) of a specially formulated market with transferrable payoff. Given the designed mechanism, the strategic behaviors of the participating RPPs entail a non-cooperative game: It is proven that a unique pure Nash equilibrium (NE) exists among the RPPs, for which a closed form expression is found. Moreover, it is proven that the designed mechanism achieves a number of key desirable properties at the NE: these include efficiency (i.e., an ideal ""Price of Anarchy"" of one), stability (i.e., ""in the core"" from a coalitional game theoretic perspective), and no collusion. In addition, it is shown that a set of desirable ""ex-post"" properties are also achieved by the designed mechanism. Extensive simulations are conducted and corroborate the theoretical results.",hossein khazaei,electricity market,,10.1109/TPWRS.2018.2875457,IEEE Transactions on Power Systems,KhazaeiNone,False,,IEEE,Not available,Indirect Mechanism Design for Efficient and Stable Renewable Energy Aggregation,bdb68bd15592a1e330709dfc43155670,
9621,"Mechanism design is studied for aggregating renewable power producers (RPPs) in a two-settlement power market. Employing an indirect mechanism design framework, a payoff allocation mechanism (PAM) is derived from the competitive equilibrium (CE) of a specially formulated market with transferrable payoff. Given the designed mechanism, the strategic behaviors of the participating RPPs entail a non-cooperative game: It is proven that a unique pure Nash equilibrium (NE) exists among the RPPs, for which a closed form expression is found. Moreover, it is proven that the designed mechanism achieves a number of key desirable properties at the NE: these include efficiency (i.e., an ideal ""Price of Anarchy"" of one), stability (i.e., ""in the core"" from a coalitional game theoretic perspective), and no collusion. In addition, it is shown that a set of desirable ""ex-post"" properties are also achieved by the designed mechanism. Extensive simulations are conducted and corroborate the theoretical results.",yue zhao,Cost allocation,,10.1109/TPWRS.2018.2875457,IEEE Transactions on Power Systems,KhazaeiNone,False,,IEEE,Not available,Indirect Mechanism Design for Efficient and Stable Renewable Energy Aggregation,bdb68bd15592a1e330709dfc43155670,
9622,"Mechanism design is studied for aggregating renewable power producers (RPPs) in a two-settlement power market. Employing an indirect mechanism design framework, a payoff allocation mechanism (PAM) is derived from the competitive equilibrium (CE) of a specially formulated market with transferrable payoff. Given the designed mechanism, the strategic behaviors of the participating RPPs entail a non-cooperative game: It is proven that a unique pure Nash equilibrium (NE) exists among the RPPs, for which a closed form expression is found. Moreover, it is proven that the designed mechanism achieves a number of key desirable properties at the NE: these include efficiency (i.e., an ideal ""Price of Anarchy"" of one), stability (i.e., ""in the core"" from a coalitional game theoretic perspective), and no collusion. In addition, it is shown that a set of desirable ""ex-post"" properties are also achieved by the designed mechanism. Extensive simulations are conducted and corroborate the theoretical results.",yue zhao,Nash equilibrium,,10.1109/TPWRS.2018.2875457,IEEE Transactions on Power Systems,KhazaeiNone,False,,IEEE,Not available,Indirect Mechanism Design for Efficient and Stable Renewable Energy Aggregation,bdb68bd15592a1e330709dfc43155670,
9623,"Mechanism design is studied for aggregating renewable power producers (RPPs) in a two-settlement power market. Employing an indirect mechanism design framework, a payoff allocation mechanism (PAM) is derived from the competitive equilibrium (CE) of a specially formulated market with transferrable payoff. Given the designed mechanism, the strategic behaviors of the participating RPPs entail a non-cooperative game: It is proven that a unique pure Nash equilibrium (NE) exists among the RPPs, for which a closed form expression is found. Moreover, it is proven that the designed mechanism achieves a number of key desirable properties at the NE: these include efficiency (i.e., an ideal ""Price of Anarchy"" of one), stability (i.e., ""in the core"" from a coalitional game theoretic perspective), and no collusion. In addition, it is shown that a set of desirable ""ex-post"" properties are also achieved by the designed mechanism. Extensive simulations are conducted and corroborate the theoretical results.",yue zhao,mechanism design,,10.1109/TPWRS.2018.2875457,IEEE Transactions on Power Systems,KhazaeiNone,False,,IEEE,Not available,Indirect Mechanism Design for Efficient and Stable Renewable Energy Aggregation,bdb68bd15592a1e330709dfc43155670,
9624,"Mechanism design is studied for aggregating renewable power producers (RPPs) in a two-settlement power market. Employing an indirect mechanism design framework, a payoff allocation mechanism (PAM) is derived from the competitive equilibrium (CE) of a specially formulated market with transferrable payoff. Given the designed mechanism, the strategic behaviors of the participating RPPs entail a non-cooperative game: It is proven that a unique pure Nash equilibrium (NE) exists among the RPPs, for which a closed form expression is found. Moreover, it is proven that the designed mechanism achieves a number of key desirable properties at the NE: these include efficiency (i.e., an ideal ""Price of Anarchy"" of one), stability (i.e., ""in the core"" from a coalitional game theoretic perspective), and no collusion. In addition, it is shown that a set of desirable ""ex-post"" properties are also achieved by the designed mechanism. Extensive simulations are conducted and corroborate the theoretical results.",yue zhao,coalitional game,,10.1109/TPWRS.2018.2875457,IEEE Transactions on Power Systems,KhazaeiNone,False,,IEEE,Not available,Indirect Mechanism Design for Efficient and Stable Renewable Energy Aggregation,bdb68bd15592a1e330709dfc43155670,
9625,"Mechanism design is studied for aggregating renewable power producers (RPPs) in a two-settlement power market. Employing an indirect mechanism design framework, a payoff allocation mechanism (PAM) is derived from the competitive equilibrium (CE) of a specially formulated market with transferrable payoff. Given the designed mechanism, the strategic behaviors of the participating RPPs entail a non-cooperative game: It is proven that a unique pure Nash equilibrium (NE) exists among the RPPs, for which a closed form expression is found. Moreover, it is proven that the designed mechanism achieves a number of key desirable properties at the NE: these include efficiency (i.e., an ideal ""Price of Anarchy"" of one), stability (i.e., ""in the core"" from a coalitional game theoretic perspective), and no collusion. In addition, it is shown that a set of desirable ""ex-post"" properties are also achieved by the designed mechanism. Extensive simulations are conducted and corroborate the theoretical results.",yue zhao,renewable energy,,10.1109/TPWRS.2018.2875457,IEEE Transactions on Power Systems,KhazaeiNone,False,,IEEE,Not available,Indirect Mechanism Design for Efficient and Stable Renewable Energy Aggregation,bdb68bd15592a1e330709dfc43155670,
9626,"Mechanism design is studied for aggregating renewable power producers (RPPs) in a two-settlement power market. Employing an indirect mechanism design framework, a payoff allocation mechanism (PAM) is derived from the competitive equilibrium (CE) of a specially formulated market with transferrable payoff. Given the designed mechanism, the strategic behaviors of the participating RPPs entail a non-cooperative game: It is proven that a unique pure Nash equilibrium (NE) exists among the RPPs, for which a closed form expression is found. Moreover, it is proven that the designed mechanism achieves a number of key desirable properties at the NE: these include efficiency (i.e., an ideal ""Price of Anarchy"" of one), stability (i.e., ""in the core"" from a coalitional game theoretic perspective), and no collusion. In addition, it is shown that a set of desirable ""ex-post"" properties are also achieved by the designed mechanism. Extensive simulations are conducted and corroborate the theoretical results.",yue zhao,electricity market,,10.1109/TPWRS.2018.2875457,IEEE Transactions on Power Systems,KhazaeiNone,False,,IEEE,Not available,Indirect Mechanism Design for Efficient and Stable Renewable Energy Aggregation,bdb68bd15592a1e330709dfc43155670,
9627,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
9628,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",s. etesami,Games,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
9629,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",s. etesami,Batteries,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
9630,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",s. etesami,Charging stations,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
9631,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",s. etesami,Routing,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
9632,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",s. etesami,Smart grids,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
9633,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",s. etesami,Pricing,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
9634,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",s. etesami,Roads,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
9635,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",walid saad,Games,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
9636,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",walid saad,Batteries,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
9637,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",walid saad,Charging stations,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
9638,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
9639,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",walid saad,Routing,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
9640,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",walid saad,Smart grids,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
9641,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",walid saad,Pricing,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
9642,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",walid saad,Roads,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
9643,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",narayan mandayam,Games,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
9644,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",narayan mandayam,Batteries,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
9645,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",narayan mandayam,Charging stations,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
9646,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",narayan mandayam,Routing,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
9647,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",narayan mandayam,Smart grids,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
9648,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",narayan mandayam,Pricing,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
9649,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
9650,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",narayan mandayam,Roads,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
9651,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",h. poor,Games,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
9652,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",h. poor,Batteries,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
9653,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",h. poor,Charging stations,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
9654,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",h. poor,Routing,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
9655,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",h. poor,Smart grids,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
9656,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",h. poor,Pricing,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
9657,"Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel game-theoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a repeated noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the “variance” of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.",h. poor,Roads,2017.0,10.1109/CDC.2017.8264036,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Etesami2017,False,,IEEE,Not available,Smart routing in smart grids,0ac972480c0c2fa04516672f1f09342c,https://ieeexplore.ieee.org/document/8264036/
9658,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9659,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9660,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
9661,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
9662,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9663,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9664,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9665,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9666,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9667,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9668,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9669,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9670,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9671,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9672,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
9673,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9674,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9675,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9676,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9677,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9678,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9679,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9680,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
9681,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",sangwoo moon,User association,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
9682,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",sangwoo moon,population game,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
9683,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
9684,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",sangwoo moon,evolutionary dynamics,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
9685,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",sangwoo moon,load balancing,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
9686,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",sangwoo moon,cellular networks,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
9687,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",sangwoo moon,User association,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
9688,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",sangwoo moon,population game,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
9689,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",sangwoo moon,evolutionary dynamics,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
9690,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",sangwoo moon,load balancing,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
9691,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",sangwoo moon,cellular networks,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
9692,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",hongseok kim,User association,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
9693,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",hongseok kim,population game,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
9694,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
9695,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",hongseok kim,evolutionary dynamics,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
9696,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",hongseok kim,load balancing,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
9697,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",hongseok kim,cellular networks,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
9698,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",hongseok kim,User association,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
9699,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",hongseok kim,population game,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
9700,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",hongseok kim,evolutionary dynamics,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
9701,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",hongseok kim,load balancing,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
9702,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",hongseok kim,cellular networks,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
9703,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",yung yi,User association,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
9704,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",yung yi,population game,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
9705,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
9706,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",yung yi,evolutionary dynamics,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
9707,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",yung yi,load balancing,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
9708,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",yung yi,cellular networks,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
9709,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",yung yi,User association,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
9710,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",yung yi,population game,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
9711,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",yung yi,evolutionary dynamics,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
9712,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",yung yi,load balancing,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
9713,"In this paper, we address the problem of associating mobile stations (MSs) with base stations (BSs) in an energy-efficient manner. We take a population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity. From our game-theoretical analysis, we prove that a simple power-dependent pricing by operators leads a Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., no price-of-anarchy). We study three evolution dynamics of associating MSs, each expressed as a differential equation, all of which provably and/or numerically converge to the Nash equilibrium. Based on several considerations regarding implementation of association algorithms in practice, we found that asynchronicity and fast load tracking are the key components to practical algorithms. Motivated by this, we propose a practical energy-efficient user association mechanism, named BRUTE. To evaluate the performance of BRUTE, we implement a cellular network simulator using an event-driven simulator, SimPy, and perform extensive simulations under various scenarios including a real BS topology in U.K. Our simulation results show that BRUTE outperforms other conventional user association techniques.",yung yi,cellular networks,2016.0,10.1109/TWC.2015.2477297,IEEE Transactions on Wireless Communications,Moon2016,False,,IEEE,Not available,BRUTE: Energy-Efficient User Association in Cellular Networks From Population Game Perspective,2e4b7bff39463368edbeb27d90b34c81,https://ieeexplore.ieee.org/document/7244342/
9714,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",r. johari,Resource management,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
9715,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",r. johari,Computer aided software engineering,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
9716,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
9717,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",r. johari,Aggregates,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
9718,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",r. johari,Internet,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
9719,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",r. johari,Environmental economics,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
9720,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",r. johari,Nash equilibrium,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
9721,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",r. johari,Peer to peer computing,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
9722,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",r. johari,Computer science,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
9723,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",r. johari,Routing,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
9724,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",r. johari,Telecommunication traffic,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
9725,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",j.n. tsitsiklis,Resource management,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
9726,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",j.n. tsitsiklis,Computer aided software engineering,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
9727,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
9728,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",j.n. tsitsiklis,Aggregates,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
9729,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",j.n. tsitsiklis,Internet,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
9730,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",j.n. tsitsiklis,Environmental economics,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
9731,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",j.n. tsitsiklis,Nash equilibrium,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
9732,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",j.n. tsitsiklis,Peer to peer computing,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
9733,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",j.n. tsitsiklis,Computer science,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
9734,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",j.n. tsitsiklis,Routing,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
9735,"We explore the properties of a congestion game where users of a congested resource anticipate the effect of their actions on the price of the resource. When users are sharing a single resource, we show existence and uniqueness of the Nash equilibrium, and establish that the aggregate utility received by the users is at least 3/4 of the maximum possible aggregate utility. These results form part of a growing literature on the ""price of anarchy,"" i.e., the extent to which selfish behavior affects system efficiency.",j.n. tsitsiklis,Telecommunication traffic,2003.0,10.1109/CDC.2003.1272929,42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475),Johari2003,False,,IEEE,Not available,Network resource allocation and a congestion game: the single link case,6811036d17f2e69a8fdc63367cbcf491,https://ieeexplore.ieee.org/document/1272929/
9736,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",elliot anshelevich,Peer to peer computing,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
9737,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",elliot anshelevich,Contracts,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
9738,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
9739,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",elliot anshelevich,IP networks,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
9740,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",elliot anshelevich,Internet,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
9741,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",elliot anshelevich,Stability,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
9742,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",elliot anshelevich,Game theory,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
9743,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",elliot anshelevich,Heart,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
9744,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",elliot anshelevich,Network topology,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
9745,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",elliot anshelevich,Predictive models,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
9746,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",elliot anshelevich,Traffic control,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
9747,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",bruce shepherd,Peer to peer computing,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
9748,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",bruce shepherd,Contracts,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
9749,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
9750,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",bruce shepherd,IP networks,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
9751,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",bruce shepherd,Internet,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
9752,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",bruce shepherd,Stability,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
9753,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",bruce shepherd,Game theory,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
9754,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",bruce shepherd,Heart,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
9755,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",bruce shepherd,Network topology,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
9756,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",bruce shepherd,Predictive models,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
9757,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",bruce shepherd,Traffic control,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
9758,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",gordon wilfong,Peer to peer computing,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
9759,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",gordon wilfong,Contracts,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
9760,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
9761,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",gordon wilfong,IP networks,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
9762,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",gordon wilfong,Internet,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
9763,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",gordon wilfong,Stability,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
9764,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",gordon wilfong,Game theory,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
9765,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",gordon wilfong,Heart,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
9766,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",gordon wilfong,Network topology,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
9767,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",gordon wilfong,Predictive models,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
9768,"We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., autonomous systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model has predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives; solutions created by an ""altruistic entity"" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques",gordon wilfong,Traffic control,2006.0,10.1109/FOCS.2006.72,2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06),Anshelevich2006,False,,IEEE,Not available,Strategic Network Formation through Peering and Service Agreements,811068c0d6b4aaa96ff01cf1e9d83100,https://ieeexplore.ieee.org/document/4031345/
9769,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",ilaria malanchini,Games,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
9770,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",ilaria malanchini,Interference,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
9771,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
9772,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
9773,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
9774,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",ilaria malanchini,Resource management,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
9775,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",ilaria malanchini,Nash equilibrium,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
9776,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",ilaria malanchini,Transmitters,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
9777,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",ilaria malanchini,Noise,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
9778,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",ilaria malanchini,Analytical models,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
9779,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",steven weber,Games,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
9780,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",steven weber,Interference,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
9781,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",steven weber,Resource management,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
9782,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",steven weber,Nash equilibrium,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
9783,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",steven weber,Transmitters,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
9784,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
9785,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",steven weber,Noise,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
9786,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",steven weber,Analytical models,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
9787,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",matteo cesana,Games,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
9788,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",matteo cesana,Interference,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
9789,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",matteo cesana,Resource management,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
9790,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",matteo cesana,Nash equilibrium,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
9791,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",matteo cesana,Transmitters,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
9792,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",matteo cesana,Noise,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
9793,"The spectrum sharing game and the quality of its equilibria have been widely studied in a variety of contexts. In this paper we consider two pairs of communicating users that share two bands of spectrum. Through the analysis of the Nash equilibria, we provide the conditions, with respect to the normalized signal and interference strengths, for the set of equilibria power allocations to coincide with the set of optimal allocations. In contrast, when these sets do not coincide, we characterize the quality of the equilibria using the price of stability and the price of anarchy measures. In the more general case of N pairs of transmit receive pairs in an ad hoc network, we provide simulation results of a simple distributed player power allocation update heuristic that improves the sum rate utility above that achieved by the equilibrium of splitting the power evenly between the two bands.",matteo cesana,Analytical models,2010.0,10.1109/ALLERTON.2010.5706987,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Malanchini2010,False,,IEEE,Not available,Nash equilibria for spectrum sharing of two bands among two players,d60d91a8c1d50cf51aef6a2500afe149,https://ieeexplore.ieee.org/document/5706987/
9794,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of a game arising in a two-user decentralized interference channel (DIC) with noisy feedback in which transmit-receiver pairs seek an optimal individual transmission rate are fully characterized. In particular, it is shown that in all interference regimes, there always exists at least one Pareto optimal Nash equilibrium (NE). More specifically, there always exists an NE at which players maximize the network sum-rate and thus, the PoS of the corresponding game is always equal to one. A second result provides closed form expressions for the PoA, which allows the full characterization of the reduction of the sum rate due to the anarchic behavior of all transmitter-receiver pairs.",samir perlaza,Games,2014.0,10.1109/ISCCSP.2014.6877900,"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)",Perlaza2014,False,,IEEE,Not available,Decentralized interference channels with noisy feedback possess Pareto optimal Nash equilibria,68af928085080cc846bbbcd98fcf8b9d,https://ieeexplore.ieee.org/document/6877900/
9795,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
9796,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of a game arising in a two-user decentralized interference channel (DIC) with noisy feedback in which transmit-receiver pairs seek an optimal individual transmission rate are fully characterized. In particular, it is shown that in all interference regimes, there always exists at least one Pareto optimal Nash equilibrium (NE). More specifically, there always exists an NE at which players maximize the network sum-rate and thus, the PoS of the corresponding game is always equal to one. A second result provides closed form expressions for the PoA, which allows the full characterization of the reduction of the sum rate due to the anarchic behavior of all transmitter-receiver pairs.",samir perlaza,Noise measurement,2014.0,10.1109/ISCCSP.2014.6877900,"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)",Perlaza2014,False,,IEEE,Not available,Decentralized interference channels with noisy feedback possess Pareto optimal Nash equilibria,68af928085080cc846bbbcd98fcf8b9d,https://ieeexplore.ieee.org/document/6877900/
9797,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of a game arising in a two-user decentralized interference channel (DIC) with noisy feedback in which transmit-receiver pairs seek an optimal individual transmission rate are fully characterized. In particular, it is shown that in all interference regimes, there always exists at least one Pareto optimal Nash equilibrium (NE). More specifically, there always exists an NE at which players maximize the network sum-rate and thus, the PoS of the corresponding game is always equal to one. A second result provides closed form expressions for the PoA, which allows the full characterization of the reduction of the sum rate due to the anarchic behavior of all transmitter-receiver pairs.",samir perlaza,Transmitters,2014.0,10.1109/ISCCSP.2014.6877900,"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)",Perlaza2014,False,,IEEE,Not available,Decentralized interference channels with noisy feedback possess Pareto optimal Nash equilibria,68af928085080cc846bbbcd98fcf8b9d,https://ieeexplore.ieee.org/document/6877900/
9798,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of a game arising in a two-user decentralized interference channel (DIC) with noisy feedback in which transmit-receiver pairs seek an optimal individual transmission rate are fully characterized. In particular, it is shown that in all interference regimes, there always exists at least one Pareto optimal Nash equilibrium (NE). More specifically, there always exists an NE at which players maximize the network sum-rate and thus, the PoS of the corresponding game is always equal to one. A second result provides closed form expressions for the PoA, which allows the full characterization of the reduction of the sum rate due to the anarchic behavior of all transmitter-receiver pairs.",samir perlaza,Receivers,2014.0,10.1109/ISCCSP.2014.6877900,"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)",Perlaza2014,False,,IEEE,Not available,Decentralized interference channels with noisy feedback possess Pareto optimal Nash equilibria,68af928085080cc846bbbcd98fcf8b9d,https://ieeexplore.ieee.org/document/6877900/
9799,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of a game arising in a two-user decentralized interference channel (DIC) with noisy feedback in which transmit-receiver pairs seek an optimal individual transmission rate are fully characterized. In particular, it is shown that in all interference regimes, there always exists at least one Pareto optimal Nash equilibrium (NE). More specifically, there always exists an NE at which players maximize the network sum-rate and thus, the PoS of the corresponding game is always equal to one. A second result provides closed form expressions for the PoA, which allows the full characterization of the reduction of the sum rate due to the anarchic behavior of all transmitter-receiver pairs.",samir perlaza,Interference channels,2014.0,10.1109/ISCCSP.2014.6877900,"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)",Perlaza2014,False,,IEEE,Not available,Decentralized interference channels with noisy feedback possess Pareto optimal Nash equilibria,68af928085080cc846bbbcd98fcf8b9d,https://ieeexplore.ieee.org/document/6877900/
9800,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of a game arising in a two-user decentralized interference channel (DIC) with noisy feedback in which transmit-receiver pairs seek an optimal individual transmission rate are fully characterized. In particular, it is shown that in all interference regimes, there always exists at least one Pareto optimal Nash equilibrium (NE). More specifically, there always exists an NE at which players maximize the network sum-rate and thus, the PoS of the corresponding game is always equal to one. A second result provides closed form expressions for the PoA, which allows the full characterization of the reduction of the sum rate due to the anarchic behavior of all transmitter-receiver pairs.",samir perlaza,Nash equilibrium,2014.0,10.1109/ISCCSP.2014.6877900,"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)",Perlaza2014,False,,IEEE,Not available,Decentralized interference channels with noisy feedback possess Pareto optimal Nash equilibria,68af928085080cc846bbbcd98fcf8b9d,https://ieeexplore.ieee.org/document/6877900/
9801,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of a game arising in a two-user decentralized interference channel (DIC) with noisy feedback in which transmit-receiver pairs seek an optimal individual transmission rate are fully characterized. In particular, it is shown that in all interference regimes, there always exists at least one Pareto optimal Nash equilibrium (NE). More specifically, there always exists an NE at which players maximize the network sum-rate and thus, the PoS of the corresponding game is always equal to one. A second result provides closed form expressions for the PoA, which allows the full characterization of the reduction of the sum rate due to the anarchic behavior of all transmitter-receiver pairs.",ravi tandon,Games,2014.0,10.1109/ISCCSP.2014.6877900,"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)",Perlaza2014,False,,IEEE,Not available,Decentralized interference channels with noisy feedback possess Pareto optimal Nash equilibria,68af928085080cc846bbbcd98fcf8b9d,https://ieeexplore.ieee.org/document/6877900/
9802,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of a game arising in a two-user decentralized interference channel (DIC) with noisy feedback in which transmit-receiver pairs seek an optimal individual transmission rate are fully characterized. In particular, it is shown that in all interference regimes, there always exists at least one Pareto optimal Nash equilibrium (NE). More specifically, there always exists an NE at which players maximize the network sum-rate and thus, the PoS of the corresponding game is always equal to one. A second result provides closed form expressions for the PoA, which allows the full characterization of the reduction of the sum rate due to the anarchic behavior of all transmitter-receiver pairs.",ravi tandon,Noise measurement,2014.0,10.1109/ISCCSP.2014.6877900,"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)",Perlaza2014,False,,IEEE,Not available,Decentralized interference channels with noisy feedback possess Pareto optimal Nash equilibria,68af928085080cc846bbbcd98fcf8b9d,https://ieeexplore.ieee.org/document/6877900/
9803,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of a game arising in a two-user decentralized interference channel (DIC) with noisy feedback in which transmit-receiver pairs seek an optimal individual transmission rate are fully characterized. In particular, it is shown that in all interference regimes, there always exists at least one Pareto optimal Nash equilibrium (NE). More specifically, there always exists an NE at which players maximize the network sum-rate and thus, the PoS of the corresponding game is always equal to one. A second result provides closed form expressions for the PoA, which allows the full characterization of the reduction of the sum rate due to the anarchic behavior of all transmitter-receiver pairs.",ravi tandon,Transmitters,2014.0,10.1109/ISCCSP.2014.6877900,"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)",Perlaza2014,False,,IEEE,Not available,Decentralized interference channels with noisy feedback possess Pareto optimal Nash equilibria,68af928085080cc846bbbcd98fcf8b9d,https://ieeexplore.ieee.org/document/6877900/
9804,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of a game arising in a two-user decentralized interference channel (DIC) with noisy feedback in which transmit-receiver pairs seek an optimal individual transmission rate are fully characterized. In particular, it is shown that in all interference regimes, there always exists at least one Pareto optimal Nash equilibrium (NE). More specifically, there always exists an NE at which players maximize the network sum-rate and thus, the PoS of the corresponding game is always equal to one. A second result provides closed form expressions for the PoA, which allows the full characterization of the reduction of the sum rate due to the anarchic behavior of all transmitter-receiver pairs.",ravi tandon,Receivers,2014.0,10.1109/ISCCSP.2014.6877900,"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)",Perlaza2014,False,,IEEE,Not available,Decentralized interference channels with noisy feedback possess Pareto optimal Nash equilibria,68af928085080cc846bbbcd98fcf8b9d,https://ieeexplore.ieee.org/document/6877900/
9805,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of a game arising in a two-user decentralized interference channel (DIC) with noisy feedback in which transmit-receiver pairs seek an optimal individual transmission rate are fully characterized. In particular, it is shown that in all interference regimes, there always exists at least one Pareto optimal Nash equilibrium (NE). More specifically, there always exists an NE at which players maximize the network sum-rate and thus, the PoS of the corresponding game is always equal to one. A second result provides closed form expressions for the PoA, which allows the full characterization of the reduction of the sum rate due to the anarchic behavior of all transmitter-receiver pairs.",ravi tandon,Interference channels,2014.0,10.1109/ISCCSP.2014.6877900,"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)",Perlaza2014,False,,IEEE,Not available,Decentralized interference channels with noisy feedback possess Pareto optimal Nash equilibria,68af928085080cc846bbbcd98fcf8b9d,https://ieeexplore.ieee.org/document/6877900/
9806,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
9807,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of a game arising in a two-user decentralized interference channel (DIC) with noisy feedback in which transmit-receiver pairs seek an optimal individual transmission rate are fully characterized. In particular, it is shown that in all interference regimes, there always exists at least one Pareto optimal Nash equilibrium (NE). More specifically, there always exists an NE at which players maximize the network sum-rate and thus, the PoS of the corresponding game is always equal to one. A second result provides closed form expressions for the PoA, which allows the full characterization of the reduction of the sum rate due to the anarchic behavior of all transmitter-receiver pairs.",ravi tandon,Nash equilibrium,2014.0,10.1109/ISCCSP.2014.6877900,"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)",Perlaza2014,False,,IEEE,Not available,Decentralized interference channels with noisy feedback possess Pareto optimal Nash equilibria,68af928085080cc846bbbcd98fcf8b9d,https://ieeexplore.ieee.org/document/6877900/
9808,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of a game arising in a two-user decentralized interference channel (DIC) with noisy feedback in which transmit-receiver pairs seek an optimal individual transmission rate are fully characterized. In particular, it is shown that in all interference regimes, there always exists at least one Pareto optimal Nash equilibrium (NE). More specifically, there always exists an NE at which players maximize the network sum-rate and thus, the PoS of the corresponding game is always equal to one. A second result provides closed form expressions for the PoA, which allows the full characterization of the reduction of the sum rate due to the anarchic behavior of all transmitter-receiver pairs.",h. poor,Games,2014.0,10.1109/ISCCSP.2014.6877900,"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)",Perlaza2014,False,,IEEE,Not available,Decentralized interference channels with noisy feedback possess Pareto optimal Nash equilibria,68af928085080cc846bbbcd98fcf8b9d,https://ieeexplore.ieee.org/document/6877900/
9809,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of a game arising in a two-user decentralized interference channel (DIC) with noisy feedback in which transmit-receiver pairs seek an optimal individual transmission rate are fully characterized. In particular, it is shown that in all interference regimes, there always exists at least one Pareto optimal Nash equilibrium (NE). More specifically, there always exists an NE at which players maximize the network sum-rate and thus, the PoS of the corresponding game is always equal to one. A second result provides closed form expressions for the PoA, which allows the full characterization of the reduction of the sum rate due to the anarchic behavior of all transmitter-receiver pairs.",h. poor,Noise measurement,2014.0,10.1109/ISCCSP.2014.6877900,"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)",Perlaza2014,False,,IEEE,Not available,Decentralized interference channels with noisy feedback possess Pareto optimal Nash equilibria,68af928085080cc846bbbcd98fcf8b9d,https://ieeexplore.ieee.org/document/6877900/
9810,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of a game arising in a two-user decentralized interference channel (DIC) with noisy feedback in which transmit-receiver pairs seek an optimal individual transmission rate are fully characterized. In particular, it is shown that in all interference regimes, there always exists at least one Pareto optimal Nash equilibrium (NE). More specifically, there always exists an NE at which players maximize the network sum-rate and thus, the PoS of the corresponding game is always equal to one. A second result provides closed form expressions for the PoA, which allows the full characterization of the reduction of the sum rate due to the anarchic behavior of all transmitter-receiver pairs.",h. poor,Transmitters,2014.0,10.1109/ISCCSP.2014.6877900,"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)",Perlaza2014,False,,IEEE,Not available,Decentralized interference channels with noisy feedback possess Pareto optimal Nash equilibria,68af928085080cc846bbbcd98fcf8b9d,https://ieeexplore.ieee.org/document/6877900/
9811,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of a game arising in a two-user decentralized interference channel (DIC) with noisy feedback in which transmit-receiver pairs seek an optimal individual transmission rate are fully characterized. In particular, it is shown that in all interference regimes, there always exists at least one Pareto optimal Nash equilibrium (NE). More specifically, there always exists an NE at which players maximize the network sum-rate and thus, the PoS of the corresponding game is always equal to one. A second result provides closed form expressions for the PoA, which allows the full characterization of the reduction of the sum rate due to the anarchic behavior of all transmitter-receiver pairs.",h. poor,Receivers,2014.0,10.1109/ISCCSP.2014.6877900,"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)",Perlaza2014,False,,IEEE,Not available,Decentralized interference channels with noisy feedback possess Pareto optimal Nash equilibria,68af928085080cc846bbbcd98fcf8b9d,https://ieeexplore.ieee.org/document/6877900/
9812,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of a game arising in a two-user decentralized interference channel (DIC) with noisy feedback in which transmit-receiver pairs seek an optimal individual transmission rate are fully characterized. In particular, it is shown that in all interference regimes, there always exists at least one Pareto optimal Nash equilibrium (NE). More specifically, there always exists an NE at which players maximize the network sum-rate and thus, the PoS of the corresponding game is always equal to one. A second result provides closed form expressions for the PoA, which allows the full characterization of the reduction of the sum rate due to the anarchic behavior of all transmitter-receiver pairs.",h. poor,Interference channels,2014.0,10.1109/ISCCSP.2014.6877900,"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)",Perlaza2014,False,,IEEE,Not available,Decentralized interference channels with noisy feedback possess Pareto optimal Nash equilibria,68af928085080cc846bbbcd98fcf8b9d,https://ieeexplore.ieee.org/document/6877900/
9813,"In this paper, the price of anarchy (PoA) and the price of stability (PoS) of a game arising in a two-user decentralized interference channel (DIC) with noisy feedback in which transmit-receiver pairs seek an optimal individual transmission rate are fully characterized. In particular, it is shown that in all interference regimes, there always exists at least one Pareto optimal Nash equilibrium (NE). More specifically, there always exists an NE at which players maximize the network sum-rate and thus, the PoS of the corresponding game is always equal to one. A second result provides closed form expressions for the PoA, which allows the full characterization of the reduction of the sum rate due to the anarchic behavior of all transmitter-receiver pairs.",h. poor,Nash equilibrium,2014.0,10.1109/ISCCSP.2014.6877900,"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)",Perlaza2014,False,,IEEE,Not available,Decentralized interference channels with noisy feedback possess Pareto optimal Nash equilibria,68af928085080cc846bbbcd98fcf8b9d,https://ieeexplore.ieee.org/document/6877900/
9814,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",nassim kaci,Quality of service,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
9815,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",nassim kaci,Telecommunications,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
9816,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",nassim kaci,Costs,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
9817,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
9818,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",nassim kaci,Finance,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
9819,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",nassim kaci,Loss measurement,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
9820,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",nassim kaci,Mobile computing,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
9821,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",nassim kaci,Wireless networks,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
9822,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",nassim kaci,Pricing,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
9823,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",nassim kaci,Wireless communication,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
9824,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",nassim kaci,Communications technology,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
9825,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",patrick maille,Quality of service,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
9826,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",patrick maille,Telecommunications,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
9827,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",patrick maille,Costs,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
9828,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
9829,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",patrick maille,Finance,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
9830,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",patrick maille,Loss measurement,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
9831,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",patrick maille,Mobile computing,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
9832,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",patrick maille,Wireless networks,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
9833,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",patrick maille,Pricing,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
9834,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",patrick maille,Wireless communication,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
9835,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",patrick maille,Communications technology,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
9836,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",jean-marie bonnin,Quality of service,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
9837,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",jean-marie bonnin,Telecommunications,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
9838,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",jean-marie bonnin,Costs,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
9839,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
9840,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",jean-marie bonnin,Finance,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
9841,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",jean-marie bonnin,Loss measurement,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
9842,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",jean-marie bonnin,Mobile computing,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
9843,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",jean-marie bonnin,Wireless networks,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
9844,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",jean-marie bonnin,Pricing,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
9845,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",jean-marie bonnin,Wireless communication,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
9846,"We consider a geographic area covered by two wireless networks. Assuming delay-sensitive users, we study the loss of efficiency of the user equilibrium (the Price of Anarchy) in terms of total delay, with M/M/l delay functions on each network. The user equilibrium is proved to be less efficient when the network is very heterogeneous, i.e. the two networks have different capacities. In order to elicit coordination among users, we suggest to use marginal cost pricing. We investigate the computation of the optimal taxes to use, and give several arguments in favor of the technical feasibility of such a scheme. Applying taxes therefore seems particularly well-suited to improve the overall performance of a network selection game with selfish users.",jean-marie bonnin,Communications technology,2009.0,10.1109/NGI.2009.5175776,2009 Next Generation Internet Networks,Kaci2009,False,,IEEE,Not available,Performance of Wireless Heterogeneous Networks with Always-best-connected Users,b03b6d9112d9ca37e455718ebe05c06e,https://ieeexplore.ieee.org/document/5175776/
9847,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",mathew goonewardena,Games,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
9848,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",mathew goonewardena,Heuristic algorithms,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
9849,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",mathew goonewardena,Color,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
9850,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
9851,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",mathew goonewardena,Routing,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
9852,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",mathew goonewardena,Wireless communication,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
9853,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",mathew goonewardena,Convergence,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
9854,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",mathew goonewardena,Cost function,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
9855,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",hoda akbari,Games,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
9856,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",hoda akbari,Heuristic algorithms,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
9857,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",hoda akbari,Color,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
9858,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",hoda akbari,Routing,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
9859,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",hoda akbari,Wireless communication,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
9860,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",hoda akbari,Convergence,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
9861,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
9862,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",hoda akbari,Cost function,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
9863,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",wessam ajib,Games,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
9864,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",wessam ajib,Heuristic algorithms,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
9865,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",wessam ajib,Color,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
9866,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",wessam ajib,Routing,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
9867,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",wessam ajib,Wireless communication,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
9868,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",wessam ajib,Convergence,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
9869,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",wessam ajib,Cost function,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
9870,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",halima elbiaze,Games,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
9871,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",halima elbiaze,Heuristic algorithms,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
9872,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
9873,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",halima elbiaze,Color,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
9874,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",halima elbiaze,Routing,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
9875,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",halima elbiaze,Wireless communication,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
9876,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",halima elbiaze,Convergence,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
9877,"Minimum-collisions assignment (MCA), in a wireless network, is the distribution of a finite resource set, such that the number of neighbor cells which receive common elements is minimized. In classical operator deployed networks, resources are assigned centrally. Heterogeneous networks contain user deployed cells, therefore centralized assignment is problematic. MCA includes orthogonal frequency bands, time slots, and physical cell identity (PCI) allocation. MCA is NP-complete, therefore a potential-game-theoretic model is proposed as a distributed solution. The players of the game are the cells, actions are the set of PCIs and the cost of a cell is the number of neighbor cells in collision. The price of anarchy and price of stability are derived. Moreover the paper adapts a randomized-distributed-synchronous-update algorithm, for the case, when the number of PCIs is higher than the maximum degree of the neighbor relations graph. It is proven that the algorithm converges to a optimal pure strategy Nash equilibrium in finite time and it is robust to node addition. Simulation results demonstrate that the algorithm is sub-linear in the size of the input graph, thus outperforms best response dynamics.",halima elbiaze,Cost function,2014.0,10.1109/GLOCOM.2014.7037544,2014 IEEE Global Communications Conference,Goonewardena2014,False,,IEEE,Not available,On minimum-collisions assignment in heterogeneous self-organizing networks,227cb69670cfe05689d3285258c2d66e,https://ieeexplore.ieee.org/document/7037544/
9878,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, subject to transmission and generator capacity constraints. Under the assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying game, and derive a tight bound on its price of anarchy. Under the more restrictive setting of a two-node power network, we present a detailed comparison of market outcomes predicted by the simultaneous-move formulation of the game against those predicted by the more plausible sequential-move formulation, where the ISO observes the generators' strategy profile prior to determining their production quantities.",weixuan lin,Production,2016.0,10.1109/CDC.2016.7798485,2016 IEEE 55th Conference on Decision and Control (CDC),Lin2016,False,,IEEE,Not available,Parameterized supply function equilibrium in power networks,acdbefa6303f83fc1143bded80b0ea96,https://ieeexplore.ieee.org/document/7798485/
9879,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, subject to transmission and generator capacity constraints. Under the assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying game, and derive a tight bound on its price of anarchy. Under the more restrictive setting of a two-node power network, we present a detailed comparison of market outcomes predicted by the simultaneous-move formulation of the game against those predicted by the more plausible sequential-move formulation, where the ISO observes the generators' strategy profile prior to determining their production quantities.",weixuan lin,ISO,2016.0,10.1109/CDC.2016.7798485,2016 IEEE 55th Conference on Decision and Control (CDC),Lin2016,False,,IEEE,Not available,Parameterized supply function equilibrium in power networks,acdbefa6303f83fc1143bded80b0ea96,https://ieeexplore.ieee.org/document/7798485/
9880,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, subject to transmission and generator capacity constraints. Under the assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying game, and derive a tight bound on its price of anarchy. Under the more restrictive setting of a two-node power network, we present a detailed comparison of market outcomes predicted by the simultaneous-move formulation of the game against those predicted by the more plausible sequential-move formulation, where the ISO observes the generators' strategy profile prior to determining their production quantities.",weixuan lin,Games,2016.0,10.1109/CDC.2016.7798485,2016 IEEE 55th Conference on Decision and Control (CDC),Lin2016,False,,IEEE,Not available,Parameterized supply function equilibrium in power networks,acdbefa6303f83fc1143bded80b0ea96,https://ieeexplore.ieee.org/document/7798485/
9881,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, subject to transmission and generator capacity constraints. Under the assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying game, and derive a tight bound on its price of anarchy. Under the more restrictive setting of a two-node power network, we present a detailed comparison of market outcomes predicted by the simultaneous-move formulation of the game against those predicted by the more plausible sequential-move formulation, where the ISO observes the generators' strategy profile prior to determining their production quantities.",weixuan lin,Nickel,2016.0,10.1109/CDC.2016.7798485,2016 IEEE 55th Conference on Decision and Control (CDC),Lin2016,False,,IEEE,Not available,Parameterized supply function equilibrium in power networks,acdbefa6303f83fc1143bded80b0ea96,https://ieeexplore.ieee.org/document/7798485/
9882,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, subject to transmission and generator capacity constraints. Under the assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying game, and derive a tight bound on its price of anarchy. Under the more restrictive setting of a two-node power network, we present a detailed comparison of market outcomes predicted by the simultaneous-move formulation of the game against those predicted by the more plausible sequential-move formulation, where the ISO observes the generators' strategy profile prior to determining their production quantities.",weixuan lin,Generators,2016.0,10.1109/CDC.2016.7798485,2016 IEEE 55th Conference on Decision and Control (CDC),Lin2016,False,,IEEE,Not available,Parameterized supply function equilibrium in power networks,acdbefa6303f83fc1143bded80b0ea96,https://ieeexplore.ieee.org/document/7798485/
9883,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
9884,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
9885,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, subject to transmission and generator capacity constraints. Under the assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying game, and derive a tight bound on its price of anarchy. Under the more restrictive setting of a two-node power network, we present a detailed comparison of market outcomes predicted by the simultaneous-move formulation of the game against those predicted by the more plausible sequential-move formulation, where the ISO observes the generators' strategy profile prior to determining their production quantities.",weixuan lin,Economics,2016.0,10.1109/CDC.2016.7798485,2016 IEEE 55th Conference on Decision and Control (CDC),Lin2016,False,,IEEE,Not available,Parameterized supply function equilibrium in power networks,acdbefa6303f83fc1143bded80b0ea96,https://ieeexplore.ieee.org/document/7798485/
9886,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, subject to transmission and generator capacity constraints. Under the assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying game, and derive a tight bound on its price of anarchy. Under the more restrictive setting of a two-node power network, we present a detailed comparison of market outcomes predicted by the simultaneous-move formulation of the game against those predicted by the more plausible sequential-move formulation, where the ISO observes the generators' strategy profile prior to determining their production quantities.",weixuan lin,Pricing,2016.0,10.1109/CDC.2016.7798485,2016 IEEE 55th Conference on Decision and Control (CDC),Lin2016,False,,IEEE,Not available,Parameterized supply function equilibrium in power networks,acdbefa6303f83fc1143bded80b0ea96,https://ieeexplore.ieee.org/document/7798485/
9887,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, subject to transmission and generator capacity constraints. Under the assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying game, and derive a tight bound on its price of anarchy. Under the more restrictive setting of a two-node power network, we present a detailed comparison of market outcomes predicted by the simultaneous-move formulation of the game against those predicted by the more plausible sequential-move formulation, where the ISO observes the generators' strategy profile prior to determining their production quantities.",eilyan bitar,Production,2016.0,10.1109/CDC.2016.7798485,2016 IEEE 55th Conference on Decision and Control (CDC),Lin2016,False,,IEEE,Not available,Parameterized supply function equilibrium in power networks,acdbefa6303f83fc1143bded80b0ea96,https://ieeexplore.ieee.org/document/7798485/
9888,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, subject to transmission and generator capacity constraints. Under the assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying game, and derive a tight bound on its price of anarchy. Under the more restrictive setting of a two-node power network, we present a detailed comparison of market outcomes predicted by the simultaneous-move formulation of the game against those predicted by the more plausible sequential-move formulation, where the ISO observes the generators' strategy profile prior to determining their production quantities.",eilyan bitar,ISO,2016.0,10.1109/CDC.2016.7798485,2016 IEEE 55th Conference on Decision and Control (CDC),Lin2016,False,,IEEE,Not available,Parameterized supply function equilibrium in power networks,acdbefa6303f83fc1143bded80b0ea96,https://ieeexplore.ieee.org/document/7798485/
9889,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, subject to transmission and generator capacity constraints. Under the assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying game, and derive a tight bound on its price of anarchy. Under the more restrictive setting of a two-node power network, we present a detailed comparison of market outcomes predicted by the simultaneous-move formulation of the game against those predicted by the more plausible sequential-move formulation, where the ISO observes the generators' strategy profile prior to determining their production quantities.",eilyan bitar,Games,2016.0,10.1109/CDC.2016.7798485,2016 IEEE 55th Conference on Decision and Control (CDC),Lin2016,False,,IEEE,Not available,Parameterized supply function equilibrium in power networks,acdbefa6303f83fc1143bded80b0ea96,https://ieeexplore.ieee.org/document/7798485/
9890,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, subject to transmission and generator capacity constraints. Under the assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying game, and derive a tight bound on its price of anarchy. Under the more restrictive setting of a two-node power network, we present a detailed comparison of market outcomes predicted by the simultaneous-move formulation of the game against those predicted by the more plausible sequential-move formulation, where the ISO observes the generators' strategy profile prior to determining their production quantities.",eilyan bitar,Nickel,2016.0,10.1109/CDC.2016.7798485,2016 IEEE 55th Conference on Decision and Control (CDC),Lin2016,False,,IEEE,Not available,Parameterized supply function equilibrium in power networks,acdbefa6303f83fc1143bded80b0ea96,https://ieeexplore.ieee.org/document/7798485/
9891,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, subject to transmission and generator capacity constraints. Under the assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying game, and derive a tight bound on its price of anarchy. Under the more restrictive setting of a two-node power network, we present a detailed comparison of market outcomes predicted by the simultaneous-move formulation of the game against those predicted by the more plausible sequential-move formulation, where the ISO observes the generators' strategy profile prior to determining their production quantities.",eilyan bitar,Generators,2016.0,10.1109/CDC.2016.7798485,2016 IEEE 55th Conference on Decision and Control (CDC),Lin2016,False,,IEEE,Not available,Parameterized supply function equilibrium in power networks,acdbefa6303f83fc1143bded80b0ea96,https://ieeexplore.ieee.org/document/7798485/
9892,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, subject to transmission and generator capacity constraints. Under the assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying game, and derive a tight bound on its price of anarchy. Under the more restrictive setting of a two-node power network, we present a detailed comparison of market outcomes predicted by the simultaneous-move formulation of the game against those predicted by the more plausible sequential-move formulation, where the ISO observes the generators' strategy profile prior to determining their production quantities.",eilyan bitar,Economics,2016.0,10.1109/CDC.2016.7798485,2016 IEEE 55th Conference on Decision and Control (CDC),Lin2016,False,,IEEE,Not available,Parameterized supply function equilibrium in power networks,acdbefa6303f83fc1143bded80b0ea96,https://ieeexplore.ieee.org/document/7798485/
9893,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, subject to transmission and generator capacity constraints. Under the assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying game, and derive a tight bound on its price of anarchy. Under the more restrictive setting of a two-node power network, we present a detailed comparison of market outcomes predicted by the simultaneous-move formulation of the game against those predicted by the more plausible sequential-move formulation, where the ISO observes the generators' strategy profile prior to determining their production quantities.",eilyan bitar,Pricing,2016.0,10.1109/CDC.2016.7798485,2016 IEEE 55th Conference on Decision and Control (CDC),Lin2016,False,,IEEE,Not available,Parameterized supply function equilibrium in power networks,acdbefa6303f83fc1143bded80b0ea96,https://ieeexplore.ieee.org/document/7798485/
9894,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",fan bai,Wireless networks,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
9895,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
9896,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",fan bai,Time division multiple access,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
9897,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",fan bai,Game theory,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
9898,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",fan bai,Frequency division multiaccess,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
9899,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",fan bai,Access protocols,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
9900,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",fan bai,Multiaccess communication,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
9901,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",fan bai,Radio transceivers,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
9902,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",fan bai,Media Access Protocol,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
9903,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",fan bai,Computer science,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
9904,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",fan bai,Helium,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
9905,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",xinhua he,Wireless networks,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
9906,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
9907,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",xinhua he,Time division multiple access,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
9908,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",xinhua he,Game theory,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
9909,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",xinhua he,Frequency division multiaccess,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
9910,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",xinhua he,Access protocols,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
9911,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",xinhua he,Multiaccess communication,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
9912,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",xinhua he,Radio transceivers,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
9913,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",xinhua he,Media Access Protocol,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
9914,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",xinhua he,Computer science,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
9915,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",xinhua he,Helium,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
9916,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",wenjun li,Wireless networks,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
9917,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
9918,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",wenjun li,Time division multiple access,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
9919,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",wenjun li,Game theory,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
9920,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",wenjun li,Frequency division multiaccess,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
9921,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",wenjun li,Access protocols,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
9922,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",wenjun li,Multiaccess communication,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
9923,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",wenjun li,Radio transceivers,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
9924,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",wenjun li,Media Access Protocol,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
9925,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",wenjun li,Computer science,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
9926,"Channel assignment has become a very important research area nowadays. In this paper, we study the existence of Nash Equilibria of selfish channel assignment in Aloha-type multi-channel multi-radio (MCMR) wireless networks. Our analysis shows that selfishness leads to balanced channel assignment in a single collision domain, while usually unbalanced solutions in multiple collision domains. We also investigate the price of anarchy and the price of randomness analytically. Efficient algorithms are proposed to perform channel assignment in MCMR wireless networks.",wenjun li,Helium,2010.0,10.1109/ICN.2010.11,2010 Ninth International Conference on Networks,Bai2010,False,,IEEE,Not available,Aloha-Type Random Access in Multi-channel Multi-radio Wireless Networks,b46576f5da29f9830d1ef9a52e0c7c0d,https://ieeexplore.ieee.org/document/5474020/
9927,"We combine queueing theory and game theory to evaluate the performance of a queueing system with multiple strategic candidate servers. The intent is to model a transmission system where packets can be sent via multiple options, each incurring a cost and controlled by a distributed management. Our purpose is to analyze the effects of the presence or the lack of both cooperation and communication between servers. The mathematical characterization of the uncertainty about the characteristics of the transmission alternatives available is captured through a Bayesian game formulation. In this setup, we compute both the Price of Anarchy, quantifying the inherent inefficiency arising from selfish management of each server, and the Price of Stability, which is the loss due to distributed system management, under different conditions of signaling exchange among the servers.",anna guglielmi,Queueing analysis,2015.0,10.1109/CAMAD.2015.7390486,2015 IEEE 20th International Workshop on Computer Aided Modelling and Design of Communication Links and Networks (CAMAD),Guglielmi2015,False,,IEEE,Not available,Bayesian game analysis of a queueing system with multiple candidate servers,603463c4e0930af0157ab3c10da065b2,https://ieeexplore.ieee.org/document/7390486/
9928,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
9929,"We combine queueing theory and game theory to evaluate the performance of a queueing system with multiple strategic candidate servers. The intent is to model a transmission system where packets can be sent via multiple options, each incurring a cost and controlled by a distributed management. Our purpose is to analyze the effects of the presence or the lack of both cooperation and communication between servers. The mathematical characterization of the uncertainty about the characteristics of the transmission alternatives available is captured through a Bayesian game formulation. In this setup, we compute both the Price of Anarchy, quantifying the inherent inefficiency arising from selfish management of each server, and the Price of Stability, which is the loss due to distributed system management, under different conditions of signaling exchange among the servers.",anna guglielmi,telecommunication networks,2015.0,10.1109/CAMAD.2015.7390486,2015 IEEE 20th International Workshop on Computer Aided Modelling and Design of Communication Links and Networks (CAMAD),Guglielmi2015,False,,IEEE,Not available,Bayesian game analysis of a queueing system with multiple candidate servers,603463c4e0930af0157ab3c10da065b2,https://ieeexplore.ieee.org/document/7390486/
9930,"We combine queueing theory and game theory to evaluate the performance of a queueing system with multiple strategic candidate servers. The intent is to model a transmission system where packets can be sent via multiple options, each incurring a cost and controlled by a distributed management. Our purpose is to analyze the effects of the presence or the lack of both cooperation and communication between servers. The mathematical characterization of the uncertainty about the characteristics of the transmission alternatives available is captured through a Bayesian game formulation. In this setup, we compute both the Price of Anarchy, quantifying the inherent inefficiency arising from selfish management of each server, and the Price of Stability, which is the loss due to distributed system management, under different conditions of signaling exchange among the servers.",anna guglielmi,game theory,2015.0,10.1109/CAMAD.2015.7390486,2015 IEEE 20th International Workshop on Computer Aided Modelling and Design of Communication Links and Networks (CAMAD),Guglielmi2015,False,,IEEE,Not available,Bayesian game analysis of a queueing system with multiple candidate servers,603463c4e0930af0157ab3c10da065b2,https://ieeexplore.ieee.org/document/7390486/
9931,"We combine queueing theory and game theory to evaluate the performance of a queueing system with multiple strategic candidate servers. The intent is to model a transmission system where packets can be sent via multiple options, each incurring a cost and controlled by a distributed management. Our purpose is to analyze the effects of the presence or the lack of both cooperation and communication between servers. The mathematical characterization of the uncertainty about the characteristics of the transmission alternatives available is captured through a Bayesian game formulation. In this setup, we compute both the Price of Anarchy, quantifying the inherent inefficiency arising from selfish management of each server, and the Price of Stability, which is the loss due to distributed system management, under different conditions of signaling exchange among the servers.",anna guglielmi,Bayesian games,2015.0,10.1109/CAMAD.2015.7390486,2015 IEEE 20th International Workshop on Computer Aided Modelling and Design of Communication Links and Networks (CAMAD),Guglielmi2015,False,,IEEE,Not available,Bayesian game analysis of a queueing system with multiple candidate servers,603463c4e0930af0157ab3c10da065b2,https://ieeexplore.ieee.org/document/7390486/
9932,"We combine queueing theory and game theory to evaluate the performance of a queueing system with multiple strategic candidate servers. The intent is to model a transmission system where packets can be sent via multiple options, each incurring a cost and controlled by a distributed management. Our purpose is to analyze the effects of the presence or the lack of both cooperation and communication between servers. The mathematical characterization of the uncertainty about the characteristics of the transmission alternatives available is captured through a Bayesian game formulation. In this setup, we compute both the Price of Anarchy, quantifying the inherent inefficiency arising from selfish management of each server, and the Price of Stability, which is the loss due to distributed system management, under different conditions of signaling exchange among the servers.",anna guglielmi,Price of Anarchy,2015.0,10.1109/CAMAD.2015.7390486,2015 IEEE 20th International Workshop on Computer Aided Modelling and Design of Communication Links and Networks (CAMAD),Guglielmi2015,False,,IEEE,Not available,Bayesian game analysis of a queueing system with multiple candidate servers,603463c4e0930af0157ab3c10da065b2,https://ieeexplore.ieee.org/document/7390486/
9933,"We combine queueing theory and game theory to evaluate the performance of a queueing system with multiple strategic candidate servers. The intent is to model a transmission system where packets can be sent via multiple options, each incurring a cost and controlled by a distributed management. Our purpose is to analyze the effects of the presence or the lack of both cooperation and communication between servers. The mathematical characterization of the uncertainty about the characteristics of the transmission alternatives available is captured through a Bayesian game formulation. In this setup, we compute both the Price of Anarchy, quantifying the inherent inefficiency arising from selfish management of each server, and the Price of Stability, which is the loss due to distributed system management, under different conditions of signaling exchange among the servers.",leonardo badia,Queueing analysis,2015.0,10.1109/CAMAD.2015.7390486,2015 IEEE 20th International Workshop on Computer Aided Modelling and Design of Communication Links and Networks (CAMAD),Guglielmi2015,False,,IEEE,Not available,Bayesian game analysis of a queueing system with multiple candidate servers,603463c4e0930af0157ab3c10da065b2,https://ieeexplore.ieee.org/document/7390486/
9934,"We combine queueing theory and game theory to evaluate the performance of a queueing system with multiple strategic candidate servers. The intent is to model a transmission system where packets can be sent via multiple options, each incurring a cost and controlled by a distributed management. Our purpose is to analyze the effects of the presence or the lack of both cooperation and communication between servers. The mathematical characterization of the uncertainty about the characteristics of the transmission alternatives available is captured through a Bayesian game formulation. In this setup, we compute both the Price of Anarchy, quantifying the inherent inefficiency arising from selfish management of each server, and the Price of Stability, which is the loss due to distributed system management, under different conditions of signaling exchange among the servers.",leonardo badia,telecommunication networks,2015.0,10.1109/CAMAD.2015.7390486,2015 IEEE 20th International Workshop on Computer Aided Modelling and Design of Communication Links and Networks (CAMAD),Guglielmi2015,False,,IEEE,Not available,Bayesian game analysis of a queueing system with multiple candidate servers,603463c4e0930af0157ab3c10da065b2,https://ieeexplore.ieee.org/document/7390486/
9935,"We combine queueing theory and game theory to evaluate the performance of a queueing system with multiple strategic candidate servers. The intent is to model a transmission system where packets can be sent via multiple options, each incurring a cost and controlled by a distributed management. Our purpose is to analyze the effects of the presence or the lack of both cooperation and communication between servers. The mathematical characterization of the uncertainty about the characteristics of the transmission alternatives available is captured through a Bayesian game formulation. In this setup, we compute both the Price of Anarchy, quantifying the inherent inefficiency arising from selfish management of each server, and the Price of Stability, which is the loss due to distributed system management, under different conditions of signaling exchange among the servers.",leonardo badia,game theory,2015.0,10.1109/CAMAD.2015.7390486,2015 IEEE 20th International Workshop on Computer Aided Modelling and Design of Communication Links and Networks (CAMAD),Guglielmi2015,False,,IEEE,Not available,Bayesian game analysis of a queueing system with multiple candidate servers,603463c4e0930af0157ab3c10da065b2,https://ieeexplore.ieee.org/document/7390486/
9936,"We combine queueing theory and game theory to evaluate the performance of a queueing system with multiple strategic candidate servers. The intent is to model a transmission system where packets can be sent via multiple options, each incurring a cost and controlled by a distributed management. Our purpose is to analyze the effects of the presence or the lack of both cooperation and communication between servers. The mathematical characterization of the uncertainty about the characteristics of the transmission alternatives available is captured through a Bayesian game formulation. In this setup, we compute both the Price of Anarchy, quantifying the inherent inefficiency arising from selfish management of each server, and the Price of Stability, which is the loss due to distributed system management, under different conditions of signaling exchange among the servers.",leonardo badia,Bayesian games,2015.0,10.1109/CAMAD.2015.7390486,2015 IEEE 20th International Workshop on Computer Aided Modelling and Design of Communication Links and Networks (CAMAD),Guglielmi2015,False,,IEEE,Not available,Bayesian game analysis of a queueing system with multiple candidate servers,603463c4e0930af0157ab3c10da065b2,https://ieeexplore.ieee.org/document/7390486/
9937,"We combine queueing theory and game theory to evaluate the performance of a queueing system with multiple strategic candidate servers. The intent is to model a transmission system where packets can be sent via multiple options, each incurring a cost and controlled by a distributed management. Our purpose is to analyze the effects of the presence or the lack of both cooperation and communication between servers. The mathematical characterization of the uncertainty about the characteristics of the transmission alternatives available is captured through a Bayesian game formulation. In this setup, we compute both the Price of Anarchy, quantifying the inherent inefficiency arising from selfish management of each server, and the Price of Stability, which is the loss due to distributed system management, under different conditions of signaling exchange among the servers.",leonardo badia,Price of Anarchy,2015.0,10.1109/CAMAD.2015.7390486,2015 IEEE 20th International Workshop on Computer Aided Modelling and Design of Communication Links and Networks (CAMAD),Guglielmi2015,False,,IEEE,Not available,Bayesian game analysis of a queueing system with multiple candidate servers,603463c4e0930af0157ab3c10da065b2,https://ieeexplore.ieee.org/document/7390486/
9938,"In this work, we employ stochastic queueing models to design charging fees for a network of public electric vehicle charging stations operated by a Charging Network Operator (CNO). We assume that the CNO has access to statistics of electric vehicle (EV) users' mobility patterns that determine the demand for charging stations. We model geographically distributed charging stations as a network of unobservable queues with heterogeneous operational costs due to their geographical location and variations in the locational marginal price of electricity. Individual EV users are modeled as selfish agents that minimize their own expected cost of traveling and charging. To eliminate the inefficiencies of selfish routing in the queueing network and reduce aggregate electricity costs, the CNO designs charging fees to control the equilibrium travel and charging patterns on the charging station network. We consider the socially optimal solution to this charging fee design problem and analyze its performance. We also provide bounds on the Price of Anarchy in the charging network (including congestion and electricity costs).",philip wong,Charging stations,2017.0,10.1109/ALLERTON.2017.8262816,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Wong2017,False,,IEEE,Not available,Congestion control and pricing in a network of electric vehicle public charging stations,0b957456c4a9d86277ceb5592e20db54,https://ieeexplore.ieee.org/document/8262816/
9939,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
9940,"In this work, we employ stochastic queueing models to design charging fees for a network of public electric vehicle charging stations operated by a Charging Network Operator (CNO). We assume that the CNO has access to statistics of electric vehicle (EV) users' mobility patterns that determine the demand for charging stations. We model geographically distributed charging stations as a network of unobservable queues with heterogeneous operational costs due to their geographical location and variations in the locational marginal price of electricity. Individual EV users are modeled as selfish agents that minimize their own expected cost of traveling and charging. To eliminate the inefficiencies of selfish routing in the queueing network and reduce aggregate electricity costs, the CNO designs charging fees to control the equilibrium travel and charging patterns on the charging station network. We consider the socially optimal solution to this charging fee design problem and analyze its performance. We also provide bounds on the Price of Anarchy in the charging network (including congestion and electricity costs).",philip wong,Roads,2017.0,10.1109/ALLERTON.2017.8262816,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Wong2017,False,,IEEE,Not available,Congestion control and pricing in a network of electric vehicle public charging stations,0b957456c4a9d86277ceb5592e20db54,https://ieeexplore.ieee.org/document/8262816/
9941,"In this work, we employ stochastic queueing models to design charging fees for a network of public electric vehicle charging stations operated by a Charging Network Operator (CNO). We assume that the CNO has access to statistics of electric vehicle (EV) users' mobility patterns that determine the demand for charging stations. We model geographically distributed charging stations as a network of unobservable queues with heterogeneous operational costs due to their geographical location and variations in the locational marginal price of electricity. Individual EV users are modeled as selfish agents that minimize their own expected cost of traveling and charging. To eliminate the inefficiencies of selfish routing in the queueing network and reduce aggregate electricity costs, the CNO designs charging fees to control the equilibrium travel and charging patterns on the charging station network. We consider the socially optimal solution to this charging fee design problem and analyze its performance. We also provide bounds on the Price of Anarchy in the charging network (including congestion and electricity costs).",philip wong,Pricing,2017.0,10.1109/ALLERTON.2017.8262816,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Wong2017,False,,IEEE,Not available,Congestion control and pricing in a network of electric vehicle public charging stations,0b957456c4a9d86277ceb5592e20db54,https://ieeexplore.ieee.org/document/8262816/
9942,"In this work, we employ stochastic queueing models to design charging fees for a network of public electric vehicle charging stations operated by a Charging Network Operator (CNO). We assume that the CNO has access to statistics of electric vehicle (EV) users' mobility patterns that determine the demand for charging stations. We model geographically distributed charging stations as a network of unobservable queues with heterogeneous operational costs due to their geographical location and variations in the locational marginal price of electricity. Individual EV users are modeled as selfish agents that minimize their own expected cost of traveling and charging. To eliminate the inefficiencies of selfish routing in the queueing network and reduce aggregate electricity costs, the CNO designs charging fees to control the equilibrium travel and charging patterns on the charging station network. We consider the socially optimal solution to this charging fee design problem and analyze its performance. We also provide bounds on the Price of Anarchy in the charging network (including congestion and electricity costs).",philip wong,Random variables,2017.0,10.1109/ALLERTON.2017.8262816,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Wong2017,False,,IEEE,Not available,Congestion control and pricing in a network of electric vehicle public charging stations,0b957456c4a9d86277ceb5592e20db54,https://ieeexplore.ieee.org/document/8262816/
9943,"In this work, we employ stochastic queueing models to design charging fees for a network of public electric vehicle charging stations operated by a Charging Network Operator (CNO). We assume that the CNO has access to statistics of electric vehicle (EV) users' mobility patterns that determine the demand for charging stations. We model geographically distributed charging stations as a network of unobservable queues with heterogeneous operational costs due to their geographical location and variations in the locational marginal price of electricity. Individual EV users are modeled as selfish agents that minimize their own expected cost of traveling and charging. To eliminate the inefficiencies of selfish routing in the queueing network and reduce aggregate electricity costs, the CNO designs charging fees to control the equilibrium travel and charging patterns on the charging station network. We consider the socially optimal solution to this charging fee design problem and analyze its performance. We also provide bounds on the Price of Anarchy in the charging network (including congestion and electricity costs).",mahnoosh alizadeh,Charging stations,2017.0,10.1109/ALLERTON.2017.8262816,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Wong2017,False,,IEEE,Not available,Congestion control and pricing in a network of electric vehicle public charging stations,0b957456c4a9d86277ceb5592e20db54,https://ieeexplore.ieee.org/document/8262816/
9944,"In this work, we employ stochastic queueing models to design charging fees for a network of public electric vehicle charging stations operated by a Charging Network Operator (CNO). We assume that the CNO has access to statistics of electric vehicle (EV) users' mobility patterns that determine the demand for charging stations. We model geographically distributed charging stations as a network of unobservable queues with heterogeneous operational costs due to their geographical location and variations in the locational marginal price of electricity. Individual EV users are modeled as selfish agents that minimize their own expected cost of traveling and charging. To eliminate the inefficiencies of selfish routing in the queueing network and reduce aggregate electricity costs, the CNO designs charging fees to control the equilibrium travel and charging patterns on the charging station network. We consider the socially optimal solution to this charging fee design problem and analyze its performance. We also provide bounds on the Price of Anarchy in the charging network (including congestion and electricity costs).",mahnoosh alizadeh,Roads,2017.0,10.1109/ALLERTON.2017.8262816,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Wong2017,False,,IEEE,Not available,Congestion control and pricing in a network of electric vehicle public charging stations,0b957456c4a9d86277ceb5592e20db54,https://ieeexplore.ieee.org/document/8262816/
9945,"In this work, we employ stochastic queueing models to design charging fees for a network of public electric vehicle charging stations operated by a Charging Network Operator (CNO). We assume that the CNO has access to statistics of electric vehicle (EV) users' mobility patterns that determine the demand for charging stations. We model geographically distributed charging stations as a network of unobservable queues with heterogeneous operational costs due to their geographical location and variations in the locational marginal price of electricity. Individual EV users are modeled as selfish agents that minimize their own expected cost of traveling and charging. To eliminate the inefficiencies of selfish routing in the queueing network and reduce aggregate electricity costs, the CNO designs charging fees to control the equilibrium travel and charging patterns on the charging station network. We consider the socially optimal solution to this charging fee design problem and analyze its performance. We also provide bounds on the Price of Anarchy in the charging network (including congestion and electricity costs).",mahnoosh alizadeh,Pricing,2017.0,10.1109/ALLERTON.2017.8262816,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Wong2017,False,,IEEE,Not available,Congestion control and pricing in a network of electric vehicle public charging stations,0b957456c4a9d86277ceb5592e20db54,https://ieeexplore.ieee.org/document/8262816/
9946,"In this work, we employ stochastic queueing models to design charging fees for a network of public electric vehicle charging stations operated by a Charging Network Operator (CNO). We assume that the CNO has access to statistics of electric vehicle (EV) users' mobility patterns that determine the demand for charging stations. We model geographically distributed charging stations as a network of unobservable queues with heterogeneous operational costs due to their geographical location and variations in the locational marginal price of electricity. Individual EV users are modeled as selfish agents that minimize their own expected cost of traveling and charging. To eliminate the inefficiencies of selfish routing in the queueing network and reduce aggregate electricity costs, the CNO designs charging fees to control the equilibrium travel and charging patterns on the charging station network. We consider the socially optimal solution to this charging fee design problem and analyze its performance. We also provide bounds on the Price of Anarchy in the charging network (including congestion and electricity costs).",mahnoosh alizadeh,Random variables,2017.0,10.1109/ALLERTON.2017.8262816,"2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Wong2017,False,,IEEE,Not available,Congestion control and pricing in a network of electric vehicle public charging stations,0b957456c4a9d86277ceb5592e20db54,https://ieeexplore.ieee.org/document/8262816/
9947,"This paper explains when and how communication and computational lower bounds for algorithms for an optimization problem translate to lower bounds on the worst-case quality of equilibria in games derived from the problem. We give three families of lower bounds on the quality of equilibria, each motivated by a different set of problems: congestion, scheduling, and distributed welfare games, welfare-maximization in combinatorial auctions with ""black-box"" bidder valuations, and welfare-maximization in combinatorial auctions with succinctly described valuations. The most straightforward use of our lower bound framework is to harness an existing computational or communication lower bound to derive a lower bound on the worst-case price of anarchy (POA) in a class of games. This is a new approach to POA lower bounds, which relies on reductions in lieu of explicit constructions. More generally, the POA lower bounds implied by our framework apply to all classes of games that share the same underlying optimization problem, independent of the details of players' utility functions. For this reason, our lower bounds are particularly significant for problems of game design -- ranging from the design of simple combinatorial auctions to the computation of tolls for routing networks -- where the goal is to design a game that has only near-optimal equilibria. For example, our results imply that the simultaneous first-price auction format is optimal among all ""simple combinatorial auctions"" in several settings.",tim roughgarden,price of anarchy,2014.0,10.1109/FOCS.2014.16,2014 IEEE 55th Annual Symposium on Foundations of Computer Science,Roughgarden2014,False,,IEEE,Not available,Barriers to Near-Optimal Equilibria,4c4f4ab60e53a1f1df03162eff4e269f,https://ieeexplore.ieee.org/document/6978991/
9948,"This paper explains when and how communication and computational lower bounds for algorithms for an optimization problem translate to lower bounds on the worst-case quality of equilibria in games derived from the problem. We give three families of lower bounds on the quality of equilibria, each motivated by a different set of problems: congestion, scheduling, and distributed welfare games, welfare-maximization in combinatorial auctions with ""black-box"" bidder valuations, and welfare-maximization in combinatorial auctions with succinctly described valuations. The most straightforward use of our lower bound framework is to harness an existing computational or communication lower bound to derive a lower bound on the worst-case price of anarchy (POA) in a class of games. This is a new approach to POA lower bounds, which relies on reductions in lieu of explicit constructions. More generally, the POA lower bounds implied by our framework apply to all classes of games that share the same underlying optimization problem, independent of the details of players' utility functions. For this reason, our lower bounds are particularly significant for problems of game design -- ranging from the design of simple combinatorial auctions to the computation of tolls for routing networks -- where the goal is to design a game that has only near-optimal equilibria. For example, our results imply that the simultaneous first-price auction format is optimal among all ""simple combinatorial auctions"" in several settings.",tim roughgarden,mechanism design,2014.0,10.1109/FOCS.2014.16,2014 IEEE 55th Annual Symposium on Foundations of Computer Science,Roughgarden2014,False,,IEEE,Not available,Barriers to Near-Optimal Equilibria,4c4f4ab60e53a1f1df03162eff4e269f,https://ieeexplore.ieee.org/document/6978991/
9949,"This paper explains when and how communication and computational lower bounds for algorithms for an optimization problem translate to lower bounds on the worst-case quality of equilibria in games derived from the problem. We give three families of lower bounds on the quality of equilibria, each motivated by a different set of problems: congestion, scheduling, and distributed welfare games, welfare-maximization in combinatorial auctions with ""black-box"" bidder valuations, and welfare-maximization in combinatorial auctions with succinctly described valuations. The most straightforward use of our lower bound framework is to harness an existing computational or communication lower bound to derive a lower bound on the worst-case price of anarchy (POA) in a class of games. This is a new approach to POA lower bounds, which relies on reductions in lieu of explicit constructions. More generally, the POA lower bounds implied by our framework apply to all classes of games that share the same underlying optimization problem, independent of the details of players' utility functions. For this reason, our lower bounds are particularly significant for problems of game design -- ranging from the design of simple combinatorial auctions to the computation of tolls for routing networks -- where the goal is to design a game that has only near-optimal equilibria. For example, our results imply that the simultaneous first-price auction format is optimal among all ""simple combinatorial auctions"" in several settings.",tim roughgarden,complexity of equilbria,2014.0,10.1109/FOCS.2014.16,2014 IEEE 55th Annual Symposium on Foundations of Computer Science,Roughgarden2014,False,,IEEE,Not available,Barriers to Near-Optimal Equilibria,4c4f4ab60e53a1f1df03162eff4e269f,https://ieeexplore.ieee.org/document/6978991/
9950,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
9951,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",yupeng li,Congestion game,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
9952,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",yupeng li,agent failure,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
9953,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",yupeng li,resource failure,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
9954,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",yupeng li,Nash equilibrium,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
9955,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",yupeng li,price of anarchy,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
9956,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",yongzheng jia,Congestion game,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
9957,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",yongzheng jia,agent failure,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
9958,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",yongzheng jia,resource failure,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
9959,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",yongzheng jia,Nash equilibrium,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
9960,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",yongzheng jia,price of anarchy,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
9961,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
9962,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",haisheng tan,Congestion game,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
9963,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",haisheng tan,agent failure,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
9964,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",haisheng tan,resource failure,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
9965,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",haisheng tan,Nash equilibrium,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
9966,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",haisheng tan,price of anarchy,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
9967,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",rui wang,Congestion game,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
9968,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",rui wang,agent failure,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
9969,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",rui wang,resource failure,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
9970,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",rui wang,Nash equilibrium,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
9971,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",rui wang,price of anarchy,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
9972,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
9973,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",zhenhua han,Congestion game,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
9974,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",zhenhua han,agent failure,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
9975,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",zhenhua han,resource failure,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
9976,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",zhenhua han,Nash equilibrium,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
9977,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",zhenhua han,price of anarchy,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
9978,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",francis lau,Congestion game,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
9979,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",francis lau,agent failure,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
9980,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",francis lau,resource failure,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
9981,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",francis lau,Nash equilibrium,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
9982,"Motivated by practical scenarios, we study congestion games with failures. We investigate two models. The first model is congestion games with both resource and agent failures, where each agent chooses the same number of resources with the minimum expected cost. We prove that the game is potential and hence admits at least one pure-strategy Nash equilibrium (pure-NE). We also show that the Price of Anarchy and the Price of Stability are bounded (equal to 1 in some cases). The second model is congestion games with only resource failures (CG-CRF), where resources are provided in packages, and their failures can be correlated with each other. Each agent can choose multiple packages for reliability's sake and utilize the survived one having the minimum cost. CG-CRF is shown to be not potential. We prove that it admits at least one pure-NE by constructing one efficiently. Finally, we discuss various applications of these two games in the networking field. To the best of our knowledge, this is the first paper studying congestion games with the coexistence of resource and agent failures, and we give also the first proof of the existence of a pure-NE in congestion games with correlated package failures.",francis lau,price of anarchy,2017.0,10.1109/JSAC.2017.2672358,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Congestion Game With Agent and Resource Failures,64c11c779bd23deaf98ff0119d9f2c68,https://ieeexplore.ieee.org/document/7859268/
9983,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
9984,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",giovanni accongiagioco,Internet Modeling,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
9985,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",giovanni accongiagioco,Complex Networks,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
9986,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",giovanni accongiagioco,Game Theory,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
9987,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",giovanni accongiagioco,AS-level Internet Topology,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
9988,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",giovanni accongiagioco,Supermodular Games,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
9989,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",eitan altman,Internet Modeling,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
9990,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",eitan altman,Complex Networks,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
9991,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",eitan altman,Game Theory,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
9992,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",eitan altman,AS-level Internet Topology,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
9993,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",eitan altman,Supermodular Games,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
9994,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
9995,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
9996,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",enrico gregori,Internet Modeling,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
9997,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",enrico gregori,Complex Networks,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
9998,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",enrico gregori,Game Theory,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
9999,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",enrico gregori,AS-level Internet Topology,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
10000,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",enrico gregori,Supermodular Games,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
10001,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",luciano lenzini,Internet Modeling,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
10002,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",luciano lenzini,Complex Networks,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
10003,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",luciano lenzini,Game Theory,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
10004,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",luciano lenzini,AS-level Internet Topology,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
10005,"We propose a model to analyze the decisions taken by an Autonomous System (AS) when joining the Internet. We first define a realistic model for the interconnection costs incurred and then we use this cost model to perform a game theoretic analysis of the decisions related to the creation of new links in the Internet. The proposed model doesn't fall into the standard category of routing games, hence we devise new tools to solve it by exploiting peculiar properties of our game. We prove analytically the existence of multiple equilibria for specific cases, and provide an algorithm to compute the stable ones. The analysis of the model's outcome highlights the existence of a Price of Anarchy (PoA) and a Price of Stability (PoS), originated by the non-cooperative behavior of the ASes, which optimize their cost function in a selfish and decentralized manner. We further observe the presence of competition between the facilities providing either transit or peering connectivity, caused by the cost differences between these two interconnection strategies.",luciano lenzini,Supermodular Games,2014.0,10.1109/IFIPNetworking.2014.6857114,2014 IFIP Networking Conference,Accongiagioco2014,False,,IEEE,Not available,Peering vs transit: A game theoretical model for autonomous systems connectivity,31c591bf872437561d06a66c72294ce0,
10006,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
10007,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",hyeryung jang,CSMA,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
10008,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",hyeryung jang,distributed algorithms,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
10009,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",hyeryung jang,game theory,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
10010,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",hyeryung jang,wireless ad-hoc network,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
10011,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",hyeryung jang,stochastic approximation,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
10012,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",se-young yun,CSMA,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
10013,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",se-young yun,distributed algorithms,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
10014,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",se-young yun,game theory,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
10015,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",se-young yun,wireless ad-hoc network,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
10016,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",se-young yun,stochastic approximation,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
10017,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
10018,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",jinwoo shin,CSMA,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
10019,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",jinwoo shin,distributed algorithms,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
10020,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",jinwoo shin,game theory,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
10021,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",jinwoo shin,wireless ad-hoc network,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
10022,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",jinwoo shin,stochastic approximation,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
10023,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",yung yi,CSMA,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
10024,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",yung yi,distributed algorithms,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
10025,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",yung yi,game theory,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
10026,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",yung yi,wireless ad-hoc network,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
10027,"Game-theoretic approaches have provided valuable insights into the design of robust local control rules for the individuals in multi-agent systems, e.g., Internet congestion control, road transportation networks, and so on. In this paper, we introduce a non-cooperative medium access control game for wireless networks and propose new fully distributed carrier sense multiple access (CSMA) algorithms that are provably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing novel price functions in agents' utilities so that the proposed game admits an ordinal potential function with no price-of-anarchy. The game formulation naturally leads to game-based dynamics finding a Nash equilibrium, but they often require global information. Toward our goal of designing fully distributed operations, we propose new game-inspired dynamics by utilizing a certain property of CSMA that enables links to estimate their temporary throughputs without message passing. They can be thought of as stochastic approximations to the standard dynamics, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, and numerically evaluate their performance to support our theoretical findings.",yung yi,stochastic approximation,2018.0,10.1109/TWC.2017.2764081,IEEE Transactions on Wireless Communications,Jang2018,False,,IEEE,Not available,Game Theoretic Perspective of Optimal CSMA,5a993a9208367d1e9f9cce838f2f149c,https://ieeexplore.ieee.org/document/8077763/
10028,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
10029,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,tejas bodas,Servers,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
10030,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,tejas bodas,Resource management,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
10031,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,tejas bodas,Routing,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
10032,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,tejas bodas,Load management,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
10033,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,tejas bodas,Queueing analysis,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
10034,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,tejas bodas,Cost function,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
10035,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,tejas bodas,Delay,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
10036,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,ayalvadi ganesh,Servers,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
10037,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,ayalvadi ganesh,Resource management,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
10038,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,ayalvadi ganesh,Routing,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
10039,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
10040,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,ayalvadi ganesh,Load management,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
10041,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,ayalvadi ganesh,Queueing analysis,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
10042,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,ayalvadi ganesh,Cost function,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
10043,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,ayalvadi ganesh,Delay,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
10044,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,d. manjunath,Servers,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
10045,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,d. manjunath,Resource management,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
10046,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,d. manjunath,Routing,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
10047,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,d. manjunath,Load management,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
10048,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,d. manjunath,Queueing analysis,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
10049,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,d. manjunath,Cost function,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
10050,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
10051,We consider load balancing with routing games in a multiclass traffic environment. The servers are M/M/1 type servers and charge an admission price to each customer that joins the queue for service. Service requirements of all arriving customers are i.i.d. and they can receive service from any of the servers. Customers also have a waiting time cost that is proportional to their expected waiting times. Arrivals are from a multiclass population with the different classes differing in the their waiting time costs and having different arrival rates. In this paper we consider the following two load balancing schemes. (1) Both classes are non atomic; each arriving customer independently chooses one of the servers with a probability that optimizes an individual objective function. (2) One of the classes has a dispatcher that routes customers of that class to the servers with probabilities that minimize the total cost for that class; customers of the other class choose a server like in the first scheme. We analyze the equilibrium behavior of both the systems. We also describe a system that can be used to bound the price of anarchy in such systems.,d. manjunath,Delay,2011.0,10.1109/CDC.2011.6161083,2011 50th IEEE Conference on Decision and Control and European Control Conference,Bodas2011,False,,IEEE,Not available,Load balancing and routing games with admission price,750dc706a46321578ff7adae19807d3b,https://ieeexplore.ieee.org/document/6161083/
10052,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",diego lucerna,Game theory,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10053,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",diego lucerna,WDM networks,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10054,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",diego lucerna,Optical fiber networks,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10055,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",diego lucerna,Repeaters,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10056,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",diego lucerna,Nash equilibrium,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10057,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",diego lucerna,Wavelength division multiplexing,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10058,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",diego lucerna,Mathematical model,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10059,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",diego lucerna,Optical signal processing,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10060,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",diego lucerna,Upper bound,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10061,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
10062,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",diego lucerna,Mathematical programming,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10063,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",nicola gatti,Game theory,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10064,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",nicola gatti,WDM networks,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10065,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",nicola gatti,Optical fiber networks,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10066,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",nicola gatti,Repeaters,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10067,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",nicola gatti,Nash equilibrium,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10068,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",nicola gatti,Wavelength division multiplexing,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10069,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",nicola gatti,Mathematical model,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10070,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",nicola gatti,Optical signal processing,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10071,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",nicola gatti,Upper bound,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10072,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
10073,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",nicola gatti,Mathematical programming,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10074,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",guido maier,Game theory,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10075,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",guido maier,WDM networks,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10076,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",guido maier,Optical fiber networks,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10077,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",guido maier,Repeaters,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10078,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",guido maier,Nash equilibrium,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10079,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",guido maier,Wavelength division multiplexing,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10080,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",guido maier,Mathematical model,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10081,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",guido maier,Optical signal processing,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10082,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",guido maier,Upper bound,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10083,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
10084,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",guido maier,Mathematical programming,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10085,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",achille pattavina,Game theory,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10086,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",achille pattavina,WDM networks,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10087,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",achille pattavina,Optical fiber networks,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10088,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",achille pattavina,Repeaters,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10089,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",achille pattavina,Nash equilibrium,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10090,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",achille pattavina,Wavelength division multiplexing,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10091,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",achille pattavina,Mathematical model,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10092,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",achille pattavina,Optical signal processing,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10093,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",achille pattavina,Upper bound,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10094,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
10095,"In this paper we provide a mathematical ILP model for the Regeneration Placement Problem (RPP) which minimizes the total number of regeneration nodes allocated in a translucent optical network ensuring that all the node pairs can always reach one another via two link-disjoint lightpaths under physical-impairment constraints. Since RPP is NP-complete, large-site design problem can not be solved relying upon exact approaches. We then propose a game-theoretic approach to model RPP as a non-cooperative game and solve it applying the best response dynamic concept. Finally, we evaluate the performance of the proposed approach in terms of closeness of the obtained results to these provided by ILP: a MILP formulation is given in order to study the quality of the Nash equilibria by comparison to Price-of-Anarchy and Price-of-Stability bounds.",achille pattavina,Mathematical programming,2009.0,10.1109/GLOCOM.2009.5425388,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Lucerna2009,False,,IEEE,Not available,On the Efficiency of a Game Theoretic Approach to Sparse Regenerator Placement in WDM Networks,a3906a3798552c4c1e914c4059848598,https://ieeexplore.ieee.org/document/5425388/
10096,"This paper investigates the subcarrier allocation problem for a downlink multi-cell multiuser OFDMA network using potential game theory. Each player is considered to be a central base station together with all the mobiles distributed within its coverage area. In such a system, co-channel interferences (CCI), if left uncontrolled, could hinder the transmissions and limit the throughputs of the users, especially those near the cell-edge area. Certain remedies, including power control with pricing, did not seem to solve the problem completely. We specifically address this issue from an interference-minimizing approach, where the utility function adopted is meant to minimize the total CCI among players. Under such formulation, we show that the formulated game can be mathematically described by a potential game. Hence, a Nash equilibrium (NE) will be guaranteed for the proposed game and stable solutions can be achieved via myopic gameplays such as the best/better responses. We propose our iterative algorithm for obtaining the NEs and address several performance issues such as fairness for edge-users and the price of anarchy. Numerical results show the improvement in efficiency and fairness using this approach.",quang la,Downlink multi-cell OFDMA,2012.0,10.1109/TWC.2012.072512.112046,IEEE Transactions on Wireless Communications,La2012,False,,IEEE,Not available,Performance Analysis of Downlink Multi-Cell OFDMA Systems Based on Potential Game,f3fca19762ba02d434ee0cf5edc89e03,https://ieeexplore.ieee.org/document/6251826/
10097,"This paper investigates the subcarrier allocation problem for a downlink multi-cell multiuser OFDMA network using potential game theory. Each player is considered to be a central base station together with all the mobiles distributed within its coverage area. In such a system, co-channel interferences (CCI), if left uncontrolled, could hinder the transmissions and limit the throughputs of the users, especially those near the cell-edge area. Certain remedies, including power control with pricing, did not seem to solve the problem completely. We specifically address this issue from an interference-minimizing approach, where the utility function adopted is meant to minimize the total CCI among players. Under such formulation, we show that the formulated game can be mathematically described by a potential game. Hence, a Nash equilibrium (NE) will be guaranteed for the proposed game and stable solutions can be achieved via myopic gameplays such as the best/better responses. We propose our iterative algorithm for obtaining the NEs and address several performance issues such as fairness for edge-users and the price of anarchy. Numerical results show the improvement in efficiency and fairness using this approach.",quang la,potential game,2012.0,10.1109/TWC.2012.072512.112046,IEEE Transactions on Wireless Communications,La2012,False,,IEEE,Not available,Performance Analysis of Downlink Multi-Cell OFDMA Systems Based on Potential Game,f3fca19762ba02d434ee0cf5edc89e03,https://ieeexplore.ieee.org/document/6251826/
10098,"This paper investigates the subcarrier allocation problem for a downlink multi-cell multiuser OFDMA network using potential game theory. Each player is considered to be a central base station together with all the mobiles distributed within its coverage area. In such a system, co-channel interferences (CCI), if left uncontrolled, could hinder the transmissions and limit the throughputs of the users, especially those near the cell-edge area. Certain remedies, including power control with pricing, did not seem to solve the problem completely. We specifically address this issue from an interference-minimizing approach, where the utility function adopted is meant to minimize the total CCI among players. Under such formulation, we show that the formulated game can be mathematically described by a potential game. Hence, a Nash equilibrium (NE) will be guaranteed for the proposed game and stable solutions can be achieved via myopic gameplays such as the best/better responses. We propose our iterative algorithm for obtaining the NEs and address several performance issues such as fairness for edge-users and the price of anarchy. Numerical results show the improvement in efficiency and fairness using this approach.",quang la,interference minimization,2012.0,10.1109/TWC.2012.072512.112046,IEEE Transactions on Wireless Communications,La2012,False,,IEEE,Not available,Performance Analysis of Downlink Multi-Cell OFDMA Systems Based on Potential Game,f3fca19762ba02d434ee0cf5edc89e03,https://ieeexplore.ieee.org/document/6251826/
10099,"This paper investigates the subcarrier allocation problem for a downlink multi-cell multiuser OFDMA network using potential game theory. Each player is considered to be a central base station together with all the mobiles distributed within its coverage area. In such a system, co-channel interferences (CCI), if left uncontrolled, could hinder the transmissions and limit the throughputs of the users, especially those near the cell-edge area. Certain remedies, including power control with pricing, did not seem to solve the problem completely. We specifically address this issue from an interference-minimizing approach, where the utility function adopted is meant to minimize the total CCI among players. Under such formulation, we show that the formulated game can be mathematically described by a potential game. Hence, a Nash equilibrium (NE) will be guaranteed for the proposed game and stable solutions can be achieved via myopic gameplays such as the best/better responses. We propose our iterative algorithm for obtaining the NEs and address several performance issues such as fairness for edge-users and the price of anarchy. Numerical results show the improvement in efficiency and fairness using this approach.",quang la,Nash equilibrium,2012.0,10.1109/TWC.2012.072512.112046,IEEE Transactions on Wireless Communications,La2012,False,,IEEE,Not available,Performance Analysis of Downlink Multi-Cell OFDMA Systems Based on Potential Game,f3fca19762ba02d434ee0cf5edc89e03,https://ieeexplore.ieee.org/document/6251826/
10100,"This paper investigates the subcarrier allocation problem for a downlink multi-cell multiuser OFDMA network using potential game theory. Each player is considered to be a central base station together with all the mobiles distributed within its coverage area. In such a system, co-channel interferences (CCI), if left uncontrolled, could hinder the transmissions and limit the throughputs of the users, especially those near the cell-edge area. Certain remedies, including power control with pricing, did not seem to solve the problem completely. We specifically address this issue from an interference-minimizing approach, where the utility function adopted is meant to minimize the total CCI among players. Under such formulation, we show that the formulated game can be mathematically described by a potential game. Hence, a Nash equilibrium (NE) will be guaranteed for the proposed game and stable solutions can be achieved via myopic gameplays such as the best/better responses. We propose our iterative algorithm for obtaining the NEs and address several performance issues such as fairness for edge-users and the price of anarchy. Numerical results show the improvement in efficiency and fairness using this approach.",yong chew,Downlink multi-cell OFDMA,2012.0,10.1109/TWC.2012.072512.112046,IEEE Transactions on Wireless Communications,La2012,False,,IEEE,Not available,Performance Analysis of Downlink Multi-Cell OFDMA Systems Based on Potential Game,f3fca19762ba02d434ee0cf5edc89e03,https://ieeexplore.ieee.org/document/6251826/
10101,"This paper investigates the subcarrier allocation problem for a downlink multi-cell multiuser OFDMA network using potential game theory. Each player is considered to be a central base station together with all the mobiles distributed within its coverage area. In such a system, co-channel interferences (CCI), if left uncontrolled, could hinder the transmissions and limit the throughputs of the users, especially those near the cell-edge area. Certain remedies, including power control with pricing, did not seem to solve the problem completely. We specifically address this issue from an interference-minimizing approach, where the utility function adopted is meant to minimize the total CCI among players. Under such formulation, we show that the formulated game can be mathematically described by a potential game. Hence, a Nash equilibrium (NE) will be guaranteed for the proposed game and stable solutions can be achieved via myopic gameplays such as the best/better responses. We propose our iterative algorithm for obtaining the NEs and address several performance issues such as fairness for edge-users and the price of anarchy. Numerical results show the improvement in efficiency and fairness using this approach.",yong chew,potential game,2012.0,10.1109/TWC.2012.072512.112046,IEEE Transactions on Wireless Communications,La2012,False,,IEEE,Not available,Performance Analysis of Downlink Multi-Cell OFDMA Systems Based on Potential Game,f3fca19762ba02d434ee0cf5edc89e03,https://ieeexplore.ieee.org/document/6251826/
10102,"This paper investigates the subcarrier allocation problem for a downlink multi-cell multiuser OFDMA network using potential game theory. Each player is considered to be a central base station together with all the mobiles distributed within its coverage area. In such a system, co-channel interferences (CCI), if left uncontrolled, could hinder the transmissions and limit the throughputs of the users, especially those near the cell-edge area. Certain remedies, including power control with pricing, did not seem to solve the problem completely. We specifically address this issue from an interference-minimizing approach, where the utility function adopted is meant to minimize the total CCI among players. Under such formulation, we show that the formulated game can be mathematically described by a potential game. Hence, a Nash equilibrium (NE) will be guaranteed for the proposed game and stable solutions can be achieved via myopic gameplays such as the best/better responses. We propose our iterative algorithm for obtaining the NEs and address several performance issues such as fairness for edge-users and the price of anarchy. Numerical results show the improvement in efficiency and fairness using this approach.",yong chew,interference minimization,2012.0,10.1109/TWC.2012.072512.112046,IEEE Transactions on Wireless Communications,La2012,False,,IEEE,Not available,Performance Analysis of Downlink Multi-Cell OFDMA Systems Based on Potential Game,f3fca19762ba02d434ee0cf5edc89e03,https://ieeexplore.ieee.org/document/6251826/
10103,"This paper investigates the subcarrier allocation problem for a downlink multi-cell multiuser OFDMA network using potential game theory. Each player is considered to be a central base station together with all the mobiles distributed within its coverage area. In such a system, co-channel interferences (CCI), if left uncontrolled, could hinder the transmissions and limit the throughputs of the users, especially those near the cell-edge area. Certain remedies, including power control with pricing, did not seem to solve the problem completely. We specifically address this issue from an interference-minimizing approach, where the utility function adopted is meant to minimize the total CCI among players. Under such formulation, we show that the formulated game can be mathematically described by a potential game. Hence, a Nash equilibrium (NE) will be guaranteed for the proposed game and stable solutions can be achieved via myopic gameplays such as the best/better responses. We propose our iterative algorithm for obtaining the NEs and address several performance issues such as fairness for edge-users and the price of anarchy. Numerical results show the improvement in efficiency and fairness using this approach.",yong chew,Nash equilibrium,2012.0,10.1109/TWC.2012.072512.112046,IEEE Transactions on Wireless Communications,La2012,False,,IEEE,Not available,Performance Analysis of Downlink Multi-Cell OFDMA Systems Based on Potential Game,f3fca19762ba02d434ee0cf5edc89e03,https://ieeexplore.ieee.org/document/6251826/
10104,"This paper investigates the subcarrier allocation problem for a downlink multi-cell multiuser OFDMA network using potential game theory. Each player is considered to be a central base station together with all the mobiles distributed within its coverage area. In such a system, co-channel interferences (CCI), if left uncontrolled, could hinder the transmissions and limit the throughputs of the users, especially those near the cell-edge area. Certain remedies, including power control with pricing, did not seem to solve the problem completely. We specifically address this issue from an interference-minimizing approach, where the utility function adopted is meant to minimize the total CCI among players. Under such formulation, we show that the formulated game can be mathematically described by a potential game. Hence, a Nash equilibrium (NE) will be guaranteed for the proposed game and stable solutions can be achieved via myopic gameplays such as the best/better responses. We propose our iterative algorithm for obtaining the NEs and address several performance issues such as fairness for edge-users and the price of anarchy. Numerical results show the improvement in efficiency and fairness using this approach.",boon soong,Downlink multi-cell OFDMA,2012.0,10.1109/TWC.2012.072512.112046,IEEE Transactions on Wireless Communications,La2012,False,,IEEE,Not available,Performance Analysis of Downlink Multi-Cell OFDMA Systems Based on Potential Game,f3fca19762ba02d434ee0cf5edc89e03,https://ieeexplore.ieee.org/document/6251826/
10105,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
10106,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
10107,"This paper investigates the subcarrier allocation problem for a downlink multi-cell multiuser OFDMA network using potential game theory. Each player is considered to be a central base station together with all the mobiles distributed within its coverage area. In such a system, co-channel interferences (CCI), if left uncontrolled, could hinder the transmissions and limit the throughputs of the users, especially those near the cell-edge area. Certain remedies, including power control with pricing, did not seem to solve the problem completely. We specifically address this issue from an interference-minimizing approach, where the utility function adopted is meant to minimize the total CCI among players. Under such formulation, we show that the formulated game can be mathematically described by a potential game. Hence, a Nash equilibrium (NE) will be guaranteed for the proposed game and stable solutions can be achieved via myopic gameplays such as the best/better responses. We propose our iterative algorithm for obtaining the NEs and address several performance issues such as fairness for edge-users and the price of anarchy. Numerical results show the improvement in efficiency and fairness using this approach.",boon soong,potential game,2012.0,10.1109/TWC.2012.072512.112046,IEEE Transactions on Wireless Communications,La2012,False,,IEEE,Not available,Performance Analysis of Downlink Multi-Cell OFDMA Systems Based on Potential Game,f3fca19762ba02d434ee0cf5edc89e03,https://ieeexplore.ieee.org/document/6251826/
10108,"This paper investigates the subcarrier allocation problem for a downlink multi-cell multiuser OFDMA network using potential game theory. Each player is considered to be a central base station together with all the mobiles distributed within its coverage area. In such a system, co-channel interferences (CCI), if left uncontrolled, could hinder the transmissions and limit the throughputs of the users, especially those near the cell-edge area. Certain remedies, including power control with pricing, did not seem to solve the problem completely. We specifically address this issue from an interference-minimizing approach, where the utility function adopted is meant to minimize the total CCI among players. Under such formulation, we show that the formulated game can be mathematically described by a potential game. Hence, a Nash equilibrium (NE) will be guaranteed for the proposed game and stable solutions can be achieved via myopic gameplays such as the best/better responses. We propose our iterative algorithm for obtaining the NEs and address several performance issues such as fairness for edge-users and the price of anarchy. Numerical results show the improvement in efficiency and fairness using this approach.",boon soong,interference minimization,2012.0,10.1109/TWC.2012.072512.112046,IEEE Transactions on Wireless Communications,La2012,False,,IEEE,Not available,Performance Analysis of Downlink Multi-Cell OFDMA Systems Based on Potential Game,f3fca19762ba02d434ee0cf5edc89e03,https://ieeexplore.ieee.org/document/6251826/
10109,"This paper investigates the subcarrier allocation problem for a downlink multi-cell multiuser OFDMA network using potential game theory. Each player is considered to be a central base station together with all the mobiles distributed within its coverage area. In such a system, co-channel interferences (CCI), if left uncontrolled, could hinder the transmissions and limit the throughputs of the users, especially those near the cell-edge area. Certain remedies, including power control with pricing, did not seem to solve the problem completely. We specifically address this issue from an interference-minimizing approach, where the utility function adopted is meant to minimize the total CCI among players. Under such formulation, we show that the formulated game can be mathematically described by a potential game. Hence, a Nash equilibrium (NE) will be guaranteed for the proposed game and stable solutions can be achieved via myopic gameplays such as the best/better responses. We propose our iterative algorithm for obtaining the NEs and address several performance issues such as fairness for edge-users and the price of anarchy. Numerical results show the improvement in efficiency and fairness using this approach.",boon soong,Nash equilibrium,2012.0,10.1109/TWC.2012.072512.112046,IEEE Transactions on Wireless Communications,La2012,False,,IEEE,Not available,Performance Analysis of Downlink Multi-Cell OFDMA Systems Based on Potential Game,f3fca19762ba02d434ee0cf5edc89e03,https://ieeexplore.ieee.org/document/6251826/
10110,"The Nash equilibrium region for a 2-user game was defined and characterized first for a linear deterministic channel and then for a Gaussian channel. Challenges in extending this understanding to some special K-user cases have also been explored. In this paper, we study two indices which compare the performance (sum-rate) of the `best' and the `worst' Nash equilibria to the optimum (sum-capacity) and reflect the `price of stability' and the `price of anarchy', respectively. These indices are evaluated for the 2-user and some special K-user linear deterministic interference channels. We further investigate the impact on these indices of changing the payoff functions of each user to include a cost of transmission.",suvarup saha,Interference channels,2010.0,10.1109/ACSSC.2010.5757523,"2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers",Saha2010,False,,IEEE,Not available,On information theoretic games for interference networks,487af391c98553951dedbd104bdb1869,https://ieeexplore.ieee.org/document/5757523/
10111,"The Nash equilibrium region for a 2-user game was defined and characterized first for a linear deterministic channel and then for a Gaussian channel. Challenges in extending this understanding to some special K-user cases have also been explored. In this paper, we study two indices which compare the performance (sum-rate) of the `best' and the `worst' Nash equilibria to the optimum (sum-capacity) and reflect the `price of stability' and the `price of anarchy', respectively. These indices are evaluated for the 2-user and some special K-user linear deterministic interference channels. We further investigate the impact on these indices of changing the payoff functions of each user to include a cost of transmission.",suvarup saha,Games,2010.0,10.1109/ACSSC.2010.5757523,"2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers",Saha2010,False,,IEEE,Not available,On information theoretic games for interference networks,487af391c98553951dedbd104bdb1869,https://ieeexplore.ieee.org/document/5757523/
10112,"The Nash equilibrium region for a 2-user game was defined and characterized first for a linear deterministic channel and then for a Gaussian channel. Challenges in extending this understanding to some special K-user cases have also been explored. In this paper, we study two indices which compare the performance (sum-rate) of the `best' and the `worst' Nash equilibria to the optimum (sum-capacity) and reflect the `price of stability' and the `price of anarchy', respectively. These indices are evaluated for the 2-user and some special K-user linear deterministic interference channels. We further investigate the impact on these indices of changing the payoff functions of each user to include a cost of transmission.",suvarup saha,Receivers,2010.0,10.1109/ACSSC.2010.5757523,"2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers",Saha2010,False,,IEEE,Not available,On information theoretic games for interference networks,487af391c98553951dedbd104bdb1869,https://ieeexplore.ieee.org/document/5757523/
10113,"The Nash equilibrium region for a 2-user game was defined and characterized first for a linear deterministic channel and then for a Gaussian channel. Challenges in extending this understanding to some special K-user cases have also been explored. In this paper, we study two indices which compare the performance (sum-rate) of the `best' and the `worst' Nash equilibria to the optimum (sum-capacity) and reflect the `price of stability' and the `price of anarchy', respectively. These indices are evaluated for the 2-user and some special K-user linear deterministic interference channels. We further investigate the impact on these indices of changing the payoff functions of each user to include a cost of transmission.",suvarup saha,Noise,2010.0,10.1109/ACSSC.2010.5757523,"2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers",Saha2010,False,,IEEE,Not available,On information theoretic games for interference networks,487af391c98553951dedbd104bdb1869,https://ieeexplore.ieee.org/document/5757523/
10114,"The Nash equilibrium region for a 2-user game was defined and characterized first for a linear deterministic channel and then for a Gaussian channel. Challenges in extending this understanding to some special K-user cases have also been explored. In this paper, we study two indices which compare the performance (sum-rate) of the `best' and the `worst' Nash equilibria to the optimum (sum-capacity) and reflect the `price of stability' and the `price of anarchy', respectively. These indices are evaluated for the 2-user and some special K-user linear deterministic interference channels. We further investigate the impact on these indices of changing the payoff functions of each user to include a cost of transmission.",suvarup saha,Transmitters,2010.0,10.1109/ACSSC.2010.5757523,"2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers",Saha2010,False,,IEEE,Not available,On information theoretic games for interference networks,487af391c98553951dedbd104bdb1869,https://ieeexplore.ieee.org/document/5757523/
10115,"The Nash equilibrium region for a 2-user game was defined and characterized first for a linear deterministic channel and then for a Gaussian channel. Challenges in extending this understanding to some special K-user cases have also been explored. In this paper, we study two indices which compare the performance (sum-rate) of the `best' and the `worst' Nash equilibria to the optimum (sum-capacity) and reflect the `price of stability' and the `price of anarchy', respectively. These indices are evaluated for the 2-user and some special K-user linear deterministic interference channels. We further investigate the impact on these indices of changing the payoff functions of each user to include a cost of transmission.",suvarup saha,Nash equilibrium,2010.0,10.1109/ACSSC.2010.5757523,"2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers",Saha2010,False,,IEEE,Not available,On information theoretic games for interference networks,487af391c98553951dedbd104bdb1869,https://ieeexplore.ieee.org/document/5757523/
10116,"The Nash equilibrium region for a 2-user game was defined and characterized first for a linear deterministic channel and then for a Gaussian channel. Challenges in extending this understanding to some special K-user cases have also been explored. In this paper, we study two indices which compare the performance (sum-rate) of the `best' and the `worst' Nash equilibria to the optimum (sum-capacity) and reflect the `price of stability' and the `price of anarchy', respectively. These indices are evaluated for the 2-user and some special K-user linear deterministic interference channels. We further investigate the impact on these indices of changing the payoff functions of each user to include a cost of transmission.",randall berry,Interference channels,2010.0,10.1109/ACSSC.2010.5757523,"2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers",Saha2010,False,,IEEE,Not available,On information theoretic games for interference networks,487af391c98553951dedbd104bdb1869,https://ieeexplore.ieee.org/document/5757523/
10117,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
10118,"The Nash equilibrium region for a 2-user game was defined and characterized first for a linear deterministic channel and then for a Gaussian channel. Challenges in extending this understanding to some special K-user cases have also been explored. In this paper, we study two indices which compare the performance (sum-rate) of the `best' and the `worst' Nash equilibria to the optimum (sum-capacity) and reflect the `price of stability' and the `price of anarchy', respectively. These indices are evaluated for the 2-user and some special K-user linear deterministic interference channels. We further investigate the impact on these indices of changing the payoff functions of each user to include a cost of transmission.",randall berry,Games,2010.0,10.1109/ACSSC.2010.5757523,"2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers",Saha2010,False,,IEEE,Not available,On information theoretic games for interference networks,487af391c98553951dedbd104bdb1869,https://ieeexplore.ieee.org/document/5757523/
10119,"The Nash equilibrium region for a 2-user game was defined and characterized first for a linear deterministic channel and then for a Gaussian channel. Challenges in extending this understanding to some special K-user cases have also been explored. In this paper, we study two indices which compare the performance (sum-rate) of the `best' and the `worst' Nash equilibria to the optimum (sum-capacity) and reflect the `price of stability' and the `price of anarchy', respectively. These indices are evaluated for the 2-user and some special K-user linear deterministic interference channels. We further investigate the impact on these indices of changing the payoff functions of each user to include a cost of transmission.",randall berry,Receivers,2010.0,10.1109/ACSSC.2010.5757523,"2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers",Saha2010,False,,IEEE,Not available,On information theoretic games for interference networks,487af391c98553951dedbd104bdb1869,https://ieeexplore.ieee.org/document/5757523/
10120,"The Nash equilibrium region for a 2-user game was defined and characterized first for a linear deterministic channel and then for a Gaussian channel. Challenges in extending this understanding to some special K-user cases have also been explored. In this paper, we study two indices which compare the performance (sum-rate) of the `best' and the `worst' Nash equilibria to the optimum (sum-capacity) and reflect the `price of stability' and the `price of anarchy', respectively. These indices are evaluated for the 2-user and some special K-user linear deterministic interference channels. We further investigate the impact on these indices of changing the payoff functions of each user to include a cost of transmission.",randall berry,Noise,2010.0,10.1109/ACSSC.2010.5757523,"2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers",Saha2010,False,,IEEE,Not available,On information theoretic games for interference networks,487af391c98553951dedbd104bdb1869,https://ieeexplore.ieee.org/document/5757523/
10121,"The Nash equilibrium region for a 2-user game was defined and characterized first for a linear deterministic channel and then for a Gaussian channel. Challenges in extending this understanding to some special K-user cases have also been explored. In this paper, we study two indices which compare the performance (sum-rate) of the `best' and the `worst' Nash equilibria to the optimum (sum-capacity) and reflect the `price of stability' and the `price of anarchy', respectively. These indices are evaluated for the 2-user and some special K-user linear deterministic interference channels. We further investigate the impact on these indices of changing the payoff functions of each user to include a cost of transmission.",randall berry,Transmitters,2010.0,10.1109/ACSSC.2010.5757523,"2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers",Saha2010,False,,IEEE,Not available,On information theoretic games for interference networks,487af391c98553951dedbd104bdb1869,https://ieeexplore.ieee.org/document/5757523/
10122,"The Nash equilibrium region for a 2-user game was defined and characterized first for a linear deterministic channel and then for a Gaussian channel. Challenges in extending this understanding to some special K-user cases have also been explored. In this paper, we study two indices which compare the performance (sum-rate) of the `best' and the `worst' Nash equilibria to the optimum (sum-capacity) and reflect the `price of stability' and the `price of anarchy', respectively. These indices are evaluated for the 2-user and some special K-user linear deterministic interference channels. We further investigate the impact on these indices of changing the payoff functions of each user to include a cost of transmission.",randall berry,Nash equilibrium,2010.0,10.1109/ACSSC.2010.5757523,"2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers",Saha2010,False,,IEEE,Not available,On information theoretic games for interference networks,487af391c98553951dedbd104bdb1869,https://ieeexplore.ieee.org/document/5757523/
10123,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",jun zhao,Quality of service,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10124,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",jun zhao,Games,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10125,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",jun zhao,Resource management,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10126,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",jun zhao,Base stations,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10127,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",jun zhao,Interference,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10128,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
10129,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",jun zhao,Throughput,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10130,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",jun zhao,Algorithm design and analysis,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10131,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",haijun zhang,Quality of service,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10132,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",haijun zhang,Games,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10133,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",haijun zhang,Resource management,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10134,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",haijun zhang,Base stations,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10135,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",haijun zhang,Interference,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10136,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",haijun zhang,Throughput,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10137,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",haijun zhang,Algorithm design and analysis,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10138,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",zhaoming lu,Quality of service,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10139,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
10140,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",zhaoming lu,Games,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10141,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",zhaoming lu,Resource management,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10142,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",zhaoming lu,Base stations,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10143,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",zhaoming lu,Interference,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10144,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",zhaoming lu,Throughput,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10145,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",zhaoming lu,Algorithm design and analysis,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10146,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",xiangming wen,Quality of service,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10147,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",xiangming wen,Games,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10148,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",xiangming wen,Resource management,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10149,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",xiangming wen,Base stations,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10150,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
10151,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",xiangming wen,Interference,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10152,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",xiangming wen,Throughput,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10153,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",xiangming wen,Algorithm design and analysis,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10154,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",wei zheng,Quality of service,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10155,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",wei zheng,Games,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10156,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",wei zheng,Resource management,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10157,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",wei zheng,Base stations,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10158,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",wei zheng,Interference,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10159,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",wei zheng,Throughput,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10160,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",wei zheng,Algorithm design and analysis,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10161,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
10162,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",xidong wang,Quality of service,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10163,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",xidong wang,Games,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10164,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",xidong wang,Resource management,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10165,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",xidong wang,Base stations,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10166,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",xidong wang,Interference,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10167,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",xidong wang,Throughput,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10168,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",xidong wang,Algorithm design and analysis,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10169,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",zhiqun hu,Quality of service,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10170,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",zhiqun hu,Games,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10171,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",zhiqun hu,Resource management,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10172,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
10173,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",zhiqun hu,Base stations,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10174,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",zhiqun hu,Interference,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10175,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",zhiqun hu,Throughput,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10176,"In this paper, we consider the problem of interference mitigation in the downlink of multicell networks via base station coordination. In this paper, a simple and efficient scheme for interference management based on potential game is proposed. The main emphasis of this paper is placed on the problem of users' quality of service (QoS) in order to maximize the efficient throughput of system. Meanwhile, a pricing factor is introduced which is proportion to the co-channel interference to other base stations. Furthermore, an improved gradient projection rule with variable step size and Jacobi iterative algorithm are utilized to solve the optimization problem. Pareto optimal is verified by using ""price of anarchy"" as an optimize performance indicators in potential game. Simulation results show that our proposed scheme can significantly improve the performance of multicell networks.",zhiqun hu,Algorithm design and analysis,2014.0,10.1109/VTCSpring.2014.7022867,2014 IEEE 79th Vehicular Technology Conference (VTC Spring),Zhao2014,False,,IEEE,Not available,Coordinated Interference Management Based on Potential Game in MultiCell OFDMA Networks with Diverse QoS Guarantee,8d87ae73841d29ffecc65533aa80c068,https://ieeexplore.ieee.org/document/7022867/
10177,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",ehsan monsef,Nash equilibrium,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
10178,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",ehsan monsef,Global Positioning System,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
10179,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",ehsan monsef,Routing,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
10180,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",ehsan monsef,Quality of service,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
10181,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",ehsan monsef,Delays,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
10182,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",ehsan monsef,Cost function,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
10183,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
10184,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",ehsan monsef,Games,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
10185,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",tricha anjali,Nash equilibrium,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
10186,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",tricha anjali,Global Positioning System,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
10187,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",tricha anjali,Routing,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
10188,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",tricha anjali,Quality of service,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
10189,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",tricha anjali,Delays,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
10190,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",tricha anjali,Cost function,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
10191,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",tricha anjali,Games,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
10192,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",sanjiv kapoor,Nash equilibrium,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
10193,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",sanjiv kapoor,Global Positioning System,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
10194,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
10195,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",sanjiv kapoor,Routing,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
10196,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",sanjiv kapoor,Quality of service,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
10197,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",sanjiv kapoor,Delays,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
10198,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",sanjiv kapoor,Cost function,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
10199,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",sanjiv kapoor,Games,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
10200,"We consider a model of priced resource sharing that combines both queueing behavior and strategic behavior. We study a priority service model where a single server allocates its capacity to agents in proportion to their payment to the system, and users from different classes act to minimize the sum of their cost for processing delay and payment. As the exact processing time of this system is hard to compute and cannot be characterized in closed form, we introduce the notion of heavy traffic equilibrium as an approximation of the Nash equilibrium, derived by considering the asymptotic regime where the system load approaches capacity. We discuss efficiency and revenue, and in particular provide a bound for the price of anarchy of the heavy traffic equilibrium.",yu wu,resource sharing,2012.0,10.1109/JSAC.2012.121212,IEEE Journal on Selected Areas in Communications,Wu2012,False,,IEEE,Not available,Heavy Traffic Approximation of Equilibria in Resource Sharing Games,9a491a3b859471f8ada5a0833227b335,https://ieeexplore.ieee.org/document/6354278/
10201,"We consider a model of priced resource sharing that combines both queueing behavior and strategic behavior. We study a priority service model where a single server allocates its capacity to agents in proportion to their payment to the system, and users from different classes act to minimize the sum of their cost for processing delay and payment. As the exact processing time of this system is hard to compute and cannot be characterized in closed form, we introduce the notion of heavy traffic equilibrium as an approximation of the Nash equilibrium, derived by considering the asymptotic regime where the system load approaches capacity. We discuss efficiency and revenue, and in particular provide a bound for the price of anarchy of the heavy traffic equilibrium.",yu wu,discriminatory processor sharing,2012.0,10.1109/JSAC.2012.121212,IEEE Journal on Selected Areas in Communications,Wu2012,False,,IEEE,Not available,Heavy Traffic Approximation of Equilibria in Resource Sharing Games,9a491a3b859471f8ada5a0833227b335,https://ieeexplore.ieee.org/document/6354278/
10202,"We consider a model of priced resource sharing that combines both queueing behavior and strategic behavior. We study a priority service model where a single server allocates its capacity to agents in proportion to their payment to the system, and users from different classes act to minimize the sum of their cost for processing delay and payment. As the exact processing time of this system is hard to compute and cannot be characterized in closed form, we introduce the notion of heavy traffic equilibrium as an approximation of the Nash equilibrium, derived by considering the asymptotic regime where the system load approaches capacity. We discuss efficiency and revenue, and in particular provide a bound for the price of anarchy of the heavy traffic equilibrium.",yu wu,equilibrium,2012.0,10.1109/JSAC.2012.121212,IEEE Journal on Selected Areas in Communications,Wu2012,False,,IEEE,Not available,Heavy Traffic Approximation of Equilibria in Resource Sharing Games,9a491a3b859471f8ada5a0833227b335,https://ieeexplore.ieee.org/document/6354278/
10203,"We consider a model of priced resource sharing that combines both queueing behavior and strategic behavior. We study a priority service model where a single server allocates its capacity to agents in proportion to their payment to the system, and users from different classes act to minimize the sum of their cost for processing delay and payment. As the exact processing time of this system is hard to compute and cannot be characterized in closed form, we introduce the notion of heavy traffic equilibrium as an approximation of the Nash equilibrium, derived by considering the asymptotic regime where the system load approaches capacity. We discuss efficiency and revenue, and in particular provide a bound for the price of anarchy of the heavy traffic equilibrium.",yu wu,heavy traffic approximation,2012.0,10.1109/JSAC.2012.121212,IEEE Journal on Selected Areas in Communications,Wu2012,False,,IEEE,Not available,Heavy Traffic Approximation of Equilibria in Resource Sharing Games,9a491a3b859471f8ada5a0833227b335,https://ieeexplore.ieee.org/document/6354278/
10204,"We consider a model of priced resource sharing that combines both queueing behavior and strategic behavior. We study a priority service model where a single server allocates its capacity to agents in proportion to their payment to the system, and users from different classes act to minimize the sum of their cost for processing delay and payment. As the exact processing time of this system is hard to compute and cannot be characterized in closed form, we introduce the notion of heavy traffic equilibrium as an approximation of the Nash equilibrium, derived by considering the asymptotic regime where the system load approaches capacity. We discuss efficiency and revenue, and in particular provide a bound for the price of anarchy of the heavy traffic equilibrium.",loc bui,resource sharing,2012.0,10.1109/JSAC.2012.121212,IEEE Journal on Selected Areas in Communications,Wu2012,False,,IEEE,Not available,Heavy Traffic Approximation of Equilibria in Resource Sharing Games,9a491a3b859471f8ada5a0833227b335,https://ieeexplore.ieee.org/document/6354278/
10205,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
10206,"We consider a model of priced resource sharing that combines both queueing behavior and strategic behavior. We study a priority service model where a single server allocates its capacity to agents in proportion to their payment to the system, and users from different classes act to minimize the sum of their cost for processing delay and payment. As the exact processing time of this system is hard to compute and cannot be characterized in closed form, we introduce the notion of heavy traffic equilibrium as an approximation of the Nash equilibrium, derived by considering the asymptotic regime where the system load approaches capacity. We discuss efficiency and revenue, and in particular provide a bound for the price of anarchy of the heavy traffic equilibrium.",loc bui,discriminatory processor sharing,2012.0,10.1109/JSAC.2012.121212,IEEE Journal on Selected Areas in Communications,Wu2012,False,,IEEE,Not available,Heavy Traffic Approximation of Equilibria in Resource Sharing Games,9a491a3b859471f8ada5a0833227b335,https://ieeexplore.ieee.org/document/6354278/
10207,"We consider a model of priced resource sharing that combines both queueing behavior and strategic behavior. We study a priority service model where a single server allocates its capacity to agents in proportion to their payment to the system, and users from different classes act to minimize the sum of their cost for processing delay and payment. As the exact processing time of this system is hard to compute and cannot be characterized in closed form, we introduce the notion of heavy traffic equilibrium as an approximation of the Nash equilibrium, derived by considering the asymptotic regime where the system load approaches capacity. We discuss efficiency and revenue, and in particular provide a bound for the price of anarchy of the heavy traffic equilibrium.",loc bui,equilibrium,2012.0,10.1109/JSAC.2012.121212,IEEE Journal on Selected Areas in Communications,Wu2012,False,,IEEE,Not available,Heavy Traffic Approximation of Equilibria in Resource Sharing Games,9a491a3b859471f8ada5a0833227b335,https://ieeexplore.ieee.org/document/6354278/
10208,"We consider a model of priced resource sharing that combines both queueing behavior and strategic behavior. We study a priority service model where a single server allocates its capacity to agents in proportion to their payment to the system, and users from different classes act to minimize the sum of their cost for processing delay and payment. As the exact processing time of this system is hard to compute and cannot be characterized in closed form, we introduce the notion of heavy traffic equilibrium as an approximation of the Nash equilibrium, derived by considering the asymptotic regime where the system load approaches capacity. We discuss efficiency and revenue, and in particular provide a bound for the price of anarchy of the heavy traffic equilibrium.",loc bui,heavy traffic approximation,2012.0,10.1109/JSAC.2012.121212,IEEE Journal on Selected Areas in Communications,Wu2012,False,,IEEE,Not available,Heavy Traffic Approximation of Equilibria in Resource Sharing Games,9a491a3b859471f8ada5a0833227b335,https://ieeexplore.ieee.org/document/6354278/
10209,"We consider a model of priced resource sharing that combines both queueing behavior and strategic behavior. We study a priority service model where a single server allocates its capacity to agents in proportion to their payment to the system, and users from different classes act to minimize the sum of their cost for processing delay and payment. As the exact processing time of this system is hard to compute and cannot be characterized in closed form, we introduce the notion of heavy traffic equilibrium as an approximation of the Nash equilibrium, derived by considering the asymptotic regime where the system load approaches capacity. We discuss efficiency and revenue, and in particular provide a bound for the price of anarchy of the heavy traffic equilibrium.",ramesh johari,resource sharing,2012.0,10.1109/JSAC.2012.121212,IEEE Journal on Selected Areas in Communications,Wu2012,False,,IEEE,Not available,Heavy Traffic Approximation of Equilibria in Resource Sharing Games,9a491a3b859471f8ada5a0833227b335,https://ieeexplore.ieee.org/document/6354278/
10210,"We consider a model of priced resource sharing that combines both queueing behavior and strategic behavior. We study a priority service model where a single server allocates its capacity to agents in proportion to their payment to the system, and users from different classes act to minimize the sum of their cost for processing delay and payment. As the exact processing time of this system is hard to compute and cannot be characterized in closed form, we introduce the notion of heavy traffic equilibrium as an approximation of the Nash equilibrium, derived by considering the asymptotic regime where the system load approaches capacity. We discuss efficiency and revenue, and in particular provide a bound for the price of anarchy of the heavy traffic equilibrium.",ramesh johari,discriminatory processor sharing,2012.0,10.1109/JSAC.2012.121212,IEEE Journal on Selected Areas in Communications,Wu2012,False,,IEEE,Not available,Heavy Traffic Approximation of Equilibria in Resource Sharing Games,9a491a3b859471f8ada5a0833227b335,https://ieeexplore.ieee.org/document/6354278/
10211,"We consider a model of priced resource sharing that combines both queueing behavior and strategic behavior. We study a priority service model where a single server allocates its capacity to agents in proportion to their payment to the system, and users from different classes act to minimize the sum of their cost for processing delay and payment. As the exact processing time of this system is hard to compute and cannot be characterized in closed form, we introduce the notion of heavy traffic equilibrium as an approximation of the Nash equilibrium, derived by considering the asymptotic regime where the system load approaches capacity. We discuss efficiency and revenue, and in particular provide a bound for the price of anarchy of the heavy traffic equilibrium.",ramesh johari,equilibrium,2012.0,10.1109/JSAC.2012.121212,IEEE Journal on Selected Areas in Communications,Wu2012,False,,IEEE,Not available,Heavy Traffic Approximation of Equilibria in Resource Sharing Games,9a491a3b859471f8ada5a0833227b335,https://ieeexplore.ieee.org/document/6354278/
10212,"We consider a model of priced resource sharing that combines both queueing behavior and strategic behavior. We study a priority service model where a single server allocates its capacity to agents in proportion to their payment to the system, and users from different classes act to minimize the sum of their cost for processing delay and payment. As the exact processing time of this system is hard to compute and cannot be characterized in closed form, we introduce the notion of heavy traffic equilibrium as an approximation of the Nash equilibrium, derived by considering the asymptotic regime where the system load approaches capacity. We discuss efficiency and revenue, and in particular provide a bound for the price of anarchy of the heavy traffic equilibrium.",ramesh johari,heavy traffic approximation,2012.0,10.1109/JSAC.2012.121212,IEEE Journal on Selected Areas in Communications,Wu2012,False,,IEEE,Not available,Heavy Traffic Approximation of Equilibria in Resource Sharing Games,9a491a3b859471f8ada5a0833227b335,https://ieeexplore.ieee.org/document/6354278/
10213,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",gang wang,Price of Ararchy (PoA),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
10214,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",gang wang,Network Coding (NC),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
10215,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",gang wang,Average Cost Sharing (ACS),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
10216,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
10217,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
10218,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",gang wang,Affine Marginal Cost (AMC),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
10219,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",gang wang,Affine marginal cost (AMC),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
10220,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",gang wang,average cost sharing (ACS),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
10221,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",gang wang,network coding (NC),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
10222,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",gang wang,price of anarchy (PoA),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
10223,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",xia dai,Price of Ararchy (PoA),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
10224,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",xia dai,Network Coding (NC),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
10225,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",xia dai,Average Cost Sharing (ACS),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
10226,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",xia dai,Affine Marginal Cost (AMC),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
10227,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",xia dai,Affine marginal cost (AMC),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
10228,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
10229,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",xia dai,average cost sharing (ACS),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
10230,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",xia dai,network coding (NC),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
10231,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",xia dai,price of anarchy (PoA),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
10232,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",yonghui li,Price of Ararchy (PoA),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
10233,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",yonghui li,Network Coding (NC),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
10234,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",yonghui li,Average Cost Sharing (ACS),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
10235,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",yonghui li,Affine Marginal Cost (AMC),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
10236,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",yonghui li,Affine marginal cost (AMC),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
10237,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",yonghui li,average cost sharing (ACS),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
10238,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",yonghui li,network coding (NC),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
10239,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
10240,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",yonghui li,price of anarchy (PoA),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
10241,"This paper discusses a special type of multi-user communication scenario, in which users' utilities are linearly impacted by their competitors' actions. First, we explicitly characterize the Nash equilibrium and Pareto boundary of the achievable utility region. Second, the price of anarchy incurred by the non-collaborative Nash strategy is quantified. Third, to improve the performance in the non-cooperative scenarios, we investigate the properties of an alternative solution concept named conjectural equilibrium, in which individual users compensate for their lack of information by forming internal beliefs about their competitors. The global convergence of the best response and Jacobi update dynamics that achieve various conjectural equilibria is analyzed. It is shown that the Pareto boundaries of the investigated linearly coupled games can be sustained as stable conjectural equilibria if the belief functions are properly initialized. The investigated models apply to a variety of realistic applications encountered in the multiple access design, including wireless random access and flow control.",yi su,Nash equilibrium,2011.0,10.1109/TCOMM.2011.062111.090417,IEEE Transactions on Communications,Su2011,False,,IEEE,Not available,Linearly Coupled Communication Games,f0dfc5e3d6f04d4e03bb40448e923854,https://ieeexplore.ieee.org/document/5934673/
10242,"This paper discusses a special type of multi-user communication scenario, in which users' utilities are linearly impacted by their competitors' actions. First, we explicitly characterize the Nash equilibrium and Pareto boundary of the achievable utility region. Second, the price of anarchy incurred by the non-collaborative Nash strategy is quantified. Third, to improve the performance in the non-cooperative scenarios, we investigate the properties of an alternative solution concept named conjectural equilibrium, in which individual users compensate for their lack of information by forming internal beliefs about their competitors. The global convergence of the best response and Jacobi update dynamics that achieve various conjectural equilibria is analyzed. It is shown that the Pareto boundaries of the investigated linearly coupled games can be sustained as stable conjectural equilibria if the belief functions are properly initialized. The investigated models apply to a variety of realistic applications encountered in the multiple access design, including wireless random access and flow control.",yi su,Pareto-optimality,2011.0,10.1109/TCOMM.2011.062111.090417,IEEE Transactions on Communications,Su2011,False,,IEEE,Not available,Linearly Coupled Communication Games,f0dfc5e3d6f04d4e03bb40448e923854,https://ieeexplore.ieee.org/document/5934673/
10243,"This paper discusses a special type of multi-user communication scenario, in which users' utilities are linearly impacted by their competitors' actions. First, we explicitly characterize the Nash equilibrium and Pareto boundary of the achievable utility region. Second, the price of anarchy incurred by the non-collaborative Nash strategy is quantified. Third, to improve the performance in the non-cooperative scenarios, we investigate the properties of an alternative solution concept named conjectural equilibrium, in which individual users compensate for their lack of information by forming internal beliefs about their competitors. The global convergence of the best response and Jacobi update dynamics that achieve various conjectural equilibria is analyzed. It is shown that the Pareto boundaries of the investigated linearly coupled games can be sustained as stable conjectural equilibria if the belief functions are properly initialized. The investigated models apply to a variety of realistic applications encountered in the multiple access design, including wireless random access and flow control.",yi su,conjectural equilibrium,2011.0,10.1109/TCOMM.2011.062111.090417,IEEE Transactions on Communications,Su2011,False,,IEEE,Not available,Linearly Coupled Communication Games,f0dfc5e3d6f04d4e03bb40448e923854,https://ieeexplore.ieee.org/document/5934673/
10244,"This paper discusses a special type of multi-user communication scenario, in which users' utilities are linearly impacted by their competitors' actions. First, we explicitly characterize the Nash equilibrium and Pareto boundary of the achievable utility region. Second, the price of anarchy incurred by the non-collaborative Nash strategy is quantified. Third, to improve the performance in the non-cooperative scenarios, we investigate the properties of an alternative solution concept named conjectural equilibrium, in which individual users compensate for their lack of information by forming internal beliefs about their competitors. The global convergence of the best response and Jacobi update dynamics that achieve various conjectural equilibria is analyzed. It is shown that the Pareto boundaries of the investigated linearly coupled games can be sustained as stable conjectural equilibria if the belief functions are properly initialized. The investigated models apply to a variety of realistic applications encountered in the multiple access design, including wireless random access and flow control.",yi su,non-cooperative games,2011.0,10.1109/TCOMM.2011.062111.090417,IEEE Transactions on Communications,Su2011,False,,IEEE,Not available,Linearly Coupled Communication Games,f0dfc5e3d6f04d4e03bb40448e923854,https://ieeexplore.ieee.org/document/5934673/
10245,"This paper discusses a special type of multi-user communication scenario, in which users' utilities are linearly impacted by their competitors' actions. First, we explicitly characterize the Nash equilibrium and Pareto boundary of the achievable utility region. Second, the price of anarchy incurred by the non-collaborative Nash strategy is quantified. Third, to improve the performance in the non-cooperative scenarios, we investigate the properties of an alternative solution concept named conjectural equilibrium, in which individual users compensate for their lack of information by forming internal beliefs about their competitors. The global convergence of the best response and Jacobi update dynamics that achieve various conjectural equilibria is analyzed. It is shown that the Pareto boundaries of the investigated linearly coupled games can be sustained as stable conjectural equilibria if the belief functions are properly initialized. The investigated models apply to a variety of realistic applications encountered in the multiple access design, including wireless random access and flow control.",mihaela schaar,Nash equilibrium,2011.0,10.1109/TCOMM.2011.062111.090417,IEEE Transactions on Communications,Su2011,False,,IEEE,Not available,Linearly Coupled Communication Games,f0dfc5e3d6f04d4e03bb40448e923854,https://ieeexplore.ieee.org/document/5934673/
10246,"This paper discusses a special type of multi-user communication scenario, in which users' utilities are linearly impacted by their competitors' actions. First, we explicitly characterize the Nash equilibrium and Pareto boundary of the achievable utility region. Second, the price of anarchy incurred by the non-collaborative Nash strategy is quantified. Third, to improve the performance in the non-cooperative scenarios, we investigate the properties of an alternative solution concept named conjectural equilibrium, in which individual users compensate for their lack of information by forming internal beliefs about their competitors. The global convergence of the best response and Jacobi update dynamics that achieve various conjectural equilibria is analyzed. It is shown that the Pareto boundaries of the investigated linearly coupled games can be sustained as stable conjectural equilibria if the belief functions are properly initialized. The investigated models apply to a variety of realistic applications encountered in the multiple access design, including wireless random access and flow control.",mihaela schaar,Pareto-optimality,2011.0,10.1109/TCOMM.2011.062111.090417,IEEE Transactions on Communications,Su2011,False,,IEEE,Not available,Linearly Coupled Communication Games,f0dfc5e3d6f04d4e03bb40448e923854,https://ieeexplore.ieee.org/document/5934673/
10247,"This paper discusses a special type of multi-user communication scenario, in which users' utilities are linearly impacted by their competitors' actions. First, we explicitly characterize the Nash equilibrium and Pareto boundary of the achievable utility region. Second, the price of anarchy incurred by the non-collaborative Nash strategy is quantified. Third, to improve the performance in the non-cooperative scenarios, we investigate the properties of an alternative solution concept named conjectural equilibrium, in which individual users compensate for their lack of information by forming internal beliefs about their competitors. The global convergence of the best response and Jacobi update dynamics that achieve various conjectural equilibria is analyzed. It is shown that the Pareto boundaries of the investigated linearly coupled games can be sustained as stable conjectural equilibria if the belief functions are properly initialized. The investigated models apply to a variety of realistic applications encountered in the multiple access design, including wireless random access and flow control.",mihaela schaar,conjectural equilibrium,2011.0,10.1109/TCOMM.2011.062111.090417,IEEE Transactions on Communications,Su2011,False,,IEEE,Not available,Linearly Coupled Communication Games,f0dfc5e3d6f04d4e03bb40448e923854,https://ieeexplore.ieee.org/document/5934673/
10248,"This paper discusses a special type of multi-user communication scenario, in which users' utilities are linearly impacted by their competitors' actions. First, we explicitly characterize the Nash equilibrium and Pareto boundary of the achievable utility region. Second, the price of anarchy incurred by the non-collaborative Nash strategy is quantified. Third, to improve the performance in the non-cooperative scenarios, we investigate the properties of an alternative solution concept named conjectural equilibrium, in which individual users compensate for their lack of information by forming internal beliefs about their competitors. The global convergence of the best response and Jacobi update dynamics that achieve various conjectural equilibria is analyzed. It is shown that the Pareto boundaries of the investigated linearly coupled games can be sustained as stable conjectural equilibria if the belief functions are properly initialized. The investigated models apply to a variety of realistic applications encountered in the multiple access design, including wireless random access and flow control.",mihaela schaar,non-cooperative games,2011.0,10.1109/TCOMM.2011.062111.090417,IEEE Transactions on Communications,Su2011,False,,IEEE,Not available,Linearly Coupled Communication Games,f0dfc5e3d6f04d4e03bb40448e923854,https://ieeexplore.ieee.org/document/5934673/
10249,"Increased variability in power generation due to large scale integration of renewable energy sources such as wind and solar power is a significant technical challenge in power systems operations and control. In addition, there is a compelling value in reducing the peak demand since it occurs only for a small fraction of time, while the power system is designed to reliably satisfy the peak demand. One promising approach to reduce variability of renewable generation and peak demand is to harness the inherent flexibility of electric power loads of consumers. Efficient control techniques are required to manage flexibility in consumer demands. Advancements in sensing, communications and computational technologies infused into the power system resulting in the cyber-physical-social electric grid, are creating opportunities for novel control solutions. In this paper, we first formulate a centralized demand side management approach. Next, we consider a decentralized approach for controlling the loads where the flexible load consumers play a non-cooperative game among each other. We show that Nash equilibria exist for this game. Our main technical result is that the demand response game in decentralized approach has the property of being a valid monotone utility game. This in turn leads to robust lower bounds on the price of anarchy (POA) for our game.",pratyush chakraborty,Games,2014.0,10.1109/SmartGridComm.2014.7007720,2014 IEEE International Conference on Smart Grid Communications (SmartGridComm),Chakraborty2014,False,,IEEE,Not available,A demand response game and its robust price of anarchy,251780ce58a1c0f564342aaae2120172,https://ieeexplore.ieee.org/document/7007720/
10250,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
10251,"Increased variability in power generation due to large scale integration of renewable energy sources such as wind and solar power is a significant technical challenge in power systems operations and control. In addition, there is a compelling value in reducing the peak demand since it occurs only for a small fraction of time, while the power system is designed to reliably satisfy the peak demand. One promising approach to reduce variability of renewable generation and peak demand is to harness the inherent flexibility of electric power loads of consumers. Efficient control techniques are required to manage flexibility in consumer demands. Advancements in sensing, communications and computational technologies infused into the power system resulting in the cyber-physical-social electric grid, are creating opportunities for novel control solutions. In this paper, we first formulate a centralized demand side management approach. Next, we consider a decentralized approach for controlling the loads where the flexible load consumers play a non-cooperative game among each other. We show that Nash equilibria exist for this game. Our main technical result is that the demand response game in decentralized approach has the property of being a valid monotone utility game. This in turn leads to robust lower bounds on the price of anarchy (POA) for our game.",pratyush chakraborty,Power demand,2014.0,10.1109/SmartGridComm.2014.7007720,2014 IEEE International Conference on Smart Grid Communications (SmartGridComm),Chakraborty2014,False,,IEEE,Not available,A demand response game and its robust price of anarchy,251780ce58a1c0f564342aaae2120172,https://ieeexplore.ieee.org/document/7007720/
10252,"Increased variability in power generation due to large scale integration of renewable energy sources such as wind and solar power is a significant technical challenge in power systems operations and control. In addition, there is a compelling value in reducing the peak demand since it occurs only for a small fraction of time, while the power system is designed to reliably satisfy the peak demand. One promising approach to reduce variability of renewable generation and peak demand is to harness the inherent flexibility of electric power loads of consumers. Efficient control techniques are required to manage flexibility in consumer demands. Advancements in sensing, communications and computational technologies infused into the power system resulting in the cyber-physical-social electric grid, are creating opportunities for novel control solutions. In this paper, we first formulate a centralized demand side management approach. Next, we consider a decentralized approach for controlling the loads where the flexible load consumers play a non-cooperative game among each other. We show that Nash equilibria exist for this game. Our main technical result is that the demand response game in decentralized approach has the property of being a valid monotone utility game. This in turn leads to robust lower bounds on the price of anarchy (POA) for our game.",pratyush chakraborty,Load management,2014.0,10.1109/SmartGridComm.2014.7007720,2014 IEEE International Conference on Smart Grid Communications (SmartGridComm),Chakraborty2014,False,,IEEE,Not available,A demand response game and its robust price of anarchy,251780ce58a1c0f564342aaae2120172,https://ieeexplore.ieee.org/document/7007720/
10253,"Increased variability in power generation due to large scale integration of renewable energy sources such as wind and solar power is a significant technical challenge in power systems operations and control. In addition, there is a compelling value in reducing the peak demand since it occurs only for a small fraction of time, while the power system is designed to reliably satisfy the peak demand. One promising approach to reduce variability of renewable generation and peak demand is to harness the inherent flexibility of electric power loads of consumers. Efficient control techniques are required to manage flexibility in consumer demands. Advancements in sensing, communications and computational technologies infused into the power system resulting in the cyber-physical-social electric grid, are creating opportunities for novel control solutions. In this paper, we first formulate a centralized demand side management approach. Next, we consider a decentralized approach for controlling the loads where the flexible load consumers play a non-cooperative game among each other. We show that Nash equilibria exist for this game. Our main technical result is that the demand response game in decentralized approach has the property of being a valid monotone utility game. This in turn leads to robust lower bounds on the price of anarchy (POA) for our game.",pratyush chakraborty,Schedules,2014.0,10.1109/SmartGridComm.2014.7007720,2014 IEEE International Conference on Smart Grid Communications (SmartGridComm),Chakraborty2014,False,,IEEE,Not available,A demand response game and its robust price of anarchy,251780ce58a1c0f564342aaae2120172,https://ieeexplore.ieee.org/document/7007720/
10254,"Increased variability in power generation due to large scale integration of renewable energy sources such as wind and solar power is a significant technical challenge in power systems operations and control. In addition, there is a compelling value in reducing the peak demand since it occurs only for a small fraction of time, while the power system is designed to reliably satisfy the peak demand. One promising approach to reduce variability of renewable generation and peak demand is to harness the inherent flexibility of electric power loads of consumers. Efficient control techniques are required to manage flexibility in consumer demands. Advancements in sensing, communications and computational technologies infused into the power system resulting in the cyber-physical-social electric grid, are creating opportunities for novel control solutions. In this paper, we first formulate a centralized demand side management approach. Next, we consider a decentralized approach for controlling the loads where the flexible load consumers play a non-cooperative game among each other. We show that Nash equilibria exist for this game. Our main technical result is that the demand response game in decentralized approach has the property of being a valid monotone utility game. This in turn leads to robust lower bounds on the price of anarchy (POA) for our game.",pratyush chakraborty,Centralized control,2014.0,10.1109/SmartGridComm.2014.7007720,2014 IEEE International Conference on Smart Grid Communications (SmartGridComm),Chakraborty2014,False,,IEEE,Not available,A demand response game and its robust price of anarchy,251780ce58a1c0f564342aaae2120172,https://ieeexplore.ieee.org/document/7007720/
10255,"Increased variability in power generation due to large scale integration of renewable energy sources such as wind and solar power is a significant technical challenge in power systems operations and control. In addition, there is a compelling value in reducing the peak demand since it occurs only for a small fraction of time, while the power system is designed to reliably satisfy the peak demand. One promising approach to reduce variability of renewable generation and peak demand is to harness the inherent flexibility of electric power loads of consumers. Efficient control techniques are required to manage flexibility in consumer demands. Advancements in sensing, communications and computational technologies infused into the power system resulting in the cyber-physical-social electric grid, are creating opportunities for novel control solutions. In this paper, we first formulate a centralized demand side management approach. Next, we consider a decentralized approach for controlling the loads where the flexible load consumers play a non-cooperative game among each other. We show that Nash equilibria exist for this game. Our main technical result is that the demand response game in decentralized approach has the property of being a valid monotone utility game. This in turn leads to robust lower bounds on the price of anarchy (POA) for our game.",pratyush chakraborty,Nash equilibrium,2014.0,10.1109/SmartGridComm.2014.7007720,2014 IEEE International Conference on Smart Grid Communications (SmartGridComm),Chakraborty2014,False,,IEEE,Not available,A demand response game and its robust price of anarchy,251780ce58a1c0f564342aaae2120172,https://ieeexplore.ieee.org/document/7007720/
10256,"Increased variability in power generation due to large scale integration of renewable energy sources such as wind and solar power is a significant technical challenge in power systems operations and control. In addition, there is a compelling value in reducing the peak demand since it occurs only for a small fraction of time, while the power system is designed to reliably satisfy the peak demand. One promising approach to reduce variability of renewable generation and peak demand is to harness the inherent flexibility of electric power loads of consumers. Efficient control techniques are required to manage flexibility in consumer demands. Advancements in sensing, communications and computational technologies infused into the power system resulting in the cyber-physical-social electric grid, are creating opportunities for novel control solutions. In this paper, we first formulate a centralized demand side management approach. Next, we consider a decentralized approach for controlling the loads where the flexible load consumers play a non-cooperative game among each other. We show that Nash equilibria exist for this game. Our main technical result is that the demand response game in decentralized approach has the property of being a valid monotone utility game. This in turn leads to robust lower bounds on the price of anarchy (POA) for our game.",pramod khargonekar,Games,2014.0,10.1109/SmartGridComm.2014.7007720,2014 IEEE International Conference on Smart Grid Communications (SmartGridComm),Chakraborty2014,False,,IEEE,Not available,A demand response game and its robust price of anarchy,251780ce58a1c0f564342aaae2120172,https://ieeexplore.ieee.org/document/7007720/
10257,"Increased variability in power generation due to large scale integration of renewable energy sources such as wind and solar power is a significant technical challenge in power systems operations and control. In addition, there is a compelling value in reducing the peak demand since it occurs only for a small fraction of time, while the power system is designed to reliably satisfy the peak demand. One promising approach to reduce variability of renewable generation and peak demand is to harness the inherent flexibility of electric power loads of consumers. Efficient control techniques are required to manage flexibility in consumer demands. Advancements in sensing, communications and computational technologies infused into the power system resulting in the cyber-physical-social electric grid, are creating opportunities for novel control solutions. In this paper, we first formulate a centralized demand side management approach. Next, we consider a decentralized approach for controlling the loads where the flexible load consumers play a non-cooperative game among each other. We show that Nash equilibria exist for this game. Our main technical result is that the demand response game in decentralized approach has the property of being a valid monotone utility game. This in turn leads to robust lower bounds on the price of anarchy (POA) for our game.",pramod khargonekar,Power demand,2014.0,10.1109/SmartGridComm.2014.7007720,2014 IEEE International Conference on Smart Grid Communications (SmartGridComm),Chakraborty2014,False,,IEEE,Not available,A demand response game and its robust price of anarchy,251780ce58a1c0f564342aaae2120172,https://ieeexplore.ieee.org/document/7007720/
10258,"Increased variability in power generation due to large scale integration of renewable energy sources such as wind and solar power is a significant technical challenge in power systems operations and control. In addition, there is a compelling value in reducing the peak demand since it occurs only for a small fraction of time, while the power system is designed to reliably satisfy the peak demand. One promising approach to reduce variability of renewable generation and peak demand is to harness the inherent flexibility of electric power loads of consumers. Efficient control techniques are required to manage flexibility in consumer demands. Advancements in sensing, communications and computational technologies infused into the power system resulting in the cyber-physical-social electric grid, are creating opportunities for novel control solutions. In this paper, we first formulate a centralized demand side management approach. Next, we consider a decentralized approach for controlling the loads where the flexible load consumers play a non-cooperative game among each other. We show that Nash equilibria exist for this game. Our main technical result is that the demand response game in decentralized approach has the property of being a valid monotone utility game. This in turn leads to robust lower bounds on the price of anarchy (POA) for our game.",pramod khargonekar,Load management,2014.0,10.1109/SmartGridComm.2014.7007720,2014 IEEE International Conference on Smart Grid Communications (SmartGridComm),Chakraborty2014,False,,IEEE,Not available,A demand response game and its robust price of anarchy,251780ce58a1c0f564342aaae2120172,https://ieeexplore.ieee.org/document/7007720/
10259,"Increased variability in power generation due to large scale integration of renewable energy sources such as wind and solar power is a significant technical challenge in power systems operations and control. In addition, there is a compelling value in reducing the peak demand since it occurs only for a small fraction of time, while the power system is designed to reliably satisfy the peak demand. One promising approach to reduce variability of renewable generation and peak demand is to harness the inherent flexibility of electric power loads of consumers. Efficient control techniques are required to manage flexibility in consumer demands. Advancements in sensing, communications and computational technologies infused into the power system resulting in the cyber-physical-social electric grid, are creating opportunities for novel control solutions. In this paper, we first formulate a centralized demand side management approach. Next, we consider a decentralized approach for controlling the loads where the flexible load consumers play a non-cooperative game among each other. We show that Nash equilibria exist for this game. Our main technical result is that the demand response game in decentralized approach has the property of being a valid monotone utility game. This in turn leads to robust lower bounds on the price of anarchy (POA) for our game.",pramod khargonekar,Schedules,2014.0,10.1109/SmartGridComm.2014.7007720,2014 IEEE International Conference on Smart Grid Communications (SmartGridComm),Chakraborty2014,False,,IEEE,Not available,A demand response game and its robust price of anarchy,251780ce58a1c0f564342aaae2120172,https://ieeexplore.ieee.org/document/7007720/
10260,"Increased variability in power generation due to large scale integration of renewable energy sources such as wind and solar power is a significant technical challenge in power systems operations and control. In addition, there is a compelling value in reducing the peak demand since it occurs only for a small fraction of time, while the power system is designed to reliably satisfy the peak demand. One promising approach to reduce variability of renewable generation and peak demand is to harness the inherent flexibility of electric power loads of consumers. Efficient control techniques are required to manage flexibility in consumer demands. Advancements in sensing, communications and computational technologies infused into the power system resulting in the cyber-physical-social electric grid, are creating opportunities for novel control solutions. In this paper, we first formulate a centralized demand side management approach. Next, we consider a decentralized approach for controlling the loads where the flexible load consumers play a non-cooperative game among each other. We show that Nash equilibria exist for this game. Our main technical result is that the demand response game in decentralized approach has the property of being a valid monotone utility game. This in turn leads to robust lower bounds on the price of anarchy (POA) for our game.",pramod khargonekar,Centralized control,2014.0,10.1109/SmartGridComm.2014.7007720,2014 IEEE International Conference on Smart Grid Communications (SmartGridComm),Chakraborty2014,False,,IEEE,Not available,A demand response game and its robust price of anarchy,251780ce58a1c0f564342aaae2120172,https://ieeexplore.ieee.org/document/7007720/
10261,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
10262,"Increased variability in power generation due to large scale integration of renewable energy sources such as wind and solar power is a significant technical challenge in power systems operations and control. In addition, there is a compelling value in reducing the peak demand since it occurs only for a small fraction of time, while the power system is designed to reliably satisfy the peak demand. One promising approach to reduce variability of renewable generation and peak demand is to harness the inherent flexibility of electric power loads of consumers. Efficient control techniques are required to manage flexibility in consumer demands. Advancements in sensing, communications and computational technologies infused into the power system resulting in the cyber-physical-social electric grid, are creating opportunities for novel control solutions. In this paper, we first formulate a centralized demand side management approach. Next, we consider a decentralized approach for controlling the loads where the flexible load consumers play a non-cooperative game among each other. We show that Nash equilibria exist for this game. Our main technical result is that the demand response game in decentralized approach has the property of being a valid monotone utility game. This in turn leads to robust lower bounds on the price of anarchy (POA) for our game.",pramod khargonekar,Nash equilibrium,2014.0,10.1109/SmartGridComm.2014.7007720,2014 IEEE International Conference on Smart Grid Communications (SmartGridComm),Chakraborty2014,False,,IEEE,Not available,A demand response game and its robust price of anarchy,251780ce58a1c0f564342aaae2120172,https://ieeexplore.ieee.org/document/7007720/
10263,"Server selection plays an essential role in content replication networks, such as peer-to-peer (P2P) and content delivery networks (CDNs). In this paper, we perform an analytical investigation of the strengths and weaknesses of existing server selection policies, based initially on an &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 processor sharing (PS) queueing-theoretic model. We develop a theoretical benchmark to evaluate the performance of two general server selection policies, referred to as EQ_DELAY and EQ_LOAD, which characterize a wide range of existing server selection algorithms. We find that EQ_LOAD achieves an average delay always higher than or equal to that of EQ_DELAY. A key theoretical result of this paper is that in an &lt;i&gt;N&lt;/i&gt;-server system, the worst case ratio between the average delay of EQ_DELAY or EQ_LOAD and the minimal average delay (obtained from the benchmark) is precisely &lt;i&gt;N&lt;/i&gt;. We constructively show how this worst case scenario can arise in highly heterogeneous systems. This result, when interpreted in the context of selfish routing, means that the price of anarchy in unbounded delay networks depends on the topology, and can potentially be very large. Our analytical findings are extended in asymptotic regimes to the &lt;i&gt;G&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 first-come first-serve and multi-class &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1-PS models and supported by simulations run for various arrival and service processes, scheduling disciplines, and workload exhibiting temporal locality. These results indicate that our analysis is applicable to realistic scenarios.",tao wu,Content delivery networks,2008.0,10.1109/TNET.2007.909752,IEEE/ACM Transactions on Networking,Wu2008,False,,IEEE,Not available,A Comparative Analysis of Server Selection in Content Replication Networks,19c4fbd837166c20b209d320503781c4,https://ieeexplore.ieee.org/document/4469924/
10264,"Server selection plays an essential role in content replication networks, such as peer-to-peer (P2P) and content delivery networks (CDNs). In this paper, we perform an analytical investigation of the strengths and weaknesses of existing server selection policies, based initially on an &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 processor sharing (PS) queueing-theoretic model. We develop a theoretical benchmark to evaluate the performance of two general server selection policies, referred to as EQ_DELAY and EQ_LOAD, which characterize a wide range of existing server selection algorithms. We find that EQ_LOAD achieves an average delay always higher than or equal to that of EQ_DELAY. A key theoretical result of this paper is that in an &lt;i&gt;N&lt;/i&gt;-server system, the worst case ratio between the average delay of EQ_DELAY or EQ_LOAD and the minimal average delay (obtained from the benchmark) is precisely &lt;i&gt;N&lt;/i&gt;. We constructively show how this worst case scenario can arise in highly heterogeneous systems. This result, when interpreted in the context of selfish routing, means that the price of anarchy in unbounded delay networks depends on the topology, and can potentially be very large. Our analytical findings are extended in asymptotic regimes to the &lt;i&gt;G&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 first-come first-serve and multi-class &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1-PS models and supported by simulations run for various arrival and service processes, scheduling disciplines, and workload exhibiting temporal locality. These results indicate that our analysis is applicable to realistic scenarios.",tao wu,distributed systems,2008.0,10.1109/TNET.2007.909752,IEEE/ACM Transactions on Networking,Wu2008,False,,IEEE,Not available,A Comparative Analysis of Server Selection in Content Replication Networks,19c4fbd837166c20b209d320503781c4,https://ieeexplore.ieee.org/document/4469924/
10265,"Server selection plays an essential role in content replication networks, such as peer-to-peer (P2P) and content delivery networks (CDNs). In this paper, we perform an analytical investigation of the strengths and weaknesses of existing server selection policies, based initially on an &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 processor sharing (PS) queueing-theoretic model. We develop a theoretical benchmark to evaluate the performance of two general server selection policies, referred to as EQ_DELAY and EQ_LOAD, which characterize a wide range of existing server selection algorithms. We find that EQ_LOAD achieves an average delay always higher than or equal to that of EQ_DELAY. A key theoretical result of this paper is that in an &lt;i&gt;N&lt;/i&gt;-server system, the worst case ratio between the average delay of EQ_DELAY or EQ_LOAD and the minimal average delay (obtained from the benchmark) is precisely &lt;i&gt;N&lt;/i&gt;. We constructively show how this worst case scenario can arise in highly heterogeneous systems. This result, when interpreted in the context of selfish routing, means that the price of anarchy in unbounded delay networks depends on the topology, and can potentially be very large. Our analytical findings are extended in asymptotic regimes to the &lt;i&gt;G&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 first-come first-serve and multi-class &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1-PS models and supported by simulations run for various arrival and service processes, scheduling disciplines, and workload exhibiting temporal locality. These results indicate that our analysis is applicable to realistic scenarios.",tao wu,game theory,2008.0,10.1109/TNET.2007.909752,IEEE/ACM Transactions on Networking,Wu2008,False,,IEEE,Not available,A Comparative Analysis of Server Selection in Content Replication Networks,19c4fbd837166c20b209d320503781c4,https://ieeexplore.ieee.org/document/4469924/
10266,"Server selection plays an essential role in content replication networks, such as peer-to-peer (P2P) and content delivery networks (CDNs). In this paper, we perform an analytical investigation of the strengths and weaknesses of existing server selection policies, based initially on an &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 processor sharing (PS) queueing-theoretic model. We develop a theoretical benchmark to evaluate the performance of two general server selection policies, referred to as EQ_DELAY and EQ_LOAD, which characterize a wide range of existing server selection algorithms. We find that EQ_LOAD achieves an average delay always higher than or equal to that of EQ_DELAY. A key theoretical result of this paper is that in an &lt;i&gt;N&lt;/i&gt;-server system, the worst case ratio between the average delay of EQ_DELAY or EQ_LOAD and the minimal average delay (obtained from the benchmark) is precisely &lt;i&gt;N&lt;/i&gt;. We constructively show how this worst case scenario can arise in highly heterogeneous systems. This result, when interpreted in the context of selfish routing, means that the price of anarchy in unbounded delay networks depends on the topology, and can potentially be very large. Our analytical findings are extended in asymptotic regimes to the &lt;i&gt;G&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 first-come first-serve and multi-class &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1-PS models and supported by simulations run for various arrival and service processes, scheduling disciplines, and workload exhibiting temporal locality. These results indicate that our analysis is applicable to realistic scenarios.",tao wu,load balancing,2008.0,10.1109/TNET.2007.909752,IEEE/ACM Transactions on Networking,Wu2008,False,,IEEE,Not available,A Comparative Analysis of Server Selection in Content Replication Networks,19c4fbd837166c20b209d320503781c4,https://ieeexplore.ieee.org/document/4469924/
10267,"Server selection plays an essential role in content replication networks, such as peer-to-peer (P2P) and content delivery networks (CDNs). In this paper, we perform an analytical investigation of the strengths and weaknesses of existing server selection policies, based initially on an &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 processor sharing (PS) queueing-theoretic model. We develop a theoretical benchmark to evaluate the performance of two general server selection policies, referred to as EQ_DELAY and EQ_LOAD, which characterize a wide range of existing server selection algorithms. We find that EQ_LOAD achieves an average delay always higher than or equal to that of EQ_DELAY. A key theoretical result of this paper is that in an &lt;i&gt;N&lt;/i&gt;-server system, the worst case ratio between the average delay of EQ_DELAY or EQ_LOAD and the minimal average delay (obtained from the benchmark) is precisely &lt;i&gt;N&lt;/i&gt;. We constructively show how this worst case scenario can arise in highly heterogeneous systems. This result, when interpreted in the context of selfish routing, means that the price of anarchy in unbounded delay networks depends on the topology, and can potentially be very large. Our analytical findings are extended in asymptotic regimes to the &lt;i&gt;G&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 first-come first-serve and multi-class &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1-PS models and supported by simulations run for various arrival and service processes, scheduling disciplines, and workload exhibiting temporal locality. These results indicate that our analysis is applicable to realistic scenarios.",tao wu,peer-to-peer networks,2008.0,10.1109/TNET.2007.909752,IEEE/ACM Transactions on Networking,Wu2008,False,,IEEE,Not available,A Comparative Analysis of Server Selection in Content Replication Networks,19c4fbd837166c20b209d320503781c4,https://ieeexplore.ieee.org/document/4469924/
10268,"Server selection plays an essential role in content replication networks, such as peer-to-peer (P2P) and content delivery networks (CDNs). In this paper, we perform an analytical investigation of the strengths and weaknesses of existing server selection policies, based initially on an &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 processor sharing (PS) queueing-theoretic model. We develop a theoretical benchmark to evaluate the performance of two general server selection policies, referred to as EQ_DELAY and EQ_LOAD, which characterize a wide range of existing server selection algorithms. We find that EQ_LOAD achieves an average delay always higher than or equal to that of EQ_DELAY. A key theoretical result of this paper is that in an &lt;i&gt;N&lt;/i&gt;-server system, the worst case ratio between the average delay of EQ_DELAY or EQ_LOAD and the minimal average delay (obtained from the benchmark) is precisely &lt;i&gt;N&lt;/i&gt;. We constructively show how this worst case scenario can arise in highly heterogeneous systems. This result, when interpreted in the context of selfish routing, means that the price of anarchy in unbounded delay networks depends on the topology, and can potentially be very large. Our analytical findings are extended in asymptotic regimes to the &lt;i&gt;G&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 first-come first-serve and multi-class &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1-PS models and supported by simulations run for various arrival and service processes, scheduling disciplines, and workload exhibiting temporal locality. These results indicate that our analysis is applicable to realistic scenarios.",tao wu,price of anarchy,2008.0,10.1109/TNET.2007.909752,IEEE/ACM Transactions on Networking,Wu2008,False,,IEEE,Not available,A Comparative Analysis of Server Selection in Content Replication Networks,19c4fbd837166c20b209d320503781c4,https://ieeexplore.ieee.org/document/4469924/
10269,"Server selection plays an essential role in content replication networks, such as peer-to-peer (P2P) and content delivery networks (CDNs). In this paper, we perform an analytical investigation of the strengths and weaknesses of existing server selection policies, based initially on an &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 processor sharing (PS) queueing-theoretic model. We develop a theoretical benchmark to evaluate the performance of two general server selection policies, referred to as EQ_DELAY and EQ_LOAD, which characterize a wide range of existing server selection algorithms. We find that EQ_LOAD achieves an average delay always higher than or equal to that of EQ_DELAY. A key theoretical result of this paper is that in an &lt;i&gt;N&lt;/i&gt;-server system, the worst case ratio between the average delay of EQ_DELAY or EQ_LOAD and the minimal average delay (obtained from the benchmark) is precisely &lt;i&gt;N&lt;/i&gt;. We constructively show how this worst case scenario can arise in highly heterogeneous systems. This result, when interpreted in the context of selfish routing, means that the price of anarchy in unbounded delay networks depends on the topology, and can potentially be very large. Our analytical findings are extended in asymptotic regimes to the &lt;i&gt;G&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 first-come first-serve and multi-class &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1-PS models and supported by simulations run for various arrival and service processes, scheduling disciplines, and workload exhibiting temporal locality. These results indicate that our analysis is applicable to realistic scenarios.",david starobinski,Content delivery networks,2008.0,10.1109/TNET.2007.909752,IEEE/ACM Transactions on Networking,Wu2008,False,,IEEE,Not available,A Comparative Analysis of Server Selection in Content Replication Networks,19c4fbd837166c20b209d320503781c4,https://ieeexplore.ieee.org/document/4469924/
10270,"Server selection plays an essential role in content replication networks, such as peer-to-peer (P2P) and content delivery networks (CDNs). In this paper, we perform an analytical investigation of the strengths and weaknesses of existing server selection policies, based initially on an &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 processor sharing (PS) queueing-theoretic model. We develop a theoretical benchmark to evaluate the performance of two general server selection policies, referred to as EQ_DELAY and EQ_LOAD, which characterize a wide range of existing server selection algorithms. We find that EQ_LOAD achieves an average delay always higher than or equal to that of EQ_DELAY. A key theoretical result of this paper is that in an &lt;i&gt;N&lt;/i&gt;-server system, the worst case ratio between the average delay of EQ_DELAY or EQ_LOAD and the minimal average delay (obtained from the benchmark) is precisely &lt;i&gt;N&lt;/i&gt;. We constructively show how this worst case scenario can arise in highly heterogeneous systems. This result, when interpreted in the context of selfish routing, means that the price of anarchy in unbounded delay networks depends on the topology, and can potentially be very large. Our analytical findings are extended in asymptotic regimes to the &lt;i&gt;G&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 first-come first-serve and multi-class &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1-PS models and supported by simulations run for various arrival and service processes, scheduling disciplines, and workload exhibiting temporal locality. These results indicate that our analysis is applicable to realistic scenarios.",david starobinski,distributed systems,2008.0,10.1109/TNET.2007.909752,IEEE/ACM Transactions on Networking,Wu2008,False,,IEEE,Not available,A Comparative Analysis of Server Selection in Content Replication Networks,19c4fbd837166c20b209d320503781c4,https://ieeexplore.ieee.org/document/4469924/
10271,"Server selection plays an essential role in content replication networks, such as peer-to-peer (P2P) and content delivery networks (CDNs). In this paper, we perform an analytical investigation of the strengths and weaknesses of existing server selection policies, based initially on an &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 processor sharing (PS) queueing-theoretic model. We develop a theoretical benchmark to evaluate the performance of two general server selection policies, referred to as EQ_DELAY and EQ_LOAD, which characterize a wide range of existing server selection algorithms. We find that EQ_LOAD achieves an average delay always higher than or equal to that of EQ_DELAY. A key theoretical result of this paper is that in an &lt;i&gt;N&lt;/i&gt;-server system, the worst case ratio between the average delay of EQ_DELAY or EQ_LOAD and the minimal average delay (obtained from the benchmark) is precisely &lt;i&gt;N&lt;/i&gt;. We constructively show how this worst case scenario can arise in highly heterogeneous systems. This result, when interpreted in the context of selfish routing, means that the price of anarchy in unbounded delay networks depends on the topology, and can potentially be very large. Our analytical findings are extended in asymptotic regimes to the &lt;i&gt;G&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 first-come first-serve and multi-class &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1-PS models and supported by simulations run for various arrival and service processes, scheduling disciplines, and workload exhibiting temporal locality. These results indicate that our analysis is applicable to realistic scenarios.",david starobinski,game theory,2008.0,10.1109/TNET.2007.909752,IEEE/ACM Transactions on Networking,Wu2008,False,,IEEE,Not available,A Comparative Analysis of Server Selection in Content Replication Networks,19c4fbd837166c20b209d320503781c4,https://ieeexplore.ieee.org/document/4469924/
10272,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
10273,"Server selection plays an essential role in content replication networks, such as peer-to-peer (P2P) and content delivery networks (CDNs). In this paper, we perform an analytical investigation of the strengths and weaknesses of existing server selection policies, based initially on an &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 processor sharing (PS) queueing-theoretic model. We develop a theoretical benchmark to evaluate the performance of two general server selection policies, referred to as EQ_DELAY and EQ_LOAD, which characterize a wide range of existing server selection algorithms. We find that EQ_LOAD achieves an average delay always higher than or equal to that of EQ_DELAY. A key theoretical result of this paper is that in an &lt;i&gt;N&lt;/i&gt;-server system, the worst case ratio between the average delay of EQ_DELAY or EQ_LOAD and the minimal average delay (obtained from the benchmark) is precisely &lt;i&gt;N&lt;/i&gt;. We constructively show how this worst case scenario can arise in highly heterogeneous systems. This result, when interpreted in the context of selfish routing, means that the price of anarchy in unbounded delay networks depends on the topology, and can potentially be very large. Our analytical findings are extended in asymptotic regimes to the &lt;i&gt;G&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 first-come first-serve and multi-class &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1-PS models and supported by simulations run for various arrival and service processes, scheduling disciplines, and workload exhibiting temporal locality. These results indicate that our analysis is applicable to realistic scenarios.",david starobinski,load balancing,2008.0,10.1109/TNET.2007.909752,IEEE/ACM Transactions on Networking,Wu2008,False,,IEEE,Not available,A Comparative Analysis of Server Selection in Content Replication Networks,19c4fbd837166c20b209d320503781c4,https://ieeexplore.ieee.org/document/4469924/
10274,"Server selection plays an essential role in content replication networks, such as peer-to-peer (P2P) and content delivery networks (CDNs). In this paper, we perform an analytical investigation of the strengths and weaknesses of existing server selection policies, based initially on an &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 processor sharing (PS) queueing-theoretic model. We develop a theoretical benchmark to evaluate the performance of two general server selection policies, referred to as EQ_DELAY and EQ_LOAD, which characterize a wide range of existing server selection algorithms. We find that EQ_LOAD achieves an average delay always higher than or equal to that of EQ_DELAY. A key theoretical result of this paper is that in an &lt;i&gt;N&lt;/i&gt;-server system, the worst case ratio between the average delay of EQ_DELAY or EQ_LOAD and the minimal average delay (obtained from the benchmark) is precisely &lt;i&gt;N&lt;/i&gt;. We constructively show how this worst case scenario can arise in highly heterogeneous systems. This result, when interpreted in the context of selfish routing, means that the price of anarchy in unbounded delay networks depends on the topology, and can potentially be very large. Our analytical findings are extended in asymptotic regimes to the &lt;i&gt;G&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 first-come first-serve and multi-class &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1-PS models and supported by simulations run for various arrival and service processes, scheduling disciplines, and workload exhibiting temporal locality. These results indicate that our analysis is applicable to realistic scenarios.",david starobinski,peer-to-peer networks,2008.0,10.1109/TNET.2007.909752,IEEE/ACM Transactions on Networking,Wu2008,False,,IEEE,Not available,A Comparative Analysis of Server Selection in Content Replication Networks,19c4fbd837166c20b209d320503781c4,https://ieeexplore.ieee.org/document/4469924/
10275,"Server selection plays an essential role in content replication networks, such as peer-to-peer (P2P) and content delivery networks (CDNs). In this paper, we perform an analytical investigation of the strengths and weaknesses of existing server selection policies, based initially on an &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 processor sharing (PS) queueing-theoretic model. We develop a theoretical benchmark to evaluate the performance of two general server selection policies, referred to as EQ_DELAY and EQ_LOAD, which characterize a wide range of existing server selection algorithms. We find that EQ_LOAD achieves an average delay always higher than or equal to that of EQ_DELAY. A key theoretical result of this paper is that in an &lt;i&gt;N&lt;/i&gt;-server system, the worst case ratio between the average delay of EQ_DELAY or EQ_LOAD and the minimal average delay (obtained from the benchmark) is precisely &lt;i&gt;N&lt;/i&gt;. We constructively show how this worst case scenario can arise in highly heterogeneous systems. This result, when interpreted in the context of selfish routing, means that the price of anarchy in unbounded delay networks depends on the topology, and can potentially be very large. Our analytical findings are extended in asymptotic regimes to the &lt;i&gt;G&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1 first-come first-serve and multi-class &lt;i&gt;M&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/1-PS models and supported by simulations run for various arrival and service processes, scheduling disciplines, and workload exhibiting temporal locality. These results indicate that our analysis is applicable to realistic scenarios.",david starobinski,price of anarchy,2008.0,10.1109/TNET.2007.909752,IEEE/ACM Transactions on Networking,Wu2008,False,,IEEE,Not available,A Comparative Analysis of Server Selection in Content Replication Networks,19c4fbd837166c20b209d320503781c4,https://ieeexplore.ieee.org/document/4469924/
10276,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",konstantinos poularakis,Heuristic algorithms,2013.0,10.1109/INFCOMW.2013.6562882,2013 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS),Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6562882/
10277,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",konstantinos poularakis,Games,2013.0,10.1109/INFCOMW.2013.6562882,2013 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS),Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6562882/
10278,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",konstantinos poularakis,Nash equilibrium,2013.0,10.1109/INFCOMW.2013.6562882,2013 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS),Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6562882/
10279,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",konstantinos poularakis,Aggregates,2013.0,10.1109/INFCOMW.2013.6562882,2013 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS),Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6562882/
10280,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",konstantinos poularakis,Vectors,2013.0,10.1109/INFCOMW.2013.6562882,2013 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS),Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6562882/
10281,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",konstantinos poularakis,Linear programming,2013.0,10.1109/INFCOMW.2013.6562882,2013 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS),Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6562882/
10282,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",konstantinos poularakis,Conferences,2013.0,10.1109/INFCOMW.2013.6562882,2013 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS),Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6562882/
10283,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
10284,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",leandros tassiulas,Heuristic algorithms,2013.0,10.1109/INFCOMW.2013.6562882,2013 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS),Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6562882/
10285,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",leandros tassiulas,Games,2013.0,10.1109/INFCOMW.2013.6562882,2013 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS),Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6562882/
10286,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",leandros tassiulas,Nash equilibrium,2013.0,10.1109/INFCOMW.2013.6562882,2013 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS),Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6562882/
10287,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",leandros tassiulas,Aggregates,2013.0,10.1109/INFCOMW.2013.6562882,2013 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS),Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6562882/
10288,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",leandros tassiulas,Vectors,2013.0,10.1109/INFCOMW.2013.6562882,2013 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS),Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6562882/
10289,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",leandros tassiulas,Linear programming,2013.0,10.1109/INFCOMW.2013.6562882,2013 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS),Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6562882/
10290,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",leandros tassiulas,Conferences,2013.0,10.1109/INFCOMW.2013.6562882,2013 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS),Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6562882/
10291,"We study a dynamic random access game with a finite number of opportunities for transmission and with energy constraints. We provide sufficient conditions for feasible strategies and for existence of Nash-Pareto solutions and show that finding Nash-Pareto policies of the dynamic random access game is equivalent to partitioning the set of time slot opportunities with constraints into a set of terminals. We further derive upper bounds for pure Nash-Pareto policies, and extend the study to non-integer energy constraints and unknown termination time, where time division multiplexing policies can be suboptimal. We show that the dynamic random access game has several strong equilibria (resilient to coalition of any size), and we compute them explicitly. We introduce the (strong) price of anarchy concept to measure the gap between the payoff under strong equilibria and the social optimum.",eitan altman,Dynamic game,2009.0,10.1109/WIOPT.2009.5291611,"2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Altman2009,False,,IEEE,Not available,A dynamic random access game with energy constraints,4eb2d71138fc92f3f433cb60a9b9bed6,https://ieeexplore.ieee.org/document/5291611/
10292,"We study a dynamic random access game with a finite number of opportunities for transmission and with energy constraints. We provide sufficient conditions for feasible strategies and for existence of Nash-Pareto solutions and show that finding Nash-Pareto policies of the dynamic random access game is equivalent to partitioning the set of time slot opportunities with constraints into a set of terminals. We further derive upper bounds for pure Nash-Pareto policies, and extend the study to non-integer energy constraints and unknown termination time, where time division multiplexing policies can be suboptimal. We show that the dynamic random access game has several strong equilibria (resilient to coalition of any size), and we compute them explicitly. We introduce the (strong) price of anarchy concept to measure the gap between the payoff under strong equilibria and the social optimum.",eitan altman,multiple access control,2009.0,10.1109/WIOPT.2009.5291611,"2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Altman2009,False,,IEEE,Not available,A dynamic random access game with energy constraints,4eb2d71138fc92f3f433cb60a9b9bed6,https://ieeexplore.ieee.org/document/5291611/
10293,"We study a dynamic random access game with a finite number of opportunities for transmission and with energy constraints. We provide sufficient conditions for feasible strategies and for existence of Nash-Pareto solutions and show that finding Nash-Pareto policies of the dynamic random access game is equivalent to partitioning the set of time slot opportunities with constraints into a set of terminals. We further derive upper bounds for pure Nash-Pareto policies, and extend the study to non-integer energy constraints and unknown termination time, where time division multiplexing policies can be suboptimal. We show that the dynamic random access game has several strong equilibria (resilient to coalition of any size), and we compute them explicitly. We introduce the (strong) price of anarchy concept to measure the gap between the payoff under strong equilibria and the social optimum.",eitan altman,strong equilibria,2009.0,10.1109/WIOPT.2009.5291611,"2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Altman2009,False,,IEEE,Not available,A dynamic random access game with energy constraints,4eb2d71138fc92f3f433cb60a9b9bed6,https://ieeexplore.ieee.org/document/5291611/
10294,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
10295,"We study a dynamic random access game with a finite number of opportunities for transmission and with energy constraints. We provide sufficient conditions for feasible strategies and for existence of Nash-Pareto solutions and show that finding Nash-Pareto policies of the dynamic random access game is equivalent to partitioning the set of time slot opportunities with constraints into a set of terminals. We further derive upper bounds for pure Nash-Pareto policies, and extend the study to non-integer energy constraints and unknown termination time, where time division multiplexing policies can be suboptimal. We show that the dynamic random access game has several strong equilibria (resilient to coalition of any size), and we compute them explicitly. We introduce the (strong) price of anarchy concept to measure the gap between the payoff under strong equilibria and the social optimum.",eitan altman,TDM policy,2009.0,10.1109/WIOPT.2009.5291611,"2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Altman2009,False,,IEEE,Not available,A dynamic random access game with energy constraints,4eb2d71138fc92f3f433cb60a9b9bed6,https://ieeexplore.ieee.org/document/5291611/
10296,"We study a dynamic random access game with a finite number of opportunities for transmission and with energy constraints. We provide sufficient conditions for feasible strategies and for existence of Nash-Pareto solutions and show that finding Nash-Pareto policies of the dynamic random access game is equivalent to partitioning the set of time slot opportunities with constraints into a set of terminals. We further derive upper bounds for pure Nash-Pareto policies, and extend the study to non-integer energy constraints and unknown termination time, where time division multiplexing policies can be suboptimal. We show that the dynamic random access game has several strong equilibria (resilient to coalition of any size), and we compute them explicitly. We introduce the (strong) price of anarchy concept to measure the gap between the payoff under strong equilibria and the social optimum.",tamer basar,Dynamic game,2009.0,10.1109/WIOPT.2009.5291611,"2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Altman2009,False,,IEEE,Not available,A dynamic random access game with energy constraints,4eb2d71138fc92f3f433cb60a9b9bed6,https://ieeexplore.ieee.org/document/5291611/
10297,"We study a dynamic random access game with a finite number of opportunities for transmission and with energy constraints. We provide sufficient conditions for feasible strategies and for existence of Nash-Pareto solutions and show that finding Nash-Pareto policies of the dynamic random access game is equivalent to partitioning the set of time slot opportunities with constraints into a set of terminals. We further derive upper bounds for pure Nash-Pareto policies, and extend the study to non-integer energy constraints and unknown termination time, where time division multiplexing policies can be suboptimal. We show that the dynamic random access game has several strong equilibria (resilient to coalition of any size), and we compute them explicitly. We introduce the (strong) price of anarchy concept to measure the gap between the payoff under strong equilibria and the social optimum.",tamer basar,multiple access control,2009.0,10.1109/WIOPT.2009.5291611,"2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Altman2009,False,,IEEE,Not available,A dynamic random access game with energy constraints,4eb2d71138fc92f3f433cb60a9b9bed6,https://ieeexplore.ieee.org/document/5291611/
10298,"We study a dynamic random access game with a finite number of opportunities for transmission and with energy constraints. We provide sufficient conditions for feasible strategies and for existence of Nash-Pareto solutions and show that finding Nash-Pareto policies of the dynamic random access game is equivalent to partitioning the set of time slot opportunities with constraints into a set of terminals. We further derive upper bounds for pure Nash-Pareto policies, and extend the study to non-integer energy constraints and unknown termination time, where time division multiplexing policies can be suboptimal. We show that the dynamic random access game has several strong equilibria (resilient to coalition of any size), and we compute them explicitly. We introduce the (strong) price of anarchy concept to measure the gap between the payoff under strong equilibria and the social optimum.",tamer basar,strong equilibria,2009.0,10.1109/WIOPT.2009.5291611,"2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Altman2009,False,,IEEE,Not available,A dynamic random access game with energy constraints,4eb2d71138fc92f3f433cb60a9b9bed6,https://ieeexplore.ieee.org/document/5291611/
10299,"We study a dynamic random access game with a finite number of opportunities for transmission and with energy constraints. We provide sufficient conditions for feasible strategies and for existence of Nash-Pareto solutions and show that finding Nash-Pareto policies of the dynamic random access game is equivalent to partitioning the set of time slot opportunities with constraints into a set of terminals. We further derive upper bounds for pure Nash-Pareto policies, and extend the study to non-integer energy constraints and unknown termination time, where time division multiplexing policies can be suboptimal. We show that the dynamic random access game has several strong equilibria (resilient to coalition of any size), and we compute them explicitly. We introduce the (strong) price of anarchy concept to measure the gap between the payoff under strong equilibria and the social optimum.",tamer basar,TDM policy,2009.0,10.1109/WIOPT.2009.5291611,"2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Altman2009,False,,IEEE,Not available,A dynamic random access game with energy constraints,4eb2d71138fc92f3f433cb60a9b9bed6,https://ieeexplore.ieee.org/document/5291611/
10300,"We study a dynamic random access game with a finite number of opportunities for transmission and with energy constraints. We provide sufficient conditions for feasible strategies and for existence of Nash-Pareto solutions and show that finding Nash-Pareto policies of the dynamic random access game is equivalent to partitioning the set of time slot opportunities with constraints into a set of terminals. We further derive upper bounds for pure Nash-Pareto policies, and extend the study to non-integer energy constraints and unknown termination time, where time division multiplexing policies can be suboptimal. We show that the dynamic random access game has several strong equilibria (resilient to coalition of any size), and we compute them explicitly. We introduce the (strong) price of anarchy concept to measure the gap between the payoff under strong equilibria and the social optimum.",ishai menache,Dynamic game,2009.0,10.1109/WIOPT.2009.5291611,"2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Altman2009,False,,IEEE,Not available,A dynamic random access game with energy constraints,4eb2d71138fc92f3f433cb60a9b9bed6,https://ieeexplore.ieee.org/document/5291611/
10301,"We study a dynamic random access game with a finite number of opportunities for transmission and with energy constraints. We provide sufficient conditions for feasible strategies and for existence of Nash-Pareto solutions and show that finding Nash-Pareto policies of the dynamic random access game is equivalent to partitioning the set of time slot opportunities with constraints into a set of terminals. We further derive upper bounds for pure Nash-Pareto policies, and extend the study to non-integer energy constraints and unknown termination time, where time division multiplexing policies can be suboptimal. We show that the dynamic random access game has several strong equilibria (resilient to coalition of any size), and we compute them explicitly. We introduce the (strong) price of anarchy concept to measure the gap between the payoff under strong equilibria and the social optimum.",ishai menache,multiple access control,2009.0,10.1109/WIOPT.2009.5291611,"2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Altman2009,False,,IEEE,Not available,A dynamic random access game with energy constraints,4eb2d71138fc92f3f433cb60a9b9bed6,https://ieeexplore.ieee.org/document/5291611/
10302,"We study a dynamic random access game with a finite number of opportunities for transmission and with energy constraints. We provide sufficient conditions for feasible strategies and for existence of Nash-Pareto solutions and show that finding Nash-Pareto policies of the dynamic random access game is equivalent to partitioning the set of time slot opportunities with constraints into a set of terminals. We further derive upper bounds for pure Nash-Pareto policies, and extend the study to non-integer energy constraints and unknown termination time, where time division multiplexing policies can be suboptimal. We show that the dynamic random access game has several strong equilibria (resilient to coalition of any size), and we compute them explicitly. We introduce the (strong) price of anarchy concept to measure the gap between the payoff under strong equilibria and the social optimum.",ishai menache,strong equilibria,2009.0,10.1109/WIOPT.2009.5291611,"2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Altman2009,False,,IEEE,Not available,A dynamic random access game with energy constraints,4eb2d71138fc92f3f433cb60a9b9bed6,https://ieeexplore.ieee.org/document/5291611/
10303,"We study a dynamic random access game with a finite number of opportunities for transmission and with energy constraints. We provide sufficient conditions for feasible strategies and for existence of Nash-Pareto solutions and show that finding Nash-Pareto policies of the dynamic random access game is equivalent to partitioning the set of time slot opportunities with constraints into a set of terminals. We further derive upper bounds for pure Nash-Pareto policies, and extend the study to non-integer energy constraints and unknown termination time, where time division multiplexing policies can be suboptimal. We show that the dynamic random access game has several strong equilibria (resilient to coalition of any size), and we compute them explicitly. We introduce the (strong) price of anarchy concept to measure the gap between the payoff under strong equilibria and the social optimum.",ishai menache,TDM policy,2009.0,10.1109/WIOPT.2009.5291611,"2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Altman2009,False,,IEEE,Not available,A dynamic random access game with energy constraints,4eb2d71138fc92f3f433cb60a9b9bed6,https://ieeexplore.ieee.org/document/5291611/
10304,"We study a dynamic random access game with a finite number of opportunities for transmission and with energy constraints. We provide sufficient conditions for feasible strategies and for existence of Nash-Pareto solutions and show that finding Nash-Pareto policies of the dynamic random access game is equivalent to partitioning the set of time slot opportunities with constraints into a set of terminals. We further derive upper bounds for pure Nash-Pareto policies, and extend the study to non-integer energy constraints and unknown termination time, where time division multiplexing policies can be suboptimal. We show that the dynamic random access game has several strong equilibria (resilient to coalition of any size), and we compute them explicitly. We introduce the (strong) price of anarchy concept to measure the gap between the payoff under strong equilibria and the social optimum.",hamidou tembine,Dynamic game,2009.0,10.1109/WIOPT.2009.5291611,"2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Altman2009,False,,IEEE,Not available,A dynamic random access game with energy constraints,4eb2d71138fc92f3f433cb60a9b9bed6,https://ieeexplore.ieee.org/document/5291611/
10305,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
10306,"We study a dynamic random access game with a finite number of opportunities for transmission and with energy constraints. We provide sufficient conditions for feasible strategies and for existence of Nash-Pareto solutions and show that finding Nash-Pareto policies of the dynamic random access game is equivalent to partitioning the set of time slot opportunities with constraints into a set of terminals. We further derive upper bounds for pure Nash-Pareto policies, and extend the study to non-integer energy constraints and unknown termination time, where time division multiplexing policies can be suboptimal. We show that the dynamic random access game has several strong equilibria (resilient to coalition of any size), and we compute them explicitly. We introduce the (strong) price of anarchy concept to measure the gap between the payoff under strong equilibria and the social optimum.",hamidou tembine,multiple access control,2009.0,10.1109/WIOPT.2009.5291611,"2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Altman2009,False,,IEEE,Not available,A dynamic random access game with energy constraints,4eb2d71138fc92f3f433cb60a9b9bed6,https://ieeexplore.ieee.org/document/5291611/
10307,"We study a dynamic random access game with a finite number of opportunities for transmission and with energy constraints. We provide sufficient conditions for feasible strategies and for existence of Nash-Pareto solutions and show that finding Nash-Pareto policies of the dynamic random access game is equivalent to partitioning the set of time slot opportunities with constraints into a set of terminals. We further derive upper bounds for pure Nash-Pareto policies, and extend the study to non-integer energy constraints and unknown termination time, where time division multiplexing policies can be suboptimal. We show that the dynamic random access game has several strong equilibria (resilient to coalition of any size), and we compute them explicitly. We introduce the (strong) price of anarchy concept to measure the gap between the payoff under strong equilibria and the social optimum.",hamidou tembine,strong equilibria,2009.0,10.1109/WIOPT.2009.5291611,"2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Altman2009,False,,IEEE,Not available,A dynamic random access game with energy constraints,4eb2d71138fc92f3f433cb60a9b9bed6,https://ieeexplore.ieee.org/document/5291611/
10308,"We study a dynamic random access game with a finite number of opportunities for transmission and with energy constraints. We provide sufficient conditions for feasible strategies and for existence of Nash-Pareto solutions and show that finding Nash-Pareto policies of the dynamic random access game is equivalent to partitioning the set of time slot opportunities with constraints into a set of terminals. We further derive upper bounds for pure Nash-Pareto policies, and extend the study to non-integer energy constraints and unknown termination time, where time division multiplexing policies can be suboptimal. We show that the dynamic random access game has several strong equilibria (resilient to coalition of any size), and we compute them explicitly. We introduce the (strong) price of anarchy concept to measure the gap between the payoff under strong equilibria and the social optimum.",hamidou tembine,TDM policy,2009.0,10.1109/WIOPT.2009.5291611,"2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks",Altman2009,False,,IEEE,Not available,A dynamic random access game with energy constraints,4eb2d71138fc92f3f433cb60a9b9bed6,https://ieeexplore.ieee.org/document/5291611/
10309,"We consider a geographically distributed request processing system composed of various organizations and their servers connected by the Internet. The latency a user observes is a sum of communication delays and the time needed to handle the request on a server. The handling time depends on the server congestion, i.e. the total number of requests a server must handle. We analyze the problem of balancing the load in a network of servers in order to minimize the total observed latency. We consider both cooperative and selfish organizations (each organization aiming to minimize the latency of the locally-produced requests). The problem can be generalized to the task scheduling in a distributed cloud; or to content delivery in an organizationally-distributed CDNs. In a cooperative network, we show that the problem is polynomially solvable. We also present a distributed algorithm iteratively balancing the load. We show how to estimate the distance between the current solution and the optimum based on the amount of load exchanged by the algorithm. During the experimental evaluation, we show that the distributed algorithm is efficient, therefore it can be used in networks with dynamically changing loads. In a network of selfish organizations, we prove that the price of anarchy (the worst-case loss of performance due to selfishness) is low when the network is homogeneous and the servers are loaded (the request handling time is high compared to the communication delay). After relaxing these assumptions, we assess the loss of performance caused by the selfishness experimentally, showing that it remains low. Our results indicate that a set of servers handling requests, connected in a heterogeneous network, can be efficiently managed by a distributed algorithm. Additionally, even if the network is organizationally distributed, with individual organizations optimizing performance of their requests, the network remains efficient.",piotr skowron,load balancing,2013.0,10.1109/IPDPSW.2013.21,"2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum",Skowron2013,False,,IEEE,Not available,Network Delay-Aware Load Balancing in Selfish and Cooperative Distributed Systems,fc60b1bb89747a09a889abb542672d4f,https://ieeexplore.ieee.org/document/6650867/
10310,"We consider a geographically distributed request processing system composed of various organizations and their servers connected by the Internet. The latency a user observes is a sum of communication delays and the time needed to handle the request on a server. The handling time depends on the server congestion, i.e. the total number of requests a server must handle. We analyze the problem of balancing the load in a network of servers in order to minimize the total observed latency. We consider both cooperative and selfish organizations (each organization aiming to minimize the latency of the locally-produced requests). The problem can be generalized to the task scheduling in a distributed cloud; or to content delivery in an organizationally-distributed CDNs. In a cooperative network, we show that the problem is polynomially solvable. We also present a distributed algorithm iteratively balancing the load. We show how to estimate the distance between the current solution and the optimum based on the amount of load exchanged by the algorithm. During the experimental evaluation, we show that the distributed algorithm is efficient, therefore it can be used in networks with dynamically changing loads. In a network of selfish organizations, we prove that the price of anarchy (the worst-case loss of performance due to selfishness) is low when the network is homogeneous and the servers are loaded (the request handling time is high compared to the communication delay). After relaxing these assumptions, we assess the loss of performance caused by the selfishness experimentally, showing that it remains low. Our results indicate that a set of servers handling requests, connected in a heterogeneous network, can be efficiently managed by a distributed algorithm. Additionally, even if the network is organizationally distributed, with individual organizations optimizing performance of their requests, the network remains efficient.",piotr skowron,distributed algorithm,2013.0,10.1109/IPDPSW.2013.21,"2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum",Skowron2013,False,,IEEE,Not available,Network Delay-Aware Load Balancing in Selfish and Cooperative Distributed Systems,fc60b1bb89747a09a889abb542672d4f,https://ieeexplore.ieee.org/document/6650867/
10311,"We consider a geographically distributed request processing system composed of various organizations and their servers connected by the Internet. The latency a user observes is a sum of communication delays and the time needed to handle the request on a server. The handling time depends on the server congestion, i.e. the total number of requests a server must handle. We analyze the problem of balancing the load in a network of servers in order to minimize the total observed latency. We consider both cooperative and selfish organizations (each organization aiming to minimize the latency of the locally-produced requests). The problem can be generalized to the task scheduling in a distributed cloud; or to content delivery in an organizationally-distributed CDNs. In a cooperative network, we show that the problem is polynomially solvable. We also present a distributed algorithm iteratively balancing the load. We show how to estimate the distance between the current solution and the optimum based on the amount of load exchanged by the algorithm. During the experimental evaluation, we show that the distributed algorithm is efficient, therefore it can be used in networks with dynamically changing loads. In a network of selfish organizations, we prove that the price of anarchy (the worst-case loss of performance due to selfishness) is low when the network is homogeneous and the servers are loaded (the request handling time is high compared to the communication delay). After relaxing these assumptions, we assess the loss of performance caused by the selfishness experimentally, showing that it remains low. Our results indicate that a set of servers handling requests, connected in a heterogeneous network, can be efficiently managed by a distributed algorithm. Additionally, even if the network is organizationally distributed, with individual organizations optimizing performance of their requests, the network remains efficient.",piotr skowron,price of anarchy,2013.0,10.1109/IPDPSW.2013.21,"2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum",Skowron2013,False,,IEEE,Not available,Network Delay-Aware Load Balancing in Selfish and Cooperative Distributed Systems,fc60b1bb89747a09a889abb542672d4f,https://ieeexplore.ieee.org/document/6650867/
10312,"We consider a geographically distributed request processing system composed of various organizations and their servers connected by the Internet. The latency a user observes is a sum of communication delays and the time needed to handle the request on a server. The handling time depends on the server congestion, i.e. the total number of requests a server must handle. We analyze the problem of balancing the load in a network of servers in order to minimize the total observed latency. We consider both cooperative and selfish organizations (each organization aiming to minimize the latency of the locally-produced requests). The problem can be generalized to the task scheduling in a distributed cloud; or to content delivery in an organizationally-distributed CDNs. In a cooperative network, we show that the problem is polynomially solvable. We also present a distributed algorithm iteratively balancing the load. We show how to estimate the distance between the current solution and the optimum based on the amount of load exchanged by the algorithm. During the experimental evaluation, we show that the distributed algorithm is efficient, therefore it can be used in networks with dynamically changing loads. In a network of selfish organizations, we prove that the price of anarchy (the worst-case loss of performance due to selfishness) is low when the network is homogeneous and the servers are loaded (the request handling time is high compared to the communication delay). After relaxing these assumptions, we assess the loss of performance caused by the selfishness experimentally, showing that it remains low. Our results indicate that a set of servers handling requests, connected in a heterogeneous network, can be efficiently managed by a distributed algorithm. Additionally, even if the network is organizationally distributed, with individual organizations optimizing performance of their requests, the network remains efficient.",krzysztof rzadca,load balancing,2013.0,10.1109/IPDPSW.2013.21,"2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum",Skowron2013,False,,IEEE,Not available,Network Delay-Aware Load Balancing in Selfish and Cooperative Distributed Systems,fc60b1bb89747a09a889abb542672d4f,https://ieeexplore.ieee.org/document/6650867/
10313,"We consider a geographically distributed request processing system composed of various organizations and their servers connected by the Internet. The latency a user observes is a sum of communication delays and the time needed to handle the request on a server. The handling time depends on the server congestion, i.e. the total number of requests a server must handle. We analyze the problem of balancing the load in a network of servers in order to minimize the total observed latency. We consider both cooperative and selfish organizations (each organization aiming to minimize the latency of the locally-produced requests). The problem can be generalized to the task scheduling in a distributed cloud; or to content delivery in an organizationally-distributed CDNs. In a cooperative network, we show that the problem is polynomially solvable. We also present a distributed algorithm iteratively balancing the load. We show how to estimate the distance between the current solution and the optimum based on the amount of load exchanged by the algorithm. During the experimental evaluation, we show that the distributed algorithm is efficient, therefore it can be used in networks with dynamically changing loads. In a network of selfish organizations, we prove that the price of anarchy (the worst-case loss of performance due to selfishness) is low when the network is homogeneous and the servers are loaded (the request handling time is high compared to the communication delay). After relaxing these assumptions, we assess the loss of performance caused by the selfishness experimentally, showing that it remains low. Our results indicate that a set of servers handling requests, connected in a heterogeneous network, can be efficiently managed by a distributed algorithm. Additionally, even if the network is organizationally distributed, with individual organizations optimizing performance of their requests, the network remains efficient.",krzysztof rzadca,distributed algorithm,2013.0,10.1109/IPDPSW.2013.21,"2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum",Skowron2013,False,,IEEE,Not available,Network Delay-Aware Load Balancing in Selfish and Cooperative Distributed Systems,fc60b1bb89747a09a889abb542672d4f,https://ieeexplore.ieee.org/document/6650867/
10314,"We consider a geographically distributed request processing system composed of various organizations and their servers connected by the Internet. The latency a user observes is a sum of communication delays and the time needed to handle the request on a server. The handling time depends on the server congestion, i.e. the total number of requests a server must handle. We analyze the problem of balancing the load in a network of servers in order to minimize the total observed latency. We consider both cooperative and selfish organizations (each organization aiming to minimize the latency of the locally-produced requests). The problem can be generalized to the task scheduling in a distributed cloud; or to content delivery in an organizationally-distributed CDNs. In a cooperative network, we show that the problem is polynomially solvable. We also present a distributed algorithm iteratively balancing the load. We show how to estimate the distance between the current solution and the optimum based on the amount of load exchanged by the algorithm. During the experimental evaluation, we show that the distributed algorithm is efficient, therefore it can be used in networks with dynamically changing loads. In a network of selfish organizations, we prove that the price of anarchy (the worst-case loss of performance due to selfishness) is low when the network is homogeneous and the servers are loaded (the request handling time is high compared to the communication delay). After relaxing these assumptions, we assess the loss of performance caused by the selfishness experimentally, showing that it remains low. Our results indicate that a set of servers handling requests, connected in a heterogeneous network, can be efficiently managed by a distributed algorithm. Additionally, even if the network is organizationally distributed, with individual organizations optimizing performance of their requests, the network remains efficient.",krzysztof rzadca,price of anarchy,2013.0,10.1109/IPDPSW.2013.21,"2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum",Skowron2013,False,,IEEE,Not available,Network Delay-Aware Load Balancing in Selfish and Cooperative Distributed Systems,fc60b1bb89747a09a889abb542672d4f,https://ieeexplore.ieee.org/document/6650867/
10315,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",v.s. kumar,Approximation algorithms,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10316,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
10317,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",v.s. kumar,Game theory,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10318,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",v.s. kumar,Costs,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10319,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",v.s. kumar,Information security,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10320,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",v.s. kumar,Computer viruses,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10321,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",v.s. kumar,Computer worms,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10322,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",v.s. kumar,Protection,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10323,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",v.s. kumar,Distributed computing,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10324,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",v.s. kumar,Sun,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10325,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",v.s. kumar,Computer networks,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10326,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",rajmohan rajaraman,Approximation algorithms,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10327,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
10328,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
10329,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",rajmohan rajaraman,Game theory,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10330,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",rajmohan rajaraman,Costs,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10331,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",rajmohan rajaraman,Information security,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10332,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",rajmohan rajaraman,Computer viruses,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10333,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",rajmohan rajaraman,Computer worms,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10334,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",rajmohan rajaraman,Protection,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10335,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",rajmohan rajaraman,Distributed computing,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10336,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",rajmohan rajaraman,Sun,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10337,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",rajmohan rajaraman,Computer networks,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10338,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",zhifeng sun,Approximation algorithms,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10339,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
10340,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",zhifeng sun,Game theory,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10341,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",zhifeng sun,Costs,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10342,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",zhifeng sun,Information security,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10343,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",zhifeng sun,Computer viruses,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10344,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",zhifeng sun,Computer worms,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10345,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",zhifeng sun,Protection,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10346,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",zhifeng sun,Distributed computing,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10347,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",zhifeng sun,Sun,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10348,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",zhifeng sun,Computer networks,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10349,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",ravi sundaram,Approximation algorithms,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10350,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
10351,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",ravi sundaram,Game theory,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10352,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",ravi sundaram,Costs,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10353,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",ravi sundaram,Information security,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10354,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",ravi sundaram,Computer viruses,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10355,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",ravi sundaram,Computer worms,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10356,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",ravi sundaram,Protection,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10357,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",ravi sundaram,Distributed computing,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10358,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",ravi sundaram,Sun,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10359,"Aspnes et al introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to install anti-virus software or not on an individual basis while the viruses or worms start from a node chosen uniformly at random and spread along paths consisting of insecure nodes. They showed the surprising result that a pure Nash Equilibrium always exists when all nodes have identical installation costs and identical infection costs. In this paper we present a substantial generalization of the model of that allows for arbitrary security and infection costs, and arbitrary distributions for the starting point of the attack. More significantly, our model GNS(d) incorporates a network locality parameter d which represents a hop-limit on the spread of infection as accounted for in the strategic decisions, due to either the intrinsic nature of the infection or the extent of neighborhood information that is available to a node. We determine that the network locality parameter plays a key role in the existence of pure Nash equilibria (NE): local (d = 1) and global games (d = ∞) have pure NE, while for GNS(d) games with 1 &lt;; d &lt;; ∞, pure NE may not exist, and in fact, it is NP-complete to determine whether a given instance has a pure NE. For local and global games, we also characterize the price of anarchy in terms of the maximum degree and vertex expansion of the contact network; these suggest natural heuristics to aid a network planner in enforcing efficient equilibria. We design a general LP-based framework for approximating the NP-complete problem of finding a socially optimal configuration in our game. Our framework yields a 2d-approximation for general GNS(d) games, and an O(log n)-approximation for the global model where n is the number of network nodes; the latter result improves on the approximation bound of O(log<sup>1.5</sup>n) of achieved for a special case of our global model. We study the characteristics of NE and the quality of our approximations empirically in two distinct classes of graphs: random geometric graphs and power law graphs. We find that in local and global games on these real-world networks, best response dynamics converge in linear or sub-linear time and have costs comparable to the social optimum. Finally, we study the performance of our approximation algorithms, and find that the approximation guarantees with respect to social cost are much better in practice than our theoretical bounds.",ravi sundaram,Computer networks,2010.0,10.1109/ICDCS.2010.70,2010 IEEE 30th International Conference on Distributed Computing Systems,Kumar2010,False,,IEEE,Not available,Existence Theorems and Approximation Algorithms for Generalized Network Security Games,85bd3b1c4c7f5b65cbb8ec86ccbd1643,https://ieeexplore.ieee.org/document/5541670/
10360,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",jocelyne elias,Cost function,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10361,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
10362,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",jocelyne elias,Game theory,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10363,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",jocelyne elias,Nash equilibrium,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10364,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",jocelyne elias,Communications Society,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10365,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",jocelyne elias,IP networks,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10366,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",jocelyne elias,Network topology,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10367,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",jocelyne elias,Web and internet services,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10368,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",jocelyne elias,System performance,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10369,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",jocelyne elias,Stability,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10370,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",jocelyne elias,Degradation,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10371,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",fabio martignon,Cost function,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10372,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
10373,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",fabio martignon,Game theory,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10374,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",fabio martignon,Nash equilibrium,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10375,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",fabio martignon,Communications Society,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10376,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",fabio martignon,IP networks,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10377,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",fabio martignon,Network topology,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10378,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",fabio martignon,Web and internet services,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10379,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",fabio martignon,System performance,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10380,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",fabio martignon,Stability,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10381,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",fabio martignon,Degradation,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10382,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",konstantin avrachenkov,Cost function,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10383,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
10384,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",konstantin avrachenkov,Game theory,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10385,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",konstantin avrachenkov,Nash equilibrium,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10386,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",konstantin avrachenkov,Communications Society,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10387,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",konstantin avrachenkov,IP networks,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10388,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",konstantin avrachenkov,Network topology,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10389,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",konstantin avrachenkov,Web and internet services,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10390,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",konstantin avrachenkov,System performance,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10391,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",konstantin avrachenkov,Stability,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10392,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",konstantin avrachenkov,Degradation,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10393,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",giovanni neglia,Cost function,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10394,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
10395,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",giovanni neglia,Game theory,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10396,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",giovanni neglia,Nash equilibrium,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10397,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",giovanni neglia,Communications Society,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10398,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",giovanni neglia,IP networks,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10399,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",giovanni neglia,Network topology,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10400,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",giovanni neglia,Web and internet services,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10401,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",giovanni neglia,System performance,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10402,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",giovanni neglia,Stability,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10403,"In many scenarios network design is not enforced by a central authority, but arises from the interactions of several self-interested agents. This is the case of the Internet, where connectivity is due to Autonomous Systems' choices, but also of overlay networks, where each user client can decide the set of connections to establish. Recent works have used game theory, and in particular the concept of Nash Equilibrium, to characterize stable networks created by a set of selfish agents. The majority of these works assume that users are completely non-cooperative, leading, in most cases, to inefficient equilibria. To improve efficiency, in this paper we propose two novel socially-aware network design games. In the first game we incorporate a socially-aware component in the users' utility functions, while in the second game we use additionally a Stackelberg (leader-follower) approach, where a leader (e.g., the network administrator) architects the desired network buying an appropriate subset of network's links, driving in this way the users to overall efficient Nash equilibria. We provide bounds on the Price of Anarchy and other efficiency measures, and study the performance of the proposed schemes in several network scenarios, including realistic topologies where players build an overlay on top of real Internet Service Provider networks. Numerical results demonstrate that (1) introducing some incentives to make users more sociallyaware is an effective solution to achieve stable and efficient networks in a distributed way, and (2) the proposed Stackelberg approach permits to achieve dramatic performance improvements, designing almost always the socially optimal network.",giovanni neglia,Degradation,2010.0,10.1109/INFCOM.2010.5462275,2010 Proceedings IEEE INFOCOM,Elias2010,False,,IEEE,Not available,Socially-Aware Network Design Games,495509849a81f17d5913a4776d3c47b2,https://ieeexplore.ieee.org/document/5462275/
10404,"In this paper, a static non-cooperative game formulation of the problem of distributed charging in electrical vehicle (EV) networks is proposed. This formulation allows one to model the interaction between several EV which are connected to a common residential distribution transformer. Each EV aims at choosing the time at which it starts charging its battery in order to minimize an individual cost which is mainly related to the total power delivered by the transformer, the location of the time interval over which the charging operation is performed, and the charging duration needed for the considered EV to have its battery fully recharged. As individual cost functions are assumed to be memoryless, it is possible to show that the game of interest is always an ordinal potential game. More precisely, both an atomic and nonatomic versions of the charging game are considered. In both cases, equilibrium analysis is conducted. In particular, important issues such as equilibrium uniqueness and efficiency are tackled. Interestingly, both analytical and numerical results show that the efficiency loss due to decentralization (e.g., when cost functions such as distribution network Joule losses or life of residential distribution transformers when no thermal inertia is assumed) induced by charging is small and the corresponding “efficiency”, a notion close to the Price of Anarchy, tends to one when the number of EV increases.",olivier beaude,Charging games,2012.0,,"2012 6th International Conference on Network Games, Control and Optimization (NetGCooP)",Beaude2012,False,,IEEE,Not available,Charging games in networks of electrical vehicles,914d658c34542b3882aa11ffdb928190,
10405,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
10406,"In this paper, a static non-cooperative game formulation of the problem of distributed charging in electrical vehicle (EV) networks is proposed. This formulation allows one to model the interaction between several EV which are connected to a common residential distribution transformer. Each EV aims at choosing the time at which it starts charging its battery in order to minimize an individual cost which is mainly related to the total power delivered by the transformer, the location of the time interval over which the charging operation is performed, and the charging duration needed for the considered EV to have its battery fully recharged. As individual cost functions are assumed to be memoryless, it is possible to show that the game of interest is always an ordinal potential game. More precisely, both an atomic and nonatomic versions of the charging game are considered. In both cases, equilibrium analysis is conducted. In particular, important issues such as equilibrium uniqueness and efficiency are tackled. Interestingly, both analytical and numerical results show that the efficiency loss due to decentralization (e.g., when cost functions such as distribution network Joule losses or life of residential distribution transformers when no thermal inertia is assumed) induced by charging is small and the corresponding “efficiency”, a notion close to the Price of Anarchy, tends to one when the number of EV increases.",olivier beaude,electrical vehicle,2012.0,,"2012 6th International Conference on Network Games, Control and Optimization (NetGCooP)",Beaude2012,False,,IEEE,Not available,Charging games in networks of electrical vehicles,914d658c34542b3882aa11ffdb928190,
10407,"In this paper, a static non-cooperative game formulation of the problem of distributed charging in electrical vehicle (EV) networks is proposed. This formulation allows one to model the interaction between several EV which are connected to a common residential distribution transformer. Each EV aims at choosing the time at which it starts charging its battery in order to minimize an individual cost which is mainly related to the total power delivered by the transformer, the location of the time interval over which the charging operation is performed, and the charging duration needed for the considered EV to have its battery fully recharged. As individual cost functions are assumed to be memoryless, it is possible to show that the game of interest is always an ordinal potential game. More precisely, both an atomic and nonatomic versions of the charging game are considered. In both cases, equilibrium analysis is conducted. In particular, important issues such as equilibrium uniqueness and efficiency are tackled. Interestingly, both analytical and numerical results show that the efficiency loss due to decentralization (e.g., when cost functions such as distribution network Joule losses or life of residential distribution transformers when no thermal inertia is assumed) induced by charging is small and the corresponding “efficiency”, a notion close to the Price of Anarchy, tends to one when the number of EV increases.",olivier beaude,distribution networks,2012.0,,"2012 6th International Conference on Network Games, Control and Optimization (NetGCooP)",Beaude2012,False,,IEEE,Not available,Charging games in networks of electrical vehicles,914d658c34542b3882aa11ffdb928190,
10408,"In this paper, a static non-cooperative game formulation of the problem of distributed charging in electrical vehicle (EV) networks is proposed. This formulation allows one to model the interaction between several EV which are connected to a common residential distribution transformer. Each EV aims at choosing the time at which it starts charging its battery in order to minimize an individual cost which is mainly related to the total power delivered by the transformer, the location of the time interval over which the charging operation is performed, and the charging duration needed for the considered EV to have its battery fully recharged. As individual cost functions are assumed to be memoryless, it is possible to show that the game of interest is always an ordinal potential game. More precisely, both an atomic and nonatomic versions of the charging game are considered. In both cases, equilibrium analysis is conducted. In particular, important issues such as equilibrium uniqueness and efficiency are tackled. Interestingly, both analytical and numerical results show that the efficiency loss due to decentralization (e.g., when cost functions such as distribution network Joule losses or life of residential distribution transformers when no thermal inertia is assumed) induced by charging is small and the corresponding “efficiency”, a notion close to the Price of Anarchy, tends to one when the number of EV increases.",olivier beaude,potential games,2012.0,,"2012 6th International Conference on Network Games, Control and Optimization (NetGCooP)",Beaude2012,False,,IEEE,Not available,Charging games in networks of electrical vehicles,914d658c34542b3882aa11ffdb928190,
10409,"In this paper, a static non-cooperative game formulation of the problem of distributed charging in electrical vehicle (EV) networks is proposed. This formulation allows one to model the interaction between several EV which are connected to a common residential distribution transformer. Each EV aims at choosing the time at which it starts charging its battery in order to minimize an individual cost which is mainly related to the total power delivered by the transformer, the location of the time interval over which the charging operation is performed, and the charging duration needed for the considered EV to have its battery fully recharged. As individual cost functions are assumed to be memoryless, it is possible to show that the game of interest is always an ordinal potential game. More precisely, both an atomic and nonatomic versions of the charging game are considered. In both cases, equilibrium analysis is conducted. In particular, important issues such as equilibrium uniqueness and efficiency are tackled. Interestingly, both analytical and numerical results show that the efficiency loss due to decentralization (e.g., when cost functions such as distribution network Joule losses or life of residential distribution transformers when no thermal inertia is assumed) induced by charging is small and the corresponding “efficiency”, a notion close to the Price of Anarchy, tends to one when the number of EV increases.",olivier beaude,Nash equilibrium,2012.0,,"2012 6th International Conference on Network Games, Control and Optimization (NetGCooP)",Beaude2012,False,,IEEE,Not available,Charging games in networks of electrical vehicles,914d658c34542b3882aa11ffdb928190,
10410,"In this paper, a static non-cooperative game formulation of the problem of distributed charging in electrical vehicle (EV) networks is proposed. This formulation allows one to model the interaction between several EV which are connected to a common residential distribution transformer. Each EV aims at choosing the time at which it starts charging its battery in order to minimize an individual cost which is mainly related to the total power delivered by the transformer, the location of the time interval over which the charging operation is performed, and the charging duration needed for the considered EV to have its battery fully recharged. As individual cost functions are assumed to be memoryless, it is possible to show that the game of interest is always an ordinal potential game. More precisely, both an atomic and nonatomic versions of the charging game are considered. In both cases, equilibrium analysis is conducted. In particular, important issues such as equilibrium uniqueness and efficiency are tackled. Interestingly, both analytical and numerical results show that the efficiency loss due to decentralization (e.g., when cost functions such as distribution network Joule losses or life of residential distribution transformers when no thermal inertia is assumed) induced by charging is small and the corresponding “efficiency”, a notion close to the Price of Anarchy, tends to one when the number of EV increases.",olivier beaude,price of anarchy,2012.0,,"2012 6th International Conference on Network Games, Control and Optimization (NetGCooP)",Beaude2012,False,,IEEE,Not available,Charging games in networks of electrical vehicles,914d658c34542b3882aa11ffdb928190,
10411,"In this paper, a static non-cooperative game formulation of the problem of distributed charging in electrical vehicle (EV) networks is proposed. This formulation allows one to model the interaction between several EV which are connected to a common residential distribution transformer. Each EV aims at choosing the time at which it starts charging its battery in order to minimize an individual cost which is mainly related to the total power delivered by the transformer, the location of the time interval over which the charging operation is performed, and the charging duration needed for the considered EV to have its battery fully recharged. As individual cost functions are assumed to be memoryless, it is possible to show that the game of interest is always an ordinal potential game. More precisely, both an atomic and nonatomic versions of the charging game are considered. In both cases, equilibrium analysis is conducted. In particular, important issues such as equilibrium uniqueness and efficiency are tackled. Interestingly, both analytical and numerical results show that the efficiency loss due to decentralization (e.g., when cost functions such as distribution network Joule losses or life of residential distribution transformers when no thermal inertia is assumed) induced by charging is small and the corresponding “efficiency”, a notion close to the Price of Anarchy, tends to one when the number of EV increases.",samson lasaulce,Charging games,2012.0,,"2012 6th International Conference on Network Games, Control and Optimization (NetGCooP)",Beaude2012,False,,IEEE,Not available,Charging games in networks of electrical vehicles,914d658c34542b3882aa11ffdb928190,
10412,"In this paper, a static non-cooperative game formulation of the problem of distributed charging in electrical vehicle (EV) networks is proposed. This formulation allows one to model the interaction between several EV which are connected to a common residential distribution transformer. Each EV aims at choosing the time at which it starts charging its battery in order to minimize an individual cost which is mainly related to the total power delivered by the transformer, the location of the time interval over which the charging operation is performed, and the charging duration needed for the considered EV to have its battery fully recharged. As individual cost functions are assumed to be memoryless, it is possible to show that the game of interest is always an ordinal potential game. More precisely, both an atomic and nonatomic versions of the charging game are considered. In both cases, equilibrium analysis is conducted. In particular, important issues such as equilibrium uniqueness and efficiency are tackled. Interestingly, both analytical and numerical results show that the efficiency loss due to decentralization (e.g., when cost functions such as distribution network Joule losses or life of residential distribution transformers when no thermal inertia is assumed) induced by charging is small and the corresponding “efficiency”, a notion close to the Price of Anarchy, tends to one when the number of EV increases.",samson lasaulce,electrical vehicle,2012.0,,"2012 6th International Conference on Network Games, Control and Optimization (NetGCooP)",Beaude2012,False,,IEEE,Not available,Charging games in networks of electrical vehicles,914d658c34542b3882aa11ffdb928190,
10413,"In this paper, a static non-cooperative game formulation of the problem of distributed charging in electrical vehicle (EV) networks is proposed. This formulation allows one to model the interaction between several EV which are connected to a common residential distribution transformer. Each EV aims at choosing the time at which it starts charging its battery in order to minimize an individual cost which is mainly related to the total power delivered by the transformer, the location of the time interval over which the charging operation is performed, and the charging duration needed for the considered EV to have its battery fully recharged. As individual cost functions are assumed to be memoryless, it is possible to show that the game of interest is always an ordinal potential game. More precisely, both an atomic and nonatomic versions of the charging game are considered. In both cases, equilibrium analysis is conducted. In particular, important issues such as equilibrium uniqueness and efficiency are tackled. Interestingly, both analytical and numerical results show that the efficiency loss due to decentralization (e.g., when cost functions such as distribution network Joule losses or life of residential distribution transformers when no thermal inertia is assumed) induced by charging is small and the corresponding “efficiency”, a notion close to the Price of Anarchy, tends to one when the number of EV increases.",samson lasaulce,distribution networks,2012.0,,"2012 6th International Conference on Network Games, Control and Optimization (NetGCooP)",Beaude2012,False,,IEEE,Not available,Charging games in networks of electrical vehicles,914d658c34542b3882aa11ffdb928190,
10414,"In this paper, a static non-cooperative game formulation of the problem of distributed charging in electrical vehicle (EV) networks is proposed. This formulation allows one to model the interaction between several EV which are connected to a common residential distribution transformer. Each EV aims at choosing the time at which it starts charging its battery in order to minimize an individual cost which is mainly related to the total power delivered by the transformer, the location of the time interval over which the charging operation is performed, and the charging duration needed for the considered EV to have its battery fully recharged. As individual cost functions are assumed to be memoryless, it is possible to show that the game of interest is always an ordinal potential game. More precisely, both an atomic and nonatomic versions of the charging game are considered. In both cases, equilibrium analysis is conducted. In particular, important issues such as equilibrium uniqueness and efficiency are tackled. Interestingly, both analytical and numerical results show that the efficiency loss due to decentralization (e.g., when cost functions such as distribution network Joule losses or life of residential distribution transformers when no thermal inertia is assumed) induced by charging is small and the corresponding “efficiency”, a notion close to the Price of Anarchy, tends to one when the number of EV increases.",samson lasaulce,potential games,2012.0,,"2012 6th International Conference on Network Games, Control and Optimization (NetGCooP)",Beaude2012,False,,IEEE,Not available,Charging games in networks of electrical vehicles,914d658c34542b3882aa11ffdb928190,
10415,"In this paper, a static non-cooperative game formulation of the problem of distributed charging in electrical vehicle (EV) networks is proposed. This formulation allows one to model the interaction between several EV which are connected to a common residential distribution transformer. Each EV aims at choosing the time at which it starts charging its battery in order to minimize an individual cost which is mainly related to the total power delivered by the transformer, the location of the time interval over which the charging operation is performed, and the charging duration needed for the considered EV to have its battery fully recharged. As individual cost functions are assumed to be memoryless, it is possible to show that the game of interest is always an ordinal potential game. More precisely, both an atomic and nonatomic versions of the charging game are considered. In both cases, equilibrium analysis is conducted. In particular, important issues such as equilibrium uniqueness and efficiency are tackled. Interestingly, both analytical and numerical results show that the efficiency loss due to decentralization (e.g., when cost functions such as distribution network Joule losses or life of residential distribution transformers when no thermal inertia is assumed) induced by charging is small and the corresponding “efficiency”, a notion close to the Price of Anarchy, tends to one when the number of EV increases.",samson lasaulce,Nash equilibrium,2012.0,,"2012 6th International Conference on Network Games, Control and Optimization (NetGCooP)",Beaude2012,False,,IEEE,Not available,Charging games in networks of electrical vehicles,914d658c34542b3882aa11ffdb928190,
10416,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
10417,"In this paper, a static non-cooperative game formulation of the problem of distributed charging in electrical vehicle (EV) networks is proposed. This formulation allows one to model the interaction between several EV which are connected to a common residential distribution transformer. Each EV aims at choosing the time at which it starts charging its battery in order to minimize an individual cost which is mainly related to the total power delivered by the transformer, the location of the time interval over which the charging operation is performed, and the charging duration needed for the considered EV to have its battery fully recharged. As individual cost functions are assumed to be memoryless, it is possible to show that the game of interest is always an ordinal potential game. More precisely, both an atomic and nonatomic versions of the charging game are considered. In both cases, equilibrium analysis is conducted. In particular, important issues such as equilibrium uniqueness and efficiency are tackled. Interestingly, both analytical and numerical results show that the efficiency loss due to decentralization (e.g., when cost functions such as distribution network Joule losses or life of residential distribution transformers when no thermal inertia is assumed) induced by charging is small and the corresponding “efficiency”, a notion close to the Price of Anarchy, tends to one when the number of EV increases.",samson lasaulce,price of anarchy,2012.0,,"2012 6th International Conference on Network Games, Control and Optimization (NetGCooP)",Beaude2012,False,,IEEE,Not available,Charging games in networks of electrical vehicles,914d658c34542b3882aa11ffdb928190,
10418,"In this paper, a static non-cooperative game formulation of the problem of distributed charging in electrical vehicle (EV) networks is proposed. This formulation allows one to model the interaction between several EV which are connected to a common residential distribution transformer. Each EV aims at choosing the time at which it starts charging its battery in order to minimize an individual cost which is mainly related to the total power delivered by the transformer, the location of the time interval over which the charging operation is performed, and the charging duration needed for the considered EV to have its battery fully recharged. As individual cost functions are assumed to be memoryless, it is possible to show that the game of interest is always an ordinal potential game. More precisely, both an atomic and nonatomic versions of the charging game are considered. In both cases, equilibrium analysis is conducted. In particular, important issues such as equilibrium uniqueness and efficiency are tackled. Interestingly, both analytical and numerical results show that the efficiency loss due to decentralization (e.g., when cost functions such as distribution network Joule losses or life of residential distribution transformers when no thermal inertia is assumed) induced by charging is small and the corresponding “efficiency”, a notion close to the Price of Anarchy, tends to one when the number of EV increases.",martin hennebel,Charging games,2012.0,,"2012 6th International Conference on Network Games, Control and Optimization (NetGCooP)",Beaude2012,False,,IEEE,Not available,Charging games in networks of electrical vehicles,914d658c34542b3882aa11ffdb928190,
10419,"In this paper, a static non-cooperative game formulation of the problem of distributed charging in electrical vehicle (EV) networks is proposed. This formulation allows one to model the interaction between several EV which are connected to a common residential distribution transformer. Each EV aims at choosing the time at which it starts charging its battery in order to minimize an individual cost which is mainly related to the total power delivered by the transformer, the location of the time interval over which the charging operation is performed, and the charging duration needed for the considered EV to have its battery fully recharged. As individual cost functions are assumed to be memoryless, it is possible to show that the game of interest is always an ordinal potential game. More precisely, both an atomic and nonatomic versions of the charging game are considered. In both cases, equilibrium analysis is conducted. In particular, important issues such as equilibrium uniqueness and efficiency are tackled. Interestingly, both analytical and numerical results show that the efficiency loss due to decentralization (e.g., when cost functions such as distribution network Joule losses or life of residential distribution transformers when no thermal inertia is assumed) induced by charging is small and the corresponding “efficiency”, a notion close to the Price of Anarchy, tends to one when the number of EV increases.",martin hennebel,electrical vehicle,2012.0,,"2012 6th International Conference on Network Games, Control and Optimization (NetGCooP)",Beaude2012,False,,IEEE,Not available,Charging games in networks of electrical vehicles,914d658c34542b3882aa11ffdb928190,
10420,"In this paper, a static non-cooperative game formulation of the problem of distributed charging in electrical vehicle (EV) networks is proposed. This formulation allows one to model the interaction between several EV which are connected to a common residential distribution transformer. Each EV aims at choosing the time at which it starts charging its battery in order to minimize an individual cost which is mainly related to the total power delivered by the transformer, the location of the time interval over which the charging operation is performed, and the charging duration needed for the considered EV to have its battery fully recharged. As individual cost functions are assumed to be memoryless, it is possible to show that the game of interest is always an ordinal potential game. More precisely, both an atomic and nonatomic versions of the charging game are considered. In both cases, equilibrium analysis is conducted. In particular, important issues such as equilibrium uniqueness and efficiency are tackled. Interestingly, both analytical and numerical results show that the efficiency loss due to decentralization (e.g., when cost functions such as distribution network Joule losses or life of residential distribution transformers when no thermal inertia is assumed) induced by charging is small and the corresponding “efficiency”, a notion close to the Price of Anarchy, tends to one when the number of EV increases.",martin hennebel,distribution networks,2012.0,,"2012 6th International Conference on Network Games, Control and Optimization (NetGCooP)",Beaude2012,False,,IEEE,Not available,Charging games in networks of electrical vehicles,914d658c34542b3882aa11ffdb928190,
10421,"In this paper, a static non-cooperative game formulation of the problem of distributed charging in electrical vehicle (EV) networks is proposed. This formulation allows one to model the interaction between several EV which are connected to a common residential distribution transformer. Each EV aims at choosing the time at which it starts charging its battery in order to minimize an individual cost which is mainly related to the total power delivered by the transformer, the location of the time interval over which the charging operation is performed, and the charging duration needed for the considered EV to have its battery fully recharged. As individual cost functions are assumed to be memoryless, it is possible to show that the game of interest is always an ordinal potential game. More precisely, both an atomic and nonatomic versions of the charging game are considered. In both cases, equilibrium analysis is conducted. In particular, important issues such as equilibrium uniqueness and efficiency are tackled. Interestingly, both analytical and numerical results show that the efficiency loss due to decentralization (e.g., when cost functions such as distribution network Joule losses or life of residential distribution transformers when no thermal inertia is assumed) induced by charging is small and the corresponding “efficiency”, a notion close to the Price of Anarchy, tends to one when the number of EV increases.",martin hennebel,potential games,2012.0,,"2012 6th International Conference on Network Games, Control and Optimization (NetGCooP)",Beaude2012,False,,IEEE,Not available,Charging games in networks of electrical vehicles,914d658c34542b3882aa11ffdb928190,
10422,"In this paper, a static non-cooperative game formulation of the problem of distributed charging in electrical vehicle (EV) networks is proposed. This formulation allows one to model the interaction between several EV which are connected to a common residential distribution transformer. Each EV aims at choosing the time at which it starts charging its battery in order to minimize an individual cost which is mainly related to the total power delivered by the transformer, the location of the time interval over which the charging operation is performed, and the charging duration needed for the considered EV to have its battery fully recharged. As individual cost functions are assumed to be memoryless, it is possible to show that the game of interest is always an ordinal potential game. More precisely, both an atomic and nonatomic versions of the charging game are considered. In both cases, equilibrium analysis is conducted. In particular, important issues such as equilibrium uniqueness and efficiency are tackled. Interestingly, both analytical and numerical results show that the efficiency loss due to decentralization (e.g., when cost functions such as distribution network Joule losses or life of residential distribution transformers when no thermal inertia is assumed) induced by charging is small and the corresponding “efficiency”, a notion close to the Price of Anarchy, tends to one when the number of EV increases.",martin hennebel,Nash equilibrium,2012.0,,"2012 6th International Conference on Network Games, Control and Optimization (NetGCooP)",Beaude2012,False,,IEEE,Not available,Charging games in networks of electrical vehicles,914d658c34542b3882aa11ffdb928190,
10423,"In this paper, a static non-cooperative game formulation of the problem of distributed charging in electrical vehicle (EV) networks is proposed. This formulation allows one to model the interaction between several EV which are connected to a common residential distribution transformer. Each EV aims at choosing the time at which it starts charging its battery in order to minimize an individual cost which is mainly related to the total power delivered by the transformer, the location of the time interval over which the charging operation is performed, and the charging duration needed for the considered EV to have its battery fully recharged. As individual cost functions are assumed to be memoryless, it is possible to show that the game of interest is always an ordinal potential game. More precisely, both an atomic and nonatomic versions of the charging game are considered. In both cases, equilibrium analysis is conducted. In particular, important issues such as equilibrium uniqueness and efficiency are tackled. Interestingly, both analytical and numerical results show that the efficiency loss due to decentralization (e.g., when cost functions such as distribution network Joule losses or life of residential distribution transformers when no thermal inertia is assumed) induced by charging is small and the corresponding “efficiency”, a notion close to the Price of Anarchy, tends to one when the number of EV increases.",martin hennebel,price of anarchy,2012.0,,"2012 6th International Conference on Network Games, Control and Optimization (NetGCooP)",Beaude2012,False,,IEEE,Not available,Charging games in networks of electrical vehicles,914d658c34542b3882aa11ffdb928190,
10424,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",lok law,Games,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
10425,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",lok law,Nash equilibrium,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
10426,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",lok law,Optimized production technology,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
10427,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
10428,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",lok law,Resource management,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
10429,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",lok law,Computational modeling,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
10430,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",lok law,Computer science,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
10431,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",lok law,Erbium,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
10432,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",jianwei huang,Games,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
10433,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",jianwei huang,Nash equilibrium,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
10434,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",jianwei huang,Optimized production technology,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
10435,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",jianwei huang,Resource management,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
10436,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",jianwei huang,Computational modeling,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
10437,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",jianwei huang,Computer science,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
10438,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
10439,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
10440,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",jianwei huang,Erbium,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
10441,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",mingyan liu,Games,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
10442,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",mingyan liu,Nash equilibrium,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
10443,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",mingyan liu,Optimized production technology,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
10444,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",mingyan liu,Resource management,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
10445,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",mingyan liu,Computational modeling,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
10446,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",mingyan liu,Computer science,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
10447,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",mingyan liu,Erbium,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
10448,"In this paper, we address the problem of minimizing the energy cost of positioning nodes in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a two-fold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is supermodular and that it possesses a unique Nash equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",ana moragrega,Distributed algorithms,2013.0,10.1109/TSP.2013.2259160,IEEE Transactions on Signal Processing,Moragrega2013,False,,IEEE,Not available,Supermodular Game for Power Control in TOA-Based Positioning,cdba3d719214dc4acde5c4a909b15190,https://ieeexplore.ieee.org/document/6506112/
10449,"In this paper, we address the problem of minimizing the energy cost of positioning nodes in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a two-fold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is supermodular and that it possesses a unique Nash equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",ana moragrega,game theory,2013.0,10.1109/TSP.2013.2259160,IEEE Transactions on Signal Processing,Moragrega2013,False,,IEEE,Not available,Supermodular Game for Power Control in TOA-Based Positioning,cdba3d719214dc4acde5c4a909b15190,https://ieeexplore.ieee.org/document/6506112/
10450,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
10451,"In this paper, we address the problem of minimizing the energy cost of positioning nodes in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a two-fold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is supermodular and that it possesses a unique Nash equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",ana moragrega,positioning,2013.0,10.1109/TSP.2013.2259160,IEEE Transactions on Signal Processing,Moragrega2013,False,,IEEE,Not available,Supermodular Game for Power Control in TOA-Based Positioning,cdba3d719214dc4acde5c4a909b15190,https://ieeexplore.ieee.org/document/6506112/
10452,"In this paper, we address the problem of minimizing the energy cost of positioning nodes in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a two-fold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is supermodular and that it possesses a unique Nash equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",ana moragrega,supermodular games,2013.0,10.1109/TSP.2013.2259160,IEEE Transactions on Signal Processing,Moragrega2013,False,,IEEE,Not available,Supermodular Game for Power Control in TOA-Based Positioning,cdba3d719214dc4acde5c4a909b15190,https://ieeexplore.ieee.org/document/6506112/
10453,"In this paper, we address the problem of minimizing the energy cost of positioning nodes in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a two-fold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is supermodular and that it possesses a unique Nash equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",ana moragrega,wireless sensor networks,2013.0,10.1109/TSP.2013.2259160,IEEE Transactions on Signal Processing,Moragrega2013,False,,IEEE,Not available,Supermodular Game for Power Control in TOA-Based Positioning,cdba3d719214dc4acde5c4a909b15190,https://ieeexplore.ieee.org/document/6506112/
10454,"In this paper, we address the problem of minimizing the energy cost of positioning nodes in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a two-fold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is supermodular and that it possesses a unique Nash equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",pau closas,Distributed algorithms,2013.0,10.1109/TSP.2013.2259160,IEEE Transactions on Signal Processing,Moragrega2013,False,,IEEE,Not available,Supermodular Game for Power Control in TOA-Based Positioning,cdba3d719214dc4acde5c4a909b15190,https://ieeexplore.ieee.org/document/6506112/
10455,"In this paper, we address the problem of minimizing the energy cost of positioning nodes in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a two-fold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is supermodular and that it possesses a unique Nash equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",pau closas,game theory,2013.0,10.1109/TSP.2013.2259160,IEEE Transactions on Signal Processing,Moragrega2013,False,,IEEE,Not available,Supermodular Game for Power Control in TOA-Based Positioning,cdba3d719214dc4acde5c4a909b15190,https://ieeexplore.ieee.org/document/6506112/
10456,"In this paper, we address the problem of minimizing the energy cost of positioning nodes in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a two-fold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is supermodular and that it possesses a unique Nash equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",pau closas,positioning,2013.0,10.1109/TSP.2013.2259160,IEEE Transactions on Signal Processing,Moragrega2013,False,,IEEE,Not available,Supermodular Game for Power Control in TOA-Based Positioning,cdba3d719214dc4acde5c4a909b15190,https://ieeexplore.ieee.org/document/6506112/
10457,"In this paper, we address the problem of minimizing the energy cost of positioning nodes in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a two-fold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is supermodular and that it possesses a unique Nash equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",pau closas,supermodular games,2013.0,10.1109/TSP.2013.2259160,IEEE Transactions on Signal Processing,Moragrega2013,False,,IEEE,Not available,Supermodular Game for Power Control in TOA-Based Positioning,cdba3d719214dc4acde5c4a909b15190,https://ieeexplore.ieee.org/document/6506112/
10458,"In this paper, we address the problem of minimizing the energy cost of positioning nodes in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a two-fold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is supermodular and that it possesses a unique Nash equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",pau closas,wireless sensor networks,2013.0,10.1109/TSP.2013.2259160,IEEE Transactions on Signal Processing,Moragrega2013,False,,IEEE,Not available,Supermodular Game for Power Control in TOA-Based Positioning,cdba3d719214dc4acde5c4a909b15190,https://ieeexplore.ieee.org/document/6506112/
10459,"In this paper, we address the problem of minimizing the energy cost of positioning nodes in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a two-fold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is supermodular and that it possesses a unique Nash equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",christian ibars,Distributed algorithms,2013.0,10.1109/TSP.2013.2259160,IEEE Transactions on Signal Processing,Moragrega2013,False,,IEEE,Not available,Supermodular Game for Power Control in TOA-Based Positioning,cdba3d719214dc4acde5c4a909b15190,https://ieeexplore.ieee.org/document/6506112/
10460,"In this paper, we address the problem of minimizing the energy cost of positioning nodes in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a two-fold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is supermodular and that it possesses a unique Nash equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",christian ibars,game theory,2013.0,10.1109/TSP.2013.2259160,IEEE Transactions on Signal Processing,Moragrega2013,False,,IEEE,Not available,Supermodular Game for Power Control in TOA-Based Positioning,cdba3d719214dc4acde5c4a909b15190,https://ieeexplore.ieee.org/document/6506112/
10461,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
10462,"In this paper, we address the problem of minimizing the energy cost of positioning nodes in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a two-fold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is supermodular and that it possesses a unique Nash equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",christian ibars,positioning,2013.0,10.1109/TSP.2013.2259160,IEEE Transactions on Signal Processing,Moragrega2013,False,,IEEE,Not available,Supermodular Game for Power Control in TOA-Based Positioning,cdba3d719214dc4acde5c4a909b15190,https://ieeexplore.ieee.org/document/6506112/
10463,"In this paper, we address the problem of minimizing the energy cost of positioning nodes in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a two-fold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is supermodular and that it possesses a unique Nash equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",christian ibars,supermodular games,2013.0,10.1109/TSP.2013.2259160,IEEE Transactions on Signal Processing,Moragrega2013,False,,IEEE,Not available,Supermodular Game for Power Control in TOA-Based Positioning,cdba3d719214dc4acde5c4a909b15190,https://ieeexplore.ieee.org/document/6506112/
10464,"In this paper, we address the problem of minimizing the energy cost of positioning nodes in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a two-fold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is supermodular and that it possesses a unique Nash equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",christian ibars,wireless sensor networks,2013.0,10.1109/TSP.2013.2259160,IEEE Transactions on Signal Processing,Moragrega2013,False,,IEEE,Not available,Supermodular Game for Power Control in TOA-Based Positioning,cdba3d719214dc4acde5c4a909b15190,https://ieeexplore.ieee.org/document/6506112/
10465,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",yunpeng li,Mobile social networks,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
10466,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",yunpeng li,mobile crowdsensing,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
10467,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",yunpeng li,information sharing,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
10468,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",yunpeng li,routing game,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
10469,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",yunpeng li,price of anarchy,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
10470,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",yunpeng li,mechanism design,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
10471,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",yunpeng li,side payments,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
10472,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
10473,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",yunpeng li,content-restriction,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
10474,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",costas courcoubetis,Mobile social networks,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
10475,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",costas courcoubetis,mobile crowdsensing,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
10476,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",costas courcoubetis,information sharing,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
10477,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",costas courcoubetis,routing game,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
10478,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",costas courcoubetis,price of anarchy,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
10479,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",costas courcoubetis,mechanism design,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
10480,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",costas courcoubetis,side payments,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
10481,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",costas courcoubetis,content-restriction,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
10482,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",lingjie duan,Mobile social networks,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
10483,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
10484,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",lingjie duan,mobile crowdsensing,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
10485,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",lingjie duan,information sharing,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
10486,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",lingjie duan,routing game,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
10487,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",lingjie duan,price of anarchy,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
10488,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",lingjie duan,mechanism design,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
10489,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",lingjie duan,side payments,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
10490,"Today, mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model, the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths, despite the potentially higher costs associated with their trips. In this paper, we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decides their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyze two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. Under asymmetric information about user types (their valuations for content quality), both mechanisms efficiently penalize the participants that use the low-cost path and reward the participants that take the high-cost path. They lead to greater path diversity and hence to more total available content at the social cost of reduced user participation or restricted content to part of the users. We show that user heterogeneity can have opposite effects on social efficiency depending on the mechanism used. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.",lingjie duan,content-restriction,2017.0,10.1109/JSAC.2017.2659578,IEEE Journal on Selected Areas in Communications,Li2017,False,,IEEE,Not available,Dynamic Routing for Social Information Sharing,bc77298f4d1bb3c73740ca392fcfca25,https://ieeexplore.ieee.org/document/7835196/
10491,"In this paper, we consider a cognitive radio network where multiple heterogenous secondary users (SUs) compete for transmissions on idle primary channels. We model this as a singleton congestion game, where the probability for an SU to successfully access a channel decreases with the number of SUs selecting the same channel. In particular, we consider player-specific payoffs that depend not only on the shares of the channel but also on different preference constants. Such system can be modeled as a congestion game, and we study the price of anarchy (PoA) for four families of such a game: identical, player-specific symmetric, resource-specific symmetric, and asymmetric games. We characterize the worst-case PoA in terms of the number of SUs and channels, and illustrate the network scenarios under which the worse case performance is reached. We further illustrate the PoA results with two Medium Access Control (MAC) schemes: uniform MAC and slotted Aloha. For both cases, we observe that the average performance of the game equilibrium is better than the worst-case PoA. Our study sheds light on how to design stable systems with smaller efficiency loss of the equilibrium.",lok law,Cognitive radio,2012.0,10.1109/TWC.2012.083112.120371,IEEE Transactions on Wireless Communications,Law2012,False,,IEEE,Not available,Price of Anarchy for Congestion Games in Cognitive Radio Networks,d78287bf43af78c169dac2e1b5572756,https://ieeexplore.ieee.org/document/6294502/
10492,"In this paper, we consider a cognitive radio network where multiple heterogenous secondary users (SUs) compete for transmissions on idle primary channels. We model this as a singleton congestion game, where the probability for an SU to successfully access a channel decreases with the number of SUs selecting the same channel. In particular, we consider player-specific payoffs that depend not only on the shares of the channel but also on different preference constants. Such system can be modeled as a congestion game, and we study the price of anarchy (PoA) for four families of such a game: identical, player-specific symmetric, resource-specific symmetric, and asymmetric games. We characterize the worst-case PoA in terms of the number of SUs and channels, and illustrate the network scenarios under which the worse case performance is reached. We further illustrate the PoA results with two Medium Access Control (MAC) schemes: uniform MAC and slotted Aloha. For both cases, we observe that the average performance of the game equilibrium is better than the worst-case PoA. Our study sheds light on how to design stable systems with smaller efficiency loss of the equilibrium.",lok law,spectrum sharing,2012.0,10.1109/TWC.2012.083112.120371,IEEE Transactions on Wireless Communications,Law2012,False,,IEEE,Not available,Price of Anarchy for Congestion Games in Cognitive Radio Networks,d78287bf43af78c169dac2e1b5572756,https://ieeexplore.ieee.org/document/6294502/
10493,"In this paper, we consider a cognitive radio network where multiple heterogenous secondary users (SUs) compete for transmissions on idle primary channels. We model this as a singleton congestion game, where the probability for an SU to successfully access a channel decreases with the number of SUs selecting the same channel. In particular, we consider player-specific payoffs that depend not only on the shares of the channel but also on different preference constants. Such system can be modeled as a congestion game, and we study the price of anarchy (PoA) for four families of such a game: identical, player-specific symmetric, resource-specific symmetric, and asymmetric games. We characterize the worst-case PoA in terms of the number of SUs and channels, and illustrate the network scenarios under which the worse case performance is reached. We further illustrate the PoA results with two Medium Access Control (MAC) schemes: uniform MAC and slotted Aloha. For both cases, we observe that the average performance of the game equilibrium is better than the worst-case PoA. Our study sheds light on how to design stable systems with smaller efficiency loss of the equilibrium.",lok law,congestion game,2012.0,10.1109/TWC.2012.083112.120371,IEEE Transactions on Wireless Communications,Law2012,False,,IEEE,Not available,Price of Anarchy for Congestion Games in Cognitive Radio Networks,d78287bf43af78c169dac2e1b5572756,https://ieeexplore.ieee.org/document/6294502/
10494,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
10495,"In this paper, we consider a cognitive radio network where multiple heterogenous secondary users (SUs) compete for transmissions on idle primary channels. We model this as a singleton congestion game, where the probability for an SU to successfully access a channel decreases with the number of SUs selecting the same channel. In particular, we consider player-specific payoffs that depend not only on the shares of the channel but also on different preference constants. Such system can be modeled as a congestion game, and we study the price of anarchy (PoA) for four families of such a game: identical, player-specific symmetric, resource-specific symmetric, and asymmetric games. We characterize the worst-case PoA in terms of the number of SUs and channels, and illustrate the network scenarios under which the worse case performance is reached. We further illustrate the PoA results with two Medium Access Control (MAC) schemes: uniform MAC and slotted Aloha. For both cases, we observe that the average performance of the game equilibrium is better than the worst-case PoA. Our study sheds light on how to design stable systems with smaller efficiency loss of the equilibrium.",lok law,price of anarchy,2012.0,10.1109/TWC.2012.083112.120371,IEEE Transactions on Wireless Communications,Law2012,False,,IEEE,Not available,Price of Anarchy for Congestion Games in Cognitive Radio Networks,d78287bf43af78c169dac2e1b5572756,https://ieeexplore.ieee.org/document/6294502/
10496,"In this paper, we consider a cognitive radio network where multiple heterogenous secondary users (SUs) compete for transmissions on idle primary channels. We model this as a singleton congestion game, where the probability for an SU to successfully access a channel decreases with the number of SUs selecting the same channel. In particular, we consider player-specific payoffs that depend not only on the shares of the channel but also on different preference constants. Such system can be modeled as a congestion game, and we study the price of anarchy (PoA) for four families of such a game: identical, player-specific symmetric, resource-specific symmetric, and asymmetric games. We characterize the worst-case PoA in terms of the number of SUs and channels, and illustrate the network scenarios under which the worse case performance is reached. We further illustrate the PoA results with two Medium Access Control (MAC) schemes: uniform MAC and slotted Aloha. For both cases, we observe that the average performance of the game equilibrium is better than the worst-case PoA. Our study sheds light on how to design stable systems with smaller efficiency loss of the equilibrium.",jianwei huang,Cognitive radio,2012.0,10.1109/TWC.2012.083112.120371,IEEE Transactions on Wireless Communications,Law2012,False,,IEEE,Not available,Price of Anarchy for Congestion Games in Cognitive Radio Networks,d78287bf43af78c169dac2e1b5572756,https://ieeexplore.ieee.org/document/6294502/
10497,"In this paper, we consider a cognitive radio network where multiple heterogenous secondary users (SUs) compete for transmissions on idle primary channels. We model this as a singleton congestion game, where the probability for an SU to successfully access a channel decreases with the number of SUs selecting the same channel. In particular, we consider player-specific payoffs that depend not only on the shares of the channel but also on different preference constants. Such system can be modeled as a congestion game, and we study the price of anarchy (PoA) for four families of such a game: identical, player-specific symmetric, resource-specific symmetric, and asymmetric games. We characterize the worst-case PoA in terms of the number of SUs and channels, and illustrate the network scenarios under which the worse case performance is reached. We further illustrate the PoA results with two Medium Access Control (MAC) schemes: uniform MAC and slotted Aloha. For both cases, we observe that the average performance of the game equilibrium is better than the worst-case PoA. Our study sheds light on how to design stable systems with smaller efficiency loss of the equilibrium.",jianwei huang,spectrum sharing,2012.0,10.1109/TWC.2012.083112.120371,IEEE Transactions on Wireless Communications,Law2012,False,,IEEE,Not available,Price of Anarchy for Congestion Games in Cognitive Radio Networks,d78287bf43af78c169dac2e1b5572756,https://ieeexplore.ieee.org/document/6294502/
10498,"In this paper, we consider a cognitive radio network where multiple heterogenous secondary users (SUs) compete for transmissions on idle primary channels. We model this as a singleton congestion game, where the probability for an SU to successfully access a channel decreases with the number of SUs selecting the same channel. In particular, we consider player-specific payoffs that depend not only on the shares of the channel but also on different preference constants. Such system can be modeled as a congestion game, and we study the price of anarchy (PoA) for four families of such a game: identical, player-specific symmetric, resource-specific symmetric, and asymmetric games. We characterize the worst-case PoA in terms of the number of SUs and channels, and illustrate the network scenarios under which the worse case performance is reached. We further illustrate the PoA results with two Medium Access Control (MAC) schemes: uniform MAC and slotted Aloha. For both cases, we observe that the average performance of the game equilibrium is better than the worst-case PoA. Our study sheds light on how to design stable systems with smaller efficiency loss of the equilibrium.",jianwei huang,congestion game,2012.0,10.1109/TWC.2012.083112.120371,IEEE Transactions on Wireless Communications,Law2012,False,,IEEE,Not available,Price of Anarchy for Congestion Games in Cognitive Radio Networks,d78287bf43af78c169dac2e1b5572756,https://ieeexplore.ieee.org/document/6294502/
10499,"In this paper, we consider a cognitive radio network where multiple heterogenous secondary users (SUs) compete for transmissions on idle primary channels. We model this as a singleton congestion game, where the probability for an SU to successfully access a channel decreases with the number of SUs selecting the same channel. In particular, we consider player-specific payoffs that depend not only on the shares of the channel but also on different preference constants. Such system can be modeled as a congestion game, and we study the price of anarchy (PoA) for four families of such a game: identical, player-specific symmetric, resource-specific symmetric, and asymmetric games. We characterize the worst-case PoA in terms of the number of SUs and channels, and illustrate the network scenarios under which the worse case performance is reached. We further illustrate the PoA results with two Medium Access Control (MAC) schemes: uniform MAC and slotted Aloha. For both cases, we observe that the average performance of the game equilibrium is better than the worst-case PoA. Our study sheds light on how to design stable systems with smaller efficiency loss of the equilibrium.",jianwei huang,price of anarchy,2012.0,10.1109/TWC.2012.083112.120371,IEEE Transactions on Wireless Communications,Law2012,False,,IEEE,Not available,Price of Anarchy for Congestion Games in Cognitive Radio Networks,d78287bf43af78c169dac2e1b5572756,https://ieeexplore.ieee.org/document/6294502/
10500,"In this paper, we consider a cognitive radio network where multiple heterogenous secondary users (SUs) compete for transmissions on idle primary channels. We model this as a singleton congestion game, where the probability for an SU to successfully access a channel decreases with the number of SUs selecting the same channel. In particular, we consider player-specific payoffs that depend not only on the shares of the channel but also on different preference constants. Such system can be modeled as a congestion game, and we study the price of anarchy (PoA) for four families of such a game: identical, player-specific symmetric, resource-specific symmetric, and asymmetric games. We characterize the worst-case PoA in terms of the number of SUs and channels, and illustrate the network scenarios under which the worse case performance is reached. We further illustrate the PoA results with two Medium Access Control (MAC) schemes: uniform MAC and slotted Aloha. For both cases, we observe that the average performance of the game equilibrium is better than the worst-case PoA. Our study sheds light on how to design stable systems with smaller efficiency loss of the equilibrium.",mingyan liu,Cognitive radio,2012.0,10.1109/TWC.2012.083112.120371,IEEE Transactions on Wireless Communications,Law2012,False,,IEEE,Not available,Price of Anarchy for Congestion Games in Cognitive Radio Networks,d78287bf43af78c169dac2e1b5572756,https://ieeexplore.ieee.org/document/6294502/
10501,"In this paper, we consider a cognitive radio network where multiple heterogenous secondary users (SUs) compete for transmissions on idle primary channels. We model this as a singleton congestion game, where the probability for an SU to successfully access a channel decreases with the number of SUs selecting the same channel. In particular, we consider player-specific payoffs that depend not only on the shares of the channel but also on different preference constants. Such system can be modeled as a congestion game, and we study the price of anarchy (PoA) for four families of such a game: identical, player-specific symmetric, resource-specific symmetric, and asymmetric games. We characterize the worst-case PoA in terms of the number of SUs and channels, and illustrate the network scenarios under which the worse case performance is reached. We further illustrate the PoA results with two Medium Access Control (MAC) schemes: uniform MAC and slotted Aloha. For both cases, we observe that the average performance of the game equilibrium is better than the worst-case PoA. Our study sheds light on how to design stable systems with smaller efficiency loss of the equilibrium.",mingyan liu,spectrum sharing,2012.0,10.1109/TWC.2012.083112.120371,IEEE Transactions on Wireless Communications,Law2012,False,,IEEE,Not available,Price of Anarchy for Congestion Games in Cognitive Radio Networks,d78287bf43af78c169dac2e1b5572756,https://ieeexplore.ieee.org/document/6294502/
10502,"In this paper, we consider a cognitive radio network where multiple heterogenous secondary users (SUs) compete for transmissions on idle primary channels. We model this as a singleton congestion game, where the probability for an SU to successfully access a channel decreases with the number of SUs selecting the same channel. In particular, we consider player-specific payoffs that depend not only on the shares of the channel but also on different preference constants. Such system can be modeled as a congestion game, and we study the price of anarchy (PoA) for four families of such a game: identical, player-specific symmetric, resource-specific symmetric, and asymmetric games. We characterize the worst-case PoA in terms of the number of SUs and channels, and illustrate the network scenarios under which the worse case performance is reached. We further illustrate the PoA results with two Medium Access Control (MAC) schemes: uniform MAC and slotted Aloha. For both cases, we observe that the average performance of the game equilibrium is better than the worst-case PoA. Our study sheds light on how to design stable systems with smaller efficiency loss of the equilibrium.",mingyan liu,congestion game,2012.0,10.1109/TWC.2012.083112.120371,IEEE Transactions on Wireless Communications,Law2012,False,,IEEE,Not available,Price of Anarchy for Congestion Games in Cognitive Radio Networks,d78287bf43af78c169dac2e1b5572756,https://ieeexplore.ieee.org/document/6294502/
10503,"In this paper, we consider a cognitive radio network where multiple heterogenous secondary users (SUs) compete for transmissions on idle primary channels. We model this as a singleton congestion game, where the probability for an SU to successfully access a channel decreases with the number of SUs selecting the same channel. In particular, we consider player-specific payoffs that depend not only on the shares of the channel but also on different preference constants. Such system can be modeled as a congestion game, and we study the price of anarchy (PoA) for four families of such a game: identical, player-specific symmetric, resource-specific symmetric, and asymmetric games. We characterize the worst-case PoA in terms of the number of SUs and channels, and illustrate the network scenarios under which the worse case performance is reached. We further illustrate the PoA results with two Medium Access Control (MAC) schemes: uniform MAC and slotted Aloha. For both cases, we observe that the average performance of the game equilibrium is better than the worst-case PoA. Our study sheds light on how to design stable systems with smaller efficiency loss of the equilibrium.",mingyan liu,price of anarchy,2012.0,10.1109/TWC.2012.083112.120371,IEEE Transactions on Wireless Communications,Law2012,False,,IEEE,Not available,Price of Anarchy for Congestion Games in Cognitive Radio Networks,d78287bf43af78c169dac2e1b5572756,https://ieeexplore.ieee.org/document/6294502/
10504,"This paper studies the problem of content distribution in wireless peer-to-peer networks with selfish nodes. In this problem a group of wireless nodes exchange data over a lossless broadcast channel. Each node aims to increase its own download rate and minimize its upload rate. We propose a distributed protocol that provides incentives for the nodes to participate in the content distribution. Our protocol does not require any exchange of money, reputation, etc., and hence can be easily implemented without additional infrastructure. Moreover, our protocol can be easily modified to employ network coding. Focusing on the important case in which the system contains two files that need to be distributed, we derive a closed-form expression of Nash Equilibria. We also derive the prices of anarchy, both from each node's perspective and the whole system's perspective. Furthermore, we propose a distributed mechanism where the strategy of each node is only based on the local information and show that the mechanism converges to a Nash Equilibrium. We also introduce an approach for calculating Nash Equilibria for systems that incorporate network coding when more than two files need to be distributed.",i-hong hou,Encoding,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Hou2013,False,,IEEE,Not available,A non-monetary protocol for peer-to-peer content distribution in wireless broadcast networks with network coding,6f0349238813aa9ecf23742874393812,https://ieeexplore.ieee.org/document/6576431/
10505,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
10506,"This paper studies the problem of content distribution in wireless peer-to-peer networks with selfish nodes. In this problem a group of wireless nodes exchange data over a lossless broadcast channel. Each node aims to increase its own download rate and minimize its upload rate. We propose a distributed protocol that provides incentives for the nodes to participate in the content distribution. Our protocol does not require any exchange of money, reputation, etc., and hence can be easily implemented without additional infrastructure. Moreover, our protocol can be easily modified to employ network coding. Focusing on the important case in which the system contains two files that need to be distributed, we derive a closed-form expression of Nash Equilibria. We also derive the prices of anarchy, both from each node's perspective and the whole system's perspective. Furthermore, we propose a distributed mechanism where the strategy of each node is only based on the local information and show that the mechanism converges to a Nash Equilibrium. We also introduce an approach for calculating Nash Equilibria for systems that incorporate network coding when more than two files need to be distributed.",i-hong hou,Wireless communication,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Hou2013,False,,IEEE,Not available,A non-monetary protocol for peer-to-peer content distribution in wireless broadcast networks with network coding,6f0349238813aa9ecf23742874393812,https://ieeexplore.ieee.org/document/6576431/
10507,"This paper studies the problem of content distribution in wireless peer-to-peer networks with selfish nodes. In this problem a group of wireless nodes exchange data over a lossless broadcast channel. Each node aims to increase its own download rate and minimize its upload rate. We propose a distributed protocol that provides incentives for the nodes to participate in the content distribution. Our protocol does not require any exchange of money, reputation, etc., and hence can be easily implemented without additional infrastructure. Moreover, our protocol can be easily modified to employ network coding. Focusing on the important case in which the system contains two files that need to be distributed, we derive a closed-form expression of Nash Equilibria. We also derive the prices of anarchy, both from each node's perspective and the whole system's perspective. Furthermore, we propose a distributed mechanism where the strategy of each node is only based on the local information and show that the mechanism converges to a Nash Equilibrium. We also introduce an approach for calculating Nash Equilibria for systems that incorporate network coding when more than two files need to be distributed.",i-hong hou,Broadcasting,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Hou2013,False,,IEEE,Not available,A non-monetary protocol for peer-to-peer content distribution in wireless broadcast networks with network coding,6f0349238813aa9ecf23742874393812,https://ieeexplore.ieee.org/document/6576431/
10508,"This paper studies the problem of content distribution in wireless peer-to-peer networks with selfish nodes. In this problem a group of wireless nodes exchange data over a lossless broadcast channel. Each node aims to increase its own download rate and minimize its upload rate. We propose a distributed protocol that provides incentives for the nodes to participate in the content distribution. Our protocol does not require any exchange of money, reputation, etc., and hence can be easily implemented without additional infrastructure. Moreover, our protocol can be easily modified to employ network coding. Focusing on the important case in which the system contains two files that need to be distributed, we derive a closed-form expression of Nash Equilibria. We also derive the prices of anarchy, both from each node's perspective and the whole system's perspective. Furthermore, we propose a distributed mechanism where the strategy of each node is only based on the local information and show that the mechanism converges to a Nash Equilibrium. We also introduce an approach for calculating Nash Equilibria for systems that incorporate network coding when more than two files need to be distributed.",yao liu,Encoding,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Hou2013,False,,IEEE,Not available,A non-monetary protocol for peer-to-peer content distribution in wireless broadcast networks with network coding,6f0349238813aa9ecf23742874393812,https://ieeexplore.ieee.org/document/6576431/
10509,"This paper studies the problem of content distribution in wireless peer-to-peer networks with selfish nodes. In this problem a group of wireless nodes exchange data over a lossless broadcast channel. Each node aims to increase its own download rate and minimize its upload rate. We propose a distributed protocol that provides incentives for the nodes to participate in the content distribution. Our protocol does not require any exchange of money, reputation, etc., and hence can be easily implemented without additional infrastructure. Moreover, our protocol can be easily modified to employ network coding. Focusing on the important case in which the system contains two files that need to be distributed, we derive a closed-form expression of Nash Equilibria. We also derive the prices of anarchy, both from each node's perspective and the whole system's perspective. Furthermore, we propose a distributed mechanism where the strategy of each node is only based on the local information and show that the mechanism converges to a Nash Equilibrium. We also introduce an approach for calculating Nash Equilibria for systems that incorporate network coding when more than two files need to be distributed.",yao liu,Wireless communication,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Hou2013,False,,IEEE,Not available,A non-monetary protocol for peer-to-peer content distribution in wireless broadcast networks with network coding,6f0349238813aa9ecf23742874393812,https://ieeexplore.ieee.org/document/6576431/
10510,"This paper studies the problem of content distribution in wireless peer-to-peer networks with selfish nodes. In this problem a group of wireless nodes exchange data over a lossless broadcast channel. Each node aims to increase its own download rate and minimize its upload rate. We propose a distributed protocol that provides incentives for the nodes to participate in the content distribution. Our protocol does not require any exchange of money, reputation, etc., and hence can be easily implemented without additional infrastructure. Moreover, our protocol can be easily modified to employ network coding. Focusing on the important case in which the system contains two files that need to be distributed, we derive a closed-form expression of Nash Equilibria. We also derive the prices of anarchy, both from each node's perspective and the whole system's perspective. Furthermore, we propose a distributed mechanism where the strategy of each node is only based on the local information and show that the mechanism converges to a Nash Equilibrium. We also introduce an approach for calculating Nash Equilibria for systems that incorporate network coding when more than two files need to be distributed.",yao liu,Broadcasting,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Hou2013,False,,IEEE,Not available,A non-monetary protocol for peer-to-peer content distribution in wireless broadcast networks with network coding,6f0349238813aa9ecf23742874393812,https://ieeexplore.ieee.org/document/6576431/
10511,"This paper studies the problem of content distribution in wireless peer-to-peer networks with selfish nodes. In this problem a group of wireless nodes exchange data over a lossless broadcast channel. Each node aims to increase its own download rate and minimize its upload rate. We propose a distributed protocol that provides incentives for the nodes to participate in the content distribution. Our protocol does not require any exchange of money, reputation, etc., and hence can be easily implemented without additional infrastructure. Moreover, our protocol can be easily modified to employ network coding. Focusing on the important case in which the system contains two files that need to be distributed, we derive a closed-form expression of Nash Equilibria. We also derive the prices of anarchy, both from each node's perspective and the whole system's perspective. Furthermore, we propose a distributed mechanism where the strategy of each node is only based on the local information and show that the mechanism converges to a Nash Equilibrium. We also introduce an approach for calculating Nash Equilibria for systems that incorporate network coding when more than two files need to be distributed.",alex sprintson,Encoding,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Hou2013,False,,IEEE,Not available,A non-monetary protocol for peer-to-peer content distribution in wireless broadcast networks with network coding,6f0349238813aa9ecf23742874393812,https://ieeexplore.ieee.org/document/6576431/
10512,"This paper studies the problem of content distribution in wireless peer-to-peer networks with selfish nodes. In this problem a group of wireless nodes exchange data over a lossless broadcast channel. Each node aims to increase its own download rate and minimize its upload rate. We propose a distributed protocol that provides incentives for the nodes to participate in the content distribution. Our protocol does not require any exchange of money, reputation, etc., and hence can be easily implemented without additional infrastructure. Moreover, our protocol can be easily modified to employ network coding. Focusing on the important case in which the system contains two files that need to be distributed, we derive a closed-form expression of Nash Equilibria. We also derive the prices of anarchy, both from each node's perspective and the whole system's perspective. Furthermore, we propose a distributed mechanism where the strategy of each node is only based on the local information and show that the mechanism converges to a Nash Equilibrium. We also introduce an approach for calculating Nash Equilibria for systems that incorporate network coding when more than two files need to be distributed.",alex sprintson,Wireless communication,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Hou2013,False,,IEEE,Not available,A non-monetary protocol for peer-to-peer content distribution in wireless broadcast networks with network coding,6f0349238813aa9ecf23742874393812,https://ieeexplore.ieee.org/document/6576431/
10513,"This paper studies the problem of content distribution in wireless peer-to-peer networks with selfish nodes. In this problem a group of wireless nodes exchange data over a lossless broadcast channel. Each node aims to increase its own download rate and minimize its upload rate. We propose a distributed protocol that provides incentives for the nodes to participate in the content distribution. Our protocol does not require any exchange of money, reputation, etc., and hence can be easily implemented without additional infrastructure. Moreover, our protocol can be easily modified to employ network coding. Focusing on the important case in which the system contains two files that need to be distributed, we derive a closed-form expression of Nash Equilibria. We also derive the prices of anarchy, both from each node's perspective and the whole system's perspective. Furthermore, we propose a distributed mechanism where the strategy of each node is only based on the local information and show that the mechanism converges to a Nash Equilibrium. We also introduce an approach for calculating Nash Equilibria for systems that incorporate network coding when more than two files need to be distributed.",alex sprintson,Broadcasting,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Hou2013,False,,IEEE,Not available,A non-monetary protocol for peer-to-peer content distribution in wireless broadcast networks with network coding,6f0349238813aa9ecf23742874393812,https://ieeexplore.ieee.org/document/6576431/
10514,"We consider the concert queueing game in the fluid framework, where the service facility opens at a specified time, the customers are particles in a fluid with homogeneous costs that are linear and additive in the waiting time and in the time to service completion, and wish to choose their own arrival times so as to minimize their cost. This problem has recently been analyzed under the assumption that the total volume of arriving customers is deterministic and known beforehand. We consider here the more plausible setting where this volume may be random, and only its probability distribution is known beforehand. In this setting, we identify the unique symmetric Nash equilibrium and show that under it the customer behavior significantly differs from the case where such uncertainties do not exist. While, in the latter case, the equilibrium profile is uniform, in the former case it is uniform up to a point and then it tapers off. We also solve the associated optimization problem to determine the socially optimal solution when the central planner is unaware of the actual amount of arrivals. Interestingly, the Price of Anarchy (ratio of the social cost of the equilibrium solution to that of the optimal one) for this model turns out to be two exactly, as in the deterministic case, despite the different form of the social and equilibrium arrival profiles.",sandeep juneja,Fluids,2012.0,10.4108/valuetools.2012.250166,6th International ICST Conference on Performance Evaluation Methodologies and Tools,Juneja2012,False,,IEEE,Not available,The concert queueing game with a random volume of arrivals,9626b38ca07343c760573194f79e112c,https://ieeexplore.ieee.org/document/6376339/
10515,"We consider the concert queueing game in the fluid framework, where the service facility opens at a specified time, the customers are particles in a fluid with homogeneous costs that are linear and additive in the waiting time and in the time to service completion, and wish to choose their own arrival times so as to minimize their cost. This problem has recently been analyzed under the assumption that the total volume of arriving customers is deterministic and known beforehand. We consider here the more plausible setting where this volume may be random, and only its probability distribution is known beforehand. In this setting, we identify the unique symmetric Nash equilibrium and show that under it the customer behavior significantly differs from the case where such uncertainties do not exist. While, in the latter case, the equilibrium profile is uniform, in the former case it is uniform up to a point and then it tapers off. We also solve the associated optimization problem to determine the socially optimal solution when the central planner is unaware of the actual amount of arrivals. Interestingly, the Price of Anarchy (ratio of the social cost of the equilibrium solution to that of the optimal one) for this model turns out to be two exactly, as in the deterministic case, despite the different form of the social and equilibrium arrival profiles.",sandeep juneja,Standards,2012.0,10.4108/valuetools.2012.250166,6th International ICST Conference on Performance Evaluation Methodologies and Tools,Juneja2012,False,,IEEE,Not available,The concert queueing game with a random volume of arrivals,9626b38ca07343c760573194f79e112c,https://ieeexplore.ieee.org/document/6376339/
10516,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
10517,"We consider the concert queueing game in the fluid framework, where the service facility opens at a specified time, the customers are particles in a fluid with homogeneous costs that are linear and additive in the waiting time and in the time to service completion, and wish to choose their own arrival times so as to minimize their cost. This problem has recently been analyzed under the assumption that the total volume of arriving customers is deterministic and known beforehand. We consider here the more plausible setting where this volume may be random, and only its probability distribution is known beforehand. In this setting, we identify the unique symmetric Nash equilibrium and show that under it the customer behavior significantly differs from the case where such uncertainties do not exist. While, in the latter case, the equilibrium profile is uniform, in the former case it is uniform up to a point and then it tapers off. We also solve the associated optimization problem to determine the socially optimal solution when the central planner is unaware of the actual amount of arrivals. Interestingly, the Price of Anarchy (ratio of the social cost of the equilibrium solution to that of the optimal one) for this model turns out to be two exactly, as in the deterministic case, despite the different form of the social and equilibrium arrival profiles.",sandeep juneja,Facsimile,2012.0,10.4108/valuetools.2012.250166,6th International ICST Conference on Performance Evaluation Methodologies and Tools,Juneja2012,False,,IEEE,Not available,The concert queueing game with a random volume of arrivals,9626b38ca07343c760573194f79e112c,https://ieeexplore.ieee.org/document/6376339/
10518,"We consider the concert queueing game in the fluid framework, where the service facility opens at a specified time, the customers are particles in a fluid with homogeneous costs that are linear and additive in the waiting time and in the time to service completion, and wish to choose their own arrival times so as to minimize their cost. This problem has recently been analyzed under the assumption that the total volume of arriving customers is deterministic and known beforehand. We consider here the more plausible setting where this volume may be random, and only its probability distribution is known beforehand. In this setting, we identify the unique symmetric Nash equilibrium and show that under it the customer behavior significantly differs from the case where such uncertainties do not exist. While, in the latter case, the equilibrium profile is uniform, in the former case it is uniform up to a point and then it tapers off. We also solve the associated optimization problem to determine the socially optimal solution when the central planner is unaware of the actual amount of arrivals. Interestingly, the Price of Anarchy (ratio of the social cost of the equilibrium solution to that of the optimal one) for this model turns out to be two exactly, as in the deterministic case, despite the different form of the social and equilibrium arrival profiles.",tushar raheja,Fluids,2012.0,10.4108/valuetools.2012.250166,6th International ICST Conference on Performance Evaluation Methodologies and Tools,Juneja2012,False,,IEEE,Not available,The concert queueing game with a random volume of arrivals,9626b38ca07343c760573194f79e112c,https://ieeexplore.ieee.org/document/6376339/
10519,"We consider the concert queueing game in the fluid framework, where the service facility opens at a specified time, the customers are particles in a fluid with homogeneous costs that are linear and additive in the waiting time and in the time to service completion, and wish to choose their own arrival times so as to minimize their cost. This problem has recently been analyzed under the assumption that the total volume of arriving customers is deterministic and known beforehand. We consider here the more plausible setting where this volume may be random, and only its probability distribution is known beforehand. In this setting, we identify the unique symmetric Nash equilibrium and show that under it the customer behavior significantly differs from the case where such uncertainties do not exist. While, in the latter case, the equilibrium profile is uniform, in the former case it is uniform up to a point and then it tapers off. We also solve the associated optimization problem to determine the socially optimal solution when the central planner is unaware of the actual amount of arrivals. Interestingly, the Price of Anarchy (ratio of the social cost of the equilibrium solution to that of the optimal one) for this model turns out to be two exactly, as in the deterministic case, despite the different form of the social and equilibrium arrival profiles.",tushar raheja,Standards,2012.0,10.4108/valuetools.2012.250166,6th International ICST Conference on Performance Evaluation Methodologies and Tools,Juneja2012,False,,IEEE,Not available,The concert queueing game with a random volume of arrivals,9626b38ca07343c760573194f79e112c,https://ieeexplore.ieee.org/document/6376339/
10520,"We consider the concert queueing game in the fluid framework, where the service facility opens at a specified time, the customers are particles in a fluid with homogeneous costs that are linear and additive in the waiting time and in the time to service completion, and wish to choose their own arrival times so as to minimize their cost. This problem has recently been analyzed under the assumption that the total volume of arriving customers is deterministic and known beforehand. We consider here the more plausible setting where this volume may be random, and only its probability distribution is known beforehand. In this setting, we identify the unique symmetric Nash equilibrium and show that under it the customer behavior significantly differs from the case where such uncertainties do not exist. While, in the latter case, the equilibrium profile is uniform, in the former case it is uniform up to a point and then it tapers off. We also solve the associated optimization problem to determine the socially optimal solution when the central planner is unaware of the actual amount of arrivals. Interestingly, the Price of Anarchy (ratio of the social cost of the equilibrium solution to that of the optimal one) for this model turns out to be two exactly, as in the deterministic case, despite the different form of the social and equilibrium arrival profiles.",tushar raheja,Facsimile,2012.0,10.4108/valuetools.2012.250166,6th International ICST Conference on Performance Evaluation Methodologies and Tools,Juneja2012,False,,IEEE,Not available,The concert queueing game with a random volume of arrivals,9626b38ca07343c760573194f79e112c,https://ieeexplore.ieee.org/document/6376339/
10521,"We consider the concert queueing game in the fluid framework, where the service facility opens at a specified time, the customers are particles in a fluid with homogeneous costs that are linear and additive in the waiting time and in the time to service completion, and wish to choose their own arrival times so as to minimize their cost. This problem has recently been analyzed under the assumption that the total volume of arriving customers is deterministic and known beforehand. We consider here the more plausible setting where this volume may be random, and only its probability distribution is known beforehand. In this setting, we identify the unique symmetric Nash equilibrium and show that under it the customer behavior significantly differs from the case where such uncertainties do not exist. While, in the latter case, the equilibrium profile is uniform, in the former case it is uniform up to a point and then it tapers off. We also solve the associated optimization problem to determine the socially optimal solution when the central planner is unaware of the actual amount of arrivals. Interestingly, the Price of Anarchy (ratio of the social cost of the equilibrium solution to that of the optimal one) for this model turns out to be two exactly, as in the deterministic case, despite the different form of the social and equilibrium arrival profiles.",nahum shimkin,Fluids,2012.0,10.4108/valuetools.2012.250166,6th International ICST Conference on Performance Evaluation Methodologies and Tools,Juneja2012,False,,IEEE,Not available,The concert queueing game with a random volume of arrivals,9626b38ca07343c760573194f79e112c,https://ieeexplore.ieee.org/document/6376339/
10522,"We consider the concert queueing game in the fluid framework, where the service facility opens at a specified time, the customers are particles in a fluid with homogeneous costs that are linear and additive in the waiting time and in the time to service completion, and wish to choose their own arrival times so as to minimize their cost. This problem has recently been analyzed under the assumption that the total volume of arriving customers is deterministic and known beforehand. We consider here the more plausible setting where this volume may be random, and only its probability distribution is known beforehand. In this setting, we identify the unique symmetric Nash equilibrium and show that under it the customer behavior significantly differs from the case where such uncertainties do not exist. While, in the latter case, the equilibrium profile is uniform, in the former case it is uniform up to a point and then it tapers off. We also solve the associated optimization problem to determine the socially optimal solution when the central planner is unaware of the actual amount of arrivals. Interestingly, the Price of Anarchy (ratio of the social cost of the equilibrium solution to that of the optimal one) for this model turns out to be two exactly, as in the deterministic case, despite the different form of the social and equilibrium arrival profiles.",nahum shimkin,Standards,2012.0,10.4108/valuetools.2012.250166,6th International ICST Conference on Performance Evaluation Methodologies and Tools,Juneja2012,False,,IEEE,Not available,The concert queueing game with a random volume of arrivals,9626b38ca07343c760573194f79e112c,https://ieeexplore.ieee.org/document/6376339/
10523,"We consider the concert queueing game in the fluid framework, where the service facility opens at a specified time, the customers are particles in a fluid with homogeneous costs that are linear and additive in the waiting time and in the time to service completion, and wish to choose their own arrival times so as to minimize their cost. This problem has recently been analyzed under the assumption that the total volume of arriving customers is deterministic and known beforehand. We consider here the more plausible setting where this volume may be random, and only its probability distribution is known beforehand. In this setting, we identify the unique symmetric Nash equilibrium and show that under it the customer behavior significantly differs from the case where such uncertainties do not exist. While, in the latter case, the equilibrium profile is uniform, in the former case it is uniform up to a point and then it tapers off. We also solve the associated optimization problem to determine the socially optimal solution when the central planner is unaware of the actual amount of arrivals. Interestingly, the Price of Anarchy (ratio of the social cost of the equilibrium solution to that of the optimal one) for this model turns out to be two exactly, as in the deterministic case, despite the different form of the social and equilibrium arrival profiles.",nahum shimkin,Facsimile,2012.0,10.4108/valuetools.2012.250166,6th International ICST Conference on Performance Evaluation Methodologies and Tools,Juneja2012,False,,IEEE,Not available,The concert queueing game with a random volume of arrivals,9626b38ca07343c760573194f79e112c,https://ieeexplore.ieee.org/document/6376339/
10524,"The Price of Anarchy (PoA) is a measure for the loss of optimality due to decentralized behavior. It has been studied in many settings but, surprisingly, not in the most fundamental queueing system involving customers' decisions, namely, the single server Markovian queue. We find that the loss of efficiency in such systems is bounded by 50% in most practical cases, in which the arrival rate of the customers is significantly lower than the service rate. We also find that the loss of efficiency has an interesting behavior in two aspects: first, it sharply increases as the arrival rate comes close to the service rate; second, it becomes unbounded exactly when the arrival rate is greater than the service rate, a surprising behavior because the system is always stable. Knowing these bounds is important for the queue controller, for example when considering an investment in added service capacity.",gail gilboa-freedman,Adaptive control,2014.0,10.1109/TAC.2013.2270872,IEEE Transactions on Automatic Control,Gilboa-Freedman2014,False,,IEEE,Not available,The Price of Anarchy in the Markovian Single Server Queue,f3be4782a4e01807d8aac7e3e76fedf7,https://ieeexplore.ieee.org/document/6545289/
10525,"The Price of Anarchy (PoA) is a measure for the loss of optimality due to decentralized behavior. It has been studied in many settings but, surprisingly, not in the most fundamental queueing system involving customers' decisions, namely, the single server Markovian queue. We find that the loss of efficiency in such systems is bounded by 50% in most practical cases, in which the arrival rate of the customers is significantly lower than the service rate. We also find that the loss of efficiency has an interesting behavior in two aspects: first, it sharply increases as the arrival rate comes close to the service rate; second, it becomes unbounded exactly when the arrival rate is greater than the service rate, a surprising behavior because the system is always stable. Knowing these bounds is important for the queue controller, for example when considering an investment in added service capacity.",gail gilboa-freedman,cost function,2014.0,10.1109/TAC.2013.2270872,IEEE Transactions on Automatic Control,Gilboa-Freedman2014,False,,IEEE,Not available,The Price of Anarchy in the Markovian Single Server Queue,f3be4782a4e01807d8aac7e3e76fedf7,https://ieeexplore.ieee.org/document/6545289/
10526,"The Price of Anarchy (PoA) is a measure for the loss of optimality due to decentralized behavior. It has been studied in many settings but, surprisingly, not in the most fundamental queueing system involving customers' decisions, namely, the single server Markovian queue. We find that the loss of efficiency in such systems is bounded by 50% in most practical cases, in which the arrival rate of the customers is significantly lower than the service rate. We also find that the loss of efficiency has an interesting behavior in two aspects: first, it sharply increases as the arrival rate comes close to the service rate; second, it becomes unbounded exactly when the arrival rate is greater than the service rate, a surprising behavior because the system is always stable. Knowing these bounds is important for the queue controller, for example when considering an investment in added service capacity.",gail gilboa-freedman,numerical simulation,2014.0,10.1109/TAC.2013.2270872,IEEE Transactions on Automatic Control,Gilboa-Freedman2014,False,,IEEE,Not available,The Price of Anarchy in the Markovian Single Server Queue,f3be4782a4e01807d8aac7e3e76fedf7,https://ieeexplore.ieee.org/document/6545289/
10527,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
10528,"The Price of Anarchy (PoA) is a measure for the loss of optimality due to decentralized behavior. It has been studied in many settings but, surprisingly, not in the most fundamental queueing system involving customers' decisions, namely, the single server Markovian queue. We find that the loss of efficiency in such systems is bounded by 50% in most practical cases, in which the arrival rate of the customers is significantly lower than the service rate. We also find that the loss of efficiency has an interesting behavior in two aspects: first, it sharply increases as the arrival rate comes close to the service rate; second, it becomes unbounded exactly when the arrival rate is greater than the service rate, a surprising behavior because the system is always stable. Knowing these bounds is important for the queue controller, for example when considering an investment in added service capacity.",refael hassin,Adaptive control,2014.0,10.1109/TAC.2013.2270872,IEEE Transactions on Automatic Control,Gilboa-Freedman2014,False,,IEEE,Not available,The Price of Anarchy in the Markovian Single Server Queue,f3be4782a4e01807d8aac7e3e76fedf7,https://ieeexplore.ieee.org/document/6545289/
10529,"The Price of Anarchy (PoA) is a measure for the loss of optimality due to decentralized behavior. It has been studied in many settings but, surprisingly, not in the most fundamental queueing system involving customers' decisions, namely, the single server Markovian queue. We find that the loss of efficiency in such systems is bounded by 50% in most practical cases, in which the arrival rate of the customers is significantly lower than the service rate. We also find that the loss of efficiency has an interesting behavior in two aspects: first, it sharply increases as the arrival rate comes close to the service rate; second, it becomes unbounded exactly when the arrival rate is greater than the service rate, a surprising behavior because the system is always stable. Knowing these bounds is important for the queue controller, for example when considering an investment in added service capacity.",refael hassin,cost function,2014.0,10.1109/TAC.2013.2270872,IEEE Transactions on Automatic Control,Gilboa-Freedman2014,False,,IEEE,Not available,The Price of Anarchy in the Markovian Single Server Queue,f3be4782a4e01807d8aac7e3e76fedf7,https://ieeexplore.ieee.org/document/6545289/
10530,"The Price of Anarchy (PoA) is a measure for the loss of optimality due to decentralized behavior. It has been studied in many settings but, surprisingly, not in the most fundamental queueing system involving customers' decisions, namely, the single server Markovian queue. We find that the loss of efficiency in such systems is bounded by 50% in most practical cases, in which the arrival rate of the customers is significantly lower than the service rate. We also find that the loss of efficiency has an interesting behavior in two aspects: first, it sharply increases as the arrival rate comes close to the service rate; second, it becomes unbounded exactly when the arrival rate is greater than the service rate, a surprising behavior because the system is always stable. Knowing these bounds is important for the queue controller, for example when considering an investment in added service capacity.",refael hassin,numerical simulation,2014.0,10.1109/TAC.2013.2270872,IEEE Transactions on Automatic Control,Gilboa-Freedman2014,False,,IEEE,Not available,The Price of Anarchy in the Markovian Single Server Queue,f3be4782a4e01807d8aac7e3e76fedf7,https://ieeexplore.ieee.org/document/6545289/
10531,"The Price of Anarchy (PoA) is a measure for the loss of optimality due to decentralized behavior. It has been studied in many settings but, surprisingly, not in the most fundamental queueing system involving customers' decisions, namely, the single server Markovian queue. We find that the loss of efficiency in such systems is bounded by 50% in most practical cases, in which the arrival rate of the customers is significantly lower than the service rate. We also find that the loss of efficiency has an interesting behavior in two aspects: first, it sharply increases as the arrival rate comes close to the service rate; second, it becomes unbounded exactly when the arrival rate is greater than the service rate, a surprising behavior because the system is always stable. Knowing these bounds is important for the queue controller, for example when considering an investment in added service capacity.",yoav kerner,Adaptive control,2014.0,10.1109/TAC.2013.2270872,IEEE Transactions on Automatic Control,Gilboa-Freedman2014,False,,IEEE,Not available,The Price of Anarchy in the Markovian Single Server Queue,f3be4782a4e01807d8aac7e3e76fedf7,https://ieeexplore.ieee.org/document/6545289/
10532,"The Price of Anarchy (PoA) is a measure for the loss of optimality due to decentralized behavior. It has been studied in many settings but, surprisingly, not in the most fundamental queueing system involving customers' decisions, namely, the single server Markovian queue. We find that the loss of efficiency in such systems is bounded by 50% in most practical cases, in which the arrival rate of the customers is significantly lower than the service rate. We also find that the loss of efficiency has an interesting behavior in two aspects: first, it sharply increases as the arrival rate comes close to the service rate; second, it becomes unbounded exactly when the arrival rate is greater than the service rate, a surprising behavior because the system is always stable. Knowing these bounds is important for the queue controller, for example when considering an investment in added service capacity.",yoav kerner,cost function,2014.0,10.1109/TAC.2013.2270872,IEEE Transactions on Automatic Control,Gilboa-Freedman2014,False,,IEEE,Not available,The Price of Anarchy in the Markovian Single Server Queue,f3be4782a4e01807d8aac7e3e76fedf7,https://ieeexplore.ieee.org/document/6545289/
10533,"The Price of Anarchy (PoA) is a measure for the loss of optimality due to decentralized behavior. It has been studied in many settings but, surprisingly, not in the most fundamental queueing system involving customers' decisions, namely, the single server Markovian queue. We find that the loss of efficiency in such systems is bounded by 50% in most practical cases, in which the arrival rate of the customers is significantly lower than the service rate. We also find that the loss of efficiency has an interesting behavior in two aspects: first, it sharply increases as the arrival rate comes close to the service rate; second, it becomes unbounded exactly when the arrival rate is greater than the service rate, a surprising behavior because the system is always stable. Knowing these bounds is important for the queue controller, for example when considering an investment in added service capacity.",yoav kerner,numerical simulation,2014.0,10.1109/TAC.2013.2270872,IEEE Transactions on Automatic Control,Gilboa-Freedman2014,False,,IEEE,Not available,The Price of Anarchy in the Markovian Single Server Queue,f3be4782a4e01807d8aac7e3e76fedf7,https://ieeexplore.ieee.org/document/6545289/
10534,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",h. nama,Peer to peer computing,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
10535,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",h. nama,Costs,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
10536,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",h. nama,IP networks,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
10537,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",h. nama,Energy efficiency,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
10538,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
10539,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",h. nama,IEEE news,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
10540,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",h. nama,Telecommunication traffic,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
10541,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",h. nama,Internet,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
10542,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",h. nama,Communications Society,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
10543,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",h. nama,Mobile handsets,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
10544,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",h. nama,Personal digital assistants,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
10545,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",n. mandayam,Peer to peer computing,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
10546,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",n. mandayam,Costs,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
10547,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",n. mandayam,IP networks,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
10548,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",n. mandayam,Energy efficiency,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
10549,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
10550,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
10551,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",n. mandayam,IEEE news,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
10552,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",n. mandayam,Telecommunication traffic,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
10553,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",n. mandayam,Internet,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
10554,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",n. mandayam,Communications Society,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
10555,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",n. mandayam,Mobile handsets,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
10556,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",n. mandayam,Personal digital assistants,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
10557,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",r. yates,Peer to peer computing,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
10558,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",r. yates,Costs,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
10559,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",r. yates,IP networks,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
10560,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",r. yates,Energy efficiency,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
10561,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
10562,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",r. yates,IEEE news,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
10563,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",r. yates,Telecommunication traffic,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
10564,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",r. yates,Internet,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
10565,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",r. yates,Communications Society,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
10566,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",r. yates,Mobile handsets,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
10567,"We study the formation of ad-hoc networks among selfish energy-constrained wireless devices that are primarily interested in being &lt;i&gt;connected&lt;/i&gt; with other devices. We use a non-cooperative bilateral connection game (BCG) framework to study network formation. For a BCG in which devices choose their individual strategies to remain connected by minimizing only their direct transmission power costs, we show that the price-of-anarchy is unbounded in the network size. We propose a BCG with an alternate cost structure in which each device additionally &lt;i&gt;pays&lt;/i&gt; the transmission power costs incurred by other devices for its own traffic. We show that a unique network structure emerges in this game that is stable as well as socially efficient. We then study the achievable throughput for random point-to-point traffic in this stable energy-efficient network. When the nodes of a network are located in a bounded planar region the distribution of point- to-point flows through the nodes exhibits a scale-free behavior.",r. yates,Personal digital assistants,2008.0,10.1109/INFOCOM.2008.126,IEEE INFOCOM 2008 - The 27th Conference on Computer Communications,Nama2008,False,,IEEE,Not available,Network Formation Among Selfish Energy-Constrained Wireless Devices,3b199fb154b27e422da638640b24c261,https://ieeexplore.ieee.org/document/4509721/
10568,"The network function virtualization (NFV) paradigm has gained increasing interest in both academia and industry as it promises scalable and flexible network management and orchestration. In NFV networks, network services are provided as chains of different virtual network functions (VNFs), which are instantiated and executed on dedicated VNF-compliant servers. The problem of composing those chains is referred to as the service chain composition problem. In contrast to centralized solutions that suffer from scalability and privacy issues, in this paper, we leverage non-cooperative game theory to achieve a low-complexity distributed solution to the above-mentioned problem. Specifically, to account for selfish and competitive behavior of users, we formulate the service chain composition problem as an atomic weighted congestion game with unsplittable flows and player-specific cost functions. We show that the game possesses a weighted potential function and admits a Nash equilibrium (NE). We prove that the price of anarchy is upper-bounded, and also propose a distributed and privacy-preserving algorithm which provably converges toward an NE of the game in polynomial time. Finally, through extensive numerical results, we assess the performance of the proposed distributed solution to the service chain composition problem.",salvatore d'oro,Game theory,2017.0,10.1109/JSAC.2017.2659298,IEEE Journal on Selected Areas in Communications,D’Oro2017,False,,IEEE,Not available,Exploiting Congestion Games to Achieve Distributed Service Chaining in NFV Networks,517eadd90b74ef58c8b28fda2647e689,https://ieeexplore.ieee.org/document/7835234/
10569,"The network function virtualization (NFV) paradigm has gained increasing interest in both academia and industry as it promises scalable and flexible network management and orchestration. In NFV networks, network services are provided as chains of different virtual network functions (VNFs), which are instantiated and executed on dedicated VNF-compliant servers. The problem of composing those chains is referred to as the service chain composition problem. In contrast to centralized solutions that suffer from scalability and privacy issues, in this paper, we leverage non-cooperative game theory to achieve a low-complexity distributed solution to the above-mentioned problem. Specifically, to account for selfish and competitive behavior of users, we formulate the service chain composition problem as an atomic weighted congestion game with unsplittable flows and player-specific cost functions. We show that the game possesses a weighted potential function and admits a Nash equilibrium (NE). We prove that the price of anarchy is upper-bounded, and also propose a distributed and privacy-preserving algorithm which provably converges toward an NE of the game in polynomial time. Finally, through extensive numerical results, we assess the performance of the proposed distributed solution to the service chain composition problem.",salvatore d'oro,congestion games,2017.0,10.1109/JSAC.2017.2659298,IEEE Journal on Selected Areas in Communications,D’Oro2017,False,,IEEE,Not available,Exploiting Congestion Games to Achieve Distributed Service Chaining in NFV Networks,517eadd90b74ef58c8b28fda2647e689,https://ieeexplore.ieee.org/document/7835234/
10570,"The network function virtualization (NFV) paradigm has gained increasing interest in both academia and industry as it promises scalable and flexible network management and orchestration. In NFV networks, network services are provided as chains of different virtual network functions (VNFs), which are instantiated and executed on dedicated VNF-compliant servers. The problem of composing those chains is referred to as the service chain composition problem. In contrast to centralized solutions that suffer from scalability and privacy issues, in this paper, we leverage non-cooperative game theory to achieve a low-complexity distributed solution to the above-mentioned problem. Specifically, to account for selfish and competitive behavior of users, we formulate the service chain composition problem as an atomic weighted congestion game with unsplittable flows and player-specific cost functions. We show that the game possesses a weighted potential function and admits a Nash equilibrium (NE). We prove that the price of anarchy is upper-bounded, and also propose a distributed and privacy-preserving algorithm which provably converges toward an NE of the game in polynomial time. Finally, through extensive numerical results, we assess the performance of the proposed distributed solution to the service chain composition problem.",salvatore d'oro,service chaining,2017.0,10.1109/JSAC.2017.2659298,IEEE Journal on Selected Areas in Communications,D’Oro2017,False,,IEEE,Not available,Exploiting Congestion Games to Achieve Distributed Service Chaining in NFV Networks,517eadd90b74ef58c8b28fda2647e689,https://ieeexplore.ieee.org/document/7835234/
10571,"The network function virtualization (NFV) paradigm has gained increasing interest in both academia and industry as it promises scalable and flexible network management and orchestration. In NFV networks, network services are provided as chains of different virtual network functions (VNFs), which are instantiated and executed on dedicated VNF-compliant servers. The problem of composing those chains is referred to as the service chain composition problem. In contrast to centralized solutions that suffer from scalability and privacy issues, in this paper, we leverage non-cooperative game theory to achieve a low-complexity distributed solution to the above-mentioned problem. Specifically, to account for selfish and competitive behavior of users, we formulate the service chain composition problem as an atomic weighted congestion game with unsplittable flows and player-specific cost functions. We show that the game possesses a weighted potential function and admits a Nash equilibrium (NE). We prove that the price of anarchy is upper-bounded, and also propose a distributed and privacy-preserving algorithm which provably converges toward an NE of the game in polynomial time. Finally, through extensive numerical results, we assess the performance of the proposed distributed solution to the service chain composition problem.",salvatore d'oro,network function virtualization (NFV),2017.0,10.1109/JSAC.2017.2659298,IEEE Journal on Selected Areas in Communications,D’Oro2017,False,,IEEE,Not available,Exploiting Congestion Games to Achieve Distributed Service Chaining in NFV Networks,517eadd90b74ef58c8b28fda2647e689,https://ieeexplore.ieee.org/document/7835234/
10572,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
10573,"The network function virtualization (NFV) paradigm has gained increasing interest in both academia and industry as it promises scalable and flexible network management and orchestration. In NFV networks, network services are provided as chains of different virtual network functions (VNFs), which are instantiated and executed on dedicated VNF-compliant servers. The problem of composing those chains is referred to as the service chain composition problem. In contrast to centralized solutions that suffer from scalability and privacy issues, in this paper, we leverage non-cooperative game theory to achieve a low-complexity distributed solution to the above-mentioned problem. Specifically, to account for selfish and competitive behavior of users, we formulate the service chain composition problem as an atomic weighted congestion game with unsplittable flows and player-specific cost functions. We show that the game possesses a weighted potential function and admits a Nash equilibrium (NE). We prove that the price of anarchy is upper-bounded, and also propose a distributed and privacy-preserving algorithm which provably converges toward an NE of the game in polynomial time. Finally, through extensive numerical results, we assess the performance of the proposed distributed solution to the service chain composition problem.",laura galluccio,Game theory,2017.0,10.1109/JSAC.2017.2659298,IEEE Journal on Selected Areas in Communications,D’Oro2017,False,,IEEE,Not available,Exploiting Congestion Games to Achieve Distributed Service Chaining in NFV Networks,517eadd90b74ef58c8b28fda2647e689,https://ieeexplore.ieee.org/document/7835234/
10574,"The network function virtualization (NFV) paradigm has gained increasing interest in both academia and industry as it promises scalable and flexible network management and orchestration. In NFV networks, network services are provided as chains of different virtual network functions (VNFs), which are instantiated and executed on dedicated VNF-compliant servers. The problem of composing those chains is referred to as the service chain composition problem. In contrast to centralized solutions that suffer from scalability and privacy issues, in this paper, we leverage non-cooperative game theory to achieve a low-complexity distributed solution to the above-mentioned problem. Specifically, to account for selfish and competitive behavior of users, we formulate the service chain composition problem as an atomic weighted congestion game with unsplittable flows and player-specific cost functions. We show that the game possesses a weighted potential function and admits a Nash equilibrium (NE). We prove that the price of anarchy is upper-bounded, and also propose a distributed and privacy-preserving algorithm which provably converges toward an NE of the game in polynomial time. Finally, through extensive numerical results, we assess the performance of the proposed distributed solution to the service chain composition problem.",laura galluccio,congestion games,2017.0,10.1109/JSAC.2017.2659298,IEEE Journal on Selected Areas in Communications,D’Oro2017,False,,IEEE,Not available,Exploiting Congestion Games to Achieve Distributed Service Chaining in NFV Networks,517eadd90b74ef58c8b28fda2647e689,https://ieeexplore.ieee.org/document/7835234/
10575,"The network function virtualization (NFV) paradigm has gained increasing interest in both academia and industry as it promises scalable and flexible network management and orchestration. In NFV networks, network services are provided as chains of different virtual network functions (VNFs), which are instantiated and executed on dedicated VNF-compliant servers. The problem of composing those chains is referred to as the service chain composition problem. In contrast to centralized solutions that suffer from scalability and privacy issues, in this paper, we leverage non-cooperative game theory to achieve a low-complexity distributed solution to the above-mentioned problem. Specifically, to account for selfish and competitive behavior of users, we formulate the service chain composition problem as an atomic weighted congestion game with unsplittable flows and player-specific cost functions. We show that the game possesses a weighted potential function and admits a Nash equilibrium (NE). We prove that the price of anarchy is upper-bounded, and also propose a distributed and privacy-preserving algorithm which provably converges toward an NE of the game in polynomial time. Finally, through extensive numerical results, we assess the performance of the proposed distributed solution to the service chain composition problem.",laura galluccio,service chaining,2017.0,10.1109/JSAC.2017.2659298,IEEE Journal on Selected Areas in Communications,D’Oro2017,False,,IEEE,Not available,Exploiting Congestion Games to Achieve Distributed Service Chaining in NFV Networks,517eadd90b74ef58c8b28fda2647e689,https://ieeexplore.ieee.org/document/7835234/
10576,"The network function virtualization (NFV) paradigm has gained increasing interest in both academia and industry as it promises scalable and flexible network management and orchestration. In NFV networks, network services are provided as chains of different virtual network functions (VNFs), which are instantiated and executed on dedicated VNF-compliant servers. The problem of composing those chains is referred to as the service chain composition problem. In contrast to centralized solutions that suffer from scalability and privacy issues, in this paper, we leverage non-cooperative game theory to achieve a low-complexity distributed solution to the above-mentioned problem. Specifically, to account for selfish and competitive behavior of users, we formulate the service chain composition problem as an atomic weighted congestion game with unsplittable flows and player-specific cost functions. We show that the game possesses a weighted potential function and admits a Nash equilibrium (NE). We prove that the price of anarchy is upper-bounded, and also propose a distributed and privacy-preserving algorithm which provably converges toward an NE of the game in polynomial time. Finally, through extensive numerical results, we assess the performance of the proposed distributed solution to the service chain composition problem.",laura galluccio,network function virtualization (NFV),2017.0,10.1109/JSAC.2017.2659298,IEEE Journal on Selected Areas in Communications,D’Oro2017,False,,IEEE,Not available,Exploiting Congestion Games to Achieve Distributed Service Chaining in NFV Networks,517eadd90b74ef58c8b28fda2647e689,https://ieeexplore.ieee.org/document/7835234/
10577,"The network function virtualization (NFV) paradigm has gained increasing interest in both academia and industry as it promises scalable and flexible network management and orchestration. In NFV networks, network services are provided as chains of different virtual network functions (VNFs), which are instantiated and executed on dedicated VNF-compliant servers. The problem of composing those chains is referred to as the service chain composition problem. In contrast to centralized solutions that suffer from scalability and privacy issues, in this paper, we leverage non-cooperative game theory to achieve a low-complexity distributed solution to the above-mentioned problem. Specifically, to account for selfish and competitive behavior of users, we formulate the service chain composition problem as an atomic weighted congestion game with unsplittable flows and player-specific cost functions. We show that the game possesses a weighted potential function and admits a Nash equilibrium (NE). We prove that the price of anarchy is upper-bounded, and also propose a distributed and privacy-preserving algorithm which provably converges toward an NE of the game in polynomial time. Finally, through extensive numerical results, we assess the performance of the proposed distributed solution to the service chain composition problem.",sergio palazzo,Game theory,2017.0,10.1109/JSAC.2017.2659298,IEEE Journal on Selected Areas in Communications,D’Oro2017,False,,IEEE,Not available,Exploiting Congestion Games to Achieve Distributed Service Chaining in NFV Networks,517eadd90b74ef58c8b28fda2647e689,https://ieeexplore.ieee.org/document/7835234/
10578,"The network function virtualization (NFV) paradigm has gained increasing interest in both academia and industry as it promises scalable and flexible network management and orchestration. In NFV networks, network services are provided as chains of different virtual network functions (VNFs), which are instantiated and executed on dedicated VNF-compliant servers. The problem of composing those chains is referred to as the service chain composition problem. In contrast to centralized solutions that suffer from scalability and privacy issues, in this paper, we leverage non-cooperative game theory to achieve a low-complexity distributed solution to the above-mentioned problem. Specifically, to account for selfish and competitive behavior of users, we formulate the service chain composition problem as an atomic weighted congestion game with unsplittable flows and player-specific cost functions. We show that the game possesses a weighted potential function and admits a Nash equilibrium (NE). We prove that the price of anarchy is upper-bounded, and also propose a distributed and privacy-preserving algorithm which provably converges toward an NE of the game in polynomial time. Finally, through extensive numerical results, we assess the performance of the proposed distributed solution to the service chain composition problem.",sergio palazzo,congestion games,2017.0,10.1109/JSAC.2017.2659298,IEEE Journal on Selected Areas in Communications,D’Oro2017,False,,IEEE,Not available,Exploiting Congestion Games to Achieve Distributed Service Chaining in NFV Networks,517eadd90b74ef58c8b28fda2647e689,https://ieeexplore.ieee.org/document/7835234/
10579,"The network function virtualization (NFV) paradigm has gained increasing interest in both academia and industry as it promises scalable and flexible network management and orchestration. In NFV networks, network services are provided as chains of different virtual network functions (VNFs), which are instantiated and executed on dedicated VNF-compliant servers. The problem of composing those chains is referred to as the service chain composition problem. In contrast to centralized solutions that suffer from scalability and privacy issues, in this paper, we leverage non-cooperative game theory to achieve a low-complexity distributed solution to the above-mentioned problem. Specifically, to account for selfish and competitive behavior of users, we formulate the service chain composition problem as an atomic weighted congestion game with unsplittable flows and player-specific cost functions. We show that the game possesses a weighted potential function and admits a Nash equilibrium (NE). We prove that the price of anarchy is upper-bounded, and also propose a distributed and privacy-preserving algorithm which provably converges toward an NE of the game in polynomial time. Finally, through extensive numerical results, we assess the performance of the proposed distributed solution to the service chain composition problem.",sergio palazzo,service chaining,2017.0,10.1109/JSAC.2017.2659298,IEEE Journal on Selected Areas in Communications,D’Oro2017,False,,IEEE,Not available,Exploiting Congestion Games to Achieve Distributed Service Chaining in NFV Networks,517eadd90b74ef58c8b28fda2647e689,https://ieeexplore.ieee.org/document/7835234/
10580,"The network function virtualization (NFV) paradigm has gained increasing interest in both academia and industry as it promises scalable and flexible network management and orchestration. In NFV networks, network services are provided as chains of different virtual network functions (VNFs), which are instantiated and executed on dedicated VNF-compliant servers. The problem of composing those chains is referred to as the service chain composition problem. In contrast to centralized solutions that suffer from scalability and privacy issues, in this paper, we leverage non-cooperative game theory to achieve a low-complexity distributed solution to the above-mentioned problem. Specifically, to account for selfish and competitive behavior of users, we formulate the service chain composition problem as an atomic weighted congestion game with unsplittable flows and player-specific cost functions. We show that the game possesses a weighted potential function and admits a Nash equilibrium (NE). We prove that the price of anarchy is upper-bounded, and also propose a distributed and privacy-preserving algorithm which provably converges toward an NE of the game in polynomial time. Finally, through extensive numerical results, we assess the performance of the proposed distributed solution to the service chain composition problem.",sergio palazzo,network function virtualization (NFV),2017.0,10.1109/JSAC.2017.2659298,IEEE Journal on Selected Areas in Communications,D’Oro2017,False,,IEEE,Not available,Exploiting Congestion Games to Achieve Distributed Service Chaining in NFV Networks,517eadd90b74ef58c8b28fda2647e689,https://ieeexplore.ieee.org/document/7835234/
10581,"The network function virtualization (NFV) paradigm has gained increasing interest in both academia and industry as it promises scalable and flexible network management and orchestration. In NFV networks, network services are provided as chains of different virtual network functions (VNFs), which are instantiated and executed on dedicated VNF-compliant servers. The problem of composing those chains is referred to as the service chain composition problem. In contrast to centralized solutions that suffer from scalability and privacy issues, in this paper, we leverage non-cooperative game theory to achieve a low-complexity distributed solution to the above-mentioned problem. Specifically, to account for selfish and competitive behavior of users, we formulate the service chain composition problem as an atomic weighted congestion game with unsplittable flows and player-specific cost functions. We show that the game possesses a weighted potential function and admits a Nash equilibrium (NE). We prove that the price of anarchy is upper-bounded, and also propose a distributed and privacy-preserving algorithm which provably converges toward an NE of the game in polynomial time. Finally, through extensive numerical results, we assess the performance of the proposed distributed solution to the service chain composition problem.",giovanni schembra,Game theory,2017.0,10.1109/JSAC.2017.2659298,IEEE Journal on Selected Areas in Communications,D’Oro2017,False,,IEEE,Not available,Exploiting Congestion Games to Achieve Distributed Service Chaining in NFV Networks,517eadd90b74ef58c8b28fda2647e689,https://ieeexplore.ieee.org/document/7835234/
10582,"The network function virtualization (NFV) paradigm has gained increasing interest in both academia and industry as it promises scalable and flexible network management and orchestration. In NFV networks, network services are provided as chains of different virtual network functions (VNFs), which are instantiated and executed on dedicated VNF-compliant servers. The problem of composing those chains is referred to as the service chain composition problem. In contrast to centralized solutions that suffer from scalability and privacy issues, in this paper, we leverage non-cooperative game theory to achieve a low-complexity distributed solution to the above-mentioned problem. Specifically, to account for selfish and competitive behavior of users, we formulate the service chain composition problem as an atomic weighted congestion game with unsplittable flows and player-specific cost functions. We show that the game possesses a weighted potential function and admits a Nash equilibrium (NE). We prove that the price of anarchy is upper-bounded, and also propose a distributed and privacy-preserving algorithm which provably converges toward an NE of the game in polynomial time. Finally, through extensive numerical results, we assess the performance of the proposed distributed solution to the service chain composition problem.",giovanni schembra,congestion games,2017.0,10.1109/JSAC.2017.2659298,IEEE Journal on Selected Areas in Communications,D’Oro2017,False,,IEEE,Not available,Exploiting Congestion Games to Achieve Distributed Service Chaining in NFV Networks,517eadd90b74ef58c8b28fda2647e689,https://ieeexplore.ieee.org/document/7835234/
10583,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
10584,"The network function virtualization (NFV) paradigm has gained increasing interest in both academia and industry as it promises scalable and flexible network management and orchestration. In NFV networks, network services are provided as chains of different virtual network functions (VNFs), which are instantiated and executed on dedicated VNF-compliant servers. The problem of composing those chains is referred to as the service chain composition problem. In contrast to centralized solutions that suffer from scalability and privacy issues, in this paper, we leverage non-cooperative game theory to achieve a low-complexity distributed solution to the above-mentioned problem. Specifically, to account for selfish and competitive behavior of users, we formulate the service chain composition problem as an atomic weighted congestion game with unsplittable flows and player-specific cost functions. We show that the game possesses a weighted potential function and admits a Nash equilibrium (NE). We prove that the price of anarchy is upper-bounded, and also propose a distributed and privacy-preserving algorithm which provably converges toward an NE of the game in polynomial time. Finally, through extensive numerical results, we assess the performance of the proposed distributed solution to the service chain composition problem.",giovanni schembra,service chaining,2017.0,10.1109/JSAC.2017.2659298,IEEE Journal on Selected Areas in Communications,D’Oro2017,False,,IEEE,Not available,Exploiting Congestion Games to Achieve Distributed Service Chaining in NFV Networks,517eadd90b74ef58c8b28fda2647e689,https://ieeexplore.ieee.org/document/7835234/
10585,"The network function virtualization (NFV) paradigm has gained increasing interest in both academia and industry as it promises scalable and flexible network management and orchestration. In NFV networks, network services are provided as chains of different virtual network functions (VNFs), which are instantiated and executed on dedicated VNF-compliant servers. The problem of composing those chains is referred to as the service chain composition problem. In contrast to centralized solutions that suffer from scalability and privacy issues, in this paper, we leverage non-cooperative game theory to achieve a low-complexity distributed solution to the above-mentioned problem. Specifically, to account for selfish and competitive behavior of users, we formulate the service chain composition problem as an atomic weighted congestion game with unsplittable flows and player-specific cost functions. We show that the game possesses a weighted potential function and admits a Nash equilibrium (NE). We prove that the price of anarchy is upper-bounded, and also propose a distributed and privacy-preserving algorithm which provably converges toward an NE of the game in polynomial time. Finally, through extensive numerical results, we assess the performance of the proposed distributed solution to the service chain composition problem.",giovanni schembra,network function virtualization (NFV),2017.0,10.1109/JSAC.2017.2659298,IEEE Journal on Selected Areas in Communications,D’Oro2017,False,,IEEE,Not available,Exploiting Congestion Games to Achieve Distributed Service Chaining in NFV Networks,517eadd90b74ef58c8b28fda2647e689,https://ieeexplore.ieee.org/document/7835234/
10586,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",thomas carroll,Processor scheduling,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
10587,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",thomas carroll,Surface-mount technology,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
10588,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",thomas carroll,Game theory,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
10589,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",thomas carroll,Costs,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
10590,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",thomas carroll,Scheduling algorithm,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
10591,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",thomas carroll,Routing,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
10592,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",thomas carroll,Single machine scheduling,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
10593,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",thomas carroll,Computer science,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
10594,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
10595,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",thomas carroll,Decision making,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
10596,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",thomas carroll,Steady-state,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
10597,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",daniel grosu,Processor scheduling,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
10598,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",daniel grosu,Surface-mount technology,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
10599,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",daniel grosu,Game theory,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
10600,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",daniel grosu,Costs,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
10601,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",daniel grosu,Scheduling algorithm,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
10602,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",daniel grosu,Routing,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
10603,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",daniel grosu,Single machine scheduling,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
10604,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",daniel grosu,Computer science,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
10605,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
10606,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",daniel grosu,Decision making,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
10607,"In this paper we formulate and study a new scheduling problem called selfish multi-user task scheduling. This problem assumes that there are several users, each of them having multiple tasks that need processing on a set of parallel identical machines. Each user is selfish and her goal is to minimize the makespan of her own tasks. We model this problem as a non-cooperative, extensive-form game. We use the subgame perfect equilibrium solution concept to analyze the game which provides insight into the problem's properties. We compute the price of anarchy to quantify the costs due to lack of coordination among the users",daniel grosu,Steady-state,2006.0,10.1109/ISPDC.2006.44,2006 Fifth International Symposium on Parallel and Distributed Computing,Carroll2006,False,,IEEE,Not available,Selfish Multi-User Task Scheduling,8581aa693ef9cc5a50350374dbec7809,https://ieeexplore.ieee.org/document/4021915/
10608,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",ninoslav marina,Relays,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
10609,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",ninoslav marina,Peer to peer computing,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
10610,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",ninoslav marina,Games,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
10611,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",ninoslav marina,Resource management,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
10612,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",ninoslav marina,Ad hoc networks,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
10613,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",ninoslav marina,Upper bound,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
10614,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",ninoslav marina,Nash equilibrium,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
10615,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",gurdal arslan,Relays,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
10616,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
10617,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",gurdal arslan,Peer to peer computing,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
10618,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",gurdal arslan,Games,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
10619,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",gurdal arslan,Resource management,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
10620,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",gurdal arslan,Ad hoc networks,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
10621,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",gurdal arslan,Upper bound,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
10622,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",gurdal arslan,Nash equilibrium,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
10623,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",aleksandar kavcic,Relays,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
10624,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",aleksandar kavcic,Peer to peer computing,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
10625,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",aleksandar kavcic,Games,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
10626,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",aleksandar kavcic,Resource management,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
10627,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
10628,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",aleksandar kavcic,Ad hoc networks,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
10629,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",aleksandar kavcic,Upper bound,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
10630,"We introduce a power allocation game in a four node relay network which consists of two source and two destination nodes. The sources employ a time sharing protocol such that in each discrete time instance one of the sources communicates with its destination while the other source aids this communication by acting as a relay. Each source uses some portion of its limited power for its own transmission and uses the remaining portion to aid the other source. The noncooperative solution, which is the Nash equilibrium of the game where each source tries to maximize its own rate, dictates each source to use all of its power for its own use, i.e., no relaying. This results in an inferior sum rate with respect to the optimum sum rate jointly maximized over all possible power allocations. The main contribution of this paper is to establish an upper bound on the worst-case equilibrium efficiency (a.k.a. the price of anarchy), defined as the ratio of the equilibrium sum rate to the optimal sum rate for the worst channel conditions. More specifically, we show that if the path loss coefficient is beta &amp;gt; 0 and the received signals are corrupted by additive white Gaussian noise, then the worst case equilibrium efficiency is upper bounded by (1/2)&lt;sup&gt;beta&lt;/sup&gt;. We also note that this upper bound can be extended to relay networks with more than two sources.",aleksandar kavcic,Nash equilibrium,2008.0,10.1109/ICTEL.2008.4652675,2008 International Conference on Telecommunications,Marina2008,False,,IEEE,Not available,A power allocation game in a four node relay network: An upper bound on the worst-case equilibrium efficiency,08965fda553965e992b866a0a6c0a8cb,https://ieeexplore.ieee.org/document/4652675/
10631,"In the decentralized networks, an important requirement arises in the design of Medium Access Control protocols is the robustness to self-interested behavior of the users. Indeed it's well known that the Medium Access Control protocols are designed based on the assumption that all mobile users act selfishly and follow a personal objective, such behavior may decrease the performance of the majority of users, hence causing fairness issue and decreasing the global energy consumption significantly. In this paper we propose a reward mechanism in a non-cooperative game framework. We assume that the base station promises the user a reward which can be a number of amounts of credit that the users use to transmit their own packets. The reward is given only to a user that transmits its packet successfully. First, we analyze the implementation of our mechanism on the equilibrium and show that as the arrival rate increases, the behavior of users become more and more aggressive resulting in a global deterioration of the expected reward the base station pays. Second and in order to achieve an efficient outcome despite the selfish behavior of users, we propose an incentive mechanism when each failure transmission of a packet incurs a certain number of costs. The cost could in fact be expressed in terms of the energy consumption when attempting to access the wireless channel. Under the proposed scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via the price of anarchy we show that the global performance of the system is improved considerably compared to the original game in particular at high loads.",moulay lmater,Wireless Networks,2015.0,10.1109/WINCOM.2015.7381303,2015 International Conference on Wireless Networks and Mobile Communications (WINCOM),Lmater2015,False,,IEEE,Not available,An efficient pricing mechanism of random access in wireless network with self-interested mobile users,0abf002fd892b61c3b904d03fc474daa,https://ieeexplore.ieee.org/document/7381303/
10632,"In the decentralized networks, an important requirement arises in the design of Medium Access Control protocols is the robustness to self-interested behavior of the users. Indeed it's well known that the Medium Access Control protocols are designed based on the assumption that all mobile users act selfishly and follow a personal objective, such behavior may decrease the performance of the majority of users, hence causing fairness issue and decreasing the global energy consumption significantly. In this paper we propose a reward mechanism in a non-cooperative game framework. We assume that the base station promises the user a reward which can be a number of amounts of credit that the users use to transmit their own packets. The reward is given only to a user that transmits its packet successfully. First, we analyze the implementation of our mechanism on the equilibrium and show that as the arrival rate increases, the behavior of users become more and more aggressive resulting in a global deterioration of the expected reward the base station pays. Second and in order to achieve an efficient outcome despite the selfish behavior of users, we propose an incentive mechanism when each failure transmission of a packet incurs a certain number of costs. The cost could in fact be expressed in terms of the energy consumption when attempting to access the wireless channel. Under the proposed scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via the price of anarchy we show that the global performance of the system is improved considerably compared to the original game in particular at high loads.",moulay lmater,Wireless Random Access Protocol,2015.0,10.1109/WINCOM.2015.7381303,2015 International Conference on Wireless Networks and Mobile Communications (WINCOM),Lmater2015,False,,IEEE,Not available,An efficient pricing mechanism of random access in wireless network with self-interested mobile users,0abf002fd892b61c3b904d03fc474daa,https://ieeexplore.ieee.org/document/7381303/
10633,"In the decentralized networks, an important requirement arises in the design of Medium Access Control protocols is the robustness to self-interested behavior of the users. Indeed it's well known that the Medium Access Control protocols are designed based on the assumption that all mobile users act selfishly and follow a personal objective, such behavior may decrease the performance of the majority of users, hence causing fairness issue and decreasing the global energy consumption significantly. In this paper we propose a reward mechanism in a non-cooperative game framework. We assume that the base station promises the user a reward which can be a number of amounts of credit that the users use to transmit their own packets. The reward is given only to a user that transmits its packet successfully. First, we analyze the implementation of our mechanism on the equilibrium and show that as the arrival rate increases, the behavior of users become more and more aggressive resulting in a global deterioration of the expected reward the base station pays. Second and in order to achieve an efficient outcome despite the selfish behavior of users, we propose an incentive mechanism when each failure transmission of a packet incurs a certain number of costs. The cost could in fact be expressed in terms of the energy consumption when attempting to access the wireless channel. Under the proposed scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via the price of anarchy we show that the global performance of the system is improved considerably compared to the original game in particular at high loads.",moulay lmater,MAC Layer,2015.0,10.1109/WINCOM.2015.7381303,2015 International Conference on Wireless Networks and Mobile Communications (WINCOM),Lmater2015,False,,IEEE,Not available,An efficient pricing mechanism of random access in wireless network with self-interested mobile users,0abf002fd892b61c3b904d03fc474daa,https://ieeexplore.ieee.org/document/7381303/
10634,"In the decentralized networks, an important requirement arises in the design of Medium Access Control protocols is the robustness to self-interested behavior of the users. Indeed it's well known that the Medium Access Control protocols are designed based on the assumption that all mobile users act selfishly and follow a personal objective, such behavior may decrease the performance of the majority of users, hence causing fairness issue and decreasing the global energy consumption significantly. In this paper we propose a reward mechanism in a non-cooperative game framework. We assume that the base station promises the user a reward which can be a number of amounts of credit that the users use to transmit their own packets. The reward is given only to a user that transmits its packet successfully. First, we analyze the implementation of our mechanism on the equilibrium and show that as the arrival rate increases, the behavior of users become more and more aggressive resulting in a global deterioration of the expected reward the base station pays. Second and in order to achieve an efficient outcome despite the selfish behavior of users, we propose an incentive mechanism when each failure transmission of a packet incurs a certain number of costs. The cost could in fact be expressed in terms of the energy consumption when attempting to access the wireless channel. Under the proposed scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via the price of anarchy we show that the global performance of the system is improved considerably compared to the original game in particular at high loads.",moulay lmater,Markov Chains,2015.0,10.1109/WINCOM.2015.7381303,2015 International Conference on Wireless Networks and Mobile Communications (WINCOM),Lmater2015,False,,IEEE,Not available,An efficient pricing mechanism of random access in wireless network with self-interested mobile users,0abf002fd892b61c3b904d03fc474daa,https://ieeexplore.ieee.org/document/7381303/
10635,"In the decentralized networks, an important requirement arises in the design of Medium Access Control protocols is the robustness to self-interested behavior of the users. Indeed it's well known that the Medium Access Control protocols are designed based on the assumption that all mobile users act selfishly and follow a personal objective, such behavior may decrease the performance of the majority of users, hence causing fairness issue and decreasing the global energy consumption significantly. In this paper we propose a reward mechanism in a non-cooperative game framework. We assume that the base station promises the user a reward which can be a number of amounts of credit that the users use to transmit their own packets. The reward is given only to a user that transmits its packet successfully. First, we analyze the implementation of our mechanism on the equilibrium and show that as the arrival rate increases, the behavior of users become more and more aggressive resulting in a global deterioration of the expected reward the base station pays. Second and in order to achieve an efficient outcome despite the selfish behavior of users, we propose an incentive mechanism when each failure transmission of a packet incurs a certain number of costs. The cost could in fact be expressed in terms of the energy consumption when attempting to access the wireless channel. Under the proposed scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via the price of anarchy we show that the global performance of the system is improved considerably compared to the original game in particular at high loads.",moulay lmater,Game Theory,2015.0,10.1109/WINCOM.2015.7381303,2015 International Conference on Wireless Networks and Mobile Communications (WINCOM),Lmater2015,False,,IEEE,Not available,An efficient pricing mechanism of random access in wireless network with self-interested mobile users,0abf002fd892b61c3b904d03fc474daa,https://ieeexplore.ieee.org/document/7381303/
10636,"In the decentralized networks, an important requirement arises in the design of Medium Access Control protocols is the robustness to self-interested behavior of the users. Indeed it's well known that the Medium Access Control protocols are designed based on the assumption that all mobile users act selfishly and follow a personal objective, such behavior may decrease the performance of the majority of users, hence causing fairness issue and decreasing the global energy consumption significantly. In this paper we propose a reward mechanism in a non-cooperative game framework. We assume that the base station promises the user a reward which can be a number of amounts of credit that the users use to transmit their own packets. The reward is given only to a user that transmits its packet successfully. First, we analyze the implementation of our mechanism on the equilibrium and show that as the arrival rate increases, the behavior of users become more and more aggressive resulting in a global deterioration of the expected reward the base station pays. Second and in order to achieve an efficient outcome despite the selfish behavior of users, we propose an incentive mechanism when each failure transmission of a packet incurs a certain number of costs. The cost could in fact be expressed in terms of the energy consumption when attempting to access the wireless channel. Under the proposed scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via the price of anarchy we show that the global performance of the system is improved considerably compared to the original game in particular at high loads.",moulay lmater,Nash Equilibrium,2015.0,10.1109/WINCOM.2015.7381303,2015 International Conference on Wireless Networks and Mobile Communications (WINCOM),Lmater2015,False,,IEEE,Not available,An efficient pricing mechanism of random access in wireless network with self-interested mobile users,0abf002fd892b61c3b904d03fc474daa,https://ieeexplore.ieee.org/document/7381303/
10637,"In the decentralized networks, an important requirement arises in the design of Medium Access Control protocols is the robustness to self-interested behavior of the users. Indeed it's well known that the Medium Access Control protocols are designed based on the assumption that all mobile users act selfishly and follow a personal objective, such behavior may decrease the performance of the majority of users, hence causing fairness issue and decreasing the global energy consumption significantly. In this paper we propose a reward mechanism in a non-cooperative game framework. We assume that the base station promises the user a reward which can be a number of amounts of credit that the users use to transmit their own packets. The reward is given only to a user that transmits its packet successfully. First, we analyze the implementation of our mechanism on the equilibrium and show that as the arrival rate increases, the behavior of users become more and more aggressive resulting in a global deterioration of the expected reward the base station pays. Second and in order to achieve an efficient outcome despite the selfish behavior of users, we propose an incentive mechanism when each failure transmission of a packet incurs a certain number of costs. The cost could in fact be expressed in terms of the energy consumption when attempting to access the wireless channel. Under the proposed scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via the price of anarchy we show that the global performance of the system is improved considerably compared to the original game in particular at high loads.",abdelillah karouit,Wireless Networks,2015.0,10.1109/WINCOM.2015.7381303,2015 International Conference on Wireless Networks and Mobile Communications (WINCOM),Lmater2015,False,,IEEE,Not available,An efficient pricing mechanism of random access in wireless network with self-interested mobile users,0abf002fd892b61c3b904d03fc474daa,https://ieeexplore.ieee.org/document/7381303/
10638,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
10639,"In the decentralized networks, an important requirement arises in the design of Medium Access Control protocols is the robustness to self-interested behavior of the users. Indeed it's well known that the Medium Access Control protocols are designed based on the assumption that all mobile users act selfishly and follow a personal objective, such behavior may decrease the performance of the majority of users, hence causing fairness issue and decreasing the global energy consumption significantly. In this paper we propose a reward mechanism in a non-cooperative game framework. We assume that the base station promises the user a reward which can be a number of amounts of credit that the users use to transmit their own packets. The reward is given only to a user that transmits its packet successfully. First, we analyze the implementation of our mechanism on the equilibrium and show that as the arrival rate increases, the behavior of users become more and more aggressive resulting in a global deterioration of the expected reward the base station pays. Second and in order to achieve an efficient outcome despite the selfish behavior of users, we propose an incentive mechanism when each failure transmission of a packet incurs a certain number of costs. The cost could in fact be expressed in terms of the energy consumption when attempting to access the wireless channel. Under the proposed scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via the price of anarchy we show that the global performance of the system is improved considerably compared to the original game in particular at high loads.",abdelillah karouit,Wireless Random Access Protocol,2015.0,10.1109/WINCOM.2015.7381303,2015 International Conference on Wireless Networks and Mobile Communications (WINCOM),Lmater2015,False,,IEEE,Not available,An efficient pricing mechanism of random access in wireless network with self-interested mobile users,0abf002fd892b61c3b904d03fc474daa,https://ieeexplore.ieee.org/document/7381303/
10640,"In the decentralized networks, an important requirement arises in the design of Medium Access Control protocols is the robustness to self-interested behavior of the users. Indeed it's well known that the Medium Access Control protocols are designed based on the assumption that all mobile users act selfishly and follow a personal objective, such behavior may decrease the performance of the majority of users, hence causing fairness issue and decreasing the global energy consumption significantly. In this paper we propose a reward mechanism in a non-cooperative game framework. We assume that the base station promises the user a reward which can be a number of amounts of credit that the users use to transmit their own packets. The reward is given only to a user that transmits its packet successfully. First, we analyze the implementation of our mechanism on the equilibrium and show that as the arrival rate increases, the behavior of users become more and more aggressive resulting in a global deterioration of the expected reward the base station pays. Second and in order to achieve an efficient outcome despite the selfish behavior of users, we propose an incentive mechanism when each failure transmission of a packet incurs a certain number of costs. The cost could in fact be expressed in terms of the energy consumption when attempting to access the wireless channel. Under the proposed scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via the price of anarchy we show that the global performance of the system is improved considerably compared to the original game in particular at high loads.",abdelillah karouit,MAC Layer,2015.0,10.1109/WINCOM.2015.7381303,2015 International Conference on Wireless Networks and Mobile Communications (WINCOM),Lmater2015,False,,IEEE,Not available,An efficient pricing mechanism of random access in wireless network with self-interested mobile users,0abf002fd892b61c3b904d03fc474daa,https://ieeexplore.ieee.org/document/7381303/
10641,"In the decentralized networks, an important requirement arises in the design of Medium Access Control protocols is the robustness to self-interested behavior of the users. Indeed it's well known that the Medium Access Control protocols are designed based on the assumption that all mobile users act selfishly and follow a personal objective, such behavior may decrease the performance of the majority of users, hence causing fairness issue and decreasing the global energy consumption significantly. In this paper we propose a reward mechanism in a non-cooperative game framework. We assume that the base station promises the user a reward which can be a number of amounts of credit that the users use to transmit their own packets. The reward is given only to a user that transmits its packet successfully. First, we analyze the implementation of our mechanism on the equilibrium and show that as the arrival rate increases, the behavior of users become more and more aggressive resulting in a global deterioration of the expected reward the base station pays. Second and in order to achieve an efficient outcome despite the selfish behavior of users, we propose an incentive mechanism when each failure transmission of a packet incurs a certain number of costs. The cost could in fact be expressed in terms of the energy consumption when attempting to access the wireless channel. Under the proposed scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via the price of anarchy we show that the global performance of the system is improved considerably compared to the original game in particular at high loads.",abdelillah karouit,Markov Chains,2015.0,10.1109/WINCOM.2015.7381303,2015 International Conference on Wireless Networks and Mobile Communications (WINCOM),Lmater2015,False,,IEEE,Not available,An efficient pricing mechanism of random access in wireless network with self-interested mobile users,0abf002fd892b61c3b904d03fc474daa,https://ieeexplore.ieee.org/document/7381303/
10642,"In the decentralized networks, an important requirement arises in the design of Medium Access Control protocols is the robustness to self-interested behavior of the users. Indeed it's well known that the Medium Access Control protocols are designed based on the assumption that all mobile users act selfishly and follow a personal objective, such behavior may decrease the performance of the majority of users, hence causing fairness issue and decreasing the global energy consumption significantly. In this paper we propose a reward mechanism in a non-cooperative game framework. We assume that the base station promises the user a reward which can be a number of amounts of credit that the users use to transmit their own packets. The reward is given only to a user that transmits its packet successfully. First, we analyze the implementation of our mechanism on the equilibrium and show that as the arrival rate increases, the behavior of users become more and more aggressive resulting in a global deterioration of the expected reward the base station pays. Second and in order to achieve an efficient outcome despite the selfish behavior of users, we propose an incentive mechanism when each failure transmission of a packet incurs a certain number of costs. The cost could in fact be expressed in terms of the energy consumption when attempting to access the wireless channel. Under the proposed scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via the price of anarchy we show that the global performance of the system is improved considerably compared to the original game in particular at high loads.",abdelillah karouit,Game Theory,2015.0,10.1109/WINCOM.2015.7381303,2015 International Conference on Wireless Networks and Mobile Communications (WINCOM),Lmater2015,False,,IEEE,Not available,An efficient pricing mechanism of random access in wireless network with self-interested mobile users,0abf002fd892b61c3b904d03fc474daa,https://ieeexplore.ieee.org/document/7381303/
10643,"In the decentralized networks, an important requirement arises in the design of Medium Access Control protocols is the robustness to self-interested behavior of the users. Indeed it's well known that the Medium Access Control protocols are designed based on the assumption that all mobile users act selfishly and follow a personal objective, such behavior may decrease the performance of the majority of users, hence causing fairness issue and decreasing the global energy consumption significantly. In this paper we propose a reward mechanism in a non-cooperative game framework. We assume that the base station promises the user a reward which can be a number of amounts of credit that the users use to transmit their own packets. The reward is given only to a user that transmits its packet successfully. First, we analyze the implementation of our mechanism on the equilibrium and show that as the arrival rate increases, the behavior of users become more and more aggressive resulting in a global deterioration of the expected reward the base station pays. Second and in order to achieve an efficient outcome despite the selfish behavior of users, we propose an incentive mechanism when each failure transmission of a packet incurs a certain number of costs. The cost could in fact be expressed in terms of the energy consumption when attempting to access the wireless channel. Under the proposed scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via the price of anarchy we show that the global performance of the system is improved considerably compared to the original game in particular at high loads.",abdelillah karouit,Nash Equilibrium,2015.0,10.1109/WINCOM.2015.7381303,2015 International Conference on Wireless Networks and Mobile Communications (WINCOM),Lmater2015,False,,IEEE,Not available,An efficient pricing mechanism of random access in wireless network with self-interested mobile users,0abf002fd892b61c3b904d03fc474daa,https://ieeexplore.ieee.org/document/7381303/
10644,"In the decentralized networks, an important requirement arises in the design of Medium Access Control protocols is the robustness to self-interested behavior of the users. Indeed it's well known that the Medium Access Control protocols are designed based on the assumption that all mobile users act selfishly and follow a personal objective, such behavior may decrease the performance of the majority of users, hence causing fairness issue and decreasing the global energy consumption significantly. In this paper we propose a reward mechanism in a non-cooperative game framework. We assume that the base station promises the user a reward which can be a number of amounts of credit that the users use to transmit their own packets. The reward is given only to a user that transmits its packet successfully. First, we analyze the implementation of our mechanism on the equilibrium and show that as the arrival rate increases, the behavior of users become more and more aggressive resulting in a global deterioration of the expected reward the base station pays. Second and in order to achieve an efficient outcome despite the selfish behavior of users, we propose an incentive mechanism when each failure transmission of a packet incurs a certain number of costs. The cost could in fact be expressed in terms of the energy consumption when attempting to access the wireless channel. Under the proposed scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via the price of anarchy we show that the global performance of the system is improved considerably compared to the original game in particular at high loads.",abdelkrim haqiq,Wireless Networks,2015.0,10.1109/WINCOM.2015.7381303,2015 International Conference on Wireless Networks and Mobile Communications (WINCOM),Lmater2015,False,,IEEE,Not available,An efficient pricing mechanism of random access in wireless network with self-interested mobile users,0abf002fd892b61c3b904d03fc474daa,https://ieeexplore.ieee.org/document/7381303/
10645,"In the decentralized networks, an important requirement arises in the design of Medium Access Control protocols is the robustness to self-interested behavior of the users. Indeed it's well known that the Medium Access Control protocols are designed based on the assumption that all mobile users act selfishly and follow a personal objective, such behavior may decrease the performance of the majority of users, hence causing fairness issue and decreasing the global energy consumption significantly. In this paper we propose a reward mechanism in a non-cooperative game framework. We assume that the base station promises the user a reward which can be a number of amounts of credit that the users use to transmit their own packets. The reward is given only to a user that transmits its packet successfully. First, we analyze the implementation of our mechanism on the equilibrium and show that as the arrival rate increases, the behavior of users become more and more aggressive resulting in a global deterioration of the expected reward the base station pays. Second and in order to achieve an efficient outcome despite the selfish behavior of users, we propose an incentive mechanism when each failure transmission of a packet incurs a certain number of costs. The cost could in fact be expressed in terms of the energy consumption when attempting to access the wireless channel. Under the proposed scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via the price of anarchy we show that the global performance of the system is improved considerably compared to the original game in particular at high loads.",abdelkrim haqiq,Wireless Random Access Protocol,2015.0,10.1109/WINCOM.2015.7381303,2015 International Conference on Wireless Networks and Mobile Communications (WINCOM),Lmater2015,False,,IEEE,Not available,An efficient pricing mechanism of random access in wireless network with self-interested mobile users,0abf002fd892b61c3b904d03fc474daa,https://ieeexplore.ieee.org/document/7381303/
10646,"In the decentralized networks, an important requirement arises in the design of Medium Access Control protocols is the robustness to self-interested behavior of the users. Indeed it's well known that the Medium Access Control protocols are designed based on the assumption that all mobile users act selfishly and follow a personal objective, such behavior may decrease the performance of the majority of users, hence causing fairness issue and decreasing the global energy consumption significantly. In this paper we propose a reward mechanism in a non-cooperative game framework. We assume that the base station promises the user a reward which can be a number of amounts of credit that the users use to transmit their own packets. The reward is given only to a user that transmits its packet successfully. First, we analyze the implementation of our mechanism on the equilibrium and show that as the arrival rate increases, the behavior of users become more and more aggressive resulting in a global deterioration of the expected reward the base station pays. Second and in order to achieve an efficient outcome despite the selfish behavior of users, we propose an incentive mechanism when each failure transmission of a packet incurs a certain number of costs. The cost could in fact be expressed in terms of the energy consumption when attempting to access the wireless channel. Under the proposed scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via the price of anarchy we show that the global performance of the system is improved considerably compared to the original game in particular at high loads.",abdelkrim haqiq,MAC Layer,2015.0,10.1109/WINCOM.2015.7381303,2015 International Conference on Wireless Networks and Mobile Communications (WINCOM),Lmater2015,False,,IEEE,Not available,An efficient pricing mechanism of random access in wireless network with self-interested mobile users,0abf002fd892b61c3b904d03fc474daa,https://ieeexplore.ieee.org/document/7381303/
10647,"In the decentralized networks, an important requirement arises in the design of Medium Access Control protocols is the robustness to self-interested behavior of the users. Indeed it's well known that the Medium Access Control protocols are designed based on the assumption that all mobile users act selfishly and follow a personal objective, such behavior may decrease the performance of the majority of users, hence causing fairness issue and decreasing the global energy consumption significantly. In this paper we propose a reward mechanism in a non-cooperative game framework. We assume that the base station promises the user a reward which can be a number of amounts of credit that the users use to transmit their own packets. The reward is given only to a user that transmits its packet successfully. First, we analyze the implementation of our mechanism on the equilibrium and show that as the arrival rate increases, the behavior of users become more and more aggressive resulting in a global deterioration of the expected reward the base station pays. Second and in order to achieve an efficient outcome despite the selfish behavior of users, we propose an incentive mechanism when each failure transmission of a packet incurs a certain number of costs. The cost could in fact be expressed in terms of the energy consumption when attempting to access the wireless channel. Under the proposed scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via the price of anarchy we show that the global performance of the system is improved considerably compared to the original game in particular at high loads.",abdelkrim haqiq,Markov Chains,2015.0,10.1109/WINCOM.2015.7381303,2015 International Conference on Wireless Networks and Mobile Communications (WINCOM),Lmater2015,False,,IEEE,Not available,An efficient pricing mechanism of random access in wireless network with self-interested mobile users,0abf002fd892b61c3b904d03fc474daa,https://ieeexplore.ieee.org/document/7381303/
10648,"In the decentralized networks, an important requirement arises in the design of Medium Access Control protocols is the robustness to self-interested behavior of the users. Indeed it's well known that the Medium Access Control protocols are designed based on the assumption that all mobile users act selfishly and follow a personal objective, such behavior may decrease the performance of the majority of users, hence causing fairness issue and decreasing the global energy consumption significantly. In this paper we propose a reward mechanism in a non-cooperative game framework. We assume that the base station promises the user a reward which can be a number of amounts of credit that the users use to transmit their own packets. The reward is given only to a user that transmits its packet successfully. First, we analyze the implementation of our mechanism on the equilibrium and show that as the arrival rate increases, the behavior of users become more and more aggressive resulting in a global deterioration of the expected reward the base station pays. Second and in order to achieve an efficient outcome despite the selfish behavior of users, we propose an incentive mechanism when each failure transmission of a packet incurs a certain number of costs. The cost could in fact be expressed in terms of the energy consumption when attempting to access the wireless channel. Under the proposed scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via the price of anarchy we show that the global performance of the system is improved considerably compared to the original game in particular at high loads.",abdelkrim haqiq,Game Theory,2015.0,10.1109/WINCOM.2015.7381303,2015 International Conference on Wireless Networks and Mobile Communications (WINCOM),Lmater2015,False,,IEEE,Not available,An efficient pricing mechanism of random access in wireless network with self-interested mobile users,0abf002fd892b61c3b904d03fc474daa,https://ieeexplore.ieee.org/document/7381303/
10649,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
10650,"In the decentralized networks, an important requirement arises in the design of Medium Access Control protocols is the robustness to self-interested behavior of the users. Indeed it's well known that the Medium Access Control protocols are designed based on the assumption that all mobile users act selfishly and follow a personal objective, such behavior may decrease the performance of the majority of users, hence causing fairness issue and decreasing the global energy consumption significantly. In this paper we propose a reward mechanism in a non-cooperative game framework. We assume that the base station promises the user a reward which can be a number of amounts of credit that the users use to transmit their own packets. The reward is given only to a user that transmits its packet successfully. First, we analyze the implementation of our mechanism on the equilibrium and show that as the arrival rate increases, the behavior of users become more and more aggressive resulting in a global deterioration of the expected reward the base station pays. Second and in order to achieve an efficient outcome despite the selfish behavior of users, we propose an incentive mechanism when each failure transmission of a packet incurs a certain number of costs. The cost could in fact be expressed in terms of the energy consumption when attempting to access the wireless channel. Under the proposed scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via the price of anarchy we show that the global performance of the system is improved considerably compared to the original game in particular at high loads.",abdelkrim haqiq,Nash Equilibrium,2015.0,10.1109/WINCOM.2015.7381303,2015 International Conference on Wireless Networks and Mobile Communications (WINCOM),Lmater2015,False,,IEEE,Not available,An efficient pricing mechanism of random access in wireless network with self-interested mobile users,0abf002fd892b61c3b904d03fc474daa,https://ieeexplore.ieee.org/document/7381303/
10651,"Flow scheduling is crucial in the next-generation network but hard to address due to fast changing link states and tremendous cost to explore the global structure. In this paper, we first design a distributed virtual game to solve the optimization of flow scheduling problem assuming the priori knowledge of the distribution of edge cost as a random variable. In our virtual game, we use incentives to stimulate selfish users to reach a Nash Equilibrium Point which is suboptimum based on the analysis of the `Price of Anarchy'. This algorithm is then generalized into the situation with unknown cost distribution, where the ultimate goal is to minimize the cost in the long run. In order to achieve a reasonable tradeoff between exploration of cost distribution and exploitation with limited information, we model this problem as a Multi-armed Bandit Game and combine the newly proposed DSEE with our virtual game design. Armed with these powerful tools, we find a totally distributed algorithm to ensure the logarithmic growing of regret with time, which is optimum in classic Multi-armed Bandit problem. Theoretical proof and simulation results both confirm the effectiveness of our algorithm. To the best of our knowledge, this is the first work to combine multi-armed bandit with distributed flow scheduling.",yaoqing yang,Distributed Flow Scheduling,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Yang2013,False,,IEEE,Not available,Distributed flow scheduling in an unknown environment,bd23c994ace8345256b396a372e12bfb,https://ieeexplore.ieee.org/document/6576397/
10652,"Flow scheduling is crucial in the next-generation network but hard to address due to fast changing link states and tremendous cost to explore the global structure. In this paper, we first design a distributed virtual game to solve the optimization of flow scheduling problem assuming the priori knowledge of the distribution of edge cost as a random variable. In our virtual game, we use incentives to stimulate selfish users to reach a Nash Equilibrium Point which is suboptimum based on the analysis of the `Price of Anarchy'. This algorithm is then generalized into the situation with unknown cost distribution, where the ultimate goal is to minimize the cost in the long run. In order to achieve a reasonable tradeoff between exploration of cost distribution and exploitation with limited information, we model this problem as a Multi-armed Bandit Game and combine the newly proposed DSEE with our virtual game design. Armed with these powerful tools, we find a totally distributed algorithm to ensure the logarithmic growing of regret with time, which is optimum in classic Multi-armed Bandit problem. Theoretical proof and simulation results both confirm the effectiveness of our algorithm. To the best of our knowledge, this is the first work to combine multi-armed bandit with distributed flow scheduling.",yaoqing yang,Price of Anarchy,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Yang2013,False,,IEEE,Not available,Distributed flow scheduling in an unknown environment,bd23c994ace8345256b396a372e12bfb,https://ieeexplore.ieee.org/document/6576397/
10653,"Flow scheduling is crucial in the next-generation network but hard to address due to fast changing link states and tremendous cost to explore the global structure. In this paper, we first design a distributed virtual game to solve the optimization of flow scheduling problem assuming the priori knowledge of the distribution of edge cost as a random variable. In our virtual game, we use incentives to stimulate selfish users to reach a Nash Equilibrium Point which is suboptimum based on the analysis of the `Price of Anarchy'. This algorithm is then generalized into the situation with unknown cost distribution, where the ultimate goal is to minimize the cost in the long run. In order to achieve a reasonable tradeoff between exploration of cost distribution and exploitation with limited information, we model this problem as a Multi-armed Bandit Game and combine the newly proposed DSEE with our virtual game design. Armed with these powerful tools, we find a totally distributed algorithm to ensure the logarithmic growing of regret with time, which is optimum in classic Multi-armed Bandit problem. Theoretical proof and simulation results both confirm the effectiveness of our algorithm. To the best of our knowledge, this is the first work to combine multi-armed bandit with distributed flow scheduling.",yaoqing yang,Multi-Armed Bandit,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Yang2013,False,,IEEE,Not available,Distributed flow scheduling in an unknown environment,bd23c994ace8345256b396a372e12bfb,https://ieeexplore.ieee.org/document/6576397/
10654,"Flow scheduling is crucial in the next-generation network but hard to address due to fast changing link states and tremendous cost to explore the global structure. In this paper, we first design a distributed virtual game to solve the optimization of flow scheduling problem assuming the priori knowledge of the distribution of edge cost as a random variable. In our virtual game, we use incentives to stimulate selfish users to reach a Nash Equilibrium Point which is suboptimum based on the analysis of the `Price of Anarchy'. This algorithm is then generalized into the situation with unknown cost distribution, where the ultimate goal is to minimize the cost in the long run. In order to achieve a reasonable tradeoff between exploration of cost distribution and exploitation with limited information, we model this problem as a Multi-armed Bandit Game and combine the newly proposed DSEE with our virtual game design. Armed with these powerful tools, we find a totally distributed algorithm to ensure the logarithmic growing of regret with time, which is optimum in classic Multi-armed Bandit problem. Theoretical proof and simulation results both confirm the effectiveness of our algorithm. To the best of our knowledge, this is the first work to combine multi-armed bandit with distributed flow scheduling.",yaoqing yang,Logarithmic Regret,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Yang2013,False,,IEEE,Not available,Distributed flow scheduling in an unknown environment,bd23c994ace8345256b396a372e12bfb,https://ieeexplore.ieee.org/document/6576397/
10655,"Flow scheduling is crucial in the next-generation network but hard to address due to fast changing link states and tremendous cost to explore the global structure. In this paper, we first design a distributed virtual game to solve the optimization of flow scheduling problem assuming the priori knowledge of the distribution of edge cost as a random variable. In our virtual game, we use incentives to stimulate selfish users to reach a Nash Equilibrium Point which is suboptimum based on the analysis of the `Price of Anarchy'. This algorithm is then generalized into the situation with unknown cost distribution, where the ultimate goal is to minimize the cost in the long run. In order to achieve a reasonable tradeoff between exploration of cost distribution and exploitation with limited information, we model this problem as a Multi-armed Bandit Game and combine the newly proposed DSEE with our virtual game design. Armed with these powerful tools, we find a totally distributed algorithm to ensure the logarithmic growing of regret with time, which is optimum in classic Multi-armed Bandit problem. Theoretical proof and simulation results both confirm the effectiveness of our algorithm. To the best of our knowledge, this is the first work to combine multi-armed bandit with distributed flow scheduling.",keqin liu,Distributed Flow Scheduling,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Yang2013,False,,IEEE,Not available,Distributed flow scheduling in an unknown environment,bd23c994ace8345256b396a372e12bfb,https://ieeexplore.ieee.org/document/6576397/
10656,"Flow scheduling is crucial in the next-generation network but hard to address due to fast changing link states and tremendous cost to explore the global structure. In this paper, we first design a distributed virtual game to solve the optimization of flow scheduling problem assuming the priori knowledge of the distribution of edge cost as a random variable. In our virtual game, we use incentives to stimulate selfish users to reach a Nash Equilibrium Point which is suboptimum based on the analysis of the `Price of Anarchy'. This algorithm is then generalized into the situation with unknown cost distribution, where the ultimate goal is to minimize the cost in the long run. In order to achieve a reasonable tradeoff between exploration of cost distribution and exploitation with limited information, we model this problem as a Multi-armed Bandit Game and combine the newly proposed DSEE with our virtual game design. Armed with these powerful tools, we find a totally distributed algorithm to ensure the logarithmic growing of regret with time, which is optimum in classic Multi-armed Bandit problem. Theoretical proof and simulation results both confirm the effectiveness of our algorithm. To the best of our knowledge, this is the first work to combine multi-armed bandit with distributed flow scheduling.",keqin liu,Price of Anarchy,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Yang2013,False,,IEEE,Not available,Distributed flow scheduling in an unknown environment,bd23c994ace8345256b396a372e12bfb,https://ieeexplore.ieee.org/document/6576397/
10657,"Flow scheduling is crucial in the next-generation network but hard to address due to fast changing link states and tremendous cost to explore the global structure. In this paper, we first design a distributed virtual game to solve the optimization of flow scheduling problem assuming the priori knowledge of the distribution of edge cost as a random variable. In our virtual game, we use incentives to stimulate selfish users to reach a Nash Equilibrium Point which is suboptimum based on the analysis of the `Price of Anarchy'. This algorithm is then generalized into the situation with unknown cost distribution, where the ultimate goal is to minimize the cost in the long run. In order to achieve a reasonable tradeoff between exploration of cost distribution and exploitation with limited information, we model this problem as a Multi-armed Bandit Game and combine the newly proposed DSEE with our virtual game design. Armed with these powerful tools, we find a totally distributed algorithm to ensure the logarithmic growing of regret with time, which is optimum in classic Multi-armed Bandit problem. Theoretical proof and simulation results both confirm the effectiveness of our algorithm. To the best of our knowledge, this is the first work to combine multi-armed bandit with distributed flow scheduling.",keqin liu,Multi-Armed Bandit,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Yang2013,False,,IEEE,Not available,Distributed flow scheduling in an unknown environment,bd23c994ace8345256b396a372e12bfb,https://ieeexplore.ieee.org/document/6576397/
10658,"Flow scheduling is crucial in the next-generation network but hard to address due to fast changing link states and tremendous cost to explore the global structure. In this paper, we first design a distributed virtual game to solve the optimization of flow scheduling problem assuming the priori knowledge of the distribution of edge cost as a random variable. In our virtual game, we use incentives to stimulate selfish users to reach a Nash Equilibrium Point which is suboptimum based on the analysis of the `Price of Anarchy'. This algorithm is then generalized into the situation with unknown cost distribution, where the ultimate goal is to minimize the cost in the long run. In order to achieve a reasonable tradeoff between exploration of cost distribution and exploitation with limited information, we model this problem as a Multi-armed Bandit Game and combine the newly proposed DSEE with our virtual game design. Armed with these powerful tools, we find a totally distributed algorithm to ensure the logarithmic growing of regret with time, which is optimum in classic Multi-armed Bandit problem. Theoretical proof and simulation results both confirm the effectiveness of our algorithm. To the best of our knowledge, this is the first work to combine multi-armed bandit with distributed flow scheduling.",keqin liu,Logarithmic Regret,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Yang2013,False,,IEEE,Not available,Distributed flow scheduling in an unknown environment,bd23c994ace8345256b396a372e12bfb,https://ieeexplore.ieee.org/document/6576397/
10659,"Flow scheduling is crucial in the next-generation network but hard to address due to fast changing link states and tremendous cost to explore the global structure. In this paper, we first design a distributed virtual game to solve the optimization of flow scheduling problem assuming the priori knowledge of the distribution of edge cost as a random variable. In our virtual game, we use incentives to stimulate selfish users to reach a Nash Equilibrium Point which is suboptimum based on the analysis of the `Price of Anarchy'. This algorithm is then generalized into the situation with unknown cost distribution, where the ultimate goal is to minimize the cost in the long run. In order to achieve a reasonable tradeoff between exploration of cost distribution and exploitation with limited information, we model this problem as a Multi-armed Bandit Game and combine the newly proposed DSEE with our virtual game design. Armed with these powerful tools, we find a totally distributed algorithm to ensure the logarithmic growing of regret with time, which is optimum in classic Multi-armed Bandit problem. Theoretical proof and simulation results both confirm the effectiveness of our algorithm. To the best of our knowledge, this is the first work to combine multi-armed bandit with distributed flow scheduling.",pingyi fan,Distributed Flow Scheduling,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Yang2013,False,,IEEE,Not available,Distributed flow scheduling in an unknown environment,bd23c994ace8345256b396a372e12bfb,https://ieeexplore.ieee.org/document/6576397/
10660,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
10661,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
10662,"Flow scheduling is crucial in the next-generation network but hard to address due to fast changing link states and tremendous cost to explore the global structure. In this paper, we first design a distributed virtual game to solve the optimization of flow scheduling problem assuming the priori knowledge of the distribution of edge cost as a random variable. In our virtual game, we use incentives to stimulate selfish users to reach a Nash Equilibrium Point which is suboptimum based on the analysis of the `Price of Anarchy'. This algorithm is then generalized into the situation with unknown cost distribution, where the ultimate goal is to minimize the cost in the long run. In order to achieve a reasonable tradeoff between exploration of cost distribution and exploitation with limited information, we model this problem as a Multi-armed Bandit Game and combine the newly proposed DSEE with our virtual game design. Armed with these powerful tools, we find a totally distributed algorithm to ensure the logarithmic growing of regret with time, which is optimum in classic Multi-armed Bandit problem. Theoretical proof and simulation results both confirm the effectiveness of our algorithm. To the best of our knowledge, this is the first work to combine multi-armed bandit with distributed flow scheduling.",pingyi fan,Price of Anarchy,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Yang2013,False,,IEEE,Not available,Distributed flow scheduling in an unknown environment,bd23c994ace8345256b396a372e12bfb,https://ieeexplore.ieee.org/document/6576397/
10663,"Flow scheduling is crucial in the next-generation network but hard to address due to fast changing link states and tremendous cost to explore the global structure. In this paper, we first design a distributed virtual game to solve the optimization of flow scheduling problem assuming the priori knowledge of the distribution of edge cost as a random variable. In our virtual game, we use incentives to stimulate selfish users to reach a Nash Equilibrium Point which is suboptimum based on the analysis of the `Price of Anarchy'. This algorithm is then generalized into the situation with unknown cost distribution, where the ultimate goal is to minimize the cost in the long run. In order to achieve a reasonable tradeoff between exploration of cost distribution and exploitation with limited information, we model this problem as a Multi-armed Bandit Game and combine the newly proposed DSEE with our virtual game design. Armed with these powerful tools, we find a totally distributed algorithm to ensure the logarithmic growing of regret with time, which is optimum in classic Multi-armed Bandit problem. Theoretical proof and simulation results both confirm the effectiveness of our algorithm. To the best of our knowledge, this is the first work to combine multi-armed bandit with distributed flow scheduling.",pingyi fan,Multi-Armed Bandit,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Yang2013,False,,IEEE,Not available,Distributed flow scheduling in an unknown environment,bd23c994ace8345256b396a372e12bfb,https://ieeexplore.ieee.org/document/6576397/
10664,"Flow scheduling is crucial in the next-generation network but hard to address due to fast changing link states and tremendous cost to explore the global structure. In this paper, we first design a distributed virtual game to solve the optimization of flow scheduling problem assuming the priori knowledge of the distribution of edge cost as a random variable. In our virtual game, we use incentives to stimulate selfish users to reach a Nash Equilibrium Point which is suboptimum based on the analysis of the `Price of Anarchy'. This algorithm is then generalized into the situation with unknown cost distribution, where the ultimate goal is to minimize the cost in the long run. In order to achieve a reasonable tradeoff between exploration of cost distribution and exploitation with limited information, we model this problem as a Multi-armed Bandit Game and combine the newly proposed DSEE with our virtual game design. Armed with these powerful tools, we find a totally distributed algorithm to ensure the logarithmic growing of regret with time, which is optimum in classic Multi-armed Bandit problem. Theoretical proof and simulation results both confirm the effectiveness of our algorithm. To the best of our knowledge, this is the first work to combine multi-armed bandit with distributed flow scheduling.",pingyi fan,Logarithmic Regret,2013.0,,"2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Yang2013,False,,IEEE,Not available,Distributed flow scheduling in an unknown environment,bd23c994ace8345256b396a372e12bfb,https://ieeexplore.ieee.org/document/6576397/
10665,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",qingkai liang,Cognitive radio networks,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
10666,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",qingkai liang,game theory,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
10667,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",qingkai liang,routing,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
10668,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",qingkai liang,spectrum dynamics,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
10669,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",xinbing wang,Cognitive radio networks,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
10670,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",xinbing wang,game theory,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
10671,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",xinbing wang,routing,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
10672,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
10673,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",xinbing wang,spectrum dynamics,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
10674,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",xiaohua tian,Cognitive radio networks,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
10675,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",xiaohua tian,game theory,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
10676,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",xiaohua tian,routing,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
10677,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",xiaohua tian,spectrum dynamics,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
10678,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",fan wu,Cognitive radio networks,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
10679,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",fan wu,game theory,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
10680,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",fan wu,routing,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
10681,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",fan wu,spectrum dynamics,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
10682,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",qian zhang,Cognitive radio networks,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
10683,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
10684,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",qian zhang,game theory,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
10685,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",qian zhang,routing,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
10686,"In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multihop CRN consisting of SUs as relays, such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion. Meanwhile, tradeoffs between routing costs and channel switching costs are achieved. We further formulate the route-switching problem as the Route-Switching Game, which is shown to be a potential game and has a pure Nash equilibrium (NE). Accordingly, efficient algorithms for finding the NE and the ε-NE are proposed. Then, we extend the proposed game to the incomplete-information scenario and provide a method to compute the Bayesian NE. Finally, we prove that the price of anarchy of the proposed game has a deterministic upper bound.",qian zhang,spectrum dynamics,2015.0,10.1109/TNET.2014.2315194,IEEE/ACM Transactions on Networking,Liang2015,False,,IEEE,Not available,Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework,c892aae36678c5b0a3ec64d2dec1a22a,https://ieeexplore.ieee.org/document/6799302/
10687,"We review network formation models, contrast their behavior, and conduct numerical experiments to investigate the structural features of the networks they generate. We focus primarily on problems related to minimum spanning trees and consider the cost of selfish behavior, more commonly known as the price of anarchy, in network formation. We also explore differences between local, decentralized methods for network formation and their global, centralized counterparts.",deanne mcpherson,Biological system modeling,2011.0,10.1109/ACSSC.2011.6190123,"2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)",McPherson2011,False,,IEEE,Not available,A contrasting look at network formation models and their application to the minimum spanning tree,445db4ee8bb6562e142d1a747d04a01d,https://ieeexplore.ieee.org/document/6190123/
10688,"We review network formation models, contrast their behavior, and conduct numerical experiments to investigate the structural features of the networks they generate. We focus primarily on problems related to minimum spanning trees and consider the cost of selfish behavior, more commonly known as the price of anarchy, in network formation. We also explore differences between local, decentralized methods for network formation and their global, centralized counterparts.",deanne mcpherson,Games,2011.0,10.1109/ACSSC.2011.6190123,"2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)",McPherson2011,False,,IEEE,Not available,A contrasting look at network formation models and their application to the minimum spanning tree,445db4ee8bb6562e142d1a747d04a01d,https://ieeexplore.ieee.org/document/6190123/
10689,"We review network formation models, contrast their behavior, and conduct numerical experiments to investigate the structural features of the networks they generate. We focus primarily on problems related to minimum spanning trees and consider the cost of selfish behavior, more commonly known as the price of anarchy, in network formation. We also explore differences between local, decentralized methods for network formation and their global, centralized counterparts.",deanne mcpherson,Numerical models,2011.0,10.1109/ACSSC.2011.6190123,"2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)",McPherson2011,False,,IEEE,Not available,A contrasting look at network formation models and their application to the minimum spanning tree,445db4ee8bb6562e142d1a747d04a01d,https://ieeexplore.ieee.org/document/6190123/
10690,"We review network formation models, contrast their behavior, and conduct numerical experiments to investigate the structural features of the networks they generate. We focus primarily on problems related to minimum spanning trees and consider the cost of selfish behavior, more commonly known as the price of anarchy, in network formation. We also explore differences between local, decentralized methods for network formation and their global, centralized counterparts.",deanne mcpherson,Nash equilibrium,2011.0,10.1109/ACSSC.2011.6190123,"2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)",McPherson2011,False,,IEEE,Not available,A contrasting look at network formation models and their application to the minimum spanning tree,445db4ee8bb6562e142d1a747d04a01d,https://ieeexplore.ieee.org/document/6190123/
10691,"We review network formation models, contrast their behavior, and conduct numerical experiments to investigate the structural features of the networks they generate. We focus primarily on problems related to minimum spanning trees and consider the cost of selfish behavior, more commonly known as the price of anarchy, in network formation. We also explore differences between local, decentralized methods for network formation and their global, centralized counterparts.",deanne mcpherson,Internet,2011.0,10.1109/ACSSC.2011.6190123,"2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)",McPherson2011,False,,IEEE,Not available,A contrasting look at network formation models and their application to the minimum spanning tree,445db4ee8bb6562e142d1a747d04a01d,https://ieeexplore.ieee.org/document/6190123/
10692,"We review network formation models, contrast their behavior, and conduct numerical experiments to investigate the structural features of the networks they generate. We focus primarily on problems related to minimum spanning trees and consider the cost of selfish behavior, more commonly known as the price of anarchy, in network formation. We also explore differences between local, decentralized methods for network formation and their global, centralized counterparts.",deanne mcpherson,Optimization,2011.0,10.1109/ACSSC.2011.6190123,"2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)",McPherson2011,False,,IEEE,Not available,A contrasting look at network formation models and their application to the minimum spanning tree,445db4ee8bb6562e142d1a747d04a01d,https://ieeexplore.ieee.org/document/6190123/
10693,"We review network formation models, contrast their behavior, and conduct numerical experiments to investigate the structural features of the networks they generate. We focus primarily on problems related to minimum spanning trees and consider the cost of selfish behavior, more commonly known as the price of anarchy, in network formation. We also explore differences between local, decentralized methods for network formation and their global, centralized counterparts.",deanne mcpherson,Robustness,2011.0,10.1109/ACSSC.2011.6190123,"2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)",McPherson2011,False,,IEEE,Not available,A contrasting look at network formation models and their application to the minimum spanning tree,445db4ee8bb6562e142d1a747d04a01d,https://ieeexplore.ieee.org/document/6190123/
10694,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
10695,"We review network formation models, contrast their behavior, and conduct numerical experiments to investigate the structural features of the networks they generate. We focus primarily on problems related to minimum spanning trees and consider the cost of selfish behavior, more commonly known as the price of anarchy, in network formation. We also explore differences between local, decentralized methods for network formation and their global, centralized counterparts.",david alderson,Biological system modeling,2011.0,10.1109/ACSSC.2011.6190123,"2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)",McPherson2011,False,,IEEE,Not available,A contrasting look at network formation models and their application to the minimum spanning tree,445db4ee8bb6562e142d1a747d04a01d,https://ieeexplore.ieee.org/document/6190123/
10696,"We review network formation models, contrast their behavior, and conduct numerical experiments to investigate the structural features of the networks they generate. We focus primarily on problems related to minimum spanning trees and consider the cost of selfish behavior, more commonly known as the price of anarchy, in network formation. We also explore differences between local, decentralized methods for network formation and their global, centralized counterparts.",david alderson,Games,2011.0,10.1109/ACSSC.2011.6190123,"2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)",McPherson2011,False,,IEEE,Not available,A contrasting look at network formation models and their application to the minimum spanning tree,445db4ee8bb6562e142d1a747d04a01d,https://ieeexplore.ieee.org/document/6190123/
10697,"We review network formation models, contrast their behavior, and conduct numerical experiments to investigate the structural features of the networks they generate. We focus primarily on problems related to minimum spanning trees and consider the cost of selfish behavior, more commonly known as the price of anarchy, in network formation. We also explore differences between local, decentralized methods for network formation and their global, centralized counterparts.",david alderson,Numerical models,2011.0,10.1109/ACSSC.2011.6190123,"2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)",McPherson2011,False,,IEEE,Not available,A contrasting look at network formation models and their application to the minimum spanning tree,445db4ee8bb6562e142d1a747d04a01d,https://ieeexplore.ieee.org/document/6190123/
10698,"We review network formation models, contrast their behavior, and conduct numerical experiments to investigate the structural features of the networks they generate. We focus primarily on problems related to minimum spanning trees and consider the cost of selfish behavior, more commonly known as the price of anarchy, in network formation. We also explore differences between local, decentralized methods for network formation and their global, centralized counterparts.",david alderson,Nash equilibrium,2011.0,10.1109/ACSSC.2011.6190123,"2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)",McPherson2011,False,,IEEE,Not available,A contrasting look at network formation models and their application to the minimum spanning tree,445db4ee8bb6562e142d1a747d04a01d,https://ieeexplore.ieee.org/document/6190123/
10699,"We review network formation models, contrast their behavior, and conduct numerical experiments to investigate the structural features of the networks they generate. We focus primarily on problems related to minimum spanning trees and consider the cost of selfish behavior, more commonly known as the price of anarchy, in network formation. We also explore differences between local, decentralized methods for network formation and their global, centralized counterparts.",david alderson,Internet,2011.0,10.1109/ACSSC.2011.6190123,"2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)",McPherson2011,False,,IEEE,Not available,A contrasting look at network formation models and their application to the minimum spanning tree,445db4ee8bb6562e142d1a747d04a01d,https://ieeexplore.ieee.org/document/6190123/
10700,"We review network formation models, contrast their behavior, and conduct numerical experiments to investigate the structural features of the networks they generate. We focus primarily on problems related to minimum spanning trees and consider the cost of selfish behavior, more commonly known as the price of anarchy, in network formation. We also explore differences between local, decentralized methods for network formation and their global, centralized counterparts.",david alderson,Optimization,2011.0,10.1109/ACSSC.2011.6190123,"2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)",McPherson2011,False,,IEEE,Not available,A contrasting look at network formation models and their application to the minimum spanning tree,445db4ee8bb6562e142d1a747d04a01d,https://ieeexplore.ieee.org/document/6190123/
10701,"We review network formation models, contrast their behavior, and conduct numerical experiments to investigate the structural features of the networks they generate. We focus primarily on problems related to minimum spanning trees and consider the cost of selfish behavior, more commonly known as the price of anarchy, in network formation. We also explore differences between local, decentralized methods for network formation and their global, centralized counterparts.",david alderson,Robustness,2011.0,10.1109/ACSSC.2011.6190123,"2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)",McPherson2011,False,,IEEE,Not available,A contrasting look at network formation models and their application to the minimum spanning tree,445db4ee8bb6562e142d1a747d04a01d,https://ieeexplore.ieee.org/document/6190123/
10702,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",huigang chen,Routing,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
10703,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",huigang chen,Nash equilibrium,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
10704,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",huigang chen,Communication system traffic control,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
10705,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
10706,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",huigang chen,Traffic control,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
10707,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",huigang chen,Educational institutions,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
10708,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",huigang chen,USA Councils,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
10709,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",huigang chen,H infinity control,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
10710,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",huigang chen,Bandwidth,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
10711,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",huigang chen,Laboratories,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
10712,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",huigang chen,Distributed algorithms,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
10713,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",john baras,Routing,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
10714,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",john baras,Nash equilibrium,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
10715,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",john baras,Communication system traffic control,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
10716,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
10717,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",john baras,Traffic control,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
10718,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",john baras,Educational institutions,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
10719,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",john baras,USA Councils,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
10720,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",john baras,H infinity control,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
10721,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",john baras,Bandwidth,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
10722,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",john baras,Laboratories,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
10723,"We consider the problem of combined single- path routing and flow control, which is nonconvex and NP-hard to solve exactly. We focus on the ""many-user"" region, i.e. large networks that have far more users than bottleneck links, which is close to real network scenarios. We first show that by allowing a proportionally small number of users to use multipath routing, while keeping the remaining majority using single-path routing, results in a solution that achieves multipath optimality. Therefore it is conceptually plausible that in the many-user region a local algorithm can achieve solutions arbitrarily close to the optimal solution. To show this is indeed correct, we focus on the solutions brought out by the simplest local algorithm, the Nash algorithm. We first examine a special type of network and show that the Nash equilibrium exists and the Nash algorithm always converges. It is then shown that the 'price of anarchy', that is the gap between the worst Nash equilibrium and the social optimum, is bounded when the number of users goes to infinity. For general networks, it is not known whether there exists a Nash equilibrium. We introduce the concept of approximate Nash equilibrium, show its existence, and prove that it will be arbitrary close to the social optimum when the number of users is sufficiently large.",john baras,Distributed algorithms,2007.0,10.1109/CDC.2007.4434551,2007 46th IEEE Conference on Decision and Control,Chen2007,False,,IEEE,Not available,Combined single-path routing and flow control in many-user region: a case for nash efficiency,8b8dbc294f4d536aa8d01920793c874e,https://ieeexplore.ieee.org/document/4434551/
10724,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",jing zhang,Optimization,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
10725,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",jing zhang,Price-of-Anarchy (PoA),2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
10726,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",jing zhang,sensitivity analysis,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
10727,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
10728,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",jing zhang,traffic assignment problem,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
10729,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",jing zhang,transportation networks,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
10730,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",jing zhang,variational inequalities,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
10731,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",sepideh pourazarm,Optimization,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
10732,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",sepideh pourazarm,Price-of-Anarchy (PoA),2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
10733,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",sepideh pourazarm,sensitivity analysis,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
10734,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",sepideh pourazarm,traffic assignment problem,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
10735,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",sepideh pourazarm,transportation networks,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
10736,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",sepideh pourazarm,variational inequalities,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
10737,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",christos cassandras,Optimization,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
10738,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
10739,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",christos cassandras,Price-of-Anarchy (PoA),2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
10740,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",christos cassandras,sensitivity analysis,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
10741,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",christos cassandras,traffic assignment problem,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
10742,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",christos cassandras,transportation networks,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
10743,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",christos cassandras,variational inequalities,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
10744,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",ioannis paschalidis,Optimization,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
10745,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",ioannis paschalidis,Price-of-Anarchy (PoA),2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
10746,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",ioannis paschalidis,sensitivity analysis,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
10747,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",ioannis paschalidis,traffic assignment problem,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
10748,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",ioannis paschalidis,transportation networks,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
10749,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
10750,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",ioannis paschalidis,variational inequalities,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
10751,"We investigate cascades in networks consisting of strategic agents with interdependent security. We assume that the strategic agents have choices between (i) investing in protecting themselves, (ii) purchasing insurance to transfer (some) risks, and (iii) taking no actions. Using a population game model, we study how various system parameters, such as node degrees, infection propagation rate, and the probability with which infected nodes transmit infection to neighbors, affect nodes' choices at Nash equilibria and the resultant price of anarchy/stability. In addition, we examine how the probability that a single infected node can spread the infection to a significant portion of the entire network, called cascade probability, behaves with respect to system parameters. In particular, we demonstrate that, at least for some parameter regimes, the cascade probability increases with the average degree of nodes.",richard la,Cascade,2016.0,10.1109/TNET.2015.2408598,IEEE/ACM Transactions on Networking,La2016,False,,IEEE,Not available,Interdependent Security With Strategic Agents and Cascades of Infection,61cf886f0b42047e446f31bd8c9959af,https://ieeexplore.ieee.org/document/7065333/
10752,"We investigate cascades in networks consisting of strategic agents with interdependent security. We assume that the strategic agents have choices between (i) investing in protecting themselves, (ii) purchasing insurance to transfer (some) risks, and (iii) taking no actions. Using a population game model, we study how various system parameters, such as node degrees, infection propagation rate, and the probability with which infected nodes transmit infection to neighbors, affect nodes' choices at Nash equilibria and the resultant price of anarchy/stability. In addition, we examine how the probability that a single infected node can spread the infection to a significant portion of the entire network, called cascade probability, behaves with respect to system parameters. In particular, we demonstrate that, at least for some parameter regimes, the cascade probability increases with the average degree of nodes.",richard la,contagion,2016.0,10.1109/TNET.2015.2408598,IEEE/ACM Transactions on Networking,La2016,False,,IEEE,Not available,Interdependent Security With Strategic Agents and Cascades of Infection,61cf886f0b42047e446f31bd8c9959af,https://ieeexplore.ieee.org/document/7065333/
10753,"We investigate cascades in networks consisting of strategic agents with interdependent security. We assume that the strategic agents have choices between (i) investing in protecting themselves, (ii) purchasing insurance to transfer (some) risks, and (iii) taking no actions. Using a population game model, we study how various system parameters, such as node degrees, infection propagation rate, and the probability with which infected nodes transmit infection to neighbors, affect nodes' choices at Nash equilibria and the resultant price of anarchy/stability. In addition, we examine how the probability that a single infected node can spread the infection to a significant portion of the entire network, called cascade probability, behaves with respect to system parameters. In particular, we demonstrate that, at least for some parameter regimes, the cascade probability increases with the average degree of nodes.",richard la,interdependent security,2016.0,10.1109/TNET.2015.2408598,IEEE/ACM Transactions on Networking,La2016,False,,IEEE,Not available,Interdependent Security With Strategic Agents and Cascades of Infection,61cf886f0b42047e446f31bd8c9959af,https://ieeexplore.ieee.org/document/7065333/
10754,"We investigate cascades in networks consisting of strategic agents with interdependent security. We assume that the strategic agents have choices between (i) investing in protecting themselves, (ii) purchasing insurance to transfer (some) risks, and (iii) taking no actions. Using a population game model, we study how various system parameters, such as node degrees, infection propagation rate, and the probability with which infected nodes transmit infection to neighbors, affect nodes' choices at Nash equilibria and the resultant price of anarchy/stability. In addition, we examine how the probability that a single infected node can spread the infection to a significant portion of the entire network, called cascade probability, behaves with respect to system parameters. In particular, we demonstrate that, at least for some parameter regimes, the cascade probability increases with the average degree of nodes.",richard la,population game,2016.0,10.1109/TNET.2015.2408598,IEEE/ACM Transactions on Networking,La2016,False,,IEEE,Not available,Interdependent Security With Strategic Agents and Cascades of Infection,61cf886f0b42047e446f31bd8c9959af,https://ieeexplore.ieee.org/document/7065333/
10755,"We investigate cascades in networks consisting of strategic agents with interdependent security. We assume that the strategic agents have choices between (i) investing in protecting themselves, (ii) purchasing insurance to transfer (some) risks, and (iii) taking no actions. Using a population game model, we study how various system parameters, such as node degrees, infection propagation rate, and the probability with which infected nodes transmit infection to neighbors, affect nodes' choices at Nash equilibria and the resultant price of anarchy/stability. In addition, we examine how the probability that a single infected node can spread the infection to a significant portion of the entire network, called cascade probability, behaves with respect to system parameters. In particular, we demonstrate that, at least for some parameter regimes, the cascade probability increases with the average degree of nodes.",richard la,price of anarchy,2016.0,10.1109/TNET.2015.2408598,IEEE/ACM Transactions on Networking,La2016,False,,IEEE,Not available,Interdependent Security With Strategic Agents and Cascades of Infection,61cf886f0b42047e446f31bd8c9959af,https://ieeexplore.ieee.org/document/7065333/
10756,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",wenchao xu,Games,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
10757,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",wenchao xu,Switches,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
10758,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",wenchao xu,IEEE 802.11 Standards,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
10759,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",wenchao xu,Wireless networks,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
10760,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
10761,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",wenchao xu,Indexes,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
10762,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",wenchao xu,Nash equilibrium,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
10763,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",wenchao xu,Delay,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
10764,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",cunqing hua,Games,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
10765,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",cunqing hua,Switches,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
10766,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",cunqing hua,IEEE 802.11 Standards,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
10767,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",cunqing hua,Wireless networks,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
10768,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",cunqing hua,Indexes,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
10769,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",cunqing hua,Nash equilibrium,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
10770,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",cunqing hua,Delay,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
10771,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
10772,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
10773,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",aiping huang,Games,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
10774,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",aiping huang,Switches,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
10775,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",aiping huang,IEEE 802.11 Standards,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
10776,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",aiping huang,Wireless networks,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
10777,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",aiping huang,Indexes,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
10778,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",aiping huang,Nash equilibrium,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
10779,"In densely deployed IEEE 802.11 wireless networks, the transmission delay experienced by a user depends not only on the traffic load of the associated AP, but also the contention level of other APs operating on the same channel. However, due to the random distribution of users and inappropriate allocation of AP channels, the traffic loads of different APs are often uneven, leading to unfair delay experience to different users. In this paper, we consider the problem of channel assignment and user association for balancing the traffic load of APs operating on different channels, which is modeled as a non-cooperative game. We prove the existence of Nash equilibrium (NE) for this game, and derive the price of anarchy and the fairness index at NE. Simulation results are provided to compare the performance of the proposed algorithm with the theoretical bounds.",aiping huang,Delay,2011.0,10.1109/icc.2011.5962628,2011 IEEE International Conference on Communications (ICC),Xu2011,False,,IEEE,Not available,Channel Assignment and User Association Game in Dense 802.11 Wireless Networks,d39d1f31a7cdbbd10163db303bd2879e,https://ieeexplore.ieee.org/document/5962628/
10780,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",ahmed alaa,Cognitive networking,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
10781,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",ahmed alaa,cognitive agents,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
10782,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",ahmed alaa,information networks,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
10783,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
10784,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",ahmed alaa,network formation,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
10785,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",ahmed alaa,self-organizing networks,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
10786,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",ahmed alaa,Cognitive networking,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
10787,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",ahmed alaa,cognitive agents,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
10788,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",ahmed alaa,information networks,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
10789,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",ahmed alaa,network formation,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
10790,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",ahmed alaa,self-organizing networks,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
10791,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",kartik ahuja,Cognitive networking,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
10792,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",kartik ahuja,cognitive agents,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
10793,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",kartik ahuja,information networks,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
10794,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
10795,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",kartik ahuja,network formation,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
10796,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",kartik ahuja,self-organizing networks,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
10797,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",kartik ahuja,Cognitive networking,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
10798,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",kartik ahuja,cognitive agents,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
10799,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",kartik ahuja,information networks,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
10800,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",kartik ahuja,network formation,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
10801,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",kartik ahuja,self-organizing networks,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
10802,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",mihaela schaar,Cognitive networking,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
10803,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",mihaela schaar,cognitive agents,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
10804,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",mihaela schaar,information networks,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
10805,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
10806,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",mihaela schaar,network formation,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
10807,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",mihaela schaar,self-organizing networks,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
10808,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",mihaela schaar,Cognitive networking,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
10809,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",mihaela schaar,cognitive agents,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
10810,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",mihaela schaar,information networks,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
10811,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",mihaela schaar,network formation,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
10812,"In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper, we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a noncooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss we provide estimates for the price of anarchy (PoA), and to quantify the impact on individual information loss we introduce and provide estimates for a measure we call maximum information loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known “law of the few” depends on how information aggregates, in particular, the “law of the few” fails when information displays complementarities.",mihaela schaar,self-organizing networks,2015.0,10.1109/TCCN.2015.2499284,IEEE Transactions on Cognitive Communications and Networking,Alaa2015,False,,IEEE,Not available,Self-Organizing Networks of Information Gathering Cognitive Agents,b852fa82585cd8ca3a5bdd9e7b2465ac,https://ieeexplore.ieee.org/document/7323822/
10813,"Renewable energy continues to increase its share of total US electricity production at a dramatic rate. Power derived from such resources is inherently variable and naturally incurs a balancing cost to the power system. A basic question we aim to address in this paper is, given a collection of variable energy producers, how to disentangle the individual sources of cost causation from the aggregate system cost and allocate it back to those responsible parties, so as to induce a near efficient outcome in the forward market for energy. In particular, we propose an ex post cost sharing mechanism, satisfying certain fairness axioms, to allocate to each player a share of the total system cost in proportion to her relative contribution to the aggregate system imbalance. We establish the existence and certain properties of Nash equilibria of the forward contract game under proportional cost sharing and provide an explicit characterization for the Price of Anarchy (PoA) as the number of participants in the market grows large. We also characterize a family of `worst case' prior distributions on the supply profile at which the asymptotic PoA is maximized.",weixuan lin,Renewable Energy,2014.0,10.1109/CDC.2014.7039645,53rd IEEE Conference on Decision and Control,Lin2014,False,,IEEE,Not available,Forward electricity markets with uncertain supply: Cost sharing and efficiency loss,0dd44b6f327d72e8d22639abc523a2c6,https://ieeexplore.ieee.org/document/7039645/
10814,"Renewable energy continues to increase its share of total US electricity production at a dramatic rate. Power derived from such resources is inherently variable and naturally incurs a balancing cost to the power system. A basic question we aim to address in this paper is, given a collection of variable energy producers, how to disentangle the individual sources of cost causation from the aggregate system cost and allocate it back to those responsible parties, so as to induce a near efficient outcome in the forward market for energy. In particular, we propose an ex post cost sharing mechanism, satisfying certain fairness axioms, to allocate to each player a share of the total system cost in proportion to her relative contribution to the aggregate system imbalance. We establish the existence and certain properties of Nash equilibria of the forward contract game under proportional cost sharing and provide an explicit characterization for the Price of Anarchy (PoA) as the number of participants in the market grows large. We also characterize a family of `worst case' prior distributions on the supply profile at which the asymptotic PoA is maximized.",weixuan lin,Cost Sharing Mechanisms,2014.0,10.1109/CDC.2014.7039645,53rd IEEE Conference on Decision and Control,Lin2014,False,,IEEE,Not available,Forward electricity markets with uncertain supply: Cost sharing and efficiency loss,0dd44b6f327d72e8d22639abc523a2c6,https://ieeexplore.ieee.org/document/7039645/
10815,"Renewable energy continues to increase its share of total US electricity production at a dramatic rate. Power derived from such resources is inherently variable and naturally incurs a balancing cost to the power system. A basic question we aim to address in this paper is, given a collection of variable energy producers, how to disentangle the individual sources of cost causation from the aggregate system cost and allocate it back to those responsible parties, so as to induce a near efficient outcome in the forward market for energy. In particular, we propose an ex post cost sharing mechanism, satisfying certain fairness axioms, to allocate to each player a share of the total system cost in proportion to her relative contribution to the aggregate system imbalance. We establish the existence and certain properties of Nash equilibria of the forward contract game under proportional cost sharing and provide an explicit characterization for the Price of Anarchy (PoA) as the number of participants in the market grows large. We also characterize a family of `worst case' prior distributions on the supply profile at which the asymptotic PoA is maximized.",weixuan lin,Electricity Markets,2014.0,10.1109/CDC.2014.7039645,53rd IEEE Conference on Decision and Control,Lin2014,False,,IEEE,Not available,Forward electricity markets with uncertain supply: Cost sharing and efficiency loss,0dd44b6f327d72e8d22639abc523a2c6,https://ieeexplore.ieee.org/document/7039645/
10816,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
10817,"Renewable energy continues to increase its share of total US electricity production at a dramatic rate. Power derived from such resources is inherently variable and naturally incurs a balancing cost to the power system. A basic question we aim to address in this paper is, given a collection of variable energy producers, how to disentangle the individual sources of cost causation from the aggregate system cost and allocate it back to those responsible parties, so as to induce a near efficient outcome in the forward market for energy. In particular, we propose an ex post cost sharing mechanism, satisfying certain fairness axioms, to allocate to each player a share of the total system cost in proportion to her relative contribution to the aggregate system imbalance. We establish the existence and certain properties of Nash equilibria of the forward contract game under proportional cost sharing and provide an explicit characterization for the Price of Anarchy (PoA) as the number of participants in the market grows large. We also characterize a family of `worst case' prior distributions on the supply profile at which the asymptotic PoA is maximized.",eilyan bitar,Renewable Energy,2014.0,10.1109/CDC.2014.7039645,53rd IEEE Conference on Decision and Control,Lin2014,False,,IEEE,Not available,Forward electricity markets with uncertain supply: Cost sharing and efficiency loss,0dd44b6f327d72e8d22639abc523a2c6,https://ieeexplore.ieee.org/document/7039645/
10818,"Renewable energy continues to increase its share of total US electricity production at a dramatic rate. Power derived from such resources is inherently variable and naturally incurs a balancing cost to the power system. A basic question we aim to address in this paper is, given a collection of variable energy producers, how to disentangle the individual sources of cost causation from the aggregate system cost and allocate it back to those responsible parties, so as to induce a near efficient outcome in the forward market for energy. In particular, we propose an ex post cost sharing mechanism, satisfying certain fairness axioms, to allocate to each player a share of the total system cost in proportion to her relative contribution to the aggregate system imbalance. We establish the existence and certain properties of Nash equilibria of the forward contract game under proportional cost sharing and provide an explicit characterization for the Price of Anarchy (PoA) as the number of participants in the market grows large. We also characterize a family of `worst case' prior distributions on the supply profile at which the asymptotic PoA is maximized.",eilyan bitar,Cost Sharing Mechanisms,2014.0,10.1109/CDC.2014.7039645,53rd IEEE Conference on Decision and Control,Lin2014,False,,IEEE,Not available,Forward electricity markets with uncertain supply: Cost sharing and efficiency loss,0dd44b6f327d72e8d22639abc523a2c6,https://ieeexplore.ieee.org/document/7039645/
10819,"Renewable energy continues to increase its share of total US electricity production at a dramatic rate. Power derived from such resources is inherently variable and naturally incurs a balancing cost to the power system. A basic question we aim to address in this paper is, given a collection of variable energy producers, how to disentangle the individual sources of cost causation from the aggregate system cost and allocate it back to those responsible parties, so as to induce a near efficient outcome in the forward market for energy. In particular, we propose an ex post cost sharing mechanism, satisfying certain fairness axioms, to allocate to each player a share of the total system cost in proportion to her relative contribution to the aggregate system imbalance. We establish the existence and certain properties of Nash equilibria of the forward contract game under proportional cost sharing and provide an explicit characterization for the Price of Anarchy (PoA) as the number of participants in the market grows large. We also characterize a family of `worst case' prior distributions on the supply profile at which the asymptotic PoA is maximized.",eilyan bitar,Electricity Markets,2014.0,10.1109/CDC.2014.7039645,53rd IEEE Conference on Decision and Control,Lin2014,False,,IEEE,Not available,Forward electricity markets with uncertain supply: Cost sharing and efficiency loss,0dd44b6f327d72e8d22639abc523a2c6,https://ieeexplore.ieee.org/document/7039645/
10820,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",seyed ahmadyan,Games,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
10821,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",seyed ahmadyan,Resource management,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
10822,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",seyed ahmadyan,Nash equilibrium,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
10823,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",seyed ahmadyan,Approximation algorithms,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
10824,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",seyed ahmadyan,Search methods,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
10825,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",seyed ahmadyan,Economics,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
10826,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",seyed ahmadyan,Electronic mail,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
10827,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
10828,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",seyed etesami,Games,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
10829,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",seyed etesami,Resource management,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
10830,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",seyed etesami,Nash equilibrium,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
10831,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",seyed etesami,Approximation algorithms,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
10832,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",seyed etesami,Search methods,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
10833,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",seyed etesami,Economics,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
10834,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",seyed etesami,Electronic mail,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
10835,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",h. poor,Games,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
10836,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",h. poor,Resource management,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
10837,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",h. poor,Nash equilibrium,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
10838,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
10839,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",h. poor,Approximation algorithms,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
10840,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",h. poor,Search methods,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
10841,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",h. poor,Economics,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
10842,"In this paper, we consider a resource allocation game with binary preferences and limited capacities over large scale networks and propose a novel randomized algorithm for searching its pure-strategy Nash equilibrium points. It is known that such games always admit a pure-strategy Nash equilibrium and benefit from having a low price of anarchy. However, the best known theoretical results only provide a quasi-polynomial constant approximation algorithm of the equilibrium points over general networks. Here, we search the state space of the resource allocation game for its equilibrium points. We use a random tree based search method to minimize a proper score function and direct the search toward the pure-strategy Nash equilibrium points of the system. We demonstrate efficiency of our algorithm through some empirical results.",h. poor,Electronic mail,2016.0,10.1109/CDC.2016.7798943,2016 IEEE 55th Conference on Decision and Control (CDC),Ahmadyan2016,False,,IEEE,Not available,A random tree search algorithm for Nash equilibrium in capacitated selfish replication games,91a1944ea1ff1cf3a19e6b8676345813,https://ieeexplore.ieee.org/document/7798943/
10843,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",yezekael hayel,Games,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
10844,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",yezekael hayel,Approximation methods,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
10845,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",yezekael hayel,Investment,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
10846,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",yezekael hayel,Nash equilibrium,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
10847,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",yezekael hayel,Optimized production technology,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
10848,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",yezekael hayel,Upper bound,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
10849,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
10850,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",yezekael hayel,Communities,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
10851,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",stojan trajanovski,Games,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
10852,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",stojan trajanovski,Approximation methods,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
10853,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",stojan trajanovski,Investment,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
10854,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",stojan trajanovski,Nash equilibrium,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
10855,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",stojan trajanovski,Optimized production technology,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
10856,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",stojan trajanovski,Upper bound,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
10857,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",stojan trajanovski,Communities,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
10858,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",eitan altman,Games,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
10859,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",eitan altman,Approximation methods,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
10860,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
10861,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",eitan altman,Investment,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
10862,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",eitan altman,Nash equilibrium,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
10863,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",eitan altman,Optimized production technology,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
10864,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",eitan altman,Upper bound,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
10865,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",eitan altman,Communities,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
10866,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",huijuan wang,Games,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
10867,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",huijuan wang,Approximation methods,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
10868,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",huijuan wang,Investment,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
10869,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",huijuan wang,Nash equilibrium,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
10870,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",huijuan wang,Optimized production technology,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
10871,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
10872,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",huijuan wang,Upper bound,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
10873,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",huijuan wang,Communities,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
10874,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",piet mieghem,Games,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
10875,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",piet mieghem,Approximation methods,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
10876,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",piet mieghem,Investment,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
10877,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",piet mieghem,Nash equilibrium,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
10878,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",piet mieghem,Optimized production technology,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
10879,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",piet mieghem,Upper bound,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
10880,"Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a Susceptible Infected Susceptible (SIS) epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework. Based on this model, we find pure and mixed equilibria, and evaluate the performance of the equilibria by finding the Price of Anarchy (PoA) in several network topologies. Finally, we give numerical illustrations of our results.",piet mieghem,Communities,2014.0,10.1109/CDC.2014.7039541,53rd IEEE Conference on Decision and Control,Hayel2014,False,,IEEE,Not available,Complete game-theoretic characterization of SIS epidemics protection strategies,7dc45cee93f9e725c9a27527b7e6be61,https://ieeexplore.ieee.org/document/7039541/
10881,"A classic optimization problem in network routing is to minimize C + D, where C is the maximum edge congestion and D is the maximum path length (also known as dilation). The problem of computing the optimal C* + D* is NP-complete even when either C* or D* is a small constant. We study routing games in general networks where each player i selfishly selects a path that minimizes C&lt;sub&gt;i&lt;/sub&gt; + D&lt;sub&gt;i&lt;/sub&gt; the sum of congestion and dilation of the player's path. We first show that there are instances of this game without Nash equilibria. We then turn to the related quality of routing (QoR) games which always have Nash equilibria. QoR games represent networks with a small number of service classes where paths in different classes do not interfere with each other (with frequency or time division multiplexing). QoR games have O(log&lt;sup&gt;4&lt;/sup&gt; n) price of anarchy when either C* or D* is a constant. Thus, Nash equilibria of QoR games give poly-log approximations to hard optimization problems.",costas busch,Algorithmic game theory,2012.0,10.1109/TC.2011.145,IEEE Transactions on Computers,Busch2012,False,,IEEE,Not available,Approximating Congestion + Dilation in Networks via &amp;#x0022;Quality of Routing&amp;amp;#x201D; Games,9915f48a2e9721b4a32e0a807083d647,https://ieeexplore.ieee.org/document/5963649/
10882,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
10883,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
10884,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
10885,"A classic optimization problem in network routing is to minimize C + D, where C is the maximum edge congestion and D is the maximum path length (also known as dilation). The problem of computing the optimal C* + D* is NP-complete even when either C* or D* is a small constant. We study routing games in general networks where each player i selfishly selects a path that minimizes C&lt;sub&gt;i&lt;/sub&gt; + D&lt;sub&gt;i&lt;/sub&gt; the sum of congestion and dilation of the player's path. We first show that there are instances of this game without Nash equilibria. We then turn to the related quality of routing (QoR) games which always have Nash equilibria. QoR games represent networks with a small number of service classes where paths in different classes do not interfere with each other (with frequency or time division multiplexing). QoR games have O(log&lt;sup&gt;4&lt;/sup&gt; n) price of anarchy when either C* or D* is a constant. Thus, Nash equilibria of QoR games give poly-log approximations to hard optimization problems.",costas busch,congestion game,2012.0,10.1109/TC.2011.145,IEEE Transactions on Computers,Busch2012,False,,IEEE,Not available,Approximating Congestion + Dilation in Networks via &amp;#x0022;Quality of Routing&amp;amp;#x201D; Games,9915f48a2e9721b4a32e0a807083d647,https://ieeexplore.ieee.org/document/5963649/
10886,"A classic optimization problem in network routing is to minimize C + D, where C is the maximum edge congestion and D is the maximum path length (also known as dilation). The problem of computing the optimal C* + D* is NP-complete even when either C* or D* is a small constant. We study routing games in general networks where each player i selfishly selects a path that minimizes C&lt;sub&gt;i&lt;/sub&gt; + D&lt;sub&gt;i&lt;/sub&gt; the sum of congestion and dilation of the player's path. We first show that there are instances of this game without Nash equilibria. We then turn to the related quality of routing (QoR) games which always have Nash equilibria. QoR games represent networks with a small number of service classes where paths in different classes do not interfere with each other (with frequency or time division multiplexing). QoR games have O(log&lt;sup&gt;4&lt;/sup&gt; n) price of anarchy when either C* or D* is a constant. Thus, Nash equilibria of QoR games give poly-log approximations to hard optimization problems.",costas busch,routing game,2012.0,10.1109/TC.2011.145,IEEE Transactions on Computers,Busch2012,False,,IEEE,Not available,Approximating Congestion + Dilation in Networks via &amp;#x0022;Quality of Routing&amp;amp;#x201D; Games,9915f48a2e9721b4a32e0a807083d647,https://ieeexplore.ieee.org/document/5963649/
10887,"A classic optimization problem in network routing is to minimize C + D, where C is the maximum edge congestion and D is the maximum path length (also known as dilation). The problem of computing the optimal C* + D* is NP-complete even when either C* or D* is a small constant. We study routing games in general networks where each player i selfishly selects a path that minimizes C&lt;sub&gt;i&lt;/sub&gt; + D&lt;sub&gt;i&lt;/sub&gt; the sum of congestion and dilation of the player's path. We first show that there are instances of this game without Nash equilibria. We then turn to the related quality of routing (QoR) games which always have Nash equilibria. QoR games represent networks with a small number of service classes where paths in different classes do not interfere with each other (with frequency or time division multiplexing). QoR games have O(log&lt;sup&gt;4&lt;/sup&gt; n) price of anarchy when either C* or D* is a constant. Thus, Nash equilibria of QoR games give poly-log approximations to hard optimization problems.",costas busch,Nash equilibrium,2012.0,10.1109/TC.2011.145,IEEE Transactions on Computers,Busch2012,False,,IEEE,Not available,Approximating Congestion + Dilation in Networks via &amp;#x0022;Quality of Routing&amp;amp;#x201D; Games,9915f48a2e9721b4a32e0a807083d647,https://ieeexplore.ieee.org/document/5963649/
10888,"A classic optimization problem in network routing is to minimize C + D, where C is the maximum edge congestion and D is the maximum path length (also known as dilation). The problem of computing the optimal C* + D* is NP-complete even when either C* or D* is a small constant. We study routing games in general networks where each player i selfishly selects a path that minimizes C&lt;sub&gt;i&lt;/sub&gt; + D&lt;sub&gt;i&lt;/sub&gt; the sum of congestion and dilation of the player's path. We first show that there are instances of this game without Nash equilibria. We then turn to the related quality of routing (QoR) games which always have Nash equilibria. QoR games represent networks with a small number of service classes where paths in different classes do not interfere with each other (with frequency or time division multiplexing). QoR games have O(log&lt;sup&gt;4&lt;/sup&gt; n) price of anarchy when either C* or D* is a constant. Thus, Nash equilibria of QoR games give poly-log approximations to hard optimization problems.",costas busch,price of anarchy.,2012.0,10.1109/TC.2011.145,IEEE Transactions on Computers,Busch2012,False,,IEEE,Not available,Approximating Congestion + Dilation in Networks via &amp;#x0022;Quality of Routing&amp;amp;#x201D; Games,9915f48a2e9721b4a32e0a807083d647,https://ieeexplore.ieee.org/document/5963649/
10889,"A classic optimization problem in network routing is to minimize C + D, where C is the maximum edge congestion and D is the maximum path length (also known as dilation). The problem of computing the optimal C* + D* is NP-complete even when either C* or D* is a small constant. We study routing games in general networks where each player i selfishly selects a path that minimizes C&lt;sub&gt;i&lt;/sub&gt; + D&lt;sub&gt;i&lt;/sub&gt; the sum of congestion and dilation of the player's path. We first show that there are instances of this game without Nash equilibria. We then turn to the related quality of routing (QoR) games which always have Nash equilibria. QoR games represent networks with a small number of service classes where paths in different classes do not interfere with each other (with frequency or time division multiplexing). QoR games have O(log&lt;sup&gt;4&lt;/sup&gt; n) price of anarchy when either C* or D* is a constant. Thus, Nash equilibria of QoR games give poly-log approximations to hard optimization problems.",rajgopal kannan,Algorithmic game theory,2012.0,10.1109/TC.2011.145,IEEE Transactions on Computers,Busch2012,False,,IEEE,Not available,Approximating Congestion + Dilation in Networks via &amp;#x0022;Quality of Routing&amp;amp;#x201D; Games,9915f48a2e9721b4a32e0a807083d647,https://ieeexplore.ieee.org/document/5963649/
10890,"A classic optimization problem in network routing is to minimize C + D, where C is the maximum edge congestion and D is the maximum path length (also known as dilation). The problem of computing the optimal C* + D* is NP-complete even when either C* or D* is a small constant. We study routing games in general networks where each player i selfishly selects a path that minimizes C&lt;sub&gt;i&lt;/sub&gt; + D&lt;sub&gt;i&lt;/sub&gt; the sum of congestion and dilation of the player's path. We first show that there are instances of this game without Nash equilibria. We then turn to the related quality of routing (QoR) games which always have Nash equilibria. QoR games represent networks with a small number of service classes where paths in different classes do not interfere with each other (with frequency or time division multiplexing). QoR games have O(log&lt;sup&gt;4&lt;/sup&gt; n) price of anarchy when either C* or D* is a constant. Thus, Nash equilibria of QoR games give poly-log approximations to hard optimization problems.",rajgopal kannan,congestion game,2012.0,10.1109/TC.2011.145,IEEE Transactions on Computers,Busch2012,False,,IEEE,Not available,Approximating Congestion + Dilation in Networks via &amp;#x0022;Quality of Routing&amp;amp;#x201D; Games,9915f48a2e9721b4a32e0a807083d647,https://ieeexplore.ieee.org/document/5963649/
10891,"A classic optimization problem in network routing is to minimize C + D, where C is the maximum edge congestion and D is the maximum path length (also known as dilation). The problem of computing the optimal C* + D* is NP-complete even when either C* or D* is a small constant. We study routing games in general networks where each player i selfishly selects a path that minimizes C&lt;sub&gt;i&lt;/sub&gt; + D&lt;sub&gt;i&lt;/sub&gt; the sum of congestion and dilation of the player's path. We first show that there are instances of this game without Nash equilibria. We then turn to the related quality of routing (QoR) games which always have Nash equilibria. QoR games represent networks with a small number of service classes where paths in different classes do not interfere with each other (with frequency or time division multiplexing). QoR games have O(log&lt;sup&gt;4&lt;/sup&gt; n) price of anarchy when either C* or D* is a constant. Thus, Nash equilibria of QoR games give poly-log approximations to hard optimization problems.",rajgopal kannan,routing game,2012.0,10.1109/TC.2011.145,IEEE Transactions on Computers,Busch2012,False,,IEEE,Not available,Approximating Congestion + Dilation in Networks via &amp;#x0022;Quality of Routing&amp;amp;#x201D; Games,9915f48a2e9721b4a32e0a807083d647,https://ieeexplore.ieee.org/document/5963649/
10892,"A classic optimization problem in network routing is to minimize C + D, where C is the maximum edge congestion and D is the maximum path length (also known as dilation). The problem of computing the optimal C* + D* is NP-complete even when either C* or D* is a small constant. We study routing games in general networks where each player i selfishly selects a path that minimizes C&lt;sub&gt;i&lt;/sub&gt; + D&lt;sub&gt;i&lt;/sub&gt; the sum of congestion and dilation of the player's path. We first show that there are instances of this game without Nash equilibria. We then turn to the related quality of routing (QoR) games which always have Nash equilibria. QoR games represent networks with a small number of service classes where paths in different classes do not interfere with each other (with frequency or time division multiplexing). QoR games have O(log&lt;sup&gt;4&lt;/sup&gt; n) price of anarchy when either C* or D* is a constant. Thus, Nash equilibria of QoR games give poly-log approximations to hard optimization problems.",rajgopal kannan,Nash equilibrium,2012.0,10.1109/TC.2011.145,IEEE Transactions on Computers,Busch2012,False,,IEEE,Not available,Approximating Congestion + Dilation in Networks via &amp;#x0022;Quality of Routing&amp;amp;#x201D; Games,9915f48a2e9721b4a32e0a807083d647,https://ieeexplore.ieee.org/document/5963649/
10893,"A classic optimization problem in network routing is to minimize C + D, where C is the maximum edge congestion and D is the maximum path length (also known as dilation). The problem of computing the optimal C* + D* is NP-complete even when either C* or D* is a small constant. We study routing games in general networks where each player i selfishly selects a path that minimizes C&lt;sub&gt;i&lt;/sub&gt; + D&lt;sub&gt;i&lt;/sub&gt; the sum of congestion and dilation of the player's path. We first show that there are instances of this game without Nash equilibria. We then turn to the related quality of routing (QoR) games which always have Nash equilibria. QoR games represent networks with a small number of service classes where paths in different classes do not interfere with each other (with frequency or time division multiplexing). QoR games have O(log&lt;sup&gt;4&lt;/sup&gt; n) price of anarchy when either C* or D* is a constant. Thus, Nash equilibria of QoR games give poly-log approximations to hard optimization problems.",rajgopal kannan,price of anarchy.,2012.0,10.1109/TC.2011.145,IEEE Transactions on Computers,Busch2012,False,,IEEE,Not available,Approximating Congestion + Dilation in Networks via &amp;#x0022;Quality of Routing&amp;amp;#x201D; Games,9915f48a2e9721b4a32e0a807083d647,https://ieeexplore.ieee.org/document/5963649/
10894,"A classic optimization problem in network routing is to minimize C + D, where C is the maximum edge congestion and D is the maximum path length (also known as dilation). The problem of computing the optimal C* + D* is NP-complete even when either C* or D* is a small constant. We study routing games in general networks where each player i selfishly selects a path that minimizes C&lt;sub&gt;i&lt;/sub&gt; + D&lt;sub&gt;i&lt;/sub&gt; the sum of congestion and dilation of the player's path. We first show that there are instances of this game without Nash equilibria. We then turn to the related quality of routing (QoR) games which always have Nash equilibria. QoR games represent networks with a small number of service classes where paths in different classes do not interfere with each other (with frequency or time division multiplexing). QoR games have O(log&lt;sup&gt;4&lt;/sup&gt; n) price of anarchy when either C* or D* is a constant. Thus, Nash equilibria of QoR games give poly-log approximations to hard optimization problems.",athanasios vasilakos,Algorithmic game theory,2012.0,10.1109/TC.2011.145,IEEE Transactions on Computers,Busch2012,False,,IEEE,Not available,Approximating Congestion + Dilation in Networks via &amp;#x0022;Quality of Routing&amp;amp;#x201D; Games,9915f48a2e9721b4a32e0a807083d647,https://ieeexplore.ieee.org/document/5963649/
10895,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
10896,"A classic optimization problem in network routing is to minimize C + D, where C is the maximum edge congestion and D is the maximum path length (also known as dilation). The problem of computing the optimal C* + D* is NP-complete even when either C* or D* is a small constant. We study routing games in general networks where each player i selfishly selects a path that minimizes C&lt;sub&gt;i&lt;/sub&gt; + D&lt;sub&gt;i&lt;/sub&gt; the sum of congestion and dilation of the player's path. We first show that there are instances of this game without Nash equilibria. We then turn to the related quality of routing (QoR) games which always have Nash equilibria. QoR games represent networks with a small number of service classes where paths in different classes do not interfere with each other (with frequency or time division multiplexing). QoR games have O(log&lt;sup&gt;4&lt;/sup&gt; n) price of anarchy when either C* or D* is a constant. Thus, Nash equilibria of QoR games give poly-log approximations to hard optimization problems.",athanasios vasilakos,congestion game,2012.0,10.1109/TC.2011.145,IEEE Transactions on Computers,Busch2012,False,,IEEE,Not available,Approximating Congestion + Dilation in Networks via &amp;#x0022;Quality of Routing&amp;amp;#x201D; Games,9915f48a2e9721b4a32e0a807083d647,https://ieeexplore.ieee.org/document/5963649/
10897,"A classic optimization problem in network routing is to minimize C + D, where C is the maximum edge congestion and D is the maximum path length (also known as dilation). The problem of computing the optimal C* + D* is NP-complete even when either C* or D* is a small constant. We study routing games in general networks where each player i selfishly selects a path that minimizes C&lt;sub&gt;i&lt;/sub&gt; + D&lt;sub&gt;i&lt;/sub&gt; the sum of congestion and dilation of the player's path. We first show that there are instances of this game without Nash equilibria. We then turn to the related quality of routing (QoR) games which always have Nash equilibria. QoR games represent networks with a small number of service classes where paths in different classes do not interfere with each other (with frequency or time division multiplexing). QoR games have O(log&lt;sup&gt;4&lt;/sup&gt; n) price of anarchy when either C* or D* is a constant. Thus, Nash equilibria of QoR games give poly-log approximations to hard optimization problems.",athanasios vasilakos,routing game,2012.0,10.1109/TC.2011.145,IEEE Transactions on Computers,Busch2012,False,,IEEE,Not available,Approximating Congestion + Dilation in Networks via &amp;#x0022;Quality of Routing&amp;amp;#x201D; Games,9915f48a2e9721b4a32e0a807083d647,https://ieeexplore.ieee.org/document/5963649/
10898,"A classic optimization problem in network routing is to minimize C + D, where C is the maximum edge congestion and D is the maximum path length (also known as dilation). The problem of computing the optimal C* + D* is NP-complete even when either C* or D* is a small constant. We study routing games in general networks where each player i selfishly selects a path that minimizes C&lt;sub&gt;i&lt;/sub&gt; + D&lt;sub&gt;i&lt;/sub&gt; the sum of congestion and dilation of the player's path. We first show that there are instances of this game without Nash equilibria. We then turn to the related quality of routing (QoR) games which always have Nash equilibria. QoR games represent networks with a small number of service classes where paths in different classes do not interfere with each other (with frequency or time division multiplexing). QoR games have O(log&lt;sup&gt;4&lt;/sup&gt; n) price of anarchy when either C* or D* is a constant. Thus, Nash equilibria of QoR games give poly-log approximations to hard optimization problems.",athanasios vasilakos,Nash equilibrium,2012.0,10.1109/TC.2011.145,IEEE Transactions on Computers,Busch2012,False,,IEEE,Not available,Approximating Congestion + Dilation in Networks via &amp;#x0022;Quality of Routing&amp;amp;#x201D; Games,9915f48a2e9721b4a32e0a807083d647,https://ieeexplore.ieee.org/document/5963649/
10899,"A classic optimization problem in network routing is to minimize C + D, where C is the maximum edge congestion and D is the maximum path length (also known as dilation). The problem of computing the optimal C* + D* is NP-complete even when either C* or D* is a small constant. We study routing games in general networks where each player i selfishly selects a path that minimizes C&lt;sub&gt;i&lt;/sub&gt; + D&lt;sub&gt;i&lt;/sub&gt; the sum of congestion and dilation of the player's path. We first show that there are instances of this game without Nash equilibria. We then turn to the related quality of routing (QoR) games which always have Nash equilibria. QoR games represent networks with a small number of service classes where paths in different classes do not interfere with each other (with frequency or time division multiplexing). QoR games have O(log&lt;sup&gt;4&lt;/sup&gt; n) price of anarchy when either C* or D* is a constant. Thus, Nash equilibria of QoR games give poly-log approximations to hard optimization problems.",athanasios vasilakos,price of anarchy.,2012.0,10.1109/TC.2011.145,IEEE Transactions on Computers,Busch2012,False,,IEEE,Not available,Approximating Congestion + Dilation in Networks via &amp;#x0022;Quality of Routing&amp;amp;#x201D; Games,9915f48a2e9721b4a32e0a807083d647,https://ieeexplore.ieee.org/document/5963649/
10900,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",mehdi soorki,5G cellular network,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
10901,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",mehdi soorki,virtual MIMO,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
10902,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",mehdi soorki,D2D relaying,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
10903,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",mehdi soorki,coalitional game,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
10904,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",mehdi soorki,mechanism design,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
10905,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",mohammad manshaei,5G cellular network,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
10906,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
10907,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",mohammad manshaei,virtual MIMO,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
10908,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",mohammad manshaei,D2D relaying,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
10909,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",mohammad manshaei,coalitional game,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
10910,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",mohammad manshaei,mechanism design,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
10911,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",behrouz maham,5G cellular network,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
10912,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",behrouz maham,virtual MIMO,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
10913,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",behrouz maham,D2D relaying,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
10914,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",behrouz maham,coalitional game,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
10915,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",behrouz maham,mechanism design,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
10916,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",hossein saidi,5G cellular network,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
10917,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
10918,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",hossein saidi,virtual MIMO,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
10919,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",hossein saidi,D2D relaying,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
10920,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",hossein saidi,coalitional game,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
10921,"In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others' data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs' data.",hossein saidi,mechanism design,2018.0,10.1109/TMC.2017.2707540,IEEE Transactions on Mobile Computing,Soorki2018,False,,IEEE,Not available,On Uplink Virtual MIMO with Device Relaying Cooperation Enforcement in 5G Networks,a3a6187171a16cc40374e3d58fefaf3d,https://ieeexplore.ieee.org/document/7933233/
10922,"Secondary users sharing primary users' spectrum is modeled as a graphical game. Users located in random graphs and a regular lattice are considered. Secondary users are assumed to differentiate the ``quality"" of the primary spectrum while interacting within their local neighborhood to minimize interference and congestion. The learning algorithm is also shown to be effective in punishing malicious users that violate spectrum etiquettes. An equivalence between spectrum sharing neighborhood interaction and the spin-glass model in statistical physics is established. A distributed exponential learning algorithm is used to arrive at an evolutionary stable solution to the game. Some theoretical properties of the system are studied and simulation results are presented to illustrate price of anarchy, convergence of the learning algorithm and asymptotic invariance of the system performance with respect to spectrum quality.",mahdi azarafrooz,Games,2011.0,10.1109/GLOCOM.2011.6134250,2011 IEEE Global Telecommunications Conference - GLOBECOM 2011,Azarafrooz2011,False,,IEEE,Not available,Distributed Learning in Secondary Spectrum Sharing Graphical Game,011fb578d25e9aa0ee215c044b67b2cf,https://ieeexplore.ieee.org/document/6134250/
10923,"Secondary users sharing primary users' spectrum is modeled as a graphical game. Users located in random graphs and a regular lattice are considered. Secondary users are assumed to differentiate the ``quality"" of the primary spectrum while interacting within their local neighborhood to minimize interference and congestion. The learning algorithm is also shown to be effective in punishing malicious users that violate spectrum etiquettes. An equivalence between spectrum sharing neighborhood interaction and the spin-glass model in statistical physics is established. A distributed exponential learning algorithm is used to arrive at an evolutionary stable solution to the game. Some theoretical properties of the system are studied and simulation results are presented to illustrate price of anarchy, convergence of the learning algorithm and asymptotic invariance of the system performance with respect to spectrum quality.",mahdi azarafrooz,Peer to peer computing,2011.0,10.1109/GLOCOM.2011.6134250,2011 IEEE Global Telecommunications Conference - GLOBECOM 2011,Azarafrooz2011,False,,IEEE,Not available,Distributed Learning in Secondary Spectrum Sharing Graphical Game,011fb578d25e9aa0ee215c044b67b2cf,https://ieeexplore.ieee.org/document/6134250/
10924,"Secondary users sharing primary users' spectrum is modeled as a graphical game. Users located in random graphs and a regular lattice are considered. Secondary users are assumed to differentiate the ``quality"" of the primary spectrum while interacting within their local neighborhood to minimize interference and congestion. The learning algorithm is also shown to be effective in punishing malicious users that violate spectrum etiquettes. An equivalence between spectrum sharing neighborhood interaction and the spin-glass model in statistical physics is established. A distributed exponential learning algorithm is used to arrive at an evolutionary stable solution to the game. Some theoretical properties of the system are studied and simulation results are presented to illustrate price of anarchy, convergence of the learning algorithm and asymptotic invariance of the system performance with respect to spectrum quality.",mahdi azarafrooz,Switches,2011.0,10.1109/GLOCOM.2011.6134250,2011 IEEE Global Telecommunications Conference - GLOBECOM 2011,Azarafrooz2011,False,,IEEE,Not available,Distributed Learning in Secondary Spectrum Sharing Graphical Game,011fb578d25e9aa0ee215c044b67b2cf,https://ieeexplore.ieee.org/document/6134250/
10925,"Secondary users sharing primary users' spectrum is modeled as a graphical game. Users located in random graphs and a regular lattice are considered. Secondary users are assumed to differentiate the ``quality"" of the primary spectrum while interacting within their local neighborhood to minimize interference and congestion. The learning algorithm is also shown to be effective in punishing malicious users that violate spectrum etiquettes. An equivalence between spectrum sharing neighborhood interaction and the spin-glass model in statistical physics is established. A distributed exponential learning algorithm is used to arrive at an evolutionary stable solution to the game. Some theoretical properties of the system are studied and simulation results are presented to illustrate price of anarchy, convergence of the learning algorithm and asymptotic invariance of the system performance with respect to spectrum quality.",mahdi azarafrooz,Interference,2011.0,10.1109/GLOCOM.2011.6134250,2011 IEEE Global Telecommunications Conference - GLOBECOM 2011,Azarafrooz2011,False,,IEEE,Not available,Distributed Learning in Secondary Spectrum Sharing Graphical Game,011fb578d25e9aa0ee215c044b67b2cf,https://ieeexplore.ieee.org/document/6134250/
10926,"Secondary users sharing primary users' spectrum is modeled as a graphical game. Users located in random graphs and a regular lattice are considered. Secondary users are assumed to differentiate the ``quality"" of the primary spectrum while interacting within their local neighborhood to minimize interference and congestion. The learning algorithm is also shown to be effective in punishing malicious users that violate spectrum etiquettes. An equivalence between spectrum sharing neighborhood interaction and the spin-glass model in statistical physics is established. A distributed exponential learning algorithm is used to arrive at an evolutionary stable solution to the game. Some theoretical properties of the system are studied and simulation results are presented to illustrate price of anarchy, convergence of the learning algorithm and asymptotic invariance of the system performance with respect to spectrum quality.",mahdi azarafrooz,Indexes,2011.0,10.1109/GLOCOM.2011.6134250,2011 IEEE Global Telecommunications Conference - GLOBECOM 2011,Azarafrooz2011,False,,IEEE,Not available,Distributed Learning in Secondary Spectrum Sharing Graphical Game,011fb578d25e9aa0ee215c044b67b2cf,https://ieeexplore.ieee.org/document/6134250/
10927,"Secondary users sharing primary users' spectrum is modeled as a graphical game. Users located in random graphs and a regular lattice are considered. Secondary users are assumed to differentiate the ``quality"" of the primary spectrum while interacting within their local neighborhood to minimize interference and congestion. The learning algorithm is also shown to be effective in punishing malicious users that violate spectrum etiquettes. An equivalence between spectrum sharing neighborhood interaction and the spin-glass model in statistical physics is established. A distributed exponential learning algorithm is used to arrive at an evolutionary stable solution to the game. Some theoretical properties of the system are studied and simulation results are presented to illustrate price of anarchy, convergence of the learning algorithm and asymptotic invariance of the system performance with respect to spectrum quality.",mahdi azarafrooz,IEEE Communications Society,2011.0,10.1109/GLOCOM.2011.6134250,2011 IEEE Global Telecommunications Conference - GLOBECOM 2011,Azarafrooz2011,False,,IEEE,Not available,Distributed Learning in Secondary Spectrum Sharing Graphical Game,011fb578d25e9aa0ee215c044b67b2cf,https://ieeexplore.ieee.org/document/6134250/
10928,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
10929,"Secondary users sharing primary users' spectrum is modeled as a graphical game. Users located in random graphs and a regular lattice are considered. Secondary users are assumed to differentiate the ``quality"" of the primary spectrum while interacting within their local neighborhood to minimize interference and congestion. The learning algorithm is also shown to be effective in punishing malicious users that violate spectrum etiquettes. An equivalence between spectrum sharing neighborhood interaction and the spin-glass model in statistical physics is established. A distributed exponential learning algorithm is used to arrive at an evolutionary stable solution to the game. Some theoretical properties of the system are studied and simulation results are presented to illustrate price of anarchy, convergence of the learning algorithm and asymptotic invariance of the system performance with respect to spectrum quality.",mahdi azarafrooz,Nash equilibrium,2011.0,10.1109/GLOCOM.2011.6134250,2011 IEEE Global Telecommunications Conference - GLOBECOM 2011,Azarafrooz2011,False,,IEEE,Not available,Distributed Learning in Secondary Spectrum Sharing Graphical Game,011fb578d25e9aa0ee215c044b67b2cf,https://ieeexplore.ieee.org/document/6134250/
10930,"Secondary users sharing primary users' spectrum is modeled as a graphical game. Users located in random graphs and a regular lattice are considered. Secondary users are assumed to differentiate the ``quality"" of the primary spectrum while interacting within their local neighborhood to minimize interference and congestion. The learning algorithm is also shown to be effective in punishing malicious users that violate spectrum etiquettes. An equivalence between spectrum sharing neighborhood interaction and the spin-glass model in statistical physics is established. A distributed exponential learning algorithm is used to arrive at an evolutionary stable solution to the game. Some theoretical properties of the system are studied and simulation results are presented to illustrate price of anarchy, convergence of the learning algorithm and asymptotic invariance of the system performance with respect to spectrum quality.",r. chandramouli,Games,2011.0,10.1109/GLOCOM.2011.6134250,2011 IEEE Global Telecommunications Conference - GLOBECOM 2011,Azarafrooz2011,False,,IEEE,Not available,Distributed Learning in Secondary Spectrum Sharing Graphical Game,011fb578d25e9aa0ee215c044b67b2cf,https://ieeexplore.ieee.org/document/6134250/
10931,"Secondary users sharing primary users' spectrum is modeled as a graphical game. Users located in random graphs and a regular lattice are considered. Secondary users are assumed to differentiate the ``quality"" of the primary spectrum while interacting within their local neighborhood to minimize interference and congestion. The learning algorithm is also shown to be effective in punishing malicious users that violate spectrum etiquettes. An equivalence between spectrum sharing neighborhood interaction and the spin-glass model in statistical physics is established. A distributed exponential learning algorithm is used to arrive at an evolutionary stable solution to the game. Some theoretical properties of the system are studied and simulation results are presented to illustrate price of anarchy, convergence of the learning algorithm and asymptotic invariance of the system performance with respect to spectrum quality.",r. chandramouli,Peer to peer computing,2011.0,10.1109/GLOCOM.2011.6134250,2011 IEEE Global Telecommunications Conference - GLOBECOM 2011,Azarafrooz2011,False,,IEEE,Not available,Distributed Learning in Secondary Spectrum Sharing Graphical Game,011fb578d25e9aa0ee215c044b67b2cf,https://ieeexplore.ieee.org/document/6134250/
10932,"Secondary users sharing primary users' spectrum is modeled as a graphical game. Users located in random graphs and a regular lattice are considered. Secondary users are assumed to differentiate the ``quality"" of the primary spectrum while interacting within their local neighborhood to minimize interference and congestion. The learning algorithm is also shown to be effective in punishing malicious users that violate spectrum etiquettes. An equivalence between spectrum sharing neighborhood interaction and the spin-glass model in statistical physics is established. A distributed exponential learning algorithm is used to arrive at an evolutionary stable solution to the game. Some theoretical properties of the system are studied and simulation results are presented to illustrate price of anarchy, convergence of the learning algorithm and asymptotic invariance of the system performance with respect to spectrum quality.",r. chandramouli,Switches,2011.0,10.1109/GLOCOM.2011.6134250,2011 IEEE Global Telecommunications Conference - GLOBECOM 2011,Azarafrooz2011,False,,IEEE,Not available,Distributed Learning in Secondary Spectrum Sharing Graphical Game,011fb578d25e9aa0ee215c044b67b2cf,https://ieeexplore.ieee.org/document/6134250/
10933,"Secondary users sharing primary users' spectrum is modeled as a graphical game. Users located in random graphs and a regular lattice are considered. Secondary users are assumed to differentiate the ``quality"" of the primary spectrum while interacting within their local neighborhood to minimize interference and congestion. The learning algorithm is also shown to be effective in punishing malicious users that violate spectrum etiquettes. An equivalence between spectrum sharing neighborhood interaction and the spin-glass model in statistical physics is established. A distributed exponential learning algorithm is used to arrive at an evolutionary stable solution to the game. Some theoretical properties of the system are studied and simulation results are presented to illustrate price of anarchy, convergence of the learning algorithm and asymptotic invariance of the system performance with respect to spectrum quality.",r. chandramouli,Interference,2011.0,10.1109/GLOCOM.2011.6134250,2011 IEEE Global Telecommunications Conference - GLOBECOM 2011,Azarafrooz2011,False,,IEEE,Not available,Distributed Learning in Secondary Spectrum Sharing Graphical Game,011fb578d25e9aa0ee215c044b67b2cf,https://ieeexplore.ieee.org/document/6134250/
10934,"Secondary users sharing primary users' spectrum is modeled as a graphical game. Users located in random graphs and a regular lattice are considered. Secondary users are assumed to differentiate the ``quality"" of the primary spectrum while interacting within their local neighborhood to minimize interference and congestion. The learning algorithm is also shown to be effective in punishing malicious users that violate spectrum etiquettes. An equivalence between spectrum sharing neighborhood interaction and the spin-glass model in statistical physics is established. A distributed exponential learning algorithm is used to arrive at an evolutionary stable solution to the game. Some theoretical properties of the system are studied and simulation results are presented to illustrate price of anarchy, convergence of the learning algorithm and asymptotic invariance of the system performance with respect to spectrum quality.",r. chandramouli,Indexes,2011.0,10.1109/GLOCOM.2011.6134250,2011 IEEE Global Telecommunications Conference - GLOBECOM 2011,Azarafrooz2011,False,,IEEE,Not available,Distributed Learning in Secondary Spectrum Sharing Graphical Game,011fb578d25e9aa0ee215c044b67b2cf,https://ieeexplore.ieee.org/document/6134250/
10935,"Secondary users sharing primary users' spectrum is modeled as a graphical game. Users located in random graphs and a regular lattice are considered. Secondary users are assumed to differentiate the ``quality"" of the primary spectrum while interacting within their local neighborhood to minimize interference and congestion. The learning algorithm is also shown to be effective in punishing malicious users that violate spectrum etiquettes. An equivalence between spectrum sharing neighborhood interaction and the spin-glass model in statistical physics is established. A distributed exponential learning algorithm is used to arrive at an evolutionary stable solution to the game. Some theoretical properties of the system are studied and simulation results are presented to illustrate price of anarchy, convergence of the learning algorithm and asymptotic invariance of the system performance with respect to spectrum quality.",r. chandramouli,IEEE Communications Society,2011.0,10.1109/GLOCOM.2011.6134250,2011 IEEE Global Telecommunications Conference - GLOBECOM 2011,Azarafrooz2011,False,,IEEE,Not available,Distributed Learning in Secondary Spectrum Sharing Graphical Game,011fb578d25e9aa0ee215c044b67b2cf,https://ieeexplore.ieee.org/document/6134250/
10936,"Secondary users sharing primary users' spectrum is modeled as a graphical game. Users located in random graphs and a regular lattice are considered. Secondary users are assumed to differentiate the ``quality"" of the primary spectrum while interacting within their local neighborhood to minimize interference and congestion. The learning algorithm is also shown to be effective in punishing malicious users that violate spectrum etiquettes. An equivalence between spectrum sharing neighborhood interaction and the spin-glass model in statistical physics is established. A distributed exponential learning algorithm is used to arrive at an evolutionary stable solution to the game. Some theoretical properties of the system are studied and simulation results are presented to illustrate price of anarchy, convergence of the learning algorithm and asymptotic invariance of the system performance with respect to spectrum quality.",r. chandramouli,Nash equilibrium,2011.0,10.1109/GLOCOM.2011.6134250,2011 IEEE Global Telecommunications Conference - GLOBECOM 2011,Azarafrooz2011,False,,IEEE,Not available,Distributed Learning in Secondary Spectrum Sharing Graphical Game,011fb578d25e9aa0ee215c044b67b2cf,https://ieeexplore.ieee.org/document/6134250/
10937,"We formulate two coordination mechanisms between local and centralized electricity markets. The first one is a centralized mechanism ruled by the national market operator and formulated as a standard constrained optimization problem. The second one is a decentralized mechanism, governed by local market operators that interact with a central market operator. In both cases, conventional generators submit block quantity offers subject to inter-temporal constraints while anticipating the outcome of the market clearing(s). The decentralized coordination mechanism can be interpreted as a Stackelberg game that we formulate as a bilevel mathematical programming problem. We prove that in case of simple bids, the Stackelberg game admits a unique subgame perfect Nash equilibrium and extend this result to block quantity offers using Complementarity Theory. Through a case study we determine that the decentralized design is as efficient as the centralized one with high shares of renewables, using the Price of Anarchy as performance measure, and that imperfect information has a limited impact on the performance of the decentralized market design.",helene cadre,Games,2017.0,10.1109/EEM.2017.7981863,2017 14th International Conference on the European Energy Market (EEM),Cadre2017,False,,IEEE,Not available,On the efficiency of local electricity markets,cdf6c470b7a6dcbb5a40035d43ed02f6,https://ieeexplore.ieee.org/document/7981863/
10938,"We formulate two coordination mechanisms between local and centralized electricity markets. The first one is a centralized mechanism ruled by the national market operator and formulated as a standard constrained optimization problem. The second one is a decentralized mechanism, governed by local market operators that interact with a central market operator. In both cases, conventional generators submit block quantity offers subject to inter-temporal constraints while anticipating the outcome of the market clearing(s). The decentralized coordination mechanism can be interpreted as a Stackelberg game that we formulate as a bilevel mathematical programming problem. We prove that in case of simple bids, the Stackelberg game admits a unique subgame perfect Nash equilibrium and extend this result to block quantity offers using Complementarity Theory. Through a case study we determine that the decentralized design is as efficient as the centralized one with high shares of renewables, using the Price of Anarchy as performance measure, and that imperfect information has a limited impact on the performance of the decentralized market design.",helene cadre,Generators,2017.0,10.1109/EEM.2017.7981863,2017 14th International Conference on the European Energy Market (EEM),Cadre2017,False,,IEEE,Not available,On the efficiency of local electricity markets,cdf6c470b7a6dcbb5a40035d43ed02f6,https://ieeexplore.ieee.org/document/7981863/
10939,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
10940,"We formulate two coordination mechanisms between local and centralized electricity markets. The first one is a centralized mechanism ruled by the national market operator and formulated as a standard constrained optimization problem. The second one is a decentralized mechanism, governed by local market operators that interact with a central market operator. In both cases, conventional generators submit block quantity offers subject to inter-temporal constraints while anticipating the outcome of the market clearing(s). The decentralized coordination mechanism can be interpreted as a Stackelberg game that we formulate as a bilevel mathematical programming problem. We prove that in case of simple bids, the Stackelberg game admits a unique subgame perfect Nash equilibrium and extend this result to block quantity offers using Complementarity Theory. Through a case study we determine that the decentralized design is as efficient as the centralized one with high shares of renewables, using the Price of Anarchy as performance measure, and that imperfect information has a limited impact on the performance of the decentralized market design.",helene cadre,Mathematical model,2017.0,10.1109/EEM.2017.7981863,2017 14th International Conference on the European Energy Market (EEM),Cadre2017,False,,IEEE,Not available,On the efficiency of local electricity markets,cdf6c470b7a6dcbb5a40035d43ed02f6,https://ieeexplore.ieee.org/document/7981863/
10941,"We formulate two coordination mechanisms between local and centralized electricity markets. The first one is a centralized mechanism ruled by the national market operator and formulated as a standard constrained optimization problem. The second one is a decentralized mechanism, governed by local market operators that interact with a central market operator. In both cases, conventional generators submit block quantity offers subject to inter-temporal constraints while anticipating the outcome of the market clearing(s). The decentralized coordination mechanism can be interpreted as a Stackelberg game that we formulate as a bilevel mathematical programming problem. We prove that in case of simple bids, the Stackelberg game admits a unique subgame perfect Nash equilibrium and extend this result to block quantity offers using Complementarity Theory. Through a case study we determine that the decentralized design is as efficient as the centralized one with high shares of renewables, using the Price of Anarchy as performance measure, and that imperfect information has a limited impact on the performance of the decentralized market design.",helene cadre,Electricity supply industry,2017.0,10.1109/EEM.2017.7981863,2017 14th International Conference on the European Energy Market (EEM),Cadre2017,False,,IEEE,Not available,On the efficiency of local electricity markets,cdf6c470b7a6dcbb5a40035d43ed02f6,https://ieeexplore.ieee.org/document/7981863/
10942,"We formulate two coordination mechanisms between local and centralized electricity markets. The first one is a centralized mechanism ruled by the national market operator and formulated as a standard constrained optimization problem. The second one is a decentralized mechanism, governed by local market operators that interact with a central market operator. In both cases, conventional generators submit block quantity offers subject to inter-temporal constraints while anticipating the outcome of the market clearing(s). The decentralized coordination mechanism can be interpreted as a Stackelberg game that we formulate as a bilevel mathematical programming problem. We prove that in case of simple bids, the Stackelberg game admits a unique subgame perfect Nash equilibrium and extend this result to block quantity offers using Complementarity Theory. Through a case study we determine that the decentralized design is as efficient as the centralized one with high shares of renewables, using the Price of Anarchy as performance measure, and that imperfect information has a limited impact on the performance of the decentralized market design.",helene cadre,Standards,2017.0,10.1109/EEM.2017.7981863,2017 14th International Conference on the European Energy Market (EEM),Cadre2017,False,,IEEE,Not available,On the efficiency of local electricity markets,cdf6c470b7a6dcbb5a40035d43ed02f6,https://ieeexplore.ieee.org/document/7981863/
10943,"We formulate two coordination mechanisms between local and centralized electricity markets. The first one is a centralized mechanism ruled by the national market operator and formulated as a standard constrained optimization problem. The second one is a decentralized mechanism, governed by local market operators that interact with a central market operator. In both cases, conventional generators submit block quantity offers subject to inter-temporal constraints while anticipating the outcome of the market clearing(s). The decentralized coordination mechanism can be interpreted as a Stackelberg game that we formulate as a bilevel mathematical programming problem. We prove that in case of simple bids, the Stackelberg game admits a unique subgame perfect Nash equilibrium and extend this result to block quantity offers using Complementarity Theory. Through a case study we determine that the decentralized design is as efficient as the centralized one with high shares of renewables, using the Price of Anarchy as performance measure, and that imperfect information has a limited impact on the performance of the decentralized market design.",helene cadre,Mathematical programming,2017.0,10.1109/EEM.2017.7981863,2017 14th International Conference on the European Energy Market (EEM),Cadre2017,False,,IEEE,Not available,On the efficiency of local electricity markets,cdf6c470b7a6dcbb5a40035d43ed02f6,https://ieeexplore.ieee.org/document/7981863/
10944,"This paper studies the problem of non-cooperative joint channel and bandwidth allocations in multi-radio multichannel wireless networks. Existing works only studied non-cooperative multi-radio channel allocation and they did not consider two important issues, impact of traffic load to channel's transmission quality, and difference of bandwidth demands for different node pairs, which may have significant impact on the modeling and designing solutions. To address these two issues, we extend the problem of non-cooperative multi-radio channel allocation to Non-cooperative Joint Channel and Bandwidth Allocation problem (NJCBA). In the NJCBA problem, node pairs need to consider not only allocating radios to channels, but also allocating bandwidth to selected channels to maximize its own benefit. To the best of our knowledge, we are the first to study the NJCBA problem in multi-radio multi-channel wireless networks. We model the problem as a non-cooperative game, denoted by NJCBA game. Using the best response concept, we prove that there exist pure Nash Equilibriums (NEs) for the NJCBA game, which means that NJCBA can converge to a stable state. We also analyze the efficiency of the NEs for NJCBA game, and prove that these NEs can achieve a constant Price Of Anarchy (POA) in the heavy-load network. Here, POA denotes the ratio between the sum of the payoffs of all players in a globally optimal solution and the sum of the payoffs achieved in a worst-case NE. We design a distributed algorithm, denoted by NE Convergence (NEC) algorithm, to enable node pairs to converge to a pure NE. The NEC algorithm is evaluated through extensive simulations. The results show that NEC algorithms can improve the system throughput by 2 or 3 times compared with a greedy allocation algorithm.",wei feng,Game Theory,2011.0,10.1109/WCNC.2011.5779215,2011 IEEE Wireless Communications and Networking Conference,Feng2011,False,,IEEE,Not available,Non-cooperative quality-aware channel and bandwidth allocations in multi-radio multi-channel wireless networks,410b0604f9b53b68d708418580b5fa3f,https://ieeexplore.ieee.org/document/5779215/
10945,"This paper studies the problem of non-cooperative joint channel and bandwidth allocations in multi-radio multichannel wireless networks. Existing works only studied non-cooperative multi-radio channel allocation and they did not consider two important issues, impact of traffic load to channel's transmission quality, and difference of bandwidth demands for different node pairs, which may have significant impact on the modeling and designing solutions. To address these two issues, we extend the problem of non-cooperative multi-radio channel allocation to Non-cooperative Joint Channel and Bandwidth Allocation problem (NJCBA). In the NJCBA problem, node pairs need to consider not only allocating radios to channels, but also allocating bandwidth to selected channels to maximize its own benefit. To the best of our knowledge, we are the first to study the NJCBA problem in multi-radio multi-channel wireless networks. We model the problem as a non-cooperative game, denoted by NJCBA game. Using the best response concept, we prove that there exist pure Nash Equilibriums (NEs) for the NJCBA game, which means that NJCBA can converge to a stable state. We also analyze the efficiency of the NEs for NJCBA game, and prove that these NEs can achieve a constant Price Of Anarchy (POA) in the heavy-load network. Here, POA denotes the ratio between the sum of the payoffs of all players in a globally optimal solution and the sum of the payoffs achieved in a worst-case NE. We design a distributed algorithm, denoted by NE Convergence (NEC) algorithm, to enable node pairs to converge to a pure NE. The NEC algorithm is evaluated through extensive simulations. The results show that NEC algorithms can improve the system throughput by 2 or 3 times compared with a greedy allocation algorithm.",wei feng,Channel and Bandwidth Allocaiton,2011.0,10.1109/WCNC.2011.5779215,2011 IEEE Wireless Communications and Networking Conference,Feng2011,False,,IEEE,Not available,Non-cooperative quality-aware channel and bandwidth allocations in multi-radio multi-channel wireless networks,410b0604f9b53b68d708418580b5fa3f,https://ieeexplore.ieee.org/document/5779215/
10946,"This paper studies the problem of non-cooperative joint channel and bandwidth allocations in multi-radio multichannel wireless networks. Existing works only studied non-cooperative multi-radio channel allocation and they did not consider two important issues, impact of traffic load to channel's transmission quality, and difference of bandwidth demands for different node pairs, which may have significant impact on the modeling and designing solutions. To address these two issues, we extend the problem of non-cooperative multi-radio channel allocation to Non-cooperative Joint Channel and Bandwidth Allocation problem (NJCBA). In the NJCBA problem, node pairs need to consider not only allocating radios to channels, but also allocating bandwidth to selected channels to maximize its own benefit. To the best of our knowledge, we are the first to study the NJCBA problem in multi-radio multi-channel wireless networks. We model the problem as a non-cooperative game, denoted by NJCBA game. Using the best response concept, we prove that there exist pure Nash Equilibriums (NEs) for the NJCBA game, which means that NJCBA can converge to a stable state. We also analyze the efficiency of the NEs for NJCBA game, and prove that these NEs can achieve a constant Price Of Anarchy (POA) in the heavy-load network. Here, POA denotes the ratio between the sum of the payoffs of all players in a globally optimal solution and the sum of the payoffs achieved in a worst-case NE. We design a distributed algorithm, denoted by NE Convergence (NEC) algorithm, to enable node pairs to converge to a pure NE. The NEC algorithm is evaluated through extensive simulations. The results show that NEC algorithms can improve the system throughput by 2 or 3 times compared with a greedy allocation algorithm.",wei feng,Multi-Radio Multi-Channel,2011.0,10.1109/WCNC.2011.5779215,2011 IEEE Wireless Communications and Networking Conference,Feng2011,False,,IEEE,Not available,Non-cooperative quality-aware channel and bandwidth allocations in multi-radio multi-channel wireless networks,410b0604f9b53b68d708418580b5fa3f,https://ieeexplore.ieee.org/document/5779215/
10947,"This paper studies the problem of non-cooperative joint channel and bandwidth allocations in multi-radio multichannel wireless networks. Existing works only studied non-cooperative multi-radio channel allocation and they did not consider two important issues, impact of traffic load to channel's transmission quality, and difference of bandwidth demands for different node pairs, which may have significant impact on the modeling and designing solutions. To address these two issues, we extend the problem of non-cooperative multi-radio channel allocation to Non-cooperative Joint Channel and Bandwidth Allocation problem (NJCBA). In the NJCBA problem, node pairs need to consider not only allocating radios to channels, but also allocating bandwidth to selected channels to maximize its own benefit. To the best of our knowledge, we are the first to study the NJCBA problem in multi-radio multi-channel wireless networks. We model the problem as a non-cooperative game, denoted by NJCBA game. Using the best response concept, we prove that there exist pure Nash Equilibriums (NEs) for the NJCBA game, which means that NJCBA can converge to a stable state. We also analyze the efficiency of the NEs for NJCBA game, and prove that these NEs can achieve a constant Price Of Anarchy (POA) in the heavy-load network. Here, POA denotes the ratio between the sum of the payoffs of all players in a globally optimal solution and the sum of the payoffs achieved in a worst-case NE. We design a distributed algorithm, denoted by NE Convergence (NEC) algorithm, to enable node pairs to converge to a pure NE. The NEC algorithm is evaluated through extensive simulations. The results show that NEC algorithms can improve the system throughput by 2 or 3 times compared with a greedy allocation algorithm.",jiannong cao,Game Theory,2011.0,10.1109/WCNC.2011.5779215,2011 IEEE Wireless Communications and Networking Conference,Feng2011,False,,IEEE,Not available,Non-cooperative quality-aware channel and bandwidth allocations in multi-radio multi-channel wireless networks,410b0604f9b53b68d708418580b5fa3f,https://ieeexplore.ieee.org/document/5779215/
10948,"This paper studies the problem of non-cooperative joint channel and bandwidth allocations in multi-radio multichannel wireless networks. Existing works only studied non-cooperative multi-radio channel allocation and they did not consider two important issues, impact of traffic load to channel's transmission quality, and difference of bandwidth demands for different node pairs, which may have significant impact on the modeling and designing solutions. To address these two issues, we extend the problem of non-cooperative multi-radio channel allocation to Non-cooperative Joint Channel and Bandwidth Allocation problem (NJCBA). In the NJCBA problem, node pairs need to consider not only allocating radios to channels, but also allocating bandwidth to selected channels to maximize its own benefit. To the best of our knowledge, we are the first to study the NJCBA problem in multi-radio multi-channel wireless networks. We model the problem as a non-cooperative game, denoted by NJCBA game. Using the best response concept, we prove that there exist pure Nash Equilibriums (NEs) for the NJCBA game, which means that NJCBA can converge to a stable state. We also analyze the efficiency of the NEs for NJCBA game, and prove that these NEs can achieve a constant Price Of Anarchy (POA) in the heavy-load network. Here, POA denotes the ratio between the sum of the payoffs of all players in a globally optimal solution and the sum of the payoffs achieved in a worst-case NE. We design a distributed algorithm, denoted by NE Convergence (NEC) algorithm, to enable node pairs to converge to a pure NE. The NEC algorithm is evaluated through extensive simulations. The results show that NEC algorithms can improve the system throughput by 2 or 3 times compared with a greedy allocation algorithm.",jiannong cao,Channel and Bandwidth Allocaiton,2011.0,10.1109/WCNC.2011.5779215,2011 IEEE Wireless Communications and Networking Conference,Feng2011,False,,IEEE,Not available,Non-cooperative quality-aware channel and bandwidth allocations in multi-radio multi-channel wireless networks,410b0604f9b53b68d708418580b5fa3f,https://ieeexplore.ieee.org/document/5779215/
10949,"This paper studies the problem of non-cooperative joint channel and bandwidth allocations in multi-radio multichannel wireless networks. Existing works only studied non-cooperative multi-radio channel allocation and they did not consider two important issues, impact of traffic load to channel's transmission quality, and difference of bandwidth demands for different node pairs, which may have significant impact on the modeling and designing solutions. To address these two issues, we extend the problem of non-cooperative multi-radio channel allocation to Non-cooperative Joint Channel and Bandwidth Allocation problem (NJCBA). In the NJCBA problem, node pairs need to consider not only allocating radios to channels, but also allocating bandwidth to selected channels to maximize its own benefit. To the best of our knowledge, we are the first to study the NJCBA problem in multi-radio multi-channel wireless networks. We model the problem as a non-cooperative game, denoted by NJCBA game. Using the best response concept, we prove that there exist pure Nash Equilibriums (NEs) for the NJCBA game, which means that NJCBA can converge to a stable state. We also analyze the efficiency of the NEs for NJCBA game, and prove that these NEs can achieve a constant Price Of Anarchy (POA) in the heavy-load network. Here, POA denotes the ratio between the sum of the payoffs of all players in a globally optimal solution and the sum of the payoffs achieved in a worst-case NE. We design a distributed algorithm, denoted by NE Convergence (NEC) algorithm, to enable node pairs to converge to a pure NE. The NEC algorithm is evaluated through extensive simulations. The results show that NEC algorithms can improve the system throughput by 2 or 3 times compared with a greedy allocation algorithm.",jiannong cao,Multi-Radio Multi-Channel,2011.0,10.1109/WCNC.2011.5779215,2011 IEEE Wireless Communications and Networking Conference,Feng2011,False,,IEEE,Not available,Non-cooperative quality-aware channel and bandwidth allocations in multi-radio multi-channel wireless networks,410b0604f9b53b68d708418580b5fa3f,https://ieeexplore.ieee.org/document/5779215/
10950,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
10951,"This paper studies the problem of non-cooperative joint channel and bandwidth allocations in multi-radio multichannel wireless networks. Existing works only studied non-cooperative multi-radio channel allocation and they did not consider two important issues, impact of traffic load to channel's transmission quality, and difference of bandwidth demands for different node pairs, which may have significant impact on the modeling and designing solutions. To address these two issues, we extend the problem of non-cooperative multi-radio channel allocation to Non-cooperative Joint Channel and Bandwidth Allocation problem (NJCBA). In the NJCBA problem, node pairs need to consider not only allocating radios to channels, but also allocating bandwidth to selected channels to maximize its own benefit. To the best of our knowledge, we are the first to study the NJCBA problem in multi-radio multi-channel wireless networks. We model the problem as a non-cooperative game, denoted by NJCBA game. Using the best response concept, we prove that there exist pure Nash Equilibriums (NEs) for the NJCBA game, which means that NJCBA can converge to a stable state. We also analyze the efficiency of the NEs for NJCBA game, and prove that these NEs can achieve a constant Price Of Anarchy (POA) in the heavy-load network. Here, POA denotes the ratio between the sum of the payoffs of all players in a globally optimal solution and the sum of the payoffs achieved in a worst-case NE. We design a distributed algorithm, denoted by NE Convergence (NEC) algorithm, to enable node pairs to converge to a pure NE. The NEC algorithm is evaluated through extensive simulations. The results show that NEC algorithms can improve the system throughput by 2 or 3 times compared with a greedy allocation algorithm.",liang yang,Game Theory,2011.0,10.1109/WCNC.2011.5779215,2011 IEEE Wireless Communications and Networking Conference,Feng2011,False,,IEEE,Not available,Non-cooperative quality-aware channel and bandwidth allocations in multi-radio multi-channel wireless networks,410b0604f9b53b68d708418580b5fa3f,https://ieeexplore.ieee.org/document/5779215/
10952,"This paper studies the problem of non-cooperative joint channel and bandwidth allocations in multi-radio multichannel wireless networks. Existing works only studied non-cooperative multi-radio channel allocation and they did not consider two important issues, impact of traffic load to channel's transmission quality, and difference of bandwidth demands for different node pairs, which may have significant impact on the modeling and designing solutions. To address these two issues, we extend the problem of non-cooperative multi-radio channel allocation to Non-cooperative Joint Channel and Bandwidth Allocation problem (NJCBA). In the NJCBA problem, node pairs need to consider not only allocating radios to channels, but also allocating bandwidth to selected channels to maximize its own benefit. To the best of our knowledge, we are the first to study the NJCBA problem in multi-radio multi-channel wireless networks. We model the problem as a non-cooperative game, denoted by NJCBA game. Using the best response concept, we prove that there exist pure Nash Equilibriums (NEs) for the NJCBA game, which means that NJCBA can converge to a stable state. We also analyze the efficiency of the NEs for NJCBA game, and prove that these NEs can achieve a constant Price Of Anarchy (POA) in the heavy-load network. Here, POA denotes the ratio between the sum of the payoffs of all players in a globally optimal solution and the sum of the payoffs achieved in a worst-case NE. We design a distributed algorithm, denoted by NE Convergence (NEC) algorithm, to enable node pairs to converge to a pure NE. The NEC algorithm is evaluated through extensive simulations. The results show that NEC algorithms can improve the system throughput by 2 or 3 times compared with a greedy allocation algorithm.",liang yang,Channel and Bandwidth Allocaiton,2011.0,10.1109/WCNC.2011.5779215,2011 IEEE Wireless Communications and Networking Conference,Feng2011,False,,IEEE,Not available,Non-cooperative quality-aware channel and bandwidth allocations in multi-radio multi-channel wireless networks,410b0604f9b53b68d708418580b5fa3f,https://ieeexplore.ieee.org/document/5779215/
10953,"This paper studies the problem of non-cooperative joint channel and bandwidth allocations in multi-radio multichannel wireless networks. Existing works only studied non-cooperative multi-radio channel allocation and they did not consider two important issues, impact of traffic load to channel's transmission quality, and difference of bandwidth demands for different node pairs, which may have significant impact on the modeling and designing solutions. To address these two issues, we extend the problem of non-cooperative multi-radio channel allocation to Non-cooperative Joint Channel and Bandwidth Allocation problem (NJCBA). In the NJCBA problem, node pairs need to consider not only allocating radios to channels, but also allocating bandwidth to selected channels to maximize its own benefit. To the best of our knowledge, we are the first to study the NJCBA problem in multi-radio multi-channel wireless networks. We model the problem as a non-cooperative game, denoted by NJCBA game. Using the best response concept, we prove that there exist pure Nash Equilibriums (NEs) for the NJCBA game, which means that NJCBA can converge to a stable state. We also analyze the efficiency of the NEs for NJCBA game, and prove that these NEs can achieve a constant Price Of Anarchy (POA) in the heavy-load network. Here, POA denotes the ratio between the sum of the payoffs of all players in a globally optimal solution and the sum of the payoffs achieved in a worst-case NE. We design a distributed algorithm, denoted by NE Convergence (NEC) algorithm, to enable node pairs to converge to a pure NE. The NEC algorithm is evaluated through extensive simulations. The results show that NEC algorithms can improve the system throughput by 2 or 3 times compared with a greedy allocation algorithm.",liang yang,Multi-Radio Multi-Channel,2011.0,10.1109/WCNC.2011.5779215,2011 IEEE Wireless Communications and Networking Conference,Feng2011,False,,IEEE,Not available,Non-cooperative quality-aware channel and bandwidth allocations in multi-radio multi-channel wireless networks,410b0604f9b53b68d708418580b5fa3f,https://ieeexplore.ieee.org/document/5779215/
10954,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ahmed abdulla,Unmanned Aircraft System (UAS)-aided networks,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10955,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ahmed abdulla,energy efficiency,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10956,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ahmed abdulla,throughput per energy,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10957,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ahmed abdulla,fairness,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10958,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ahmed abdulla,adaptive modulation,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10959,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ahmed abdulla,game theory,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10960,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ahmed abdulla,wireless network optimization,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10961,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
10962,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",zubair fadlullah,Unmanned Aircraft System (UAS)-aided networks,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10963,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",zubair fadlullah,energy efficiency,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10964,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",zubair fadlullah,throughput per energy,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10965,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",zubair fadlullah,fairness,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10966,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",zubair fadlullah,adaptive modulation,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10967,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",zubair fadlullah,game theory,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10968,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",zubair fadlullah,wireless network optimization,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10969,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",hiroki nishiyama,Unmanned Aircraft System (UAS)-aided networks,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10970,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",hiroki nishiyama,energy efficiency,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10971,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",hiroki nishiyama,throughput per energy,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10972,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
10973,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",hiroki nishiyama,fairness,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10974,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",hiroki nishiyama,adaptive modulation,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10975,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",hiroki nishiyama,game theory,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10976,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",hiroki nishiyama,wireless network optimization,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10977,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",nei kato,Unmanned Aircraft System (UAS)-aided networks,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10978,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",nei kato,energy efficiency,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10979,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",nei kato,throughput per energy,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10980,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",nei kato,fairness,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10981,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",nei kato,adaptive modulation,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10982,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",nei kato,game theory,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10983,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
10984,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",nei kato,wireless network optimization,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10985,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",fumie ono,Unmanned Aircraft System (UAS)-aided networks,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10986,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",fumie ono,energy efficiency,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10987,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",fumie ono,throughput per energy,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10988,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",fumie ono,fairness,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10989,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",fumie ono,adaptive modulation,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10990,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",fumie ono,game theory,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10991,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",fumie ono,wireless network optimization,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10992,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ryu miura,Unmanned Aircraft System (UAS)-aided networks,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10993,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ryu miura,energy efficiency,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10994,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
10995,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
10996,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ryu miura,throughput per energy,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10997,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ryu miura,fairness,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10998,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ryu miura,adaptive modulation,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
10999,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ryu miura,game theory,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
11000,"Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ryu miura,wireless network optimization,2015.0,10.1109/TWC.2014.2343219,IEEE Transactions on Wireless Communications,Abdulla2015,False,,IEEE,Not available,Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology,151bf8cd9b7f119b4eb47b848423875b,https://ieeexplore.ieee.org/document/6867394/
11001,"Queueing networks are typically analyzed assuming that the arrival process is exogenous, and unaffected by admission control, scheduling policies, etc. In many situations arriving users are strategic, and do time their arrivals taking delay and other metrics into account. This paper builds on, and extends the framework developed to a network setting. We first consider just a single population of users arriving into two queues in parallel (they can join either queue). The queues start serving at different times. We characterize the arrival process into both queues and the Price of Anarchy with strategic arrivals. We then extend this when there are multiple populations, each with different cost metrics. The whole analysis is done in the fluid limit.",harsha honnappa,Strategic arrivals,2010.0,10.1109/ALLERTON.2010.5706993,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Honnappa2010,False,,IEEE,Not available,Strategic arrivals into queueing networks,5b5adbba2f2ba0c09bc8a937d331c4e3,https://ieeexplore.ieee.org/document/5706993/
11002,"Queueing networks are typically analyzed assuming that the arrival process is exogenous, and unaffected by admission control, scheduling policies, etc. In many situations arriving users are strategic, and do time their arrivals taking delay and other metrics into account. This paper builds on, and extends the framework developed to a network setting. We first consider just a single population of users arriving into two queues in parallel (they can join either queue). The queues start serving at different times. We characterize the arrival process into both queues and the Price of Anarchy with strategic arrivals. We then extend this when there are multiple populations, each with different cost metrics. The whole analysis is done in the fluid limit.",harsha honnappa,Population games,2010.0,10.1109/ALLERTON.2010.5706993,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Honnappa2010,False,,IEEE,Not available,Strategic arrivals into queueing networks,5b5adbba2f2ba0c09bc8a937d331c4e3,https://ieeexplore.ieee.org/document/5706993/
11003,"Queueing networks are typically analyzed assuming that the arrival process is exogenous, and unaffected by admission control, scheduling policies, etc. In many situations arriving users are strategic, and do time their arrivals taking delay and other metrics into account. This paper builds on, and extends the framework developed to a network setting. We first consider just a single population of users arriving into two queues in parallel (they can join either queue). The queues start serving at different times. We characterize the arrival process into both queues and the Price of Anarchy with strategic arrivals. We then extend this when there are multiple populations, each with different cost metrics. The whole analysis is done in the fluid limit.",harsha honnappa,Game theory,2010.0,10.1109/ALLERTON.2010.5706993,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Honnappa2010,False,,IEEE,Not available,Strategic arrivals into queueing networks,5b5adbba2f2ba0c09bc8a937d331c4e3,https://ieeexplore.ieee.org/document/5706993/
11004,"Queueing networks are typically analyzed assuming that the arrival process is exogenous, and unaffected by admission control, scheduling policies, etc. In many situations arriving users are strategic, and do time their arrivals taking delay and other metrics into account. This paper builds on, and extends the framework developed to a network setting. We first consider just a single population of users arriving into two queues in parallel (they can join either queue). The queues start serving at different times. We characterize the arrival process into both queues and the Price of Anarchy with strategic arrivals. We then extend this when there are multiple populations, each with different cost metrics. The whole analysis is done in the fluid limit.",harsha honnappa,Queueing Networks,2010.0,10.1109/ALLERTON.2010.5706993,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Honnappa2010,False,,IEEE,Not available,Strategic arrivals into queueing networks,5b5adbba2f2ba0c09bc8a937d331c4e3,https://ieeexplore.ieee.org/document/5706993/
11005,"Queueing networks are typically analyzed assuming that the arrival process is exogenous, and unaffected by admission control, scheduling policies, etc. In many situations arriving users are strategic, and do time their arrivals taking delay and other metrics into account. This paper builds on, and extends the framework developed to a network setting. We first consider just a single population of users arriving into two queues in parallel (they can join either queue). The queues start serving at different times. We characterize the arrival process into both queues and the Price of Anarchy with strategic arrivals. We then extend this when there are multiple populations, each with different cost metrics. The whole analysis is done in the fluid limit.",rahul jain,Strategic arrivals,2010.0,10.1109/ALLERTON.2010.5706993,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Honnappa2010,False,,IEEE,Not available,Strategic arrivals into queueing networks,5b5adbba2f2ba0c09bc8a937d331c4e3,https://ieeexplore.ieee.org/document/5706993/
11006,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11007,"Queueing networks are typically analyzed assuming that the arrival process is exogenous, and unaffected by admission control, scheduling policies, etc. In many situations arriving users are strategic, and do time their arrivals taking delay and other metrics into account. This paper builds on, and extends the framework developed to a network setting. We first consider just a single population of users arriving into two queues in parallel (they can join either queue). The queues start serving at different times. We characterize the arrival process into both queues and the Price of Anarchy with strategic arrivals. We then extend this when there are multiple populations, each with different cost metrics. The whole analysis is done in the fluid limit.",rahul jain,Population games,2010.0,10.1109/ALLERTON.2010.5706993,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Honnappa2010,False,,IEEE,Not available,Strategic arrivals into queueing networks,5b5adbba2f2ba0c09bc8a937d331c4e3,https://ieeexplore.ieee.org/document/5706993/
11008,"Queueing networks are typically analyzed assuming that the arrival process is exogenous, and unaffected by admission control, scheduling policies, etc. In many situations arriving users are strategic, and do time their arrivals taking delay and other metrics into account. This paper builds on, and extends the framework developed to a network setting. We first consider just a single population of users arriving into two queues in parallel (they can join either queue). The queues start serving at different times. We characterize the arrival process into both queues and the Price of Anarchy with strategic arrivals. We then extend this when there are multiple populations, each with different cost metrics. The whole analysis is done in the fluid limit.",rahul jain,Game theory,2010.0,10.1109/ALLERTON.2010.5706993,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Honnappa2010,False,,IEEE,Not available,Strategic arrivals into queueing networks,5b5adbba2f2ba0c09bc8a937d331c4e3,https://ieeexplore.ieee.org/document/5706993/
11009,"Queueing networks are typically analyzed assuming that the arrival process is exogenous, and unaffected by admission control, scheduling policies, etc. In many situations arriving users are strategic, and do time their arrivals taking delay and other metrics into account. This paper builds on, and extends the framework developed to a network setting. We first consider just a single population of users arriving into two queues in parallel (they can join either queue). The queues start serving at different times. We characterize the arrival process into both queues and the Price of Anarchy with strategic arrivals. We then extend this when there are multiple populations, each with different cost metrics. The whole analysis is done in the fluid limit.",rahul jain,Queueing Networks,2010.0,10.1109/ALLERTON.2010.5706993,"2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",Honnappa2010,False,,IEEE,Not available,Strategic arrivals into queueing networks,5b5adbba2f2ba0c09bc8a937d331c4e3,https://ieeexplore.ieee.org/document/5706993/
11010,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",fengxiao tang,Anticoordination game,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
11011,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",fengxiao tang,channel assignment,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
11012,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",fengxiao tang,device to device (D2D),2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
11013,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",fengxiao tang,game theory,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
11014,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",fengxiao tang,partially overlapping channel (PoC),2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
11015,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",fengxiao tang,potential game,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
11016,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",fengxiao tang,unmanned aerial vehicle (UAV),2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
11017,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11018,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",zubair fadlullah,Anticoordination game,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
11019,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",zubair fadlullah,channel assignment,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
11020,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",zubair fadlullah,device to device (D2D),2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
11021,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",zubair fadlullah,game theory,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
11022,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",zubair fadlullah,partially overlapping channel (PoC),2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
11023,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",zubair fadlullah,potential game,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
11024,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",zubair fadlullah,unmanned aerial vehicle (UAV),2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
11025,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",nei kato,Anticoordination game,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
11026,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",nei kato,channel assignment,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
11027,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",nei kato,device to device (D2D),2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
11028,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11029,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",nei kato,game theory,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
11030,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",nei kato,partially overlapping channel (PoC),2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
11031,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",nei kato,potential game,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
11032,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",nei kato,unmanned aerial vehicle (UAV),2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
11033,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",fumie ono,Anticoordination game,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
11034,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",fumie ono,channel assignment,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
11035,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",fumie ono,device to device (D2D),2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
11036,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",fumie ono,game theory,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
11037,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",fumie ono,partially overlapping channel (PoC),2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
11038,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",fumie ono,potential game,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
11039,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11040,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",fumie ono,unmanned aerial vehicle (UAV),2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
11041,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",ryu miura,Anticoordination game,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
11042,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",ryu miura,channel assignment,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
11043,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",ryu miura,device to device (D2D),2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
11044,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",ryu miura,game theory,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
11045,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",ryu miura,partially overlapping channel (PoC),2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
11046,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",ryu miura,potential game,2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
11047,"Device-to-device (D2D)-enabled wireless networks are becoming increasingly popular. However, in remote, rural, and disaster affected areas, it is difficult to construct such wireless networks due to the unavailability or inadequacy of cellular infrastructures. Unmanned aerial vehicles (UAVs) can be a good candidate to promptly construct the D2D-enabled wireless network. However, the assignment of the radio channels of the nodes (i.e., UAVs and user terminals) is challenging due to the availability of only a limited number of orthogonal channels and the interference issue resulted from using arbitrary channels. Furthermore, the dynamic topology and high mobility of nodes in such a combined UAV and D2D-based network make conventional channel assignment (CA) algorithm no longer suitable. In this paper, we formally address this problem, and demonstrate how partially overlapping channels (POCs) and game theory can be exploited to alleviate the problem. In this vein, we propose a distributed anticoordination game based POC assignment algorithm referred to as AC-POCA. In our proposed AC-POCA, the nodes use only local information to play the game, and reach a steady state, uniqueness of which is verified through analysis. Also, the upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results. In addition, simulation results demonstrate the effectiveness of AC-POCA in terms of good throughput and low signaling overhead in a dynamic environment.",ryu miura,unmanned aerial vehicle (UAV),2018.0,10.1109/TVT.2017.2753280,IEEE Transactions on Vehicular Technology,Tang2018,False,,IEEE,Not available,AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks,26764c478aba8c1f932915724c37df9c,https://ieeexplore.ieee.org/document/8039268/
11048,"We consider random medium access schemes for devices that support sleep modes, i.e. turning off electronic compartments for energy saving. Due to hardware limitations, sleep mode transitions cannot occur at the medium access timescale. Each terminal can choose when to turn on/off and its probability to transmit on an arbitrary slot. Thus, we develop a two level model, consisting of a fast timescale for transmission scheduling and a slower timescale for the sleep mode transitions. We take a game theoretic approach to model the user interactions and show that the energy constraints modify the medium access problem significantly, decreasing the price of anarchy. Our results give valuable insights on the energy-throughput tradeoff for contention based systems.",lazaros gkatzikis,ALOHA,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Gkatzikis2011,False,,IEEE,Not available,Medium access games: The impact of energy constraints,278310a495a996d675257e3f30f18177,https://ieeexplore.ieee.org/document/6103901/
11049,"We consider random medium access schemes for devices that support sleep modes, i.e. turning off electronic compartments for energy saving. Due to hardware limitations, sleep mode transitions cannot occur at the medium access timescale. Each terminal can choose when to turn on/off and its probability to transmit on an arbitrary slot. Thus, we develop a two level model, consisting of a fast timescale for transmission scheduling and a slower timescale for the sleep mode transitions. We take a game theoretic approach to model the user interactions and show that the energy constraints modify the medium access problem significantly, decreasing the price of anarchy. Our results give valuable insights on the energy-throughput tradeoff for contention based systems.",lazaros gkatzikis,contention,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Gkatzikis2011,False,,IEEE,Not available,Medium access games: The impact of energy constraints,278310a495a996d675257e3f30f18177,https://ieeexplore.ieee.org/document/6103901/
11050,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11051,"We consider random medium access schemes for devices that support sleep modes, i.e. turning off electronic compartments for energy saving. Due to hardware limitations, sleep mode transitions cannot occur at the medium access timescale. Each terminal can choose when to turn on/off and its probability to transmit on an arbitrary slot. Thus, we develop a two level model, consisting of a fast timescale for transmission scheduling and a slower timescale for the sleep mode transitions. We take a game theoretic approach to model the user interactions and show that the energy constraints modify the medium access problem significantly, decreasing the price of anarchy. Our results give valuable insights on the energy-throughput tradeoff for contention based systems.",lazaros gkatzikis,energy saving,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Gkatzikis2011,False,,IEEE,Not available,Medium access games: The impact of energy constraints,278310a495a996d675257e3f30f18177,https://ieeexplore.ieee.org/document/6103901/
11052,"We consider random medium access schemes for devices that support sleep modes, i.e. turning off electronic compartments for energy saving. Due to hardware limitations, sleep mode transitions cannot occur at the medium access timescale. Each terminal can choose when to turn on/off and its probability to transmit on an arbitrary slot. Thus, we develop a two level model, consisting of a fast timescale for transmission scheduling and a slower timescale for the sleep mode transitions. We take a game theoretic approach to model the user interactions and show that the energy constraints modify the medium access problem significantly, decreasing the price of anarchy. Our results give valuable insights on the energy-throughput tradeoff for contention based systems.",lazaros gkatzikis,game theory,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Gkatzikis2011,False,,IEEE,Not available,Medium access games: The impact of energy constraints,278310a495a996d675257e3f30f18177,https://ieeexplore.ieee.org/document/6103901/
11053,"We consider random medium access schemes for devices that support sleep modes, i.e. turning off electronic compartments for energy saving. Due to hardware limitations, sleep mode transitions cannot occur at the medium access timescale. Each terminal can choose when to turn on/off and its probability to transmit on an arbitrary slot. Thus, we develop a two level model, consisting of a fast timescale for transmission scheduling and a slower timescale for the sleep mode transitions. We take a game theoretic approach to model the user interactions and show that the energy constraints modify the medium access problem significantly, decreasing the price of anarchy. Our results give valuable insights on the energy-throughput tradeoff for contention based systems.",georgios paschos,ALOHA,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Gkatzikis2011,False,,IEEE,Not available,Medium access games: The impact of energy constraints,278310a495a996d675257e3f30f18177,https://ieeexplore.ieee.org/document/6103901/
11054,"We consider random medium access schemes for devices that support sleep modes, i.e. turning off electronic compartments for energy saving. Due to hardware limitations, sleep mode transitions cannot occur at the medium access timescale. Each terminal can choose when to turn on/off and its probability to transmit on an arbitrary slot. Thus, we develop a two level model, consisting of a fast timescale for transmission scheduling and a slower timescale for the sleep mode transitions. We take a game theoretic approach to model the user interactions and show that the energy constraints modify the medium access problem significantly, decreasing the price of anarchy. Our results give valuable insights on the energy-throughput tradeoff for contention based systems.",georgios paschos,contention,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Gkatzikis2011,False,,IEEE,Not available,Medium access games: The impact of energy constraints,278310a495a996d675257e3f30f18177,https://ieeexplore.ieee.org/document/6103901/
11055,"We consider random medium access schemes for devices that support sleep modes, i.e. turning off electronic compartments for energy saving. Due to hardware limitations, sleep mode transitions cannot occur at the medium access timescale. Each terminal can choose when to turn on/off and its probability to transmit on an arbitrary slot. Thus, we develop a two level model, consisting of a fast timescale for transmission scheduling and a slower timescale for the sleep mode transitions. We take a game theoretic approach to model the user interactions and show that the energy constraints modify the medium access problem significantly, decreasing the price of anarchy. Our results give valuable insights on the energy-throughput tradeoff for contention based systems.",georgios paschos,energy saving,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Gkatzikis2011,False,,IEEE,Not available,Medium access games: The impact of energy constraints,278310a495a996d675257e3f30f18177,https://ieeexplore.ieee.org/document/6103901/
11056,"We consider random medium access schemes for devices that support sleep modes, i.e. turning off electronic compartments for energy saving. Due to hardware limitations, sleep mode transitions cannot occur at the medium access timescale. Each terminal can choose when to turn on/off and its probability to transmit on an arbitrary slot. Thus, we develop a two level model, consisting of a fast timescale for transmission scheduling and a slower timescale for the sleep mode transitions. We take a game theoretic approach to model the user interactions and show that the energy constraints modify the medium access problem significantly, decreasing the price of anarchy. Our results give valuable insights on the energy-throughput tradeoff for contention based systems.",georgios paschos,game theory,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Gkatzikis2011,False,,IEEE,Not available,Medium access games: The impact of energy constraints,278310a495a996d675257e3f30f18177,https://ieeexplore.ieee.org/document/6103901/
11057,"We consider random medium access schemes for devices that support sleep modes, i.e. turning off electronic compartments for energy saving. Due to hardware limitations, sleep mode transitions cannot occur at the medium access timescale. Each terminal can choose when to turn on/off and its probability to transmit on an arbitrary slot. Thus, we develop a two level model, consisting of a fast timescale for transmission scheduling and a slower timescale for the sleep mode transitions. We take a game theoretic approach to model the user interactions and show that the energy constraints modify the medium access problem significantly, decreasing the price of anarchy. Our results give valuable insights on the energy-throughput tradeoff for contention based systems.",iordanis koutsopoulos,ALOHA,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Gkatzikis2011,False,,IEEE,Not available,Medium access games: The impact of energy constraints,278310a495a996d675257e3f30f18177,https://ieeexplore.ieee.org/document/6103901/
11058,"We consider random medium access schemes for devices that support sleep modes, i.e. turning off electronic compartments for energy saving. Due to hardware limitations, sleep mode transitions cannot occur at the medium access timescale. Each terminal can choose when to turn on/off and its probability to transmit on an arbitrary slot. Thus, we develop a two level model, consisting of a fast timescale for transmission scheduling and a slower timescale for the sleep mode transitions. We take a game theoretic approach to model the user interactions and show that the energy constraints modify the medium access problem significantly, decreasing the price of anarchy. Our results give valuable insights on the energy-throughput tradeoff for contention based systems.",iordanis koutsopoulos,contention,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Gkatzikis2011,False,,IEEE,Not available,Medium access games: The impact of energy constraints,278310a495a996d675257e3f30f18177,https://ieeexplore.ieee.org/document/6103901/
11059,"We consider random medium access schemes for devices that support sleep modes, i.e. turning off electronic compartments for energy saving. Due to hardware limitations, sleep mode transitions cannot occur at the medium access timescale. Each terminal can choose when to turn on/off and its probability to transmit on an arbitrary slot. Thus, we develop a two level model, consisting of a fast timescale for transmission scheduling and a slower timescale for the sleep mode transitions. We take a game theoretic approach to model the user interactions and show that the energy constraints modify the medium access problem significantly, decreasing the price of anarchy. Our results give valuable insights on the energy-throughput tradeoff for contention based systems.",iordanis koutsopoulos,energy saving,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Gkatzikis2011,False,,IEEE,Not available,Medium access games: The impact of energy constraints,278310a495a996d675257e3f30f18177,https://ieeexplore.ieee.org/document/6103901/
11060,"We consider random medium access schemes for devices that support sleep modes, i.e. turning off electronic compartments for energy saving. Due to hardware limitations, sleep mode transitions cannot occur at the medium access timescale. Each terminal can choose when to turn on/off and its probability to transmit on an arbitrary slot. Thus, we develop a two level model, consisting of a fast timescale for transmission scheduling and a slower timescale for the sleep mode transitions. We take a game theoretic approach to model the user interactions and show that the energy constraints modify the medium access problem significantly, decreasing the price of anarchy. Our results give valuable insights on the energy-throughput tradeoff for contention based systems.",iordanis koutsopoulos,game theory,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Gkatzikis2011,False,,IEEE,Not available,Medium access games: The impact of energy constraints,278310a495a996d675257e3f30f18177,https://ieeexplore.ieee.org/document/6103901/
11061,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11062,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",majed haddad,WLAN,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
11063,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",majed haddad,3G,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
11064,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",majed haddad,association problem,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
11065,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",majed haddad,misleading information,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
11066,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",majed haddad,channel state information,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
11067,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",majed haddad,game theory,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
11068,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",majed haddad,Bayes-Nash equilibrium,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
11069,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",majed haddad,Bayes-Stackelberg equilibrium,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
11070,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",majed haddad,Price of Anarchy,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
11071,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",habib sidi,WLAN,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
11072,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11073,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",habib sidi,3G,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
11074,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",habib sidi,association problem,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
11075,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",habib sidi,misleading information,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
11076,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",habib sidi,channel state information,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
11077,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",habib sidi,game theory,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
11078,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",habib sidi,Bayes-Nash equilibrium,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
11079,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",habib sidi,Bayes-Stackelberg equilibrium,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
11080,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",habib sidi,Price of Anarchy,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
11081,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",piotr wiecek,WLAN,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
11082,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",piotr wiecek,3G,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
11083,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11084,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",piotr wiecek,association problem,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
11085,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",piotr wiecek,misleading information,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
11086,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",piotr wiecek,channel state information,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
11087,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",piotr wiecek,game theory,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
11088,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",piotr wiecek,Bayes-Nash equilibrium,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
11089,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",piotr wiecek,Bayes-Stackelberg equilibrium,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
11090,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",piotr wiecek,Price of Anarchy,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
11091,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",eitan altman,WLAN,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
11092,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",eitan altman,3G,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
11093,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",eitan altman,association problem,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
11094,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11095,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",eitan altman,misleading information,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
11096,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",eitan altman,channel state information,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
11097,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",eitan altman,game theory,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
11098,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",eitan altman,Bayes-Nash equilibrium,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
11099,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",eitan altman,Bayes-Stackelberg equilibrium,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
11100,"In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.",eitan altman,Price of Anarchy,2014.0,10.1109/INFOCOM.2014.6848117,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Haddad2014,False,,IEEE,Not available,Automated dynamic offset applied to cell association,d14bc934cab9b7131be7e6ebd214a4ef,https://ieeexplore.ieee.org/document/6848117/
11101,"We consider routing games where the performance of each user is dictated by the worst (bottleneck) element it employs. We are given a network, finitely many (selfish) users, each associated with a positive flow demand, and a load-dependent performance function for each network element; the social (i.e., system) objective is to optimize the performance of the worst element in the network (i.e., the network bottleneck). Although we show that such ""bottleneck"" routing games appear in a variety of practical scenarios, they have not been considered yet. Accordingly, we study their properties, considering two routing scenarios, namely when a user can split its traffic over more than one path (splittable bottleneck game) and when it cannot (unsplittable bottleneck game). First, we prove that, for both splittable and unsplittable bottleneck games, there is a (not necessarily unique) Nash equilibrium. Then, we consider the rate of convergence to a Nash equilibrium in each game. Finally, we investigate the efficiency of the Nash equilibria in both games with respect to the social optimum; specifically, while for both games we show that the price of anarchy is unbounded, we identify for each game conditions under which Nash equilibria are socially optimal.",ron banner,Routing,2007.0,10.1109/JSAC.2007.070811,IEEE Journal on Selected Areas in Communications,Banner2007,False,,IEEE,Not available,Bottleneck Routing Games in Communication Networks,6e4bebc959c5e449d56dba0cd3746284,https://ieeexplore.ieee.org/document/4278417/
11102,"We consider routing games where the performance of each user is dictated by the worst (bottleneck) element it employs. We are given a network, finitely many (selfish) users, each associated with a positive flow demand, and a load-dependent performance function for each network element; the social (i.e., system) objective is to optimize the performance of the worst element in the network (i.e., the network bottleneck). Although we show that such ""bottleneck"" routing games appear in a variety of practical scenarios, they have not been considered yet. Accordingly, we study their properties, considering two routing scenarios, namely when a user can split its traffic over more than one path (splittable bottleneck game) and when it cannot (unsplittable bottleneck game). First, we prove that, for both splittable and unsplittable bottleneck games, there is a (not necessarily unique) Nash equilibrium. Then, we consider the rate of convergence to a Nash equilibrium in each game. Finally, we investigate the efficiency of the Nash equilibria in both games with respect to the social optimum; specifically, while for both games we show that the price of anarchy is unbounded, we identify for each game conditions under which Nash equilibria are socially optimal.",ron banner,Communication networks,2007.0,10.1109/JSAC.2007.070811,IEEE Journal on Selected Areas in Communications,Banner2007,False,,IEEE,Not available,Bottleneck Routing Games in Communication Networks,6e4bebc959c5e449d56dba0cd3746284,https://ieeexplore.ieee.org/document/4278417/
11103,"We consider routing games where the performance of each user is dictated by the worst (bottleneck) element it employs. We are given a network, finitely many (selfish) users, each associated with a positive flow demand, and a load-dependent performance function for each network element; the social (i.e., system) objective is to optimize the performance of the worst element in the network (i.e., the network bottleneck). Although we show that such ""bottleneck"" routing games appear in a variety of practical scenarios, they have not been considered yet. Accordingly, we study their properties, considering two routing scenarios, namely when a user can split its traffic over more than one path (splittable bottleneck game) and when it cannot (unsplittable bottleneck game). First, we prove that, for both splittable and unsplittable bottleneck games, there is a (not necessarily unique) Nash equilibrium. Then, we consider the rate of convergence to a Nash equilibrium in each game. Finally, we investigate the efficiency of the Nash equilibria in both games with respect to the social optimum; specifically, while for both games we show that the price of anarchy is unbounded, we identify for each game conditions under which Nash equilibria are socially optimal.",ron banner,Nash equilibrium,2007.0,10.1109/JSAC.2007.070811,IEEE Journal on Selected Areas in Communications,Banner2007,False,,IEEE,Not available,Bottleneck Routing Games in Communication Networks,6e4bebc959c5e449d56dba0cd3746284,https://ieeexplore.ieee.org/document/4278417/
11104,"We consider routing games where the performance of each user is dictated by the worst (bottleneck) element it employs. We are given a network, finitely many (selfish) users, each associated with a positive flow demand, and a load-dependent performance function for each network element; the social (i.e., system) objective is to optimize the performance of the worst element in the network (i.e., the network bottleneck). Although we show that such ""bottleneck"" routing games appear in a variety of practical scenarios, they have not been considered yet. Accordingly, we study their properties, considering two routing scenarios, namely when a user can split its traffic over more than one path (splittable bottleneck game) and when it cannot (unsplittable bottleneck game). First, we prove that, for both splittable and unsplittable bottleneck games, there is a (not necessarily unique) Nash equilibrium. Then, we consider the rate of convergence to a Nash equilibrium in each game. Finally, we investigate the efficiency of the Nash equilibria in both games with respect to the social optimum; specifically, while for both games we show that the price of anarchy is unbounded, we identify for each game conditions under which Nash equilibria are socially optimal.",ron banner,Telecommunication traffic,2007.0,10.1109/JSAC.2007.070811,IEEE Journal on Selected Areas in Communications,Banner2007,False,,IEEE,Not available,Bottleneck Routing Games in Communication Networks,6e4bebc959c5e449d56dba0cd3746284,https://ieeexplore.ieee.org/document/4278417/
11105,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11106,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11107,"We consider routing games where the performance of each user is dictated by the worst (bottleneck) element it employs. We are given a network, finitely many (selfish) users, each associated with a positive flow demand, and a load-dependent performance function for each network element; the social (i.e., system) objective is to optimize the performance of the worst element in the network (i.e., the network bottleneck). Although we show that such ""bottleneck"" routing games appear in a variety of practical scenarios, they have not been considered yet. Accordingly, we study their properties, considering two routing scenarios, namely when a user can split its traffic over more than one path (splittable bottleneck game) and when it cannot (unsplittable bottleneck game). First, we prove that, for both splittable and unsplittable bottleneck games, there is a (not necessarily unique) Nash equilibrium. Then, we consider the rate of convergence to a Nash equilibrium in each game. Finally, we investigate the efficiency of the Nash equilibria in both games with respect to the social optimum; specifically, while for both games we show that the price of anarchy is unbounded, we identify for each game conditions under which Nash equilibria are socially optimal.",ron banner,Batteries,2007.0,10.1109/JSAC.2007.070811,IEEE Journal on Selected Areas in Communications,Banner2007,False,,IEEE,Not available,Bottleneck Routing Games in Communication Networks,6e4bebc959c5e449d56dba0cd3746284,https://ieeexplore.ieee.org/document/4278417/
11108,"We consider routing games where the performance of each user is dictated by the worst (bottleneck) element it employs. We are given a network, finitely many (selfish) users, each associated with a positive flow demand, and a load-dependent performance function for each network element; the social (i.e., system) objective is to optimize the performance of the worst element in the network (i.e., the network bottleneck). Although we show that such ""bottleneck"" routing games appear in a variety of practical scenarios, they have not been considered yet. Accordingly, we study their properties, considering two routing scenarios, namely when a user can split its traffic over more than one path (splittable bottleneck game) and when it cannot (unsplittable bottleneck game). First, we prove that, for both splittable and unsplittable bottleneck games, there is a (not necessarily unique) Nash equilibrium. Then, we consider the rate of convergence to a Nash equilibrium in each game. Finally, we investigate the efficiency of the Nash equilibria in both games with respect to the social optimum; specifically, while for both games we show that the price of anarchy is unbounded, we identify for each game conditions under which Nash equilibria are socially optimal.",ron banner,Game theory,2007.0,10.1109/JSAC.2007.070811,IEEE Journal on Selected Areas in Communications,Banner2007,False,,IEEE,Not available,Bottleneck Routing Games in Communication Networks,6e4bebc959c5e449d56dba0cd3746284,https://ieeexplore.ieee.org/document/4278417/
11109,"We consider routing games where the performance of each user is dictated by the worst (bottleneck) element it employs. We are given a network, finitely many (selfish) users, each associated with a positive flow demand, and a load-dependent performance function for each network element; the social (i.e., system) objective is to optimize the performance of the worst element in the network (i.e., the network bottleneck). Although we show that such ""bottleneck"" routing games appear in a variety of practical scenarios, they have not been considered yet. Accordingly, we study their properties, considering two routing scenarios, namely when a user can split its traffic over more than one path (splittable bottleneck game) and when it cannot (unsplittable bottleneck game). First, we prove that, for both splittable and unsplittable bottleneck games, there is a (not necessarily unique) Nash equilibrium. Then, we consider the rate of convergence to a Nash equilibrium in each game. Finally, we investigate the efficiency of the Nash equilibria in both games with respect to the social optimum; specifically, while for both games we show that the price of anarchy is unbounded, we identify for each game conditions under which Nash equilibria are socially optimal.",ron banner,Cities and towns,2007.0,10.1109/JSAC.2007.070811,IEEE Journal on Selected Areas in Communications,Banner2007,False,,IEEE,Not available,Bottleneck Routing Games in Communication Networks,6e4bebc959c5e449d56dba0cd3746284,https://ieeexplore.ieee.org/document/4278417/
11110,"We consider routing games where the performance of each user is dictated by the worst (bottleneck) element it employs. We are given a network, finitely many (selfish) users, each associated with a positive flow demand, and a load-dependent performance function for each network element; the social (i.e., system) objective is to optimize the performance of the worst element in the network (i.e., the network bottleneck). Although we show that such ""bottleneck"" routing games appear in a variety of practical scenarios, they have not been considered yet. Accordingly, we study their properties, considering two routing scenarios, namely when a user can split its traffic over more than one path (splittable bottleneck game) and when it cannot (unsplittable bottleneck game). First, we prove that, for both splittable and unsplittable bottleneck games, there is a (not necessarily unique) Nash equilibrium. Then, we consider the rate of convergence to a Nash equilibrium in each game. Finally, we investigate the efficiency of the Nash equilibria in both games with respect to the social optimum; specifically, while for both games we show that the price of anarchy is unbounded, we identify for each game conditions under which Nash equilibria are socially optimal.",ron banner,Convergence,2007.0,10.1109/JSAC.2007.070811,IEEE Journal on Selected Areas in Communications,Banner2007,False,,IEEE,Not available,Bottleneck Routing Games in Communication Networks,6e4bebc959c5e449d56dba0cd3746284,https://ieeexplore.ieee.org/document/4278417/
11111,"We consider routing games where the performance of each user is dictated by the worst (bottleneck) element it employs. We are given a network, finitely many (selfish) users, each associated with a positive flow demand, and a load-dependent performance function for each network element; the social (i.e., system) objective is to optimize the performance of the worst element in the network (i.e., the network bottleneck). Although we show that such ""bottleneck"" routing games appear in a variety of practical scenarios, they have not been considered yet. Accordingly, we study their properties, considering two routing scenarios, namely when a user can split its traffic over more than one path (splittable bottleneck game) and when it cannot (unsplittable bottleneck game). First, we prove that, for both splittable and unsplittable bottleneck games, there is a (not necessarily unique) Nash equilibrium. Then, we consider the rate of convergence to a Nash equilibrium in each game. Finally, we investigate the efficiency of the Nash equilibria in both games with respect to the social optimum; specifically, while for both games we show that the price of anarchy is unbounded, we identify for each game conditions under which Nash equilibria are socially optimal.",ron banner,Communication system control,2007.0,10.1109/JSAC.2007.070811,IEEE Journal on Selected Areas in Communications,Banner2007,False,,IEEE,Not available,Bottleneck Routing Games in Communication Networks,6e4bebc959c5e449d56dba0cd3746284,https://ieeexplore.ieee.org/document/4278417/
11112,"We consider routing games where the performance of each user is dictated by the worst (bottleneck) element it employs. We are given a network, finitely many (selfish) users, each associated with a positive flow demand, and a load-dependent performance function for each network element; the social (i.e., system) objective is to optimize the performance of the worst element in the network (i.e., the network bottleneck). Although we show that such ""bottleneck"" routing games appear in a variety of practical scenarios, they have not been considered yet. Accordingly, we study their properties, considering two routing scenarios, namely when a user can split its traffic over more than one path (splittable bottleneck game) and when it cannot (unsplittable bottleneck game). First, we prove that, for both splittable and unsplittable bottleneck games, there is a (not necessarily unique) Nash equilibrium. Then, we consider the rate of convergence to a Nash equilibrium in each game. Finally, we investigate the efficiency of the Nash equilibria in both games with respect to the social optimum; specifically, while for both games we show that the price of anarchy is unbounded, we identify for each game conditions under which Nash equilibria are socially optimal.",ron banner,Large-scale systems,2007.0,10.1109/JSAC.2007.070811,IEEE Journal on Selected Areas in Communications,Banner2007,False,,IEEE,Not available,Bottleneck Routing Games in Communication Networks,6e4bebc959c5e449d56dba0cd3746284,https://ieeexplore.ieee.org/document/4278417/
11113,"We consider routing games where the performance of each user is dictated by the worst (bottleneck) element it employs. We are given a network, finitely many (selfish) users, each associated with a positive flow demand, and a load-dependent performance function for each network element; the social (i.e., system) objective is to optimize the performance of the worst element in the network (i.e., the network bottleneck). Although we show that such ""bottleneck"" routing games appear in a variety of practical scenarios, they have not been considered yet. Accordingly, we study their properties, considering two routing scenarios, namely when a user can split its traffic over more than one path (splittable bottleneck game) and when it cannot (unsplittable bottleneck game). First, we prove that, for both splittable and unsplittable bottleneck games, there is a (not necessarily unique) Nash equilibrium. Then, we consider the rate of convergence to a Nash equilibrium in each game. Finally, we investigate the efficiency of the Nash equilibria in both games with respect to the social optimum; specifically, while for both games we show that the price of anarchy is unbounded, we identify for each game conditions under which Nash equilibria are socially optimal.",ariel orda,Routing,2007.0,10.1109/JSAC.2007.070811,IEEE Journal on Selected Areas in Communications,Banner2007,False,,IEEE,Not available,Bottleneck Routing Games in Communication Networks,6e4bebc959c5e449d56dba0cd3746284,https://ieeexplore.ieee.org/document/4278417/
11114,"We consider routing games where the performance of each user is dictated by the worst (bottleneck) element it employs. We are given a network, finitely many (selfish) users, each associated with a positive flow demand, and a load-dependent performance function for each network element; the social (i.e., system) objective is to optimize the performance of the worst element in the network (i.e., the network bottleneck). Although we show that such ""bottleneck"" routing games appear in a variety of practical scenarios, they have not been considered yet. Accordingly, we study their properties, considering two routing scenarios, namely when a user can split its traffic over more than one path (splittable bottleneck game) and when it cannot (unsplittable bottleneck game). First, we prove that, for both splittable and unsplittable bottleneck games, there is a (not necessarily unique) Nash equilibrium. Then, we consider the rate of convergence to a Nash equilibrium in each game. Finally, we investigate the efficiency of the Nash equilibria in both games with respect to the social optimum; specifically, while for both games we show that the price of anarchy is unbounded, we identify for each game conditions under which Nash equilibria are socially optimal.",ariel orda,Communication networks,2007.0,10.1109/JSAC.2007.070811,IEEE Journal on Selected Areas in Communications,Banner2007,False,,IEEE,Not available,Bottleneck Routing Games in Communication Networks,6e4bebc959c5e449d56dba0cd3746284,https://ieeexplore.ieee.org/document/4278417/
11115,"We consider routing games where the performance of each user is dictated by the worst (bottleneck) element it employs. We are given a network, finitely many (selfish) users, each associated with a positive flow demand, and a load-dependent performance function for each network element; the social (i.e., system) objective is to optimize the performance of the worst element in the network (i.e., the network bottleneck). Although we show that such ""bottleneck"" routing games appear in a variety of practical scenarios, they have not been considered yet. Accordingly, we study their properties, considering two routing scenarios, namely when a user can split its traffic over more than one path (splittable bottleneck game) and when it cannot (unsplittable bottleneck game). First, we prove that, for both splittable and unsplittable bottleneck games, there is a (not necessarily unique) Nash equilibrium. Then, we consider the rate of convergence to a Nash equilibrium in each game. Finally, we investigate the efficiency of the Nash equilibria in both games with respect to the social optimum; specifically, while for both games we show that the price of anarchy is unbounded, we identify for each game conditions under which Nash equilibria are socially optimal.",ariel orda,Nash equilibrium,2007.0,10.1109/JSAC.2007.070811,IEEE Journal on Selected Areas in Communications,Banner2007,False,,IEEE,Not available,Bottleneck Routing Games in Communication Networks,6e4bebc959c5e449d56dba0cd3746284,https://ieeexplore.ieee.org/document/4278417/
11116,"We consider routing games where the performance of each user is dictated by the worst (bottleneck) element it employs. We are given a network, finitely many (selfish) users, each associated with a positive flow demand, and a load-dependent performance function for each network element; the social (i.e., system) objective is to optimize the performance of the worst element in the network (i.e., the network bottleneck). Although we show that such ""bottleneck"" routing games appear in a variety of practical scenarios, they have not been considered yet. Accordingly, we study their properties, considering two routing scenarios, namely when a user can split its traffic over more than one path (splittable bottleneck game) and when it cannot (unsplittable bottleneck game). First, we prove that, for both splittable and unsplittable bottleneck games, there is a (not necessarily unique) Nash equilibrium. Then, we consider the rate of convergence to a Nash equilibrium in each game. Finally, we investigate the efficiency of the Nash equilibria in both games with respect to the social optimum; specifically, while for both games we show that the price of anarchy is unbounded, we identify for each game conditions under which Nash equilibria are socially optimal.",ariel orda,Telecommunication traffic,2007.0,10.1109/JSAC.2007.070811,IEEE Journal on Selected Areas in Communications,Banner2007,False,,IEEE,Not available,Bottleneck Routing Games in Communication Networks,6e4bebc959c5e449d56dba0cd3746284,https://ieeexplore.ieee.org/document/4278417/
11117,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11118,"We consider routing games where the performance of each user is dictated by the worst (bottleneck) element it employs. We are given a network, finitely many (selfish) users, each associated with a positive flow demand, and a load-dependent performance function for each network element; the social (i.e., system) objective is to optimize the performance of the worst element in the network (i.e., the network bottleneck). Although we show that such ""bottleneck"" routing games appear in a variety of practical scenarios, they have not been considered yet. Accordingly, we study their properties, considering two routing scenarios, namely when a user can split its traffic over more than one path (splittable bottleneck game) and when it cannot (unsplittable bottleneck game). First, we prove that, for both splittable and unsplittable bottleneck games, there is a (not necessarily unique) Nash equilibrium. Then, we consider the rate of convergence to a Nash equilibrium in each game. Finally, we investigate the efficiency of the Nash equilibria in both games with respect to the social optimum; specifically, while for both games we show that the price of anarchy is unbounded, we identify for each game conditions under which Nash equilibria are socially optimal.",ariel orda,Batteries,2007.0,10.1109/JSAC.2007.070811,IEEE Journal on Selected Areas in Communications,Banner2007,False,,IEEE,Not available,Bottleneck Routing Games in Communication Networks,6e4bebc959c5e449d56dba0cd3746284,https://ieeexplore.ieee.org/document/4278417/
11119,"We consider routing games where the performance of each user is dictated by the worst (bottleneck) element it employs. We are given a network, finitely many (selfish) users, each associated with a positive flow demand, and a load-dependent performance function for each network element; the social (i.e., system) objective is to optimize the performance of the worst element in the network (i.e., the network bottleneck). Although we show that such ""bottleneck"" routing games appear in a variety of practical scenarios, they have not been considered yet. Accordingly, we study their properties, considering two routing scenarios, namely when a user can split its traffic over more than one path (splittable bottleneck game) and when it cannot (unsplittable bottleneck game). First, we prove that, for both splittable and unsplittable bottleneck games, there is a (not necessarily unique) Nash equilibrium. Then, we consider the rate of convergence to a Nash equilibrium in each game. Finally, we investigate the efficiency of the Nash equilibria in both games with respect to the social optimum; specifically, while for both games we show that the price of anarchy is unbounded, we identify for each game conditions under which Nash equilibria are socially optimal.",ariel orda,Game theory,2007.0,10.1109/JSAC.2007.070811,IEEE Journal on Selected Areas in Communications,Banner2007,False,,IEEE,Not available,Bottleneck Routing Games in Communication Networks,6e4bebc959c5e449d56dba0cd3746284,https://ieeexplore.ieee.org/document/4278417/
11120,"We consider routing games where the performance of each user is dictated by the worst (bottleneck) element it employs. We are given a network, finitely many (selfish) users, each associated with a positive flow demand, and a load-dependent performance function for each network element; the social (i.e., system) objective is to optimize the performance of the worst element in the network (i.e., the network bottleneck). Although we show that such ""bottleneck"" routing games appear in a variety of practical scenarios, they have not been considered yet. Accordingly, we study their properties, considering two routing scenarios, namely when a user can split its traffic over more than one path (splittable bottleneck game) and when it cannot (unsplittable bottleneck game). First, we prove that, for both splittable and unsplittable bottleneck games, there is a (not necessarily unique) Nash equilibrium. Then, we consider the rate of convergence to a Nash equilibrium in each game. Finally, we investigate the efficiency of the Nash equilibria in both games with respect to the social optimum; specifically, while for both games we show that the price of anarchy is unbounded, we identify for each game conditions under which Nash equilibria are socially optimal.",ariel orda,Cities and towns,2007.0,10.1109/JSAC.2007.070811,IEEE Journal on Selected Areas in Communications,Banner2007,False,,IEEE,Not available,Bottleneck Routing Games in Communication Networks,6e4bebc959c5e449d56dba0cd3746284,https://ieeexplore.ieee.org/document/4278417/
11121,"We consider routing games where the performance of each user is dictated by the worst (bottleneck) element it employs. We are given a network, finitely many (selfish) users, each associated with a positive flow demand, and a load-dependent performance function for each network element; the social (i.e., system) objective is to optimize the performance of the worst element in the network (i.e., the network bottleneck). Although we show that such ""bottleneck"" routing games appear in a variety of practical scenarios, they have not been considered yet. Accordingly, we study their properties, considering two routing scenarios, namely when a user can split its traffic over more than one path (splittable bottleneck game) and when it cannot (unsplittable bottleneck game). First, we prove that, for both splittable and unsplittable bottleneck games, there is a (not necessarily unique) Nash equilibrium. Then, we consider the rate of convergence to a Nash equilibrium in each game. Finally, we investigate the efficiency of the Nash equilibria in both games with respect to the social optimum; specifically, while for both games we show that the price of anarchy is unbounded, we identify for each game conditions under which Nash equilibria are socially optimal.",ariel orda,Convergence,2007.0,10.1109/JSAC.2007.070811,IEEE Journal on Selected Areas in Communications,Banner2007,False,,IEEE,Not available,Bottleneck Routing Games in Communication Networks,6e4bebc959c5e449d56dba0cd3746284,https://ieeexplore.ieee.org/document/4278417/
11122,"We consider routing games where the performance of each user is dictated by the worst (bottleneck) element it employs. We are given a network, finitely many (selfish) users, each associated with a positive flow demand, and a load-dependent performance function for each network element; the social (i.e., system) objective is to optimize the performance of the worst element in the network (i.e., the network bottleneck). Although we show that such ""bottleneck"" routing games appear in a variety of practical scenarios, they have not been considered yet. Accordingly, we study their properties, considering two routing scenarios, namely when a user can split its traffic over more than one path (splittable bottleneck game) and when it cannot (unsplittable bottleneck game). First, we prove that, for both splittable and unsplittable bottleneck games, there is a (not necessarily unique) Nash equilibrium. Then, we consider the rate of convergence to a Nash equilibrium in each game. Finally, we investigate the efficiency of the Nash equilibria in both games with respect to the social optimum; specifically, while for both games we show that the price of anarchy is unbounded, we identify for each game conditions under which Nash equilibria are socially optimal.",ariel orda,Communication system control,2007.0,10.1109/JSAC.2007.070811,IEEE Journal on Selected Areas in Communications,Banner2007,False,,IEEE,Not available,Bottleneck Routing Games in Communication Networks,6e4bebc959c5e449d56dba0cd3746284,https://ieeexplore.ieee.org/document/4278417/
11123,"We consider routing games where the performance of each user is dictated by the worst (bottleneck) element it employs. We are given a network, finitely many (selfish) users, each associated with a positive flow demand, and a load-dependent performance function for each network element; the social (i.e., system) objective is to optimize the performance of the worst element in the network (i.e., the network bottleneck). Although we show that such ""bottleneck"" routing games appear in a variety of practical scenarios, they have not been considered yet. Accordingly, we study their properties, considering two routing scenarios, namely when a user can split its traffic over more than one path (splittable bottleneck game) and when it cannot (unsplittable bottleneck game). First, we prove that, for both splittable and unsplittable bottleneck games, there is a (not necessarily unique) Nash equilibrium. Then, we consider the rate of convergence to a Nash equilibrium in each game. Finally, we investigate the efficiency of the Nash equilibria in both games with respect to the social optimum; specifically, while for both games we show that the price of anarchy is unbounded, we identify for each game conditions under which Nash equilibria are socially optimal.",ariel orda,Large-scale systems,2007.0,10.1109/JSAC.2007.070811,IEEE Journal on Selected Areas in Communications,Banner2007,False,,IEEE,Not available,Bottleneck Routing Games in Communication Networks,6e4bebc959c5e449d56dba0cd3746284,https://ieeexplore.ieee.org/document/4278417/
11124,"The Wireless Mesh Network (WMN) has already been recognized as a promising broadband access network technology from both academic and commercial perspective. In order to improve the performance of WMNs, extensive research efforts have been dedicated towards finding means to increase the number of simultaneous transmissions in the network while avoiding signal interference among radios. In case of WMNs based on IEEE 802.11 b/g standards, most recent research works have relied upon the usage of orthogonal channels for solving the Channel Assignment (CA) problem. In this paper, we explore the possibility of exploiting Partially Overlapped Channels (POCs) by introducing a novel game theoretic distributed CA algorithm. Our proposed algorithm outperforms both the conventional orthogonal channel approach and the recent heuristic CA algorithms using POC. The proposed algorithm is shown to achieve near-optimal performance in the average case. In addition, the upper bound Price of Anarchy for Multi-Radio Multi-Channel (MRMC) networks is derived to evaluate the effectiveness of the proposed approach.",pedro duarte,Wireless Mesh Networks (WMNs),2012.0,10.1109/JSAC.2012.120111,IEEE Journal on Selected Areas in Communications,Duarte2012,False,,IEEE,Not available,On the Partially Overlapped Channel Assignment on Wireless Mesh Network Backbone: A Game Theoretic Approach,bc6491ceea7fbf858df9ef47db4a17fe,https://ieeexplore.ieee.org/document/6117767/
11125,"The Wireless Mesh Network (WMN) has already been recognized as a promising broadband access network technology from both academic and commercial perspective. In order to improve the performance of WMNs, extensive research efforts have been dedicated towards finding means to increase the number of simultaneous transmissions in the network while avoiding signal interference among radios. In case of WMNs based on IEEE 802.11 b/g standards, most recent research works have relied upon the usage of orthogonal channels for solving the Channel Assignment (CA) problem. In this paper, we explore the possibility of exploiting Partially Overlapped Channels (POCs) by introducing a novel game theoretic distributed CA algorithm. Our proposed algorithm outperforms both the conventional orthogonal channel approach and the recent heuristic CA algorithms using POC. The proposed algorithm is shown to achieve near-optimal performance in the average case. In addition, the upper bound Price of Anarchy for Multi-Radio Multi-Channel (MRMC) networks is derived to evaluate the effectiveness of the proposed approach.",pedro duarte,channel assignment problem,2012.0,10.1109/JSAC.2012.120111,IEEE Journal on Selected Areas in Communications,Duarte2012,False,,IEEE,Not available,On the Partially Overlapped Channel Assignment on Wireless Mesh Network Backbone: A Game Theoretic Approach,bc6491ceea7fbf858df9ef47db4a17fe,https://ieeexplore.ieee.org/document/6117767/
11126,"The Wireless Mesh Network (WMN) has already been recognized as a promising broadband access network technology from both academic and commercial perspective. In order to improve the performance of WMNs, extensive research efforts have been dedicated towards finding means to increase the number of simultaneous transmissions in the network while avoiding signal interference among radios. In case of WMNs based on IEEE 802.11 b/g standards, most recent research works have relied upon the usage of orthogonal channels for solving the Channel Assignment (CA) problem. In this paper, we explore the possibility of exploiting Partially Overlapped Channels (POCs) by introducing a novel game theoretic distributed CA algorithm. Our proposed algorithm outperforms both the conventional orthogonal channel approach and the recent heuristic CA algorithms using POC. The proposed algorithm is shown to achieve near-optimal performance in the average case. In addition, the upper bound Price of Anarchy for Multi-Radio Multi-Channel (MRMC) networks is derived to evaluate the effectiveness of the proposed approach.",pedro duarte,partially overlapped channels,2012.0,10.1109/JSAC.2012.120111,IEEE Journal on Selected Areas in Communications,Duarte2012,False,,IEEE,Not available,On the Partially Overlapped Channel Assignment on Wireless Mesh Network Backbone: A Game Theoretic Approach,bc6491ceea7fbf858df9ef47db4a17fe,https://ieeexplore.ieee.org/document/6117767/
11127,"The Wireless Mesh Network (WMN) has already been recognized as a promising broadband access network technology from both academic and commercial perspective. In order to improve the performance of WMNs, extensive research efforts have been dedicated towards finding means to increase the number of simultaneous transmissions in the network while avoiding signal interference among radios. In case of WMNs based on IEEE 802.11 b/g standards, most recent research works have relied upon the usage of orthogonal channels for solving the Channel Assignment (CA) problem. In this paper, we explore the possibility of exploiting Partially Overlapped Channels (POCs) by introducing a novel game theoretic distributed CA algorithm. Our proposed algorithm outperforms both the conventional orthogonal channel approach and the recent heuristic CA algorithms using POC. The proposed algorithm is shown to achieve near-optimal performance in the average case. In addition, the upper bound Price of Anarchy for Multi-Radio Multi-Channel (MRMC) networks is derived to evaluate the effectiveness of the proposed approach.",pedro duarte,game theory,2012.0,10.1109/JSAC.2012.120111,IEEE Journal on Selected Areas in Communications,Duarte2012,False,,IEEE,Not available,On the Partially Overlapped Channel Assignment on Wireless Mesh Network Backbone: A Game Theoretic Approach,bc6491ceea7fbf858df9ef47db4a17fe,https://ieeexplore.ieee.org/document/6117767/
11128,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11129,"The Wireless Mesh Network (WMN) has already been recognized as a promising broadband access network technology from both academic and commercial perspective. In order to improve the performance of WMNs, extensive research efforts have been dedicated towards finding means to increase the number of simultaneous transmissions in the network while avoiding signal interference among radios. In case of WMNs based on IEEE 802.11 b/g standards, most recent research works have relied upon the usage of orthogonal channels for solving the Channel Assignment (CA) problem. In this paper, we explore the possibility of exploiting Partially Overlapped Channels (POCs) by introducing a novel game theoretic distributed CA algorithm. Our proposed algorithm outperforms both the conventional orthogonal channel approach and the recent heuristic CA algorithms using POC. The proposed algorithm is shown to achieve near-optimal performance in the average case. In addition, the upper bound Price of Anarchy for Multi-Radio Multi-Channel (MRMC) networks is derived to evaluate the effectiveness of the proposed approach.",pedro duarte,potential games,2012.0,10.1109/JSAC.2012.120111,IEEE Journal on Selected Areas in Communications,Duarte2012,False,,IEEE,Not available,On the Partially Overlapped Channel Assignment on Wireless Mesh Network Backbone: A Game Theoretic Approach,bc6491ceea7fbf858df9ef47db4a17fe,https://ieeexplore.ieee.org/document/6117767/
11130,"The Wireless Mesh Network (WMN) has already been recognized as a promising broadband access network technology from both academic and commercial perspective. In order to improve the performance of WMNs, extensive research efforts have been dedicated towards finding means to increase the number of simultaneous transmissions in the network while avoiding signal interference among radios. In case of WMNs based on IEEE 802.11 b/g standards, most recent research works have relied upon the usage of orthogonal channels for solving the Channel Assignment (CA) problem. In this paper, we explore the possibility of exploiting Partially Overlapped Channels (POCs) by introducing a novel game theoretic distributed CA algorithm. Our proposed algorithm outperforms both the conventional orthogonal channel approach and the recent heuristic CA algorithms using POC. The proposed algorithm is shown to achieve near-optimal performance in the average case. In addition, the upper bound Price of Anarchy for Multi-Radio Multi-Channel (MRMC) networks is derived to evaluate the effectiveness of the proposed approach.",zubair fadlullah,Wireless Mesh Networks (WMNs),2012.0,10.1109/JSAC.2012.120111,IEEE Journal on Selected Areas in Communications,Duarte2012,False,,IEEE,Not available,On the Partially Overlapped Channel Assignment on Wireless Mesh Network Backbone: A Game Theoretic Approach,bc6491ceea7fbf858df9ef47db4a17fe,https://ieeexplore.ieee.org/document/6117767/
11131,"The Wireless Mesh Network (WMN) has already been recognized as a promising broadband access network technology from both academic and commercial perspective. In order to improve the performance of WMNs, extensive research efforts have been dedicated towards finding means to increase the number of simultaneous transmissions in the network while avoiding signal interference among radios. In case of WMNs based on IEEE 802.11 b/g standards, most recent research works have relied upon the usage of orthogonal channels for solving the Channel Assignment (CA) problem. In this paper, we explore the possibility of exploiting Partially Overlapped Channels (POCs) by introducing a novel game theoretic distributed CA algorithm. Our proposed algorithm outperforms both the conventional orthogonal channel approach and the recent heuristic CA algorithms using POC. The proposed algorithm is shown to achieve near-optimal performance in the average case. In addition, the upper bound Price of Anarchy for Multi-Radio Multi-Channel (MRMC) networks is derived to evaluate the effectiveness of the proposed approach.",zubair fadlullah,channel assignment problem,2012.0,10.1109/JSAC.2012.120111,IEEE Journal on Selected Areas in Communications,Duarte2012,False,,IEEE,Not available,On the Partially Overlapped Channel Assignment on Wireless Mesh Network Backbone: A Game Theoretic Approach,bc6491ceea7fbf858df9ef47db4a17fe,https://ieeexplore.ieee.org/document/6117767/
11132,"The Wireless Mesh Network (WMN) has already been recognized as a promising broadband access network technology from both academic and commercial perspective. In order to improve the performance of WMNs, extensive research efforts have been dedicated towards finding means to increase the number of simultaneous transmissions in the network while avoiding signal interference among radios. In case of WMNs based on IEEE 802.11 b/g standards, most recent research works have relied upon the usage of orthogonal channels for solving the Channel Assignment (CA) problem. In this paper, we explore the possibility of exploiting Partially Overlapped Channels (POCs) by introducing a novel game theoretic distributed CA algorithm. Our proposed algorithm outperforms both the conventional orthogonal channel approach and the recent heuristic CA algorithms using POC. The proposed algorithm is shown to achieve near-optimal performance in the average case. In addition, the upper bound Price of Anarchy for Multi-Radio Multi-Channel (MRMC) networks is derived to evaluate the effectiveness of the proposed approach.",zubair fadlullah,partially overlapped channels,2012.0,10.1109/JSAC.2012.120111,IEEE Journal on Selected Areas in Communications,Duarte2012,False,,IEEE,Not available,On the Partially Overlapped Channel Assignment on Wireless Mesh Network Backbone: A Game Theoretic Approach,bc6491ceea7fbf858df9ef47db4a17fe,https://ieeexplore.ieee.org/document/6117767/
11133,"The Wireless Mesh Network (WMN) has already been recognized as a promising broadband access network technology from both academic and commercial perspective. In order to improve the performance of WMNs, extensive research efforts have been dedicated towards finding means to increase the number of simultaneous transmissions in the network while avoiding signal interference among radios. In case of WMNs based on IEEE 802.11 b/g standards, most recent research works have relied upon the usage of orthogonal channels for solving the Channel Assignment (CA) problem. In this paper, we explore the possibility of exploiting Partially Overlapped Channels (POCs) by introducing a novel game theoretic distributed CA algorithm. Our proposed algorithm outperforms both the conventional orthogonal channel approach and the recent heuristic CA algorithms using POC. The proposed algorithm is shown to achieve near-optimal performance in the average case. In addition, the upper bound Price of Anarchy for Multi-Radio Multi-Channel (MRMC) networks is derived to evaluate the effectiveness of the proposed approach.",zubair fadlullah,game theory,2012.0,10.1109/JSAC.2012.120111,IEEE Journal on Selected Areas in Communications,Duarte2012,False,,IEEE,Not available,On the Partially Overlapped Channel Assignment on Wireless Mesh Network Backbone: A Game Theoretic Approach,bc6491ceea7fbf858df9ef47db4a17fe,https://ieeexplore.ieee.org/document/6117767/
11134,"The Wireless Mesh Network (WMN) has already been recognized as a promising broadband access network technology from both academic and commercial perspective. In order to improve the performance of WMNs, extensive research efforts have been dedicated towards finding means to increase the number of simultaneous transmissions in the network while avoiding signal interference among radios. In case of WMNs based on IEEE 802.11 b/g standards, most recent research works have relied upon the usage of orthogonal channels for solving the Channel Assignment (CA) problem. In this paper, we explore the possibility of exploiting Partially Overlapped Channels (POCs) by introducing a novel game theoretic distributed CA algorithm. Our proposed algorithm outperforms both the conventional orthogonal channel approach and the recent heuristic CA algorithms using POC. The proposed algorithm is shown to achieve near-optimal performance in the average case. In addition, the upper bound Price of Anarchy for Multi-Radio Multi-Channel (MRMC) networks is derived to evaluate the effectiveness of the proposed approach.",zubair fadlullah,potential games,2012.0,10.1109/JSAC.2012.120111,IEEE Journal on Selected Areas in Communications,Duarte2012,False,,IEEE,Not available,On the Partially Overlapped Channel Assignment on Wireless Mesh Network Backbone: A Game Theoretic Approach,bc6491ceea7fbf858df9ef47db4a17fe,https://ieeexplore.ieee.org/document/6117767/
11135,"The Wireless Mesh Network (WMN) has already been recognized as a promising broadband access network technology from both academic and commercial perspective. In order to improve the performance of WMNs, extensive research efforts have been dedicated towards finding means to increase the number of simultaneous transmissions in the network while avoiding signal interference among radios. In case of WMNs based on IEEE 802.11 b/g standards, most recent research works have relied upon the usage of orthogonal channels for solving the Channel Assignment (CA) problem. In this paper, we explore the possibility of exploiting Partially Overlapped Channels (POCs) by introducing a novel game theoretic distributed CA algorithm. Our proposed algorithm outperforms both the conventional orthogonal channel approach and the recent heuristic CA algorithms using POC. The proposed algorithm is shown to achieve near-optimal performance in the average case. In addition, the upper bound Price of Anarchy for Multi-Radio Multi-Channel (MRMC) networks is derived to evaluate the effectiveness of the proposed approach.",athanasios vasilakos,Wireless Mesh Networks (WMNs),2012.0,10.1109/JSAC.2012.120111,IEEE Journal on Selected Areas in Communications,Duarte2012,False,,IEEE,Not available,On the Partially Overlapped Channel Assignment on Wireless Mesh Network Backbone: A Game Theoretic Approach,bc6491ceea7fbf858df9ef47db4a17fe,https://ieeexplore.ieee.org/document/6117767/
11136,"The Wireless Mesh Network (WMN) has already been recognized as a promising broadband access network technology from both academic and commercial perspective. In order to improve the performance of WMNs, extensive research efforts have been dedicated towards finding means to increase the number of simultaneous transmissions in the network while avoiding signal interference among radios. In case of WMNs based on IEEE 802.11 b/g standards, most recent research works have relied upon the usage of orthogonal channels for solving the Channel Assignment (CA) problem. In this paper, we explore the possibility of exploiting Partially Overlapped Channels (POCs) by introducing a novel game theoretic distributed CA algorithm. Our proposed algorithm outperforms both the conventional orthogonal channel approach and the recent heuristic CA algorithms using POC. The proposed algorithm is shown to achieve near-optimal performance in the average case. In addition, the upper bound Price of Anarchy for Multi-Radio Multi-Channel (MRMC) networks is derived to evaluate the effectiveness of the proposed approach.",athanasios vasilakos,channel assignment problem,2012.0,10.1109/JSAC.2012.120111,IEEE Journal on Selected Areas in Communications,Duarte2012,False,,IEEE,Not available,On the Partially Overlapped Channel Assignment on Wireless Mesh Network Backbone: A Game Theoretic Approach,bc6491ceea7fbf858df9ef47db4a17fe,https://ieeexplore.ieee.org/document/6117767/
11137,"The Wireless Mesh Network (WMN) has already been recognized as a promising broadband access network technology from both academic and commercial perspective. In order to improve the performance of WMNs, extensive research efforts have been dedicated towards finding means to increase the number of simultaneous transmissions in the network while avoiding signal interference among radios. In case of WMNs based on IEEE 802.11 b/g standards, most recent research works have relied upon the usage of orthogonal channels for solving the Channel Assignment (CA) problem. In this paper, we explore the possibility of exploiting Partially Overlapped Channels (POCs) by introducing a novel game theoretic distributed CA algorithm. Our proposed algorithm outperforms both the conventional orthogonal channel approach and the recent heuristic CA algorithms using POC. The proposed algorithm is shown to achieve near-optimal performance in the average case. In addition, the upper bound Price of Anarchy for Multi-Radio Multi-Channel (MRMC) networks is derived to evaluate the effectiveness of the proposed approach.",athanasios vasilakos,partially overlapped channels,2012.0,10.1109/JSAC.2012.120111,IEEE Journal on Selected Areas in Communications,Duarte2012,False,,IEEE,Not available,On the Partially Overlapped Channel Assignment on Wireless Mesh Network Backbone: A Game Theoretic Approach,bc6491ceea7fbf858df9ef47db4a17fe,https://ieeexplore.ieee.org/document/6117767/
11138,"The Wireless Mesh Network (WMN) has already been recognized as a promising broadband access network technology from both academic and commercial perspective. In order to improve the performance of WMNs, extensive research efforts have been dedicated towards finding means to increase the number of simultaneous transmissions in the network while avoiding signal interference among radios. In case of WMNs based on IEEE 802.11 b/g standards, most recent research works have relied upon the usage of orthogonal channels for solving the Channel Assignment (CA) problem. In this paper, we explore the possibility of exploiting Partially Overlapped Channels (POCs) by introducing a novel game theoretic distributed CA algorithm. Our proposed algorithm outperforms both the conventional orthogonal channel approach and the recent heuristic CA algorithms using POC. The proposed algorithm is shown to achieve near-optimal performance in the average case. In addition, the upper bound Price of Anarchy for Multi-Radio Multi-Channel (MRMC) networks is derived to evaluate the effectiveness of the proposed approach.",athanasios vasilakos,game theory,2012.0,10.1109/JSAC.2012.120111,IEEE Journal on Selected Areas in Communications,Duarte2012,False,,IEEE,Not available,On the Partially Overlapped Channel Assignment on Wireless Mesh Network Backbone: A Game Theoretic Approach,bc6491ceea7fbf858df9ef47db4a17fe,https://ieeexplore.ieee.org/document/6117767/
11139,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11140,"The Wireless Mesh Network (WMN) has already been recognized as a promising broadband access network technology from both academic and commercial perspective. In order to improve the performance of WMNs, extensive research efforts have been dedicated towards finding means to increase the number of simultaneous transmissions in the network while avoiding signal interference among radios. In case of WMNs based on IEEE 802.11 b/g standards, most recent research works have relied upon the usage of orthogonal channels for solving the Channel Assignment (CA) problem. In this paper, we explore the possibility of exploiting Partially Overlapped Channels (POCs) by introducing a novel game theoretic distributed CA algorithm. Our proposed algorithm outperforms both the conventional orthogonal channel approach and the recent heuristic CA algorithms using POC. The proposed algorithm is shown to achieve near-optimal performance in the average case. In addition, the upper bound Price of Anarchy for Multi-Radio Multi-Channel (MRMC) networks is derived to evaluate the effectiveness of the proposed approach.",athanasios vasilakos,potential games,2012.0,10.1109/JSAC.2012.120111,IEEE Journal on Selected Areas in Communications,Duarte2012,False,,IEEE,Not available,On the Partially Overlapped Channel Assignment on Wireless Mesh Network Backbone: A Game Theoretic Approach,bc6491ceea7fbf858df9ef47db4a17fe,https://ieeexplore.ieee.org/document/6117767/
11141,"The Wireless Mesh Network (WMN) has already been recognized as a promising broadband access network technology from both academic and commercial perspective. In order to improve the performance of WMNs, extensive research efforts have been dedicated towards finding means to increase the number of simultaneous transmissions in the network while avoiding signal interference among radios. In case of WMNs based on IEEE 802.11 b/g standards, most recent research works have relied upon the usage of orthogonal channels for solving the Channel Assignment (CA) problem. In this paper, we explore the possibility of exploiting Partially Overlapped Channels (POCs) by introducing a novel game theoretic distributed CA algorithm. Our proposed algorithm outperforms both the conventional orthogonal channel approach and the recent heuristic CA algorithms using POC. The proposed algorithm is shown to achieve near-optimal performance in the average case. In addition, the upper bound Price of Anarchy for Multi-Radio Multi-Channel (MRMC) networks is derived to evaluate the effectiveness of the proposed approach.",nei kato,Wireless Mesh Networks (WMNs),2012.0,10.1109/JSAC.2012.120111,IEEE Journal on Selected Areas in Communications,Duarte2012,False,,IEEE,Not available,On the Partially Overlapped Channel Assignment on Wireless Mesh Network Backbone: A Game Theoretic Approach,bc6491ceea7fbf858df9ef47db4a17fe,https://ieeexplore.ieee.org/document/6117767/
11142,"The Wireless Mesh Network (WMN) has already been recognized as a promising broadband access network technology from both academic and commercial perspective. In order to improve the performance of WMNs, extensive research efforts have been dedicated towards finding means to increase the number of simultaneous transmissions in the network while avoiding signal interference among radios. In case of WMNs based on IEEE 802.11 b/g standards, most recent research works have relied upon the usage of orthogonal channels for solving the Channel Assignment (CA) problem. In this paper, we explore the possibility of exploiting Partially Overlapped Channels (POCs) by introducing a novel game theoretic distributed CA algorithm. Our proposed algorithm outperforms both the conventional orthogonal channel approach and the recent heuristic CA algorithms using POC. The proposed algorithm is shown to achieve near-optimal performance in the average case. In addition, the upper bound Price of Anarchy for Multi-Radio Multi-Channel (MRMC) networks is derived to evaluate the effectiveness of the proposed approach.",nei kato,channel assignment problem,2012.0,10.1109/JSAC.2012.120111,IEEE Journal on Selected Areas in Communications,Duarte2012,False,,IEEE,Not available,On the Partially Overlapped Channel Assignment on Wireless Mesh Network Backbone: A Game Theoretic Approach,bc6491ceea7fbf858df9ef47db4a17fe,https://ieeexplore.ieee.org/document/6117767/
11143,"The Wireless Mesh Network (WMN) has already been recognized as a promising broadband access network technology from both academic and commercial perspective. In order to improve the performance of WMNs, extensive research efforts have been dedicated towards finding means to increase the number of simultaneous transmissions in the network while avoiding signal interference among radios. In case of WMNs based on IEEE 802.11 b/g standards, most recent research works have relied upon the usage of orthogonal channels for solving the Channel Assignment (CA) problem. In this paper, we explore the possibility of exploiting Partially Overlapped Channels (POCs) by introducing a novel game theoretic distributed CA algorithm. Our proposed algorithm outperforms both the conventional orthogonal channel approach and the recent heuristic CA algorithms using POC. The proposed algorithm is shown to achieve near-optimal performance in the average case. In addition, the upper bound Price of Anarchy for Multi-Radio Multi-Channel (MRMC) networks is derived to evaluate the effectiveness of the proposed approach.",nei kato,partially overlapped channels,2012.0,10.1109/JSAC.2012.120111,IEEE Journal on Selected Areas in Communications,Duarte2012,False,,IEEE,Not available,On the Partially Overlapped Channel Assignment on Wireless Mesh Network Backbone: A Game Theoretic Approach,bc6491ceea7fbf858df9ef47db4a17fe,https://ieeexplore.ieee.org/document/6117767/
11144,"The Wireless Mesh Network (WMN) has already been recognized as a promising broadband access network technology from both academic and commercial perspective. In order to improve the performance of WMNs, extensive research efforts have been dedicated towards finding means to increase the number of simultaneous transmissions in the network while avoiding signal interference among radios. In case of WMNs based on IEEE 802.11 b/g standards, most recent research works have relied upon the usage of orthogonal channels for solving the Channel Assignment (CA) problem. In this paper, we explore the possibility of exploiting Partially Overlapped Channels (POCs) by introducing a novel game theoretic distributed CA algorithm. Our proposed algorithm outperforms both the conventional orthogonal channel approach and the recent heuristic CA algorithms using POC. The proposed algorithm is shown to achieve near-optimal performance in the average case. In addition, the upper bound Price of Anarchy for Multi-Radio Multi-Channel (MRMC) networks is derived to evaluate the effectiveness of the proposed approach.",nei kato,game theory,2012.0,10.1109/JSAC.2012.120111,IEEE Journal on Selected Areas in Communications,Duarte2012,False,,IEEE,Not available,On the Partially Overlapped Channel Assignment on Wireless Mesh Network Backbone: A Game Theoretic Approach,bc6491ceea7fbf858df9ef47db4a17fe,https://ieeexplore.ieee.org/document/6117767/
11145,"The Wireless Mesh Network (WMN) has already been recognized as a promising broadband access network technology from both academic and commercial perspective. In order to improve the performance of WMNs, extensive research efforts have been dedicated towards finding means to increase the number of simultaneous transmissions in the network while avoiding signal interference among radios. In case of WMNs based on IEEE 802.11 b/g standards, most recent research works have relied upon the usage of orthogonal channels for solving the Channel Assignment (CA) problem. In this paper, we explore the possibility of exploiting Partially Overlapped Channels (POCs) by introducing a novel game theoretic distributed CA algorithm. Our proposed algorithm outperforms both the conventional orthogonal channel approach and the recent heuristic CA algorithms using POC. The proposed algorithm is shown to achieve near-optimal performance in the average case. In addition, the upper bound Price of Anarchy for Multi-Radio Multi-Channel (MRMC) networks is derived to evaluate the effectiveness of the proposed approach.",nei kato,potential games,2012.0,10.1109/JSAC.2012.120111,IEEE Journal on Selected Areas in Communications,Duarte2012,False,,IEEE,Not available,On the Partially Overlapped Channel Assignment on Wireless Mesh Network Backbone: A Game Theoretic Approach,bc6491ceea7fbf858df9ef47db4a17fe,https://ieeexplore.ieee.org/document/6117767/
11146,"Malicious softwares or malwares for short have become a major security threat. While originating in criminal behavior, their impact are also influenced by the decisions of legitimate end users. Getting agents in the Internet, and in networks in general, to invest in and deploy security features and protocols is a challenge, in particular because of economic reasons arising from the presence of network externalities. In this paper, we focus on the question of incentive alignment for agents of a large network towards a better security. We start with an economic model for a single agent, that determines the optimal amount to invest in protection. The model takes into account the vulnerability of the agent to a security breach and the potential loss if a security breach occurs. We derive conditions on the quality of the protection to ensure that the optimal amount spent on security is an increasing function of the agent's vulnerability and potential loss. We also show that for a large class of risks, only a small fraction of the expected loss should be invested. Building on these results, we study a network of interconnected agents subject to epidemic risks. We derive conditions to ensure that the incentives of all agents are aligned towards a better security. When agents are strategic, we show that security investments are always socially inefficient due to the network externalities. Moreover alignment of incentives typically implies a coordination problem, leading to an equilibrium with a very high price of anarchy.",marc lelarge,Economics of Information Security,2012.0,10.1109/JSAC.2012.121213,IEEE Journal on Selected Areas in Communications,Lelarge2012,False,,IEEE,Not available,Coordination in Network Security Games: A Monotone Comparative Statics Approach,5a5c1851d512f2df11c1a0cedc722ae7,https://ieeexplore.ieee.org/document/6354279/
11147,"Malicious softwares or malwares for short have become a major security threat. While originating in criminal behavior, their impact are also influenced by the decisions of legitimate end users. Getting agents in the Internet, and in networks in general, to invest in and deploy security features and protocols is a challenge, in particular because of economic reasons arising from the presence of network externalities. In this paper, we focus on the question of incentive alignment for agents of a large network towards a better security. We start with an economic model for a single agent, that determines the optimal amount to invest in protection. The model takes into account the vulnerability of the agent to a security breach and the potential loss if a security breach occurs. We derive conditions on the quality of the protection to ensure that the optimal amount spent on security is an increasing function of the agent's vulnerability and potential loss. We also show that for a large class of risks, only a small fraction of the expected loss should be invested. Building on these results, we study a network of interconnected agents subject to epidemic risks. We derive conditions to ensure that the incentives of all agents are aligned towards a better security. When agents are strategic, we show that security investments are always socially inefficient due to the network externalities. Moreover alignment of incentives typically implies a coordination problem, leading to an equilibrium with a very high price of anarchy.",marc lelarge,Optimal Security Investment,2012.0,10.1109/JSAC.2012.121213,IEEE Journal on Selected Areas in Communications,Lelarge2012,False,,IEEE,Not available,Coordination in Network Security Games: A Monotone Comparative Statics Approach,5a5c1851d512f2df11c1a0cedc722ae7,https://ieeexplore.ieee.org/document/6354279/
11148,"Malicious softwares or malwares for short have become a major security threat. While originating in criminal behavior, their impact are also influenced by the decisions of legitimate end users. Getting agents in the Internet, and in networks in general, to invest in and deploy security features and protocols is a challenge, in particular because of economic reasons arising from the presence of network externalities. In this paper, we focus on the question of incentive alignment for agents of a large network towards a better security. We start with an economic model for a single agent, that determines the optimal amount to invest in protection. The model takes into account the vulnerability of the agent to a security breach and the potential loss if a security breach occurs. We derive conditions on the quality of the protection to ensure that the optimal amount spent on security is an increasing function of the agent's vulnerability and potential loss. We also show that for a large class of risks, only a small fraction of the expected loss should be invested. Building on these results, we study a network of interconnected agents subject to epidemic risks. We derive conditions to ensure that the incentives of all agents are aligned towards a better security. When agents are strategic, we show that security investments are always socially inefficient due to the network externalities. Moreover alignment of incentives typically implies a coordination problem, leading to an equilibrium with a very high price of anarchy.",marc lelarge,Game Theory,2012.0,10.1109/JSAC.2012.121213,IEEE Journal on Selected Areas in Communications,Lelarge2012,False,,IEEE,Not available,Coordination in Network Security Games: A Monotone Comparative Statics Approach,5a5c1851d512f2df11c1a0cedc722ae7,https://ieeexplore.ieee.org/document/6354279/
11149,"Malicious softwares or malwares for short have become a major security threat. While originating in criminal behavior, their impact are also influenced by the decisions of legitimate end users. Getting agents in the Internet, and in networks in general, to invest in and deploy security features and protocols is a challenge, in particular because of economic reasons arising from the presence of network externalities. In this paper, we focus on the question of incentive alignment for agents of a large network towards a better security. We start with an economic model for a single agent, that determines the optimal amount to invest in protection. The model takes into account the vulnerability of the agent to a security breach and the potential loss if a security breach occurs. We derive conditions on the quality of the protection to ensure that the optimal amount spent on security is an increasing function of the agent's vulnerability and potential loss. We also show that for a large class of risks, only a small fraction of the expected loss should be invested. Building on these results, we study a network of interconnected agents subject to epidemic risks. We derive conditions to ensure that the incentives of all agents are aligned towards a better security. When agents are strategic, we show that security investments are always socially inefficient due to the network externalities. Moreover alignment of incentives typically implies a coordination problem, leading to an equilibrium with a very high price of anarchy.",marc lelarge,Network Effects,2012.0,10.1109/JSAC.2012.121213,IEEE Journal on Selected Areas in Communications,Lelarge2012,False,,IEEE,Not available,Coordination in Network Security Games: A Monotone Comparative Statics Approach,5a5c1851d512f2df11c1a0cedc722ae7,https://ieeexplore.ieee.org/document/6354279/
11150,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11151,"Malicious softwares or malwares for short have become a major security threat. While originating in criminal behavior, their impact are also influenced by the decisions of legitimate end users. Getting agents in the Internet, and in networks in general, to invest in and deploy security features and protocols is a challenge, in particular because of economic reasons arising from the presence of network externalities. In this paper, we focus on the question of incentive alignment for agents of a large network towards a better security. We start with an economic model for a single agent, that determines the optimal amount to invest in protection. The model takes into account the vulnerability of the agent to a security breach and the potential loss if a security breach occurs. We derive conditions on the quality of the protection to ensure that the optimal amount spent on security is an increasing function of the agent's vulnerability and potential loss. We also show that for a large class of risks, only a small fraction of the expected loss should be invested. Building on these results, we study a network of interconnected agents subject to epidemic risks. We derive conditions to ensure that the incentives of all agents are aligned towards a better security. When agents are strategic, we show that security investments are always socially inefficient due to the network externalities. Moreover alignment of incentives typically implies a coordination problem, leading to an equilibrium with a very high price of anarchy.",marc lelarge,Incentives,2012.0,10.1109/JSAC.2012.121213,IEEE Journal on Selected Areas in Communications,Lelarge2012,False,,IEEE,Not available,Coordination in Network Security Games: A Monotone Comparative Statics Approach,5a5c1851d512f2df11c1a0cedc722ae7,https://ieeexplore.ieee.org/document/6354279/
11152,"Sharing economy is a distributed peer-to-peer economic paradigm, which gives rise to a variety of social interactions for economic purposes. One fundamental distributed decision-making process is coalition formation for sharing certain replaceable resources collaboratively, for example, sharing hotel rooms among travelers, sharing taxi-rides among passengers, and sharing regular passes among users. Motivated by the applications of sharing economy, this paper studies a coalition formation game subject to the capacity of &lt;formula&gt;&lt;tex&gt;$K$&lt;/tex&gt;&lt;/formula&gt; participants per coalition. The participants in each coalition are supposed to split the associated cost according to a given cost-sharing mechanism. A stable coalition structure is established when no group of participants can opt out to form another coalition that leads to lower individual payments. We quantify the inefficiency of distributed decision-making processes under a cost-sharing mechanism by the strong price of anarchy (SPoA), comparing a worst-case stable coalition structure and a social optimum. In particular, we derive SPoA for common fair cost-sharing mechanisms (e.g., equal-split, proportional-split, egalitarian and Nash bargaining solutions of bargaining games, and usage based cost-sharing). We show that the SPoA for equal-split, proportional-split, and usage based costsharing (under certain conditions) is &lt;formula&gt;&lt;tex&gt;$\Theta (\log K)$&lt;/tex&gt;&lt;/formula&gt;, whereas the one for egalitarian and Nash bargaining solutions is &lt;formula&gt;&lt;tex&gt;$O (\sqrt{K} \log K)$&lt;/tex&gt;&lt;/formula&gt;. Therefore, distributed decision-making processes under common fair cost-sharing mechanisms induce only moderate inefficiency.",chi-kin chau,Sharing economy,,10.1109/TCNS.2017.2763747,IEEE Transactions on Control of Network Systems,ChauNone,False,,IEEE,Not available,Quantifying Inefficiency of Fair Cost-Sharing Mechanisms for Sharing Economy,9e2de514989fbf60d9bd46f907d80a91,
11153,"Sharing economy is a distributed peer-to-peer economic paradigm, which gives rise to a variety of social interactions for economic purposes. One fundamental distributed decision-making process is coalition formation for sharing certain replaceable resources collaboratively, for example, sharing hotel rooms among travelers, sharing taxi-rides among passengers, and sharing regular passes among users. Motivated by the applications of sharing economy, this paper studies a coalition formation game subject to the capacity of &lt;formula&gt;&lt;tex&gt;$K$&lt;/tex&gt;&lt;/formula&gt; participants per coalition. The participants in each coalition are supposed to split the associated cost according to a given cost-sharing mechanism. A stable coalition structure is established when no group of participants can opt out to form another coalition that leads to lower individual payments. We quantify the inefficiency of distributed decision-making processes under a cost-sharing mechanism by the strong price of anarchy (SPoA), comparing a worst-case stable coalition structure and a social optimum. In particular, we derive SPoA for common fair cost-sharing mechanisms (e.g., equal-split, proportional-split, egalitarian and Nash bargaining solutions of bargaining games, and usage based cost-sharing). We show that the SPoA for equal-split, proportional-split, and usage based costsharing (under certain conditions) is &lt;formula&gt;&lt;tex&gt;$\Theta (\log K)$&lt;/tex&gt;&lt;/formula&gt;, whereas the one for egalitarian and Nash bargaining solutions is &lt;formula&gt;&lt;tex&gt;$O (\sqrt{K} \log K)$&lt;/tex&gt;&lt;/formula&gt;. Therefore, distributed decision-making processes under common fair cost-sharing mechanisms induce only moderate inefficiency.",chi-kin chau,coalition formation,,10.1109/TCNS.2017.2763747,IEEE Transactions on Control of Network Systems,ChauNone,False,,IEEE,Not available,Quantifying Inefficiency of Fair Cost-Sharing Mechanisms for Sharing Economy,9e2de514989fbf60d9bd46f907d80a91,
11154,"Sharing economy is a distributed peer-to-peer economic paradigm, which gives rise to a variety of social interactions for economic purposes. One fundamental distributed decision-making process is coalition formation for sharing certain replaceable resources collaboratively, for example, sharing hotel rooms among travelers, sharing taxi-rides among passengers, and sharing regular passes among users. Motivated by the applications of sharing economy, this paper studies a coalition formation game subject to the capacity of &lt;formula&gt;&lt;tex&gt;$K$&lt;/tex&gt;&lt;/formula&gt; participants per coalition. The participants in each coalition are supposed to split the associated cost according to a given cost-sharing mechanism. A stable coalition structure is established when no group of participants can opt out to form another coalition that leads to lower individual payments. We quantify the inefficiency of distributed decision-making processes under a cost-sharing mechanism by the strong price of anarchy (SPoA), comparing a worst-case stable coalition structure and a social optimum. In particular, we derive SPoA for common fair cost-sharing mechanisms (e.g., equal-split, proportional-split, egalitarian and Nash bargaining solutions of bargaining games, and usage based cost-sharing). We show that the SPoA for equal-split, proportional-split, and usage based costsharing (under certain conditions) is &lt;formula&gt;&lt;tex&gt;$\Theta (\log K)$&lt;/tex&gt;&lt;/formula&gt;, whereas the one for egalitarian and Nash bargaining solutions is &lt;formula&gt;&lt;tex&gt;$O (\sqrt{K} \log K)$&lt;/tex&gt;&lt;/formula&gt;. Therefore, distributed decision-making processes under common fair cost-sharing mechanisms induce only moderate inefficiency.",chi-kin chau,social and economic networks,,10.1109/TCNS.2017.2763747,IEEE Transactions on Control of Network Systems,ChauNone,False,,IEEE,Not available,Quantifying Inefficiency of Fair Cost-Sharing Mechanisms for Sharing Economy,9e2de514989fbf60d9bd46f907d80a91,
11155,"Sharing economy is a distributed peer-to-peer economic paradigm, which gives rise to a variety of social interactions for economic purposes. One fundamental distributed decision-making process is coalition formation for sharing certain replaceable resources collaboratively, for example, sharing hotel rooms among travelers, sharing taxi-rides among passengers, and sharing regular passes among users. Motivated by the applications of sharing economy, this paper studies a coalition formation game subject to the capacity of &lt;formula&gt;&lt;tex&gt;$K$&lt;/tex&gt;&lt;/formula&gt; participants per coalition. The participants in each coalition are supposed to split the associated cost according to a given cost-sharing mechanism. A stable coalition structure is established when no group of participants can opt out to form another coalition that leads to lower individual payments. We quantify the inefficiency of distributed decision-making processes under a cost-sharing mechanism by the strong price of anarchy (SPoA), comparing a worst-case stable coalition structure and a social optimum. In particular, we derive SPoA for common fair cost-sharing mechanisms (e.g., equal-split, proportional-split, egalitarian and Nash bargaining solutions of bargaining games, and usage based cost-sharing). We show that the SPoA for equal-split, proportional-split, and usage based costsharing (under certain conditions) is &lt;formula&gt;&lt;tex&gt;$\Theta (\log K)$&lt;/tex&gt;&lt;/formula&gt;, whereas the one for egalitarian and Nash bargaining solutions is &lt;formula&gt;&lt;tex&gt;$O (\sqrt{K} \log K)$&lt;/tex&gt;&lt;/formula&gt;. Therefore, distributed decision-making processes under common fair cost-sharing mechanisms induce only moderate inefficiency.",chi-kin chau,fair cost-sharing mechanisms,,10.1109/TCNS.2017.2763747,IEEE Transactions on Control of Network Systems,ChauNone,False,,IEEE,Not available,Quantifying Inefficiency of Fair Cost-Sharing Mechanisms for Sharing Economy,9e2de514989fbf60d9bd46f907d80a91,
11156,"Sharing economy is a distributed peer-to-peer economic paradigm, which gives rise to a variety of social interactions for economic purposes. One fundamental distributed decision-making process is coalition formation for sharing certain replaceable resources collaboratively, for example, sharing hotel rooms among travelers, sharing taxi-rides among passengers, and sharing regular passes among users. Motivated by the applications of sharing economy, this paper studies a coalition formation game subject to the capacity of &lt;formula&gt;&lt;tex&gt;$K$&lt;/tex&gt;&lt;/formula&gt; participants per coalition. The participants in each coalition are supposed to split the associated cost according to a given cost-sharing mechanism. A stable coalition structure is established when no group of participants can opt out to form another coalition that leads to lower individual payments. We quantify the inefficiency of distributed decision-making processes under a cost-sharing mechanism by the strong price of anarchy (SPoA), comparing a worst-case stable coalition structure and a social optimum. In particular, we derive SPoA for common fair cost-sharing mechanisms (e.g., equal-split, proportional-split, egalitarian and Nash bargaining solutions of bargaining games, and usage based cost-sharing). We show that the SPoA for equal-split, proportional-split, and usage based costsharing (under certain conditions) is &lt;formula&gt;&lt;tex&gt;$\Theta (\log K)$&lt;/tex&gt;&lt;/formula&gt;, whereas the one for egalitarian and Nash bargaining solutions is &lt;formula&gt;&lt;tex&gt;$O (\sqrt{K} \log K)$&lt;/tex&gt;&lt;/formula&gt;. Therefore, distributed decision-making processes under common fair cost-sharing mechanisms induce only moderate inefficiency.",khaled elbassioni,Sharing economy,,10.1109/TCNS.2017.2763747,IEEE Transactions on Control of Network Systems,ChauNone,False,,IEEE,Not available,Quantifying Inefficiency of Fair Cost-Sharing Mechanisms for Sharing Economy,9e2de514989fbf60d9bd46f907d80a91,
11157,"Sharing economy is a distributed peer-to-peer economic paradigm, which gives rise to a variety of social interactions for economic purposes. One fundamental distributed decision-making process is coalition formation for sharing certain replaceable resources collaboratively, for example, sharing hotel rooms among travelers, sharing taxi-rides among passengers, and sharing regular passes among users. Motivated by the applications of sharing economy, this paper studies a coalition formation game subject to the capacity of &lt;formula&gt;&lt;tex&gt;$K$&lt;/tex&gt;&lt;/formula&gt; participants per coalition. The participants in each coalition are supposed to split the associated cost according to a given cost-sharing mechanism. A stable coalition structure is established when no group of participants can opt out to form another coalition that leads to lower individual payments. We quantify the inefficiency of distributed decision-making processes under a cost-sharing mechanism by the strong price of anarchy (SPoA), comparing a worst-case stable coalition structure and a social optimum. In particular, we derive SPoA for common fair cost-sharing mechanisms (e.g., equal-split, proportional-split, egalitarian and Nash bargaining solutions of bargaining games, and usage based cost-sharing). We show that the SPoA for equal-split, proportional-split, and usage based costsharing (under certain conditions) is &lt;formula&gt;&lt;tex&gt;$\Theta (\log K)$&lt;/tex&gt;&lt;/formula&gt;, whereas the one for egalitarian and Nash bargaining solutions is &lt;formula&gt;&lt;tex&gt;$O (\sqrt{K} \log K)$&lt;/tex&gt;&lt;/formula&gt;. Therefore, distributed decision-making processes under common fair cost-sharing mechanisms induce only moderate inefficiency.",khaled elbassioni,coalition formation,,10.1109/TCNS.2017.2763747,IEEE Transactions on Control of Network Systems,ChauNone,False,,IEEE,Not available,Quantifying Inefficiency of Fair Cost-Sharing Mechanisms for Sharing Economy,9e2de514989fbf60d9bd46f907d80a91,
11158,"Sharing economy is a distributed peer-to-peer economic paradigm, which gives rise to a variety of social interactions for economic purposes. One fundamental distributed decision-making process is coalition formation for sharing certain replaceable resources collaboratively, for example, sharing hotel rooms among travelers, sharing taxi-rides among passengers, and sharing regular passes among users. Motivated by the applications of sharing economy, this paper studies a coalition formation game subject to the capacity of &lt;formula&gt;&lt;tex&gt;$K$&lt;/tex&gt;&lt;/formula&gt; participants per coalition. The participants in each coalition are supposed to split the associated cost according to a given cost-sharing mechanism. A stable coalition structure is established when no group of participants can opt out to form another coalition that leads to lower individual payments. We quantify the inefficiency of distributed decision-making processes under a cost-sharing mechanism by the strong price of anarchy (SPoA), comparing a worst-case stable coalition structure and a social optimum. In particular, we derive SPoA for common fair cost-sharing mechanisms (e.g., equal-split, proportional-split, egalitarian and Nash bargaining solutions of bargaining games, and usage based cost-sharing). We show that the SPoA for equal-split, proportional-split, and usage based costsharing (under certain conditions) is &lt;formula&gt;&lt;tex&gt;$\Theta (\log K)$&lt;/tex&gt;&lt;/formula&gt;, whereas the one for egalitarian and Nash bargaining solutions is &lt;formula&gt;&lt;tex&gt;$O (\sqrt{K} \log K)$&lt;/tex&gt;&lt;/formula&gt;. Therefore, distributed decision-making processes under common fair cost-sharing mechanisms induce only moderate inefficiency.",khaled elbassioni,social and economic networks,,10.1109/TCNS.2017.2763747,IEEE Transactions on Control of Network Systems,ChauNone,False,,IEEE,Not available,Quantifying Inefficiency of Fair Cost-Sharing Mechanisms for Sharing Economy,9e2de514989fbf60d9bd46f907d80a91,
11159,"Sharing economy is a distributed peer-to-peer economic paradigm, which gives rise to a variety of social interactions for economic purposes. One fundamental distributed decision-making process is coalition formation for sharing certain replaceable resources collaboratively, for example, sharing hotel rooms among travelers, sharing taxi-rides among passengers, and sharing regular passes among users. Motivated by the applications of sharing economy, this paper studies a coalition formation game subject to the capacity of &lt;formula&gt;&lt;tex&gt;$K$&lt;/tex&gt;&lt;/formula&gt; participants per coalition. The participants in each coalition are supposed to split the associated cost according to a given cost-sharing mechanism. A stable coalition structure is established when no group of participants can opt out to form another coalition that leads to lower individual payments. We quantify the inefficiency of distributed decision-making processes under a cost-sharing mechanism by the strong price of anarchy (SPoA), comparing a worst-case stable coalition structure and a social optimum. In particular, we derive SPoA for common fair cost-sharing mechanisms (e.g., equal-split, proportional-split, egalitarian and Nash bargaining solutions of bargaining games, and usage based cost-sharing). We show that the SPoA for equal-split, proportional-split, and usage based costsharing (under certain conditions) is &lt;formula&gt;&lt;tex&gt;$\Theta (\log K)$&lt;/tex&gt;&lt;/formula&gt;, whereas the one for egalitarian and Nash bargaining solutions is &lt;formula&gt;&lt;tex&gt;$O (\sqrt{K} \log K)$&lt;/tex&gt;&lt;/formula&gt;. Therefore, distributed decision-making processes under common fair cost-sharing mechanisms induce only moderate inefficiency.",khaled elbassioni,fair cost-sharing mechanisms,,10.1109/TCNS.2017.2763747,IEEE Transactions on Control of Network Systems,ChauNone,False,,IEEE,Not available,Quantifying Inefficiency of Fair Cost-Sharing Mechanisms for Sharing Economy,9e2de514989fbf60d9bd46f907d80a91,
11160,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",bo gao,Mobile computing,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
11161,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11162,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",bo gao,mobile cloud computing,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
11163,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",bo gao,energy-aware,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
11164,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",bo gao,Mobile computing,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
11165,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",bo gao,mobile cloud computing,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
11166,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",bo gao,energy-aware,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
11167,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",ligang he,Mobile computing,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
11168,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",ligang he,mobile cloud computing,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
11169,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",ligang he,energy-aware,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
11170,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",ligang he,Mobile computing,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
11171,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",ligang he,mobile cloud computing,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
11172,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11173,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",ligang he,energy-aware,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
11174,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",stephen jarvis,Mobile computing,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
11175,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",stephen jarvis,mobile cloud computing,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
11176,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",stephen jarvis,energy-aware,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
11177,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",stephen jarvis,Mobile computing,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
11178,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",stephen jarvis,mobile cloud computing,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
11179,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",stephen jarvis,energy-aware,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
11180,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",quansheng guan,Green communication networks,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
11181,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",quansheng guan,sleep scheduling algorithm,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
11182,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",quansheng guan,weighted cost sharing,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
11183,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11184,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",quansheng guan,approximate potential game,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
11185,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",tianyu chen,Green communication networks,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
11186,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",tianyu chen,sleep scheduling algorithm,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
11187,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",tianyu chen,weighted cost sharing,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
11188,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",tianyu chen,approximate potential game,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
11189,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",shengming jiang,Green communication networks,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
11190,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",shengming jiang,sleep scheduling algorithm,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
11191,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",shengming jiang,weighted cost sharing,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
11192,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",shengming jiang,approximate potential game,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
11193,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",fei ji,Green communication networks,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
11194,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11195,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",fei ji,sleep scheduling algorithm,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
11196,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",fei ji,weighted cost sharing,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
11197,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",fei ji,approximate potential game,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
11198,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",fangjiong chen,Green communication networks,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
11199,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",fangjiong chen,sleep scheduling algorithm,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
11200,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",fangjiong chen,weighted cost sharing,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
11201,"The redundant design and dynamic nature of traffic raise an energy inefficiency issue in communication networks. We exploit the selfishness of both users and the network to schedule cooperatively the idle links and nodes into sleep to save energy. We first formulate the sleep scheduling problem from a perspective of routing, and then propose a greedy algorithm to solve the problem. To reduce the complexity of centralized computation, we further propose a user-network cooperation-based mechanism, where the network publishes a proportionally weighted cost-sharing rule related to energy consumption, while the users selfishly choose their routes with the least cost accordingly. The proposed cooperation mechanism attracts users to aggregate their traffic on fewer links and nodes. The network then simply puts the idle links and nodes into sleep. Selfish routing behaviors are modeled by an α-approximate routing game, where the α factor is adopted to consider the energy consumption, packet losses, and delay during re-routing. We prove the equilibrium existence, convergence, and convergence speed of the best responses, and evaluate the lower bound performance in terms of price of anarchy with further improvement by an advertisement method. Distributed algorithms based on the best responses are also developed to implement the cooperative mechanism. Simulation results over network instants from SNDlib show that our game-based algorithms outperform the greedy and heuristic centralized algorithms in saving energy.",fangjiong chen,approximate potential game,2016.0,10.1109/JSAC.2016.2624040,IEEE Journal on Selected Areas in Communications,Guan2016,False,,IEEE,Not available,User-Network Cooperation-Based Sleep Scheduling for Communication Networks,8a034bfec444e4dc5ac87d11f0a9fb72,https://ieeexplore.ieee.org/document/7727939/
11202,"The authors are interested in evaluating the performance of a cognitive radio network composed of secondary and primary mobiles, and look for optimising the decision process of the secondary mobiles when they have to choose between licensed or unlicensed channels. In fact, the system is composed of several channels where only one unlicensed channel is shared between all the secondary mobiles, when they decide to use this particular channel. As the secondary mobiles are equipped with cognitive radios, they are able to sense the licensed channels and use one of them if it is free. The authors consider first the global system and look for the optimal proportion of secondary mobiles that sense the licensed channels in order to optimise an average performance of the system. Second, the authors assume that each secondary mobile decides to sense or not the licensed channels and, are interested in an equilibrium situation as the secondary mobiles are in competition. After showing the existence and the uniqueness of equilibrium, the performance of this equilibrium is evaluated by looking at the price of the anarchy of the system.",o. habachi,,2012.0,10.1049/iet-com.2010.0537,IET Communications,Habachi2012,False,,IEEE,Not available,Optimal opportunistic sensing in cognitive radio networks,cb511075f0a205101bf390e6cc83432b,
11203,"The authors are interested in evaluating the performance of a cognitive radio network composed of secondary and primary mobiles, and look for optimising the decision process of the secondary mobiles when they have to choose between licensed or unlicensed channels. In fact, the system is composed of several channels where only one unlicensed channel is shared between all the secondary mobiles, when they decide to use this particular channel. As the secondary mobiles are equipped with cognitive radios, they are able to sense the licensed channels and use one of them if it is free. The authors consider first the global system and look for the optimal proportion of secondary mobiles that sense the licensed channels in order to optimise an average performance of the system. Second, the authors assume that each secondary mobile decides to sense or not the licensed channels and, are interested in an equilibrium situation as the secondary mobiles are in competition. After showing the existence and the uniqueness of equilibrium, the performance of this equilibrium is evaluated by looking at the price of the anarchy of the system.",y. hayel,,2012.0,10.1049/iet-com.2010.0537,IET Communications,Habachi2012,False,,IEEE,Not available,Optimal opportunistic sensing in cognitive radio networks,cb511075f0a205101bf390e6cc83432b,
11204,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",konstantinos poularakis,Heuristic algorithms,2013.0,10.1109/INFCOM.2013.6567150,2013 Proceedings IEEE INFOCOM,Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6567150/
11205,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11206,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",konstantinos poularakis,Games,2013.0,10.1109/INFCOM.2013.6567150,2013 Proceedings IEEE INFOCOM,Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6567150/
11207,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",konstantinos poularakis,Nash equilibrium,2013.0,10.1109/INFCOM.2013.6567150,2013 Proceedings IEEE INFOCOM,Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6567150/
11208,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",konstantinos poularakis,Aggregates,2013.0,10.1109/INFCOM.2013.6567150,2013 Proceedings IEEE INFOCOM,Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6567150/
11209,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",konstantinos poularakis,Vectors,2013.0,10.1109/INFCOM.2013.6567150,2013 Proceedings IEEE INFOCOM,Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6567150/
11210,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",konstantinos poularakis,Linear programming,2013.0,10.1109/INFCOM.2013.6567150,2013 Proceedings IEEE INFOCOM,Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6567150/
11211,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",konstantinos poularakis,Conferences,2013.0,10.1109/INFCOM.2013.6567150,2013 Proceedings IEEE INFOCOM,Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6567150/
11212,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",leandros tassiulas,Heuristic algorithms,2013.0,10.1109/INFCOM.2013.6567150,2013 Proceedings IEEE INFOCOM,Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6567150/
11213,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",leandros tassiulas,Games,2013.0,10.1109/INFCOM.2013.6567150,2013 Proceedings IEEE INFOCOM,Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6567150/
11214,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",leandros tassiulas,Nash equilibrium,2013.0,10.1109/INFCOM.2013.6567150,2013 Proceedings IEEE INFOCOM,Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6567150/
11215,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",leandros tassiulas,Aggregates,2013.0,10.1109/INFCOM.2013.6567150,2013 Proceedings IEEE INFOCOM,Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6567150/
11216,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11217,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11218,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",leandros tassiulas,Vectors,2013.0,10.1109/INFCOM.2013.6567150,2013 Proceedings IEEE INFOCOM,Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6567150/
11219,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",leandros tassiulas,Linear programming,2013.0,10.1109/INFCOM.2013.6567150,2013 Proceedings IEEE INFOCOM,Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6567150/
11220,"As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there is the minimum utility level that a provider needs to provide to the society of consumers to cover it's investment cost. In this paper we present a novel decision model for a set of competing providers that wish to enter a market. It may happen that due to the competition, some competitors will not be able to cover their investment cost and therefore will disappear. We analyze the optimum way of forming the market, in order to maximize the aggregate utility of it. We show that this problem is NP-complete and present a linear programming rounding heuristic algorithm to solve it. Besides, we study a game where every player (provider) is to choose whether to join the market or not. We compute the price of anarchy of the game and present a heuristic algorithm that belongs to the family of best response dynamic algorithms. Systematic experiments on a real world data set have demonstrated the effectiveness of our proposed approach.",leandros tassiulas,Conferences,2013.0,10.1109/INFCOM.2013.6567150,2013 Proceedings IEEE INFOCOM,Poularakis2013,False,,IEEE,Not available,Surviving in a competitive market of information providers,ff78fb53465391eab4d97aca6f217a5f,https://ieeexplore.ieee.org/document/6567150/
11221,"We consider two pairs of communicating users sharing two bands of spectrum under a sum band power constraint. Our earlier work proposed a natural spectrum sharing game for this problem and characterized the Nash equilibria as a function of the signal and interference distances, when the positions of the four nodes were assumed fixed. In this work, we derive i) the joint distribution of the interference distances conditioned on the transmitter separation distance, as well as ii) the unconditioned interference distance distribution when we place one transmitter at the origin and the second uniformly at random over a disk. This allows us to compute the distribution of the random Nash equilibria and random prices of anarchy and stability as a function of the random interference distances. We leverage the analysis to give an asymptotic expression for the coupling probability in a game where the transmitter positions form a (low density) Poisson process, which may be interpreted as the fraction of players essentially playing a two player game.",ilaria malanchini,Games,2012.0,,"2012 10th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Malanchini2012,False,,IEEE,Not available,Stochastic characterization of the two band two player spectrum sharing game,cc4115be5302341dce92727be785aa4f,https://ieeexplore.ieee.org/document/6260480/
11222,"We consider two pairs of communicating users sharing two bands of spectrum under a sum band power constraint. Our earlier work proposed a natural spectrum sharing game for this problem and characterized the Nash equilibria as a function of the signal and interference distances, when the positions of the four nodes were assumed fixed. In this work, we derive i) the joint distribution of the interference distances conditioned on the transmitter separation distance, as well as ii) the unconditioned interference distance distribution when we place one transmitter at the origin and the second uniformly at random over a disk. This allows us to compute the distribution of the random Nash equilibria and random prices of anarchy and stability as a function of the random interference distances. We leverage the analysis to give an asymptotic expression for the coupling probability in a game where the transmitter positions form a (low density) Poisson process, which may be interpreted as the fraction of players essentially playing a two player game.",ilaria malanchini,Transmitters,2012.0,,"2012 10th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Malanchini2012,False,,IEEE,Not available,Stochastic characterization of the two band two player spectrum sharing game,cc4115be5302341dce92727be785aa4f,https://ieeexplore.ieee.org/document/6260480/
11223,"We consider two pairs of communicating users sharing two bands of spectrum under a sum band power constraint. Our earlier work proposed a natural spectrum sharing game for this problem and characterized the Nash equilibria as a function of the signal and interference distances, when the positions of the four nodes were assumed fixed. In this work, we derive i) the joint distribution of the interference distances conditioned on the transmitter separation distance, as well as ii) the unconditioned interference distance distribution when we place one transmitter at the origin and the second uniformly at random over a disk. This allows us to compute the distribution of the random Nash equilibria and random prices of anarchy and stability as a function of the random interference distances. We leverage the analysis to give an asymptotic expression for the coupling probability in a game where the transmitter positions form a (low density) Poisson process, which may be interpreted as the fraction of players essentially playing a two player game.",ilaria malanchini,Interference,2012.0,,"2012 10th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Malanchini2012,False,,IEEE,Not available,Stochastic characterization of the two band two player spectrum sharing game,cc4115be5302341dce92727be785aa4f,https://ieeexplore.ieee.org/document/6260480/
11224,"We consider two pairs of communicating users sharing two bands of spectrum under a sum band power constraint. Our earlier work proposed a natural spectrum sharing game for this problem and characterized the Nash equilibria as a function of the signal and interference distances, when the positions of the four nodes were assumed fixed. In this work, we derive i) the joint distribution of the interference distances conditioned on the transmitter separation distance, as well as ii) the unconditioned interference distance distribution when we place one transmitter at the origin and the second uniformly at random over a disk. This allows us to compute the distribution of the random Nash equilibria and random prices of anarchy and stability as a function of the random interference distances. We leverage the analysis to give an asymptotic expression for the coupling probability in a game where the transmitter positions form a (low density) Poisson process, which may be interpreted as the fraction of players essentially playing a two player game.",ilaria malanchini,Receivers,2012.0,,"2012 10th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Malanchini2012,False,,IEEE,Not available,Stochastic characterization of the two band two player spectrum sharing game,cc4115be5302341dce92727be785aa4f,https://ieeexplore.ieee.org/document/6260480/
11225,"We consider two pairs of communicating users sharing two bands of spectrum under a sum band power constraint. Our earlier work proposed a natural spectrum sharing game for this problem and characterized the Nash equilibria as a function of the signal and interference distances, when the positions of the four nodes were assumed fixed. In this work, we derive i) the joint distribution of the interference distances conditioned on the transmitter separation distance, as well as ii) the unconditioned interference distance distribution when we place one transmitter at the origin and the second uniformly at random over a disk. This allows us to compute the distribution of the random Nash equilibria and random prices of anarchy and stability as a function of the random interference distances. We leverage the analysis to give an asymptotic expression for the coupling probability in a game where the transmitter positions form a (low density) Poisson process, which may be interpreted as the fraction of players essentially playing a two player game.",ilaria malanchini,Stochastic processes,2012.0,,"2012 10th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Malanchini2012,False,,IEEE,Not available,Stochastic characterization of the two band two player spectrum sharing game,cc4115be5302341dce92727be785aa4f,https://ieeexplore.ieee.org/document/6260480/
11226,"We consider two pairs of communicating users sharing two bands of spectrum under a sum band power constraint. Our earlier work proposed a natural spectrum sharing game for this problem and characterized the Nash equilibria as a function of the signal and interference distances, when the positions of the four nodes were assumed fixed. In this work, we derive i) the joint distribution of the interference distances conditioned on the transmitter separation distance, as well as ii) the unconditioned interference distance distribution when we place one transmitter at the origin and the second uniformly at random over a disk. This allows us to compute the distribution of the random Nash equilibria and random prices of anarchy and stability as a function of the random interference distances. We leverage the analysis to give an asymptotic expression for the coupling probability in a game where the transmitter positions form a (low density) Poisson process, which may be interpreted as the fraction of players essentially playing a two player game.",ilaria malanchini,Joints,2012.0,,"2012 10th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Malanchini2012,False,,IEEE,Not available,Stochastic characterization of the two band two player spectrum sharing game,cc4115be5302341dce92727be785aa4f,https://ieeexplore.ieee.org/document/6260480/
11227,"We consider two pairs of communicating users sharing two bands of spectrum under a sum band power constraint. Our earlier work proposed a natural spectrum sharing game for this problem and characterized the Nash equilibria as a function of the signal and interference distances, when the positions of the four nodes were assumed fixed. In this work, we derive i) the joint distribution of the interference distances conditioned on the transmitter separation distance, as well as ii) the unconditioned interference distance distribution when we place one transmitter at the origin and the second uniformly at random over a disk. This allows us to compute the distribution of the random Nash equilibria and random prices of anarchy and stability as a function of the random interference distances. We leverage the analysis to give an asymptotic expression for the coupling probability in a game where the transmitter positions form a (low density) Poisson process, which may be interpreted as the fraction of players essentially playing a two player game.",ilaria malanchini,Approximation methods,2012.0,,"2012 10th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Malanchini2012,False,,IEEE,Not available,Stochastic characterization of the two band two player spectrum sharing game,cc4115be5302341dce92727be785aa4f,https://ieeexplore.ieee.org/document/6260480/
11228,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11229,"We consider two pairs of communicating users sharing two bands of spectrum under a sum band power constraint. Our earlier work proposed a natural spectrum sharing game for this problem and characterized the Nash equilibria as a function of the signal and interference distances, when the positions of the four nodes were assumed fixed. In this work, we derive i) the joint distribution of the interference distances conditioned on the transmitter separation distance, as well as ii) the unconditioned interference distance distribution when we place one transmitter at the origin and the second uniformly at random over a disk. This allows us to compute the distribution of the random Nash equilibria and random prices of anarchy and stability as a function of the random interference distances. We leverage the analysis to give an asymptotic expression for the coupling probability in a game where the transmitter positions form a (low density) Poisson process, which may be interpreted as the fraction of players essentially playing a two player game.",steven weber,Games,2012.0,,"2012 10th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Malanchini2012,False,,IEEE,Not available,Stochastic characterization of the two band two player spectrum sharing game,cc4115be5302341dce92727be785aa4f,https://ieeexplore.ieee.org/document/6260480/
11230,"We consider two pairs of communicating users sharing two bands of spectrum under a sum band power constraint. Our earlier work proposed a natural spectrum sharing game for this problem and characterized the Nash equilibria as a function of the signal and interference distances, when the positions of the four nodes were assumed fixed. In this work, we derive i) the joint distribution of the interference distances conditioned on the transmitter separation distance, as well as ii) the unconditioned interference distance distribution when we place one transmitter at the origin and the second uniformly at random over a disk. This allows us to compute the distribution of the random Nash equilibria and random prices of anarchy and stability as a function of the random interference distances. We leverage the analysis to give an asymptotic expression for the coupling probability in a game where the transmitter positions form a (low density) Poisson process, which may be interpreted as the fraction of players essentially playing a two player game.",steven weber,Transmitters,2012.0,,"2012 10th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Malanchini2012,False,,IEEE,Not available,Stochastic characterization of the two band two player spectrum sharing game,cc4115be5302341dce92727be785aa4f,https://ieeexplore.ieee.org/document/6260480/
11231,"We consider two pairs of communicating users sharing two bands of spectrum under a sum band power constraint. Our earlier work proposed a natural spectrum sharing game for this problem and characterized the Nash equilibria as a function of the signal and interference distances, when the positions of the four nodes were assumed fixed. In this work, we derive i) the joint distribution of the interference distances conditioned on the transmitter separation distance, as well as ii) the unconditioned interference distance distribution when we place one transmitter at the origin and the second uniformly at random over a disk. This allows us to compute the distribution of the random Nash equilibria and random prices of anarchy and stability as a function of the random interference distances. We leverage the analysis to give an asymptotic expression for the coupling probability in a game where the transmitter positions form a (low density) Poisson process, which may be interpreted as the fraction of players essentially playing a two player game.",steven weber,Interference,2012.0,,"2012 10th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Malanchini2012,False,,IEEE,Not available,Stochastic characterization of the two band two player spectrum sharing game,cc4115be5302341dce92727be785aa4f,https://ieeexplore.ieee.org/document/6260480/
11232,"We consider two pairs of communicating users sharing two bands of spectrum under a sum band power constraint. Our earlier work proposed a natural spectrum sharing game for this problem and characterized the Nash equilibria as a function of the signal and interference distances, when the positions of the four nodes were assumed fixed. In this work, we derive i) the joint distribution of the interference distances conditioned on the transmitter separation distance, as well as ii) the unconditioned interference distance distribution when we place one transmitter at the origin and the second uniformly at random over a disk. This allows us to compute the distribution of the random Nash equilibria and random prices of anarchy and stability as a function of the random interference distances. We leverage the analysis to give an asymptotic expression for the coupling probability in a game where the transmitter positions form a (low density) Poisson process, which may be interpreted as the fraction of players essentially playing a two player game.",steven weber,Receivers,2012.0,,"2012 10th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Malanchini2012,False,,IEEE,Not available,Stochastic characterization of the two band two player spectrum sharing game,cc4115be5302341dce92727be785aa4f,https://ieeexplore.ieee.org/document/6260480/
11233,"We consider two pairs of communicating users sharing two bands of spectrum under a sum band power constraint. Our earlier work proposed a natural spectrum sharing game for this problem and characterized the Nash equilibria as a function of the signal and interference distances, when the positions of the four nodes were assumed fixed. In this work, we derive i) the joint distribution of the interference distances conditioned on the transmitter separation distance, as well as ii) the unconditioned interference distance distribution when we place one transmitter at the origin and the second uniformly at random over a disk. This allows us to compute the distribution of the random Nash equilibria and random prices of anarchy and stability as a function of the random interference distances. We leverage the analysis to give an asymptotic expression for the coupling probability in a game where the transmitter positions form a (low density) Poisson process, which may be interpreted as the fraction of players essentially playing a two player game.",steven weber,Stochastic processes,2012.0,,"2012 10th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Malanchini2012,False,,IEEE,Not available,Stochastic characterization of the two band two player spectrum sharing game,cc4115be5302341dce92727be785aa4f,https://ieeexplore.ieee.org/document/6260480/
11234,"We consider two pairs of communicating users sharing two bands of spectrum under a sum band power constraint. Our earlier work proposed a natural spectrum sharing game for this problem and characterized the Nash equilibria as a function of the signal and interference distances, when the positions of the four nodes were assumed fixed. In this work, we derive i) the joint distribution of the interference distances conditioned on the transmitter separation distance, as well as ii) the unconditioned interference distance distribution when we place one transmitter at the origin and the second uniformly at random over a disk. This allows us to compute the distribution of the random Nash equilibria and random prices of anarchy and stability as a function of the random interference distances. We leverage the analysis to give an asymptotic expression for the coupling probability in a game where the transmitter positions form a (low density) Poisson process, which may be interpreted as the fraction of players essentially playing a two player game.",steven weber,Joints,2012.0,,"2012 10th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Malanchini2012,False,,IEEE,Not available,Stochastic characterization of the two band two player spectrum sharing game,cc4115be5302341dce92727be785aa4f,https://ieeexplore.ieee.org/document/6260480/
11235,"We consider two pairs of communicating users sharing two bands of spectrum under a sum band power constraint. Our earlier work proposed a natural spectrum sharing game for this problem and characterized the Nash equilibria as a function of the signal and interference distances, when the positions of the four nodes were assumed fixed. In this work, we derive i) the joint distribution of the interference distances conditioned on the transmitter separation distance, as well as ii) the unconditioned interference distance distribution when we place one transmitter at the origin and the second uniformly at random over a disk. This allows us to compute the distribution of the random Nash equilibria and random prices of anarchy and stability as a function of the random interference distances. We leverage the analysis to give an asymptotic expression for the coupling probability in a game where the transmitter positions form a (low density) Poisson process, which may be interpreted as the fraction of players essentially playing a two player game.",steven weber,Approximation methods,2012.0,,"2012 10th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Malanchini2012,False,,IEEE,Not available,Stochastic characterization of the two band two player spectrum sharing game,cc4115be5302341dce92727be785aa4f,https://ieeexplore.ieee.org/document/6260480/
11236,"We consider two pairs of communicating users sharing two bands of spectrum under a sum band power constraint. Our earlier work proposed a natural spectrum sharing game for this problem and characterized the Nash equilibria as a function of the signal and interference distances, when the positions of the four nodes were assumed fixed. In this work, we derive i) the joint distribution of the interference distances conditioned on the transmitter separation distance, as well as ii) the unconditioned interference distance distribution when we place one transmitter at the origin and the second uniformly at random over a disk. This allows us to compute the distribution of the random Nash equilibria and random prices of anarchy and stability as a function of the random interference distances. We leverage the analysis to give an asymptotic expression for the coupling probability in a game where the transmitter positions form a (low density) Poisson process, which may be interpreted as the fraction of players essentially playing a two player game.",matteo cesana,Games,2012.0,,"2012 10th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Malanchini2012,False,,IEEE,Not available,Stochastic characterization of the two band two player spectrum sharing game,cc4115be5302341dce92727be785aa4f,https://ieeexplore.ieee.org/document/6260480/
11237,"We consider two pairs of communicating users sharing two bands of spectrum under a sum band power constraint. Our earlier work proposed a natural spectrum sharing game for this problem and characterized the Nash equilibria as a function of the signal and interference distances, when the positions of the four nodes were assumed fixed. In this work, we derive i) the joint distribution of the interference distances conditioned on the transmitter separation distance, as well as ii) the unconditioned interference distance distribution when we place one transmitter at the origin and the second uniformly at random over a disk. This allows us to compute the distribution of the random Nash equilibria and random prices of anarchy and stability as a function of the random interference distances. We leverage the analysis to give an asymptotic expression for the coupling probability in a game where the transmitter positions form a (low density) Poisson process, which may be interpreted as the fraction of players essentially playing a two player game.",matteo cesana,Transmitters,2012.0,,"2012 10th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Malanchini2012,False,,IEEE,Not available,Stochastic characterization of the two band two player spectrum sharing game,cc4115be5302341dce92727be785aa4f,https://ieeexplore.ieee.org/document/6260480/
11238,"We consider two pairs of communicating users sharing two bands of spectrum under a sum band power constraint. Our earlier work proposed a natural spectrum sharing game for this problem and characterized the Nash equilibria as a function of the signal and interference distances, when the positions of the four nodes were assumed fixed. In this work, we derive i) the joint distribution of the interference distances conditioned on the transmitter separation distance, as well as ii) the unconditioned interference distance distribution when we place one transmitter at the origin and the second uniformly at random over a disk. This allows us to compute the distribution of the random Nash equilibria and random prices of anarchy and stability as a function of the random interference distances. We leverage the analysis to give an asymptotic expression for the coupling probability in a game where the transmitter positions form a (low density) Poisson process, which may be interpreted as the fraction of players essentially playing a two player game.",matteo cesana,Interference,2012.0,,"2012 10th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Malanchini2012,False,,IEEE,Not available,Stochastic characterization of the two band two player spectrum sharing game,cc4115be5302341dce92727be785aa4f,https://ieeexplore.ieee.org/document/6260480/
11239,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11240,"We consider two pairs of communicating users sharing two bands of spectrum under a sum band power constraint. Our earlier work proposed a natural spectrum sharing game for this problem and characterized the Nash equilibria as a function of the signal and interference distances, when the positions of the four nodes were assumed fixed. In this work, we derive i) the joint distribution of the interference distances conditioned on the transmitter separation distance, as well as ii) the unconditioned interference distance distribution when we place one transmitter at the origin and the second uniformly at random over a disk. This allows us to compute the distribution of the random Nash equilibria and random prices of anarchy and stability as a function of the random interference distances. We leverage the analysis to give an asymptotic expression for the coupling probability in a game where the transmitter positions form a (low density) Poisson process, which may be interpreted as the fraction of players essentially playing a two player game.",matteo cesana,Receivers,2012.0,,"2012 10th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Malanchini2012,False,,IEEE,Not available,Stochastic characterization of the two band two player spectrum sharing game,cc4115be5302341dce92727be785aa4f,https://ieeexplore.ieee.org/document/6260480/
11241,"We consider two pairs of communicating users sharing two bands of spectrum under a sum band power constraint. Our earlier work proposed a natural spectrum sharing game for this problem and characterized the Nash equilibria as a function of the signal and interference distances, when the positions of the four nodes were assumed fixed. In this work, we derive i) the joint distribution of the interference distances conditioned on the transmitter separation distance, as well as ii) the unconditioned interference distance distribution when we place one transmitter at the origin and the second uniformly at random over a disk. This allows us to compute the distribution of the random Nash equilibria and random prices of anarchy and stability as a function of the random interference distances. We leverage the analysis to give an asymptotic expression for the coupling probability in a game where the transmitter positions form a (low density) Poisson process, which may be interpreted as the fraction of players essentially playing a two player game.",matteo cesana,Stochastic processes,2012.0,,"2012 10th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Malanchini2012,False,,IEEE,Not available,Stochastic characterization of the two band two player spectrum sharing game,cc4115be5302341dce92727be785aa4f,https://ieeexplore.ieee.org/document/6260480/
11242,"We consider two pairs of communicating users sharing two bands of spectrum under a sum band power constraint. Our earlier work proposed a natural spectrum sharing game for this problem and characterized the Nash equilibria as a function of the signal and interference distances, when the positions of the four nodes were assumed fixed. In this work, we derive i) the joint distribution of the interference distances conditioned on the transmitter separation distance, as well as ii) the unconditioned interference distance distribution when we place one transmitter at the origin and the second uniformly at random over a disk. This allows us to compute the distribution of the random Nash equilibria and random prices of anarchy and stability as a function of the random interference distances. We leverage the analysis to give an asymptotic expression for the coupling probability in a game where the transmitter positions form a (low density) Poisson process, which may be interpreted as the fraction of players essentially playing a two player game.",matteo cesana,Joints,2012.0,,"2012 10th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Malanchini2012,False,,IEEE,Not available,Stochastic characterization of the two band two player spectrum sharing game,cc4115be5302341dce92727be785aa4f,https://ieeexplore.ieee.org/document/6260480/
11243,"We consider two pairs of communicating users sharing two bands of spectrum under a sum band power constraint. Our earlier work proposed a natural spectrum sharing game for this problem and characterized the Nash equilibria as a function of the signal and interference distances, when the positions of the four nodes were assumed fixed. In this work, we derive i) the joint distribution of the interference distances conditioned on the transmitter separation distance, as well as ii) the unconditioned interference distance distribution when we place one transmitter at the origin and the second uniformly at random over a disk. This allows us to compute the distribution of the random Nash equilibria and random prices of anarchy and stability as a function of the random interference distances. We leverage the analysis to give an asymptotic expression for the coupling probability in a game where the transmitter positions form a (low density) Poisson process, which may be interpreted as the fraction of players essentially playing a two player game.",matteo cesana,Approximation methods,2012.0,,"2012 10th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)",Malanchini2012,False,,IEEE,Not available,Stochastic characterization of the two band two player spectrum sharing game,cc4115be5302341dce92727be785aa4f,https://ieeexplore.ieee.org/document/6260480/
11244,"It is well known that the data transport capacity of a wireless network can be increased by leveraging the spatial and frequency diversity of the wireless transmission medium. This has motivated the recent surge of research in cooperative and dynamic-spectrum-access (which we also refer to as cognitive spectrum access) networks. Still, as of today, a key open research challenge is to design distributed control strategies to dynamically jointly assign: 1) portions of the spectrum and 2) cooperative relays to different traffic sessions to maximize the resulting network-wide data rate. In this paper, we make a significant contribution in this direction. First, we mathematically formulate the problem of joint spectrum management and relay selection for a set of sessions concurrently utilizing an interference-limited infrastructure-less wireless network. We then study distributed solutions to this (nonlinear and nonconvex) problem. The overall problem is separated into two subproblems: 1) spectrum management through power allocation with given relay selection strategy; and 2) relay selection for a given spectral profile. Distributed solutions for each of the two subproblems are proposed, which are then analyzed based on notions from variational inequality (VI) theory. The distributed algorithms can be proven to converge, under certain conditions, to VI solutions, which are also Nash equilibrium (NE) solutions of the equivalent NE problems. A distributed algorithm based on iterative solution of the two subproblems is then designed. Performance and price of anarchy of the distributed algorithm are then studied by comparing it to the globally optimal solution obtained with a newly designed centralized algorithm. Simulation results show that the proposed distributed algorithm achieves performance that is within a few percentage points of the optimal solution.",zhangyu guan,Cognitive radio networks,2016.0,10.1109/TNET.2015.2431714,IEEE/ACM Transactions on Networking,Guan2016,False,,IEEE,Not available,Distributed Resource Management for Cognitive Ad Hoc Networks With Cooperative Relays,834fb20ae9626c276bb279f27ab70d67,https://ieeexplore.ieee.org/document/7128414/
11245,"It is well known that the data transport capacity of a wireless network can be increased by leveraging the spatial and frequency diversity of the wireless transmission medium. This has motivated the recent surge of research in cooperative and dynamic-spectrum-access (which we also refer to as cognitive spectrum access) networks. Still, as of today, a key open research challenge is to design distributed control strategies to dynamically jointly assign: 1) portions of the spectrum and 2) cooperative relays to different traffic sessions to maximize the resulting network-wide data rate. In this paper, we make a significant contribution in this direction. First, we mathematically formulate the problem of joint spectrum management and relay selection for a set of sessions concurrently utilizing an interference-limited infrastructure-less wireless network. We then study distributed solutions to this (nonlinear and nonconvex) problem. The overall problem is separated into two subproblems: 1) spectrum management through power allocation with given relay selection strategy; and 2) relay selection for a given spectral profile. Distributed solutions for each of the two subproblems are proposed, which are then analyzed based on notions from variational inequality (VI) theory. The distributed algorithms can be proven to converge, under certain conditions, to VI solutions, which are also Nash equilibrium (NE) solutions of the equivalent NE problems. A distributed algorithm based on iterative solution of the two subproblems is then designed. Performance and price of anarchy of the distributed algorithm are then studied by comparing it to the globally optimal solution obtained with a newly designed centralized algorithm. Simulation results show that the proposed distributed algorithm achieves performance that is within a few percentage points of the optimal solution.",zhangyu guan,cooperative relay,2016.0,10.1109/TNET.2015.2431714,IEEE/ACM Transactions on Networking,Guan2016,False,,IEEE,Not available,Distributed Resource Management for Cognitive Ad Hoc Networks With Cooperative Relays,834fb20ae9626c276bb279f27ab70d67,https://ieeexplore.ieee.org/document/7128414/
11246,"It is well known that the data transport capacity of a wireless network can be increased by leveraging the spatial and frequency diversity of the wireless transmission medium. This has motivated the recent surge of research in cooperative and dynamic-spectrum-access (which we also refer to as cognitive spectrum access) networks. Still, as of today, a key open research challenge is to design distributed control strategies to dynamically jointly assign: 1) portions of the spectrum and 2) cooperative relays to different traffic sessions to maximize the resulting network-wide data rate. In this paper, we make a significant contribution in this direction. First, we mathematically formulate the problem of joint spectrum management and relay selection for a set of sessions concurrently utilizing an interference-limited infrastructure-less wireless network. We then study distributed solutions to this (nonlinear and nonconvex) problem. The overall problem is separated into two subproblems: 1) spectrum management through power allocation with given relay selection strategy; and 2) relay selection for a given spectral profile. Distributed solutions for each of the two subproblems are proposed, which are then analyzed based on notions from variational inequality (VI) theory. The distributed algorithms can be proven to converge, under certain conditions, to VI solutions, which are also Nash equilibrium (NE) solutions of the equivalent NE problems. A distributed algorithm based on iterative solution of the two subproblems is then designed. Performance and price of anarchy of the distributed algorithm are then studied by comparing it to the globally optimal solution obtained with a newly designed centralized algorithm. Simulation results show that the proposed distributed algorithm achieves performance that is within a few percentage points of the optimal solution.",zhangyu guan,distributed spectrum management,2016.0,10.1109/TNET.2015.2431714,IEEE/ACM Transactions on Networking,Guan2016,False,,IEEE,Not available,Distributed Resource Management for Cognitive Ad Hoc Networks With Cooperative Relays,834fb20ae9626c276bb279f27ab70d67,https://ieeexplore.ieee.org/document/7128414/
11247,"It is well known that the data transport capacity of a wireless network can be increased by leveraging the spatial and frequency diversity of the wireless transmission medium. This has motivated the recent surge of research in cooperative and dynamic-spectrum-access (which we also refer to as cognitive spectrum access) networks. Still, as of today, a key open research challenge is to design distributed control strategies to dynamically jointly assign: 1) portions of the spectrum and 2) cooperative relays to different traffic sessions to maximize the resulting network-wide data rate. In this paper, we make a significant contribution in this direction. First, we mathematically formulate the problem of joint spectrum management and relay selection for a set of sessions concurrently utilizing an interference-limited infrastructure-less wireless network. We then study distributed solutions to this (nonlinear and nonconvex) problem. The overall problem is separated into two subproblems: 1) spectrum management through power allocation with given relay selection strategy; and 2) relay selection for a given spectral profile. Distributed solutions for each of the two subproblems are proposed, which are then analyzed based on notions from variational inequality (VI) theory. The distributed algorithms can be proven to converge, under certain conditions, to VI solutions, which are also Nash equilibrium (NE) solutions of the equivalent NE problems. A distributed algorithm based on iterative solution of the two subproblems is then designed. Performance and price of anarchy of the distributed algorithm are then studied by comparing it to the globally optimal solution obtained with a newly designed centralized algorithm. Simulation results show that the proposed distributed algorithm achieves performance that is within a few percentage points of the optimal solution.",zhangyu guan,game theory,2016.0,10.1109/TNET.2015.2431714,IEEE/ACM Transactions on Networking,Guan2016,False,,IEEE,Not available,Distributed Resource Management for Cognitive Ad Hoc Networks With Cooperative Relays,834fb20ae9626c276bb279f27ab70d67,https://ieeexplore.ieee.org/document/7128414/
11248,"It is well known that the data transport capacity of a wireless network can be increased by leveraging the spatial and frequency diversity of the wireless transmission medium. This has motivated the recent surge of research in cooperative and dynamic-spectrum-access (which we also refer to as cognitive spectrum access) networks. Still, as of today, a key open research challenge is to design distributed control strategies to dynamically jointly assign: 1) portions of the spectrum and 2) cooperative relays to different traffic sessions to maximize the resulting network-wide data rate. In this paper, we make a significant contribution in this direction. First, we mathematically formulate the problem of joint spectrum management and relay selection for a set of sessions concurrently utilizing an interference-limited infrastructure-less wireless network. We then study distributed solutions to this (nonlinear and nonconvex) problem. The overall problem is separated into two subproblems: 1) spectrum management through power allocation with given relay selection strategy; and 2) relay selection for a given spectral profile. Distributed solutions for each of the two subproblems are proposed, which are then analyzed based on notions from variational inequality (VI) theory. The distributed algorithms can be proven to converge, under certain conditions, to VI solutions, which are also Nash equilibrium (NE) solutions of the equivalent NE problems. A distributed algorithm based on iterative solution of the two subproblems is then designed. Performance and price of anarchy of the distributed algorithm are then studied by comparing it to the globally optimal solution obtained with a newly designed centralized algorithm. Simulation results show that the proposed distributed algorithm achieves performance that is within a few percentage points of the optimal solution.",tommaso melodia,Cognitive radio networks,2016.0,10.1109/TNET.2015.2431714,IEEE/ACM Transactions on Networking,Guan2016,False,,IEEE,Not available,Distributed Resource Management for Cognitive Ad Hoc Networks With Cooperative Relays,834fb20ae9626c276bb279f27ab70d67,https://ieeexplore.ieee.org/document/7128414/
11249,"It is well known that the data transport capacity of a wireless network can be increased by leveraging the spatial and frequency diversity of the wireless transmission medium. This has motivated the recent surge of research in cooperative and dynamic-spectrum-access (which we also refer to as cognitive spectrum access) networks. Still, as of today, a key open research challenge is to design distributed control strategies to dynamically jointly assign: 1) portions of the spectrum and 2) cooperative relays to different traffic sessions to maximize the resulting network-wide data rate. In this paper, we make a significant contribution in this direction. First, we mathematically formulate the problem of joint spectrum management and relay selection for a set of sessions concurrently utilizing an interference-limited infrastructure-less wireless network. We then study distributed solutions to this (nonlinear and nonconvex) problem. The overall problem is separated into two subproblems: 1) spectrum management through power allocation with given relay selection strategy; and 2) relay selection for a given spectral profile. Distributed solutions for each of the two subproblems are proposed, which are then analyzed based on notions from variational inequality (VI) theory. The distributed algorithms can be proven to converge, under certain conditions, to VI solutions, which are also Nash equilibrium (NE) solutions of the equivalent NE problems. A distributed algorithm based on iterative solution of the two subproblems is then designed. Performance and price of anarchy of the distributed algorithm are then studied by comparing it to the globally optimal solution obtained with a newly designed centralized algorithm. Simulation results show that the proposed distributed algorithm achieves performance that is within a few percentage points of the optimal solution.",tommaso melodia,cooperative relay,2016.0,10.1109/TNET.2015.2431714,IEEE/ACM Transactions on Networking,Guan2016,False,,IEEE,Not available,Distributed Resource Management for Cognitive Ad Hoc Networks With Cooperative Relays,834fb20ae9626c276bb279f27ab70d67,https://ieeexplore.ieee.org/document/7128414/
11250,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11251,"It is well known that the data transport capacity of a wireless network can be increased by leveraging the spatial and frequency diversity of the wireless transmission medium. This has motivated the recent surge of research in cooperative and dynamic-spectrum-access (which we also refer to as cognitive spectrum access) networks. Still, as of today, a key open research challenge is to design distributed control strategies to dynamically jointly assign: 1) portions of the spectrum and 2) cooperative relays to different traffic sessions to maximize the resulting network-wide data rate. In this paper, we make a significant contribution in this direction. First, we mathematically formulate the problem of joint spectrum management and relay selection for a set of sessions concurrently utilizing an interference-limited infrastructure-less wireless network. We then study distributed solutions to this (nonlinear and nonconvex) problem. The overall problem is separated into two subproblems: 1) spectrum management through power allocation with given relay selection strategy; and 2) relay selection for a given spectral profile. Distributed solutions for each of the two subproblems are proposed, which are then analyzed based on notions from variational inequality (VI) theory. The distributed algorithms can be proven to converge, under certain conditions, to VI solutions, which are also Nash equilibrium (NE) solutions of the equivalent NE problems. A distributed algorithm based on iterative solution of the two subproblems is then designed. Performance and price of anarchy of the distributed algorithm are then studied by comparing it to the globally optimal solution obtained with a newly designed centralized algorithm. Simulation results show that the proposed distributed algorithm achieves performance that is within a few percentage points of the optimal solution.",tommaso melodia,distributed spectrum management,2016.0,10.1109/TNET.2015.2431714,IEEE/ACM Transactions on Networking,Guan2016,False,,IEEE,Not available,Distributed Resource Management for Cognitive Ad Hoc Networks With Cooperative Relays,834fb20ae9626c276bb279f27ab70d67,https://ieeexplore.ieee.org/document/7128414/
11252,"It is well known that the data transport capacity of a wireless network can be increased by leveraging the spatial and frequency diversity of the wireless transmission medium. This has motivated the recent surge of research in cooperative and dynamic-spectrum-access (which we also refer to as cognitive spectrum access) networks. Still, as of today, a key open research challenge is to design distributed control strategies to dynamically jointly assign: 1) portions of the spectrum and 2) cooperative relays to different traffic sessions to maximize the resulting network-wide data rate. In this paper, we make a significant contribution in this direction. First, we mathematically formulate the problem of joint spectrum management and relay selection for a set of sessions concurrently utilizing an interference-limited infrastructure-less wireless network. We then study distributed solutions to this (nonlinear and nonconvex) problem. The overall problem is separated into two subproblems: 1) spectrum management through power allocation with given relay selection strategy; and 2) relay selection for a given spectral profile. Distributed solutions for each of the two subproblems are proposed, which are then analyzed based on notions from variational inequality (VI) theory. The distributed algorithms can be proven to converge, under certain conditions, to VI solutions, which are also Nash equilibrium (NE) solutions of the equivalent NE problems. A distributed algorithm based on iterative solution of the two subproblems is then designed. Performance and price of anarchy of the distributed algorithm are then studied by comparing it to the globally optimal solution obtained with a newly designed centralized algorithm. Simulation results show that the proposed distributed algorithm achieves performance that is within a few percentage points of the optimal solution.",tommaso melodia,game theory,2016.0,10.1109/TNET.2015.2431714,IEEE/ACM Transactions on Networking,Guan2016,False,,IEEE,Not available,Distributed Resource Management for Cognitive Ad Hoc Networks With Cooperative Relays,834fb20ae9626c276bb279f27ab70d67,https://ieeexplore.ieee.org/document/7128414/
11253,"It is well known that the data transport capacity of a wireless network can be increased by leveraging the spatial and frequency diversity of the wireless transmission medium. This has motivated the recent surge of research in cooperative and dynamic-spectrum-access (which we also refer to as cognitive spectrum access) networks. Still, as of today, a key open research challenge is to design distributed control strategies to dynamically jointly assign: 1) portions of the spectrum and 2) cooperative relays to different traffic sessions to maximize the resulting network-wide data rate. In this paper, we make a significant contribution in this direction. First, we mathematically formulate the problem of joint spectrum management and relay selection for a set of sessions concurrently utilizing an interference-limited infrastructure-less wireless network. We then study distributed solutions to this (nonlinear and nonconvex) problem. The overall problem is separated into two subproblems: 1) spectrum management through power allocation with given relay selection strategy; and 2) relay selection for a given spectral profile. Distributed solutions for each of the two subproblems are proposed, which are then analyzed based on notions from variational inequality (VI) theory. The distributed algorithms can be proven to converge, under certain conditions, to VI solutions, which are also Nash equilibrium (NE) solutions of the equivalent NE problems. A distributed algorithm based on iterative solution of the two subproblems is then designed. Performance and price of anarchy of the distributed algorithm are then studied by comparing it to the globally optimal solution obtained with a newly designed centralized algorithm. Simulation results show that the proposed distributed algorithm achieves performance that is within a few percentage points of the optimal solution.",dongfeng yuan,Cognitive radio networks,2016.0,10.1109/TNET.2015.2431714,IEEE/ACM Transactions on Networking,Guan2016,False,,IEEE,Not available,Distributed Resource Management for Cognitive Ad Hoc Networks With Cooperative Relays,834fb20ae9626c276bb279f27ab70d67,https://ieeexplore.ieee.org/document/7128414/
11254,"It is well known that the data transport capacity of a wireless network can be increased by leveraging the spatial and frequency diversity of the wireless transmission medium. This has motivated the recent surge of research in cooperative and dynamic-spectrum-access (which we also refer to as cognitive spectrum access) networks. Still, as of today, a key open research challenge is to design distributed control strategies to dynamically jointly assign: 1) portions of the spectrum and 2) cooperative relays to different traffic sessions to maximize the resulting network-wide data rate. In this paper, we make a significant contribution in this direction. First, we mathematically formulate the problem of joint spectrum management and relay selection for a set of sessions concurrently utilizing an interference-limited infrastructure-less wireless network. We then study distributed solutions to this (nonlinear and nonconvex) problem. The overall problem is separated into two subproblems: 1) spectrum management through power allocation with given relay selection strategy; and 2) relay selection for a given spectral profile. Distributed solutions for each of the two subproblems are proposed, which are then analyzed based on notions from variational inequality (VI) theory. The distributed algorithms can be proven to converge, under certain conditions, to VI solutions, which are also Nash equilibrium (NE) solutions of the equivalent NE problems. A distributed algorithm based on iterative solution of the two subproblems is then designed. Performance and price of anarchy of the distributed algorithm are then studied by comparing it to the globally optimal solution obtained with a newly designed centralized algorithm. Simulation results show that the proposed distributed algorithm achieves performance that is within a few percentage points of the optimal solution.",dongfeng yuan,cooperative relay,2016.0,10.1109/TNET.2015.2431714,IEEE/ACM Transactions on Networking,Guan2016,False,,IEEE,Not available,Distributed Resource Management for Cognitive Ad Hoc Networks With Cooperative Relays,834fb20ae9626c276bb279f27ab70d67,https://ieeexplore.ieee.org/document/7128414/
11255,"It is well known that the data transport capacity of a wireless network can be increased by leveraging the spatial and frequency diversity of the wireless transmission medium. This has motivated the recent surge of research in cooperative and dynamic-spectrum-access (which we also refer to as cognitive spectrum access) networks. Still, as of today, a key open research challenge is to design distributed control strategies to dynamically jointly assign: 1) portions of the spectrum and 2) cooperative relays to different traffic sessions to maximize the resulting network-wide data rate. In this paper, we make a significant contribution in this direction. First, we mathematically formulate the problem of joint spectrum management and relay selection for a set of sessions concurrently utilizing an interference-limited infrastructure-less wireless network. We then study distributed solutions to this (nonlinear and nonconvex) problem. The overall problem is separated into two subproblems: 1) spectrum management through power allocation with given relay selection strategy; and 2) relay selection for a given spectral profile. Distributed solutions for each of the two subproblems are proposed, which are then analyzed based on notions from variational inequality (VI) theory. The distributed algorithms can be proven to converge, under certain conditions, to VI solutions, which are also Nash equilibrium (NE) solutions of the equivalent NE problems. A distributed algorithm based on iterative solution of the two subproblems is then designed. Performance and price of anarchy of the distributed algorithm are then studied by comparing it to the globally optimal solution obtained with a newly designed centralized algorithm. Simulation results show that the proposed distributed algorithm achieves performance that is within a few percentage points of the optimal solution.",dongfeng yuan,distributed spectrum management,2016.0,10.1109/TNET.2015.2431714,IEEE/ACM Transactions on Networking,Guan2016,False,,IEEE,Not available,Distributed Resource Management for Cognitive Ad Hoc Networks With Cooperative Relays,834fb20ae9626c276bb279f27ab70d67,https://ieeexplore.ieee.org/document/7128414/
11256,"It is well known that the data transport capacity of a wireless network can be increased by leveraging the spatial and frequency diversity of the wireless transmission medium. This has motivated the recent surge of research in cooperative and dynamic-spectrum-access (which we also refer to as cognitive spectrum access) networks. Still, as of today, a key open research challenge is to design distributed control strategies to dynamically jointly assign: 1) portions of the spectrum and 2) cooperative relays to different traffic sessions to maximize the resulting network-wide data rate. In this paper, we make a significant contribution in this direction. First, we mathematically formulate the problem of joint spectrum management and relay selection for a set of sessions concurrently utilizing an interference-limited infrastructure-less wireless network. We then study distributed solutions to this (nonlinear and nonconvex) problem. The overall problem is separated into two subproblems: 1) spectrum management through power allocation with given relay selection strategy; and 2) relay selection for a given spectral profile. Distributed solutions for each of the two subproblems are proposed, which are then analyzed based on notions from variational inequality (VI) theory. The distributed algorithms can be proven to converge, under certain conditions, to VI solutions, which are also Nash equilibrium (NE) solutions of the equivalent NE problems. A distributed algorithm based on iterative solution of the two subproblems is then designed. Performance and price of anarchy of the distributed algorithm are then studied by comparing it to the globally optimal solution obtained with a newly designed centralized algorithm. Simulation results show that the proposed distributed algorithm achieves performance that is within a few percentage points of the optimal solution.",dongfeng yuan,game theory,2016.0,10.1109/TNET.2015.2431714,IEEE/ACM Transactions on Networking,Guan2016,False,,IEEE,Not available,Distributed Resource Management for Cognitive Ad Hoc Networks With Cooperative Relays,834fb20ae9626c276bb279f27ab70d67,https://ieeexplore.ieee.org/document/7128414/
11257,"It is well known that the data transport capacity of a wireless network can be increased by leveraging the spatial and frequency diversity of the wireless transmission medium. This has motivated the recent surge of research in cooperative and dynamic-spectrum-access (which we also refer to as cognitive spectrum access) networks. Still, as of today, a key open research challenge is to design distributed control strategies to dynamically jointly assign: 1) portions of the spectrum and 2) cooperative relays to different traffic sessions to maximize the resulting network-wide data rate. In this paper, we make a significant contribution in this direction. First, we mathematically formulate the problem of joint spectrum management and relay selection for a set of sessions concurrently utilizing an interference-limited infrastructure-less wireless network. We then study distributed solutions to this (nonlinear and nonconvex) problem. The overall problem is separated into two subproblems: 1) spectrum management through power allocation with given relay selection strategy; and 2) relay selection for a given spectral profile. Distributed solutions for each of the two subproblems are proposed, which are then analyzed based on notions from variational inequality (VI) theory. The distributed algorithms can be proven to converge, under certain conditions, to VI solutions, which are also Nash equilibrium (NE) solutions of the equivalent NE problems. A distributed algorithm based on iterative solution of the two subproblems is then designed. Performance and price of anarchy of the distributed algorithm are then studied by comparing it to the globally optimal solution obtained with a newly designed centralized algorithm. Simulation results show that the proposed distributed algorithm achieves performance that is within a few percentage points of the optimal solution.",dimitris pados,Cognitive radio networks,2016.0,10.1109/TNET.2015.2431714,IEEE/ACM Transactions on Networking,Guan2016,False,,IEEE,Not available,Distributed Resource Management for Cognitive Ad Hoc Networks With Cooperative Relays,834fb20ae9626c276bb279f27ab70d67,https://ieeexplore.ieee.org/document/7128414/
11258,"It is well known that the data transport capacity of a wireless network can be increased by leveraging the spatial and frequency diversity of the wireless transmission medium. This has motivated the recent surge of research in cooperative and dynamic-spectrum-access (which we also refer to as cognitive spectrum access) networks. Still, as of today, a key open research challenge is to design distributed control strategies to dynamically jointly assign: 1) portions of the spectrum and 2) cooperative relays to different traffic sessions to maximize the resulting network-wide data rate. In this paper, we make a significant contribution in this direction. First, we mathematically formulate the problem of joint spectrum management and relay selection for a set of sessions concurrently utilizing an interference-limited infrastructure-less wireless network. We then study distributed solutions to this (nonlinear and nonconvex) problem. The overall problem is separated into two subproblems: 1) spectrum management through power allocation with given relay selection strategy; and 2) relay selection for a given spectral profile. Distributed solutions for each of the two subproblems are proposed, which are then analyzed based on notions from variational inequality (VI) theory. The distributed algorithms can be proven to converge, under certain conditions, to VI solutions, which are also Nash equilibrium (NE) solutions of the equivalent NE problems. A distributed algorithm based on iterative solution of the two subproblems is then designed. Performance and price of anarchy of the distributed algorithm are then studied by comparing it to the globally optimal solution obtained with a newly designed centralized algorithm. Simulation results show that the proposed distributed algorithm achieves performance that is within a few percentage points of the optimal solution.",dimitris pados,cooperative relay,2016.0,10.1109/TNET.2015.2431714,IEEE/ACM Transactions on Networking,Guan2016,False,,IEEE,Not available,Distributed Resource Management for Cognitive Ad Hoc Networks With Cooperative Relays,834fb20ae9626c276bb279f27ab70d67,https://ieeexplore.ieee.org/document/7128414/
11259,"It is well known that the data transport capacity of a wireless network can be increased by leveraging the spatial and frequency diversity of the wireless transmission medium. This has motivated the recent surge of research in cooperative and dynamic-spectrum-access (which we also refer to as cognitive spectrum access) networks. Still, as of today, a key open research challenge is to design distributed control strategies to dynamically jointly assign: 1) portions of the spectrum and 2) cooperative relays to different traffic sessions to maximize the resulting network-wide data rate. In this paper, we make a significant contribution in this direction. First, we mathematically formulate the problem of joint spectrum management and relay selection for a set of sessions concurrently utilizing an interference-limited infrastructure-less wireless network. We then study distributed solutions to this (nonlinear and nonconvex) problem. The overall problem is separated into two subproblems: 1) spectrum management through power allocation with given relay selection strategy; and 2) relay selection for a given spectral profile. Distributed solutions for each of the two subproblems are proposed, which are then analyzed based on notions from variational inequality (VI) theory. The distributed algorithms can be proven to converge, under certain conditions, to VI solutions, which are also Nash equilibrium (NE) solutions of the equivalent NE problems. A distributed algorithm based on iterative solution of the two subproblems is then designed. Performance and price of anarchy of the distributed algorithm are then studied by comparing it to the globally optimal solution obtained with a newly designed centralized algorithm. Simulation results show that the proposed distributed algorithm achieves performance that is within a few percentage points of the optimal solution.",dimitris pados,distributed spectrum management,2016.0,10.1109/TNET.2015.2431714,IEEE/ACM Transactions on Networking,Guan2016,False,,IEEE,Not available,Distributed Resource Management for Cognitive Ad Hoc Networks With Cooperative Relays,834fb20ae9626c276bb279f27ab70d67,https://ieeexplore.ieee.org/document/7128414/
11260,"It is well known that the data transport capacity of a wireless network can be increased by leveraging the spatial and frequency diversity of the wireless transmission medium. This has motivated the recent surge of research in cooperative and dynamic-spectrum-access (which we also refer to as cognitive spectrum access) networks. Still, as of today, a key open research challenge is to design distributed control strategies to dynamically jointly assign: 1) portions of the spectrum and 2) cooperative relays to different traffic sessions to maximize the resulting network-wide data rate. In this paper, we make a significant contribution in this direction. First, we mathematically formulate the problem of joint spectrum management and relay selection for a set of sessions concurrently utilizing an interference-limited infrastructure-less wireless network. We then study distributed solutions to this (nonlinear and nonconvex) problem. The overall problem is separated into two subproblems: 1) spectrum management through power allocation with given relay selection strategy; and 2) relay selection for a given spectral profile. Distributed solutions for each of the two subproblems are proposed, which are then analyzed based on notions from variational inequality (VI) theory. The distributed algorithms can be proven to converge, under certain conditions, to VI solutions, which are also Nash equilibrium (NE) solutions of the equivalent NE problems. A distributed algorithm based on iterative solution of the two subproblems is then designed. Performance and price of anarchy of the distributed algorithm are then studied by comparing it to the globally optimal solution obtained with a newly designed centralized algorithm. Simulation results show that the proposed distributed algorithm achieves performance that is within a few percentage points of the optimal solution.",dimitris pados,game theory,2016.0,10.1109/TNET.2015.2431714,IEEE/ACM Transactions on Networking,Guan2016,False,,IEEE,Not available,Distributed Resource Management for Cognitive Ad Hoc Networks With Cooperative Relays,834fb20ae9626c276bb279f27ab70d67,https://ieeexplore.ieee.org/document/7128414/
11261,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11262,"The purpose of this paper is to show how key concepts from control theory, game theory, and mean field theory can be exploited to design joint control-allocation policies in cognitive wireless networks. One of the key features of the proposed approach is that transmitters (which are assumed to be cognitive and autonomous decisionnally speaking) have a certain knowledge of the channel evolution law and want to reach a certain transmission rate target while minimizing the energy consumed by the power supply and not the one corresponding to radio-frequency signals (which is known to be important to design green wireless networks). The optimal centralized policy is derived in order to have an upper bound on the performance of the decentralized system. Then, the Nash equilibrium of the cognitive network is determined by using recent results from mean field theory (MFT). In order to evaluate the performance gap between decentralized and centralized policies we introduce and evaluate the MFT-based asymptotic price of anarchy (APoA).",hamidou tembine,Radio transmitters,2010.0,10.4108/ICST.CROWNCOM2010.9219,2010 Proceedings of the Fifth International Conference on Cognitive Radio Oriented Wireless Networks and Communications,Tembine2010,False,,IEEE,Not available,Joint power control-allocation for green cognitive wireless networks using mean field theory,a8ad7a5dd7b64f700329b584696f1929,https://ieeexplore.ieee.org/document/5577790/
11263,"The purpose of this paper is to show how key concepts from control theory, game theory, and mean field theory can be exploited to design joint control-allocation policies in cognitive wireless networks. One of the key features of the proposed approach is that transmitters (which are assumed to be cognitive and autonomous decisionnally speaking) have a certain knowledge of the channel evolution law and want to reach a certain transmission rate target while minimizing the energy consumed by the power supply and not the one corresponding to radio-frequency signals (which is known to be important to design green wireless networks). The optimal centralized policy is derived in order to have an upper bound on the performance of the decentralized system. Then, the Nash equilibrium of the cognitive network is determined by using recent results from mean field theory (MFT). In order to evaluate the performance gap between decentralized and centralized policies we introduce and evaluate the MFT-based asymptotic price of anarchy (APoA).",hamidou tembine,Resource management,2010.0,10.4108/ICST.CROWNCOM2010.9219,2010 Proceedings of the Fifth International Conference on Cognitive Radio Oriented Wireless Networks and Communications,Tembine2010,False,,IEEE,Not available,Joint power control-allocation for green cognitive wireless networks using mean field theory,a8ad7a5dd7b64f700329b584696f1929,https://ieeexplore.ieee.org/document/5577790/
11264,"The purpose of this paper is to show how key concepts from control theory, game theory, and mean field theory can be exploited to design joint control-allocation policies in cognitive wireless networks. One of the key features of the proposed approach is that transmitters (which are assumed to be cognitive and autonomous decisionnally speaking) have a certain knowledge of the channel evolution law and want to reach a certain transmission rate target while minimizing the energy consumed by the power supply and not the one corresponding to radio-frequency signals (which is known to be important to design green wireless networks). The optimal centralized policy is derived in order to have an upper bound on the performance of the decentralized system. Then, the Nash equilibrium of the cognitive network is determined by using recent results from mean field theory (MFT). In order to evaluate the performance gap between decentralized and centralized policies we introduce and evaluate the MFT-based asymptotic price of anarchy (APoA).",hamidou tembine,Games,2010.0,10.4108/ICST.CROWNCOM2010.9219,2010 Proceedings of the Fifth International Conference on Cognitive Radio Oriented Wireless Networks and Communications,Tembine2010,False,,IEEE,Not available,Joint power control-allocation for green cognitive wireless networks using mean field theory,a8ad7a5dd7b64f700329b584696f1929,https://ieeexplore.ieee.org/document/5577790/
11265,"The purpose of this paper is to show how key concepts from control theory, game theory, and mean field theory can be exploited to design joint control-allocation policies in cognitive wireless networks. One of the key features of the proposed approach is that transmitters (which are assumed to be cognitive and autonomous decisionnally speaking) have a certain knowledge of the channel evolution law and want to reach a certain transmission rate target while minimizing the energy consumed by the power supply and not the one corresponding to radio-frequency signals (which is known to be important to design green wireless networks). The optimal centralized policy is derived in order to have an upper bound on the performance of the decentralized system. Then, the Nash equilibrium of the cognitive network is determined by using recent results from mean field theory (MFT). In order to evaluate the performance gap between decentralized and centralized policies we introduce and evaluate the MFT-based asymptotic price of anarchy (APoA).",hamidou tembine,Equations,2010.0,10.4108/ICST.CROWNCOM2010.9219,2010 Proceedings of the Fifth International Conference on Cognitive Radio Oriented Wireless Networks and Communications,Tembine2010,False,,IEEE,Not available,Joint power control-allocation for green cognitive wireless networks using mean field theory,a8ad7a5dd7b64f700329b584696f1929,https://ieeexplore.ieee.org/document/5577790/
11266,"The purpose of this paper is to show how key concepts from control theory, game theory, and mean field theory can be exploited to design joint control-allocation policies in cognitive wireless networks. One of the key features of the proposed approach is that transmitters (which are assumed to be cognitive and autonomous decisionnally speaking) have a certain knowledge of the channel evolution law and want to reach a certain transmission rate target while minimizing the energy consumed by the power supply and not the one corresponding to radio-frequency signals (which is known to be important to design green wireless networks). The optimal centralized policy is derived in order to have an upper bound on the performance of the decentralized system. Then, the Nash equilibrium of the cognitive network is determined by using recent results from mean field theory (MFT). In order to evaluate the performance gap between decentralized and centralized policies we introduce and evaluate the MFT-based asymptotic price of anarchy (APoA).",hamidou tembine,Wireless networks,2010.0,10.4108/ICST.CROWNCOM2010.9219,2010 Proceedings of the Fifth International Conference on Cognitive Radio Oriented Wireless Networks and Communications,Tembine2010,False,,IEEE,Not available,Joint power control-allocation for green cognitive wireless networks using mean field theory,a8ad7a5dd7b64f700329b584696f1929,https://ieeexplore.ieee.org/document/5577790/
11267,"The purpose of this paper is to show how key concepts from control theory, game theory, and mean field theory can be exploited to design joint control-allocation policies in cognitive wireless networks. One of the key features of the proposed approach is that transmitters (which are assumed to be cognitive and autonomous decisionnally speaking) have a certain knowledge of the channel evolution law and want to reach a certain transmission rate target while minimizing the energy consumed by the power supply and not the one corresponding to radio-frequency signals (which is known to be important to design green wireless networks). The optimal centralized policy is derived in order to have an upper bound on the performance of the decentralized system. Then, the Nash equilibrium of the cognitive network is determined by using recent results from mean field theory (MFT). In order to evaluate the performance gap between decentralized and centralized policies we introduce and evaluate the MFT-based asymptotic price of anarchy (APoA).",hamidou tembine,Convergence,2010.0,10.4108/ICST.CROWNCOM2010.9219,2010 Proceedings of the Fifth International Conference on Cognitive Radio Oriented Wireless Networks and Communications,Tembine2010,False,,IEEE,Not available,Joint power control-allocation for green cognitive wireless networks using mean field theory,a8ad7a5dd7b64f700329b584696f1929,https://ieeexplore.ieee.org/document/5577790/
11268,"The purpose of this paper is to show how key concepts from control theory, game theory, and mean field theory can be exploited to design joint control-allocation policies in cognitive wireless networks. One of the key features of the proposed approach is that transmitters (which are assumed to be cognitive and autonomous decisionnally speaking) have a certain knowledge of the channel evolution law and want to reach a certain transmission rate target while minimizing the energy consumed by the power supply and not the one corresponding to radio-frequency signals (which is known to be important to design green wireless networks). The optimal centralized policy is derived in order to have an upper bound on the performance of the decentralized system. Then, the Nash equilibrium of the cognitive network is determined by using recent results from mean field theory (MFT). In order to evaluate the performance gap between decentralized and centralized policies we introduce and evaluate the MFT-based asymptotic price of anarchy (APoA).",samson lasaulce,Radio transmitters,2010.0,10.4108/ICST.CROWNCOM2010.9219,2010 Proceedings of the Fifth International Conference on Cognitive Radio Oriented Wireless Networks and Communications,Tembine2010,False,,IEEE,Not available,Joint power control-allocation for green cognitive wireless networks using mean field theory,a8ad7a5dd7b64f700329b584696f1929,https://ieeexplore.ieee.org/document/5577790/
11269,"The purpose of this paper is to show how key concepts from control theory, game theory, and mean field theory can be exploited to design joint control-allocation policies in cognitive wireless networks. One of the key features of the proposed approach is that transmitters (which are assumed to be cognitive and autonomous decisionnally speaking) have a certain knowledge of the channel evolution law and want to reach a certain transmission rate target while minimizing the energy consumed by the power supply and not the one corresponding to radio-frequency signals (which is known to be important to design green wireless networks). The optimal centralized policy is derived in order to have an upper bound on the performance of the decentralized system. Then, the Nash equilibrium of the cognitive network is determined by using recent results from mean field theory (MFT). In order to evaluate the performance gap between decentralized and centralized policies we introduce and evaluate the MFT-based asymptotic price of anarchy (APoA).",samson lasaulce,Resource management,2010.0,10.4108/ICST.CROWNCOM2010.9219,2010 Proceedings of the Fifth International Conference on Cognitive Radio Oriented Wireless Networks and Communications,Tembine2010,False,,IEEE,Not available,Joint power control-allocation for green cognitive wireless networks using mean field theory,a8ad7a5dd7b64f700329b584696f1929,https://ieeexplore.ieee.org/document/5577790/
11270,"The purpose of this paper is to show how key concepts from control theory, game theory, and mean field theory can be exploited to design joint control-allocation policies in cognitive wireless networks. One of the key features of the proposed approach is that transmitters (which are assumed to be cognitive and autonomous decisionnally speaking) have a certain knowledge of the channel evolution law and want to reach a certain transmission rate target while minimizing the energy consumed by the power supply and not the one corresponding to radio-frequency signals (which is known to be important to design green wireless networks). The optimal centralized policy is derived in order to have an upper bound on the performance of the decentralized system. Then, the Nash equilibrium of the cognitive network is determined by using recent results from mean field theory (MFT). In order to evaluate the performance gap between decentralized and centralized policies we introduce and evaluate the MFT-based asymptotic price of anarchy (APoA).",samson lasaulce,Games,2010.0,10.4108/ICST.CROWNCOM2010.9219,2010 Proceedings of the Fifth International Conference on Cognitive Radio Oriented Wireless Networks and Communications,Tembine2010,False,,IEEE,Not available,Joint power control-allocation for green cognitive wireless networks using mean field theory,a8ad7a5dd7b64f700329b584696f1929,https://ieeexplore.ieee.org/document/5577790/
11271,"The purpose of this paper is to show how key concepts from control theory, game theory, and mean field theory can be exploited to design joint control-allocation policies in cognitive wireless networks. One of the key features of the proposed approach is that transmitters (which are assumed to be cognitive and autonomous decisionnally speaking) have a certain knowledge of the channel evolution law and want to reach a certain transmission rate target while minimizing the energy consumed by the power supply and not the one corresponding to radio-frequency signals (which is known to be important to design green wireless networks). The optimal centralized policy is derived in order to have an upper bound on the performance of the decentralized system. Then, the Nash equilibrium of the cognitive network is determined by using recent results from mean field theory (MFT). In order to evaluate the performance gap between decentralized and centralized policies we introduce and evaluate the MFT-based asymptotic price of anarchy (APoA).",samson lasaulce,Equations,2010.0,10.4108/ICST.CROWNCOM2010.9219,2010 Proceedings of the Fifth International Conference on Cognitive Radio Oriented Wireless Networks and Communications,Tembine2010,False,,IEEE,Not available,Joint power control-allocation for green cognitive wireless networks using mean field theory,a8ad7a5dd7b64f700329b584696f1929,https://ieeexplore.ieee.org/document/5577790/
11272,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11273,"The purpose of this paper is to show how key concepts from control theory, game theory, and mean field theory can be exploited to design joint control-allocation policies in cognitive wireless networks. One of the key features of the proposed approach is that transmitters (which are assumed to be cognitive and autonomous decisionnally speaking) have a certain knowledge of the channel evolution law and want to reach a certain transmission rate target while minimizing the energy consumed by the power supply and not the one corresponding to radio-frequency signals (which is known to be important to design green wireless networks). The optimal centralized policy is derived in order to have an upper bound on the performance of the decentralized system. Then, the Nash equilibrium of the cognitive network is determined by using recent results from mean field theory (MFT). In order to evaluate the performance gap between decentralized and centralized policies we introduce and evaluate the MFT-based asymptotic price of anarchy (APoA).",samson lasaulce,Wireless networks,2010.0,10.4108/ICST.CROWNCOM2010.9219,2010 Proceedings of the Fifth International Conference on Cognitive Radio Oriented Wireless Networks and Communications,Tembine2010,False,,IEEE,Not available,Joint power control-allocation for green cognitive wireless networks using mean field theory,a8ad7a5dd7b64f700329b584696f1929,https://ieeexplore.ieee.org/document/5577790/
11274,"The purpose of this paper is to show how key concepts from control theory, game theory, and mean field theory can be exploited to design joint control-allocation policies in cognitive wireless networks. One of the key features of the proposed approach is that transmitters (which are assumed to be cognitive and autonomous decisionnally speaking) have a certain knowledge of the channel evolution law and want to reach a certain transmission rate target while minimizing the energy consumed by the power supply and not the one corresponding to radio-frequency signals (which is known to be important to design green wireless networks). The optimal centralized policy is derived in order to have an upper bound on the performance of the decentralized system. Then, the Nash equilibrium of the cognitive network is determined by using recent results from mean field theory (MFT). In order to evaluate the performance gap between decentralized and centralized policies we introduce and evaluate the MFT-based asymptotic price of anarchy (APoA).",samson lasaulce,Convergence,2010.0,10.4108/ICST.CROWNCOM2010.9219,2010 Proceedings of the Fifth International Conference on Cognitive Radio Oriented Wireless Networks and Communications,Tembine2010,False,,IEEE,Not available,Joint power control-allocation for green cognitive wireless networks using mean field theory,a8ad7a5dd7b64f700329b584696f1929,https://ieeexplore.ieee.org/document/5577790/
11275,"The purpose of this paper is to show how key concepts from control theory, game theory, and mean field theory can be exploited to design joint control-allocation policies in cognitive wireless networks. One of the key features of the proposed approach is that transmitters (which are assumed to be cognitive and autonomous decisionnally speaking) have a certain knowledge of the channel evolution law and want to reach a certain transmission rate target while minimizing the energy consumed by the power supply and not the one corresponding to radio-frequency signals (which is known to be important to design green wireless networks). The optimal centralized policy is derived in order to have an upper bound on the performance of the decentralized system. Then, the Nash equilibrium of the cognitive network is determined by using recent results from mean field theory (MFT). In order to evaluate the performance gap between decentralized and centralized policies we introduce and evaluate the MFT-based asymptotic price of anarchy (APoA).",marc jungers,Radio transmitters,2010.0,10.4108/ICST.CROWNCOM2010.9219,2010 Proceedings of the Fifth International Conference on Cognitive Radio Oriented Wireless Networks and Communications,Tembine2010,False,,IEEE,Not available,Joint power control-allocation for green cognitive wireless networks using mean field theory,a8ad7a5dd7b64f700329b584696f1929,https://ieeexplore.ieee.org/document/5577790/
11276,"The purpose of this paper is to show how key concepts from control theory, game theory, and mean field theory can be exploited to design joint control-allocation policies in cognitive wireless networks. One of the key features of the proposed approach is that transmitters (which are assumed to be cognitive and autonomous decisionnally speaking) have a certain knowledge of the channel evolution law and want to reach a certain transmission rate target while minimizing the energy consumed by the power supply and not the one corresponding to radio-frequency signals (which is known to be important to design green wireless networks). The optimal centralized policy is derived in order to have an upper bound on the performance of the decentralized system. Then, the Nash equilibrium of the cognitive network is determined by using recent results from mean field theory (MFT). In order to evaluate the performance gap between decentralized and centralized policies we introduce and evaluate the MFT-based asymptotic price of anarchy (APoA).",marc jungers,Resource management,2010.0,10.4108/ICST.CROWNCOM2010.9219,2010 Proceedings of the Fifth International Conference on Cognitive Radio Oriented Wireless Networks and Communications,Tembine2010,False,,IEEE,Not available,Joint power control-allocation for green cognitive wireless networks using mean field theory,a8ad7a5dd7b64f700329b584696f1929,https://ieeexplore.ieee.org/document/5577790/
11277,"The purpose of this paper is to show how key concepts from control theory, game theory, and mean field theory can be exploited to design joint control-allocation policies in cognitive wireless networks. One of the key features of the proposed approach is that transmitters (which are assumed to be cognitive and autonomous decisionnally speaking) have a certain knowledge of the channel evolution law and want to reach a certain transmission rate target while minimizing the energy consumed by the power supply and not the one corresponding to radio-frequency signals (which is known to be important to design green wireless networks). The optimal centralized policy is derived in order to have an upper bound on the performance of the decentralized system. Then, the Nash equilibrium of the cognitive network is determined by using recent results from mean field theory (MFT). In order to evaluate the performance gap between decentralized and centralized policies we introduce and evaluate the MFT-based asymptotic price of anarchy (APoA).",marc jungers,Games,2010.0,10.4108/ICST.CROWNCOM2010.9219,2010 Proceedings of the Fifth International Conference on Cognitive Radio Oriented Wireless Networks and Communications,Tembine2010,False,,IEEE,Not available,Joint power control-allocation for green cognitive wireless networks using mean field theory,a8ad7a5dd7b64f700329b584696f1929,https://ieeexplore.ieee.org/document/5577790/
11278,"The purpose of this paper is to show how key concepts from control theory, game theory, and mean field theory can be exploited to design joint control-allocation policies in cognitive wireless networks. One of the key features of the proposed approach is that transmitters (which are assumed to be cognitive and autonomous decisionnally speaking) have a certain knowledge of the channel evolution law and want to reach a certain transmission rate target while minimizing the energy consumed by the power supply and not the one corresponding to radio-frequency signals (which is known to be important to design green wireless networks). The optimal centralized policy is derived in order to have an upper bound on the performance of the decentralized system. Then, the Nash equilibrium of the cognitive network is determined by using recent results from mean field theory (MFT). In order to evaluate the performance gap between decentralized and centralized policies we introduce and evaluate the MFT-based asymptotic price of anarchy (APoA).",marc jungers,Equations,2010.0,10.4108/ICST.CROWNCOM2010.9219,2010 Proceedings of the Fifth International Conference on Cognitive Radio Oriented Wireless Networks and Communications,Tembine2010,False,,IEEE,Not available,Joint power control-allocation for green cognitive wireless networks using mean field theory,a8ad7a5dd7b64f700329b584696f1929,https://ieeexplore.ieee.org/document/5577790/
11279,"The purpose of this paper is to show how key concepts from control theory, game theory, and mean field theory can be exploited to design joint control-allocation policies in cognitive wireless networks. One of the key features of the proposed approach is that transmitters (which are assumed to be cognitive and autonomous decisionnally speaking) have a certain knowledge of the channel evolution law and want to reach a certain transmission rate target while minimizing the energy consumed by the power supply and not the one corresponding to radio-frequency signals (which is known to be important to design green wireless networks). The optimal centralized policy is derived in order to have an upper bound on the performance of the decentralized system. Then, the Nash equilibrium of the cognitive network is determined by using recent results from mean field theory (MFT). In order to evaluate the performance gap between decentralized and centralized policies we introduce and evaluate the MFT-based asymptotic price of anarchy (APoA).",marc jungers,Wireless networks,2010.0,10.4108/ICST.CROWNCOM2010.9219,2010 Proceedings of the Fifth International Conference on Cognitive Radio Oriented Wireless Networks and Communications,Tembine2010,False,,IEEE,Not available,Joint power control-allocation for green cognitive wireless networks using mean field theory,a8ad7a5dd7b64f700329b584696f1929,https://ieeexplore.ieee.org/document/5577790/
11280,"The purpose of this paper is to show how key concepts from control theory, game theory, and mean field theory can be exploited to design joint control-allocation policies in cognitive wireless networks. One of the key features of the proposed approach is that transmitters (which are assumed to be cognitive and autonomous decisionnally speaking) have a certain knowledge of the channel evolution law and want to reach a certain transmission rate target while minimizing the energy consumed by the power supply and not the one corresponding to radio-frequency signals (which is known to be important to design green wireless networks). The optimal centralized policy is derived in order to have an upper bound on the performance of the decentralized system. Then, the Nash equilibrium of the cognitive network is determined by using recent results from mean field theory (MFT). In order to evaluate the performance gap between decentralized and centralized policies we introduce and evaluate the MFT-based asymptotic price of anarchy (APoA).",marc jungers,Convergence,2010.0,10.4108/ICST.CROWNCOM2010.9219,2010 Proceedings of the Fifth International Conference on Cognitive Radio Oriented Wireless Networks and Communications,Tembine2010,False,,IEEE,Not available,Joint power control-allocation for green cognitive wireless networks using mean field theory,a8ad7a5dd7b64f700329b584696f1929,https://ieeexplore.ieee.org/document/5577790/
11281,"This paper reports on quantification and mitigation of the inefficiency of selfish investment in network recovery from Susceptible Infected Susceptible (SIS) infection in a practically important case of high losses due to infection. In this case, both socially optimal and selfish investments in the infection loss mitigation keep the system close to the boundary of the infection-free region. However, our analysis reveals that while socially optimal investments result in asymptotically zero infection losses, this is not the case for selfish investments. The inefficiency of selfish investments, which is measured by the corresponding Price of Anarchy (PoA), is due to positive externalities. In heterogeneous networks, positive externalities result in finite infection losses despite aggregate overinvestment due to imbalances of selfish investments. While the infection losses can be eliminated with ""small"" increase in the selfish investments, dealing with imbalances of selfish investments is more challenging. This assessment challenges conventional view that inefficiency of selfish investment in network security is due to aggregate underinvestment, at least in a practically important case of large infection losses. We discuss possible approaches to reduction of the second inefficiency component through regulations, incentives, or their combination, and outline directions of future research.",vladimir marbukh,Susceptible-Infected-Susceptible (SIS) infection,2018.0,10.1109/TrustCom/BigDataSE.2018.00293,"2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE)",Marbukh2018,False,,IEEE,Not available,On Mitigation Inefficiency of Selfish Investment in Network Recovery from High Loss SIS Infection,0f6e9fce6544dab492b0065c6c4ecaee,https://ieeexplore.ieee.org/document/8456161/
11282,"This paper reports on quantification and mitigation of the inefficiency of selfish investment in network recovery from Susceptible Infected Susceptible (SIS) infection in a practically important case of high losses due to infection. In this case, both socially optimal and selfish investments in the infection loss mitigation keep the system close to the boundary of the infection-free region. However, our analysis reveals that while socially optimal investments result in asymptotically zero infection losses, this is not the case for selfish investments. The inefficiency of selfish investments, which is measured by the corresponding Price of Anarchy (PoA), is due to positive externalities. In heterogeneous networks, positive externalities result in finite infection losses despite aggregate overinvestment due to imbalances of selfish investments. While the infection losses can be eliminated with ""small"" increase in the selfish investments, dealing with imbalances of selfish investments is more challenging. This assessment challenges conventional view that inefficiency of selfish investment in network security is due to aggregate underinvestment, at least in a practically important case of large infection losses. We discuss possible approaches to reduction of the second inefficiency component through regulations, incentives, or their combination, and outline directions of future research.",vladimir marbukh,selfish investment in recovery capability,2018.0,10.1109/TrustCom/BigDataSE.2018.00293,"2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE)",Marbukh2018,False,,IEEE,Not available,On Mitigation Inefficiency of Selfish Investment in Network Recovery from High Loss SIS Infection,0f6e9fce6544dab492b0065c6c4ecaee,https://ieeexplore.ieee.org/document/8456161/
11283,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11284,"This paper reports on quantification and mitigation of the inefficiency of selfish investment in network recovery from Susceptible Infected Susceptible (SIS) infection in a practically important case of high losses due to infection. In this case, both socially optimal and selfish investments in the infection loss mitigation keep the system close to the boundary of the infection-free region. However, our analysis reveals that while socially optimal investments result in asymptotically zero infection losses, this is not the case for selfish investments. The inefficiency of selfish investments, which is measured by the corresponding Price of Anarchy (PoA), is due to positive externalities. In heterogeneous networks, positive externalities result in finite infection losses despite aggregate overinvestment due to imbalances of selfish investments. While the infection losses can be eliminated with ""small"" increase in the selfish investments, dealing with imbalances of selfish investments is more challenging. This assessment challenges conventional view that inefficiency of selfish investment in network security is due to aggregate underinvestment, at least in a practically important case of large infection losses. We discuss possible approaches to reduction of the second inefficiency component through regulations, incentives, or their combination, and outline directions of future research.",vladimir marbukh,inefficiency evaluation and mitigation,2018.0,10.1109/TrustCom/BigDataSE.2018.00293,"2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE)",Marbukh2018,False,,IEEE,Not available,On Mitigation Inefficiency of Selfish Investment in Network Recovery from High Loss SIS Infection,0f6e9fce6544dab492b0065c6c4ecaee,https://ieeexplore.ieee.org/document/8456161/
11285,"In this paper, we introduce a preliminary model for interactions in the data market. Recent research has shown ways in which a single central data aggregator can design mechanisms to ensure it receives high quality data from a collection of users, even when the sources have an aversion to producing and reporting such estimates to the aggregator. However, we have shown that these mechanisms often break down in more realistic models, where multiple data aggregators are in competition for the users' data. We formulate the competition that arises between the aggregators as a game, and show this game admits either no Nash equilibria, or a continuum of Nash Equilibria. In the latter case, there is a fundamental ambiguity in who bears the burden of incentivizing different data sources. We are also able to calculate the price of anarchy, which measures how much social welfare is lost between the Nash equilibrium and the social optimum, i.e. between non-cooperative strategic play and cooperation.",tyler westenbroek,Games,2017.0,10.1109/CDC.2017.8264398,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Westenbroek2017,False,,IEEE,Not available,Statistical estimation with strategic data sources in competitive settings,c024d2a6d7c9ef30c7275ea454e38983,https://ieeexplore.ieee.org/document/8264398/
11286,"In this paper, we introduce a preliminary model for interactions in the data market. Recent research has shown ways in which a single central data aggregator can design mechanisms to ensure it receives high quality data from a collection of users, even when the sources have an aversion to producing and reporting such estimates to the aggregator. However, we have shown that these mechanisms often break down in more realistic models, where multiple data aggregators are in competition for the users' data. We formulate the competition that arises between the aggregators as a game, and show this game admits either no Nash equilibria, or a continuum of Nash Equilibria. In the latter case, there is a fundamental ambiguity in who bears the burden of incentivizing different data sources. We are also able to calculate the price of anarchy, which measures how much social welfare is lost between the Nash equilibrium and the social optimum, i.e. between non-cooperative strategic play and cooperation.",tyler westenbroek,Data models,2017.0,10.1109/CDC.2017.8264398,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Westenbroek2017,False,,IEEE,Not available,Statistical estimation with strategic data sources in competitive settings,c024d2a6d7c9ef30c7275ea454e38983,https://ieeexplore.ieee.org/document/8264398/
11287,"In this paper, we introduce a preliminary model for interactions in the data market. Recent research has shown ways in which a single central data aggregator can design mechanisms to ensure it receives high quality data from a collection of users, even when the sources have an aversion to producing and reporting such estimates to the aggregator. However, we have shown that these mechanisms often break down in more realistic models, where multiple data aggregators are in competition for the users' data. We formulate the competition that arises between the aggregators as a game, and show this game admits either no Nash equilibria, or a continuum of Nash Equilibria. In the latter case, there is a fundamental ambiguity in who bears the burden of incentivizing different data sources. We are also able to calculate the price of anarchy, which measures how much social welfare is lost between the Nash equilibrium and the social optimum, i.e. between non-cooperative strategic play and cooperation.",tyler westenbroek,Contracts,2017.0,10.1109/CDC.2017.8264398,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Westenbroek2017,False,,IEEE,Not available,Statistical estimation with strategic data sources in competitive settings,c024d2a6d7c9ef30c7275ea454e38983,https://ieeexplore.ieee.org/document/8264398/
11288,"In this paper, we introduce a preliminary model for interactions in the data market. Recent research has shown ways in which a single central data aggregator can design mechanisms to ensure it receives high quality data from a collection of users, even when the sources have an aversion to producing and reporting such estimates to the aggregator. However, we have shown that these mechanisms often break down in more realistic models, where multiple data aggregators are in competition for the users' data. We formulate the competition that arises between the aggregators as a game, and show this game admits either no Nash equilibria, or a continuum of Nash Equilibria. In the latter case, there is a fundamental ambiguity in who bears the burden of incentivizing different data sources. We are also able to calculate the price of anarchy, which measures how much social welfare is lost between the Nash equilibrium and the social optimum, i.e. between non-cooperative strategic play and cooperation.",tyler westenbroek,Nash equilibrium,2017.0,10.1109/CDC.2017.8264398,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Westenbroek2017,False,,IEEE,Not available,Statistical estimation with strategic data sources in competitive settings,c024d2a6d7c9ef30c7275ea454e38983,https://ieeexplore.ieee.org/document/8264398/
11289,"In this paper, we introduce a preliminary model for interactions in the data market. Recent research has shown ways in which a single central data aggregator can design mechanisms to ensure it receives high quality data from a collection of users, even when the sources have an aversion to producing and reporting such estimates to the aggregator. However, we have shown that these mechanisms often break down in more realistic models, where multiple data aggregators are in competition for the users' data. We formulate the competition that arises between the aggregators as a game, and show this game admits either no Nash equilibria, or a continuum of Nash Equilibria. In the latter case, there is a fundamental ambiguity in who bears the burden of incentivizing different data sources. We are also able to calculate the price of anarchy, which measures how much social welfare is lost between the Nash equilibrium and the social optimum, i.e. between non-cooperative strategic play and cooperation.",tyler westenbroek,Intelligent sensors,2017.0,10.1109/CDC.2017.8264398,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Westenbroek2017,False,,IEEE,Not available,Statistical estimation with strategic data sources in competitive settings,c024d2a6d7c9ef30c7275ea454e38983,https://ieeexplore.ieee.org/document/8264398/
11290,"In this paper, we introduce a preliminary model for interactions in the data market. Recent research has shown ways in which a single central data aggregator can design mechanisms to ensure it receives high quality data from a collection of users, even when the sources have an aversion to producing and reporting such estimates to the aggregator. However, we have shown that these mechanisms often break down in more realistic models, where multiple data aggregators are in competition for the users' data. We formulate the competition that arises between the aggregators as a game, and show this game admits either no Nash equilibria, or a continuum of Nash Equilibria. In the latter case, there is a fundamental ambiguity in who bears the burden of incentivizing different data sources. We are also able to calculate the price of anarchy, which measures how much social welfare is lost between the Nash equilibrium and the social optimum, i.e. between non-cooperative strategic play and cooperation.",tyler westenbroek,Mathematical model,2017.0,10.1109/CDC.2017.8264398,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Westenbroek2017,False,,IEEE,Not available,Statistical estimation with strategic data sources in competitive settings,c024d2a6d7c9ef30c7275ea454e38983,https://ieeexplore.ieee.org/document/8264398/
11291,"In this paper, we introduce a preliminary model for interactions in the data market. Recent research has shown ways in which a single central data aggregator can design mechanisms to ensure it receives high quality data from a collection of users, even when the sources have an aversion to producing and reporting such estimates to the aggregator. However, we have shown that these mechanisms often break down in more realistic models, where multiple data aggregators are in competition for the users' data. We formulate the competition that arises between the aggregators as a game, and show this game admits either no Nash equilibria, or a continuum of Nash Equilibria. In the latter case, there is a fundamental ambiguity in who bears the burden of incentivizing different data sources. We are also able to calculate the price of anarchy, which measures how much social welfare is lost between the Nash equilibrium and the social optimum, i.e. between non-cooperative strategic play and cooperation.",roy dong,Games,2017.0,10.1109/CDC.2017.8264398,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Westenbroek2017,False,,IEEE,Not available,Statistical estimation with strategic data sources in competitive settings,c024d2a6d7c9ef30c7275ea454e38983,https://ieeexplore.ieee.org/document/8264398/
11292,"In this paper, we introduce a preliminary model for interactions in the data market. Recent research has shown ways in which a single central data aggregator can design mechanisms to ensure it receives high quality data from a collection of users, even when the sources have an aversion to producing and reporting such estimates to the aggregator. However, we have shown that these mechanisms often break down in more realistic models, where multiple data aggregators are in competition for the users' data. We formulate the competition that arises between the aggregators as a game, and show this game admits either no Nash equilibria, or a continuum of Nash Equilibria. In the latter case, there is a fundamental ambiguity in who bears the burden of incentivizing different data sources. We are also able to calculate the price of anarchy, which measures how much social welfare is lost between the Nash equilibrium and the social optimum, i.e. between non-cooperative strategic play and cooperation.",roy dong,Data models,2017.0,10.1109/CDC.2017.8264398,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Westenbroek2017,False,,IEEE,Not available,Statistical estimation with strategic data sources in competitive settings,c024d2a6d7c9ef30c7275ea454e38983,https://ieeexplore.ieee.org/document/8264398/
11293,"In this paper, we introduce a preliminary model for interactions in the data market. Recent research has shown ways in which a single central data aggregator can design mechanisms to ensure it receives high quality data from a collection of users, even when the sources have an aversion to producing and reporting such estimates to the aggregator. However, we have shown that these mechanisms often break down in more realistic models, where multiple data aggregators are in competition for the users' data. We formulate the competition that arises between the aggregators as a game, and show this game admits either no Nash equilibria, or a continuum of Nash Equilibria. In the latter case, there is a fundamental ambiguity in who bears the burden of incentivizing different data sources. We are also able to calculate the price of anarchy, which measures how much social welfare is lost between the Nash equilibrium and the social optimum, i.e. between non-cooperative strategic play and cooperation.",roy dong,Contracts,2017.0,10.1109/CDC.2017.8264398,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Westenbroek2017,False,,IEEE,Not available,Statistical estimation with strategic data sources in competitive settings,c024d2a6d7c9ef30c7275ea454e38983,https://ieeexplore.ieee.org/document/8264398/
11294,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11295,"In this paper, we introduce a preliminary model for interactions in the data market. Recent research has shown ways in which a single central data aggregator can design mechanisms to ensure it receives high quality data from a collection of users, even when the sources have an aversion to producing and reporting such estimates to the aggregator. However, we have shown that these mechanisms often break down in more realistic models, where multiple data aggregators are in competition for the users' data. We formulate the competition that arises between the aggregators as a game, and show this game admits either no Nash equilibria, or a continuum of Nash Equilibria. In the latter case, there is a fundamental ambiguity in who bears the burden of incentivizing different data sources. We are also able to calculate the price of anarchy, which measures how much social welfare is lost between the Nash equilibrium and the social optimum, i.e. between non-cooperative strategic play and cooperation.",roy dong,Nash equilibrium,2017.0,10.1109/CDC.2017.8264398,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Westenbroek2017,False,,IEEE,Not available,Statistical estimation with strategic data sources in competitive settings,c024d2a6d7c9ef30c7275ea454e38983,https://ieeexplore.ieee.org/document/8264398/
11296,"In this paper, we introduce a preliminary model for interactions in the data market. Recent research has shown ways in which a single central data aggregator can design mechanisms to ensure it receives high quality data from a collection of users, even when the sources have an aversion to producing and reporting such estimates to the aggregator. However, we have shown that these mechanisms often break down in more realistic models, where multiple data aggregators are in competition for the users' data. We formulate the competition that arises between the aggregators as a game, and show this game admits either no Nash equilibria, or a continuum of Nash Equilibria. In the latter case, there is a fundamental ambiguity in who bears the burden of incentivizing different data sources. We are also able to calculate the price of anarchy, which measures how much social welfare is lost between the Nash equilibrium and the social optimum, i.e. between non-cooperative strategic play and cooperation.",roy dong,Intelligent sensors,2017.0,10.1109/CDC.2017.8264398,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Westenbroek2017,False,,IEEE,Not available,Statistical estimation with strategic data sources in competitive settings,c024d2a6d7c9ef30c7275ea454e38983,https://ieeexplore.ieee.org/document/8264398/
11297,"In this paper, we introduce a preliminary model for interactions in the data market. Recent research has shown ways in which a single central data aggregator can design mechanisms to ensure it receives high quality data from a collection of users, even when the sources have an aversion to producing and reporting such estimates to the aggregator. However, we have shown that these mechanisms often break down in more realistic models, where multiple data aggregators are in competition for the users' data. We formulate the competition that arises between the aggregators as a game, and show this game admits either no Nash equilibria, or a continuum of Nash Equilibria. In the latter case, there is a fundamental ambiguity in who bears the burden of incentivizing different data sources. We are also able to calculate the price of anarchy, which measures how much social welfare is lost between the Nash equilibrium and the social optimum, i.e. between non-cooperative strategic play and cooperation.",roy dong,Mathematical model,2017.0,10.1109/CDC.2017.8264398,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Westenbroek2017,False,,IEEE,Not available,Statistical estimation with strategic data sources in competitive settings,c024d2a6d7c9ef30c7275ea454e38983,https://ieeexplore.ieee.org/document/8264398/
11298,"In this paper, we introduce a preliminary model for interactions in the data market. Recent research has shown ways in which a single central data aggregator can design mechanisms to ensure it receives high quality data from a collection of users, even when the sources have an aversion to producing and reporting such estimates to the aggregator. However, we have shown that these mechanisms often break down in more realistic models, where multiple data aggregators are in competition for the users' data. We formulate the competition that arises between the aggregators as a game, and show this game admits either no Nash equilibria, or a continuum of Nash Equilibria. In the latter case, there is a fundamental ambiguity in who bears the burden of incentivizing different data sources. We are also able to calculate the price of anarchy, which measures how much social welfare is lost between the Nash equilibrium and the social optimum, i.e. between non-cooperative strategic play and cooperation.",lillian ratliff,Games,2017.0,10.1109/CDC.2017.8264398,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Westenbroek2017,False,,IEEE,Not available,Statistical estimation with strategic data sources in competitive settings,c024d2a6d7c9ef30c7275ea454e38983,https://ieeexplore.ieee.org/document/8264398/
11299,"In this paper, we introduce a preliminary model for interactions in the data market. Recent research has shown ways in which a single central data aggregator can design mechanisms to ensure it receives high quality data from a collection of users, even when the sources have an aversion to producing and reporting such estimates to the aggregator. However, we have shown that these mechanisms often break down in more realistic models, where multiple data aggregators are in competition for the users' data. We formulate the competition that arises between the aggregators as a game, and show this game admits either no Nash equilibria, or a continuum of Nash Equilibria. In the latter case, there is a fundamental ambiguity in who bears the burden of incentivizing different data sources. We are also able to calculate the price of anarchy, which measures how much social welfare is lost between the Nash equilibrium and the social optimum, i.e. between non-cooperative strategic play and cooperation.",lillian ratliff,Data models,2017.0,10.1109/CDC.2017.8264398,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Westenbroek2017,False,,IEEE,Not available,Statistical estimation with strategic data sources in competitive settings,c024d2a6d7c9ef30c7275ea454e38983,https://ieeexplore.ieee.org/document/8264398/
11300,"In this paper, we introduce a preliminary model for interactions in the data market. Recent research has shown ways in which a single central data aggregator can design mechanisms to ensure it receives high quality data from a collection of users, even when the sources have an aversion to producing and reporting such estimates to the aggregator. However, we have shown that these mechanisms often break down in more realistic models, where multiple data aggregators are in competition for the users' data. We formulate the competition that arises between the aggregators as a game, and show this game admits either no Nash equilibria, or a continuum of Nash Equilibria. In the latter case, there is a fundamental ambiguity in who bears the burden of incentivizing different data sources. We are also able to calculate the price of anarchy, which measures how much social welfare is lost between the Nash equilibrium and the social optimum, i.e. between non-cooperative strategic play and cooperation.",lillian ratliff,Contracts,2017.0,10.1109/CDC.2017.8264398,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Westenbroek2017,False,,IEEE,Not available,Statistical estimation with strategic data sources in competitive settings,c024d2a6d7c9ef30c7275ea454e38983,https://ieeexplore.ieee.org/document/8264398/
11301,"In this paper, we introduce a preliminary model for interactions in the data market. Recent research has shown ways in which a single central data aggregator can design mechanisms to ensure it receives high quality data from a collection of users, even when the sources have an aversion to producing and reporting such estimates to the aggregator. However, we have shown that these mechanisms often break down in more realistic models, where multiple data aggregators are in competition for the users' data. We formulate the competition that arises between the aggregators as a game, and show this game admits either no Nash equilibria, or a continuum of Nash Equilibria. In the latter case, there is a fundamental ambiguity in who bears the burden of incentivizing different data sources. We are also able to calculate the price of anarchy, which measures how much social welfare is lost between the Nash equilibrium and the social optimum, i.e. between non-cooperative strategic play and cooperation.",lillian ratliff,Nash equilibrium,2017.0,10.1109/CDC.2017.8264398,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Westenbroek2017,False,,IEEE,Not available,Statistical estimation with strategic data sources in competitive settings,c024d2a6d7c9ef30c7275ea454e38983,https://ieeexplore.ieee.org/document/8264398/
11302,"In this paper, we introduce a preliminary model for interactions in the data market. Recent research has shown ways in which a single central data aggregator can design mechanisms to ensure it receives high quality data from a collection of users, even when the sources have an aversion to producing and reporting such estimates to the aggregator. However, we have shown that these mechanisms often break down in more realistic models, where multiple data aggregators are in competition for the users' data. We formulate the competition that arises between the aggregators as a game, and show this game admits either no Nash equilibria, or a continuum of Nash Equilibria. In the latter case, there is a fundamental ambiguity in who bears the burden of incentivizing different data sources. We are also able to calculate the price of anarchy, which measures how much social welfare is lost between the Nash equilibrium and the social optimum, i.e. between non-cooperative strategic play and cooperation.",lillian ratliff,Intelligent sensors,2017.0,10.1109/CDC.2017.8264398,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Westenbroek2017,False,,IEEE,Not available,Statistical estimation with strategic data sources in competitive settings,c024d2a6d7c9ef30c7275ea454e38983,https://ieeexplore.ieee.org/document/8264398/
11303,"In this paper, we introduce a preliminary model for interactions in the data market. Recent research has shown ways in which a single central data aggregator can design mechanisms to ensure it receives high quality data from a collection of users, even when the sources have an aversion to producing and reporting such estimates to the aggregator. However, we have shown that these mechanisms often break down in more realistic models, where multiple data aggregators are in competition for the users' data. We formulate the competition that arises between the aggregators as a game, and show this game admits either no Nash equilibria, or a continuum of Nash Equilibria. In the latter case, there is a fundamental ambiguity in who bears the burden of incentivizing different data sources. We are also able to calculate the price of anarchy, which measures how much social welfare is lost between the Nash equilibrium and the social optimum, i.e. between non-cooperative strategic play and cooperation.",lillian ratliff,Mathematical model,2017.0,10.1109/CDC.2017.8264398,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Westenbroek2017,False,,IEEE,Not available,Statistical estimation with strategic data sources in competitive settings,c024d2a6d7c9ef30c7275ea454e38983,https://ieeexplore.ieee.org/document/8264398/
11304,"In this paper, we introduce a preliminary model for interactions in the data market. Recent research has shown ways in which a single central data aggregator can design mechanisms to ensure it receives high quality data from a collection of users, even when the sources have an aversion to producing and reporting such estimates to the aggregator. However, we have shown that these mechanisms often break down in more realistic models, where multiple data aggregators are in competition for the users' data. We formulate the competition that arises between the aggregators as a game, and show this game admits either no Nash equilibria, or a continuum of Nash Equilibria. In the latter case, there is a fundamental ambiguity in who bears the burden of incentivizing different data sources. We are also able to calculate the price of anarchy, which measures how much social welfare is lost between the Nash equilibrium and the social optimum, i.e. between non-cooperative strategic play and cooperation.",s. sastry,Games,2017.0,10.1109/CDC.2017.8264398,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Westenbroek2017,False,,IEEE,Not available,Statistical estimation with strategic data sources in competitive settings,c024d2a6d7c9ef30c7275ea454e38983,https://ieeexplore.ieee.org/document/8264398/
11305,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11306,"In this paper, we introduce a preliminary model for interactions in the data market. Recent research has shown ways in which a single central data aggregator can design mechanisms to ensure it receives high quality data from a collection of users, even when the sources have an aversion to producing and reporting such estimates to the aggregator. However, we have shown that these mechanisms often break down in more realistic models, where multiple data aggregators are in competition for the users' data. We formulate the competition that arises between the aggregators as a game, and show this game admits either no Nash equilibria, or a continuum of Nash Equilibria. In the latter case, there is a fundamental ambiguity in who bears the burden of incentivizing different data sources. We are also able to calculate the price of anarchy, which measures how much social welfare is lost between the Nash equilibrium and the social optimum, i.e. between non-cooperative strategic play and cooperation.",s. sastry,Data models,2017.0,10.1109/CDC.2017.8264398,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Westenbroek2017,False,,IEEE,Not available,Statistical estimation with strategic data sources in competitive settings,c024d2a6d7c9ef30c7275ea454e38983,https://ieeexplore.ieee.org/document/8264398/
11307,"In this paper, we introduce a preliminary model for interactions in the data market. Recent research has shown ways in which a single central data aggregator can design mechanisms to ensure it receives high quality data from a collection of users, even when the sources have an aversion to producing and reporting such estimates to the aggregator. However, we have shown that these mechanisms often break down in more realistic models, where multiple data aggregators are in competition for the users' data. We formulate the competition that arises between the aggregators as a game, and show this game admits either no Nash equilibria, or a continuum of Nash Equilibria. In the latter case, there is a fundamental ambiguity in who bears the burden of incentivizing different data sources. We are also able to calculate the price of anarchy, which measures how much social welfare is lost between the Nash equilibrium and the social optimum, i.e. between non-cooperative strategic play and cooperation.",s. sastry,Contracts,2017.0,10.1109/CDC.2017.8264398,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Westenbroek2017,False,,IEEE,Not available,Statistical estimation with strategic data sources in competitive settings,c024d2a6d7c9ef30c7275ea454e38983,https://ieeexplore.ieee.org/document/8264398/
11308,"In this paper, we introduce a preliminary model for interactions in the data market. Recent research has shown ways in which a single central data aggregator can design mechanisms to ensure it receives high quality data from a collection of users, even when the sources have an aversion to producing and reporting such estimates to the aggregator. However, we have shown that these mechanisms often break down in more realistic models, where multiple data aggregators are in competition for the users' data. We formulate the competition that arises between the aggregators as a game, and show this game admits either no Nash equilibria, or a continuum of Nash Equilibria. In the latter case, there is a fundamental ambiguity in who bears the burden of incentivizing different data sources. We are also able to calculate the price of anarchy, which measures how much social welfare is lost between the Nash equilibrium and the social optimum, i.e. between non-cooperative strategic play and cooperation.",s. sastry,Nash equilibrium,2017.0,10.1109/CDC.2017.8264398,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Westenbroek2017,False,,IEEE,Not available,Statistical estimation with strategic data sources in competitive settings,c024d2a6d7c9ef30c7275ea454e38983,https://ieeexplore.ieee.org/document/8264398/
11309,"In this paper, we introduce a preliminary model for interactions in the data market. Recent research has shown ways in which a single central data aggregator can design mechanisms to ensure it receives high quality data from a collection of users, even when the sources have an aversion to producing and reporting such estimates to the aggregator. However, we have shown that these mechanisms often break down in more realistic models, where multiple data aggregators are in competition for the users' data. We formulate the competition that arises between the aggregators as a game, and show this game admits either no Nash equilibria, or a continuum of Nash Equilibria. In the latter case, there is a fundamental ambiguity in who bears the burden of incentivizing different data sources. We are also able to calculate the price of anarchy, which measures how much social welfare is lost between the Nash equilibrium and the social optimum, i.e. between non-cooperative strategic play and cooperation.",s. sastry,Intelligent sensors,2017.0,10.1109/CDC.2017.8264398,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Westenbroek2017,False,,IEEE,Not available,Statistical estimation with strategic data sources in competitive settings,c024d2a6d7c9ef30c7275ea454e38983,https://ieeexplore.ieee.org/document/8264398/
11310,"In this paper, we introduce a preliminary model for interactions in the data market. Recent research has shown ways in which a single central data aggregator can design mechanisms to ensure it receives high quality data from a collection of users, even when the sources have an aversion to producing and reporting such estimates to the aggregator. However, we have shown that these mechanisms often break down in more realistic models, where multiple data aggregators are in competition for the users' data. We formulate the competition that arises between the aggregators as a game, and show this game admits either no Nash equilibria, or a continuum of Nash Equilibria. In the latter case, there is a fundamental ambiguity in who bears the burden of incentivizing different data sources. We are also able to calculate the price of anarchy, which measures how much social welfare is lost between the Nash equilibrium and the social optimum, i.e. between non-cooperative strategic play and cooperation.",s. sastry,Mathematical model,2017.0,10.1109/CDC.2017.8264398,2017 IEEE 56th Annual Conference on Decision and Control (CDC),Westenbroek2017,False,,IEEE,Not available,Statistical estimation with strategic data sources in competitive settings,c024d2a6d7c9ef30c7275ea454e38983,https://ieeexplore.ieee.org/document/8264398/
11311,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",wei zhong,Discrete power control,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
11312,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",wei zhong,Nash equilibrium,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
11313,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",wei zhong,potential games,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
11314,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",wei zhong,price of anarchy,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
11315,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",wei zhong,relay selection,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
11316,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11317,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",gang chen,Discrete power control,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
11318,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",gang chen,Nash equilibrium,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
11319,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",gang chen,potential games,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
11320,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",gang chen,price of anarchy,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
11321,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",gang chen,relay selection,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
11322,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",shi jin,Discrete power control,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
11323,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",shi jin,Nash equilibrium,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
11324,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",shi jin,potential games,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
11325,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",shi jin,price of anarchy,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
11326,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",shi jin,relay selection,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
11327,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11328,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11329,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",kai-kit wong,Discrete power control,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
11330,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",kai-kit wong,Nash equilibrium,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
11331,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",kai-kit wong,potential games,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
11332,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",kai-kit wong,price of anarchy,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
11333,"In this paper, we study the joint relay selection and discrete power control problem for cognitive relay networks via a game-theoretic approach subject to the interference power constraint at the primary receivers and the total available power constraint for the secondary relays. The problem is formulated as a noncooperative game where the achievable rate of the cognitive relay network is used to design a common utility. This game is shown to be a potential game which possesses at least one pure strategy Nash equilibrium (NE) and an optimal strategy profile that maximizes the rate of cognitive relay network constitutes a pure strategy NE of our proposed game. We prove that under some mild conditions, our proposed game can guarantee the feasibility of a pure strategy NE without advance knowledge of infeasible strategy profiles. Moreover, we find that the price of anarchy (PoA) of our proposed game is equal to 1 under some conditions. In order to achieve the pure strategy NE, we design a centralized iterative algorithm and a decentralized stochastic learning algorithm based on learning automata. The convergence and the complexity of our designed algorithms are discussed. It is shown that our designed algorithms can achieve optimal or near-optimal rate performance with low complexity.",kai-kit wong,relay selection,2014.0,10.1109/TSP.2014.2347261,IEEE Transactions on Signal Processing,Zhong2014,False,,IEEE,Not available,Relay Selection and Discrete Power Control for Cognitive Relay Networks via Potential Game,2464d26e2529e0e5a81267fcaf25bfc2,https://ieeexplore.ieee.org/document/6877699/
11334,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",qingqing huang,Aggregates,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
11335,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",qingqing huang,Load modeling,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
11336,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",qingqing huang,Equations,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
11337,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",qingqing huang,Electricity supply industry,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
11338,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",qingqing huang,Dynamic scheduling,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
11339,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11340,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",qingqing huang,Mathematical model,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
11341,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",qingqing huang,Pricing,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
11342,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",mardavij roozbehani,Aggregates,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
11343,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",mardavij roozbehani,Load modeling,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
11344,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",mardavij roozbehani,Equations,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
11345,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",mardavij roozbehani,Electricity supply industry,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
11346,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",mardavij roozbehani,Dynamic scheduling,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
11347,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",mardavij roozbehani,Mathematical model,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
11348,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",mardavij roozbehani,Pricing,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
11349,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",munther dahleh,Aggregates,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
11350,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11351,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",munther dahleh,Load modeling,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
11352,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",munther dahleh,Equations,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
11353,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",munther dahleh,Electricity supply industry,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
11354,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",munther dahleh,Dynamic scheduling,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
11355,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",munther dahleh,Mathematical model,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
11356,"In this paper, we examine in an abstract framework, how a tradeoff between efficiency and risk arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interested and fully rational agents dynamically update their resource consumption decisions over a finite time horizon, under the constraint that the total resource consumption requirements are met before each individual's deadline. We then compare the statistics of the stationary aggregate demand processes induced by the non-cooperative and cooperative load scheduling schemes. We show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the “price of anarchy” - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. On the other hand, when the agents can cooperate with each other in optimizing their total cost, a higher market efficiency is achieved at the cost of a higher probability of demand spikes. We thus posit that the origins of endogenous risk in such systems may lie in the market architecture, which is an inherent characteristic of the system.",munther dahleh,Pricing,2012.0,10.1109/CDC.2012.6426021,2012 IEEE 51st IEEE Conference on Decision and Control (CDC),Huang2012,False,,IEEE,Not available,Efficiency-risk tradeoffs in dynamic oligopoly markets - with application to electricity markets,4a752faa16db67850f3ea7b0d55f9c19,https://ieeexplore.ieee.org/document/6426021/
11357,"We study how an underlying network property affects network security when nodes are rational and have four choices - i) invest in protection, ii) purchase (incomplete coverage) insurance, iii) invest in protection and purchase insurance, or iv) do nothing. More specifically, using a population game model, we examine how the degree distribution of nodes influences their choices at Nash equilibria (NEs) and overall security level. We first show that there exists a degree threshold at NEs so that only the populations with degrees greater than or equal to the threshold invest in protection. Second, as the weighted degree distribution of nodes becomes stochastically larger, the risk or threat posed by a neighbor decreases, even though the aforementioned degree threshold tends to rise, hence only nodes with increasingly higher degrees invest in protection, at the same time. Third, we show that the social optimum also possesses similar properties. Finally, we derive an upper bound on the price of anarchy, which is an affine function of the average degree of nodes. This upper bound is tight in that it is achieved in some scenarios.",richard la,Cybersecurity,2014.0,10.1109/CDC.2014.7040216,53rd IEEE Conference on Decision and Control,La2014,False,,IEEE,Not available,Role of network topology in cybersecurity,b441e16e383d3046aa5174e6ac983ff1,https://ieeexplore.ieee.org/document/7040216/
11358,"We study how an underlying network property affects network security when nodes are rational and have four choices - i) invest in protection, ii) purchase (incomplete coverage) insurance, iii) invest in protection and purchase insurance, or iv) do nothing. More specifically, using a population game model, we examine how the degree distribution of nodes influences their choices at Nash equilibria (NEs) and overall security level. We first show that there exists a degree threshold at NEs so that only the populations with degrees greater than or equal to the threshold invest in protection. Second, as the weighted degree distribution of nodes becomes stochastically larger, the risk or threat posed by a neighbor decreases, even though the aforementioned degree threshold tends to rise, hence only nodes with increasingly higher degrees invest in protection, at the same time. Third, we show that the social optimum also possesses similar properties. Finally, we derive an upper bound on the price of anarchy, which is an affine function of the average degree of nodes. This upper bound is tight in that it is achieved in some scenarios.",richard la,game theory,2014.0,10.1109/CDC.2014.7040216,53rd IEEE Conference on Decision and Control,La2014,False,,IEEE,Not available,Role of network topology in cybersecurity,b441e16e383d3046aa5174e6ac983ff1,https://ieeexplore.ieee.org/document/7040216/
11359,"We study how an underlying network property affects network security when nodes are rational and have four choices - i) invest in protection, ii) purchase (incomplete coverage) insurance, iii) invest in protection and purchase insurance, or iv) do nothing. More specifically, using a population game model, we examine how the degree distribution of nodes influences their choices at Nash equilibria (NEs) and overall security level. We first show that there exists a degree threshold at NEs so that only the populations with degrees greater than or equal to the threshold invest in protection. Second, as the weighted degree distribution of nodes becomes stochastically larger, the risk or threat posed by a neighbor decreases, even though the aforementioned degree threshold tends to rise, hence only nodes with increasingly higher degrees invest in protection, at the same time. Third, we show that the social optimum also possesses similar properties. Finally, we derive an upper bound on the price of anarchy, which is an affine function of the average degree of nodes. This upper bound is tight in that it is achieved in some scenarios.",richard la,price of anarchy,2014.0,10.1109/CDC.2014.7040216,53rd IEEE Conference on Decision and Control,La2014,False,,IEEE,Not available,Role of network topology in cybersecurity,b441e16e383d3046aa5174e6ac983ff1,https://ieeexplore.ieee.org/document/7040216/
11360,"Max-min fairness (MMF) is a widely known approach to a fair allocation of bandwidth to each of the users in a network. This allocation can be computed by uniformly raising the bandwidths of all users without violating capacity constraints. We consider an extension of these allocations by raising the bandwidth with arbitrary and not necessarily uniform time-depending velocities (allocation rates). These allocations are used in a game-theoretic context for routing choices, which we formalize in progressive filling games (PFGs). We present a variety of results for equilibria in PFGs. We show that these games possess pure Nash and strong equilibria. While computation in general is NP-hard, there are polynomial-time algorithms for prominent classes of Max-Min-Fair Games (MMFG), including the case when all users have the same source-destination pair. We characterize prices of anarchy and stability for pure Nash and strong equilibria in PFGs and MMFGs when players have different or the same source-destination pairs. In addition, we show that when a designer can adjust allocation rates, it is possible to design games with optimal strong equilibria. Some initial results on polynomial-time algorithms in this direction are also derived.",tobias harks,Congestion control,2016.0,10.1109/TNET.2015.2468571,IEEE/ACM Transactions on Networking,Harks2016,False,,IEEE,Not available,Routing Games With Progressive Filling,edc64b3ec6c097f46cf736f3297d17db,https://ieeexplore.ieee.org/document/7243363/
11361,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11362,"Max-min fairness (MMF) is a widely known approach to a fair allocation of bandwidth to each of the users in a network. This allocation can be computed by uniformly raising the bandwidths of all users without violating capacity constraints. We consider an extension of these allocations by raising the bandwidth with arbitrary and not necessarily uniform time-depending velocities (allocation rates). These allocations are used in a game-theoretic context for routing choices, which we formalize in progressive filling games (PFGs). We present a variety of results for equilibria in PFGs. We show that these games possess pure Nash and strong equilibria. While computation in general is NP-hard, there are polynomial-time algorithms for prominent classes of Max-Min-Fair Games (MMFG), including the case when all users have the same source-destination pair. We characterize prices of anarchy and stability for pure Nash and strong equilibria in PFGs and MMFGs when players have different or the same source-destination pairs. In addition, we show that when a designer can adjust allocation rates, it is possible to design games with optimal strong equilibria. Some initial results on polynomial-time algorithms in this direction are also derived.",tobias harks,networks,2016.0,10.1109/TNET.2015.2468571,IEEE/ACM Transactions on Networking,Harks2016,False,,IEEE,Not available,Routing Games With Progressive Filling,edc64b3ec6c097f46cf736f3297d17db,https://ieeexplore.ieee.org/document/7243363/
11363,"Max-min fairness (MMF) is a widely known approach to a fair allocation of bandwidth to each of the users in a network. This allocation can be computed by uniformly raising the bandwidths of all users without violating capacity constraints. We consider an extension of these allocations by raising the bandwidth with arbitrary and not necessarily uniform time-depending velocities (allocation rates). These allocations are used in a game-theoretic context for routing choices, which we formalize in progressive filling games (PFGs). We present a variety of results for equilibria in PFGs. We show that these games possess pure Nash and strong equilibria. While computation in general is NP-hard, there are polynomial-time algorithms for prominent classes of Max-Min-Fair Games (MMFG), including the case when all users have the same source-destination pair. We characterize prices of anarchy and stability for pure Nash and strong equilibria in PFGs and MMFGs when players have different or the same source-destination pairs. In addition, we show that when a designer can adjust allocation rates, it is possible to design games with optimal strong equilibria. Some initial results on polynomial-time algorithms in this direction are also derived.",tobias harks,routing,2016.0,10.1109/TNET.2015.2468571,IEEE/ACM Transactions on Networking,Harks2016,False,,IEEE,Not available,Routing Games With Progressive Filling,edc64b3ec6c097f46cf736f3297d17db,https://ieeexplore.ieee.org/document/7243363/
11364,"Max-min fairness (MMF) is a widely known approach to a fair allocation of bandwidth to each of the users in a network. This allocation can be computed by uniformly raising the bandwidths of all users without violating capacity constraints. We consider an extension of these allocations by raising the bandwidth with arbitrary and not necessarily uniform time-depending velocities (allocation rates). These allocations are used in a game-theoretic context for routing choices, which we formalize in progressive filling games (PFGs). We present a variety of results for equilibria in PFGs. We show that these games possess pure Nash and strong equilibria. While computation in general is NP-hard, there are polynomial-time algorithms for prominent classes of Max-Min-Fair Games (MMFG), including the case when all users have the same source-destination pair. We characterize prices of anarchy and stability for pure Nash and strong equilibria in PFGs and MMFGs when players have different or the same source-destination pairs. In addition, we show that when a designer can adjust allocation rates, it is possible to design games with optimal strong equilibria. Some initial results on polynomial-time algorithms in this direction are also derived.",martin hoefer,Congestion control,2016.0,10.1109/TNET.2015.2468571,IEEE/ACM Transactions on Networking,Harks2016,False,,IEEE,Not available,Routing Games With Progressive Filling,edc64b3ec6c097f46cf736f3297d17db,https://ieeexplore.ieee.org/document/7243363/
11365,"Max-min fairness (MMF) is a widely known approach to a fair allocation of bandwidth to each of the users in a network. This allocation can be computed by uniformly raising the bandwidths of all users without violating capacity constraints. We consider an extension of these allocations by raising the bandwidth with arbitrary and not necessarily uniform time-depending velocities (allocation rates). These allocations are used in a game-theoretic context for routing choices, which we formalize in progressive filling games (PFGs). We present a variety of results for equilibria in PFGs. We show that these games possess pure Nash and strong equilibria. While computation in general is NP-hard, there are polynomial-time algorithms for prominent classes of Max-Min-Fair Games (MMFG), including the case when all users have the same source-destination pair. We characterize prices of anarchy and stability for pure Nash and strong equilibria in PFGs and MMFGs when players have different or the same source-destination pairs. In addition, we show that when a designer can adjust allocation rates, it is possible to design games with optimal strong equilibria. Some initial results on polynomial-time algorithms in this direction are also derived.",martin hoefer,networks,2016.0,10.1109/TNET.2015.2468571,IEEE/ACM Transactions on Networking,Harks2016,False,,IEEE,Not available,Routing Games With Progressive Filling,edc64b3ec6c097f46cf736f3297d17db,https://ieeexplore.ieee.org/document/7243363/
11366,"Max-min fairness (MMF) is a widely known approach to a fair allocation of bandwidth to each of the users in a network. This allocation can be computed by uniformly raising the bandwidths of all users without violating capacity constraints. We consider an extension of these allocations by raising the bandwidth with arbitrary and not necessarily uniform time-depending velocities (allocation rates). These allocations are used in a game-theoretic context for routing choices, which we formalize in progressive filling games (PFGs). We present a variety of results for equilibria in PFGs. We show that these games possess pure Nash and strong equilibria. While computation in general is NP-hard, there are polynomial-time algorithms for prominent classes of Max-Min-Fair Games (MMFG), including the case when all users have the same source-destination pair. We characterize prices of anarchy and stability for pure Nash and strong equilibria in PFGs and MMFGs when players have different or the same source-destination pairs. In addition, we show that when a designer can adjust allocation rates, it is possible to design games with optimal strong equilibria. Some initial results on polynomial-time algorithms in this direction are also derived.",martin hoefer,routing,2016.0,10.1109/TNET.2015.2468571,IEEE/ACM Transactions on Networking,Harks2016,False,,IEEE,Not available,Routing Games With Progressive Filling,edc64b3ec6c097f46cf736f3297d17db,https://ieeexplore.ieee.org/document/7243363/
11367,"Max-min fairness (MMF) is a widely known approach to a fair allocation of bandwidth to each of the users in a network. This allocation can be computed by uniformly raising the bandwidths of all users without violating capacity constraints. We consider an extension of these allocations by raising the bandwidth with arbitrary and not necessarily uniform time-depending velocities (allocation rates). These allocations are used in a game-theoretic context for routing choices, which we formalize in progressive filling games (PFGs). We present a variety of results for equilibria in PFGs. We show that these games possess pure Nash and strong equilibria. While computation in general is NP-hard, there are polynomial-time algorithms for prominent classes of Max-Min-Fair Games (MMFG), including the case when all users have the same source-destination pair. We characterize prices of anarchy and stability for pure Nash and strong equilibria in PFGs and MMFGs when players have different or the same source-destination pairs. In addition, we show that when a designer can adjust allocation rates, it is possible to design games with optimal strong equilibria. Some initial results on polynomial-time algorithms in this direction are also derived.",kevin schewior,Congestion control,2016.0,10.1109/TNET.2015.2468571,IEEE/ACM Transactions on Networking,Harks2016,False,,IEEE,Not available,Routing Games With Progressive Filling,edc64b3ec6c097f46cf736f3297d17db,https://ieeexplore.ieee.org/document/7243363/
11368,"Max-min fairness (MMF) is a widely known approach to a fair allocation of bandwidth to each of the users in a network. This allocation can be computed by uniformly raising the bandwidths of all users without violating capacity constraints. We consider an extension of these allocations by raising the bandwidth with arbitrary and not necessarily uniform time-depending velocities (allocation rates). These allocations are used in a game-theoretic context for routing choices, which we formalize in progressive filling games (PFGs). We present a variety of results for equilibria in PFGs. We show that these games possess pure Nash and strong equilibria. While computation in general is NP-hard, there are polynomial-time algorithms for prominent classes of Max-Min-Fair Games (MMFG), including the case when all users have the same source-destination pair. We characterize prices of anarchy and stability for pure Nash and strong equilibria in PFGs and MMFGs when players have different or the same source-destination pairs. In addition, we show that when a designer can adjust allocation rates, it is possible to design games with optimal strong equilibria. Some initial results on polynomial-time algorithms in this direction are also derived.",kevin schewior,networks,2016.0,10.1109/TNET.2015.2468571,IEEE/ACM Transactions on Networking,Harks2016,False,,IEEE,Not available,Routing Games With Progressive Filling,edc64b3ec6c097f46cf736f3297d17db,https://ieeexplore.ieee.org/document/7243363/
11369,"Max-min fairness (MMF) is a widely known approach to a fair allocation of bandwidth to each of the users in a network. This allocation can be computed by uniformly raising the bandwidths of all users without violating capacity constraints. We consider an extension of these allocations by raising the bandwidth with arbitrary and not necessarily uniform time-depending velocities (allocation rates). These allocations are used in a game-theoretic context for routing choices, which we formalize in progressive filling games (PFGs). We present a variety of results for equilibria in PFGs. We show that these games possess pure Nash and strong equilibria. While computation in general is NP-hard, there are polynomial-time algorithms for prominent classes of Max-Min-Fair Games (MMFG), including the case when all users have the same source-destination pair. We characterize prices of anarchy and stability for pure Nash and strong equilibria in PFGs and MMFGs when players have different or the same source-destination pairs. In addition, we show that when a designer can adjust allocation rates, it is possible to design games with optimal strong equilibria. Some initial results on polynomial-time algorithms in this direction are also derived.",kevin schewior,routing,2016.0,10.1109/TNET.2015.2468571,IEEE/ACM Transactions on Networking,Harks2016,False,,IEEE,Not available,Routing Games With Progressive Filling,edc64b3ec6c097f46cf736f3297d17db,https://ieeexplore.ieee.org/document/7243363/
11370,"Max-min fairness (MMF) is a widely known approach to a fair allocation of bandwidth to each of the users in a network. This allocation can be computed by uniformly raising the bandwidths of all users without violating capacity constraints. We consider an extension of these allocations by raising the bandwidth with arbitrary and not necessarily uniform time-depending velocities (allocation rates). These allocations are used in a game-theoretic context for routing choices, which we formalize in progressive filling games (PFGs). We present a variety of results for equilibria in PFGs. We show that these games possess pure Nash and strong equilibria. While computation in general is NP-hard, there are polynomial-time algorithms for prominent classes of Max-Min-Fair Games (MMFG), including the case when all users have the same source-destination pair. We characterize prices of anarchy and stability for pure Nash and strong equilibria in PFGs and MMFGs when players have different or the same source-destination pairs. In addition, we show that when a designer can adjust allocation rates, it is possible to design games with optimal strong equilibria. Some initial results on polynomial-time algorithms in this direction are also derived.",alexander skopalik,Congestion control,2016.0,10.1109/TNET.2015.2468571,IEEE/ACM Transactions on Networking,Harks2016,False,,IEEE,Not available,Routing Games With Progressive Filling,edc64b3ec6c097f46cf736f3297d17db,https://ieeexplore.ieee.org/document/7243363/
11371,"Max-min fairness (MMF) is a widely known approach to a fair allocation of bandwidth to each of the users in a network. This allocation can be computed by uniformly raising the bandwidths of all users without violating capacity constraints. We consider an extension of these allocations by raising the bandwidth with arbitrary and not necessarily uniform time-depending velocities (allocation rates). These allocations are used in a game-theoretic context for routing choices, which we formalize in progressive filling games (PFGs). We present a variety of results for equilibria in PFGs. We show that these games possess pure Nash and strong equilibria. While computation in general is NP-hard, there are polynomial-time algorithms for prominent classes of Max-Min-Fair Games (MMFG), including the case when all users have the same source-destination pair. We characterize prices of anarchy and stability for pure Nash and strong equilibria in PFGs and MMFGs when players have different or the same source-destination pairs. In addition, we show that when a designer can adjust allocation rates, it is possible to design games with optimal strong equilibria. Some initial results on polynomial-time algorithms in this direction are also derived.",alexander skopalik,networks,2016.0,10.1109/TNET.2015.2468571,IEEE/ACM Transactions on Networking,Harks2016,False,,IEEE,Not available,Routing Games With Progressive Filling,edc64b3ec6c097f46cf736f3297d17db,https://ieeexplore.ieee.org/document/7243363/
11372,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11373,"Max-min fairness (MMF) is a widely known approach to a fair allocation of bandwidth to each of the users in a network. This allocation can be computed by uniformly raising the bandwidths of all users without violating capacity constraints. We consider an extension of these allocations by raising the bandwidth with arbitrary and not necessarily uniform time-depending velocities (allocation rates). These allocations are used in a game-theoretic context for routing choices, which we formalize in progressive filling games (PFGs). We present a variety of results for equilibria in PFGs. We show that these games possess pure Nash and strong equilibria. While computation in general is NP-hard, there are polynomial-time algorithms for prominent classes of Max-Min-Fair Games (MMFG), including the case when all users have the same source-destination pair. We characterize prices of anarchy and stability for pure Nash and strong equilibria in PFGs and MMFGs when players have different or the same source-destination pairs. In addition, we show that when a designer can adjust allocation rates, it is possible to design games with optimal strong equilibria. Some initial results on polynomial-time algorithms in this direction are also derived.",alexander skopalik,routing,2016.0,10.1109/TNET.2015.2468571,IEEE/ACM Transactions on Networking,Harks2016,False,,IEEE,Not available,Routing Games With Progressive Filling,edc64b3ec6c097f46cf736f3297d17db,https://ieeexplore.ieee.org/document/7243363/
11374,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",jie xu,Cooperative networks,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
11375,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",jie xu,distributed protocols,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
11376,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",jie xu,economics networks,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
11377,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",jie xu,imperfect monitoring,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
11378,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",jie xu,incentive design,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
11379,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",jie xu,indirect reciprocity,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
11380,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",jie xu,ratings,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
11381,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",jie xu,repeated games,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
11382,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",jie xu,social networks,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
11383,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
11384,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",jie xu,social reciprocation,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
11385,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",yangbo song,Cooperative networks,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
11386,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",yangbo song,distributed protocols,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
11387,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",yangbo song,economics networks,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
11388,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",yangbo song,imperfect monitoring,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
11389,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",yangbo song,incentive design,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
11390,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",yangbo song,indirect reciprocity,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
11391,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",yangbo song,ratings,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
11392,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",yangbo song,repeated games,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
11393,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",yangbo song,social networks,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
11394,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
11395,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",yangbo song,social reciprocation,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
11396,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",mihaela schaar,Cooperative networks,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
11397,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",mihaela schaar,distributed protocols,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
11398,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",mihaela schaar,economics networks,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
11399,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",mihaela schaar,imperfect monitoring,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
11400,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",mihaela schaar,incentive design,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
11401,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",mihaela schaar,indirect reciprocity,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
11402,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",mihaela schaar,ratings,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
11403,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",mihaela schaar,repeated games,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
11404,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",mihaela schaar,social networks,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
11405,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
11406,"In social, economic and engineering networks, connected agents need to cooperate by repeatedly sharing information and/or goods. Typically, sharing is costly and there are no immediate benefits for agents who share. Hence, agents who strategically aim to maximize their own individual utilities will “free-ride” because they lack incentives to cooperate/share, thereby leading to inefficient operation or even collapse of networks. To incentivize the strategic agents to cooperate with each other, we design distributed rating protocols which exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments: agents that have behaved as directed enjoy high ratings-and hence greater future access to the information/goods of others; agents that have not behaved as directed enjoy low ratings-and hence less future access to the information/goods of others. Unlike existing rating protocols, the proposed protocol operates in a distributed manner and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many networks, the price of anarchy (PoA) obtained by adopting the proposed rating protocols is 1, that is, the optimal social welfare is attained. In networks where PoA is larger than 1, we show that the proposed rating protocol significantly outperforms existing incentive mechanisms. Last but not least, the proposed rating protocols can also operate efficiently in dynamic networks, where new agents enter the network over time.",mihaela schaar,social reciprocation,2014.0,10.1109/JSTSP.2014.2316597,IEEE Journal of Selected Topics in Signal Processing,Xu2014,False,,IEEE,Not available,Sharing in Networks of Strategic Agents,4b6fccae775b9983933715810487a90a,https://ieeexplore.ieee.org/document/6787069/
11407,"Privacy preservation is one of the greatest concerns in big data. As one of extensive applications in big data, privacy preserving data publication (PPDP) has been an important research field. One of the fundamental challenges in PPDP is the trade-off problem between privacy and utility of the single and independent data set. However, recent research has shown that the advanced privacy mechanism, i.e., differential privacy, is vulnerable when multiple data sets are correlated. In this case, the trade-off problem between privacy and utility is evolved into a game problem, in which payoff of each player is dependent on his and his neighbors&amp;#x2019; privacy parameters. In this paper, we firstly present the definition of correlated differential privacy to evaluate the real privacy level of a single data set influenced by the other data sets. Then, we construct a game model of multiple players, in which each publishes data set sanitized by differential privacy. Next, we analyze the existence and uniqueness of the pure Nash Equilibrium. We refer to a notion, i.e., the price of anarchy, to evaluate efficiency of the pure Nash Equilibrium. Finally, we show the correctness of our game analysis via simulation experiments.",xiaotong wu,Differential privacy,,10.1109/TBDATA.2017.2701817,IEEE Transactions on Big Data,WuNone,False,,IEEE,Not available,Game Theory Based Correlated Privacy Preserving Analysis in Big Data,879e89265b7f41b5d7c43d81c3555d12,
11408,"Privacy preservation is one of the greatest concerns in big data. As one of extensive applications in big data, privacy preserving data publication (PPDP) has been an important research field. One of the fundamental challenges in PPDP is the trade-off problem between privacy and utility of the single and independent data set. However, recent research has shown that the advanced privacy mechanism, i.e., differential privacy, is vulnerable when multiple data sets are correlated. In this case, the trade-off problem between privacy and utility is evolved into a game problem, in which payoff of each player is dependent on his and his neighbors&amp;#x2019; privacy parameters. In this paper, we firstly present the definition of correlated differential privacy to evaluate the real privacy level of a single data set influenced by the other data sets. Then, we construct a game model of multiple players, in which each publishes data set sanitized by differential privacy. Next, we analyze the existence and uniqueness of the pure Nash Equilibrium. We refer to a notion, i.e., the price of anarchy, to evaluate efficiency of the pure Nash Equilibrium. Finally, we show the correctness of our game analysis via simulation experiments.",xiaotong wu,privacy preservation,,10.1109/TBDATA.2017.2701817,IEEE Transactions on Big Data,WuNone,False,,IEEE,Not available,Game Theory Based Correlated Privacy Preserving Analysis in Big Data,879e89265b7f41b5d7c43d81c3555d12,
11409,"Privacy preservation is one of the greatest concerns in big data. As one of extensive applications in big data, privacy preserving data publication (PPDP) has been an important research field. One of the fundamental challenges in PPDP is the trade-off problem between privacy and utility of the single and independent data set. However, recent research has shown that the advanced privacy mechanism, i.e., differential privacy, is vulnerable when multiple data sets are correlated. In this case, the trade-off problem between privacy and utility is evolved into a game problem, in which payoff of each player is dependent on his and his neighbors&amp;#x2019; privacy parameters. In this paper, we firstly present the definition of correlated differential privacy to evaluate the real privacy level of a single data set influenced by the other data sets. Then, we construct a game model of multiple players, in which each publishes data set sanitized by differential privacy. Next, we analyze the existence and uniqueness of the pure Nash Equilibrium. We refer to a notion, i.e., the price of anarchy, to evaluate efficiency of the pure Nash Equilibrium. Finally, we show the correctness of our game analysis via simulation experiments.",xiaotong wu,game theory,,10.1109/TBDATA.2017.2701817,IEEE Transactions on Big Data,WuNone,False,,IEEE,Not available,Game Theory Based Correlated Privacy Preserving Analysis in Big Data,879e89265b7f41b5d7c43d81c3555d12,
11410,"Privacy preservation is one of the greatest concerns in big data. As one of extensive applications in big data, privacy preserving data publication (PPDP) has been an important research field. One of the fundamental challenges in PPDP is the trade-off problem between privacy and utility of the single and independent data set. However, recent research has shown that the advanced privacy mechanism, i.e., differential privacy, is vulnerable when multiple data sets are correlated. In this case, the trade-off problem between privacy and utility is evolved into a game problem, in which payoff of each player is dependent on his and his neighbors&amp;#x2019; privacy parameters. In this paper, we firstly present the definition of correlated differential privacy to evaluate the real privacy level of a single data set influenced by the other data sets. Then, we construct a game model of multiple players, in which each publishes data set sanitized by differential privacy. Next, we analyze the existence and uniqueness of the pure Nash Equilibrium. We refer to a notion, i.e., the price of anarchy, to evaluate efficiency of the pure Nash Equilibrium. Finally, we show the correctness of our game analysis via simulation experiments.",xiaotong wu,big data,,10.1109/TBDATA.2017.2701817,IEEE Transactions on Big Data,WuNone,False,,IEEE,Not available,Game Theory Based Correlated Privacy Preserving Analysis in Big Data,879e89265b7f41b5d7c43d81c3555d12,
11411,"Privacy preservation is one of the greatest concerns in big data. As one of extensive applications in big data, privacy preserving data publication (PPDP) has been an important research field. One of the fundamental challenges in PPDP is the trade-off problem between privacy and utility of the single and independent data set. However, recent research has shown that the advanced privacy mechanism, i.e., differential privacy, is vulnerable when multiple data sets are correlated. In this case, the trade-off problem between privacy and utility is evolved into a game problem, in which payoff of each player is dependent on his and his neighbors&amp;#x2019; privacy parameters. In this paper, we firstly present the definition of correlated differential privacy to evaluate the real privacy level of a single data set influenced by the other data sets. Then, we construct a game model of multiple players, in which each publishes data set sanitized by differential privacy. Next, we analyze the existence and uniqueness of the pure Nash Equilibrium. We refer to a notion, i.e., the price of anarchy, to evaluate efficiency of the pure Nash Equilibrium. Finally, we show the correctness of our game analysis via simulation experiments.",taotao wu,Differential privacy,,10.1109/TBDATA.2017.2701817,IEEE Transactions on Big Data,WuNone,False,,IEEE,Not available,Game Theory Based Correlated Privacy Preserving Analysis in Big Data,879e89265b7f41b5d7c43d81c3555d12,
11412,"Privacy preservation is one of the greatest concerns in big data. As one of extensive applications in big data, privacy preserving data publication (PPDP) has been an important research field. One of the fundamental challenges in PPDP is the trade-off problem between privacy and utility of the single and independent data set. However, recent research has shown that the advanced privacy mechanism, i.e., differential privacy, is vulnerable when multiple data sets are correlated. In this case, the trade-off problem between privacy and utility is evolved into a game problem, in which payoff of each player is dependent on his and his neighbors&amp;#x2019; privacy parameters. In this paper, we firstly present the definition of correlated differential privacy to evaluate the real privacy level of a single data set influenced by the other data sets. Then, we construct a game model of multiple players, in which each publishes data set sanitized by differential privacy. Next, we analyze the existence and uniqueness of the pure Nash Equilibrium. We refer to a notion, i.e., the price of anarchy, to evaluate efficiency of the pure Nash Equilibrium. Finally, we show the correctness of our game analysis via simulation experiments.",taotao wu,privacy preservation,,10.1109/TBDATA.2017.2701817,IEEE Transactions on Big Data,WuNone,False,,IEEE,Not available,Game Theory Based Correlated Privacy Preserving Analysis in Big Data,879e89265b7f41b5d7c43d81c3555d12,
11413,"Privacy preservation is one of the greatest concerns in big data. As one of extensive applications in big data, privacy preserving data publication (PPDP) has been an important research field. One of the fundamental challenges in PPDP is the trade-off problem between privacy and utility of the single and independent data set. However, recent research has shown that the advanced privacy mechanism, i.e., differential privacy, is vulnerable when multiple data sets are correlated. In this case, the trade-off problem between privacy and utility is evolved into a game problem, in which payoff of each player is dependent on his and his neighbors&amp;#x2019; privacy parameters. In this paper, we firstly present the definition of correlated differential privacy to evaluate the real privacy level of a single data set influenced by the other data sets. Then, we construct a game model of multiple players, in which each publishes data set sanitized by differential privacy. Next, we analyze the existence and uniqueness of the pure Nash Equilibrium. We refer to a notion, i.e., the price of anarchy, to evaluate efficiency of the pure Nash Equilibrium. Finally, we show the correctness of our game analysis via simulation experiments.",taotao wu,game theory,,10.1109/TBDATA.2017.2701817,IEEE Transactions on Big Data,WuNone,False,,IEEE,Not available,Game Theory Based Correlated Privacy Preserving Analysis in Big Data,879e89265b7f41b5d7c43d81c3555d12,
11414,"Privacy preservation is one of the greatest concerns in big data. As one of extensive applications in big data, privacy preserving data publication (PPDP) has been an important research field. One of the fundamental challenges in PPDP is the trade-off problem between privacy and utility of the single and independent data set. However, recent research has shown that the advanced privacy mechanism, i.e., differential privacy, is vulnerable when multiple data sets are correlated. In this case, the trade-off problem between privacy and utility is evolved into a game problem, in which payoff of each player is dependent on his and his neighbors&amp;#x2019; privacy parameters. In this paper, we firstly present the definition of correlated differential privacy to evaluate the real privacy level of a single data set influenced by the other data sets. Then, we construct a game model of multiple players, in which each publishes data set sanitized by differential privacy. Next, we analyze the existence and uniqueness of the pure Nash Equilibrium. We refer to a notion, i.e., the price of anarchy, to evaluate efficiency of the pure Nash Equilibrium. Finally, we show the correctness of our game analysis via simulation experiments.",taotao wu,big data,,10.1109/TBDATA.2017.2701817,IEEE Transactions on Big Data,WuNone,False,,IEEE,Not available,Game Theory Based Correlated Privacy Preserving Analysis in Big Data,879e89265b7f41b5d7c43d81c3555d12,
11415,"Privacy preservation is one of the greatest concerns in big data. As one of extensive applications in big data, privacy preserving data publication (PPDP) has been an important research field. One of the fundamental challenges in PPDP is the trade-off problem between privacy and utility of the single and independent data set. However, recent research has shown that the advanced privacy mechanism, i.e., differential privacy, is vulnerable when multiple data sets are correlated. In this case, the trade-off problem between privacy and utility is evolved into a game problem, in which payoff of each player is dependent on his and his neighbors&amp;#x2019; privacy parameters. In this paper, we firstly present the definition of correlated differential privacy to evaluate the real privacy level of a single data set influenced by the other data sets. Then, we construct a game model of multiple players, in which each publishes data set sanitized by differential privacy. Next, we analyze the existence and uniqueness of the pure Nash Equilibrium. We refer to a notion, i.e., the price of anarchy, to evaluate efficiency of the pure Nash Equilibrium. Finally, we show the correctness of our game analysis via simulation experiments.",maqbool khan,Differential privacy,,10.1109/TBDATA.2017.2701817,IEEE Transactions on Big Data,WuNone,False,,IEEE,Not available,Game Theory Based Correlated Privacy Preserving Analysis in Big Data,879e89265b7f41b5d7c43d81c3555d12,
11416,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
11417,"Privacy preservation is one of the greatest concerns in big data. As one of extensive applications in big data, privacy preserving data publication (PPDP) has been an important research field. One of the fundamental challenges in PPDP is the trade-off problem between privacy and utility of the single and independent data set. However, recent research has shown that the advanced privacy mechanism, i.e., differential privacy, is vulnerable when multiple data sets are correlated. In this case, the trade-off problem between privacy and utility is evolved into a game problem, in which payoff of each player is dependent on his and his neighbors&amp;#x2019; privacy parameters. In this paper, we firstly present the definition of correlated differential privacy to evaluate the real privacy level of a single data set influenced by the other data sets. Then, we construct a game model of multiple players, in which each publishes data set sanitized by differential privacy. Next, we analyze the existence and uniqueness of the pure Nash Equilibrium. We refer to a notion, i.e., the price of anarchy, to evaluate efficiency of the pure Nash Equilibrium. Finally, we show the correctness of our game analysis via simulation experiments.",maqbool khan,privacy preservation,,10.1109/TBDATA.2017.2701817,IEEE Transactions on Big Data,WuNone,False,,IEEE,Not available,Game Theory Based Correlated Privacy Preserving Analysis in Big Data,879e89265b7f41b5d7c43d81c3555d12,
11418,"Privacy preservation is one of the greatest concerns in big data. As one of extensive applications in big data, privacy preserving data publication (PPDP) has been an important research field. One of the fundamental challenges in PPDP is the trade-off problem between privacy and utility of the single and independent data set. However, recent research has shown that the advanced privacy mechanism, i.e., differential privacy, is vulnerable when multiple data sets are correlated. In this case, the trade-off problem between privacy and utility is evolved into a game problem, in which payoff of each player is dependent on his and his neighbors&amp;#x2019; privacy parameters. In this paper, we firstly present the definition of correlated differential privacy to evaluate the real privacy level of a single data set influenced by the other data sets. Then, we construct a game model of multiple players, in which each publishes data set sanitized by differential privacy. Next, we analyze the existence and uniqueness of the pure Nash Equilibrium. We refer to a notion, i.e., the price of anarchy, to evaluate efficiency of the pure Nash Equilibrium. Finally, we show the correctness of our game analysis via simulation experiments.",maqbool khan,game theory,,10.1109/TBDATA.2017.2701817,IEEE Transactions on Big Data,WuNone,False,,IEEE,Not available,Game Theory Based Correlated Privacy Preserving Analysis in Big Data,879e89265b7f41b5d7c43d81c3555d12,
11419,"Privacy preservation is one of the greatest concerns in big data. As one of extensive applications in big data, privacy preserving data publication (PPDP) has been an important research field. One of the fundamental challenges in PPDP is the trade-off problem between privacy and utility of the single and independent data set. However, recent research has shown that the advanced privacy mechanism, i.e., differential privacy, is vulnerable when multiple data sets are correlated. In this case, the trade-off problem between privacy and utility is evolved into a game problem, in which payoff of each player is dependent on his and his neighbors&amp;#x2019; privacy parameters. In this paper, we firstly present the definition of correlated differential privacy to evaluate the real privacy level of a single data set influenced by the other data sets. Then, we construct a game model of multiple players, in which each publishes data set sanitized by differential privacy. Next, we analyze the existence and uniqueness of the pure Nash Equilibrium. We refer to a notion, i.e., the price of anarchy, to evaluate efficiency of the pure Nash Equilibrium. Finally, we show the correctness of our game analysis via simulation experiments.",maqbool khan,big data,,10.1109/TBDATA.2017.2701817,IEEE Transactions on Big Data,WuNone,False,,IEEE,Not available,Game Theory Based Correlated Privacy Preserving Analysis in Big Data,879e89265b7f41b5d7c43d81c3555d12,
11420,"Privacy preservation is one of the greatest concerns in big data. As one of extensive applications in big data, privacy preserving data publication (PPDP) has been an important research field. One of the fundamental challenges in PPDP is the trade-off problem between privacy and utility of the single and independent data set. However, recent research has shown that the advanced privacy mechanism, i.e., differential privacy, is vulnerable when multiple data sets are correlated. In this case, the trade-off problem between privacy and utility is evolved into a game problem, in which payoff of each player is dependent on his and his neighbors&amp;#x2019; privacy parameters. In this paper, we firstly present the definition of correlated differential privacy to evaluate the real privacy level of a single data set influenced by the other data sets. Then, we construct a game model of multiple players, in which each publishes data set sanitized by differential privacy. Next, we analyze the existence and uniqueness of the pure Nash Equilibrium. We refer to a notion, i.e., the price of anarchy, to evaluate efficiency of the pure Nash Equilibrium. Finally, we show the correctness of our game analysis via simulation experiments.",qiang ni,Differential privacy,,10.1109/TBDATA.2017.2701817,IEEE Transactions on Big Data,WuNone,False,,IEEE,Not available,Game Theory Based Correlated Privacy Preserving Analysis in Big Data,879e89265b7f41b5d7c43d81c3555d12,
11421,"Privacy preservation is one of the greatest concerns in big data. As one of extensive applications in big data, privacy preserving data publication (PPDP) has been an important research field. One of the fundamental challenges in PPDP is the trade-off problem between privacy and utility of the single and independent data set. However, recent research has shown that the advanced privacy mechanism, i.e., differential privacy, is vulnerable when multiple data sets are correlated. In this case, the trade-off problem between privacy and utility is evolved into a game problem, in which payoff of each player is dependent on his and his neighbors&amp;#x2019; privacy parameters. In this paper, we firstly present the definition of correlated differential privacy to evaluate the real privacy level of a single data set influenced by the other data sets. Then, we construct a game model of multiple players, in which each publishes data set sanitized by differential privacy. Next, we analyze the existence and uniqueness of the pure Nash Equilibrium. We refer to a notion, i.e., the price of anarchy, to evaluate efficiency of the pure Nash Equilibrium. Finally, we show the correctness of our game analysis via simulation experiments.",qiang ni,privacy preservation,,10.1109/TBDATA.2017.2701817,IEEE Transactions on Big Data,WuNone,False,,IEEE,Not available,Game Theory Based Correlated Privacy Preserving Analysis in Big Data,879e89265b7f41b5d7c43d81c3555d12,
11422,"Privacy preservation is one of the greatest concerns in big data. As one of extensive applications in big data, privacy preserving data publication (PPDP) has been an important research field. One of the fundamental challenges in PPDP is the trade-off problem between privacy and utility of the single and independent data set. However, recent research has shown that the advanced privacy mechanism, i.e., differential privacy, is vulnerable when multiple data sets are correlated. In this case, the trade-off problem between privacy and utility is evolved into a game problem, in which payoff of each player is dependent on his and his neighbors&amp;#x2019; privacy parameters. In this paper, we firstly present the definition of correlated differential privacy to evaluate the real privacy level of a single data set influenced by the other data sets. Then, we construct a game model of multiple players, in which each publishes data set sanitized by differential privacy. Next, we analyze the existence and uniqueness of the pure Nash Equilibrium. We refer to a notion, i.e., the price of anarchy, to evaluate efficiency of the pure Nash Equilibrium. Finally, we show the correctness of our game analysis via simulation experiments.",qiang ni,game theory,,10.1109/TBDATA.2017.2701817,IEEE Transactions on Big Data,WuNone,False,,IEEE,Not available,Game Theory Based Correlated Privacy Preserving Analysis in Big Data,879e89265b7f41b5d7c43d81c3555d12,
11423,"Privacy preservation is one of the greatest concerns in big data. As one of extensive applications in big data, privacy preserving data publication (PPDP) has been an important research field. One of the fundamental challenges in PPDP is the trade-off problem between privacy and utility of the single and independent data set. However, recent research has shown that the advanced privacy mechanism, i.e., differential privacy, is vulnerable when multiple data sets are correlated. In this case, the trade-off problem between privacy and utility is evolved into a game problem, in which payoff of each player is dependent on his and his neighbors&amp;#x2019; privacy parameters. In this paper, we firstly present the definition of correlated differential privacy to evaluate the real privacy level of a single data set influenced by the other data sets. Then, we construct a game model of multiple players, in which each publishes data set sanitized by differential privacy. Next, we analyze the existence and uniqueness of the pure Nash Equilibrium. We refer to a notion, i.e., the price of anarchy, to evaluate efficiency of the pure Nash Equilibrium. Finally, we show the correctness of our game analysis via simulation experiments.",qiang ni,big data,,10.1109/TBDATA.2017.2701817,IEEE Transactions on Big Data,WuNone,False,,IEEE,Not available,Game Theory Based Correlated Privacy Preserving Analysis in Big Data,879e89265b7f41b5d7c43d81c3555d12,
11424,"Privacy preservation is one of the greatest concerns in big data. As one of extensive applications in big data, privacy preserving data publication (PPDP) has been an important research field. One of the fundamental challenges in PPDP is the trade-off problem between privacy and utility of the single and independent data set. However, recent research has shown that the advanced privacy mechanism, i.e., differential privacy, is vulnerable when multiple data sets are correlated. In this case, the trade-off problem between privacy and utility is evolved into a game problem, in which payoff of each player is dependent on his and his neighbors&amp;#x2019; privacy parameters. In this paper, we firstly present the definition of correlated differential privacy to evaluate the real privacy level of a single data set influenced by the other data sets. Then, we construct a game model of multiple players, in which each publishes data set sanitized by differential privacy. Next, we analyze the existence and uniqueness of the pure Nash Equilibrium. We refer to a notion, i.e., the price of anarchy, to evaluate efficiency of the pure Nash Equilibrium. Finally, we show the correctness of our game analysis via simulation experiments.",wanchun dou,Differential privacy,,10.1109/TBDATA.2017.2701817,IEEE Transactions on Big Data,WuNone,False,,IEEE,Not available,Game Theory Based Correlated Privacy Preserving Analysis in Big Data,879e89265b7f41b5d7c43d81c3555d12,
11425,"Privacy preservation is one of the greatest concerns in big data. As one of extensive applications in big data, privacy preserving data publication (PPDP) has been an important research field. One of the fundamental challenges in PPDP is the trade-off problem between privacy and utility of the single and independent data set. However, recent research has shown that the advanced privacy mechanism, i.e., differential privacy, is vulnerable when multiple data sets are correlated. In this case, the trade-off problem between privacy and utility is evolved into a game problem, in which payoff of each player is dependent on his and his neighbors&amp;#x2019; privacy parameters. In this paper, we firstly present the definition of correlated differential privacy to evaluate the real privacy level of a single data set influenced by the other data sets. Then, we construct a game model of multiple players, in which each publishes data set sanitized by differential privacy. Next, we analyze the existence and uniqueness of the pure Nash Equilibrium. We refer to a notion, i.e., the price of anarchy, to evaluate efficiency of the pure Nash Equilibrium. Finally, we show the correctness of our game analysis via simulation experiments.",wanchun dou,privacy preservation,,10.1109/TBDATA.2017.2701817,IEEE Transactions on Big Data,WuNone,False,,IEEE,Not available,Game Theory Based Correlated Privacy Preserving Analysis in Big Data,879e89265b7f41b5d7c43d81c3555d12,
11426,"Privacy preservation is one of the greatest concerns in big data. As one of extensive applications in big data, privacy preserving data publication (PPDP) has been an important research field. One of the fundamental challenges in PPDP is the trade-off problem between privacy and utility of the single and independent data set. However, recent research has shown that the advanced privacy mechanism, i.e., differential privacy, is vulnerable when multiple data sets are correlated. In this case, the trade-off problem between privacy and utility is evolved into a game problem, in which payoff of each player is dependent on his and his neighbors&amp;#x2019; privacy parameters. In this paper, we firstly present the definition of correlated differential privacy to evaluate the real privacy level of a single data set influenced by the other data sets. Then, we construct a game model of multiple players, in which each publishes data set sanitized by differential privacy. Next, we analyze the existence and uniqueness of the pure Nash Equilibrium. We refer to a notion, i.e., the price of anarchy, to evaluate efficiency of the pure Nash Equilibrium. Finally, we show the correctness of our game analysis via simulation experiments.",wanchun dou,game theory,,10.1109/TBDATA.2017.2701817,IEEE Transactions on Big Data,WuNone,False,,IEEE,Not available,Game Theory Based Correlated Privacy Preserving Analysis in Big Data,879e89265b7f41b5d7c43d81c3555d12,
11427,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
11428,"Privacy preservation is one of the greatest concerns in big data. As one of extensive applications in big data, privacy preserving data publication (PPDP) has been an important research field. One of the fundamental challenges in PPDP is the trade-off problem between privacy and utility of the single and independent data set. However, recent research has shown that the advanced privacy mechanism, i.e., differential privacy, is vulnerable when multiple data sets are correlated. In this case, the trade-off problem between privacy and utility is evolved into a game problem, in which payoff of each player is dependent on his and his neighbors&amp;#x2019; privacy parameters. In this paper, we firstly present the definition of correlated differential privacy to evaluate the real privacy level of a single data set influenced by the other data sets. Then, we construct a game model of multiple players, in which each publishes data set sanitized by differential privacy. Next, we analyze the existence and uniqueness of the pure Nash Equilibrium. We refer to a notion, i.e., the price of anarchy, to evaluate efficiency of the pure Nash Equilibrium. Finally, we show the correctness of our game analysis via simulation experiments.",wanchun dou,big data,,10.1109/TBDATA.2017.2701817,IEEE Transactions on Big Data,WuNone,False,,IEEE,Not available,Game Theory Based Correlated Privacy Preserving Analysis in Big Data,879e89265b7f41b5d7c43d81c3555d12,
11429,"Today's wireless networks are increasingly crowded with an explosion of wireless users, who have greater and more diverse quality of service (QoS) demands than ever before. However, the amount of spectrum that can be used to satisfy these demands remains finite. This leads to a great challenge for wireless users to effectively share the spectrum to achieve their QoS requirements. This paper presents a game theoretic model for spectrum sharing, where users seek to satisfy their QoS demands in a distributed fashion. Our spectrum sharing model is quite general, because we allow different wireless channels to provide different QoS, depending upon their channel conditions and how many users are trying to access them. Also, users can be highly heterogeneous, with different QoS demands, depending upon their activities, hardware capabilities, and technology choices. Under such a general setting, we show that it is NP hard to find a spectrum allocation which satisfies the maximum number of users' QoS requirements in a centralized fashion. We also show that allowing users to self-organize through distributed channel selections is a viable alternative to the centralized optimization, because better response updating is guaranteed to reach a pure Nash equilibria in polynomial time. By bounding the price of anarchy, we demonstrate that the worst case pure Nash equilibrium can be close to optimal, when users and channels are not very heterogenous. We also extend our model by considering the frequency spatial reuse, and consider the user interactions as a game upon a graph where players only contend with their neighbors. We prove that better response updating is still guaranteed to reach a pure Nash equilibrium in this more general spatial QoS satisfaction game.",richard southwell,Distributed spectrum sharing,2014.0,10.1109/JSAC.2014.1403008,IEEE Journal on Selected Areas in Communications,Southwell2014,False,,IEEE,Not available,Quality of Service Games for Spectrum Sharing,bb08892fcf8814850e29eb933fdfcfbb,https://ieeexplore.ieee.org/document/6746252/
11430,"Today's wireless networks are increasingly crowded with an explosion of wireless users, who have greater and more diverse quality of service (QoS) demands than ever before. However, the amount of spectrum that can be used to satisfy these demands remains finite. This leads to a great challenge for wireless users to effectively share the spectrum to achieve their QoS requirements. This paper presents a game theoretic model for spectrum sharing, where users seek to satisfy their QoS demands in a distributed fashion. Our spectrum sharing model is quite general, because we allow different wireless channels to provide different QoS, depending upon their channel conditions and how many users are trying to access them. Also, users can be highly heterogeneous, with different QoS demands, depending upon their activities, hardware capabilities, and technology choices. Under such a general setting, we show that it is NP hard to find a spectrum allocation which satisfies the maximum number of users' QoS requirements in a centralized fashion. We also show that allowing users to self-organize through distributed channel selections is a viable alternative to the centralized optimization, because better response updating is guaranteed to reach a pure Nash equilibria in polynomial time. By bounding the price of anarchy, we demonstrate that the worst case pure Nash equilibrium can be close to optimal, when users and channels are not very heterogenous. We also extend our model by considering the frequency spatial reuse, and consider the user interactions as a game upon a graph where players only contend with their neighbors. We prove that better response updating is still guaranteed to reach a pure Nash equilibrium in this more general spatial QoS satisfaction game.",richard southwell,game theory,2014.0,10.1109/JSAC.2014.1403008,IEEE Journal on Selected Areas in Communications,Southwell2014,False,,IEEE,Not available,Quality of Service Games for Spectrum Sharing,bb08892fcf8814850e29eb933fdfcfbb,https://ieeexplore.ieee.org/document/6746252/
11431,"Today's wireless networks are increasingly crowded with an explosion of wireless users, who have greater and more diverse quality of service (QoS) demands than ever before. However, the amount of spectrum that can be used to satisfy these demands remains finite. This leads to a great challenge for wireless users to effectively share the spectrum to achieve their QoS requirements. This paper presents a game theoretic model for spectrum sharing, where users seek to satisfy their QoS demands in a distributed fashion. Our spectrum sharing model is quite general, because we allow different wireless channels to provide different QoS, depending upon their channel conditions and how many users are trying to access them. Also, users can be highly heterogeneous, with different QoS demands, depending upon their activities, hardware capabilities, and technology choices. Under such a general setting, we show that it is NP hard to find a spectrum allocation which satisfies the maximum number of users' QoS requirements in a centralized fashion. We also show that allowing users to self-organize through distributed channel selections is a viable alternative to the centralized optimization, because better response updating is guaranteed to reach a pure Nash equilibria in polynomial time. By bounding the price of anarchy, we demonstrate that the worst case pure Nash equilibrium can be close to optimal, when users and channels are not very heterogenous. We also extend our model by considering the frequency spatial reuse, and consider the user interactions as a game upon a graph where players only contend with their neighbors. We prove that better response updating is still guaranteed to reach a pure Nash equilibrium in this more general spatial QoS satisfaction game.",richard southwell,Nash equilibrium,2014.0,10.1109/JSAC.2014.1403008,IEEE Journal on Selected Areas in Communications,Southwell2014,False,,IEEE,Not available,Quality of Service Games for Spectrum Sharing,bb08892fcf8814850e29eb933fdfcfbb,https://ieeexplore.ieee.org/document/6746252/
11432,"Today's wireless networks are increasingly crowded with an explosion of wireless users, who have greater and more diverse quality of service (QoS) demands than ever before. However, the amount of spectrum that can be used to satisfy these demands remains finite. This leads to a great challenge for wireless users to effectively share the spectrum to achieve their QoS requirements. This paper presents a game theoretic model for spectrum sharing, where users seek to satisfy their QoS demands in a distributed fashion. Our spectrum sharing model is quite general, because we allow different wireless channels to provide different QoS, depending upon their channel conditions and how many users are trying to access them. Also, users can be highly heterogeneous, with different QoS demands, depending upon their activities, hardware capabilities, and technology choices. Under such a general setting, we show that it is NP hard to find a spectrum allocation which satisfies the maximum number of users' QoS requirements in a centralized fashion. We also show that allowing users to self-organize through distributed channel selections is a viable alternative to the centralized optimization, because better response updating is guaranteed to reach a pure Nash equilibria in polynomial time. By bounding the price of anarchy, we demonstrate that the worst case pure Nash equilibrium can be close to optimal, when users and channels are not very heterogenous. We also extend our model by considering the frequency spatial reuse, and consider the user interactions as a game upon a graph where players only contend with their neighbors. We prove that better response updating is still guaranteed to reach a pure Nash equilibrium in this more general spatial QoS satisfaction game.",richard southwell,quality of service (QoS),2014.0,10.1109/JSAC.2014.1403008,IEEE Journal on Selected Areas in Communications,Southwell2014,False,,IEEE,Not available,Quality of Service Games for Spectrum Sharing,bb08892fcf8814850e29eb933fdfcfbb,https://ieeexplore.ieee.org/document/6746252/
11433,"Today's wireless networks are increasingly crowded with an explosion of wireless users, who have greater and more diverse quality of service (QoS) demands than ever before. However, the amount of spectrum that can be used to satisfy these demands remains finite. This leads to a great challenge for wireless users to effectively share the spectrum to achieve their QoS requirements. This paper presents a game theoretic model for spectrum sharing, where users seek to satisfy their QoS demands in a distributed fashion. Our spectrum sharing model is quite general, because we allow different wireless channels to provide different QoS, depending upon their channel conditions and how many users are trying to access them. Also, users can be highly heterogeneous, with different QoS demands, depending upon their activities, hardware capabilities, and technology choices. Under such a general setting, we show that it is NP hard to find a spectrum allocation which satisfies the maximum number of users' QoS requirements in a centralized fashion. We also show that allowing users to self-organize through distributed channel selections is a viable alternative to the centralized optimization, because better response updating is guaranteed to reach a pure Nash equilibria in polynomial time. By bounding the price of anarchy, we demonstrate that the worst case pure Nash equilibrium can be close to optimal, when users and channels are not very heterogenous. We also extend our model by considering the frequency spatial reuse, and consider the user interactions as a game upon a graph where players only contend with their neighbors. We prove that better response updating is still guaranteed to reach a pure Nash equilibrium in this more general spatial QoS satisfaction game.",xu chen,Distributed spectrum sharing,2014.0,10.1109/JSAC.2014.1403008,IEEE Journal on Selected Areas in Communications,Southwell2014,False,,IEEE,Not available,Quality of Service Games for Spectrum Sharing,bb08892fcf8814850e29eb933fdfcfbb,https://ieeexplore.ieee.org/document/6746252/
11434,"Today's wireless networks are increasingly crowded with an explosion of wireless users, who have greater and more diverse quality of service (QoS) demands than ever before. However, the amount of spectrum that can be used to satisfy these demands remains finite. This leads to a great challenge for wireless users to effectively share the spectrum to achieve their QoS requirements. This paper presents a game theoretic model for spectrum sharing, where users seek to satisfy their QoS demands in a distributed fashion. Our spectrum sharing model is quite general, because we allow different wireless channels to provide different QoS, depending upon their channel conditions and how many users are trying to access them. Also, users can be highly heterogeneous, with different QoS demands, depending upon their activities, hardware capabilities, and technology choices. Under such a general setting, we show that it is NP hard to find a spectrum allocation which satisfies the maximum number of users' QoS requirements in a centralized fashion. We also show that allowing users to self-organize through distributed channel selections is a viable alternative to the centralized optimization, because better response updating is guaranteed to reach a pure Nash equilibria in polynomial time. By bounding the price of anarchy, we demonstrate that the worst case pure Nash equilibrium can be close to optimal, when users and channels are not very heterogenous. We also extend our model by considering the frequency spatial reuse, and consider the user interactions as a game upon a graph where players only contend with their neighbors. We prove that better response updating is still guaranteed to reach a pure Nash equilibrium in this more general spatial QoS satisfaction game.",xu chen,game theory,2014.0,10.1109/JSAC.2014.1403008,IEEE Journal on Selected Areas in Communications,Southwell2014,False,,IEEE,Not available,Quality of Service Games for Spectrum Sharing,bb08892fcf8814850e29eb933fdfcfbb,https://ieeexplore.ieee.org/document/6746252/
11435,"Today's wireless networks are increasingly crowded with an explosion of wireless users, who have greater and more diverse quality of service (QoS) demands than ever before. However, the amount of spectrum that can be used to satisfy these demands remains finite. This leads to a great challenge for wireless users to effectively share the spectrum to achieve their QoS requirements. This paper presents a game theoretic model for spectrum sharing, where users seek to satisfy their QoS demands in a distributed fashion. Our spectrum sharing model is quite general, because we allow different wireless channels to provide different QoS, depending upon their channel conditions and how many users are trying to access them. Also, users can be highly heterogeneous, with different QoS demands, depending upon their activities, hardware capabilities, and technology choices. Under such a general setting, we show that it is NP hard to find a spectrum allocation which satisfies the maximum number of users' QoS requirements in a centralized fashion. We also show that allowing users to self-organize through distributed channel selections is a viable alternative to the centralized optimization, because better response updating is guaranteed to reach a pure Nash equilibria in polynomial time. By bounding the price of anarchy, we demonstrate that the worst case pure Nash equilibrium can be close to optimal, when users and channels are not very heterogenous. We also extend our model by considering the frequency spatial reuse, and consider the user interactions as a game upon a graph where players only contend with their neighbors. We prove that better response updating is still guaranteed to reach a pure Nash equilibrium in this more general spatial QoS satisfaction game.",xu chen,Nash equilibrium,2014.0,10.1109/JSAC.2014.1403008,IEEE Journal on Selected Areas in Communications,Southwell2014,False,,IEEE,Not available,Quality of Service Games for Spectrum Sharing,bb08892fcf8814850e29eb933fdfcfbb,https://ieeexplore.ieee.org/document/6746252/
11436,"Today's wireless networks are increasingly crowded with an explosion of wireless users, who have greater and more diverse quality of service (QoS) demands than ever before. However, the amount of spectrum that can be used to satisfy these demands remains finite. This leads to a great challenge for wireless users to effectively share the spectrum to achieve their QoS requirements. This paper presents a game theoretic model for spectrum sharing, where users seek to satisfy their QoS demands in a distributed fashion. Our spectrum sharing model is quite general, because we allow different wireless channels to provide different QoS, depending upon their channel conditions and how many users are trying to access them. Also, users can be highly heterogeneous, with different QoS demands, depending upon their activities, hardware capabilities, and technology choices. Under such a general setting, we show that it is NP hard to find a spectrum allocation which satisfies the maximum number of users' QoS requirements in a centralized fashion. We also show that allowing users to self-organize through distributed channel selections is a viable alternative to the centralized optimization, because better response updating is guaranteed to reach a pure Nash equilibria in polynomial time. By bounding the price of anarchy, we demonstrate that the worst case pure Nash equilibrium can be close to optimal, when users and channels are not very heterogenous. We also extend our model by considering the frequency spatial reuse, and consider the user interactions as a game upon a graph where players only contend with their neighbors. We prove that better response updating is still guaranteed to reach a pure Nash equilibrium in this more general spatial QoS satisfaction game.",xu chen,quality of service (QoS),2014.0,10.1109/JSAC.2014.1403008,IEEE Journal on Selected Areas in Communications,Southwell2014,False,,IEEE,Not available,Quality of Service Games for Spectrum Sharing,bb08892fcf8814850e29eb933fdfcfbb,https://ieeexplore.ieee.org/document/6746252/
11437,"Today's wireless networks are increasingly crowded with an explosion of wireless users, who have greater and more diverse quality of service (QoS) demands than ever before. However, the amount of spectrum that can be used to satisfy these demands remains finite. This leads to a great challenge for wireless users to effectively share the spectrum to achieve their QoS requirements. This paper presents a game theoretic model for spectrum sharing, where users seek to satisfy their QoS demands in a distributed fashion. Our spectrum sharing model is quite general, because we allow different wireless channels to provide different QoS, depending upon their channel conditions and how many users are trying to access them. Also, users can be highly heterogeneous, with different QoS demands, depending upon their activities, hardware capabilities, and technology choices. Under such a general setting, we show that it is NP hard to find a spectrum allocation which satisfies the maximum number of users' QoS requirements in a centralized fashion. We also show that allowing users to self-organize through distributed channel selections is a viable alternative to the centralized optimization, because better response updating is guaranteed to reach a pure Nash equilibria in polynomial time. By bounding the price of anarchy, we demonstrate that the worst case pure Nash equilibrium can be close to optimal, when users and channels are not very heterogenous. We also extend our model by considering the frequency spatial reuse, and consider the user interactions as a game upon a graph where players only contend with their neighbors. We prove that better response updating is still guaranteed to reach a pure Nash equilibrium in this more general spatial QoS satisfaction game.",jianwei huang,Distributed spectrum sharing,2014.0,10.1109/JSAC.2014.1403008,IEEE Journal on Selected Areas in Communications,Southwell2014,False,,IEEE,Not available,Quality of Service Games for Spectrum Sharing,bb08892fcf8814850e29eb933fdfcfbb,https://ieeexplore.ieee.org/document/6746252/
11438,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11439,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
11440,"Today's wireless networks are increasingly crowded with an explosion of wireless users, who have greater and more diverse quality of service (QoS) demands than ever before. However, the amount of spectrum that can be used to satisfy these demands remains finite. This leads to a great challenge for wireless users to effectively share the spectrum to achieve their QoS requirements. This paper presents a game theoretic model for spectrum sharing, where users seek to satisfy their QoS demands in a distributed fashion. Our spectrum sharing model is quite general, because we allow different wireless channels to provide different QoS, depending upon their channel conditions and how many users are trying to access them. Also, users can be highly heterogeneous, with different QoS demands, depending upon their activities, hardware capabilities, and technology choices. Under such a general setting, we show that it is NP hard to find a spectrum allocation which satisfies the maximum number of users' QoS requirements in a centralized fashion. We also show that allowing users to self-organize through distributed channel selections is a viable alternative to the centralized optimization, because better response updating is guaranteed to reach a pure Nash equilibria in polynomial time. By bounding the price of anarchy, we demonstrate that the worst case pure Nash equilibrium can be close to optimal, when users and channels are not very heterogenous. We also extend our model by considering the frequency spatial reuse, and consider the user interactions as a game upon a graph where players only contend with their neighbors. We prove that better response updating is still guaranteed to reach a pure Nash equilibrium in this more general spatial QoS satisfaction game.",jianwei huang,game theory,2014.0,10.1109/JSAC.2014.1403008,IEEE Journal on Selected Areas in Communications,Southwell2014,False,,IEEE,Not available,Quality of Service Games for Spectrum Sharing,bb08892fcf8814850e29eb933fdfcfbb,https://ieeexplore.ieee.org/document/6746252/
11441,"Today's wireless networks are increasingly crowded with an explosion of wireless users, who have greater and more diverse quality of service (QoS) demands than ever before. However, the amount of spectrum that can be used to satisfy these demands remains finite. This leads to a great challenge for wireless users to effectively share the spectrum to achieve their QoS requirements. This paper presents a game theoretic model for spectrum sharing, where users seek to satisfy their QoS demands in a distributed fashion. Our spectrum sharing model is quite general, because we allow different wireless channels to provide different QoS, depending upon their channel conditions and how many users are trying to access them. Also, users can be highly heterogeneous, with different QoS demands, depending upon their activities, hardware capabilities, and technology choices. Under such a general setting, we show that it is NP hard to find a spectrum allocation which satisfies the maximum number of users' QoS requirements in a centralized fashion. We also show that allowing users to self-organize through distributed channel selections is a viable alternative to the centralized optimization, because better response updating is guaranteed to reach a pure Nash equilibria in polynomial time. By bounding the price of anarchy, we demonstrate that the worst case pure Nash equilibrium can be close to optimal, when users and channels are not very heterogenous. We also extend our model by considering the frequency spatial reuse, and consider the user interactions as a game upon a graph where players only contend with their neighbors. We prove that better response updating is still guaranteed to reach a pure Nash equilibrium in this more general spatial QoS satisfaction game.",jianwei huang,Nash equilibrium,2014.0,10.1109/JSAC.2014.1403008,IEEE Journal on Selected Areas in Communications,Southwell2014,False,,IEEE,Not available,Quality of Service Games for Spectrum Sharing,bb08892fcf8814850e29eb933fdfcfbb,https://ieeexplore.ieee.org/document/6746252/
11442,"Today's wireless networks are increasingly crowded with an explosion of wireless users, who have greater and more diverse quality of service (QoS) demands than ever before. However, the amount of spectrum that can be used to satisfy these demands remains finite. This leads to a great challenge for wireless users to effectively share the spectrum to achieve their QoS requirements. This paper presents a game theoretic model for spectrum sharing, where users seek to satisfy their QoS demands in a distributed fashion. Our spectrum sharing model is quite general, because we allow different wireless channels to provide different QoS, depending upon their channel conditions and how many users are trying to access them. Also, users can be highly heterogeneous, with different QoS demands, depending upon their activities, hardware capabilities, and technology choices. Under such a general setting, we show that it is NP hard to find a spectrum allocation which satisfies the maximum number of users' QoS requirements in a centralized fashion. We also show that allowing users to self-organize through distributed channel selections is a viable alternative to the centralized optimization, because better response updating is guaranteed to reach a pure Nash equilibria in polynomial time. By bounding the price of anarchy, we demonstrate that the worst case pure Nash equilibrium can be close to optimal, when users and channels are not very heterogenous. We also extend our model by considering the frequency spatial reuse, and consider the user interactions as a game upon a graph where players only contend with their neighbors. We prove that better response updating is still guaranteed to reach a pure Nash equilibrium in this more general spatial QoS satisfaction game.",jianwei huang,quality of service (QoS),2014.0,10.1109/JSAC.2014.1403008,IEEE Journal on Selected Areas in Communications,Southwell2014,False,,IEEE,Not available,Quality of Service Games for Spectrum Sharing,bb08892fcf8814850e29eb933fdfcfbb,https://ieeexplore.ieee.org/document/6746252/
11443,"Offloading computation to a mobile cloud is a promising approach for enabling the use of computationally intensive applications by mobile devices. In this paper we consider autonomous devices that maximize their own performance by choosing one of many wireless access points for computation offloading. We develop a game theoretic model of the problem, prove the existence of pure strategy Nash equilibria, and provide a polynomial time algorithm for computing an equilibrium. For the case when the cloud computing resources scale with the number of mobile devices we show that all improvement paths are finite. We provide a bound on the price of anarchy of the game, thus our algorithm serves as an approximation algorithm for the global computation offloading cost minimization problem. We use extensive simulations to provide insight into the performance and the convergence time of the algorithms in various scenarios. Our results show that the equilibrium cost may be close to optimal, and the convergence time is almost linear in the number of mobile devices.",slacdana josilo,Mobile handsets,2017.0,10.1109/INFOCOM.2017.8057148,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Jošilo2017,False,,IEEE,Not available,A game theoretic analysis of selfish mobile computation offloading,fc512855343ac480a8f6f96050b4093f,https://ieeexplore.ieee.org/document/8057148/
11444,"Offloading computation to a mobile cloud is a promising approach for enabling the use of computationally intensive applications by mobile devices. In this paper we consider autonomous devices that maximize their own performance by choosing one of many wireless access points for computation offloading. We develop a game theoretic model of the problem, prove the existence of pure strategy Nash equilibria, and provide a polynomial time algorithm for computing an equilibrium. For the case when the cloud computing resources scale with the number of mobile devices we show that all improvement paths are finite. We provide a bound on the price of anarchy of the game, thus our algorithm serves as an approximation algorithm for the global computation offloading cost minimization problem. We use extensive simulations to provide insight into the performance and the convergence time of the algorithms in various scenarios. Our results show that the equilibrium cost may be close to optimal, and the convergence time is almost linear in the number of mobile devices.",slacdana josilo,Games,2017.0,10.1109/INFOCOM.2017.8057148,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Jošilo2017,False,,IEEE,Not available,A game theoretic analysis of selfish mobile computation offloading,fc512855343ac480a8f6f96050b4093f,https://ieeexplore.ieee.org/document/8057148/
11445,"Offloading computation to a mobile cloud is a promising approach for enabling the use of computationally intensive applications by mobile devices. In this paper we consider autonomous devices that maximize their own performance by choosing one of many wireless access points for computation offloading. We develop a game theoretic model of the problem, prove the existence of pure strategy Nash equilibria, and provide a polynomial time algorithm for computing an equilibrium. For the case when the cloud computing resources scale with the number of mobile devices we show that all improvement paths are finite. We provide a bound on the price of anarchy of the game, thus our algorithm serves as an approximation algorithm for the global computation offloading cost minimization problem. We use extensive simulations to provide insight into the performance and the convergence time of the algorithms in various scenarios. Our results show that the equilibrium cost may be close to optimal, and the convergence time is almost linear in the number of mobile devices.",slacdana josilo,Cloud computing,2017.0,10.1109/INFOCOM.2017.8057148,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Jošilo2017,False,,IEEE,Not available,A game theoretic analysis of selfish mobile computation offloading,fc512855343ac480a8f6f96050b4093f,https://ieeexplore.ieee.org/document/8057148/
11446,"Offloading computation to a mobile cloud is a promising approach for enabling the use of computationally intensive applications by mobile devices. In this paper we consider autonomous devices that maximize their own performance by choosing one of many wireless access points for computation offloading. We develop a game theoretic model of the problem, prove the existence of pure strategy Nash equilibria, and provide a polynomial time algorithm for computing an equilibrium. For the case when the cloud computing resources scale with the number of mobile devices we show that all improvement paths are finite. We provide a bound on the price of anarchy of the game, thus our algorithm serves as an approximation algorithm for the global computation offloading cost minimization problem. We use extensive simulations to provide insight into the performance and the convergence time of the algorithms in various scenarios. Our results show that the equilibrium cost may be close to optimal, and the convergence time is almost linear in the number of mobile devices.",slacdana josilo,Mobile communication,2017.0,10.1109/INFOCOM.2017.8057148,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Jošilo2017,False,,IEEE,Not available,A game theoretic analysis of selfish mobile computation offloading,fc512855343ac480a8f6f96050b4093f,https://ieeexplore.ieee.org/document/8057148/
11447,"Offloading computation to a mobile cloud is a promising approach for enabling the use of computationally intensive applications by mobile devices. In this paper we consider autonomous devices that maximize their own performance by choosing one of many wireless access points for computation offloading. We develop a game theoretic model of the problem, prove the existence of pure strategy Nash equilibria, and provide a polynomial time algorithm for computing an equilibrium. For the case when the cloud computing resources scale with the number of mobile devices we show that all improvement paths are finite. We provide a bound on the price of anarchy of the game, thus our algorithm serves as an approximation algorithm for the global computation offloading cost minimization problem. We use extensive simulations to provide insight into the performance and the convergence time of the algorithms in various scenarios. Our results show that the equilibrium cost may be close to optimal, and the convergence time is almost linear in the number of mobile devices.",slacdana josilo,Approximation algorithms,2017.0,10.1109/INFOCOM.2017.8057148,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Jošilo2017,False,,IEEE,Not available,A game theoretic analysis of selfish mobile computation offloading,fc512855343ac480a8f6f96050b4093f,https://ieeexplore.ieee.org/document/8057148/
11448,"Offloading computation to a mobile cloud is a promising approach for enabling the use of computationally intensive applications by mobile devices. In this paper we consider autonomous devices that maximize their own performance by choosing one of many wireless access points for computation offloading. We develop a game theoretic model of the problem, prove the existence of pure strategy Nash equilibria, and provide a polynomial time algorithm for computing an equilibrium. For the case when the cloud computing resources scale with the number of mobile devices we show that all improvement paths are finite. We provide a bound on the price of anarchy of the game, thus our algorithm serves as an approximation algorithm for the global computation offloading cost minimization problem. We use extensive simulations to provide insight into the performance and the convergence time of the algorithms in various scenarios. Our results show that the equilibrium cost may be close to optimal, and the convergence time is almost linear in the number of mobile devices.",slacdana josilo,Computational modeling,2017.0,10.1109/INFOCOM.2017.8057148,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Jošilo2017,False,,IEEE,Not available,A game theoretic analysis of selfish mobile computation offloading,fc512855343ac480a8f6f96050b4093f,https://ieeexplore.ieee.org/document/8057148/
11449,"Offloading computation to a mobile cloud is a promising approach for enabling the use of computationally intensive applications by mobile devices. In this paper we consider autonomous devices that maximize their own performance by choosing one of many wireless access points for computation offloading. We develop a game theoretic model of the problem, prove the existence of pure strategy Nash equilibria, and provide a polynomial time algorithm for computing an equilibrium. For the case when the cloud computing resources scale with the number of mobile devices we show that all improvement paths are finite. We provide a bound on the price of anarchy of the game, thus our algorithm serves as an approximation algorithm for the global computation offloading cost minimization problem. We use extensive simulations to provide insight into the performance and the convergence time of the algorithms in various scenarios. Our results show that the equilibrium cost may be close to optimal, and the convergence time is almost linear in the number of mobile devices.",slacdana josilo,Performance evaluation,2017.0,10.1109/INFOCOM.2017.8057148,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Jošilo2017,False,,IEEE,Not available,A game theoretic analysis of selfish mobile computation offloading,fc512855343ac480a8f6f96050b4093f,https://ieeexplore.ieee.org/document/8057148/
11450,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
11451,"Offloading computation to a mobile cloud is a promising approach for enabling the use of computationally intensive applications by mobile devices. In this paper we consider autonomous devices that maximize their own performance by choosing one of many wireless access points for computation offloading. We develop a game theoretic model of the problem, prove the existence of pure strategy Nash equilibria, and provide a polynomial time algorithm for computing an equilibrium. For the case when the cloud computing resources scale with the number of mobile devices we show that all improvement paths are finite. We provide a bound on the price of anarchy of the game, thus our algorithm serves as an approximation algorithm for the global computation offloading cost minimization problem. We use extensive simulations to provide insight into the performance and the convergence time of the algorithms in various scenarios. Our results show that the equilibrium cost may be close to optimal, and the convergence time is almost linear in the number of mobile devices.",gyorgy dan,Mobile handsets,2017.0,10.1109/INFOCOM.2017.8057148,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Jošilo2017,False,,IEEE,Not available,A game theoretic analysis of selfish mobile computation offloading,fc512855343ac480a8f6f96050b4093f,https://ieeexplore.ieee.org/document/8057148/
11452,"Offloading computation to a mobile cloud is a promising approach for enabling the use of computationally intensive applications by mobile devices. In this paper we consider autonomous devices that maximize their own performance by choosing one of many wireless access points for computation offloading. We develop a game theoretic model of the problem, prove the existence of pure strategy Nash equilibria, and provide a polynomial time algorithm for computing an equilibrium. For the case when the cloud computing resources scale with the number of mobile devices we show that all improvement paths are finite. We provide a bound on the price of anarchy of the game, thus our algorithm serves as an approximation algorithm for the global computation offloading cost minimization problem. We use extensive simulations to provide insight into the performance and the convergence time of the algorithms in various scenarios. Our results show that the equilibrium cost may be close to optimal, and the convergence time is almost linear in the number of mobile devices.",gyorgy dan,Games,2017.0,10.1109/INFOCOM.2017.8057148,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Jošilo2017,False,,IEEE,Not available,A game theoretic analysis of selfish mobile computation offloading,fc512855343ac480a8f6f96050b4093f,https://ieeexplore.ieee.org/document/8057148/
11453,"Offloading computation to a mobile cloud is a promising approach for enabling the use of computationally intensive applications by mobile devices. In this paper we consider autonomous devices that maximize their own performance by choosing one of many wireless access points for computation offloading. We develop a game theoretic model of the problem, prove the existence of pure strategy Nash equilibria, and provide a polynomial time algorithm for computing an equilibrium. For the case when the cloud computing resources scale with the number of mobile devices we show that all improvement paths are finite. We provide a bound on the price of anarchy of the game, thus our algorithm serves as an approximation algorithm for the global computation offloading cost minimization problem. We use extensive simulations to provide insight into the performance and the convergence time of the algorithms in various scenarios. Our results show that the equilibrium cost may be close to optimal, and the convergence time is almost linear in the number of mobile devices.",gyorgy dan,Cloud computing,2017.0,10.1109/INFOCOM.2017.8057148,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Jošilo2017,False,,IEEE,Not available,A game theoretic analysis of selfish mobile computation offloading,fc512855343ac480a8f6f96050b4093f,https://ieeexplore.ieee.org/document/8057148/
11454,"Offloading computation to a mobile cloud is a promising approach for enabling the use of computationally intensive applications by mobile devices. In this paper we consider autonomous devices that maximize their own performance by choosing one of many wireless access points for computation offloading. We develop a game theoretic model of the problem, prove the existence of pure strategy Nash equilibria, and provide a polynomial time algorithm for computing an equilibrium. For the case when the cloud computing resources scale with the number of mobile devices we show that all improvement paths are finite. We provide a bound on the price of anarchy of the game, thus our algorithm serves as an approximation algorithm for the global computation offloading cost minimization problem. We use extensive simulations to provide insight into the performance and the convergence time of the algorithms in various scenarios. Our results show that the equilibrium cost may be close to optimal, and the convergence time is almost linear in the number of mobile devices.",gyorgy dan,Mobile communication,2017.0,10.1109/INFOCOM.2017.8057148,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Jošilo2017,False,,IEEE,Not available,A game theoretic analysis of selfish mobile computation offloading,fc512855343ac480a8f6f96050b4093f,https://ieeexplore.ieee.org/document/8057148/
11455,"Offloading computation to a mobile cloud is a promising approach for enabling the use of computationally intensive applications by mobile devices. In this paper we consider autonomous devices that maximize their own performance by choosing one of many wireless access points for computation offloading. We develop a game theoretic model of the problem, prove the existence of pure strategy Nash equilibria, and provide a polynomial time algorithm for computing an equilibrium. For the case when the cloud computing resources scale with the number of mobile devices we show that all improvement paths are finite. We provide a bound on the price of anarchy of the game, thus our algorithm serves as an approximation algorithm for the global computation offloading cost minimization problem. We use extensive simulations to provide insight into the performance and the convergence time of the algorithms in various scenarios. Our results show that the equilibrium cost may be close to optimal, and the convergence time is almost linear in the number of mobile devices.",gyorgy dan,Approximation algorithms,2017.0,10.1109/INFOCOM.2017.8057148,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Jošilo2017,False,,IEEE,Not available,A game theoretic analysis of selfish mobile computation offloading,fc512855343ac480a8f6f96050b4093f,https://ieeexplore.ieee.org/document/8057148/
11456,"Offloading computation to a mobile cloud is a promising approach for enabling the use of computationally intensive applications by mobile devices. In this paper we consider autonomous devices that maximize their own performance by choosing one of many wireless access points for computation offloading. We develop a game theoretic model of the problem, prove the existence of pure strategy Nash equilibria, and provide a polynomial time algorithm for computing an equilibrium. For the case when the cloud computing resources scale with the number of mobile devices we show that all improvement paths are finite. We provide a bound on the price of anarchy of the game, thus our algorithm serves as an approximation algorithm for the global computation offloading cost minimization problem. We use extensive simulations to provide insight into the performance and the convergence time of the algorithms in various scenarios. Our results show that the equilibrium cost may be close to optimal, and the convergence time is almost linear in the number of mobile devices.",gyorgy dan,Computational modeling,2017.0,10.1109/INFOCOM.2017.8057148,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Jošilo2017,False,,IEEE,Not available,A game theoretic analysis of selfish mobile computation offloading,fc512855343ac480a8f6f96050b4093f,https://ieeexplore.ieee.org/document/8057148/
11457,"Offloading computation to a mobile cloud is a promising approach for enabling the use of computationally intensive applications by mobile devices. In this paper we consider autonomous devices that maximize their own performance by choosing one of many wireless access points for computation offloading. We develop a game theoretic model of the problem, prove the existence of pure strategy Nash equilibria, and provide a polynomial time algorithm for computing an equilibrium. For the case when the cloud computing resources scale with the number of mobile devices we show that all improvement paths are finite. We provide a bound on the price of anarchy of the game, thus our algorithm serves as an approximation algorithm for the global computation offloading cost minimization problem. We use extensive simulations to provide insight into the performance and the convergence time of the algorithms in various scenarios. Our results show that the equilibrium cost may be close to optimal, and the convergence time is almost linear in the number of mobile devices.",gyorgy dan,Performance evaluation,2017.0,10.1109/INFOCOM.2017.8057148,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Jošilo2017,False,,IEEE,Not available,A game theoretic analysis of selfish mobile computation offloading,fc512855343ac480a8f6f96050b4093f,https://ieeexplore.ieee.org/document/8057148/
11458,"Extensive research has been performed to study selfish data caching in ad hoc networks using game-theoretic analysis. However, due to the caching problem's theoretical root in classic facility location problem and k-median problem, most of the research assumes i), the data items are initially outside of the network, and ii), the caching cost is either a constant or not considered. In this paper, we study a general data caching model in which the data item is initially in the network, and both caching and access cost are distance-dependent in multi-hop ad hoc networks. We first show the studied problem is NP-hard. We construct a pure Nash Equilibrium, in which a node will not deviate its caching strategy if others remain theirs. However, a NE may not guarantee social optimal cost - due to the selfishness of each node, the price of anarchy, which is the relative cost of the lack of cooperation among nodes, could be as large as O(N), where N is number of nodes in the network. Using an external incentive mechanism based upon a payment model, we construct a Nash Equilibrium wherein social optimal is also achieved.",yutian chen,Ad hoc networks,2010.0,10.1109/SUTC.2010.60,"2010 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing",Chen2010,False,,IEEE,Not available,Data Caching in Ad Hoc Networks Using Game-Theoretic Analysis,23d5f5f76942bdf57d40c1491ed97603,https://ieeexplore.ieee.org/document/5504634/
11459,"Extensive research has been performed to study selfish data caching in ad hoc networks using game-theoretic analysis. However, due to the caching problem's theoretical root in classic facility location problem and k-median problem, most of the research assumes i), the data items are initially outside of the network, and ii), the caching cost is either a constant or not considered. In this paper, we study a general data caching model in which the data item is initially in the network, and both caching and access cost are distance-dependent in multi-hop ad hoc networks. We first show the studied problem is NP-hard. We construct a pure Nash Equilibrium, in which a node will not deviate its caching strategy if others remain theirs. However, a NE may not guarantee social optimal cost - due to the selfishness of each node, the price of anarchy, which is the relative cost of the lack of cooperation among nodes, could be as large as O(N), where N is number of nodes in the network. Using an external incentive mechanism based upon a payment model, we construct a Nash Equilibrium wherein social optimal is also achieved.",yutian chen,data caching,2010.0,10.1109/SUTC.2010.60,"2010 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing",Chen2010,False,,IEEE,Not available,Data Caching in Ad Hoc Networks Using Game-Theoretic Analysis,23d5f5f76942bdf57d40c1491ed97603,https://ieeexplore.ieee.org/document/5504634/
11460,"Extensive research has been performed to study selfish data caching in ad hoc networks using game-theoretic analysis. However, due to the caching problem's theoretical root in classic facility location problem and k-median problem, most of the research assumes i), the data items are initially outside of the network, and ii), the caching cost is either a constant or not considered. In this paper, we study a general data caching model in which the data item is initially in the network, and both caching and access cost are distance-dependent in multi-hop ad hoc networks. We first show the studied problem is NP-hard. We construct a pure Nash Equilibrium, in which a node will not deviate its caching strategy if others remain theirs. However, a NE may not guarantee social optimal cost - due to the selfishness of each node, the price of anarchy, which is the relative cost of the lack of cooperation among nodes, could be as large as O(N), where N is number of nodes in the network. Using an external incentive mechanism based upon a payment model, we construct a Nash Equilibrium wherein social optimal is also achieved.",yutian chen,game theory,2010.0,10.1109/SUTC.2010.60,"2010 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing",Chen2010,False,,IEEE,Not available,Data Caching in Ad Hoc Networks Using Game-Theoretic Analysis,23d5f5f76942bdf57d40c1491ed97603,https://ieeexplore.ieee.org/document/5504634/
11461,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
11462,"Extensive research has been performed to study selfish data caching in ad hoc networks using game-theoretic analysis. However, due to the caching problem's theoretical root in classic facility location problem and k-median problem, most of the research assumes i), the data items are initially outside of the network, and ii), the caching cost is either a constant or not considered. In this paper, we study a general data caching model in which the data item is initially in the network, and both caching and access cost are distance-dependent in multi-hop ad hoc networks. We first show the studied problem is NP-hard. We construct a pure Nash Equilibrium, in which a node will not deviate its caching strategy if others remain theirs. However, a NE may not guarantee social optimal cost - due to the selfishness of each node, the price of anarchy, which is the relative cost of the lack of cooperation among nodes, could be as large as O(N), where N is number of nodes in the network. Using an external incentive mechanism based upon a payment model, we construct a Nash Equilibrium wherein social optimal is also achieved.",bin tang,Ad hoc networks,2010.0,10.1109/SUTC.2010.60,"2010 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing",Chen2010,False,,IEEE,Not available,Data Caching in Ad Hoc Networks Using Game-Theoretic Analysis,23d5f5f76942bdf57d40c1491ed97603,https://ieeexplore.ieee.org/document/5504634/
11463,"Extensive research has been performed to study selfish data caching in ad hoc networks using game-theoretic analysis. However, due to the caching problem's theoretical root in classic facility location problem and k-median problem, most of the research assumes i), the data items are initially outside of the network, and ii), the caching cost is either a constant or not considered. In this paper, we study a general data caching model in which the data item is initially in the network, and both caching and access cost are distance-dependent in multi-hop ad hoc networks. We first show the studied problem is NP-hard. We construct a pure Nash Equilibrium, in which a node will not deviate its caching strategy if others remain theirs. However, a NE may not guarantee social optimal cost - due to the selfishness of each node, the price of anarchy, which is the relative cost of the lack of cooperation among nodes, could be as large as O(N), where N is number of nodes in the network. Using an external incentive mechanism based upon a payment model, we construct a Nash Equilibrium wherein social optimal is also achieved.",bin tang,data caching,2010.0,10.1109/SUTC.2010.60,"2010 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing",Chen2010,False,,IEEE,Not available,Data Caching in Ad Hoc Networks Using Game-Theoretic Analysis,23d5f5f76942bdf57d40c1491ed97603,https://ieeexplore.ieee.org/document/5504634/
11464,"Extensive research has been performed to study selfish data caching in ad hoc networks using game-theoretic analysis. However, due to the caching problem's theoretical root in classic facility location problem and k-median problem, most of the research assumes i), the data items are initially outside of the network, and ii), the caching cost is either a constant or not considered. In this paper, we study a general data caching model in which the data item is initially in the network, and both caching and access cost are distance-dependent in multi-hop ad hoc networks. We first show the studied problem is NP-hard. We construct a pure Nash Equilibrium, in which a node will not deviate its caching strategy if others remain theirs. However, a NE may not guarantee social optimal cost - due to the selfishness of each node, the price of anarchy, which is the relative cost of the lack of cooperation among nodes, could be as large as O(N), where N is number of nodes in the network. Using an external incentive mechanism based upon a payment model, we construct a Nash Equilibrium wherein social optimal is also achieved.",bin tang,game theory,2010.0,10.1109/SUTC.2010.60,"2010 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing",Chen2010,False,,IEEE,Not available,Data Caching in Ad Hoc Networks Using Game-Theoretic Analysis,23d5f5f76942bdf57d40c1491ed97603,https://ieeexplore.ieee.org/document/5504634/
11465,"We study the problem of distributing loads in mobile crowdsensing systems (MCS). In this context, we present a multi-commodity network game, more explicitly, an atomic routing game, to depict the linking of several crowd participants into bundles that are capable of successfully completing desired sensing tasks. The nodes of the network correspond to the resources of the crowd participants and the players of our game are sensing service requesters that wish to route their demand along paths trough the network. One resource may serve several requests at the same time, which can be modeled efficiently using the network structure. Resource usage involves load-dependent costs. Our model caters for the uncertainty inherent from crowd involvement and mobility by incorporating certainty parameters in the model. These certainty parameters describe the quality of the partial result a participant can produce. Requesters may set a minimum certainty level for the successful completion of their overall sensing tasks that has to be met. In our model, we analyze four different solution concepts for balancing loads with respect to costs and quality of results: (1) a distributed brute force approach (engaging all suitable crowd participants), (2) a random selection of suitable crowd participants, (3) a Nash equilibrium (as result of decentralized selfish cost-minimizing game play) and (4) a (centralized) social optimum. All considered distributed solutions or an epsilon-approximation of a solution can be computed efficiently (for affine cost functions). Furthermore, well-known results for the price of anarchy of atomic routing games can be transfered to our model, i.e., the relative solution quality of a Nash equilibrium compared to a social optimum is provably bounded. In addition, we provide an extensive experimental study that supports theoretical results and gives further suggestions on the impact of uncertainty. We merge the findings of our analysis into a truthful distributed mechanism such that requesters have no incentive to deviate from an efficient solution.",julia buwaya,Mobile Crowdsensing,2017.0,10.1109/DCOSS.2017.39,2017 13th International Conference on Distributed Computing in Sensor Systems (DCOSS),Buwaya2017,False,,IEEE,Not available,Atomic Routing Mechanisms for Balance of Costs and Quality in Mobile Crowdsensing Systems,fd24642d91d41f02c5182b898739f0ef,https://ieeexplore.ieee.org/document/8271958/
11466,"We study the problem of distributing loads in mobile crowdsensing systems (MCS). In this context, we present a multi-commodity network game, more explicitly, an atomic routing game, to depict the linking of several crowd participants into bundles that are capable of successfully completing desired sensing tasks. The nodes of the network correspond to the resources of the crowd participants and the players of our game are sensing service requesters that wish to route their demand along paths trough the network. One resource may serve several requests at the same time, which can be modeled efficiently using the network structure. Resource usage involves load-dependent costs. Our model caters for the uncertainty inherent from crowd involvement and mobility by incorporating certainty parameters in the model. These certainty parameters describe the quality of the partial result a participant can produce. Requesters may set a minimum certainty level for the successful completion of their overall sensing tasks that has to be met. In our model, we analyze four different solution concepts for balancing loads with respect to costs and quality of results: (1) a distributed brute force approach (engaging all suitable crowd participants), (2) a random selection of suitable crowd participants, (3) a Nash equilibrium (as result of decentralized selfish cost-minimizing game play) and (4) a (centralized) social optimum. All considered distributed solutions or an epsilon-approximation of a solution can be computed efficiently (for affine cost functions). Furthermore, well-known results for the price of anarchy of atomic routing games can be transfered to our model, i.e., the relative solution quality of a Nash equilibrium compared to a social optimum is provably bounded. In addition, we provide an extensive experimental study that supports theoretical results and gives further suggestions on the impact of uncertainty. We merge the findings of our analysis into a truthful distributed mechanism such that requesters have no incentive to deviate from an efficient solution.",julia buwaya,Load Balance,2017.0,10.1109/DCOSS.2017.39,2017 13th International Conference on Distributed Computing in Sensor Systems (DCOSS),Buwaya2017,False,,IEEE,Not available,Atomic Routing Mechanisms for Balance of Costs and Quality in Mobile Crowdsensing Systems,fd24642d91d41f02c5182b898739f0ef,https://ieeexplore.ieee.org/document/8271958/
11467,"We study the problem of distributing loads in mobile crowdsensing systems (MCS). In this context, we present a multi-commodity network game, more explicitly, an atomic routing game, to depict the linking of several crowd participants into bundles that are capable of successfully completing desired sensing tasks. The nodes of the network correspond to the resources of the crowd participants and the players of our game are sensing service requesters that wish to route their demand along paths trough the network. One resource may serve several requests at the same time, which can be modeled efficiently using the network structure. Resource usage involves load-dependent costs. Our model caters for the uncertainty inherent from crowd involvement and mobility by incorporating certainty parameters in the model. These certainty parameters describe the quality of the partial result a participant can produce. Requesters may set a minimum certainty level for the successful completion of their overall sensing tasks that has to be met. In our model, we analyze four different solution concepts for balancing loads with respect to costs and quality of results: (1) a distributed brute force approach (engaging all suitable crowd participants), (2) a random selection of suitable crowd participants, (3) a Nash equilibrium (as result of decentralized selfish cost-minimizing game play) and (4) a (centralized) social optimum. All considered distributed solutions or an epsilon-approximation of a solution can be computed efficiently (for affine cost functions). Furthermore, well-known results for the price of anarchy of atomic routing games can be transfered to our model, i.e., the relative solution quality of a Nash equilibrium compared to a social optimum is provably bounded. In addition, we provide an extensive experimental study that supports theoretical results and gives further suggestions on the impact of uncertainty. We merge the findings of our analysis into a truthful distributed mechanism such that requesters have no incentive to deviate from an efficient solution.",julia buwaya,Efficiency,2017.0,10.1109/DCOSS.2017.39,2017 13th International Conference on Distributed Computing in Sensor Systems (DCOSS),Buwaya2017,False,,IEEE,Not available,Atomic Routing Mechanisms for Balance of Costs and Quality in Mobile Crowdsensing Systems,fd24642d91d41f02c5182b898739f0ef,https://ieeexplore.ieee.org/document/8271958/
11468,"We study the problem of distributing loads in mobile crowdsensing systems (MCS). In this context, we present a multi-commodity network game, more explicitly, an atomic routing game, to depict the linking of several crowd participants into bundles that are capable of successfully completing desired sensing tasks. The nodes of the network correspond to the resources of the crowd participants and the players of our game are sensing service requesters that wish to route their demand along paths trough the network. One resource may serve several requests at the same time, which can be modeled efficiently using the network structure. Resource usage involves load-dependent costs. Our model caters for the uncertainty inherent from crowd involvement and mobility by incorporating certainty parameters in the model. These certainty parameters describe the quality of the partial result a participant can produce. Requesters may set a minimum certainty level for the successful completion of their overall sensing tasks that has to be met. In our model, we analyze four different solution concepts for balancing loads with respect to costs and quality of results: (1) a distributed brute force approach (engaging all suitable crowd participants), (2) a random selection of suitable crowd participants, (3) a Nash equilibrium (as result of decentralized selfish cost-minimizing game play) and (4) a (centralized) social optimum. All considered distributed solutions or an epsilon-approximation of a solution can be computed efficiently (for affine cost functions). Furthermore, well-known results for the price of anarchy of atomic routing games can be transfered to our model, i.e., the relative solution quality of a Nash equilibrium compared to a social optimum is provably bounded. In addition, we provide an extensive experimental study that supports theoretical results and gives further suggestions on the impact of uncertainty. We merge the findings of our analysis into a truthful distributed mechanism such that requesters have no incentive to deviate from an efficient solution.",julia buwaya,Atomic Routing,2017.0,10.1109/DCOSS.2017.39,2017 13th International Conference on Distributed Computing in Sensor Systems (DCOSS),Buwaya2017,False,,IEEE,Not available,Atomic Routing Mechanisms for Balance of Costs and Quality in Mobile Crowdsensing Systems,fd24642d91d41f02c5182b898739f0ef,https://ieeexplore.ieee.org/document/8271958/
11469,"We study the problem of distributing loads in mobile crowdsensing systems (MCS). In this context, we present a multi-commodity network game, more explicitly, an atomic routing game, to depict the linking of several crowd participants into bundles that are capable of successfully completing desired sensing tasks. The nodes of the network correspond to the resources of the crowd participants and the players of our game are sensing service requesters that wish to route their demand along paths trough the network. One resource may serve several requests at the same time, which can be modeled efficiently using the network structure. Resource usage involves load-dependent costs. Our model caters for the uncertainty inherent from crowd involvement and mobility by incorporating certainty parameters in the model. These certainty parameters describe the quality of the partial result a participant can produce. Requesters may set a minimum certainty level for the successful completion of their overall sensing tasks that has to be met. In our model, we analyze four different solution concepts for balancing loads with respect to costs and quality of results: (1) a distributed brute force approach (engaging all suitable crowd participants), (2) a random selection of suitable crowd participants, (3) a Nash equilibrium (as result of decentralized selfish cost-minimizing game play) and (4) a (centralized) social optimum. All considered distributed solutions or an epsilon-approximation of a solution can be computed efficiently (for affine cost functions). Furthermore, well-known results for the price of anarchy of atomic routing games can be transfered to our model, i.e., the relative solution quality of a Nash equilibrium compared to a social optimum is provably bounded. In addition, we provide an extensive experimental study that supports theoretical results and gives further suggestions on the impact of uncertainty. We merge the findings of our analysis into a truthful distributed mechanism such that requesters have no incentive to deviate from an efficient solution.",julia buwaya,Game Theory,2017.0,10.1109/DCOSS.2017.39,2017 13th International Conference on Distributed Computing in Sensor Systems (DCOSS),Buwaya2017,False,,IEEE,Not available,Atomic Routing Mechanisms for Balance of Costs and Quality in Mobile Crowdsensing Systems,fd24642d91d41f02c5182b898739f0ef,https://ieeexplore.ieee.org/document/8271958/
11470,"We study the problem of distributing loads in mobile crowdsensing systems (MCS). In this context, we present a multi-commodity network game, more explicitly, an atomic routing game, to depict the linking of several crowd participants into bundles that are capable of successfully completing desired sensing tasks. The nodes of the network correspond to the resources of the crowd participants and the players of our game are sensing service requesters that wish to route their demand along paths trough the network. One resource may serve several requests at the same time, which can be modeled efficiently using the network structure. Resource usage involves load-dependent costs. Our model caters for the uncertainty inherent from crowd involvement and mobility by incorporating certainty parameters in the model. These certainty parameters describe the quality of the partial result a participant can produce. Requesters may set a minimum certainty level for the successful completion of their overall sensing tasks that has to be met. In our model, we analyze four different solution concepts for balancing loads with respect to costs and quality of results: (1) a distributed brute force approach (engaging all suitable crowd participants), (2) a random selection of suitable crowd participants, (3) a Nash equilibrium (as result of decentralized selfish cost-minimizing game play) and (4) a (centralized) social optimum. All considered distributed solutions or an epsilon-approximation of a solution can be computed efficiently (for affine cost functions). Furthermore, well-known results for the price of anarchy of atomic routing games can be transfered to our model, i.e., the relative solution quality of a Nash equilibrium compared to a social optimum is provably bounded. In addition, we provide an extensive experimental study that supports theoretical results and gives further suggestions on the impact of uncertainty. We merge the findings of our analysis into a truthful distributed mechanism such that requesters have no incentive to deviate from an efficient solution.",jose rolim,Mobile Crowdsensing,2017.0,10.1109/DCOSS.2017.39,2017 13th International Conference on Distributed Computing in Sensor Systems (DCOSS),Buwaya2017,False,,IEEE,Not available,Atomic Routing Mechanisms for Balance of Costs and Quality in Mobile Crowdsensing Systems,fd24642d91d41f02c5182b898739f0ef,https://ieeexplore.ieee.org/document/8271958/
11471,"We study the problem of distributing loads in mobile crowdsensing systems (MCS). In this context, we present a multi-commodity network game, more explicitly, an atomic routing game, to depict the linking of several crowd participants into bundles that are capable of successfully completing desired sensing tasks. The nodes of the network correspond to the resources of the crowd participants and the players of our game are sensing service requesters that wish to route their demand along paths trough the network. One resource may serve several requests at the same time, which can be modeled efficiently using the network structure. Resource usage involves load-dependent costs. Our model caters for the uncertainty inherent from crowd involvement and mobility by incorporating certainty parameters in the model. These certainty parameters describe the quality of the partial result a participant can produce. Requesters may set a minimum certainty level for the successful completion of their overall sensing tasks that has to be met. In our model, we analyze four different solution concepts for balancing loads with respect to costs and quality of results: (1) a distributed brute force approach (engaging all suitable crowd participants), (2) a random selection of suitable crowd participants, (3) a Nash equilibrium (as result of decentralized selfish cost-minimizing game play) and (4) a (centralized) social optimum. All considered distributed solutions or an epsilon-approximation of a solution can be computed efficiently (for affine cost functions). Furthermore, well-known results for the price of anarchy of atomic routing games can be transfered to our model, i.e., the relative solution quality of a Nash equilibrium compared to a social optimum is provably bounded. In addition, we provide an extensive experimental study that supports theoretical results and gives further suggestions on the impact of uncertainty. We merge the findings of our analysis into a truthful distributed mechanism such that requesters have no incentive to deviate from an efficient solution.",jose rolim,Load Balance,2017.0,10.1109/DCOSS.2017.39,2017 13th International Conference on Distributed Computing in Sensor Systems (DCOSS),Buwaya2017,False,,IEEE,Not available,Atomic Routing Mechanisms for Balance of Costs and Quality in Mobile Crowdsensing Systems,fd24642d91d41f02c5182b898739f0ef,https://ieeexplore.ieee.org/document/8271958/
11472,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
11473,"We study the problem of distributing loads in mobile crowdsensing systems (MCS). In this context, we present a multi-commodity network game, more explicitly, an atomic routing game, to depict the linking of several crowd participants into bundles that are capable of successfully completing desired sensing tasks. The nodes of the network correspond to the resources of the crowd participants and the players of our game are sensing service requesters that wish to route their demand along paths trough the network. One resource may serve several requests at the same time, which can be modeled efficiently using the network structure. Resource usage involves load-dependent costs. Our model caters for the uncertainty inherent from crowd involvement and mobility by incorporating certainty parameters in the model. These certainty parameters describe the quality of the partial result a participant can produce. Requesters may set a minimum certainty level for the successful completion of their overall sensing tasks that has to be met. In our model, we analyze four different solution concepts for balancing loads with respect to costs and quality of results: (1) a distributed brute force approach (engaging all suitable crowd participants), (2) a random selection of suitable crowd participants, (3) a Nash equilibrium (as result of decentralized selfish cost-minimizing game play) and (4) a (centralized) social optimum. All considered distributed solutions or an epsilon-approximation of a solution can be computed efficiently (for affine cost functions). Furthermore, well-known results for the price of anarchy of atomic routing games can be transfered to our model, i.e., the relative solution quality of a Nash equilibrium compared to a social optimum is provably bounded. In addition, we provide an extensive experimental study that supports theoretical results and gives further suggestions on the impact of uncertainty. We merge the findings of our analysis into a truthful distributed mechanism such that requesters have no incentive to deviate from an efficient solution.",jose rolim,Efficiency,2017.0,10.1109/DCOSS.2017.39,2017 13th International Conference on Distributed Computing in Sensor Systems (DCOSS),Buwaya2017,False,,IEEE,Not available,Atomic Routing Mechanisms for Balance of Costs and Quality in Mobile Crowdsensing Systems,fd24642d91d41f02c5182b898739f0ef,https://ieeexplore.ieee.org/document/8271958/
11474,"We study the problem of distributing loads in mobile crowdsensing systems (MCS). In this context, we present a multi-commodity network game, more explicitly, an atomic routing game, to depict the linking of several crowd participants into bundles that are capable of successfully completing desired sensing tasks. The nodes of the network correspond to the resources of the crowd participants and the players of our game are sensing service requesters that wish to route their demand along paths trough the network. One resource may serve several requests at the same time, which can be modeled efficiently using the network structure. Resource usage involves load-dependent costs. Our model caters for the uncertainty inherent from crowd involvement and mobility by incorporating certainty parameters in the model. These certainty parameters describe the quality of the partial result a participant can produce. Requesters may set a minimum certainty level for the successful completion of their overall sensing tasks that has to be met. In our model, we analyze four different solution concepts for balancing loads with respect to costs and quality of results: (1) a distributed brute force approach (engaging all suitable crowd participants), (2) a random selection of suitable crowd participants, (3) a Nash equilibrium (as result of decentralized selfish cost-minimizing game play) and (4) a (centralized) social optimum. All considered distributed solutions or an epsilon-approximation of a solution can be computed efficiently (for affine cost functions). Furthermore, well-known results for the price of anarchy of atomic routing games can be transfered to our model, i.e., the relative solution quality of a Nash equilibrium compared to a social optimum is provably bounded. In addition, we provide an extensive experimental study that supports theoretical results and gives further suggestions on the impact of uncertainty. We merge the findings of our analysis into a truthful distributed mechanism such that requesters have no incentive to deviate from an efficient solution.",jose rolim,Atomic Routing,2017.0,10.1109/DCOSS.2017.39,2017 13th International Conference on Distributed Computing in Sensor Systems (DCOSS),Buwaya2017,False,,IEEE,Not available,Atomic Routing Mechanisms for Balance of Costs and Quality in Mobile Crowdsensing Systems,fd24642d91d41f02c5182b898739f0ef,https://ieeexplore.ieee.org/document/8271958/
11475,"We study the problem of distributing loads in mobile crowdsensing systems (MCS). In this context, we present a multi-commodity network game, more explicitly, an atomic routing game, to depict the linking of several crowd participants into bundles that are capable of successfully completing desired sensing tasks. The nodes of the network correspond to the resources of the crowd participants and the players of our game are sensing service requesters that wish to route their demand along paths trough the network. One resource may serve several requests at the same time, which can be modeled efficiently using the network structure. Resource usage involves load-dependent costs. Our model caters for the uncertainty inherent from crowd involvement and mobility by incorporating certainty parameters in the model. These certainty parameters describe the quality of the partial result a participant can produce. Requesters may set a minimum certainty level for the successful completion of their overall sensing tasks that has to be met. In our model, we analyze four different solution concepts for balancing loads with respect to costs and quality of results: (1) a distributed brute force approach (engaging all suitable crowd participants), (2) a random selection of suitable crowd participants, (3) a Nash equilibrium (as result of decentralized selfish cost-minimizing game play) and (4) a (centralized) social optimum. All considered distributed solutions or an epsilon-approximation of a solution can be computed efficiently (for affine cost functions). Furthermore, well-known results for the price of anarchy of atomic routing games can be transfered to our model, i.e., the relative solution quality of a Nash equilibrium compared to a social optimum is provably bounded. In addition, we provide an extensive experimental study that supports theoretical results and gives further suggestions on the impact of uncertainty. We merge the findings of our analysis into a truthful distributed mechanism such that requesters have no incentive to deviate from an efficient solution.",jose rolim,Game Theory,2017.0,10.1109/DCOSS.2017.39,2017 13th International Conference on Distributed Computing in Sensor Systems (DCOSS),Buwaya2017,False,,IEEE,Not available,Atomic Routing Mechanisms for Balance of Costs and Quality in Mobile Crowdsensing Systems,fd24642d91d41f02c5182b898739f0ef,https://ieeexplore.ieee.org/document/8271958/
11476,"The well-known Braess paradox in congestion games states that adding an additional road to a transportation network may increase the total travel time, and consequently decrease the overall efficiency. This paper presents a paradox in a similar spirit and involves a distributed resource allocation game on networks, namely the power allocation game between countries developed in Li and Morse (2017). The paradox is that by having additional friends may actually decrease a country's total welfare in equilibrium. Conditions for this paradox to occur as well as the price of anarchy results are also derived.",yuke li,Resource management,2018.0,10.1109/JAS.2018.7511129,IEEE/CAA Journal of Automatica Sinica,Li2018,False,,IEEE,Not available,The power allocation game on a network: a paradox,71d32421035ddc14684fda692117d3bb,
11477,"The well-known Braess paradox in congestion games states that adding an additional road to a transportation network may increase the total travel time, and consequently decrease the overall efficiency. This paper presents a paradox in a similar spirit and involves a distributed resource allocation game on networks, namely the power allocation game between countries developed in Li and Morse (2017). The paradox is that by having additional friends may actually decrease a country's total welfare in equilibrium. Conditions for this paradox to occur as well as the price of anarchy results are also derived.",yuke li,Games,2018.0,10.1109/JAS.2018.7511129,IEEE/CAA Journal of Automatica Sinica,Li2018,False,,IEEE,Not available,The power allocation game on a network: a paradox,71d32421035ddc14684fda692117d3bb,
11478,"The well-known Braess paradox in congestion games states that adding an additional road to a transportation network may increase the total travel time, and consequently decrease the overall efficiency. This paper presents a paradox in a similar spirit and involves a distributed resource allocation game on networks, namely the power allocation game between countries developed in Li and Morse (2017). The paradox is that by having additional friends may actually decrease a country's total welfare in equilibrium. Conditions for this paradox to occur as well as the price of anarchy results are also derived.",yuke li,3G mobile communication,2018.0,10.1109/JAS.2018.7511129,IEEE/CAA Journal of Automatica Sinica,Li2018,False,,IEEE,Not available,The power allocation game on a network: a paradox,71d32421035ddc14684fda692117d3bb,
11479,"The well-known Braess paradox in congestion games states that adding an additional road to a transportation network may increase the total travel time, and consequently decrease the overall efficiency. This paper presents a paradox in a similar spirit and involves a distributed resource allocation game on networks, namely the power allocation game between countries developed in Li and Morse (2017). The paradox is that by having additional friends may actually decrease a country's total welfare in equilibrium. Conditions for this paradox to occur as well as the price of anarchy results are also derived.",yuke li,Roads,2018.0,10.1109/JAS.2018.7511129,IEEE/CAA Journal of Automatica Sinica,Li2018,False,,IEEE,Not available,The power allocation game on a network: a paradox,71d32421035ddc14684fda692117d3bb,
11480,"The well-known Braess paradox in congestion games states that adding an additional road to a transportation network may increase the total travel time, and consequently decrease the overall efficiency. This paper presents a paradox in a similar spirit and involves a distributed resource allocation game on networks, namely the power allocation game between countries developed in Li and Morse (2017). The paradox is that by having additional friends may actually decrease a country's total welfare in equilibrium. Conditions for this paradox to occur as well as the price of anarchy results are also derived.",yuke li,Indexes,2018.0,10.1109/JAS.2018.7511129,IEEE/CAA Journal of Automatica Sinica,Li2018,False,,IEEE,Not available,The power allocation game on a network: a paradox,71d32421035ddc14684fda692117d3bb,
11481,"The well-known Braess paradox in congestion games states that adding an additional road to a transportation network may increase the total travel time, and consequently decrease the overall efficiency. This paper presents a paradox in a similar spirit and involves a distributed resource allocation game on networks, namely the power allocation game between countries developed in Li and Morse (2017). The paradox is that by having additional friends may actually decrease a country's total welfare in equilibrium. Conditions for this paradox to occur as well as the price of anarchy results are also derived.",yuke li,Routing,2018.0,10.1109/JAS.2018.7511129,IEEE/CAA Journal of Automatica Sinica,Li2018,False,,IEEE,Not available,The power allocation game on a network: a paradox,71d32421035ddc14684fda692117d3bb,
11482,"The well-known Braess paradox in congestion games states that adding an additional road to a transportation network may increase the total travel time, and consequently decrease the overall efficiency. This paper presents a paradox in a similar spirit and involves a distributed resource allocation game on networks, namely the power allocation game between countries developed in Li and Morse (2017). The paradox is that by having additional friends may actually decrease a country's total welfare in equilibrium. Conditions for this paradox to occur as well as the price of anarchy results are also derived.",a. morse,Resource management,2018.0,10.1109/JAS.2018.7511129,IEEE/CAA Journal of Automatica Sinica,Li2018,False,,IEEE,Not available,The power allocation game on a network: a paradox,71d32421035ddc14684fda692117d3bb,
11483,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
11484,"The well-known Braess paradox in congestion games states that adding an additional road to a transportation network may increase the total travel time, and consequently decrease the overall efficiency. This paper presents a paradox in a similar spirit and involves a distributed resource allocation game on networks, namely the power allocation game between countries developed in Li and Morse (2017). The paradox is that by having additional friends may actually decrease a country's total welfare in equilibrium. Conditions for this paradox to occur as well as the price of anarchy results are also derived.",a. morse,Games,2018.0,10.1109/JAS.2018.7511129,IEEE/CAA Journal of Automatica Sinica,Li2018,False,,IEEE,Not available,The power allocation game on a network: a paradox,71d32421035ddc14684fda692117d3bb,
11485,"The well-known Braess paradox in congestion games states that adding an additional road to a transportation network may increase the total travel time, and consequently decrease the overall efficiency. This paper presents a paradox in a similar spirit and involves a distributed resource allocation game on networks, namely the power allocation game between countries developed in Li and Morse (2017). The paradox is that by having additional friends may actually decrease a country's total welfare in equilibrium. Conditions for this paradox to occur as well as the price of anarchy results are also derived.",a. morse,3G mobile communication,2018.0,10.1109/JAS.2018.7511129,IEEE/CAA Journal of Automatica Sinica,Li2018,False,,IEEE,Not available,The power allocation game on a network: a paradox,71d32421035ddc14684fda692117d3bb,
11486,"The well-known Braess paradox in congestion games states that adding an additional road to a transportation network may increase the total travel time, and consequently decrease the overall efficiency. This paper presents a paradox in a similar spirit and involves a distributed resource allocation game on networks, namely the power allocation game between countries developed in Li and Morse (2017). The paradox is that by having additional friends may actually decrease a country's total welfare in equilibrium. Conditions for this paradox to occur as well as the price of anarchy results are also derived.",a. morse,Roads,2018.0,10.1109/JAS.2018.7511129,IEEE/CAA Journal of Automatica Sinica,Li2018,False,,IEEE,Not available,The power allocation game on a network: a paradox,71d32421035ddc14684fda692117d3bb,
11487,"The well-known Braess paradox in congestion games states that adding an additional road to a transportation network may increase the total travel time, and consequently decrease the overall efficiency. This paper presents a paradox in a similar spirit and involves a distributed resource allocation game on networks, namely the power allocation game between countries developed in Li and Morse (2017). The paradox is that by having additional friends may actually decrease a country's total welfare in equilibrium. Conditions for this paradox to occur as well as the price of anarchy results are also derived.",a. morse,Indexes,2018.0,10.1109/JAS.2018.7511129,IEEE/CAA Journal of Automatica Sinica,Li2018,False,,IEEE,Not available,The power allocation game on a network: a paradox,71d32421035ddc14684fda692117d3bb,
11488,"The well-known Braess paradox in congestion games states that adding an additional road to a transportation network may increase the total travel time, and consequently decrease the overall efficiency. This paper presents a paradox in a similar spirit and involves a distributed resource allocation game on networks, namely the power allocation game between countries developed in Li and Morse (2017). The paradox is that by having additional friends may actually decrease a country's total welfare in equilibrium. Conditions for this paradox to occur as well as the price of anarchy results are also derived.",a. morse,Routing,2018.0,10.1109/JAS.2018.7511129,IEEE/CAA Journal of Automatica Sinica,Li2018,False,,IEEE,Not available,The power allocation game on a network: a paradox,71d32421035ddc14684fda692117d3bb,
11489,"In this paper we address the problem of minimizing the energy cost of positioning a node in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a twofold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is Supermodular and that it possesses a unique Nash Equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",ana moragrega,Wireless sensor networks,2012.0,10.1109/SPAWC.2012.6292928,2012 IEEE 13th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC),Moragrega2012,False,,IEEE,Not available,Supermodular game for energy efficient TOA-based positioning,69eb457be192c1f1802981b17bc788f1,https://ieeexplore.ieee.org/document/6292928/
11490,"In this paper we address the problem of minimizing the energy cost of positioning a node in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a twofold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is Supermodular and that it possesses a unique Nash Equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",ana moragrega,distributed algorithms,2012.0,10.1109/SPAWC.2012.6292928,2012 IEEE 13th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC),Moragrega2012,False,,IEEE,Not available,Supermodular game for energy efficient TOA-based positioning,69eb457be192c1f1802981b17bc788f1,https://ieeexplore.ieee.org/document/6292928/
11491,"In this paper we address the problem of minimizing the energy cost of positioning a node in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a twofold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is Supermodular and that it possesses a unique Nash Equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",ana moragrega,game theory,2012.0,10.1109/SPAWC.2012.6292928,2012 IEEE 13th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC),Moragrega2012,False,,IEEE,Not available,Supermodular game for energy efficient TOA-based positioning,69eb457be192c1f1802981b17bc788f1,https://ieeexplore.ieee.org/document/6292928/
11492,"In this paper we address the problem of minimizing the energy cost of positioning a node in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a twofold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is Supermodular and that it possesses a unique Nash Equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",ana moragrega,supermodular games,2012.0,10.1109/SPAWC.2012.6292928,2012 IEEE 13th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC),Moragrega2012,False,,IEEE,Not available,Supermodular game for energy efficient TOA-based positioning,69eb457be192c1f1802981b17bc788f1,https://ieeexplore.ieee.org/document/6292928/
11493,"In this paper we address the problem of minimizing the energy cost of positioning a node in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a twofold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is Supermodular and that it possesses a unique Nash Equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",ana moragrega,positioning,2012.0,10.1109/SPAWC.2012.6292928,2012 IEEE 13th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC),Moragrega2012,False,,IEEE,Not available,Supermodular game for energy efficient TOA-based positioning,69eb457be192c1f1802981b17bc788f1,https://ieeexplore.ieee.org/document/6292928/
11494,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
11495,"In this paper we address the problem of minimizing the energy cost of positioning a node in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a twofold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is Supermodular and that it possesses a unique Nash Equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",pau closas,Wireless sensor networks,2012.0,10.1109/SPAWC.2012.6292928,2012 IEEE 13th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC),Moragrega2012,False,,IEEE,Not available,Supermodular game for energy efficient TOA-based positioning,69eb457be192c1f1802981b17bc788f1,https://ieeexplore.ieee.org/document/6292928/
11496,"In this paper we address the problem of minimizing the energy cost of positioning a node in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a twofold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is Supermodular and that it possesses a unique Nash Equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",pau closas,distributed algorithms,2012.0,10.1109/SPAWC.2012.6292928,2012 IEEE 13th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC),Moragrega2012,False,,IEEE,Not available,Supermodular game for energy efficient TOA-based positioning,69eb457be192c1f1802981b17bc788f1,https://ieeexplore.ieee.org/document/6292928/
11497,"In this paper we address the problem of minimizing the energy cost of positioning a node in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a twofold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is Supermodular and that it possesses a unique Nash Equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",pau closas,game theory,2012.0,10.1109/SPAWC.2012.6292928,2012 IEEE 13th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC),Moragrega2012,False,,IEEE,Not available,Supermodular game for energy efficient TOA-based positioning,69eb457be192c1f1802981b17bc788f1,https://ieeexplore.ieee.org/document/6292928/
11498,"In this paper we address the problem of minimizing the energy cost of positioning a node in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a twofold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is Supermodular and that it possesses a unique Nash Equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",pau closas,supermodular games,2012.0,10.1109/SPAWC.2012.6292928,2012 IEEE 13th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC),Moragrega2012,False,,IEEE,Not available,Supermodular game for energy efficient TOA-based positioning,69eb457be192c1f1802981b17bc788f1,https://ieeexplore.ieee.org/document/6292928/
11499,"In this paper we address the problem of minimizing the energy cost of positioning a node in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a twofold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is Supermodular and that it possesses a unique Nash Equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",pau closas,positioning,2012.0,10.1109/SPAWC.2012.6292928,2012 IEEE 13th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC),Moragrega2012,False,,IEEE,Not available,Supermodular game for energy efficient TOA-based positioning,69eb457be192c1f1802981b17bc788f1,https://ieeexplore.ieee.org/document/6292928/
11500,"In this paper we address the problem of minimizing the energy cost of positioning a node in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a twofold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is Supermodular and that it possesses a unique Nash Equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",christian ibars,Wireless sensor networks,2012.0,10.1109/SPAWC.2012.6292928,2012 IEEE 13th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC),Moragrega2012,False,,IEEE,Not available,Supermodular game for energy efficient TOA-based positioning,69eb457be192c1f1802981b17bc788f1,https://ieeexplore.ieee.org/document/6292928/
11501,"In this paper we address the problem of minimizing the energy cost of positioning a node in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a twofold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is Supermodular and that it possesses a unique Nash Equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",christian ibars,distributed algorithms,2012.0,10.1109/SPAWC.2012.6292928,2012 IEEE 13th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC),Moragrega2012,False,,IEEE,Not available,Supermodular game for energy efficient TOA-based positioning,69eb457be192c1f1802981b17bc788f1,https://ieeexplore.ieee.org/document/6292928/
11502,"In this paper we address the problem of minimizing the energy cost of positioning a node in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a twofold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is Supermodular and that it possesses a unique Nash Equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",christian ibars,game theory,2012.0,10.1109/SPAWC.2012.6292928,2012 IEEE 13th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC),Moragrega2012,False,,IEEE,Not available,Supermodular game for energy efficient TOA-based positioning,69eb457be192c1f1802981b17bc788f1,https://ieeexplore.ieee.org/document/6292928/
11503,"In this paper we address the problem of minimizing the energy cost of positioning a node in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a twofold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is Supermodular and that it possesses a unique Nash Equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",christian ibars,supermodular games,2012.0,10.1109/SPAWC.2012.6292928,2012 IEEE 13th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC),Moragrega2012,False,,IEEE,Not available,Supermodular game for energy efficient TOA-based positioning,69eb457be192c1f1802981b17bc788f1,https://ieeexplore.ieee.org/document/6292928/
11504,"In this paper we address the problem of minimizing the energy cost of positioning a node in a wireless sensor network, using time of arrival measurements. A sensor needs to receive at least three distance measurements to known anchors in order to position itself. The accuracy of its position estimation depends on the signal to noise ratio of the beacons from the anchor nodes, whose power levels are to be selected according to a twofold criterion: minimum power level and desired positioning quality for users, determined by the error covariance metric. We derive a solution based on modeling the positioning problem as a non-cooperative game. We show that the resulting game is Supermodular and that it possesses a unique Nash Equilibrium, which can be quickly reached with best response dynamics. Finally, in the numerical results we find the price of anarchy of our game.",christian ibars,positioning,2012.0,10.1109/SPAWC.2012.6292928,2012 IEEE 13th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC),Moragrega2012,False,,IEEE,Not available,Supermodular game for energy efficient TOA-based positioning,69eb457be192c1f1802981b17bc788f1,https://ieeexplore.ieee.org/document/6292928/
11505,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
11506,"Network slicing to enable resource sharing among multiple tenants-network operators and/or services-is considered a key functionality for next generation mobile networks. This paper provides an analysis of a well-known model for resource sharing, the `share-constrained proportional allocation' mechanism, to realize network slicing. This mechanism enables tenants to reap the performance benefits of sharing, while retaining the ability to customize their own users' allocation. This results in a network slicing game in which each tenant reacts to the user allocations of the other tenants so as to maximize its own utility. We show that, under appropriate conditions, the game associated with such strategic behavior converges to a Nash equilibrium. At the Nash equilibrium, a tenant always achieves the same, or better, performance than under a static partitioning of resources, hence providing the same level of protection as such static partitioning. We further analyze the efficiency and fairness of the resulting allocations, providing tight bounds for the price of anarchy and envy-freeness. Our analysis and extensive simulation results confirm that the mechanism provides a comprehensive practical solution to realize network slicing. Our theoretical results also fill a gap in the literature regarding the analysis of this resource allocation model under strategic players.",pablo caballero,Resource management,2017.0,10.1109/INFOCOM.2017.8057046,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Caballero2017,False,,IEEE,Not available,Network slicing games: Enabling customization in multi-tenant networks,7acf840347e01ab37ec4b58ccc08a95f,https://ieeexplore.ieee.org/document/8057046/
11507,"Network slicing to enable resource sharing among multiple tenants-network operators and/or services-is considered a key functionality for next generation mobile networks. This paper provides an analysis of a well-known model for resource sharing, the `share-constrained proportional allocation' mechanism, to realize network slicing. This mechanism enables tenants to reap the performance benefits of sharing, while retaining the ability to customize their own users' allocation. This results in a network slicing game in which each tenant reacts to the user allocations of the other tenants so as to maximize its own utility. We show that, under appropriate conditions, the game associated with such strategic behavior converges to a Nash equilibrium. At the Nash equilibrium, a tenant always achieves the same, or better, performance than under a static partitioning of resources, hence providing the same level of protection as such static partitioning. We further analyze the efficiency and fairness of the resulting allocations, providing tight bounds for the price of anarchy and envy-freeness. Our analysis and extensive simulation results confirm that the mechanism provides a comprehensive practical solution to realize network slicing. Our theoretical results also fill a gap in the literature regarding the analysis of this resource allocation model under strategic players.",pablo caballero,Base stations,2017.0,10.1109/INFOCOM.2017.8057046,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Caballero2017,False,,IEEE,Not available,Network slicing games: Enabling customization in multi-tenant networks,7acf840347e01ab37ec4b58ccc08a95f,https://ieeexplore.ieee.org/document/8057046/
11508,"Network slicing to enable resource sharing among multiple tenants-network operators and/or services-is considered a key functionality for next generation mobile networks. This paper provides an analysis of a well-known model for resource sharing, the `share-constrained proportional allocation' mechanism, to realize network slicing. This mechanism enables tenants to reap the performance benefits of sharing, while retaining the ability to customize their own users' allocation. This results in a network slicing game in which each tenant reacts to the user allocations of the other tenants so as to maximize its own utility. We show that, under appropriate conditions, the game associated with such strategic behavior converges to a Nash equilibrium. At the Nash equilibrium, a tenant always achieves the same, or better, performance than under a static partitioning of resources, hence providing the same level of protection as such static partitioning. We further analyze the efficiency and fairness of the resulting allocations, providing tight bounds for the price of anarchy and envy-freeness. Our analysis and extensive simulation results confirm that the mechanism provides a comprehensive practical solution to realize network slicing. Our theoretical results also fill a gap in the literature regarding the analysis of this resource allocation model under strategic players.",pablo caballero,Mobile communication,2017.0,10.1109/INFOCOM.2017.8057046,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Caballero2017,False,,IEEE,Not available,Network slicing games: Enabling customization in multi-tenant networks,7acf840347e01ab37ec4b58ccc08a95f,https://ieeexplore.ieee.org/document/8057046/
11509,"Network slicing to enable resource sharing among multiple tenants-network operators and/or services-is considered a key functionality for next generation mobile networks. This paper provides an analysis of a well-known model for resource sharing, the `share-constrained proportional allocation' mechanism, to realize network slicing. This mechanism enables tenants to reap the performance benefits of sharing, while retaining the ability to customize their own users' allocation. This results in a network slicing game in which each tenant reacts to the user allocations of the other tenants so as to maximize its own utility. We show that, under appropriate conditions, the game associated with such strategic behavior converges to a Nash equilibrium. At the Nash equilibrium, a tenant always achieves the same, or better, performance than under a static partitioning of resources, hence providing the same level of protection as such static partitioning. We further analyze the efficiency and fairness of the resulting allocations, providing tight bounds for the price of anarchy and envy-freeness. Our analysis and extensive simulation results confirm that the mechanism provides a comprehensive practical solution to realize network slicing. Our theoretical results also fill a gap in the literature regarding the analysis of this resource allocation model under strategic players.",pablo caballero,Mobile computing,2017.0,10.1109/INFOCOM.2017.8057046,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Caballero2017,False,,IEEE,Not available,Network slicing games: Enabling customization in multi-tenant networks,7acf840347e01ab37ec4b58ccc08a95f,https://ieeexplore.ieee.org/document/8057046/
11510,"Network slicing to enable resource sharing among multiple tenants-network operators and/or services-is considered a key functionality for next generation mobile networks. This paper provides an analysis of a well-known model for resource sharing, the `share-constrained proportional allocation' mechanism, to realize network slicing. This mechanism enables tenants to reap the performance benefits of sharing, while retaining the ability to customize their own users' allocation. This results in a network slicing game in which each tenant reacts to the user allocations of the other tenants so as to maximize its own utility. We show that, under appropriate conditions, the game associated with such strategic behavior converges to a Nash equilibrium. At the Nash equilibrium, a tenant always achieves the same, or better, performance than under a static partitioning of resources, hence providing the same level of protection as such static partitioning. We further analyze the efficiency and fairness of the resulting allocations, providing tight bounds for the price of anarchy and envy-freeness. Our analysis and extensive simulation results confirm that the mechanism provides a comprehensive practical solution to realize network slicing. Our theoretical results also fill a gap in the literature regarding the analysis of this resource allocation model under strategic players.",pablo caballero,Analytical models,2017.0,10.1109/INFOCOM.2017.8057046,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Caballero2017,False,,IEEE,Not available,Network slicing games: Enabling customization in multi-tenant networks,7acf840347e01ab37ec4b58ccc08a95f,https://ieeexplore.ieee.org/document/8057046/
11511,"Network slicing to enable resource sharing among multiple tenants-network operators and/or services-is considered a key functionality for next generation mobile networks. This paper provides an analysis of a well-known model for resource sharing, the `share-constrained proportional allocation' mechanism, to realize network slicing. This mechanism enables tenants to reap the performance benefits of sharing, while retaining the ability to customize their own users' allocation. This results in a network slicing game in which each tenant reacts to the user allocations of the other tenants so as to maximize its own utility. We show that, under appropriate conditions, the game associated with such strategic behavior converges to a Nash equilibrium. At the Nash equilibrium, a tenant always achieves the same, or better, performance than under a static partitioning of resources, hence providing the same level of protection as such static partitioning. We further analyze the efficiency and fairness of the resulting allocations, providing tight bounds for the price of anarchy and envy-freeness. Our analysis and extensive simulation results confirm that the mechanism provides a comprehensive practical solution to realize network slicing. Our theoretical results also fill a gap in the literature regarding the analysis of this resource allocation model under strategic players.",pablo caballero,Nash equilibrium,2017.0,10.1109/INFOCOM.2017.8057046,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Caballero2017,False,,IEEE,Not available,Network slicing games: Enabling customization in multi-tenant networks,7acf840347e01ab37ec4b58ccc08a95f,https://ieeexplore.ieee.org/document/8057046/
11512,"Network slicing to enable resource sharing among multiple tenants-network operators and/or services-is considered a key functionality for next generation mobile networks. This paper provides an analysis of a well-known model for resource sharing, the `share-constrained proportional allocation' mechanism, to realize network slicing. This mechanism enables tenants to reap the performance benefits of sharing, while retaining the ability to customize their own users' allocation. This results in a network slicing game in which each tenant reacts to the user allocations of the other tenants so as to maximize its own utility. We show that, under appropriate conditions, the game associated with such strategic behavior converges to a Nash equilibrium. At the Nash equilibrium, a tenant always achieves the same, or better, performance than under a static partitioning of resources, hence providing the same level of protection as such static partitioning. We further analyze the efficiency and fairness of the resulting allocations, providing tight bounds for the price of anarchy and envy-freeness. Our analysis and extensive simulation results confirm that the mechanism provides a comprehensive practical solution to realize network slicing. Our theoretical results also fill a gap in the literature regarding the analysis of this resource allocation model under strategic players.",pablo caballero,Conferences,2017.0,10.1109/INFOCOM.2017.8057046,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Caballero2017,False,,IEEE,Not available,Network slicing games: Enabling customization in multi-tenant networks,7acf840347e01ab37ec4b58ccc08a95f,https://ieeexplore.ieee.org/document/8057046/
11513,"Network slicing to enable resource sharing among multiple tenants-network operators and/or services-is considered a key functionality for next generation mobile networks. This paper provides an analysis of a well-known model for resource sharing, the `share-constrained proportional allocation' mechanism, to realize network slicing. This mechanism enables tenants to reap the performance benefits of sharing, while retaining the ability to customize their own users' allocation. This results in a network slicing game in which each tenant reacts to the user allocations of the other tenants so as to maximize its own utility. We show that, under appropriate conditions, the game associated with such strategic behavior converges to a Nash equilibrium. At the Nash equilibrium, a tenant always achieves the same, or better, performance than under a static partitioning of resources, hence providing the same level of protection as such static partitioning. We further analyze the efficiency and fairness of the resulting allocations, providing tight bounds for the price of anarchy and envy-freeness. Our analysis and extensive simulation results confirm that the mechanism provides a comprehensive practical solution to realize network slicing. Our theoretical results also fill a gap in the literature regarding the analysis of this resource allocation model under strategic players.",albert banchs,Resource management,2017.0,10.1109/INFOCOM.2017.8057046,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Caballero2017,False,,IEEE,Not available,Network slicing games: Enabling customization in multi-tenant networks,7acf840347e01ab37ec4b58ccc08a95f,https://ieeexplore.ieee.org/document/8057046/
11514,"Network slicing to enable resource sharing among multiple tenants-network operators and/or services-is considered a key functionality for next generation mobile networks. This paper provides an analysis of a well-known model for resource sharing, the `share-constrained proportional allocation' mechanism, to realize network slicing. This mechanism enables tenants to reap the performance benefits of sharing, while retaining the ability to customize their own users' allocation. This results in a network slicing game in which each tenant reacts to the user allocations of the other tenants so as to maximize its own utility. We show that, under appropriate conditions, the game associated with such strategic behavior converges to a Nash equilibrium. At the Nash equilibrium, a tenant always achieves the same, or better, performance than under a static partitioning of resources, hence providing the same level of protection as such static partitioning. We further analyze the efficiency and fairness of the resulting allocations, providing tight bounds for the price of anarchy and envy-freeness. Our analysis and extensive simulation results confirm that the mechanism provides a comprehensive practical solution to realize network slicing. Our theoretical results also fill a gap in the literature regarding the analysis of this resource allocation model under strategic players.",albert banchs,Base stations,2017.0,10.1109/INFOCOM.2017.8057046,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Caballero2017,False,,IEEE,Not available,Network slicing games: Enabling customization in multi-tenant networks,7acf840347e01ab37ec4b58ccc08a95f,https://ieeexplore.ieee.org/document/8057046/
11515,"Network slicing to enable resource sharing among multiple tenants-network operators and/or services-is considered a key functionality for next generation mobile networks. This paper provides an analysis of a well-known model for resource sharing, the `share-constrained proportional allocation' mechanism, to realize network slicing. This mechanism enables tenants to reap the performance benefits of sharing, while retaining the ability to customize their own users' allocation. This results in a network slicing game in which each tenant reacts to the user allocations of the other tenants so as to maximize its own utility. We show that, under appropriate conditions, the game associated with such strategic behavior converges to a Nash equilibrium. At the Nash equilibrium, a tenant always achieves the same, or better, performance than under a static partitioning of resources, hence providing the same level of protection as such static partitioning. We further analyze the efficiency and fairness of the resulting allocations, providing tight bounds for the price of anarchy and envy-freeness. Our analysis and extensive simulation results confirm that the mechanism provides a comprehensive practical solution to realize network slicing. Our theoretical results also fill a gap in the literature regarding the analysis of this resource allocation model under strategic players.",albert banchs,Mobile communication,2017.0,10.1109/INFOCOM.2017.8057046,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Caballero2017,False,,IEEE,Not available,Network slicing games: Enabling customization in multi-tenant networks,7acf840347e01ab37ec4b58ccc08a95f,https://ieeexplore.ieee.org/document/8057046/
11516,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
11517,"Network slicing to enable resource sharing among multiple tenants-network operators and/or services-is considered a key functionality for next generation mobile networks. This paper provides an analysis of a well-known model for resource sharing, the `share-constrained proportional allocation' mechanism, to realize network slicing. This mechanism enables tenants to reap the performance benefits of sharing, while retaining the ability to customize their own users' allocation. This results in a network slicing game in which each tenant reacts to the user allocations of the other tenants so as to maximize its own utility. We show that, under appropriate conditions, the game associated with such strategic behavior converges to a Nash equilibrium. At the Nash equilibrium, a tenant always achieves the same, or better, performance than under a static partitioning of resources, hence providing the same level of protection as such static partitioning. We further analyze the efficiency and fairness of the resulting allocations, providing tight bounds for the price of anarchy and envy-freeness. Our analysis and extensive simulation results confirm that the mechanism provides a comprehensive practical solution to realize network slicing. Our theoretical results also fill a gap in the literature regarding the analysis of this resource allocation model under strategic players.",albert banchs,Mobile computing,2017.0,10.1109/INFOCOM.2017.8057046,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Caballero2017,False,,IEEE,Not available,Network slicing games: Enabling customization in multi-tenant networks,7acf840347e01ab37ec4b58ccc08a95f,https://ieeexplore.ieee.org/document/8057046/
11518,"Network slicing to enable resource sharing among multiple tenants-network operators and/or services-is considered a key functionality for next generation mobile networks. This paper provides an analysis of a well-known model for resource sharing, the `share-constrained proportional allocation' mechanism, to realize network slicing. This mechanism enables tenants to reap the performance benefits of sharing, while retaining the ability to customize their own users' allocation. This results in a network slicing game in which each tenant reacts to the user allocations of the other tenants so as to maximize its own utility. We show that, under appropriate conditions, the game associated with such strategic behavior converges to a Nash equilibrium. At the Nash equilibrium, a tenant always achieves the same, or better, performance than under a static partitioning of resources, hence providing the same level of protection as such static partitioning. We further analyze the efficiency and fairness of the resulting allocations, providing tight bounds for the price of anarchy and envy-freeness. Our analysis and extensive simulation results confirm that the mechanism provides a comprehensive practical solution to realize network slicing. Our theoretical results also fill a gap in the literature regarding the analysis of this resource allocation model under strategic players.",albert banchs,Analytical models,2017.0,10.1109/INFOCOM.2017.8057046,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Caballero2017,False,,IEEE,Not available,Network slicing games: Enabling customization in multi-tenant networks,7acf840347e01ab37ec4b58ccc08a95f,https://ieeexplore.ieee.org/document/8057046/
11519,"Network slicing to enable resource sharing among multiple tenants-network operators and/or services-is considered a key functionality for next generation mobile networks. This paper provides an analysis of a well-known model for resource sharing, the `share-constrained proportional allocation' mechanism, to realize network slicing. This mechanism enables tenants to reap the performance benefits of sharing, while retaining the ability to customize their own users' allocation. This results in a network slicing game in which each tenant reacts to the user allocations of the other tenants so as to maximize its own utility. We show that, under appropriate conditions, the game associated with such strategic behavior converges to a Nash equilibrium. At the Nash equilibrium, a tenant always achieves the same, or better, performance than under a static partitioning of resources, hence providing the same level of protection as such static partitioning. We further analyze the efficiency and fairness of the resulting allocations, providing tight bounds for the price of anarchy and envy-freeness. Our analysis and extensive simulation results confirm that the mechanism provides a comprehensive practical solution to realize network slicing. Our theoretical results also fill a gap in the literature regarding the analysis of this resource allocation model under strategic players.",albert banchs,Nash equilibrium,2017.0,10.1109/INFOCOM.2017.8057046,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Caballero2017,False,,IEEE,Not available,Network slicing games: Enabling customization in multi-tenant networks,7acf840347e01ab37ec4b58ccc08a95f,https://ieeexplore.ieee.org/document/8057046/
11520,"Network slicing to enable resource sharing among multiple tenants-network operators and/or services-is considered a key functionality for next generation mobile networks. This paper provides an analysis of a well-known model for resource sharing, the `share-constrained proportional allocation' mechanism, to realize network slicing. This mechanism enables tenants to reap the performance benefits of sharing, while retaining the ability to customize their own users' allocation. This results in a network slicing game in which each tenant reacts to the user allocations of the other tenants so as to maximize its own utility. We show that, under appropriate conditions, the game associated with such strategic behavior converges to a Nash equilibrium. At the Nash equilibrium, a tenant always achieves the same, or better, performance than under a static partitioning of resources, hence providing the same level of protection as such static partitioning. We further analyze the efficiency and fairness of the resulting allocations, providing tight bounds for the price of anarchy and envy-freeness. Our analysis and extensive simulation results confirm that the mechanism provides a comprehensive practical solution to realize network slicing. Our theoretical results also fill a gap in the literature regarding the analysis of this resource allocation model under strategic players.",albert banchs,Conferences,2017.0,10.1109/INFOCOM.2017.8057046,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Caballero2017,False,,IEEE,Not available,Network slicing games: Enabling customization in multi-tenant networks,7acf840347e01ab37ec4b58ccc08a95f,https://ieeexplore.ieee.org/document/8057046/
11521,"Network slicing to enable resource sharing among multiple tenants-network operators and/or services-is considered a key functionality for next generation mobile networks. This paper provides an analysis of a well-known model for resource sharing, the `share-constrained proportional allocation' mechanism, to realize network slicing. This mechanism enables tenants to reap the performance benefits of sharing, while retaining the ability to customize their own users' allocation. This results in a network slicing game in which each tenant reacts to the user allocations of the other tenants so as to maximize its own utility. We show that, under appropriate conditions, the game associated with such strategic behavior converges to a Nash equilibrium. At the Nash equilibrium, a tenant always achieves the same, or better, performance than under a static partitioning of resources, hence providing the same level of protection as such static partitioning. We further analyze the efficiency and fairness of the resulting allocations, providing tight bounds for the price of anarchy and envy-freeness. Our analysis and extensive simulation results confirm that the mechanism provides a comprehensive practical solution to realize network slicing. Our theoretical results also fill a gap in the literature regarding the analysis of this resource allocation model under strategic players.",gustavo veciana,Resource management,2017.0,10.1109/INFOCOM.2017.8057046,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Caballero2017,False,,IEEE,Not available,Network slicing games: Enabling customization in multi-tenant networks,7acf840347e01ab37ec4b58ccc08a95f,https://ieeexplore.ieee.org/document/8057046/
11522,"Network slicing to enable resource sharing among multiple tenants-network operators and/or services-is considered a key functionality for next generation mobile networks. This paper provides an analysis of a well-known model for resource sharing, the `share-constrained proportional allocation' mechanism, to realize network slicing. This mechanism enables tenants to reap the performance benefits of sharing, while retaining the ability to customize their own users' allocation. This results in a network slicing game in which each tenant reacts to the user allocations of the other tenants so as to maximize its own utility. We show that, under appropriate conditions, the game associated with such strategic behavior converges to a Nash equilibrium. At the Nash equilibrium, a tenant always achieves the same, or better, performance than under a static partitioning of resources, hence providing the same level of protection as such static partitioning. We further analyze the efficiency and fairness of the resulting allocations, providing tight bounds for the price of anarchy and envy-freeness. Our analysis and extensive simulation results confirm that the mechanism provides a comprehensive practical solution to realize network slicing. Our theoretical results also fill a gap in the literature regarding the analysis of this resource allocation model under strategic players.",gustavo veciana,Base stations,2017.0,10.1109/INFOCOM.2017.8057046,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Caballero2017,False,,IEEE,Not available,Network slicing games: Enabling customization in multi-tenant networks,7acf840347e01ab37ec4b58ccc08a95f,https://ieeexplore.ieee.org/document/8057046/
11523,"Network slicing to enable resource sharing among multiple tenants-network operators and/or services-is considered a key functionality for next generation mobile networks. This paper provides an analysis of a well-known model for resource sharing, the `share-constrained proportional allocation' mechanism, to realize network slicing. This mechanism enables tenants to reap the performance benefits of sharing, while retaining the ability to customize their own users' allocation. This results in a network slicing game in which each tenant reacts to the user allocations of the other tenants so as to maximize its own utility. We show that, under appropriate conditions, the game associated with such strategic behavior converges to a Nash equilibrium. At the Nash equilibrium, a tenant always achieves the same, or better, performance than under a static partitioning of resources, hence providing the same level of protection as such static partitioning. We further analyze the efficiency and fairness of the resulting allocations, providing tight bounds for the price of anarchy and envy-freeness. Our analysis and extensive simulation results confirm that the mechanism provides a comprehensive practical solution to realize network slicing. Our theoretical results also fill a gap in the literature regarding the analysis of this resource allocation model under strategic players.",gustavo veciana,Mobile communication,2017.0,10.1109/INFOCOM.2017.8057046,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Caballero2017,False,,IEEE,Not available,Network slicing games: Enabling customization in multi-tenant networks,7acf840347e01ab37ec4b58ccc08a95f,https://ieeexplore.ieee.org/document/8057046/
11524,"Network slicing to enable resource sharing among multiple tenants-network operators and/or services-is considered a key functionality for next generation mobile networks. This paper provides an analysis of a well-known model for resource sharing, the `share-constrained proportional allocation' mechanism, to realize network slicing. This mechanism enables tenants to reap the performance benefits of sharing, while retaining the ability to customize their own users' allocation. This results in a network slicing game in which each tenant reacts to the user allocations of the other tenants so as to maximize its own utility. We show that, under appropriate conditions, the game associated with such strategic behavior converges to a Nash equilibrium. At the Nash equilibrium, a tenant always achieves the same, or better, performance than under a static partitioning of resources, hence providing the same level of protection as such static partitioning. We further analyze the efficiency and fairness of the resulting allocations, providing tight bounds for the price of anarchy and envy-freeness. Our analysis and extensive simulation results confirm that the mechanism provides a comprehensive practical solution to realize network slicing. Our theoretical results also fill a gap in the literature regarding the analysis of this resource allocation model under strategic players.",gustavo veciana,Mobile computing,2017.0,10.1109/INFOCOM.2017.8057046,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Caballero2017,False,,IEEE,Not available,Network slicing games: Enabling customization in multi-tenant networks,7acf840347e01ab37ec4b58ccc08a95f,https://ieeexplore.ieee.org/document/8057046/
11525,"Network slicing to enable resource sharing among multiple tenants-network operators and/or services-is considered a key functionality for next generation mobile networks. This paper provides an analysis of a well-known model for resource sharing, the `share-constrained proportional allocation' mechanism, to realize network slicing. This mechanism enables tenants to reap the performance benefits of sharing, while retaining the ability to customize their own users' allocation. This results in a network slicing game in which each tenant reacts to the user allocations of the other tenants so as to maximize its own utility. We show that, under appropriate conditions, the game associated with such strategic behavior converges to a Nash equilibrium. At the Nash equilibrium, a tenant always achieves the same, or better, performance than under a static partitioning of resources, hence providing the same level of protection as such static partitioning. We further analyze the efficiency and fairness of the resulting allocations, providing tight bounds for the price of anarchy and envy-freeness. Our analysis and extensive simulation results confirm that the mechanism provides a comprehensive practical solution to realize network slicing. Our theoretical results also fill a gap in the literature regarding the analysis of this resource allocation model under strategic players.",gustavo veciana,Analytical models,2017.0,10.1109/INFOCOM.2017.8057046,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Caballero2017,False,,IEEE,Not available,Network slicing games: Enabling customization in multi-tenant networks,7acf840347e01ab37ec4b58ccc08a95f,https://ieeexplore.ieee.org/document/8057046/
11526,"Network slicing to enable resource sharing among multiple tenants-network operators and/or services-is considered a key functionality for next generation mobile networks. This paper provides an analysis of a well-known model for resource sharing, the `share-constrained proportional allocation' mechanism, to realize network slicing. This mechanism enables tenants to reap the performance benefits of sharing, while retaining the ability to customize their own users' allocation. This results in a network slicing game in which each tenant reacts to the user allocations of the other tenants so as to maximize its own utility. We show that, under appropriate conditions, the game associated with such strategic behavior converges to a Nash equilibrium. At the Nash equilibrium, a tenant always achieves the same, or better, performance than under a static partitioning of resources, hence providing the same level of protection as such static partitioning. We further analyze the efficiency and fairness of the resulting allocations, providing tight bounds for the price of anarchy and envy-freeness. Our analysis and extensive simulation results confirm that the mechanism provides a comprehensive practical solution to realize network slicing. Our theoretical results also fill a gap in the literature regarding the analysis of this resource allocation model under strategic players.",gustavo veciana,Nash equilibrium,2017.0,10.1109/INFOCOM.2017.8057046,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Caballero2017,False,,IEEE,Not available,Network slicing games: Enabling customization in multi-tenant networks,7acf840347e01ab37ec4b58ccc08a95f,https://ieeexplore.ieee.org/document/8057046/
11527,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
11528,"Network slicing to enable resource sharing among multiple tenants-network operators and/or services-is considered a key functionality for next generation mobile networks. This paper provides an analysis of a well-known model for resource sharing, the `share-constrained proportional allocation' mechanism, to realize network slicing. This mechanism enables tenants to reap the performance benefits of sharing, while retaining the ability to customize their own users' allocation. This results in a network slicing game in which each tenant reacts to the user allocations of the other tenants so as to maximize its own utility. We show that, under appropriate conditions, the game associated with such strategic behavior converges to a Nash equilibrium. At the Nash equilibrium, a tenant always achieves the same, or better, performance than under a static partitioning of resources, hence providing the same level of protection as such static partitioning. We further analyze the efficiency and fairness of the resulting allocations, providing tight bounds for the price of anarchy and envy-freeness. Our analysis and extensive simulation results confirm that the mechanism provides a comprehensive practical solution to realize network slicing. Our theoretical results also fill a gap in the literature regarding the analysis of this resource allocation model under strategic players.",gustavo veciana,Conferences,2017.0,10.1109/INFOCOM.2017.8057046,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Caballero2017,False,,IEEE,Not available,Network slicing games: Enabling customization in multi-tenant networks,7acf840347e01ab37ec4b58ccc08a95f,https://ieeexplore.ieee.org/document/8057046/
11529,"Network slicing to enable resource sharing among multiple tenants-network operators and/or services-is considered a key functionality for next generation mobile networks. This paper provides an analysis of a well-known model for resource sharing, the `share-constrained proportional allocation' mechanism, to realize network slicing. This mechanism enables tenants to reap the performance benefits of sharing, while retaining the ability to customize their own users' allocation. This results in a network slicing game in which each tenant reacts to the user allocations of the other tenants so as to maximize its own utility. We show that, under appropriate conditions, the game associated with such strategic behavior converges to a Nash equilibrium. At the Nash equilibrium, a tenant always achieves the same, or better, performance than under a static partitioning of resources, hence providing the same level of protection as such static partitioning. We further analyze the efficiency and fairness of the resulting allocations, providing tight bounds for the price of anarchy and envy-freeness. Our analysis and extensive simulation results confirm that the mechanism provides a comprehensive practical solution to realize network slicing. Our theoretical results also fill a gap in the literature regarding the analysis of this resource allocation model under strategic players.",xavier costa-perez,Resource management,2017.0,10.1109/INFOCOM.2017.8057046,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Caballero2017,False,,IEEE,Not available,Network slicing games: Enabling customization in multi-tenant networks,7acf840347e01ab37ec4b58ccc08a95f,https://ieeexplore.ieee.org/document/8057046/
11530,"Network slicing to enable resource sharing among multiple tenants-network operators and/or services-is considered a key functionality for next generation mobile networks. This paper provides an analysis of a well-known model for resource sharing, the `share-constrained proportional allocation' mechanism, to realize network slicing. This mechanism enables tenants to reap the performance benefits of sharing, while retaining the ability to customize their own users' allocation. This results in a network slicing game in which each tenant reacts to the user allocations of the other tenants so as to maximize its own utility. We show that, under appropriate conditions, the game associated with such strategic behavior converges to a Nash equilibrium. At the Nash equilibrium, a tenant always achieves the same, or better, performance than under a static partitioning of resources, hence providing the same level of protection as such static partitioning. We further analyze the efficiency and fairness of the resulting allocations, providing tight bounds for the price of anarchy and envy-freeness. Our analysis and extensive simulation results confirm that the mechanism provides a comprehensive practical solution to realize network slicing. Our theoretical results also fill a gap in the literature regarding the analysis of this resource allocation model under strategic players.",xavier costa-perez,Base stations,2017.0,10.1109/INFOCOM.2017.8057046,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Caballero2017,False,,IEEE,Not available,Network slicing games: Enabling customization in multi-tenant networks,7acf840347e01ab37ec4b58ccc08a95f,https://ieeexplore.ieee.org/document/8057046/
11531,"Network slicing to enable resource sharing among multiple tenants-network operators and/or services-is considered a key functionality for next generation mobile networks. This paper provides an analysis of a well-known model for resource sharing, the `share-constrained proportional allocation' mechanism, to realize network slicing. This mechanism enables tenants to reap the performance benefits of sharing, while retaining the ability to customize their own users' allocation. This results in a network slicing game in which each tenant reacts to the user allocations of the other tenants so as to maximize its own utility. We show that, under appropriate conditions, the game associated with such strategic behavior converges to a Nash equilibrium. At the Nash equilibrium, a tenant always achieves the same, or better, performance than under a static partitioning of resources, hence providing the same level of protection as such static partitioning. We further analyze the efficiency and fairness of the resulting allocations, providing tight bounds for the price of anarchy and envy-freeness. Our analysis and extensive simulation results confirm that the mechanism provides a comprehensive practical solution to realize network slicing. Our theoretical results also fill a gap in the literature regarding the analysis of this resource allocation model under strategic players.",xavier costa-perez,Mobile communication,2017.0,10.1109/INFOCOM.2017.8057046,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Caballero2017,False,,IEEE,Not available,Network slicing games: Enabling customization in multi-tenant networks,7acf840347e01ab37ec4b58ccc08a95f,https://ieeexplore.ieee.org/document/8057046/
11532,"Network slicing to enable resource sharing among multiple tenants-network operators and/or services-is considered a key functionality for next generation mobile networks. This paper provides an analysis of a well-known model for resource sharing, the `share-constrained proportional allocation' mechanism, to realize network slicing. This mechanism enables tenants to reap the performance benefits of sharing, while retaining the ability to customize their own users' allocation. This results in a network slicing game in which each tenant reacts to the user allocations of the other tenants so as to maximize its own utility. We show that, under appropriate conditions, the game associated with such strategic behavior converges to a Nash equilibrium. At the Nash equilibrium, a tenant always achieves the same, or better, performance than under a static partitioning of resources, hence providing the same level of protection as such static partitioning. We further analyze the efficiency and fairness of the resulting allocations, providing tight bounds for the price of anarchy and envy-freeness. Our analysis and extensive simulation results confirm that the mechanism provides a comprehensive practical solution to realize network slicing. Our theoretical results also fill a gap in the literature regarding the analysis of this resource allocation model under strategic players.",xavier costa-perez,Mobile computing,2017.0,10.1109/INFOCOM.2017.8057046,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Caballero2017,False,,IEEE,Not available,Network slicing games: Enabling customization in multi-tenant networks,7acf840347e01ab37ec4b58ccc08a95f,https://ieeexplore.ieee.org/document/8057046/
11533,"Network slicing to enable resource sharing among multiple tenants-network operators and/or services-is considered a key functionality for next generation mobile networks. This paper provides an analysis of a well-known model for resource sharing, the `share-constrained proportional allocation' mechanism, to realize network slicing. This mechanism enables tenants to reap the performance benefits of sharing, while retaining the ability to customize their own users' allocation. This results in a network slicing game in which each tenant reacts to the user allocations of the other tenants so as to maximize its own utility. We show that, under appropriate conditions, the game associated with such strategic behavior converges to a Nash equilibrium. At the Nash equilibrium, a tenant always achieves the same, or better, performance than under a static partitioning of resources, hence providing the same level of protection as such static partitioning. We further analyze the efficiency and fairness of the resulting allocations, providing tight bounds for the price of anarchy and envy-freeness. Our analysis and extensive simulation results confirm that the mechanism provides a comprehensive practical solution to realize network slicing. Our theoretical results also fill a gap in the literature regarding the analysis of this resource allocation model under strategic players.",xavier costa-perez,Analytical models,2017.0,10.1109/INFOCOM.2017.8057046,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Caballero2017,False,,IEEE,Not available,Network slicing games: Enabling customization in multi-tenant networks,7acf840347e01ab37ec4b58ccc08a95f,https://ieeexplore.ieee.org/document/8057046/
11534,"Network slicing to enable resource sharing among multiple tenants-network operators and/or services-is considered a key functionality for next generation mobile networks. This paper provides an analysis of a well-known model for resource sharing, the `share-constrained proportional allocation' mechanism, to realize network slicing. This mechanism enables tenants to reap the performance benefits of sharing, while retaining the ability to customize their own users' allocation. This results in a network slicing game in which each tenant reacts to the user allocations of the other tenants so as to maximize its own utility. We show that, under appropriate conditions, the game associated with such strategic behavior converges to a Nash equilibrium. At the Nash equilibrium, a tenant always achieves the same, or better, performance than under a static partitioning of resources, hence providing the same level of protection as such static partitioning. We further analyze the efficiency and fairness of the resulting allocations, providing tight bounds for the price of anarchy and envy-freeness. Our analysis and extensive simulation results confirm that the mechanism provides a comprehensive practical solution to realize network slicing. Our theoretical results also fill a gap in the literature regarding the analysis of this resource allocation model under strategic players.",xavier costa-perez,Nash equilibrium,2017.0,10.1109/INFOCOM.2017.8057046,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Caballero2017,False,,IEEE,Not available,Network slicing games: Enabling customization in multi-tenant networks,7acf840347e01ab37ec4b58ccc08a95f,https://ieeexplore.ieee.org/document/8057046/
11535,"Network slicing to enable resource sharing among multiple tenants-network operators and/or services-is considered a key functionality for next generation mobile networks. This paper provides an analysis of a well-known model for resource sharing, the `share-constrained proportional allocation' mechanism, to realize network slicing. This mechanism enables tenants to reap the performance benefits of sharing, while retaining the ability to customize their own users' allocation. This results in a network slicing game in which each tenant reacts to the user allocations of the other tenants so as to maximize its own utility. We show that, under appropriate conditions, the game associated with such strategic behavior converges to a Nash equilibrium. At the Nash equilibrium, a tenant always achieves the same, or better, performance than under a static partitioning of resources, hence providing the same level of protection as such static partitioning. We further analyze the efficiency and fairness of the resulting allocations, providing tight bounds for the price of anarchy and envy-freeness. Our analysis and extensive simulation results confirm that the mechanism provides a comprehensive practical solution to realize network slicing. Our theoretical results also fill a gap in the literature regarding the analysis of this resource allocation model under strategic players.",xavier costa-perez,Conferences,2017.0,10.1109/INFOCOM.2017.8057046,IEEE INFOCOM 2017 - IEEE Conference on Computer Communications,Caballero2017,False,,IEEE,Not available,Network slicing games: Enabling customization in multi-tenant networks,7acf840347e01ab37ec4b58ccc08a95f,https://ieeexplore.ieee.org/document/8057046/
11536,"Random medium access on wireless channels has two key characteristics: heterogeneous channel quality across users (due to the variable wireless channel conditions with the access point across users) and packet collisions (due to random access) at the access point. The design of optimal channel contention probabilities is nontrivial on account of the need to balance between under-utilization (no transmission attempts) and over-utilization (channel collisions) of the wireless channel. The wireless random access erasure collision channel presented in this paper is a parsimonious abstraction of these phenomena. We consider a scenario wherein the base station provides a reward to users in proportion to the rate of successfully received packets, and users incur a cost in proportion to their contention probability. The objective is to select a reward such that the sum-user delivered rate in the equilibrium of the induced game is (approximately) optimal, i.e., such that only higher quality users are incentivized to contend the channel. We use the price of anarchy (PoA) measure and study the extent to which appropriate reward mechanisms can yield good PoA bounds.",vasilis gkatzelis,Wireless communication,2018.0,10.1109/ITA.2018.8503115,2018 Information Theory and Applications Workshop (ITA),Gkatzelis2018,False,,IEEE,Not available,Participation Incentives on a Wireless Random Access Erasure Collision Channel,005c0399baec6f48c8f4f42bcaa6053e,https://ieeexplore.ieee.org/document/8503115/
11537,"Random medium access on wireless channels has two key characteristics: heterogeneous channel quality across users (due to the variable wireless channel conditions with the access point across users) and packet collisions (due to random access) at the access point. The design of optimal channel contention probabilities is nontrivial on account of the need to balance between under-utilization (no transmission attempts) and over-utilization (channel collisions) of the wireless channel. The wireless random access erasure collision channel presented in this paper is a parsimonious abstraction of these phenomena. We consider a scenario wherein the base station provides a reward to users in proportion to the rate of successfully received packets, and users incur a cost in proportion to their contention probability. The objective is to select a reward such that the sum-user delivered rate in the equilibrium of the induced game is (approximately) optimal, i.e., such that only higher quality users are incentivized to contend the channel. We use the price of anarchy (PoA) measure and study the extent to which appropriate reward mechanisms can yield good PoA bounds.",vasilis gkatzelis,Games,2018.0,10.1109/ITA.2018.8503115,2018 Information Theory and Applications Workshop (ITA),Gkatzelis2018,False,,IEEE,Not available,Participation Incentives on a Wireless Random Access Erasure Collision Channel,005c0399baec6f48c8f4f42bcaa6053e,https://ieeexplore.ieee.org/document/8503115/
11538,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
11539,"Random medium access on wireless channels has two key characteristics: heterogeneous channel quality across users (due to the variable wireless channel conditions with the access point across users) and packet collisions (due to random access) at the access point. The design of optimal channel contention probabilities is nontrivial on account of the need to balance between under-utilization (no transmission attempts) and over-utilization (channel collisions) of the wireless channel. The wireless random access erasure collision channel presented in this paper is a parsimonious abstraction of these phenomena. We consider a scenario wherein the base station provides a reward to users in proportion to the rate of successfully received packets, and users incur a cost in proportion to their contention probability. The objective is to select a reward such that the sum-user delivered rate in the equilibrium of the induced game is (approximately) optimal, i.e., such that only higher quality users are incentivized to contend the channel. We use the price of anarchy (PoA) measure and study the extent to which appropriate reward mechanisms can yield good PoA bounds.",vasilis gkatzelis,Ad hoc networks,2018.0,10.1109/ITA.2018.8503115,2018 Information Theory and Applications Workshop (ITA),Gkatzelis2018,False,,IEEE,Not available,Participation Incentives on a Wireless Random Access Erasure Collision Channel,005c0399baec6f48c8f4f42bcaa6053e,https://ieeexplore.ieee.org/document/8503115/
11540,"Random medium access on wireless channels has two key characteristics: heterogeneous channel quality across users (due to the variable wireless channel conditions with the access point across users) and packet collisions (due to random access) at the access point. The design of optimal channel contention probabilities is nontrivial on account of the need to balance between under-utilization (no transmission attempts) and over-utilization (channel collisions) of the wireless channel. The wireless random access erasure collision channel presented in this paper is a parsimonious abstraction of these phenomena. We consider a scenario wherein the base station provides a reward to users in proportion to the rate of successfully received packets, and users incur a cost in proportion to their contention probability. The objective is to select a reward such that the sum-user delivered rate in the equilibrium of the induced game is (approximately) optimal, i.e., such that only higher quality users are incentivized to contend the channel. We use the price of anarchy (PoA) measure and study the extent to which appropriate reward mechanisms can yield good PoA bounds.",vasilis gkatzelis,Wireless sensor networks,2018.0,10.1109/ITA.2018.8503115,2018 Information Theory and Applications Workshop (ITA),Gkatzelis2018,False,,IEEE,Not available,Participation Incentives on a Wireless Random Access Erasure Collision Channel,005c0399baec6f48c8f4f42bcaa6053e,https://ieeexplore.ieee.org/document/8503115/
11541,"Random medium access on wireless channels has two key characteristics: heterogeneous channel quality across users (due to the variable wireless channel conditions with the access point across users) and packet collisions (due to random access) at the access point. The design of optimal channel contention probabilities is nontrivial on account of the need to balance between under-utilization (no transmission attempts) and over-utilization (channel collisions) of the wireless channel. The wireless random access erasure collision channel presented in this paper is a parsimonious abstraction of these phenomena. We consider a scenario wherein the base station provides a reward to users in proportion to the rate of successfully received packets, and users incur a cost in proportion to their contention probability. The objective is to select a reward such that the sum-user delivered rate in the equilibrium of the induced game is (approximately) optimal, i.e., such that only higher quality users are incentivized to contend the channel. We use the price of anarchy (PoA) measure and study the extent to which appropriate reward mechanisms can yield good PoA bounds.",vasilis gkatzelis,Receivers,2018.0,10.1109/ITA.2018.8503115,2018 Information Theory and Applications Workshop (ITA),Gkatzelis2018,False,,IEEE,Not available,Participation Incentives on a Wireless Random Access Erasure Collision Channel,005c0399baec6f48c8f4f42bcaa6053e,https://ieeexplore.ieee.org/document/8503115/
11542,"Random medium access on wireless channels has two key characteristics: heterogeneous channel quality across users (due to the variable wireless channel conditions with the access point across users) and packet collisions (due to random access) at the access point. The design of optimal channel contention probabilities is nontrivial on account of the need to balance between under-utilization (no transmission attempts) and over-utilization (channel collisions) of the wireless channel. The wireless random access erasure collision channel presented in this paper is a parsimonious abstraction of these phenomena. We consider a scenario wherein the base station provides a reward to users in proportion to the rate of successfully received packets, and users incur a cost in proportion to their contention probability. The objective is to select a reward such that the sum-user delivered rate in the equilibrium of the induced game is (approximately) optimal, i.e., such that only higher quality users are incentivized to contend the channel. We use the price of anarchy (PoA) measure and study the extent to which appropriate reward mechanisms can yield good PoA bounds.",vasilis gkatzelis,Mathematical model,2018.0,10.1109/ITA.2018.8503115,2018 Information Theory and Applications Workshop (ITA),Gkatzelis2018,False,,IEEE,Not available,Participation Incentives on a Wireless Random Access Erasure Collision Channel,005c0399baec6f48c8f4f42bcaa6053e,https://ieeexplore.ieee.org/document/8503115/
11543,"Random medium access on wireless channels has two key characteristics: heterogeneous channel quality across users (due to the variable wireless channel conditions with the access point across users) and packet collisions (due to random access) at the access point. The design of optimal channel contention probabilities is nontrivial on account of the need to balance between under-utilization (no transmission attempts) and over-utilization (channel collisions) of the wireless channel. The wireless random access erasure collision channel presented in this paper is a parsimonious abstraction of these phenomena. We consider a scenario wherein the base station provides a reward to users in proportion to the rate of successfully received packets, and users incur a cost in proportion to their contention probability. The objective is to select a reward such that the sum-user delivered rate in the equilibrium of the induced game is (approximately) optimal, i.e., such that only higher quality users are incentivized to contend the channel. We use the price of anarchy (PoA) measure and study the extent to which appropriate reward mechanisms can yield good PoA bounds.",vasilis gkatzelis,Atmospheric measurements,2018.0,10.1109/ITA.2018.8503115,2018 Information Theory and Applications Workshop (ITA),Gkatzelis2018,False,,IEEE,Not available,Participation Incentives on a Wireless Random Access Erasure Collision Channel,005c0399baec6f48c8f4f42bcaa6053e,https://ieeexplore.ieee.org/document/8503115/
11544,"Random medium access on wireless channels has two key characteristics: heterogeneous channel quality across users (due to the variable wireless channel conditions with the access point across users) and packet collisions (due to random access) at the access point. The design of optimal channel contention probabilities is nontrivial on account of the need to balance between under-utilization (no transmission attempts) and over-utilization (channel collisions) of the wireless channel. The wireless random access erasure collision channel presented in this paper is a parsimonious abstraction of these phenomena. We consider a scenario wherein the base station provides a reward to users in proportion to the rate of successfully received packets, and users incur a cost in proportion to their contention probability. The objective is to select a reward such that the sum-user delivered rate in the equilibrium of the induced game is (approximately) optimal, i.e., such that only higher quality users are incentivized to contend the channel. We use the price of anarchy (PoA) measure and study the extent to which appropriate reward mechanisms can yield good PoA bounds.",steven weber,Wireless communication,2018.0,10.1109/ITA.2018.8503115,2018 Information Theory and Applications Workshop (ITA),Gkatzelis2018,False,,IEEE,Not available,Participation Incentives on a Wireless Random Access Erasure Collision Channel,005c0399baec6f48c8f4f42bcaa6053e,https://ieeexplore.ieee.org/document/8503115/
11545,"Random medium access on wireless channels has two key characteristics: heterogeneous channel quality across users (due to the variable wireless channel conditions with the access point across users) and packet collisions (due to random access) at the access point. The design of optimal channel contention probabilities is nontrivial on account of the need to balance between under-utilization (no transmission attempts) and over-utilization (channel collisions) of the wireless channel. The wireless random access erasure collision channel presented in this paper is a parsimonious abstraction of these phenomena. We consider a scenario wherein the base station provides a reward to users in proportion to the rate of successfully received packets, and users incur a cost in proportion to their contention probability. The objective is to select a reward such that the sum-user delivered rate in the equilibrium of the induced game is (approximately) optimal, i.e., such that only higher quality users are incentivized to contend the channel. We use the price of anarchy (PoA) measure and study the extent to which appropriate reward mechanisms can yield good PoA bounds.",steven weber,Games,2018.0,10.1109/ITA.2018.8503115,2018 Information Theory and Applications Workshop (ITA),Gkatzelis2018,False,,IEEE,Not available,Participation Incentives on a Wireless Random Access Erasure Collision Channel,005c0399baec6f48c8f4f42bcaa6053e,https://ieeexplore.ieee.org/document/8503115/
11546,"Random medium access on wireless channels has two key characteristics: heterogeneous channel quality across users (due to the variable wireless channel conditions with the access point across users) and packet collisions (due to random access) at the access point. The design of optimal channel contention probabilities is nontrivial on account of the need to balance between under-utilization (no transmission attempts) and over-utilization (channel collisions) of the wireless channel. The wireless random access erasure collision channel presented in this paper is a parsimonious abstraction of these phenomena. We consider a scenario wherein the base station provides a reward to users in proportion to the rate of successfully received packets, and users incur a cost in proportion to their contention probability. The objective is to select a reward such that the sum-user delivered rate in the equilibrium of the induced game is (approximately) optimal, i.e., such that only higher quality users are incentivized to contend the channel. We use the price of anarchy (PoA) measure and study the extent to which appropriate reward mechanisms can yield good PoA bounds.",steven weber,Ad hoc networks,2018.0,10.1109/ITA.2018.8503115,2018 Information Theory and Applications Workshop (ITA),Gkatzelis2018,False,,IEEE,Not available,Participation Incentives on a Wireless Random Access Erasure Collision Channel,005c0399baec6f48c8f4f42bcaa6053e,https://ieeexplore.ieee.org/document/8503115/
11547,"Random medium access on wireless channels has two key characteristics: heterogeneous channel quality across users (due to the variable wireless channel conditions with the access point across users) and packet collisions (due to random access) at the access point. The design of optimal channel contention probabilities is nontrivial on account of the need to balance between under-utilization (no transmission attempts) and over-utilization (channel collisions) of the wireless channel. The wireless random access erasure collision channel presented in this paper is a parsimonious abstraction of these phenomena. We consider a scenario wherein the base station provides a reward to users in proportion to the rate of successfully received packets, and users incur a cost in proportion to their contention probability. The objective is to select a reward such that the sum-user delivered rate in the equilibrium of the induced game is (approximately) optimal, i.e., such that only higher quality users are incentivized to contend the channel. We use the price of anarchy (PoA) measure and study the extent to which appropriate reward mechanisms can yield good PoA bounds.",steven weber,Wireless sensor networks,2018.0,10.1109/ITA.2018.8503115,2018 Information Theory and Applications Workshop (ITA),Gkatzelis2018,False,,IEEE,Not available,Participation Incentives on a Wireless Random Access Erasure Collision Channel,005c0399baec6f48c8f4f42bcaa6053e,https://ieeexplore.ieee.org/document/8503115/
11548,"Random medium access on wireless channels has two key characteristics: heterogeneous channel quality across users (due to the variable wireless channel conditions with the access point across users) and packet collisions (due to random access) at the access point. The design of optimal channel contention probabilities is nontrivial on account of the need to balance between under-utilization (no transmission attempts) and over-utilization (channel collisions) of the wireless channel. The wireless random access erasure collision channel presented in this paper is a parsimonious abstraction of these phenomena. We consider a scenario wherein the base station provides a reward to users in proportion to the rate of successfully received packets, and users incur a cost in proportion to their contention probability. The objective is to select a reward such that the sum-user delivered rate in the equilibrium of the induced game is (approximately) optimal, i.e., such that only higher quality users are incentivized to contend the channel. We use the price of anarchy (PoA) measure and study the extent to which appropriate reward mechanisms can yield good PoA bounds.",steven weber,Receivers,2018.0,10.1109/ITA.2018.8503115,2018 Information Theory and Applications Workshop (ITA),Gkatzelis2018,False,,IEEE,Not available,Participation Incentives on a Wireless Random Access Erasure Collision Channel,005c0399baec6f48c8f4f42bcaa6053e,https://ieeexplore.ieee.org/document/8503115/
11549,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11550,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
11551,"Random medium access on wireless channels has two key characteristics: heterogeneous channel quality across users (due to the variable wireless channel conditions with the access point across users) and packet collisions (due to random access) at the access point. The design of optimal channel contention probabilities is nontrivial on account of the need to balance between under-utilization (no transmission attempts) and over-utilization (channel collisions) of the wireless channel. The wireless random access erasure collision channel presented in this paper is a parsimonious abstraction of these phenomena. We consider a scenario wherein the base station provides a reward to users in proportion to the rate of successfully received packets, and users incur a cost in proportion to their contention probability. The objective is to select a reward such that the sum-user delivered rate in the equilibrium of the induced game is (approximately) optimal, i.e., such that only higher quality users are incentivized to contend the channel. We use the price of anarchy (PoA) measure and study the extent to which appropriate reward mechanisms can yield good PoA bounds.",steven weber,Mathematical model,2018.0,10.1109/ITA.2018.8503115,2018 Information Theory and Applications Workshop (ITA),Gkatzelis2018,False,,IEEE,Not available,Participation Incentives on a Wireless Random Access Erasure Collision Channel,005c0399baec6f48c8f4f42bcaa6053e,https://ieeexplore.ieee.org/document/8503115/
11552,"Random medium access on wireless channels has two key characteristics: heterogeneous channel quality across users (due to the variable wireless channel conditions with the access point across users) and packet collisions (due to random access) at the access point. The design of optimal channel contention probabilities is nontrivial on account of the need to balance between under-utilization (no transmission attempts) and over-utilization (channel collisions) of the wireless channel. The wireless random access erasure collision channel presented in this paper is a parsimonious abstraction of these phenomena. We consider a scenario wherein the base station provides a reward to users in proportion to the rate of successfully received packets, and users incur a cost in proportion to their contention probability. The objective is to select a reward such that the sum-user delivered rate in the equilibrium of the induced game is (approximately) optimal, i.e., such that only higher quality users are incentivized to contend the channel. We use the price of anarchy (PoA) measure and study the extent to which appropriate reward mechanisms can yield good PoA bounds.",steven weber,Atmospheric measurements,2018.0,10.1109/ITA.2018.8503115,2018 Information Theory and Applications Workshop (ITA),Gkatzelis2018,False,,IEEE,Not available,Participation Incentives on a Wireless Random Access Erasure Collision Channel,005c0399baec6f48c8f4f42bcaa6053e,https://ieeexplore.ieee.org/document/8503115/
11553,"We propose Flock; a simple and scalable protocol that enables live migration of Virtual Machines (VMs) across heterogeneous edge and conventional cloud platforms to improve the responsiveness of cloud services. Flock is designed with properties that are suitable for the use cases of the Internet of Things (IoT). We describe the properties of regularized latency measurements that Flock can use for asynchronous and autonomous migration decisions. Such decisions allow communicating VMs to follow a flocking-like behavior that consists of three simple rules: separation, alignment, and cohesion. Using game theory, we derive analytical bounds on Flock's Price of Anarchy (PoA), and prove that flocking VMs converge to a Nash Equilibrium while settling in the best possible cloud platforms. We verify the effectiveness of Flock through simulations and discuss how its generic objective can simply be tweaked to achieve other objectives, such as cloud load balancing and energy consumption minimization.",sherif abdelwahab,Internet of things,2017.0,10.1109/ICC.2017.7996630,2017 IEEE International Conference on Communications (ICC),Abdelwahab2017,False,,IEEE,Not available,Flocking virtual machines in quest for responsive IoT cloud services,1463df007ba5cebf1f72906e00fb7d68,https://ieeexplore.ieee.org/document/7996630/
11554,"We propose Flock; a simple and scalable protocol that enables live migration of Virtual Machines (VMs) across heterogeneous edge and conventional cloud platforms to improve the responsiveness of cloud services. Flock is designed with properties that are suitable for the use cases of the Internet of Things (IoT). We describe the properties of regularized latency measurements that Flock can use for asynchronous and autonomous migration decisions. Such decisions allow communicating VMs to follow a flocking-like behavior that consists of three simple rules: separation, alignment, and cohesion. Using game theory, we derive analytical bounds on Flock's Price of Anarchy (PoA), and prove that flocking VMs converge to a Nash Equilibrium while settling in the best possible cloud platforms. We verify the effectiveness of Flock through simulations and discuss how its generic objective can simply be tweaked to achieve other objectives, such as cloud load balancing and energy consumption minimization.",sherif abdelwahab,Edge computing,2017.0,10.1109/ICC.2017.7996630,2017 IEEE International Conference on Communications (ICC),Abdelwahab2017,False,,IEEE,Not available,Flocking virtual machines in quest for responsive IoT cloud services,1463df007ba5cebf1f72906e00fb7d68,https://ieeexplore.ieee.org/document/7996630/
11555,"We propose Flock; a simple and scalable protocol that enables live migration of Virtual Machines (VMs) across heterogeneous edge and conventional cloud platforms to improve the responsiveness of cloud services. Flock is designed with properties that are suitable for the use cases of the Internet of Things (IoT). We describe the properties of regularized latency measurements that Flock can use for asynchronous and autonomous migration decisions. Such decisions allow communicating VMs to follow a flocking-like behavior that consists of three simple rules: separation, alignment, and cohesion. Using game theory, we derive analytical bounds on Flock's Price of Anarchy (PoA), and prove that flocking VMs converge to a Nash Equilibrium while settling in the best possible cloud platforms. We verify the effectiveness of Flock through simulations and discuss how its generic objective can simply be tweaked to achieve other objectives, such as cloud load balancing and energy consumption minimization.",sherif abdelwahab,Game theory,2017.0,10.1109/ICC.2017.7996630,2017 IEEE International Conference on Communications (ICC),Abdelwahab2017,False,,IEEE,Not available,Flocking virtual machines in quest for responsive IoT cloud services,1463df007ba5cebf1f72906e00fb7d68,https://ieeexplore.ieee.org/document/7996630/
11556,"We propose Flock; a simple and scalable protocol that enables live migration of Virtual Machines (VMs) across heterogeneous edge and conventional cloud platforms to improve the responsiveness of cloud services. Flock is designed with properties that are suitable for the use cases of the Internet of Things (IoT). We describe the properties of regularized latency measurements that Flock can use for asynchronous and autonomous migration decisions. Such decisions allow communicating VMs to follow a flocking-like behavior that consists of three simple rules: separation, alignment, and cohesion. Using game theory, we derive analytical bounds on Flock's Price of Anarchy (PoA), and prove that flocking VMs converge to a Nash Equilibrium while settling in the best possible cloud platforms. We verify the effectiveness of Flock through simulations and discuss how its generic objective can simply be tweaked to achieve other objectives, such as cloud load balancing and energy consumption minimization.",sherif abdelwahab,Resource management,2017.0,10.1109/ICC.2017.7996630,2017 IEEE International Conference on Communications (ICC),Abdelwahab2017,False,,IEEE,Not available,Flocking virtual machines in quest for responsive IoT cloud services,1463df007ba5cebf1f72906e00fb7d68,https://ieeexplore.ieee.org/document/7996630/
11557,"We propose Flock; a simple and scalable protocol that enables live migration of Virtual Machines (VMs) across heterogeneous edge and conventional cloud platforms to improve the responsiveness of cloud services. Flock is designed with properties that are suitable for the use cases of the Internet of Things (IoT). We describe the properties of regularized latency measurements that Flock can use for asynchronous and autonomous migration decisions. Such decisions allow communicating VMs to follow a flocking-like behavior that consists of three simple rules: separation, alignment, and cohesion. Using game theory, we derive analytical bounds on Flock's Price of Anarchy (PoA), and prove that flocking VMs converge to a Nash Equilibrium while settling in the best possible cloud platforms. We verify the effectiveness of Flock through simulations and discuss how its generic objective can simply be tweaked to achieve other objectives, such as cloud load balancing and energy consumption minimization.",bechir hamdaoui,Internet of things,2017.0,10.1109/ICC.2017.7996630,2017 IEEE International Conference on Communications (ICC),Abdelwahab2017,False,,IEEE,Not available,Flocking virtual machines in quest for responsive IoT cloud services,1463df007ba5cebf1f72906e00fb7d68,https://ieeexplore.ieee.org/document/7996630/
11558,"We propose Flock; a simple and scalable protocol that enables live migration of Virtual Machines (VMs) across heterogeneous edge and conventional cloud platforms to improve the responsiveness of cloud services. Flock is designed with properties that are suitable for the use cases of the Internet of Things (IoT). We describe the properties of regularized latency measurements that Flock can use for asynchronous and autonomous migration decisions. Such decisions allow communicating VMs to follow a flocking-like behavior that consists of three simple rules: separation, alignment, and cohesion. Using game theory, we derive analytical bounds on Flock's Price of Anarchy (PoA), and prove that flocking VMs converge to a Nash Equilibrium while settling in the best possible cloud platforms. We verify the effectiveness of Flock through simulations and discuss how its generic objective can simply be tweaked to achieve other objectives, such as cloud load balancing and energy consumption minimization.",bechir hamdaoui,Edge computing,2017.0,10.1109/ICC.2017.7996630,2017 IEEE International Conference on Communications (ICC),Abdelwahab2017,False,,IEEE,Not available,Flocking virtual machines in quest for responsive IoT cloud services,1463df007ba5cebf1f72906e00fb7d68,https://ieeexplore.ieee.org/document/7996630/
11559,"We propose Flock; a simple and scalable protocol that enables live migration of Virtual Machines (VMs) across heterogeneous edge and conventional cloud platforms to improve the responsiveness of cloud services. Flock is designed with properties that are suitable for the use cases of the Internet of Things (IoT). We describe the properties of regularized latency measurements that Flock can use for asynchronous and autonomous migration decisions. Such decisions allow communicating VMs to follow a flocking-like behavior that consists of three simple rules: separation, alignment, and cohesion. Using game theory, we derive analytical bounds on Flock's Price of Anarchy (PoA), and prove that flocking VMs converge to a Nash Equilibrium while settling in the best possible cloud platforms. We verify the effectiveness of Flock through simulations and discuss how its generic objective can simply be tweaked to achieve other objectives, such as cloud load balancing and energy consumption minimization.",bechir hamdaoui,Game theory,2017.0,10.1109/ICC.2017.7996630,2017 IEEE International Conference on Communications (ICC),Abdelwahab2017,False,,IEEE,Not available,Flocking virtual machines in quest for responsive IoT cloud services,1463df007ba5cebf1f72906e00fb7d68,https://ieeexplore.ieee.org/document/7996630/
11560,"We propose Flock; a simple and scalable protocol that enables live migration of Virtual Machines (VMs) across heterogeneous edge and conventional cloud platforms to improve the responsiveness of cloud services. Flock is designed with properties that are suitable for the use cases of the Internet of Things (IoT). We describe the properties of regularized latency measurements that Flock can use for asynchronous and autonomous migration decisions. Such decisions allow communicating VMs to follow a flocking-like behavior that consists of three simple rules: separation, alignment, and cohesion. Using game theory, we derive analytical bounds on Flock's Price of Anarchy (PoA), and prove that flocking VMs converge to a Nash Equilibrium while settling in the best possible cloud platforms. We verify the effectiveness of Flock through simulations and discuss how its generic objective can simply be tweaked to achieve other objectives, such as cloud load balancing and energy consumption minimization.",bechir hamdaoui,Resource management,2017.0,10.1109/ICC.2017.7996630,2017 IEEE International Conference on Communications (ICC),Abdelwahab2017,False,,IEEE,Not available,Flocking virtual machines in quest for responsive IoT cloud services,1463df007ba5cebf1f72906e00fb7d68,https://ieeexplore.ieee.org/document/7996630/
11561,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
11562,"Game theory has been shown to be a valuable tool to study strategic electricity consumers enrolled in a demand response program. Among the different billing mechanisms proposed in the literature, the hourly billing model is of special interest as an intuitive and fair mechanism. We focus on this model and answer to several theoretical and practical questions. First, we prove the uniqueness of the consumption profile corresponding to the Nash equilibrium, and we analyze its efficiency by providing a bound on the Price of Anarchy. Next, we address the computational issue of this equilibrium profile by providing results on the convergence rates of two decentralized algorithms to compute the equilibrium: the cycling best response dynamics and a projected gradient descent method. Last, we simulate this demand response framework in a stochastic environment where the parameters depend on forecasts. We show numerically the relevance of an online demand response procedure which reduces the impact of inaccurate forecasts in comparison to a standard offline procedure.",paulin jacquot,Smart Grid,,10.1109/TSG.2018.2855041,IEEE Transactions on Smart Grid,JacquotNone,False,,IEEE,Not available,Analysis and Implementation of an Hourly Billing Mechanism for Demand Response Management,4e9c8263db9cbdb078cb82cc4c371cce,
11563,"Game theory has been shown to be a valuable tool to study strategic electricity consumers enrolled in a demand response program. Among the different billing mechanisms proposed in the literature, the hourly billing model is of special interest as an intuitive and fair mechanism. We focus on this model and answer to several theoretical and practical questions. First, we prove the uniqueness of the consumption profile corresponding to the Nash equilibrium, and we analyze its efficiency by providing a bound on the Price of Anarchy. Next, we address the computational issue of this equilibrium profile by providing results on the convergence rates of two decentralized algorithms to compute the equilibrium: the cycling best response dynamics and a projected gradient descent method. Last, we simulate this demand response framework in a stochastic environment where the parameters depend on forecasts. We show numerically the relevance of an online demand response procedure which reduces the impact of inaccurate forecasts in comparison to a standard offline procedure.",paulin jacquot,Demand Response,,10.1109/TSG.2018.2855041,IEEE Transactions on Smart Grid,JacquotNone,False,,IEEE,Not available,Analysis and Implementation of an Hourly Billing Mechanism for Demand Response Management,4e9c8263db9cbdb078cb82cc4c371cce,
11564,"Game theory has been shown to be a valuable tool to study strategic electricity consumers enrolled in a demand response program. Among the different billing mechanisms proposed in the literature, the hourly billing model is of special interest as an intuitive and fair mechanism. We focus on this model and answer to several theoretical and practical questions. First, we prove the uniqueness of the consumption profile corresponding to the Nash equilibrium, and we analyze its efficiency by providing a bound on the Price of Anarchy. Next, we address the computational issue of this equilibrium profile by providing results on the convergence rates of two decentralized algorithms to compute the equilibrium: the cycling best response dynamics and a projected gradient descent method. Last, we simulate this demand response framework in a stochastic environment where the parameters depend on forecasts. We show numerically the relevance of an online demand response procedure which reduces the impact of inaccurate forecasts in comparison to a standard offline procedure.",paulin jacquot,Demand Side Management,,10.1109/TSG.2018.2855041,IEEE Transactions on Smart Grid,JacquotNone,False,,IEEE,Not available,Analysis and Implementation of an Hourly Billing Mechanism for Demand Response Management,4e9c8263db9cbdb078cb82cc4c371cce,
11565,"Game theory has been shown to be a valuable tool to study strategic electricity consumers enrolled in a demand response program. Among the different billing mechanisms proposed in the literature, the hourly billing model is of special interest as an intuitive and fair mechanism. We focus on this model and answer to several theoretical and practical questions. First, we prove the uniqueness of the consumption profile corresponding to the Nash equilibrium, and we analyze its efficiency by providing a bound on the Price of Anarchy. Next, we address the computational issue of this equilibrium profile by providing results on the convergence rates of two decentralized algorithms to compute the equilibrium: the cycling best response dynamics and a projected gradient descent method. Last, we simulate this demand response framework in a stochastic environment where the parameters depend on forecasts. We show numerically the relevance of an online demand response procedure which reduces the impact of inaccurate forecasts in comparison to a standard offline procedure.",paulin jacquot,Game Theory,,10.1109/TSG.2018.2855041,IEEE Transactions on Smart Grid,JacquotNone,False,,IEEE,Not available,Analysis and Implementation of an Hourly Billing Mechanism for Demand Response Management,4e9c8263db9cbdb078cb82cc4c371cce,
11566,"Game theory has been shown to be a valuable tool to study strategic electricity consumers enrolled in a demand response program. Among the different billing mechanisms proposed in the literature, the hourly billing model is of special interest as an intuitive and fair mechanism. We focus on this model and answer to several theoretical and practical questions. First, we prove the uniqueness of the consumption profile corresponding to the Nash equilibrium, and we analyze its efficiency by providing a bound on the Price of Anarchy. Next, we address the computational issue of this equilibrium profile by providing results on the convergence rates of two decentralized algorithms to compute the equilibrium: the cycling best response dynamics and a projected gradient descent method. Last, we simulate this demand response framework in a stochastic environment where the parameters depend on forecasts. We show numerically the relevance of an online demand response procedure which reduces the impact of inaccurate forecasts in comparison to a standard offline procedure.",paulin jacquot,Nash Equilibrium,,10.1109/TSG.2018.2855041,IEEE Transactions on Smart Grid,JacquotNone,False,,IEEE,Not available,Analysis and Implementation of an Hourly Billing Mechanism for Demand Response Management,4e9c8263db9cbdb078cb82cc4c371cce,
11567,"Game theory has been shown to be a valuable tool to study strategic electricity consumers enrolled in a demand response program. Among the different billing mechanisms proposed in the literature, the hourly billing model is of special interest as an intuitive and fair mechanism. We focus on this model and answer to several theoretical and practical questions. First, we prove the uniqueness of the consumption profile corresponding to the Nash equilibrium, and we analyze its efficiency by providing a bound on the Price of Anarchy. Next, we address the computational issue of this equilibrium profile by providing results on the convergence rates of two decentralized algorithms to compute the equilibrium: the cycling best response dynamics and a projected gradient descent method. Last, we simulate this demand response framework in a stochastic environment where the parameters depend on forecasts. We show numerically the relevance of an online demand response procedure which reduces the impact of inaccurate forecasts in comparison to a standard offline procedure.",paulin jacquot,Best Response.,,10.1109/TSG.2018.2855041,IEEE Transactions on Smart Grid,JacquotNone,False,,IEEE,Not available,Analysis and Implementation of an Hourly Billing Mechanism for Demand Response Management,4e9c8263db9cbdb078cb82cc4c371cce,
11568,"Game theory has been shown to be a valuable tool to study strategic electricity consumers enrolled in a demand response program. Among the different billing mechanisms proposed in the literature, the hourly billing model is of special interest as an intuitive and fair mechanism. We focus on this model and answer to several theoretical and practical questions. First, we prove the uniqueness of the consumption profile corresponding to the Nash equilibrium, and we analyze its efficiency by providing a bound on the Price of Anarchy. Next, we address the computational issue of this equilibrium profile by providing results on the convergence rates of two decentralized algorithms to compute the equilibrium: the cycling best response dynamics and a projected gradient descent method. Last, we simulate this demand response framework in a stochastic environment where the parameters depend on forecasts. We show numerically the relevance of an online demand response procedure which reduces the impact of inaccurate forecasts in comparison to a standard offline procedure.",paulin jacquot,Smart Grid,,10.1109/TSG.2018.2855041,IEEE Transactions on Smart Grid,JacquotNone,False,,IEEE,Not available,Analysis and Implementation of an Hourly Billing Mechanism for Demand Response Management,4e9c8263db9cbdb078cb82cc4c371cce,
11569,"Game theory has been shown to be a valuable tool to study strategic electricity consumers enrolled in a demand response program. Among the different billing mechanisms proposed in the literature, the hourly billing model is of special interest as an intuitive and fair mechanism. We focus on this model and answer to several theoretical and practical questions. First, we prove the uniqueness of the consumption profile corresponding to the Nash equilibrium, and we analyze its efficiency by providing a bound on the Price of Anarchy. Next, we address the computational issue of this equilibrium profile by providing results on the convergence rates of two decentralized algorithms to compute the equilibrium: the cycling best response dynamics and a projected gradient descent method. Last, we simulate this demand response framework in a stochastic environment where the parameters depend on forecasts. We show numerically the relevance of an online demand response procedure which reduces the impact of inaccurate forecasts in comparison to a standard offline procedure.",paulin jacquot,Demand Response,,10.1109/TSG.2018.2855041,IEEE Transactions on Smart Grid,JacquotNone,False,,IEEE,Not available,Analysis and Implementation of an Hourly Billing Mechanism for Demand Response Management,4e9c8263db9cbdb078cb82cc4c371cce,
11570,"Game theory has been shown to be a valuable tool to study strategic electricity consumers enrolled in a demand response program. Among the different billing mechanisms proposed in the literature, the hourly billing model is of special interest as an intuitive and fair mechanism. We focus on this model and answer to several theoretical and practical questions. First, we prove the uniqueness of the consumption profile corresponding to the Nash equilibrium, and we analyze its efficiency by providing a bound on the Price of Anarchy. Next, we address the computational issue of this equilibrium profile by providing results on the convergence rates of two decentralized algorithms to compute the equilibrium: the cycling best response dynamics and a projected gradient descent method. Last, we simulate this demand response framework in a stochastic environment where the parameters depend on forecasts. We show numerically the relevance of an online demand response procedure which reduces the impact of inaccurate forecasts in comparison to a standard offline procedure.",paulin jacquot,Demand Side Management,,10.1109/TSG.2018.2855041,IEEE Transactions on Smart Grid,JacquotNone,False,,IEEE,Not available,Analysis and Implementation of an Hourly Billing Mechanism for Demand Response Management,4e9c8263db9cbdb078cb82cc4c371cce,
11571,"Game theory has been shown to be a valuable tool to study strategic electricity consumers enrolled in a demand response program. Among the different billing mechanisms proposed in the literature, the hourly billing model is of special interest as an intuitive and fair mechanism. We focus on this model and answer to several theoretical and practical questions. First, we prove the uniqueness of the consumption profile corresponding to the Nash equilibrium, and we analyze its efficiency by providing a bound on the Price of Anarchy. Next, we address the computational issue of this equilibrium profile by providing results on the convergence rates of two decentralized algorithms to compute the equilibrium: the cycling best response dynamics and a projected gradient descent method. Last, we simulate this demand response framework in a stochastic environment where the parameters depend on forecasts. We show numerically the relevance of an online demand response procedure which reduces the impact of inaccurate forecasts in comparison to a standard offline procedure.",paulin jacquot,Game Theory,,10.1109/TSG.2018.2855041,IEEE Transactions on Smart Grid,JacquotNone,False,,IEEE,Not available,Analysis and Implementation of an Hourly Billing Mechanism for Demand Response Management,4e9c8263db9cbdb078cb82cc4c371cce,
11572,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
11573,"Game theory has been shown to be a valuable tool to study strategic electricity consumers enrolled in a demand response program. Among the different billing mechanisms proposed in the literature, the hourly billing model is of special interest as an intuitive and fair mechanism. We focus on this model and answer to several theoretical and practical questions. First, we prove the uniqueness of the consumption profile corresponding to the Nash equilibrium, and we analyze its efficiency by providing a bound on the Price of Anarchy. Next, we address the computational issue of this equilibrium profile by providing results on the convergence rates of two decentralized algorithms to compute the equilibrium: the cycling best response dynamics and a projected gradient descent method. Last, we simulate this demand response framework in a stochastic environment where the parameters depend on forecasts. We show numerically the relevance of an online demand response procedure which reduces the impact of inaccurate forecasts in comparison to a standard offline procedure.",paulin jacquot,Nash Equilibrium,,10.1109/TSG.2018.2855041,IEEE Transactions on Smart Grid,JacquotNone,False,,IEEE,Not available,Analysis and Implementation of an Hourly Billing Mechanism for Demand Response Management,4e9c8263db9cbdb078cb82cc4c371cce,
11574,"Game theory has been shown to be a valuable tool to study strategic electricity consumers enrolled in a demand response program. Among the different billing mechanisms proposed in the literature, the hourly billing model is of special interest as an intuitive and fair mechanism. We focus on this model and answer to several theoretical and practical questions. First, we prove the uniqueness of the consumption profile corresponding to the Nash equilibrium, and we analyze its efficiency by providing a bound on the Price of Anarchy. Next, we address the computational issue of this equilibrium profile by providing results on the convergence rates of two decentralized algorithms to compute the equilibrium: the cycling best response dynamics and a projected gradient descent method. Last, we simulate this demand response framework in a stochastic environment where the parameters depend on forecasts. We show numerically the relevance of an online demand response procedure which reduces the impact of inaccurate forecasts in comparison to a standard offline procedure.",paulin jacquot,Best Response.,,10.1109/TSG.2018.2855041,IEEE Transactions on Smart Grid,JacquotNone,False,,IEEE,Not available,Analysis and Implementation of an Hourly Billing Mechanism for Demand Response Management,4e9c8263db9cbdb078cb82cc4c371cce,
11575,"Game theory has been shown to be a valuable tool to study strategic electricity consumers enrolled in a demand response program. Among the different billing mechanisms proposed in the literature, the hourly billing model is of special interest as an intuitive and fair mechanism. We focus on this model and answer to several theoretical and practical questions. First, we prove the uniqueness of the consumption profile corresponding to the Nash equilibrium, and we analyze its efficiency by providing a bound on the Price of Anarchy. Next, we address the computational issue of this equilibrium profile by providing results on the convergence rates of two decentralized algorithms to compute the equilibrium: the cycling best response dynamics and a projected gradient descent method. Last, we simulate this demand response framework in a stochastic environment where the parameters depend on forecasts. We show numerically the relevance of an online demand response procedure which reduces the impact of inaccurate forecasts in comparison to a standard offline procedure.",olivier beaude,Smart Grid,,10.1109/TSG.2018.2855041,IEEE Transactions on Smart Grid,JacquotNone,False,,IEEE,Not available,Analysis and Implementation of an Hourly Billing Mechanism for Demand Response Management,4e9c8263db9cbdb078cb82cc4c371cce,
11576,"Game theory has been shown to be a valuable tool to study strategic electricity consumers enrolled in a demand response program. Among the different billing mechanisms proposed in the literature, the hourly billing model is of special interest as an intuitive and fair mechanism. We focus on this model and answer to several theoretical and practical questions. First, we prove the uniqueness of the consumption profile corresponding to the Nash equilibrium, and we analyze its efficiency by providing a bound on the Price of Anarchy. Next, we address the computational issue of this equilibrium profile by providing results on the convergence rates of two decentralized algorithms to compute the equilibrium: the cycling best response dynamics and a projected gradient descent method. Last, we simulate this demand response framework in a stochastic environment where the parameters depend on forecasts. We show numerically the relevance of an online demand response procedure which reduces the impact of inaccurate forecasts in comparison to a standard offline procedure.",olivier beaude,Demand Response,,10.1109/TSG.2018.2855041,IEEE Transactions on Smart Grid,JacquotNone,False,,IEEE,Not available,Analysis and Implementation of an Hourly Billing Mechanism for Demand Response Management,4e9c8263db9cbdb078cb82cc4c371cce,
11577,"Game theory has been shown to be a valuable tool to study strategic electricity consumers enrolled in a demand response program. Among the different billing mechanisms proposed in the literature, the hourly billing model is of special interest as an intuitive and fair mechanism. We focus on this model and answer to several theoretical and practical questions. First, we prove the uniqueness of the consumption profile corresponding to the Nash equilibrium, and we analyze its efficiency by providing a bound on the Price of Anarchy. Next, we address the computational issue of this equilibrium profile by providing results on the convergence rates of two decentralized algorithms to compute the equilibrium: the cycling best response dynamics and a projected gradient descent method. Last, we simulate this demand response framework in a stochastic environment where the parameters depend on forecasts. We show numerically the relevance of an online demand response procedure which reduces the impact of inaccurate forecasts in comparison to a standard offline procedure.",olivier beaude,Demand Side Management,,10.1109/TSG.2018.2855041,IEEE Transactions on Smart Grid,JacquotNone,False,,IEEE,Not available,Analysis and Implementation of an Hourly Billing Mechanism for Demand Response Management,4e9c8263db9cbdb078cb82cc4c371cce,
11578,"Game theory has been shown to be a valuable tool to study strategic electricity consumers enrolled in a demand response program. Among the different billing mechanisms proposed in the literature, the hourly billing model is of special interest as an intuitive and fair mechanism. We focus on this model and answer to several theoretical and practical questions. First, we prove the uniqueness of the consumption profile corresponding to the Nash equilibrium, and we analyze its efficiency by providing a bound on the Price of Anarchy. Next, we address the computational issue of this equilibrium profile by providing results on the convergence rates of two decentralized algorithms to compute the equilibrium: the cycling best response dynamics and a projected gradient descent method. Last, we simulate this demand response framework in a stochastic environment where the parameters depend on forecasts. We show numerically the relevance of an online demand response procedure which reduces the impact of inaccurate forecasts in comparison to a standard offline procedure.",olivier beaude,Game Theory,,10.1109/TSG.2018.2855041,IEEE Transactions on Smart Grid,JacquotNone,False,,IEEE,Not available,Analysis and Implementation of an Hourly Billing Mechanism for Demand Response Management,4e9c8263db9cbdb078cb82cc4c371cce,
11579,"Game theory has been shown to be a valuable tool to study strategic electricity consumers enrolled in a demand response program. Among the different billing mechanisms proposed in the literature, the hourly billing model is of special interest as an intuitive and fair mechanism. We focus on this model and answer to several theoretical and practical questions. First, we prove the uniqueness of the consumption profile corresponding to the Nash equilibrium, and we analyze its efficiency by providing a bound on the Price of Anarchy. Next, we address the computational issue of this equilibrium profile by providing results on the convergence rates of two decentralized algorithms to compute the equilibrium: the cycling best response dynamics and a projected gradient descent method. Last, we simulate this demand response framework in a stochastic environment where the parameters depend on forecasts. We show numerically the relevance of an online demand response procedure which reduces the impact of inaccurate forecasts in comparison to a standard offline procedure.",olivier beaude,Nash Equilibrium,,10.1109/TSG.2018.2855041,IEEE Transactions on Smart Grid,JacquotNone,False,,IEEE,Not available,Analysis and Implementation of an Hourly Billing Mechanism for Demand Response Management,4e9c8263db9cbdb078cb82cc4c371cce,
11580,"Game theory has been shown to be a valuable tool to study strategic electricity consumers enrolled in a demand response program. Among the different billing mechanisms proposed in the literature, the hourly billing model is of special interest as an intuitive and fair mechanism. We focus on this model and answer to several theoretical and practical questions. First, we prove the uniqueness of the consumption profile corresponding to the Nash equilibrium, and we analyze its efficiency by providing a bound on the Price of Anarchy. Next, we address the computational issue of this equilibrium profile by providing results on the convergence rates of two decentralized algorithms to compute the equilibrium: the cycling best response dynamics and a projected gradient descent method. Last, we simulate this demand response framework in a stochastic environment where the parameters depend on forecasts. We show numerically the relevance of an online demand response procedure which reduces the impact of inaccurate forecasts in comparison to a standard offline procedure.",olivier beaude,Best Response.,,10.1109/TSG.2018.2855041,IEEE Transactions on Smart Grid,JacquotNone,False,,IEEE,Not available,Analysis and Implementation of an Hourly Billing Mechanism for Demand Response Management,4e9c8263db9cbdb078cb82cc4c371cce,
11581,"Game theory has been shown to be a valuable tool to study strategic electricity consumers enrolled in a demand response program. Among the different billing mechanisms proposed in the literature, the hourly billing model is of special interest as an intuitive and fair mechanism. We focus on this model and answer to several theoretical and practical questions. First, we prove the uniqueness of the consumption profile corresponding to the Nash equilibrium, and we analyze its efficiency by providing a bound on the Price of Anarchy. Next, we address the computational issue of this equilibrium profile by providing results on the convergence rates of two decentralized algorithms to compute the equilibrium: the cycling best response dynamics and a projected gradient descent method. Last, we simulate this demand response framework in a stochastic environment where the parameters depend on forecasts. We show numerically the relevance of an online demand response procedure which reduces the impact of inaccurate forecasts in comparison to a standard offline procedure.",stephane gaubert,Smart Grid,,10.1109/TSG.2018.2855041,IEEE Transactions on Smart Grid,JacquotNone,False,,IEEE,Not available,Analysis and Implementation of an Hourly Billing Mechanism for Demand Response Management,4e9c8263db9cbdb078cb82cc4c371cce,
11582,"Game theory has been shown to be a valuable tool to study strategic electricity consumers enrolled in a demand response program. Among the different billing mechanisms proposed in the literature, the hourly billing model is of special interest as an intuitive and fair mechanism. We focus on this model and answer to several theoretical and practical questions. First, we prove the uniqueness of the consumption profile corresponding to the Nash equilibrium, and we analyze its efficiency by providing a bound on the Price of Anarchy. Next, we address the computational issue of this equilibrium profile by providing results on the convergence rates of two decentralized algorithms to compute the equilibrium: the cycling best response dynamics and a projected gradient descent method. Last, we simulate this demand response framework in a stochastic environment where the parameters depend on forecasts. We show numerically the relevance of an online demand response procedure which reduces the impact of inaccurate forecasts in comparison to a standard offline procedure.",stephane gaubert,Demand Response,,10.1109/TSG.2018.2855041,IEEE Transactions on Smart Grid,JacquotNone,False,,IEEE,Not available,Analysis and Implementation of an Hourly Billing Mechanism for Demand Response Management,4e9c8263db9cbdb078cb82cc4c371cce,
11583,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
11584,"Game theory has been shown to be a valuable tool to study strategic electricity consumers enrolled in a demand response program. Among the different billing mechanisms proposed in the literature, the hourly billing model is of special interest as an intuitive and fair mechanism. We focus on this model and answer to several theoretical and practical questions. First, we prove the uniqueness of the consumption profile corresponding to the Nash equilibrium, and we analyze its efficiency by providing a bound on the Price of Anarchy. Next, we address the computational issue of this equilibrium profile by providing results on the convergence rates of two decentralized algorithms to compute the equilibrium: the cycling best response dynamics and a projected gradient descent method. Last, we simulate this demand response framework in a stochastic environment where the parameters depend on forecasts. We show numerically the relevance of an online demand response procedure which reduces the impact of inaccurate forecasts in comparison to a standard offline procedure.",stephane gaubert,Demand Side Management,,10.1109/TSG.2018.2855041,IEEE Transactions on Smart Grid,JacquotNone,False,,IEEE,Not available,Analysis and Implementation of an Hourly Billing Mechanism for Demand Response Management,4e9c8263db9cbdb078cb82cc4c371cce,
11585,"Game theory has been shown to be a valuable tool to study strategic electricity consumers enrolled in a demand response program. Among the different billing mechanisms proposed in the literature, the hourly billing model is of special interest as an intuitive and fair mechanism. We focus on this model and answer to several theoretical and practical questions. First, we prove the uniqueness of the consumption profile corresponding to the Nash equilibrium, and we analyze its efficiency by providing a bound on the Price of Anarchy. Next, we address the computational issue of this equilibrium profile by providing results on the convergence rates of two decentralized algorithms to compute the equilibrium: the cycling best response dynamics and a projected gradient descent method. Last, we simulate this demand response framework in a stochastic environment where the parameters depend on forecasts. We show numerically the relevance of an online demand response procedure which reduces the impact of inaccurate forecasts in comparison to a standard offline procedure.",stephane gaubert,Game Theory,,10.1109/TSG.2018.2855041,IEEE Transactions on Smart Grid,JacquotNone,False,,IEEE,Not available,Analysis and Implementation of an Hourly Billing Mechanism for Demand Response Management,4e9c8263db9cbdb078cb82cc4c371cce,
11586,"Game theory has been shown to be a valuable tool to study strategic electricity consumers enrolled in a demand response program. Among the different billing mechanisms proposed in the literature, the hourly billing model is of special interest as an intuitive and fair mechanism. We focus on this model and answer to several theoretical and practical questions. First, we prove the uniqueness of the consumption profile corresponding to the Nash equilibrium, and we analyze its efficiency by providing a bound on the Price of Anarchy. Next, we address the computational issue of this equilibrium profile by providing results on the convergence rates of two decentralized algorithms to compute the equilibrium: the cycling best response dynamics and a projected gradient descent method. Last, we simulate this demand response framework in a stochastic environment where the parameters depend on forecasts. We show numerically the relevance of an online demand response procedure which reduces the impact of inaccurate forecasts in comparison to a standard offline procedure.",stephane gaubert,Nash Equilibrium,,10.1109/TSG.2018.2855041,IEEE Transactions on Smart Grid,JacquotNone,False,,IEEE,Not available,Analysis and Implementation of an Hourly Billing Mechanism for Demand Response Management,4e9c8263db9cbdb078cb82cc4c371cce,
11587,"Game theory has been shown to be a valuable tool to study strategic electricity consumers enrolled in a demand response program. Among the different billing mechanisms proposed in the literature, the hourly billing model is of special interest as an intuitive and fair mechanism. We focus on this model and answer to several theoretical and practical questions. First, we prove the uniqueness of the consumption profile corresponding to the Nash equilibrium, and we analyze its efficiency by providing a bound on the Price of Anarchy. Next, we address the computational issue of this equilibrium profile by providing results on the convergence rates of two decentralized algorithms to compute the equilibrium: the cycling best response dynamics and a projected gradient descent method. Last, we simulate this demand response framework in a stochastic environment where the parameters depend on forecasts. We show numerically the relevance of an online demand response procedure which reduces the impact of inaccurate forecasts in comparison to a standard offline procedure.",stephane gaubert,Best Response.,,10.1109/TSG.2018.2855041,IEEE Transactions on Smart Grid,JacquotNone,False,,IEEE,Not available,Analysis and Implementation of an Hourly Billing Mechanism for Demand Response Management,4e9c8263db9cbdb078cb82cc4c371cce,
11588,"Game theory has been shown to be a valuable tool to study strategic electricity consumers enrolled in a demand response program. Among the different billing mechanisms proposed in the literature, the hourly billing model is of special interest as an intuitive and fair mechanism. We focus on this model and answer to several theoretical and practical questions. First, we prove the uniqueness of the consumption profile corresponding to the Nash equilibrium, and we analyze its efficiency by providing a bound on the Price of Anarchy. Next, we address the computational issue of this equilibrium profile by providing results on the convergence rates of two decentralized algorithms to compute the equilibrium: the cycling best response dynamics and a projected gradient descent method. Last, we simulate this demand response framework in a stochastic environment where the parameters depend on forecasts. We show numerically the relevance of an online demand response procedure which reduces the impact of inaccurate forecasts in comparison to a standard offline procedure.",nadia oudjane,Smart Grid,,10.1109/TSG.2018.2855041,IEEE Transactions on Smart Grid,JacquotNone,False,,IEEE,Not available,Analysis and Implementation of an Hourly Billing Mechanism for Demand Response Management,4e9c8263db9cbdb078cb82cc4c371cce,
11589,"Game theory has been shown to be a valuable tool to study strategic electricity consumers enrolled in a demand response program. Among the different billing mechanisms proposed in the literature, the hourly billing model is of special interest as an intuitive and fair mechanism. We focus on this model and answer to several theoretical and practical questions. First, we prove the uniqueness of the consumption profile corresponding to the Nash equilibrium, and we analyze its efficiency by providing a bound on the Price of Anarchy. Next, we address the computational issue of this equilibrium profile by providing results on the convergence rates of two decentralized algorithms to compute the equilibrium: the cycling best response dynamics and a projected gradient descent method. Last, we simulate this demand response framework in a stochastic environment where the parameters depend on forecasts. We show numerically the relevance of an online demand response procedure which reduces the impact of inaccurate forecasts in comparison to a standard offline procedure.",nadia oudjane,Demand Response,,10.1109/TSG.2018.2855041,IEEE Transactions on Smart Grid,JacquotNone,False,,IEEE,Not available,Analysis and Implementation of an Hourly Billing Mechanism for Demand Response Management,4e9c8263db9cbdb078cb82cc4c371cce,
11590,"Game theory has been shown to be a valuable tool to study strategic electricity consumers enrolled in a demand response program. Among the different billing mechanisms proposed in the literature, the hourly billing model is of special interest as an intuitive and fair mechanism. We focus on this model and answer to several theoretical and practical questions. First, we prove the uniqueness of the consumption profile corresponding to the Nash equilibrium, and we analyze its efficiency by providing a bound on the Price of Anarchy. Next, we address the computational issue of this equilibrium profile by providing results on the convergence rates of two decentralized algorithms to compute the equilibrium: the cycling best response dynamics and a projected gradient descent method. Last, we simulate this demand response framework in a stochastic environment where the parameters depend on forecasts. We show numerically the relevance of an online demand response procedure which reduces the impact of inaccurate forecasts in comparison to a standard offline procedure.",nadia oudjane,Demand Side Management,,10.1109/TSG.2018.2855041,IEEE Transactions on Smart Grid,JacquotNone,False,,IEEE,Not available,Analysis and Implementation of an Hourly Billing Mechanism for Demand Response Management,4e9c8263db9cbdb078cb82cc4c371cce,
11591,"Game theory has been shown to be a valuable tool to study strategic electricity consumers enrolled in a demand response program. Among the different billing mechanisms proposed in the literature, the hourly billing model is of special interest as an intuitive and fair mechanism. We focus on this model and answer to several theoretical and practical questions. First, we prove the uniqueness of the consumption profile corresponding to the Nash equilibrium, and we analyze its efficiency by providing a bound on the Price of Anarchy. Next, we address the computational issue of this equilibrium profile by providing results on the convergence rates of two decentralized algorithms to compute the equilibrium: the cycling best response dynamics and a projected gradient descent method. Last, we simulate this demand response framework in a stochastic environment where the parameters depend on forecasts. We show numerically the relevance of an online demand response procedure which reduces the impact of inaccurate forecasts in comparison to a standard offline procedure.",nadia oudjane,Game Theory,,10.1109/TSG.2018.2855041,IEEE Transactions on Smart Grid,JacquotNone,False,,IEEE,Not available,Analysis and Implementation of an Hourly Billing Mechanism for Demand Response Management,4e9c8263db9cbdb078cb82cc4c371cce,
11592,"Game theory has been shown to be a valuable tool to study strategic electricity consumers enrolled in a demand response program. Among the different billing mechanisms proposed in the literature, the hourly billing model is of special interest as an intuitive and fair mechanism. We focus on this model and answer to several theoretical and practical questions. First, we prove the uniqueness of the consumption profile corresponding to the Nash equilibrium, and we analyze its efficiency by providing a bound on the Price of Anarchy. Next, we address the computational issue of this equilibrium profile by providing results on the convergence rates of two decentralized algorithms to compute the equilibrium: the cycling best response dynamics and a projected gradient descent method. Last, we simulate this demand response framework in a stochastic environment where the parameters depend on forecasts. We show numerically the relevance of an online demand response procedure which reduces the impact of inaccurate forecasts in comparison to a standard offline procedure.",nadia oudjane,Nash Equilibrium,,10.1109/TSG.2018.2855041,IEEE Transactions on Smart Grid,JacquotNone,False,,IEEE,Not available,Analysis and Implementation of an Hourly Billing Mechanism for Demand Response Management,4e9c8263db9cbdb078cb82cc4c371cce,
11593,"Game theory has been shown to be a valuable tool to study strategic electricity consumers enrolled in a demand response program. Among the different billing mechanisms proposed in the literature, the hourly billing model is of special interest as an intuitive and fair mechanism. We focus on this model and answer to several theoretical and practical questions. First, we prove the uniqueness of the consumption profile corresponding to the Nash equilibrium, and we analyze its efficiency by providing a bound on the Price of Anarchy. Next, we address the computational issue of this equilibrium profile by providing results on the convergence rates of two decentralized algorithms to compute the equilibrium: the cycling best response dynamics and a projected gradient descent method. Last, we simulate this demand response framework in a stochastic environment where the parameters depend on forecasts. We show numerically the relevance of an online demand response procedure which reduces the impact of inaccurate forecasts in comparison to a standard offline procedure.",nadia oudjane,Best Response.,,10.1109/TSG.2018.2855041,IEEE Transactions on Smart Grid,JacquotNone,False,,IEEE,Not available,Analysis and Implementation of an Hourly Billing Mechanism for Demand Response Management,4e9c8263db9cbdb078cb82cc4c371cce,
11594,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
11595,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",jing zhang,Transportation networks,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
11596,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",jing zhang,variational inequalities,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
11597,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",jing zhang,price of anarchy,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
11598,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",jing zhang,smart cities,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
11599,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",jing zhang,optimization,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
11600,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",sepideh pourazarm,Transportation networks,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
11601,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",sepideh pourazarm,variational inequalities,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
11602,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",sepideh pourazarm,price of anarchy,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
11603,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",sepideh pourazarm,smart cities,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
11604,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",sepideh pourazarm,optimization,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
11605,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
11606,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",christos cassandras,Transportation networks,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
11607,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",christos cassandras,variational inequalities,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
11608,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",christos cassandras,price of anarchy,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
11609,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",christos cassandras,smart cities,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
11610,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",christos cassandras,optimization,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
11611,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",ioannis paschalidis,Transportation networks,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
11612,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",ioannis paschalidis,variational inequalities,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
11613,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",ioannis paschalidis,price of anarchy,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
11614,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",ioannis paschalidis,smart cities,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
11615,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",ioannis paschalidis,optimization,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
11616,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
11617,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ahmed abdulla,Games,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11618,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ahmed abdulla,Signal to noise ratio,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11619,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ahmed abdulla,Modulation,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11620,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ahmed abdulla,Data collection,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11621,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ahmed abdulla,Convergence,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11622,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ahmed abdulla,Bit error rate,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11623,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ahmed abdulla,Game theory,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11624,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",zubair fadlullah,Games,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11625,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",zubair fadlullah,Signal to noise ratio,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11626,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",zubair fadlullah,Modulation,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11627,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
11628,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",zubair fadlullah,Data collection,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11629,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",zubair fadlullah,Convergence,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11630,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",zubair fadlullah,Bit error rate,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11631,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",zubair fadlullah,Game theory,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11632,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",hiroki nishiyama,Games,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11633,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",hiroki nishiyama,Signal to noise ratio,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11634,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",hiroki nishiyama,Modulation,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11635,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",hiroki nishiyama,Data collection,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11636,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",hiroki nishiyama,Convergence,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11637,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",hiroki nishiyama,Bit error rate,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11638,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
11639,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",hiroki nishiyama,Game theory,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11640,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",nei kato,Games,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11641,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",nei kato,Signal to noise ratio,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11642,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",nei kato,Modulation,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11643,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",nei kato,Data collection,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11644,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",nei kato,Convergence,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11645,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",nei kato,Bit error rate,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11646,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",nei kato,Game theory,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11647,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",fumie ono,Games,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11648,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",fumie ono,Signal to noise ratio,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11649,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
11650,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",fumie ono,Modulation,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11651,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",fumie ono,Data collection,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11652,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",fumie ono,Convergence,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11653,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",fumie ono,Bit error rate,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11654,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",fumie ono,Game theory,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11655,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ryu miura,Games,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11656,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ryu miura,Signal to noise ratio,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11657,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ryu miura,Modulation,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11658,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ryu miura,Data collection,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11659,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ryu miura,Convergence,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11660,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11661,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
11662,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ryu miura,Bit error rate,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11663,"Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.",ryu miura,Game theory,2014.0,10.1109/INFOCOM.2014.6848000,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Abdulla2014,False,,IEEE,Not available,An optimal data collection technique for improved utility in UAS-aided networks,5258d0f977add53a26e97d4995db92f1,https://ieeexplore.ieee.org/document/6848000/
11664,"The computation task offloading and resource management in mobile edge computing (MEC) become attractive in recent years. Many algorithms have been proposed to improve the performance of the MEC system. However, the research on power control in MEC systems is just starting. The power control in the single-user and an interference-free multi-user MEC systems has been investigated; but in the interference-aware multi-user MEC systems, this issue has not been learned in detail. Therefore, a game theory-based power control approach for the interference-aware multi-user MEC system is proposed in this paper. In this algorithm, both the interference and the multi-user scenario are considered. Moreover, the existence and uniqueness of the Nash Equilibrium (NE) of this game are proved, and the performance of this algorithm is evaluated via theoretical analysis and numerical simulation. The convergence, the computation complexity and the price of anarchy in terms of the system-wide computation overhead are investigated in detail. The performance of this algorithm has been compared with the traditional localized optimal algorithm by simulation. The simulation results demonstrate that the proposed algorithm has more advantages than the traditional one.",ning li,Edge computing,2018.0,10.1109/ACCESS.2018.2849207,IEEE Access,Li2018,True,,IEEE,Not available,Distributed Power Control for Interference-Aware Multi-User Mobile Edge Computing: A Game Theory Approach,0da1498ec14c37dfa5809040d36376ab,https://ieeexplore.ieee.org/document/8390908/
11665,"The computation task offloading and resource management in mobile edge computing (MEC) become attractive in recent years. Many algorithms have been proposed to improve the performance of the MEC system. However, the research on power control in MEC systems is just starting. The power control in the single-user and an interference-free multi-user MEC systems has been investigated; but in the interference-aware multi-user MEC systems, this issue has not been learned in detail. Therefore, a game theory-based power control approach for the interference-aware multi-user MEC system is proposed in this paper. In this algorithm, both the interference and the multi-user scenario are considered. Moreover, the existence and uniqueness of the Nash Equilibrium (NE) of this game are proved, and the performance of this algorithm is evaluated via theoretical analysis and numerical simulation. The convergence, the computation complexity and the price of anarchy in terms of the system-wide computation overhead are investigated in detail. The performance of this algorithm has been compared with the traditional localized optimal algorithm by simulation. The simulation results demonstrate that the proposed algorithm has more advantages than the traditional one.",ning li,interference,2018.0,10.1109/ACCESS.2018.2849207,IEEE Access,Li2018,True,,IEEE,Not available,Distributed Power Control for Interference-Aware Multi-User Mobile Edge Computing: A Game Theory Approach,0da1498ec14c37dfa5809040d36376ab,https://ieeexplore.ieee.org/document/8390908/
11666,"The computation task offloading and resource management in mobile edge computing (MEC) become attractive in recent years. Many algorithms have been proposed to improve the performance of the MEC system. However, the research on power control in MEC systems is just starting. The power control in the single-user and an interference-free multi-user MEC systems has been investigated; but in the interference-aware multi-user MEC systems, this issue has not been learned in detail. Therefore, a game theory-based power control approach for the interference-aware multi-user MEC system is proposed in this paper. In this algorithm, both the interference and the multi-user scenario are considered. Moreover, the existence and uniqueness of the Nash Equilibrium (NE) of this game are proved, and the performance of this algorithm is evaluated via theoretical analysis and numerical simulation. The convergence, the computation complexity and the price of anarchy in terms of the system-wide computation overhead are investigated in detail. The performance of this algorithm has been compared with the traditional localized optimal algorithm by simulation. The simulation results demonstrate that the proposed algorithm has more advantages than the traditional one.",ning li,multi-user,2018.0,10.1109/ACCESS.2018.2849207,IEEE Access,Li2018,True,,IEEE,Not available,Distributed Power Control for Interference-Aware Multi-User Mobile Edge Computing: A Game Theory Approach,0da1498ec14c37dfa5809040d36376ab,https://ieeexplore.ieee.org/document/8390908/
11667,"The computation task offloading and resource management in mobile edge computing (MEC) become attractive in recent years. Many algorithms have been proposed to improve the performance of the MEC system. However, the research on power control in MEC systems is just starting. The power control in the single-user and an interference-free multi-user MEC systems has been investigated; but in the interference-aware multi-user MEC systems, this issue has not been learned in detail. Therefore, a game theory-based power control approach for the interference-aware multi-user MEC system is proposed in this paper. In this algorithm, both the interference and the multi-user scenario are considered. Moreover, the existence and uniqueness of the Nash Equilibrium (NE) of this game are proved, and the performance of this algorithm is evaluated via theoretical analysis and numerical simulation. The convergence, the computation complexity and the price of anarchy in terms of the system-wide computation overhead are investigated in detail. The performance of this algorithm has been compared with the traditional localized optimal algorithm by simulation. The simulation results demonstrate that the proposed algorithm has more advantages than the traditional one.",ning li,power control,2018.0,10.1109/ACCESS.2018.2849207,IEEE Access,Li2018,True,,IEEE,Not available,Distributed Power Control for Interference-Aware Multi-User Mobile Edge Computing: A Game Theory Approach,0da1498ec14c37dfa5809040d36376ab,https://ieeexplore.ieee.org/document/8390908/
11668,"The computation task offloading and resource management in mobile edge computing (MEC) become attractive in recent years. Many algorithms have been proposed to improve the performance of the MEC system. However, the research on power control in MEC systems is just starting. The power control in the single-user and an interference-free multi-user MEC systems has been investigated; but in the interference-aware multi-user MEC systems, this issue has not been learned in detail. Therefore, a game theory-based power control approach for the interference-aware multi-user MEC system is proposed in this paper. In this algorithm, both the interference and the multi-user scenario are considered. Moreover, the existence and uniqueness of the Nash Equilibrium (NE) of this game are proved, and the performance of this algorithm is evaluated via theoretical analysis and numerical simulation. The convergence, the computation complexity and the price of anarchy in terms of the system-wide computation overhead are investigated in detail. The performance of this algorithm has been compared with the traditional localized optimal algorithm by simulation. The simulation results demonstrate that the proposed algorithm has more advantages than the traditional one.",ning li,game theory,2018.0,10.1109/ACCESS.2018.2849207,IEEE Access,Li2018,True,,IEEE,Not available,Distributed Power Control for Interference-Aware Multi-User Mobile Edge Computing: A Game Theory Approach,0da1498ec14c37dfa5809040d36376ab,https://ieeexplore.ieee.org/document/8390908/
11669,"The computation task offloading and resource management in mobile edge computing (MEC) become attractive in recent years. Many algorithms have been proposed to improve the performance of the MEC system. However, the research on power control in MEC systems is just starting. The power control in the single-user and an interference-free multi-user MEC systems has been investigated; but in the interference-aware multi-user MEC systems, this issue has not been learned in detail. Therefore, a game theory-based power control approach for the interference-aware multi-user MEC system is proposed in this paper. In this algorithm, both the interference and the multi-user scenario are considered. Moreover, the existence and uniqueness of the Nash Equilibrium (NE) of this game are proved, and the performance of this algorithm is evaluated via theoretical analysis and numerical simulation. The convergence, the computation complexity and the price of anarchy in terms of the system-wide computation overhead are investigated in detail. The performance of this algorithm has been compared with the traditional localized optimal algorithm by simulation. The simulation results demonstrate that the proposed algorithm has more advantages than the traditional one.",jose-fernan martinez-ortega,Edge computing,2018.0,10.1109/ACCESS.2018.2849207,IEEE Access,Li2018,True,,IEEE,Not available,Distributed Power Control for Interference-Aware Multi-User Mobile Edge Computing: A Game Theory Approach,0da1498ec14c37dfa5809040d36376ab,https://ieeexplore.ieee.org/document/8390908/
11670,"The computation task offloading and resource management in mobile edge computing (MEC) become attractive in recent years. Many algorithms have been proposed to improve the performance of the MEC system. However, the research on power control in MEC systems is just starting. The power control in the single-user and an interference-free multi-user MEC systems has been investigated; but in the interference-aware multi-user MEC systems, this issue has not been learned in detail. Therefore, a game theory-based power control approach for the interference-aware multi-user MEC system is proposed in this paper. In this algorithm, both the interference and the multi-user scenario are considered. Moreover, the existence and uniqueness of the Nash Equilibrium (NE) of this game are proved, and the performance of this algorithm is evaluated via theoretical analysis and numerical simulation. The convergence, the computation complexity and the price of anarchy in terms of the system-wide computation overhead are investigated in detail. The performance of this algorithm has been compared with the traditional localized optimal algorithm by simulation. The simulation results demonstrate that the proposed algorithm has more advantages than the traditional one.",jose-fernan martinez-ortega,interference,2018.0,10.1109/ACCESS.2018.2849207,IEEE Access,Li2018,True,,IEEE,Not available,Distributed Power Control for Interference-Aware Multi-User Mobile Edge Computing: A Game Theory Approach,0da1498ec14c37dfa5809040d36376ab,https://ieeexplore.ieee.org/document/8390908/
11671,"The computation task offloading and resource management in mobile edge computing (MEC) become attractive in recent years. Many algorithms have been proposed to improve the performance of the MEC system. However, the research on power control in MEC systems is just starting. The power control in the single-user and an interference-free multi-user MEC systems has been investigated; but in the interference-aware multi-user MEC systems, this issue has not been learned in detail. Therefore, a game theory-based power control approach for the interference-aware multi-user MEC system is proposed in this paper. In this algorithm, both the interference and the multi-user scenario are considered. Moreover, the existence and uniqueness of the Nash Equilibrium (NE) of this game are proved, and the performance of this algorithm is evaluated via theoretical analysis and numerical simulation. The convergence, the computation complexity and the price of anarchy in terms of the system-wide computation overhead are investigated in detail. The performance of this algorithm has been compared with the traditional localized optimal algorithm by simulation. The simulation results demonstrate that the proposed algorithm has more advantages than the traditional one.",jose-fernan martinez-ortega,multi-user,2018.0,10.1109/ACCESS.2018.2849207,IEEE Access,Li2018,True,,IEEE,Not available,Distributed Power Control for Interference-Aware Multi-User Mobile Edge Computing: A Game Theory Approach,0da1498ec14c37dfa5809040d36376ab,https://ieeexplore.ieee.org/document/8390908/
11672,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
11673,"The computation task offloading and resource management in mobile edge computing (MEC) become attractive in recent years. Many algorithms have been proposed to improve the performance of the MEC system. However, the research on power control in MEC systems is just starting. The power control in the single-user and an interference-free multi-user MEC systems has been investigated; but in the interference-aware multi-user MEC systems, this issue has not been learned in detail. Therefore, a game theory-based power control approach for the interference-aware multi-user MEC system is proposed in this paper. In this algorithm, both the interference and the multi-user scenario are considered. Moreover, the existence and uniqueness of the Nash Equilibrium (NE) of this game are proved, and the performance of this algorithm is evaluated via theoretical analysis and numerical simulation. The convergence, the computation complexity and the price of anarchy in terms of the system-wide computation overhead are investigated in detail. The performance of this algorithm has been compared with the traditional localized optimal algorithm by simulation. The simulation results demonstrate that the proposed algorithm has more advantages than the traditional one.",jose-fernan martinez-ortega,power control,2018.0,10.1109/ACCESS.2018.2849207,IEEE Access,Li2018,True,,IEEE,Not available,Distributed Power Control for Interference-Aware Multi-User Mobile Edge Computing: A Game Theory Approach,0da1498ec14c37dfa5809040d36376ab,https://ieeexplore.ieee.org/document/8390908/
11674,"The computation task offloading and resource management in mobile edge computing (MEC) become attractive in recent years. Many algorithms have been proposed to improve the performance of the MEC system. However, the research on power control in MEC systems is just starting. The power control in the single-user and an interference-free multi-user MEC systems has been investigated; but in the interference-aware multi-user MEC systems, this issue has not been learned in detail. Therefore, a game theory-based power control approach for the interference-aware multi-user MEC system is proposed in this paper. In this algorithm, both the interference and the multi-user scenario are considered. Moreover, the existence and uniqueness of the Nash Equilibrium (NE) of this game are proved, and the performance of this algorithm is evaluated via theoretical analysis and numerical simulation. The convergence, the computation complexity and the price of anarchy in terms of the system-wide computation overhead are investigated in detail. The performance of this algorithm has been compared with the traditional localized optimal algorithm by simulation. The simulation results demonstrate that the proposed algorithm has more advantages than the traditional one.",jose-fernan martinez-ortega,game theory,2018.0,10.1109/ACCESS.2018.2849207,IEEE Access,Li2018,True,,IEEE,Not available,Distributed Power Control for Interference-Aware Multi-User Mobile Edge Computing: A Game Theory Approach,0da1498ec14c37dfa5809040d36376ab,https://ieeexplore.ieee.org/document/8390908/
11675,"The computation task offloading and resource management in mobile edge computing (MEC) become attractive in recent years. Many algorithms have been proposed to improve the performance of the MEC system. However, the research on power control in MEC systems is just starting. The power control in the single-user and an interference-free multi-user MEC systems has been investigated; but in the interference-aware multi-user MEC systems, this issue has not been learned in detail. Therefore, a game theory-based power control approach for the interference-aware multi-user MEC system is proposed in this paper. In this algorithm, both the interference and the multi-user scenario are considered. Moreover, the existence and uniqueness of the Nash Equilibrium (NE) of this game are proved, and the performance of this algorithm is evaluated via theoretical analysis and numerical simulation. The convergence, the computation complexity and the price of anarchy in terms of the system-wide computation overhead are investigated in detail. The performance of this algorithm has been compared with the traditional localized optimal algorithm by simulation. The simulation results demonstrate that the proposed algorithm has more advantages than the traditional one.",vicente diaz,Edge computing,2018.0,10.1109/ACCESS.2018.2849207,IEEE Access,Li2018,True,,IEEE,Not available,Distributed Power Control for Interference-Aware Multi-User Mobile Edge Computing: A Game Theory Approach,0da1498ec14c37dfa5809040d36376ab,https://ieeexplore.ieee.org/document/8390908/
11676,"The computation task offloading and resource management in mobile edge computing (MEC) become attractive in recent years. Many algorithms have been proposed to improve the performance of the MEC system. However, the research on power control in MEC systems is just starting. The power control in the single-user and an interference-free multi-user MEC systems has been investigated; but in the interference-aware multi-user MEC systems, this issue has not been learned in detail. Therefore, a game theory-based power control approach for the interference-aware multi-user MEC system is proposed in this paper. In this algorithm, both the interference and the multi-user scenario are considered. Moreover, the existence and uniqueness of the Nash Equilibrium (NE) of this game are proved, and the performance of this algorithm is evaluated via theoretical analysis and numerical simulation. The convergence, the computation complexity and the price of anarchy in terms of the system-wide computation overhead are investigated in detail. The performance of this algorithm has been compared with the traditional localized optimal algorithm by simulation. The simulation results demonstrate that the proposed algorithm has more advantages than the traditional one.",vicente diaz,interference,2018.0,10.1109/ACCESS.2018.2849207,IEEE Access,Li2018,True,,IEEE,Not available,Distributed Power Control for Interference-Aware Multi-User Mobile Edge Computing: A Game Theory Approach,0da1498ec14c37dfa5809040d36376ab,https://ieeexplore.ieee.org/document/8390908/
11677,"The computation task offloading and resource management in mobile edge computing (MEC) become attractive in recent years. Many algorithms have been proposed to improve the performance of the MEC system. However, the research on power control in MEC systems is just starting. The power control in the single-user and an interference-free multi-user MEC systems has been investigated; but in the interference-aware multi-user MEC systems, this issue has not been learned in detail. Therefore, a game theory-based power control approach for the interference-aware multi-user MEC system is proposed in this paper. In this algorithm, both the interference and the multi-user scenario are considered. Moreover, the existence and uniqueness of the Nash Equilibrium (NE) of this game are proved, and the performance of this algorithm is evaluated via theoretical analysis and numerical simulation. The convergence, the computation complexity and the price of anarchy in terms of the system-wide computation overhead are investigated in detail. The performance of this algorithm has been compared with the traditional localized optimal algorithm by simulation. The simulation results demonstrate that the proposed algorithm has more advantages than the traditional one.",vicente diaz,multi-user,2018.0,10.1109/ACCESS.2018.2849207,IEEE Access,Li2018,True,,IEEE,Not available,Distributed Power Control for Interference-Aware Multi-User Mobile Edge Computing: A Game Theory Approach,0da1498ec14c37dfa5809040d36376ab,https://ieeexplore.ieee.org/document/8390908/
11678,"The computation task offloading and resource management in mobile edge computing (MEC) become attractive in recent years. Many algorithms have been proposed to improve the performance of the MEC system. However, the research on power control in MEC systems is just starting. The power control in the single-user and an interference-free multi-user MEC systems has been investigated; but in the interference-aware multi-user MEC systems, this issue has not been learned in detail. Therefore, a game theory-based power control approach for the interference-aware multi-user MEC system is proposed in this paper. In this algorithm, both the interference and the multi-user scenario are considered. Moreover, the existence and uniqueness of the Nash Equilibrium (NE) of this game are proved, and the performance of this algorithm is evaluated via theoretical analysis and numerical simulation. The convergence, the computation complexity and the price of anarchy in terms of the system-wide computation overhead are investigated in detail. The performance of this algorithm has been compared with the traditional localized optimal algorithm by simulation. The simulation results demonstrate that the proposed algorithm has more advantages than the traditional one.",vicente diaz,power control,2018.0,10.1109/ACCESS.2018.2849207,IEEE Access,Li2018,True,,IEEE,Not available,Distributed Power Control for Interference-Aware Multi-User Mobile Edge Computing: A Game Theory Approach,0da1498ec14c37dfa5809040d36376ab,https://ieeexplore.ieee.org/document/8390908/
11679,"The computation task offloading and resource management in mobile edge computing (MEC) become attractive in recent years. Many algorithms have been proposed to improve the performance of the MEC system. However, the research on power control in MEC systems is just starting. The power control in the single-user and an interference-free multi-user MEC systems has been investigated; but in the interference-aware multi-user MEC systems, this issue has not been learned in detail. Therefore, a game theory-based power control approach for the interference-aware multi-user MEC system is proposed in this paper. In this algorithm, both the interference and the multi-user scenario are considered. Moreover, the existence and uniqueness of the Nash Equilibrium (NE) of this game are proved, and the performance of this algorithm is evaluated via theoretical analysis and numerical simulation. The convergence, the computation complexity and the price of anarchy in terms of the system-wide computation overhead are investigated in detail. The performance of this algorithm has been compared with the traditional localized optimal algorithm by simulation. The simulation results demonstrate that the proposed algorithm has more advantages than the traditional one.",vicente diaz,game theory,2018.0,10.1109/ACCESS.2018.2849207,IEEE Access,Li2018,True,,IEEE,Not available,Distributed Power Control for Interference-Aware Multi-User Mobile Edge Computing: A Game Theory Approach,0da1498ec14c37dfa5809040d36376ab,https://ieeexplore.ieee.org/document/8390908/
11680,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",ninoslav marina,Relays,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
11681,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",ninoslav marina,Peer to peer computing,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
11682,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",ninoslav marina,Game theory,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
11683,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
11684,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",ninoslav marina,Nash equilibrium,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
11685,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",ninoslav marina,Upper bound,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
11686,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",ninoslav marina,Information analysis,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
11687,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",ninoslav marina,Performance analysis,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
11688,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",ninoslav marina,Wireless networks,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
11689,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",ninoslav marina,Transmitters,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
11690,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",ninoslav marina,Information rates,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
11691,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",are hjorungnes,Relays,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
11692,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",are hjorungnes,Peer to peer computing,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
11693,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",are hjorungnes,Game theory,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
11694,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
11695,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",are hjorungnes,Nash equilibrium,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
11696,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",are hjorungnes,Upper bound,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
11697,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",are hjorungnes,Information analysis,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
11698,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",are hjorungnes,Performance analysis,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
11699,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",are hjorungnes,Wireless networks,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
11700,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",are hjorungnes,Transmitters,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
11701,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",are hjorungnes,Information rates,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
11702,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",paulin jacquot,Smart Grids,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
11703,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",paulin jacquot,Demand Response,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
11704,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",paulin jacquot,Dynamic Pricing,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
11705,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
11706,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",paulin jacquot,Game Theory,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
11707,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",paulin jacquot,Equilibrium,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
11708,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",paulin jacquot,Price of Anarchy,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
11709,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",paulin jacquot,Fairness,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
11710,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",olivier beaude,Smart Grids,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
11711,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",olivier beaude,Demand Response,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
11712,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",olivier beaude,Dynamic Pricing,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
11713,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",olivier beaude,Game Theory,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
11714,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",olivier beaude,Equilibrium,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
11715,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",olivier beaude,Price of Anarchy,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
11716,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
11717,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",olivier beaude,Fairness,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
11718,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",stephane gaubert,Smart Grids,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
11719,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",stephane gaubert,Demand Response,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
11720,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",stephane gaubert,Dynamic Pricing,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
11721,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",stephane gaubert,Game Theory,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
11722,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",stephane gaubert,Equilibrium,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
11723,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",stephane gaubert,Price of Anarchy,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
11724,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",stephane gaubert,Fairness,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
11725,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",nadia oudjane,Smart Grids,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
11726,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",nadia oudjane,Demand Response,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
11727,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
11728,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",nadia oudjane,Dynamic Pricing,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
11729,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",nadia oudjane,Game Theory,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
11730,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",nadia oudjane,Equilibrium,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
11731,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",nadia oudjane,Price of Anarchy,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
11732,"We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each mechanism defines a game where the consumers optimize their flexible consumption to reduce their electricity bills. Mohsenian-Rad et al propose a daily mechanism for which they prove the social optimality. Baharlouei et al propose a hourly billing mechanism for which we give theoretical results: we prove the uniqueness of an equilibrium in the associated game and give an upper bound on its price of anarchy. We evaluate numerically the two mechanisms, using real consumption data from Pecan Street Inc. The simulations show that the equilibrium reached with the hourly mechanism is socially optimal up to 0.1%, and that it achieves an important fairness property according to a quantitative indicator we define. We observe that the two DSM mechanisms avoid the synchronization effect induced by non-game theoretic mechanisms, e.g. Peak/OffPeak hours contracts.",nadia oudjane,Fairness,2017.0,10.1109/ISGTEurope.2017.8260265,2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe),Jacquot2017,False,,IEEE,Not available,Demand side management in the smart grid: An efficiency and fairness tradeoff,75b98d203b2927feb339f0f05263d9dd,https://ieeexplore.ieee.org/document/8260265/
11733,"Malicious softwares or malwares for short have become a major security threat. While originating in criminal behavior, their impact are also influenced by the decisions of legitimate end users. Getting agents in the Internet, and in networks in general, to invest in and deploy security features and protocols is a challenge, in particular because of economic reasons arising from the presence of network externalities. An unexplored direction of this challenge consists in under- standing how to align the incentives of the agents of a large network towards a better security. This paper addresses this new line of research. We start with an economic model for a single agent, that determines the optimal amount to invest in protection. The model takes into account the vulnerability of the agent to a security breach and the potential loss if a security breach occurs. We derive conditions on the quality of the protection to ensure that the optimal amount spent on security is an increasing function of the agent's vulnerability and potential loss. We also show that for a large class of risks, only a small fraction of the expected loss should be invested. Building on these results, we study a network of interconnected agents subject to epidemic risks. We derive conditions to ensure that the incentives of all agents are aligned towards a better security. When agents are strategic, we show that security investments are always socially inefficient due to the network externalities. Moreover if our conditions are not satisfied, incentives can be aligned towards a lower security leading to an equilibrium with a very high price of anarchy.",marc lelarge,Security,2012.0,10.1109/INFCOM.2012.6195715,2012 Proceedings IEEE INFOCOM,Lelarge2012,False,,IEEE,Not available,Coordination in network security games,c9ed006e6eaac3bcd8e33e14c19bdd28,https://ieeexplore.ieee.org/document/6195715/
11734,"Malicious softwares or malwares for short have become a major security threat. While originating in criminal behavior, their impact are also influenced by the decisions of legitimate end users. Getting agents in the Internet, and in networks in general, to invest in and deploy security features and protocols is a challenge, in particular because of economic reasons arising from the presence of network externalities. An unexplored direction of this challenge consists in under- standing how to align the incentives of the agents of a large network towards a better security. This paper addresses this new line of research. We start with an economic model for a single agent, that determines the optimal amount to invest in protection. The model takes into account the vulnerability of the agent to a security breach and the potential loss if a security breach occurs. We derive conditions on the quality of the protection to ensure that the optimal amount spent on security is an increasing function of the agent's vulnerability and potential loss. We also show that for a large class of risks, only a small fraction of the expected loss should be invested. Building on these results, we study a network of interconnected agents subject to epidemic risks. We derive conditions to ensure that the incentives of all agents are aligned towards a better security. When agents are strategic, we show that security investments are always socially inefficient due to the network externalities. Moreover if our conditions are not satisfied, incentives can be aligned towards a lower security leading to an equilibrium with a very high price of anarchy.",marc lelarge,Investments,2012.0,10.1109/INFCOM.2012.6195715,2012 Proceedings IEEE INFOCOM,Lelarge2012,False,,IEEE,Not available,Coordination in network security games,c9ed006e6eaac3bcd8e33e14c19bdd28,https://ieeexplore.ieee.org/document/6195715/
11735,"Malicious softwares or malwares for short have become a major security threat. While originating in criminal behavior, their impact are also influenced by the decisions of legitimate end users. Getting agents in the Internet, and in networks in general, to invest in and deploy security features and protocols is a challenge, in particular because of economic reasons arising from the presence of network externalities. An unexplored direction of this challenge consists in under- standing how to align the incentives of the agents of a large network towards a better security. This paper addresses this new line of research. We start with an economic model for a single agent, that determines the optimal amount to invest in protection. The model takes into account the vulnerability of the agent to a security breach and the potential loss if a security breach occurs. We derive conditions on the quality of the protection to ensure that the optimal amount spent on security is an increasing function of the agent's vulnerability and potential loss. We also show that for a large class of risks, only a small fraction of the expected loss should be invested. Building on these results, we study a network of interconnected agents subject to epidemic risks. We derive conditions to ensure that the incentives of all agents are aligned towards a better security. When agents are strategic, we show that security investments are always socially inefficient due to the network externalities. Moreover if our conditions are not satisfied, incentives can be aligned towards a lower security leading to an equilibrium with a very high price of anarchy.",marc lelarge,Economics,2012.0,10.1109/INFCOM.2012.6195715,2012 Proceedings IEEE INFOCOM,Lelarge2012,False,,IEEE,Not available,Coordination in network security games,c9ed006e6eaac3bcd8e33e14c19bdd28,https://ieeexplore.ieee.org/document/6195715/
11736,"Malicious softwares or malwares for short have become a major security threat. While originating in criminal behavior, their impact are also influenced by the decisions of legitimate end users. Getting agents in the Internet, and in networks in general, to invest in and deploy security features and protocols is a challenge, in particular because of economic reasons arising from the presence of network externalities. An unexplored direction of this challenge consists in under- standing how to align the incentives of the agents of a large network towards a better security. This paper addresses this new line of research. We start with an economic model for a single agent, that determines the optimal amount to invest in protection. The model takes into account the vulnerability of the agent to a security breach and the potential loss if a security breach occurs. We derive conditions on the quality of the protection to ensure that the optimal amount spent on security is an increasing function of the agent's vulnerability and potential loss. We also show that for a large class of risks, only a small fraction of the expected loss should be invested. Building on these results, we study a network of interconnected agents subject to epidemic risks. We derive conditions to ensure that the incentives of all agents are aligned towards a better security. When agents are strategic, we show that security investments are always socially inefficient due to the network externalities. Moreover if our conditions are not satisfied, incentives can be aligned towards a lower security leading to an equilibrium with a very high price of anarchy.",marc lelarge,Games,2012.0,10.1109/INFCOM.2012.6195715,2012 Proceedings IEEE INFOCOM,Lelarge2012,False,,IEEE,Not available,Coordination in network security games,c9ed006e6eaac3bcd8e33e14c19bdd28,https://ieeexplore.ieee.org/document/6195715/
11737,"Malicious softwares or malwares for short have become a major security threat. While originating in criminal behavior, their impact are also influenced by the decisions of legitimate end users. Getting agents in the Internet, and in networks in general, to invest in and deploy security features and protocols is a challenge, in particular because of economic reasons arising from the presence of network externalities. An unexplored direction of this challenge consists in under- standing how to align the incentives of the agents of a large network towards a better security. This paper addresses this new line of research. We start with an economic model for a single agent, that determines the optimal amount to invest in protection. The model takes into account the vulnerability of the agent to a security breach and the potential loss if a security breach occurs. We derive conditions on the quality of the protection to ensure that the optimal amount spent on security is an increasing function of the agent's vulnerability and potential loss. We also show that for a large class of risks, only a small fraction of the expected loss should be invested. Building on these results, we study a network of interconnected agents subject to epidemic risks. We derive conditions to ensure that the incentives of all agents are aligned towards a better security. When agents are strategic, we show that security investments are always socially inefficient due to the network externalities. Moreover if our conditions are not satisfied, incentives can be aligned towards a lower security leading to an equilibrium with a very high price of anarchy.",marc lelarge,Computational modeling,2012.0,10.1109/INFCOM.2012.6195715,2012 Proceedings IEEE INFOCOM,Lelarge2012,False,,IEEE,Not available,Coordination in network security games,c9ed006e6eaac3bcd8e33e14c19bdd28,https://ieeexplore.ieee.org/document/6195715/
11738,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
11739,"Malicious softwares or malwares for short have become a major security threat. While originating in criminal behavior, their impact are also influenced by the decisions of legitimate end users. Getting agents in the Internet, and in networks in general, to invest in and deploy security features and protocols is a challenge, in particular because of economic reasons arising from the presence of network externalities. An unexplored direction of this challenge consists in under- standing how to align the incentives of the agents of a large network towards a better security. This paper addresses this new line of research. We start with an economic model for a single agent, that determines the optimal amount to invest in protection. The model takes into account the vulnerability of the agent to a security breach and the potential loss if a security breach occurs. We derive conditions on the quality of the protection to ensure that the optimal amount spent on security is an increasing function of the agent's vulnerability and potential loss. We also show that for a large class of risks, only a small fraction of the expected loss should be invested. Building on these results, we study a network of interconnected agents subject to epidemic risks. We derive conditions to ensure that the incentives of all agents are aligned towards a better security. When agents are strategic, we show that security investments are always socially inefficient due to the network externalities. Moreover if our conditions are not satisfied, incentives can be aligned towards a lower security leading to an equilibrium with a very high price of anarchy.",marc lelarge,Internet,2012.0,10.1109/INFCOM.2012.6195715,2012 Proceedings IEEE INFOCOM,Lelarge2012,False,,IEEE,Not available,Coordination in network security games,c9ed006e6eaac3bcd8e33e14c19bdd28,https://ieeexplore.ieee.org/document/6195715/
11740,"Malicious softwares or malwares for short have become a major security threat. While originating in criminal behavior, their impact are also influenced by the decisions of legitimate end users. Getting agents in the Internet, and in networks in general, to invest in and deploy security features and protocols is a challenge, in particular because of economic reasons arising from the presence of network externalities. An unexplored direction of this challenge consists in under- standing how to align the incentives of the agents of a large network towards a better security. This paper addresses this new line of research. We start with an economic model for a single agent, that determines the optimal amount to invest in protection. The model takes into account the vulnerability of the agent to a security breach and the potential loss if a security breach occurs. We derive conditions on the quality of the protection to ensure that the optimal amount spent on security is an increasing function of the agent's vulnerability and potential loss. We also show that for a large class of risks, only a small fraction of the expected loss should be invested. Building on these results, we study a network of interconnected agents subject to epidemic risks. We derive conditions to ensure that the incentives of all agents are aligned towards a better security. When agents are strategic, we show that security investments are always socially inefficient due to the network externalities. Moreover if our conditions are not satisfied, incentives can be aligned towards a lower security leading to an equilibrium with a very high price of anarchy.",marc lelarge,Computers,2012.0,10.1109/INFCOM.2012.6195715,2012 Proceedings IEEE INFOCOM,Lelarge2012,False,,IEEE,Not available,Coordination in network security games,c9ed006e6eaac3bcd8e33e14c19bdd28,https://ieeexplore.ieee.org/document/6195715/
11741,"We study a routing game in which one of the players unilaterally acts altruistically by taking into consideration the latency cost of other players as well as his own. By not playing selfishly, a player can not only improve the other players' equilibrium utility but also improve his own equilibrium utility. To quantify the effect, we define a metric called the Value of Unilateral Altruism (VoU) to be the ratio of the equilibrium utility of the altruistic user to the equilibrium utility he would have received in Nash equilibrium if he were selfish. We show by example that the VoU, in a game with nonlinear latency functions and atomic players, can be arbitrarily large. Since the Nash equilibrium social welfare of this example is arbitrarily far from social optimum, this example also has a Price of Anarchy (PoA) that is unbounded. The example is driven by there being a small number of players since the same example with non-atomic players yields a Nash equilibrium that is fully efficient.",amar azad,Games,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Azad2011,False,,IEEE,Not available,Unilateral altruism in network routing games with atomic players,408da6af440414521cc8e1dbab05f8cd,https://ieeexplore.ieee.org/document/6103893/
11742,"We study a routing game in which one of the players unilaterally acts altruistically by taking into consideration the latency cost of other players as well as his own. By not playing selfishly, a player can not only improve the other players' equilibrium utility but also improve his own equilibrium utility. To quantify the effect, we define a metric called the Value of Unilateral Altruism (VoU) to be the ratio of the equilibrium utility of the altruistic user to the equilibrium utility he would have received in Nash equilibrium if he were selfish. We show by example that the VoU, in a game with nonlinear latency functions and atomic players, can be arbitrarily large. Since the Nash equilibrium social welfare of this example is arbitrarily far from social optimum, this example also has a Price of Anarchy (PoA) that is unbounded. The example is driven by there being a small number of players since the same example with non-atomic players yields a Nash equilibrium that is fully efficient.",amar azad,Routing,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Azad2011,False,,IEEE,Not available,Unilateral altruism in network routing games with atomic players,408da6af440414521cc8e1dbab05f8cd,https://ieeexplore.ieee.org/document/6103893/
11743,"We study a routing game in which one of the players unilaterally acts altruistically by taking into consideration the latency cost of other players as well as his own. By not playing selfishly, a player can not only improve the other players' equilibrium utility but also improve his own equilibrium utility. To quantify the effect, we define a metric called the Value of Unilateral Altruism (VoU) to be the ratio of the equilibrium utility of the altruistic user to the equilibrium utility he would have received in Nash equilibrium if he were selfish. We show by example that the VoU, in a game with nonlinear latency functions and atomic players, can be arbitrarily large. Since the Nash equilibrium social welfare of this example is arbitrarily far from social optimum, this example also has a Price of Anarchy (PoA) that is unbounded. The example is driven by there being a small number of players since the same example with non-atomic players yields a Nash equilibrium that is fully efficient.",amar azad,Nash equilibrium,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Azad2011,False,,IEEE,Not available,Unilateral altruism in network routing games with atomic players,408da6af440414521cc8e1dbab05f8cd,https://ieeexplore.ieee.org/document/6103893/
11744,"We study a routing game in which one of the players unilaterally acts altruistically by taking into consideration the latency cost of other players as well as his own. By not playing selfishly, a player can not only improve the other players' equilibrium utility but also improve his own equilibrium utility. To quantify the effect, we define a metric called the Value of Unilateral Altruism (VoU) to be the ratio of the equilibrium utility of the altruistic user to the equilibrium utility he would have received in Nash equilibrium if he were selfish. We show by example that the VoU, in a game with nonlinear latency functions and atomic players, can be arbitrarily large. Since the Nash equilibrium social welfare of this example is arbitrarily far from social optimum, this example also has a Price of Anarchy (PoA) that is unbounded. The example is driven by there being a small number of players since the same example with non-atomic players yields a Nash equilibrium that is fully efficient.",amar azad,Elbow,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Azad2011,False,,IEEE,Not available,Unilateral altruism in network routing games with atomic players,408da6af440414521cc8e1dbab05f8cd,https://ieeexplore.ieee.org/document/6103893/
11745,"We study a routing game in which one of the players unilaterally acts altruistically by taking into consideration the latency cost of other players as well as his own. By not playing selfishly, a player can not only improve the other players' equilibrium utility but also improve his own equilibrium utility. To quantify the effect, we define a metric called the Value of Unilateral Altruism (VoU) to be the ratio of the equilibrium utility of the altruistic user to the equilibrium utility he would have received in Nash equilibrium if he were selfish. We show by example that the VoU, in a game with nonlinear latency functions and atomic players, can be arbitrarily large. Since the Nash equilibrium social welfare of this example is arbitrarily far from social optimum, this example also has a Price of Anarchy (PoA) that is unbounded. The example is driven by there being a small number of players since the same example with non-atomic players yields a Nash equilibrium that is fully efficient.",amar azad,Cost function,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Azad2011,False,,IEEE,Not available,Unilateral altruism in network routing games with atomic players,408da6af440414521cc8e1dbab05f8cd,https://ieeexplore.ieee.org/document/6103893/
11746,"We study a routing game in which one of the players unilaterally acts altruistically by taking into consideration the latency cost of other players as well as his own. By not playing selfishly, a player can not only improve the other players' equilibrium utility but also improve his own equilibrium utility. To quantify the effect, we define a metric called the Value of Unilateral Altruism (VoU) to be the ratio of the equilibrium utility of the altruistic user to the equilibrium utility he would have received in Nash equilibrium if he were selfish. We show by example that the VoU, in a game with nonlinear latency functions and atomic players, can be arbitrarily large. Since the Nash equilibrium social welfare of this example is arbitrarily far from social optimum, this example also has a Price of Anarchy (PoA) that is unbounded. The example is driven by there being a small number of players since the same example with non-atomic players yields a Nash equilibrium that is fully efficient.",amar azad,Delay,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Azad2011,False,,IEEE,Not available,Unilateral altruism in network routing games with atomic players,408da6af440414521cc8e1dbab05f8cd,https://ieeexplore.ieee.org/document/6103893/
11747,"We study a routing game in which one of the players unilaterally acts altruistically by taking into consideration the latency cost of other players as well as his own. By not playing selfishly, a player can not only improve the other players' equilibrium utility but also improve his own equilibrium utility. To quantify the effect, we define a metric called the Value of Unilateral Altruism (VoU) to be the ratio of the equilibrium utility of the altruistic user to the equilibrium utility he would have received in Nash equilibrium if he were selfish. We show by example that the VoU, in a game with nonlinear latency functions and atomic players, can be arbitrarily large. Since the Nash equilibrium social welfare of this example is arbitrarily far from social optimum, this example also has a Price of Anarchy (PoA) that is unbounded. The example is driven by there being a small number of players since the same example with non-atomic players yields a Nash equilibrium that is fully efficient.",amar azad,Vectors,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Azad2011,False,,IEEE,Not available,Unilateral altruism in network routing games with atomic players,408da6af440414521cc8e1dbab05f8cd,https://ieeexplore.ieee.org/document/6103893/
11748,"We study a routing game in which one of the players unilaterally acts altruistically by taking into consideration the latency cost of other players as well as his own. By not playing selfishly, a player can not only improve the other players' equilibrium utility but also improve his own equilibrium utility. To quantify the effect, we define a metric called the Value of Unilateral Altruism (VoU) to be the ratio of the equilibrium utility of the altruistic user to the equilibrium utility he would have received in Nash equilibrium if he were selfish. We show by example that the VoU, in a game with nonlinear latency functions and atomic players, can be arbitrarily large. Since the Nash equilibrium social welfare of this example is arbitrarily far from social optimum, this example also has a Price of Anarchy (PoA) that is unbounded. The example is driven by there being a small number of players since the same example with non-atomic players yields a Nash equilibrium that is fully efficient.",john musacchio,Games,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Azad2011,False,,IEEE,Not available,Unilateral altruism in network routing games with atomic players,408da6af440414521cc8e1dbab05f8cd,https://ieeexplore.ieee.org/document/6103893/
11749,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
11750,"We study a routing game in which one of the players unilaterally acts altruistically by taking into consideration the latency cost of other players as well as his own. By not playing selfishly, a player can not only improve the other players' equilibrium utility but also improve his own equilibrium utility. To quantify the effect, we define a metric called the Value of Unilateral Altruism (VoU) to be the ratio of the equilibrium utility of the altruistic user to the equilibrium utility he would have received in Nash equilibrium if he were selfish. We show by example that the VoU, in a game with nonlinear latency functions and atomic players, can be arbitrarily large. Since the Nash equilibrium social welfare of this example is arbitrarily far from social optimum, this example also has a Price of Anarchy (PoA) that is unbounded. The example is driven by there being a small number of players since the same example with non-atomic players yields a Nash equilibrium that is fully efficient.",john musacchio,Routing,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Azad2011,False,,IEEE,Not available,Unilateral altruism in network routing games with atomic players,408da6af440414521cc8e1dbab05f8cd,https://ieeexplore.ieee.org/document/6103893/
11751,"We study a routing game in which one of the players unilaterally acts altruistically by taking into consideration the latency cost of other players as well as his own. By not playing selfishly, a player can not only improve the other players' equilibrium utility but also improve his own equilibrium utility. To quantify the effect, we define a metric called the Value of Unilateral Altruism (VoU) to be the ratio of the equilibrium utility of the altruistic user to the equilibrium utility he would have received in Nash equilibrium if he were selfish. We show by example that the VoU, in a game with nonlinear latency functions and atomic players, can be arbitrarily large. Since the Nash equilibrium social welfare of this example is arbitrarily far from social optimum, this example also has a Price of Anarchy (PoA) that is unbounded. The example is driven by there being a small number of players since the same example with non-atomic players yields a Nash equilibrium that is fully efficient.",john musacchio,Nash equilibrium,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Azad2011,False,,IEEE,Not available,Unilateral altruism in network routing games with atomic players,408da6af440414521cc8e1dbab05f8cd,https://ieeexplore.ieee.org/document/6103893/
11752,"We study a routing game in which one of the players unilaterally acts altruistically by taking into consideration the latency cost of other players as well as his own. By not playing selfishly, a player can not only improve the other players' equilibrium utility but also improve his own equilibrium utility. To quantify the effect, we define a metric called the Value of Unilateral Altruism (VoU) to be the ratio of the equilibrium utility of the altruistic user to the equilibrium utility he would have received in Nash equilibrium if he were selfish. We show by example that the VoU, in a game with nonlinear latency functions and atomic players, can be arbitrarily large. Since the Nash equilibrium social welfare of this example is arbitrarily far from social optimum, this example also has a Price of Anarchy (PoA) that is unbounded. The example is driven by there being a small number of players since the same example with non-atomic players yields a Nash equilibrium that is fully efficient.",john musacchio,Elbow,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Azad2011,False,,IEEE,Not available,Unilateral altruism in network routing games with atomic players,408da6af440414521cc8e1dbab05f8cd,https://ieeexplore.ieee.org/document/6103893/
11753,"We study a routing game in which one of the players unilaterally acts altruistically by taking into consideration the latency cost of other players as well as his own. By not playing selfishly, a player can not only improve the other players' equilibrium utility but also improve his own equilibrium utility. To quantify the effect, we define a metric called the Value of Unilateral Altruism (VoU) to be the ratio of the equilibrium utility of the altruistic user to the equilibrium utility he would have received in Nash equilibrium if he were selfish. We show by example that the VoU, in a game with nonlinear latency functions and atomic players, can be arbitrarily large. Since the Nash equilibrium social welfare of this example is arbitrarily far from social optimum, this example also has a Price of Anarchy (PoA) that is unbounded. The example is driven by there being a small number of players since the same example with non-atomic players yields a Nash equilibrium that is fully efficient.",john musacchio,Cost function,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Azad2011,False,,IEEE,Not available,Unilateral altruism in network routing games with atomic players,408da6af440414521cc8e1dbab05f8cd,https://ieeexplore.ieee.org/document/6103893/
11754,"We study a routing game in which one of the players unilaterally acts altruistically by taking into consideration the latency cost of other players as well as his own. By not playing selfishly, a player can not only improve the other players' equilibrium utility but also improve his own equilibrium utility. To quantify the effect, we define a metric called the Value of Unilateral Altruism (VoU) to be the ratio of the equilibrium utility of the altruistic user to the equilibrium utility he would have received in Nash equilibrium if he were selfish. We show by example that the VoU, in a game with nonlinear latency functions and atomic players, can be arbitrarily large. Since the Nash equilibrium social welfare of this example is arbitrarily far from social optimum, this example also has a Price of Anarchy (PoA) that is unbounded. The example is driven by there being a small number of players since the same example with non-atomic players yields a Nash equilibrium that is fully efficient.",john musacchio,Delay,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Azad2011,False,,IEEE,Not available,Unilateral altruism in network routing games with atomic players,408da6af440414521cc8e1dbab05f8cd,https://ieeexplore.ieee.org/document/6103893/
11755,"We study a routing game in which one of the players unilaterally acts altruistically by taking into consideration the latency cost of other players as well as his own. By not playing selfishly, a player can not only improve the other players' equilibrium utility but also improve his own equilibrium utility. To quantify the effect, we define a metric called the Value of Unilateral Altruism (VoU) to be the ratio of the equilibrium utility of the altruistic user to the equilibrium utility he would have received in Nash equilibrium if he were selfish. We show by example that the VoU, in a game with nonlinear latency functions and atomic players, can be arbitrarily large. Since the Nash equilibrium social welfare of this example is arbitrarily far from social optimum, this example also has a Price of Anarchy (PoA) that is unbounded. The example is driven by there being a small number of players since the same example with non-atomic players yields a Nash equilibrium that is fully efficient.",john musacchio,Vectors,2011.0,,"International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)",Azad2011,False,,IEEE,Not available,Unilateral altruism in network routing games with atomic players,408da6af440414521cc8e1dbab05f8cd,https://ieeexplore.ieee.org/document/6103893/
11756,"We study the problem of distributing loads in mobile crowdsensing systems (MCS). In this context, we present a multi-commodity network game, more explicitly, an atomic routing game, to depict the linking of several crowd participants into bundles that are capable of successfully completing desired sensing tasks. The nodes of the network correspond to the resources of the crowd participants and the players of our game are sensing service requesters that wish to route their demand along paths trough the network. One resource may serve several requests at the same time, which can be modeled efficiently using the network structure. Resource usage involves load-dependent costs. Our model caters for the uncertainty inherent from crowd involvement and mobility by incorporating certainty parameters in the model. These certainty parameters describe the quality of the partial result a participant can produce. Requesters may set a minimum certainty level for the successful completion of their overall sensing tasks that has to be met. In our model, we analyze four different solution concepts for balancing loads with respect to costs and quality of results: (1) a distributed brute force approach (engaging all suitable crowd participants), (2) a random selection of suitable crowd participants, (3) a Nash equilibrium (as result of decentralized selfish cost-minimizing game play) and (4) a (centralized) social optimum. All considered distributed solutions or an epsilon-approximation of a solution can be computed efficiently (for affine cost functions). Furthermore, well-known results for the price of anarchy of atomic routing games can be transfered to our model, i.e., the relative solution quality of a Nash equilibrium compared to a social optimum is provably bounded. In addition, we provide an extensive experimental study that supports theoretical results and gives further suggestions on the impact of uncertainty. We merge the findings of our analysis into a truthful distributed mechanism such that requesters have no incentive to deviate from an efficient solution.",julia buwaya,Mobile Crowdsensing,2017.0,10.1109/DCOSS.2017.38,2017 13th International Conference on Distributed Computing in Sensor Systems (DCOSS),Buwaya2017,False,,IEEE,Not available,Load Balancing Mechanisms to Regulate Costs and Quality in Mobile Crowdsensing Systems,11b972601a6b3ce3ca5ea42231b95f30,https://ieeexplore.ieee.org/document/8271968/
11757,"We study the problem of distributing loads in mobile crowdsensing systems (MCS). In this context, we present a multi-commodity network game, more explicitly, an atomic routing game, to depict the linking of several crowd participants into bundles that are capable of successfully completing desired sensing tasks. The nodes of the network correspond to the resources of the crowd participants and the players of our game are sensing service requesters that wish to route their demand along paths trough the network. One resource may serve several requests at the same time, which can be modeled efficiently using the network structure. Resource usage involves load-dependent costs. Our model caters for the uncertainty inherent from crowd involvement and mobility by incorporating certainty parameters in the model. These certainty parameters describe the quality of the partial result a participant can produce. Requesters may set a minimum certainty level for the successful completion of their overall sensing tasks that has to be met. In our model, we analyze four different solution concepts for balancing loads with respect to costs and quality of results: (1) a distributed brute force approach (engaging all suitable crowd participants), (2) a random selection of suitable crowd participants, (3) a Nash equilibrium (as result of decentralized selfish cost-minimizing game play) and (4) a (centralized) social optimum. All considered distributed solutions or an epsilon-approximation of a solution can be computed efficiently (for affine cost functions). Furthermore, well-known results for the price of anarchy of atomic routing games can be transfered to our model, i.e., the relative solution quality of a Nash equilibrium compared to a social optimum is provably bounded. In addition, we provide an extensive experimental study that supports theoretical results and gives further suggestions on the impact of uncertainty. We merge the findings of our analysis into a truthful distributed mechanism such that requesters have no incentive to deviate from an efficient solution.",julia buwaya,Load Balance,2017.0,10.1109/DCOSS.2017.38,2017 13th International Conference on Distributed Computing in Sensor Systems (DCOSS),Buwaya2017,False,,IEEE,Not available,Load Balancing Mechanisms to Regulate Costs and Quality in Mobile Crowdsensing Systems,11b972601a6b3ce3ca5ea42231b95f30,https://ieeexplore.ieee.org/document/8271968/
11758,"We study the problem of distributing loads in mobile crowdsensing systems (MCS). In this context, we present a multi-commodity network game, more explicitly, an atomic routing game, to depict the linking of several crowd participants into bundles that are capable of successfully completing desired sensing tasks. The nodes of the network correspond to the resources of the crowd participants and the players of our game are sensing service requesters that wish to route their demand along paths trough the network. One resource may serve several requests at the same time, which can be modeled efficiently using the network structure. Resource usage involves load-dependent costs. Our model caters for the uncertainty inherent from crowd involvement and mobility by incorporating certainty parameters in the model. These certainty parameters describe the quality of the partial result a participant can produce. Requesters may set a minimum certainty level for the successful completion of their overall sensing tasks that has to be met. In our model, we analyze four different solution concepts for balancing loads with respect to costs and quality of results: (1) a distributed brute force approach (engaging all suitable crowd participants), (2) a random selection of suitable crowd participants, (3) a Nash equilibrium (as result of decentralized selfish cost-minimizing game play) and (4) a (centralized) social optimum. All considered distributed solutions or an epsilon-approximation of a solution can be computed efficiently (for affine cost functions). Furthermore, well-known results for the price of anarchy of atomic routing games can be transfered to our model, i.e., the relative solution quality of a Nash equilibrium compared to a social optimum is provably bounded. In addition, we provide an extensive experimental study that supports theoretical results and gives further suggestions on the impact of uncertainty. We merge the findings of our analysis into a truthful distributed mechanism such that requesters have no incentive to deviate from an efficient solution.",julia buwaya,Efficiency,2017.0,10.1109/DCOSS.2017.38,2017 13th International Conference on Distributed Computing in Sensor Systems (DCOSS),Buwaya2017,False,,IEEE,Not available,Load Balancing Mechanisms to Regulate Costs and Quality in Mobile Crowdsensing Systems,11b972601a6b3ce3ca5ea42231b95f30,https://ieeexplore.ieee.org/document/8271968/
11759,"We study the problem of distributing loads in mobile crowdsensing systems (MCS). In this context, we present a multi-commodity network game, more explicitly, an atomic routing game, to depict the linking of several crowd participants into bundles that are capable of successfully completing desired sensing tasks. The nodes of the network correspond to the resources of the crowd participants and the players of our game are sensing service requesters that wish to route their demand along paths trough the network. One resource may serve several requests at the same time, which can be modeled efficiently using the network structure. Resource usage involves load-dependent costs. Our model caters for the uncertainty inherent from crowd involvement and mobility by incorporating certainty parameters in the model. These certainty parameters describe the quality of the partial result a participant can produce. Requesters may set a minimum certainty level for the successful completion of their overall sensing tasks that has to be met. In our model, we analyze four different solution concepts for balancing loads with respect to costs and quality of results: (1) a distributed brute force approach (engaging all suitable crowd participants), (2) a random selection of suitable crowd participants, (3) a Nash equilibrium (as result of decentralized selfish cost-minimizing game play) and (4) a (centralized) social optimum. All considered distributed solutions or an epsilon-approximation of a solution can be computed efficiently (for affine cost functions). Furthermore, well-known results for the price of anarchy of atomic routing games can be transfered to our model, i.e., the relative solution quality of a Nash equilibrium compared to a social optimum is provably bounded. In addition, we provide an extensive experimental study that supports theoretical results and gives further suggestions on the impact of uncertainty. We merge the findings of our analysis into a truthful distributed mechanism such that requesters have no incentive to deviate from an efficient solution.",julia buwaya,Atomic Routing,2017.0,10.1109/DCOSS.2017.38,2017 13th International Conference on Distributed Computing in Sensor Systems (DCOSS),Buwaya2017,False,,IEEE,Not available,Load Balancing Mechanisms to Regulate Costs and Quality in Mobile Crowdsensing Systems,11b972601a6b3ce3ca5ea42231b95f30,https://ieeexplore.ieee.org/document/8271968/
11760,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
11761,"We study the problem of distributing loads in mobile crowdsensing systems (MCS). In this context, we present a multi-commodity network game, more explicitly, an atomic routing game, to depict the linking of several crowd participants into bundles that are capable of successfully completing desired sensing tasks. The nodes of the network correspond to the resources of the crowd participants and the players of our game are sensing service requesters that wish to route their demand along paths trough the network. One resource may serve several requests at the same time, which can be modeled efficiently using the network structure. Resource usage involves load-dependent costs. Our model caters for the uncertainty inherent from crowd involvement and mobility by incorporating certainty parameters in the model. These certainty parameters describe the quality of the partial result a participant can produce. Requesters may set a minimum certainty level for the successful completion of their overall sensing tasks that has to be met. In our model, we analyze four different solution concepts for balancing loads with respect to costs and quality of results: (1) a distributed brute force approach (engaging all suitable crowd participants), (2) a random selection of suitable crowd participants, (3) a Nash equilibrium (as result of decentralized selfish cost-minimizing game play) and (4) a (centralized) social optimum. All considered distributed solutions or an epsilon-approximation of a solution can be computed efficiently (for affine cost functions). Furthermore, well-known results for the price of anarchy of atomic routing games can be transfered to our model, i.e., the relative solution quality of a Nash equilibrium compared to a social optimum is provably bounded. In addition, we provide an extensive experimental study that supports theoretical results and gives further suggestions on the impact of uncertainty. We merge the findings of our analysis into a truthful distributed mechanism such that requesters have no incentive to deviate from an efficient solution.",julia buwaya,Game Theory,2017.0,10.1109/DCOSS.2017.38,2017 13th International Conference on Distributed Computing in Sensor Systems (DCOSS),Buwaya2017,False,,IEEE,Not available,Load Balancing Mechanisms to Regulate Costs and Quality in Mobile Crowdsensing Systems,11b972601a6b3ce3ca5ea42231b95f30,https://ieeexplore.ieee.org/document/8271968/
11762,"We study the problem of distributing loads in mobile crowdsensing systems (MCS). In this context, we present a multi-commodity network game, more explicitly, an atomic routing game, to depict the linking of several crowd participants into bundles that are capable of successfully completing desired sensing tasks. The nodes of the network correspond to the resources of the crowd participants and the players of our game are sensing service requesters that wish to route their demand along paths trough the network. One resource may serve several requests at the same time, which can be modeled efficiently using the network structure. Resource usage involves load-dependent costs. Our model caters for the uncertainty inherent from crowd involvement and mobility by incorporating certainty parameters in the model. These certainty parameters describe the quality of the partial result a participant can produce. Requesters may set a minimum certainty level for the successful completion of their overall sensing tasks that has to be met. In our model, we analyze four different solution concepts for balancing loads with respect to costs and quality of results: (1) a distributed brute force approach (engaging all suitable crowd participants), (2) a random selection of suitable crowd participants, (3) a Nash equilibrium (as result of decentralized selfish cost-minimizing game play) and (4) a (centralized) social optimum. All considered distributed solutions or an epsilon-approximation of a solution can be computed efficiently (for affine cost functions). Furthermore, well-known results for the price of anarchy of atomic routing games can be transfered to our model, i.e., the relative solution quality of a Nash equilibrium compared to a social optimum is provably bounded. In addition, we provide an extensive experimental study that supports theoretical results and gives further suggestions on the impact of uncertainty. We merge the findings of our analysis into a truthful distributed mechanism such that requesters have no incentive to deviate from an efficient solution.",jose rolim,Mobile Crowdsensing,2017.0,10.1109/DCOSS.2017.38,2017 13th International Conference on Distributed Computing in Sensor Systems (DCOSS),Buwaya2017,False,,IEEE,Not available,Load Balancing Mechanisms to Regulate Costs and Quality in Mobile Crowdsensing Systems,11b972601a6b3ce3ca5ea42231b95f30,https://ieeexplore.ieee.org/document/8271968/
11763,"We study the problem of distributing loads in mobile crowdsensing systems (MCS). In this context, we present a multi-commodity network game, more explicitly, an atomic routing game, to depict the linking of several crowd participants into bundles that are capable of successfully completing desired sensing tasks. The nodes of the network correspond to the resources of the crowd participants and the players of our game are sensing service requesters that wish to route their demand along paths trough the network. One resource may serve several requests at the same time, which can be modeled efficiently using the network structure. Resource usage involves load-dependent costs. Our model caters for the uncertainty inherent from crowd involvement and mobility by incorporating certainty parameters in the model. These certainty parameters describe the quality of the partial result a participant can produce. Requesters may set a minimum certainty level for the successful completion of their overall sensing tasks that has to be met. In our model, we analyze four different solution concepts for balancing loads with respect to costs and quality of results: (1) a distributed brute force approach (engaging all suitable crowd participants), (2) a random selection of suitable crowd participants, (3) a Nash equilibrium (as result of decentralized selfish cost-minimizing game play) and (4) a (centralized) social optimum. All considered distributed solutions or an epsilon-approximation of a solution can be computed efficiently (for affine cost functions). Furthermore, well-known results for the price of anarchy of atomic routing games can be transfered to our model, i.e., the relative solution quality of a Nash equilibrium compared to a social optimum is provably bounded. In addition, we provide an extensive experimental study that supports theoretical results and gives further suggestions on the impact of uncertainty. We merge the findings of our analysis into a truthful distributed mechanism such that requesters have no incentive to deviate from an efficient solution.",jose rolim,Load Balance,2017.0,10.1109/DCOSS.2017.38,2017 13th International Conference on Distributed Computing in Sensor Systems (DCOSS),Buwaya2017,False,,IEEE,Not available,Load Balancing Mechanisms to Regulate Costs and Quality in Mobile Crowdsensing Systems,11b972601a6b3ce3ca5ea42231b95f30,https://ieeexplore.ieee.org/document/8271968/
11764,"We study the problem of distributing loads in mobile crowdsensing systems (MCS). In this context, we present a multi-commodity network game, more explicitly, an atomic routing game, to depict the linking of several crowd participants into bundles that are capable of successfully completing desired sensing tasks. The nodes of the network correspond to the resources of the crowd participants and the players of our game are sensing service requesters that wish to route their demand along paths trough the network. One resource may serve several requests at the same time, which can be modeled efficiently using the network structure. Resource usage involves load-dependent costs. Our model caters for the uncertainty inherent from crowd involvement and mobility by incorporating certainty parameters in the model. These certainty parameters describe the quality of the partial result a participant can produce. Requesters may set a minimum certainty level for the successful completion of their overall sensing tasks that has to be met. In our model, we analyze four different solution concepts for balancing loads with respect to costs and quality of results: (1) a distributed brute force approach (engaging all suitable crowd participants), (2) a random selection of suitable crowd participants, (3) a Nash equilibrium (as result of decentralized selfish cost-minimizing game play) and (4) a (centralized) social optimum. All considered distributed solutions or an epsilon-approximation of a solution can be computed efficiently (for affine cost functions). Furthermore, well-known results for the price of anarchy of atomic routing games can be transfered to our model, i.e., the relative solution quality of a Nash equilibrium compared to a social optimum is provably bounded. In addition, we provide an extensive experimental study that supports theoretical results and gives further suggestions on the impact of uncertainty. We merge the findings of our analysis into a truthful distributed mechanism such that requesters have no incentive to deviate from an efficient solution.",jose rolim,Efficiency,2017.0,10.1109/DCOSS.2017.38,2017 13th International Conference on Distributed Computing in Sensor Systems (DCOSS),Buwaya2017,False,,IEEE,Not available,Load Balancing Mechanisms to Regulate Costs and Quality in Mobile Crowdsensing Systems,11b972601a6b3ce3ca5ea42231b95f30,https://ieeexplore.ieee.org/document/8271968/
11765,"We study the problem of distributing loads in mobile crowdsensing systems (MCS). In this context, we present a multi-commodity network game, more explicitly, an atomic routing game, to depict the linking of several crowd participants into bundles that are capable of successfully completing desired sensing tasks. The nodes of the network correspond to the resources of the crowd participants and the players of our game are sensing service requesters that wish to route their demand along paths trough the network. One resource may serve several requests at the same time, which can be modeled efficiently using the network structure. Resource usage involves load-dependent costs. Our model caters for the uncertainty inherent from crowd involvement and mobility by incorporating certainty parameters in the model. These certainty parameters describe the quality of the partial result a participant can produce. Requesters may set a minimum certainty level for the successful completion of their overall sensing tasks that has to be met. In our model, we analyze four different solution concepts for balancing loads with respect to costs and quality of results: (1) a distributed brute force approach (engaging all suitable crowd participants), (2) a random selection of suitable crowd participants, (3) a Nash equilibrium (as result of decentralized selfish cost-minimizing game play) and (4) a (centralized) social optimum. All considered distributed solutions or an epsilon-approximation of a solution can be computed efficiently (for affine cost functions). Furthermore, well-known results for the price of anarchy of atomic routing games can be transfered to our model, i.e., the relative solution quality of a Nash equilibrium compared to a social optimum is provably bounded. In addition, we provide an extensive experimental study that supports theoretical results and gives further suggestions on the impact of uncertainty. We merge the findings of our analysis into a truthful distributed mechanism such that requesters have no incentive to deviate from an efficient solution.",jose rolim,Atomic Routing,2017.0,10.1109/DCOSS.2017.38,2017 13th International Conference on Distributed Computing in Sensor Systems (DCOSS),Buwaya2017,False,,IEEE,Not available,Load Balancing Mechanisms to Regulate Costs and Quality in Mobile Crowdsensing Systems,11b972601a6b3ce3ca5ea42231b95f30,https://ieeexplore.ieee.org/document/8271968/
11766,"We study the problem of distributing loads in mobile crowdsensing systems (MCS). In this context, we present a multi-commodity network game, more explicitly, an atomic routing game, to depict the linking of several crowd participants into bundles that are capable of successfully completing desired sensing tasks. The nodes of the network correspond to the resources of the crowd participants and the players of our game are sensing service requesters that wish to route their demand along paths trough the network. One resource may serve several requests at the same time, which can be modeled efficiently using the network structure. Resource usage involves load-dependent costs. Our model caters for the uncertainty inherent from crowd involvement and mobility by incorporating certainty parameters in the model. These certainty parameters describe the quality of the partial result a participant can produce. Requesters may set a minimum certainty level for the successful completion of their overall sensing tasks that has to be met. In our model, we analyze four different solution concepts for balancing loads with respect to costs and quality of results: (1) a distributed brute force approach (engaging all suitable crowd participants), (2) a random selection of suitable crowd participants, (3) a Nash equilibrium (as result of decentralized selfish cost-minimizing game play) and (4) a (centralized) social optimum. All considered distributed solutions or an epsilon-approximation of a solution can be computed efficiently (for affine cost functions). Furthermore, well-known results for the price of anarchy of atomic routing games can be transfered to our model, i.e., the relative solution quality of a Nash equilibrium compared to a social optimum is provably bounded. In addition, we provide an extensive experimental study that supports theoretical results and gives further suggestions on the impact of uncertainty. We merge the findings of our analysis into a truthful distributed mechanism such that requesters have no incentive to deviate from an efficient solution.",jose rolim,Game Theory,2017.0,10.1109/DCOSS.2017.38,2017 13th International Conference on Distributed Computing in Sensor Systems (DCOSS),Buwaya2017,False,,IEEE,Not available,Load Balancing Mechanisms to Regulate Costs and Quality in Mobile Crowdsensing Systems,11b972601a6b3ce3ca5ea42231b95f30,https://ieeexplore.ieee.org/document/8271968/
11767,"Game-theoretic modeling and equilibrium analysis have provided valuable insights into the design of robust local control rules for the individual agents in multi-agent systems, e.g., Internet congestion control, road transportation networks, etc. In this paper, we introduce a non-cooperative MAC (Medium Access Control) game for wireless networks and propose new fully-distributed CSMA (Carrier Sense Multiple Access) learning algorithms that are probably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing a novel cost function in agents' utilities so that the proposed game admits an ordinal potential function with (asymptotically) no price-of-anarchy. The game formulation naturally leads to known game-based learning rules to find a Nash equilibrium, but they are computationally inefficient and often require global information. Towards our goal of fully-distributed operation, we propose new fully-distributed learning algorithms by utilizing a unique property of CSMA that enables each link to estimate its temporary link throughput without message passing for the applied CSMA parameters. The proposed algorithms can be thought as `stochastic approximations' to the standard learning rules, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, which is a utility-optimal point, numerically evaluate their performance to support our theoretical findings and further examine various features such as convergence speed and its tradeoff with efficiency.",hyeryung jang,Games,2014.0,10.1109/INFOCOM.2014.6847949,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Jang2014,False,,IEEE,Not available,Distributed learning for utility maximization over CSMA-based wireless multihop networks,233be39224ef26dcced4cb48190d398a,https://ieeexplore.ieee.org/document/6847949/
11768,"Game-theoretic modeling and equilibrium analysis have provided valuable insights into the design of robust local control rules for the individual agents in multi-agent systems, e.g., Internet congestion control, road transportation networks, etc. In this paper, we introduce a non-cooperative MAC (Medium Access Control) game for wireless networks and propose new fully-distributed CSMA (Carrier Sense Multiple Access) learning algorithms that are probably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing a novel cost function in agents' utilities so that the proposed game admits an ordinal potential function with (asymptotically) no price-of-anarchy. The game formulation naturally leads to known game-based learning rules to find a Nash equilibrium, but they are computationally inefficient and often require global information. Towards our goal of fully-distributed operation, we propose new fully-distributed learning algorithms by utilizing a unique property of CSMA that enables each link to estimate its temporary link throughput without message passing for the applied CSMA parameters. The proposed algorithms can be thought as `stochastic approximations' to the standard learning rules, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, which is a utility-optimal point, numerically evaluate their performance to support our theoretical findings and further examine various features such as convergence speed and its tradeoff with efficiency.",hyeryung jang,Throughput,2014.0,10.1109/INFOCOM.2014.6847949,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Jang2014,False,,IEEE,Not available,Distributed learning for utility maximization over CSMA-based wireless multihop networks,233be39224ef26dcced4cb48190d398a,https://ieeexplore.ieee.org/document/6847949/
11769,"Game-theoretic modeling and equilibrium analysis have provided valuable insights into the design of robust local control rules for the individual agents in multi-agent systems, e.g., Internet congestion control, road transportation networks, etc. In this paper, we introduce a non-cooperative MAC (Medium Access Control) game for wireless networks and propose new fully-distributed CSMA (Carrier Sense Multiple Access) learning algorithms that are probably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing a novel cost function in agents' utilities so that the proposed game admits an ordinal potential function with (asymptotically) no price-of-anarchy. The game formulation naturally leads to known game-based learning rules to find a Nash equilibrium, but they are computationally inefficient and often require global information. Towards our goal of fully-distributed operation, we propose new fully-distributed learning algorithms by utilizing a unique property of CSMA that enables each link to estimate its temporary link throughput without message passing for the applied CSMA parameters. The proposed algorithms can be thought as `stochastic approximations' to the standard learning rules, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, which is a utility-optimal point, numerically evaluate their performance to support our theoretical findings and further examine various features such as convergence speed and its tradeoff with efficiency.",hyeryung jang,Multiaccess communication,2014.0,10.1109/INFOCOM.2014.6847949,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Jang2014,False,,IEEE,Not available,Distributed learning for utility maximization over CSMA-based wireless multihop networks,233be39224ef26dcced4cb48190d398a,https://ieeexplore.ieee.org/document/6847949/
11770,"Game-theoretic modeling and equilibrium analysis have provided valuable insights into the design of robust local control rules for the individual agents in multi-agent systems, e.g., Internet congestion control, road transportation networks, etc. In this paper, we introduce a non-cooperative MAC (Medium Access Control) game for wireless networks and propose new fully-distributed CSMA (Carrier Sense Multiple Access) learning algorithms that are probably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing a novel cost function in agents' utilities so that the proposed game admits an ordinal potential function with (asymptotically) no price-of-anarchy. The game formulation naturally leads to known game-based learning rules to find a Nash equilibrium, but they are computationally inefficient and often require global information. Towards our goal of fully-distributed operation, we propose new fully-distributed learning algorithms by utilizing a unique property of CSMA that enables each link to estimate its temporary link throughput without message passing for the applied CSMA parameters. The proposed algorithms can be thought as `stochastic approximations' to the standard learning rules, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, which is a utility-optimal point, numerically evaluate their performance to support our theoretical findings and further examine various features such as convergence speed and its tradeoff with efficiency.",hyeryung jang,Heuristic algorithms,2014.0,10.1109/INFOCOM.2014.6847949,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Jang2014,False,,IEEE,Not available,Distributed learning for utility maximization over CSMA-based wireless multihop networks,233be39224ef26dcced4cb48190d398a,https://ieeexplore.ieee.org/document/6847949/
11771,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11772,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
11773,"Game-theoretic modeling and equilibrium analysis have provided valuable insights into the design of robust local control rules for the individual agents in multi-agent systems, e.g., Internet congestion control, road transportation networks, etc. In this paper, we introduce a non-cooperative MAC (Medium Access Control) game for wireless networks and propose new fully-distributed CSMA (Carrier Sense Multiple Access) learning algorithms that are probably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing a novel cost function in agents' utilities so that the proposed game admits an ordinal potential function with (asymptotically) no price-of-anarchy. The game formulation naturally leads to known game-based learning rules to find a Nash equilibrium, but they are computationally inefficient and often require global information. Towards our goal of fully-distributed operation, we propose new fully-distributed learning algorithms by utilizing a unique property of CSMA that enables each link to estimate its temporary link throughput without message passing for the applied CSMA parameters. The proposed algorithms can be thought as `stochastic approximations' to the standard learning rules, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, which is a utility-optimal point, numerically evaluate their performance to support our theoretical findings and further examine various features such as convergence speed and its tradeoff with efficiency.",hyeryung jang,Schedules,2014.0,10.1109/INFOCOM.2014.6847949,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Jang2014,False,,IEEE,Not available,Distributed learning for utility maximization over CSMA-based wireless multihop networks,233be39224ef26dcced4cb48190d398a,https://ieeexplore.ieee.org/document/6847949/
11774,"Game-theoretic modeling and equilibrium analysis have provided valuable insights into the design of robust local control rules for the individual agents in multi-agent systems, e.g., Internet congestion control, road transportation networks, etc. In this paper, we introduce a non-cooperative MAC (Medium Access Control) game for wireless networks and propose new fully-distributed CSMA (Carrier Sense Multiple Access) learning algorithms that are probably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing a novel cost function in agents' utilities so that the proposed game admits an ordinal potential function with (asymptotically) no price-of-anarchy. The game formulation naturally leads to known game-based learning rules to find a Nash equilibrium, but they are computationally inefficient and often require global information. Towards our goal of fully-distributed operation, we propose new fully-distributed learning algorithms by utilizing a unique property of CSMA that enables each link to estimate its temporary link throughput without message passing for the applied CSMA parameters. The proposed algorithms can be thought as `stochastic approximations' to the standard learning rules, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, which is a utility-optimal point, numerically evaluate their performance to support our theoretical findings and further examine various features such as convergence speed and its tradeoff with efficiency.",hyeryung jang,Message passing,2014.0,10.1109/INFOCOM.2014.6847949,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Jang2014,False,,IEEE,Not available,Distributed learning for utility maximization over CSMA-based wireless multihop networks,233be39224ef26dcced4cb48190d398a,https://ieeexplore.ieee.org/document/6847949/
11775,"Game-theoretic modeling and equilibrium analysis have provided valuable insights into the design of robust local control rules for the individual agents in multi-agent systems, e.g., Internet congestion control, road transportation networks, etc. In this paper, we introduce a non-cooperative MAC (Medium Access Control) game for wireless networks and propose new fully-distributed CSMA (Carrier Sense Multiple Access) learning algorithms that are probably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing a novel cost function in agents' utilities so that the proposed game admits an ordinal potential function with (asymptotically) no price-of-anarchy. The game formulation naturally leads to known game-based learning rules to find a Nash equilibrium, but they are computationally inefficient and often require global information. Towards our goal of fully-distributed operation, we propose new fully-distributed learning algorithms by utilizing a unique property of CSMA that enables each link to estimate its temporary link throughput without message passing for the applied CSMA parameters. The proposed algorithms can be thought as `stochastic approximations' to the standard learning rules, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, which is a utility-optimal point, numerically evaluate their performance to support our theoretical findings and further examine various features such as convergence speed and its tradeoff with efficiency.",hyeryung jang,Interference,2014.0,10.1109/INFOCOM.2014.6847949,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Jang2014,False,,IEEE,Not available,Distributed learning for utility maximization over CSMA-based wireless multihop networks,233be39224ef26dcced4cb48190d398a,https://ieeexplore.ieee.org/document/6847949/
11776,"Game-theoretic modeling and equilibrium analysis have provided valuable insights into the design of robust local control rules for the individual agents in multi-agent systems, e.g., Internet congestion control, road transportation networks, etc. In this paper, we introduce a non-cooperative MAC (Medium Access Control) game for wireless networks and propose new fully-distributed CSMA (Carrier Sense Multiple Access) learning algorithms that are probably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing a novel cost function in agents' utilities so that the proposed game admits an ordinal potential function with (asymptotically) no price-of-anarchy. The game formulation naturally leads to known game-based learning rules to find a Nash equilibrium, but they are computationally inefficient and often require global information. Towards our goal of fully-distributed operation, we propose new fully-distributed learning algorithms by utilizing a unique property of CSMA that enables each link to estimate its temporary link throughput without message passing for the applied CSMA parameters. The proposed algorithms can be thought as `stochastic approximations' to the standard learning rules, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, which is a utility-optimal point, numerically evaluate their performance to support our theoretical findings and further examine various features such as convergence speed and its tradeoff with efficiency.",se-young yun,Games,2014.0,10.1109/INFOCOM.2014.6847949,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Jang2014,False,,IEEE,Not available,Distributed learning for utility maximization over CSMA-based wireless multihop networks,233be39224ef26dcced4cb48190d398a,https://ieeexplore.ieee.org/document/6847949/
11777,"Game-theoretic modeling and equilibrium analysis have provided valuable insights into the design of robust local control rules for the individual agents in multi-agent systems, e.g., Internet congestion control, road transportation networks, etc. In this paper, we introduce a non-cooperative MAC (Medium Access Control) game for wireless networks and propose new fully-distributed CSMA (Carrier Sense Multiple Access) learning algorithms that are probably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing a novel cost function in agents' utilities so that the proposed game admits an ordinal potential function with (asymptotically) no price-of-anarchy. The game formulation naturally leads to known game-based learning rules to find a Nash equilibrium, but they are computationally inefficient and often require global information. Towards our goal of fully-distributed operation, we propose new fully-distributed learning algorithms by utilizing a unique property of CSMA that enables each link to estimate its temporary link throughput without message passing for the applied CSMA parameters. The proposed algorithms can be thought as `stochastic approximations' to the standard learning rules, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, which is a utility-optimal point, numerically evaluate their performance to support our theoretical findings and further examine various features such as convergence speed and its tradeoff with efficiency.",se-young yun,Throughput,2014.0,10.1109/INFOCOM.2014.6847949,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Jang2014,False,,IEEE,Not available,Distributed learning for utility maximization over CSMA-based wireless multihop networks,233be39224ef26dcced4cb48190d398a,https://ieeexplore.ieee.org/document/6847949/
11778,"Game-theoretic modeling and equilibrium analysis have provided valuable insights into the design of robust local control rules for the individual agents in multi-agent systems, e.g., Internet congestion control, road transportation networks, etc. In this paper, we introduce a non-cooperative MAC (Medium Access Control) game for wireless networks and propose new fully-distributed CSMA (Carrier Sense Multiple Access) learning algorithms that are probably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing a novel cost function in agents' utilities so that the proposed game admits an ordinal potential function with (asymptotically) no price-of-anarchy. The game formulation naturally leads to known game-based learning rules to find a Nash equilibrium, but they are computationally inefficient and often require global information. Towards our goal of fully-distributed operation, we propose new fully-distributed learning algorithms by utilizing a unique property of CSMA that enables each link to estimate its temporary link throughput without message passing for the applied CSMA parameters. The proposed algorithms can be thought as `stochastic approximations' to the standard learning rules, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, which is a utility-optimal point, numerically evaluate their performance to support our theoretical findings and further examine various features such as convergence speed and its tradeoff with efficiency.",se-young yun,Multiaccess communication,2014.0,10.1109/INFOCOM.2014.6847949,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Jang2014,False,,IEEE,Not available,Distributed learning for utility maximization over CSMA-based wireless multihop networks,233be39224ef26dcced4cb48190d398a,https://ieeexplore.ieee.org/document/6847949/
11779,"Game-theoretic modeling and equilibrium analysis have provided valuable insights into the design of robust local control rules for the individual agents in multi-agent systems, e.g., Internet congestion control, road transportation networks, etc. In this paper, we introduce a non-cooperative MAC (Medium Access Control) game for wireless networks and propose new fully-distributed CSMA (Carrier Sense Multiple Access) learning algorithms that are probably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing a novel cost function in agents' utilities so that the proposed game admits an ordinal potential function with (asymptotically) no price-of-anarchy. The game formulation naturally leads to known game-based learning rules to find a Nash equilibrium, but they are computationally inefficient and often require global information. Towards our goal of fully-distributed operation, we propose new fully-distributed learning algorithms by utilizing a unique property of CSMA that enables each link to estimate its temporary link throughput without message passing for the applied CSMA parameters. The proposed algorithms can be thought as `stochastic approximations' to the standard learning rules, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, which is a utility-optimal point, numerically evaluate their performance to support our theoretical findings and further examine various features such as convergence speed and its tradeoff with efficiency.",se-young yun,Heuristic algorithms,2014.0,10.1109/INFOCOM.2014.6847949,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Jang2014,False,,IEEE,Not available,Distributed learning for utility maximization over CSMA-based wireless multihop networks,233be39224ef26dcced4cb48190d398a,https://ieeexplore.ieee.org/document/6847949/
11780,"Game-theoretic modeling and equilibrium analysis have provided valuable insights into the design of robust local control rules for the individual agents in multi-agent systems, e.g., Internet congestion control, road transportation networks, etc. In this paper, we introduce a non-cooperative MAC (Medium Access Control) game for wireless networks and propose new fully-distributed CSMA (Carrier Sense Multiple Access) learning algorithms that are probably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing a novel cost function in agents' utilities so that the proposed game admits an ordinal potential function with (asymptotically) no price-of-anarchy. The game formulation naturally leads to known game-based learning rules to find a Nash equilibrium, but they are computationally inefficient and often require global information. Towards our goal of fully-distributed operation, we propose new fully-distributed learning algorithms by utilizing a unique property of CSMA that enables each link to estimate its temporary link throughput without message passing for the applied CSMA parameters. The proposed algorithms can be thought as `stochastic approximations' to the standard learning rules, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, which is a utility-optimal point, numerically evaluate their performance to support our theoretical findings and further examine various features such as convergence speed and its tradeoff with efficiency.",se-young yun,Schedules,2014.0,10.1109/INFOCOM.2014.6847949,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Jang2014,False,,IEEE,Not available,Distributed learning for utility maximization over CSMA-based wireless multihop networks,233be39224ef26dcced4cb48190d398a,https://ieeexplore.ieee.org/document/6847949/
11781,"Game-theoretic modeling and equilibrium analysis have provided valuable insights into the design of robust local control rules for the individual agents in multi-agent systems, e.g., Internet congestion control, road transportation networks, etc. In this paper, we introduce a non-cooperative MAC (Medium Access Control) game for wireless networks and propose new fully-distributed CSMA (Carrier Sense Multiple Access) learning algorithms that are probably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing a novel cost function in agents' utilities so that the proposed game admits an ordinal potential function with (asymptotically) no price-of-anarchy. The game formulation naturally leads to known game-based learning rules to find a Nash equilibrium, but they are computationally inefficient and often require global information. Towards our goal of fully-distributed operation, we propose new fully-distributed learning algorithms by utilizing a unique property of CSMA that enables each link to estimate its temporary link throughput without message passing for the applied CSMA parameters. The proposed algorithms can be thought as `stochastic approximations' to the standard learning rules, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, which is a utility-optimal point, numerically evaluate their performance to support our theoretical findings and further examine various features such as convergence speed and its tradeoff with efficiency.",se-young yun,Message passing,2014.0,10.1109/INFOCOM.2014.6847949,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Jang2014,False,,IEEE,Not available,Distributed learning for utility maximization over CSMA-based wireless multihop networks,233be39224ef26dcced4cb48190d398a,https://ieeexplore.ieee.org/document/6847949/
11782,"Game-theoretic modeling and equilibrium analysis have provided valuable insights into the design of robust local control rules for the individual agents in multi-agent systems, e.g., Internet congestion control, road transportation networks, etc. In this paper, we introduce a non-cooperative MAC (Medium Access Control) game for wireless networks and propose new fully-distributed CSMA (Carrier Sense Multiple Access) learning algorithms that are probably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing a novel cost function in agents' utilities so that the proposed game admits an ordinal potential function with (asymptotically) no price-of-anarchy. The game formulation naturally leads to known game-based learning rules to find a Nash equilibrium, but they are computationally inefficient and often require global information. Towards our goal of fully-distributed operation, we propose new fully-distributed learning algorithms by utilizing a unique property of CSMA that enables each link to estimate its temporary link throughput without message passing for the applied CSMA parameters. The proposed algorithms can be thought as `stochastic approximations' to the standard learning rules, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, which is a utility-optimal point, numerically evaluate their performance to support our theoretical findings and further examine various features such as convergence speed and its tradeoff with efficiency.",se-young yun,Interference,2014.0,10.1109/INFOCOM.2014.6847949,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Jang2014,False,,IEEE,Not available,Distributed learning for utility maximization over CSMA-based wireless multihop networks,233be39224ef26dcced4cb48190d398a,https://ieeexplore.ieee.org/document/6847949/
11783,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
11784,"Game-theoretic modeling and equilibrium analysis have provided valuable insights into the design of robust local control rules for the individual agents in multi-agent systems, e.g., Internet congestion control, road transportation networks, etc. In this paper, we introduce a non-cooperative MAC (Medium Access Control) game for wireless networks and propose new fully-distributed CSMA (Carrier Sense Multiple Access) learning algorithms that are probably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing a novel cost function in agents' utilities so that the proposed game admits an ordinal potential function with (asymptotically) no price-of-anarchy. The game formulation naturally leads to known game-based learning rules to find a Nash equilibrium, but they are computationally inefficient and often require global information. Towards our goal of fully-distributed operation, we propose new fully-distributed learning algorithms by utilizing a unique property of CSMA that enables each link to estimate its temporary link throughput without message passing for the applied CSMA parameters. The proposed algorithms can be thought as `stochastic approximations' to the standard learning rules, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, which is a utility-optimal point, numerically evaluate their performance to support our theoretical findings and further examine various features such as convergence speed and its tradeoff with efficiency.",jinwoo shin,Games,2014.0,10.1109/INFOCOM.2014.6847949,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Jang2014,False,,IEEE,Not available,Distributed learning for utility maximization over CSMA-based wireless multihop networks,233be39224ef26dcced4cb48190d398a,https://ieeexplore.ieee.org/document/6847949/
11785,"Game-theoretic modeling and equilibrium analysis have provided valuable insights into the design of robust local control rules for the individual agents in multi-agent systems, e.g., Internet congestion control, road transportation networks, etc. In this paper, we introduce a non-cooperative MAC (Medium Access Control) game for wireless networks and propose new fully-distributed CSMA (Carrier Sense Multiple Access) learning algorithms that are probably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing a novel cost function in agents' utilities so that the proposed game admits an ordinal potential function with (asymptotically) no price-of-anarchy. The game formulation naturally leads to known game-based learning rules to find a Nash equilibrium, but they are computationally inefficient and often require global information. Towards our goal of fully-distributed operation, we propose new fully-distributed learning algorithms by utilizing a unique property of CSMA that enables each link to estimate its temporary link throughput without message passing for the applied CSMA parameters. The proposed algorithms can be thought as `stochastic approximations' to the standard learning rules, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, which is a utility-optimal point, numerically evaluate their performance to support our theoretical findings and further examine various features such as convergence speed and its tradeoff with efficiency.",jinwoo shin,Throughput,2014.0,10.1109/INFOCOM.2014.6847949,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Jang2014,False,,IEEE,Not available,Distributed learning for utility maximization over CSMA-based wireless multihop networks,233be39224ef26dcced4cb48190d398a,https://ieeexplore.ieee.org/document/6847949/
11786,"Game-theoretic modeling and equilibrium analysis have provided valuable insights into the design of robust local control rules for the individual agents in multi-agent systems, e.g., Internet congestion control, road transportation networks, etc. In this paper, we introduce a non-cooperative MAC (Medium Access Control) game for wireless networks and propose new fully-distributed CSMA (Carrier Sense Multiple Access) learning algorithms that are probably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing a novel cost function in agents' utilities so that the proposed game admits an ordinal potential function with (asymptotically) no price-of-anarchy. The game formulation naturally leads to known game-based learning rules to find a Nash equilibrium, but they are computationally inefficient and often require global information. Towards our goal of fully-distributed operation, we propose new fully-distributed learning algorithms by utilizing a unique property of CSMA that enables each link to estimate its temporary link throughput without message passing for the applied CSMA parameters. The proposed algorithms can be thought as `stochastic approximations' to the standard learning rules, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, which is a utility-optimal point, numerically evaluate their performance to support our theoretical findings and further examine various features such as convergence speed and its tradeoff with efficiency.",jinwoo shin,Multiaccess communication,2014.0,10.1109/INFOCOM.2014.6847949,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Jang2014,False,,IEEE,Not available,Distributed learning for utility maximization over CSMA-based wireless multihop networks,233be39224ef26dcced4cb48190d398a,https://ieeexplore.ieee.org/document/6847949/
11787,"Game-theoretic modeling and equilibrium analysis have provided valuable insights into the design of robust local control rules for the individual agents in multi-agent systems, e.g., Internet congestion control, road transportation networks, etc. In this paper, we introduce a non-cooperative MAC (Medium Access Control) game for wireless networks and propose new fully-distributed CSMA (Carrier Sense Multiple Access) learning algorithms that are probably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing a novel cost function in agents' utilities so that the proposed game admits an ordinal potential function with (asymptotically) no price-of-anarchy. The game formulation naturally leads to known game-based learning rules to find a Nash equilibrium, but they are computationally inefficient and often require global information. Towards our goal of fully-distributed operation, we propose new fully-distributed learning algorithms by utilizing a unique property of CSMA that enables each link to estimate its temporary link throughput without message passing for the applied CSMA parameters. The proposed algorithms can be thought as `stochastic approximations' to the standard learning rules, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, which is a utility-optimal point, numerically evaluate their performance to support our theoretical findings and further examine various features such as convergence speed and its tradeoff with efficiency.",jinwoo shin,Heuristic algorithms,2014.0,10.1109/INFOCOM.2014.6847949,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Jang2014,False,,IEEE,Not available,Distributed learning for utility maximization over CSMA-based wireless multihop networks,233be39224ef26dcced4cb48190d398a,https://ieeexplore.ieee.org/document/6847949/
11788,"Game-theoretic modeling and equilibrium analysis have provided valuable insights into the design of robust local control rules for the individual agents in multi-agent systems, e.g., Internet congestion control, road transportation networks, etc. In this paper, we introduce a non-cooperative MAC (Medium Access Control) game for wireless networks and propose new fully-distributed CSMA (Carrier Sense Multiple Access) learning algorithms that are probably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing a novel cost function in agents' utilities so that the proposed game admits an ordinal potential function with (asymptotically) no price-of-anarchy. The game formulation naturally leads to known game-based learning rules to find a Nash equilibrium, but they are computationally inefficient and often require global information. Towards our goal of fully-distributed operation, we propose new fully-distributed learning algorithms by utilizing a unique property of CSMA that enables each link to estimate its temporary link throughput without message passing for the applied CSMA parameters. The proposed algorithms can be thought as `stochastic approximations' to the standard learning rules, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, which is a utility-optimal point, numerically evaluate their performance to support our theoretical findings and further examine various features such as convergence speed and its tradeoff with efficiency.",jinwoo shin,Schedules,2014.0,10.1109/INFOCOM.2014.6847949,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Jang2014,False,,IEEE,Not available,Distributed learning for utility maximization over CSMA-based wireless multihop networks,233be39224ef26dcced4cb48190d398a,https://ieeexplore.ieee.org/document/6847949/
11789,"Game-theoretic modeling and equilibrium analysis have provided valuable insights into the design of robust local control rules for the individual agents in multi-agent systems, e.g., Internet congestion control, road transportation networks, etc. In this paper, we introduce a non-cooperative MAC (Medium Access Control) game for wireless networks and propose new fully-distributed CSMA (Carrier Sense Multiple Access) learning algorithms that are probably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing a novel cost function in agents' utilities so that the proposed game admits an ordinal potential function with (asymptotically) no price-of-anarchy. The game formulation naturally leads to known game-based learning rules to find a Nash equilibrium, but they are computationally inefficient and often require global information. Towards our goal of fully-distributed operation, we propose new fully-distributed learning algorithms by utilizing a unique property of CSMA that enables each link to estimate its temporary link throughput without message passing for the applied CSMA parameters. The proposed algorithms can be thought as `stochastic approximations' to the standard learning rules, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, which is a utility-optimal point, numerically evaluate their performance to support our theoretical findings and further examine various features such as convergence speed and its tradeoff with efficiency.",jinwoo shin,Message passing,2014.0,10.1109/INFOCOM.2014.6847949,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Jang2014,False,,IEEE,Not available,Distributed learning for utility maximization over CSMA-based wireless multihop networks,233be39224ef26dcced4cb48190d398a,https://ieeexplore.ieee.org/document/6847949/
11790,"Game-theoretic modeling and equilibrium analysis have provided valuable insights into the design of robust local control rules for the individual agents in multi-agent systems, e.g., Internet congestion control, road transportation networks, etc. In this paper, we introduce a non-cooperative MAC (Medium Access Control) game for wireless networks and propose new fully-distributed CSMA (Carrier Sense Multiple Access) learning algorithms that are probably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing a novel cost function in agents' utilities so that the proposed game admits an ordinal potential function with (asymptotically) no price-of-anarchy. The game formulation naturally leads to known game-based learning rules to find a Nash equilibrium, but they are computationally inefficient and often require global information. Towards our goal of fully-distributed operation, we propose new fully-distributed learning algorithms by utilizing a unique property of CSMA that enables each link to estimate its temporary link throughput without message passing for the applied CSMA parameters. The proposed algorithms can be thought as `stochastic approximations' to the standard learning rules, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, which is a utility-optimal point, numerically evaluate their performance to support our theoretical findings and further examine various features such as convergence speed and its tradeoff with efficiency.",jinwoo shin,Interference,2014.0,10.1109/INFOCOM.2014.6847949,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Jang2014,False,,IEEE,Not available,Distributed learning for utility maximization over CSMA-based wireless multihop networks,233be39224ef26dcced4cb48190d398a,https://ieeexplore.ieee.org/document/6847949/
11791,"Game-theoretic modeling and equilibrium analysis have provided valuable insights into the design of robust local control rules for the individual agents in multi-agent systems, e.g., Internet congestion control, road transportation networks, etc. In this paper, we introduce a non-cooperative MAC (Medium Access Control) game for wireless networks and propose new fully-distributed CSMA (Carrier Sense Multiple Access) learning algorithms that are probably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing a novel cost function in agents' utilities so that the proposed game admits an ordinal potential function with (asymptotically) no price-of-anarchy. The game formulation naturally leads to known game-based learning rules to find a Nash equilibrium, but they are computationally inefficient and often require global information. Towards our goal of fully-distributed operation, we propose new fully-distributed learning algorithms by utilizing a unique property of CSMA that enables each link to estimate its temporary link throughput without message passing for the applied CSMA parameters. The proposed algorithms can be thought as `stochastic approximations' to the standard learning rules, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, which is a utility-optimal point, numerically evaluate their performance to support our theoretical findings and further examine various features such as convergence speed and its tradeoff with efficiency.",yung yi,Games,2014.0,10.1109/INFOCOM.2014.6847949,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Jang2014,False,,IEEE,Not available,Distributed learning for utility maximization over CSMA-based wireless multihop networks,233be39224ef26dcced4cb48190d398a,https://ieeexplore.ieee.org/document/6847949/
11792,"Game-theoretic modeling and equilibrium analysis have provided valuable insights into the design of robust local control rules for the individual agents in multi-agent systems, e.g., Internet congestion control, road transportation networks, etc. In this paper, we introduce a non-cooperative MAC (Medium Access Control) game for wireless networks and propose new fully-distributed CSMA (Carrier Sense Multiple Access) learning algorithms that are probably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing a novel cost function in agents' utilities so that the proposed game admits an ordinal potential function with (asymptotically) no price-of-anarchy. The game formulation naturally leads to known game-based learning rules to find a Nash equilibrium, but they are computationally inefficient and often require global information. Towards our goal of fully-distributed operation, we propose new fully-distributed learning algorithms by utilizing a unique property of CSMA that enables each link to estimate its temporary link throughput without message passing for the applied CSMA parameters. The proposed algorithms can be thought as `stochastic approximations' to the standard learning rules, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, which is a utility-optimal point, numerically evaluate their performance to support our theoretical findings and further examine various features such as convergence speed and its tradeoff with efficiency.",yung yi,Throughput,2014.0,10.1109/INFOCOM.2014.6847949,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Jang2014,False,,IEEE,Not available,Distributed learning for utility maximization over CSMA-based wireless multihop networks,233be39224ef26dcced4cb48190d398a,https://ieeexplore.ieee.org/document/6847949/
11793,"Game-theoretic modeling and equilibrium analysis have provided valuable insights into the design of robust local control rules for the individual agents in multi-agent systems, e.g., Internet congestion control, road transportation networks, etc. In this paper, we introduce a non-cooperative MAC (Medium Access Control) game for wireless networks and propose new fully-distributed CSMA (Carrier Sense Multiple Access) learning algorithms that are probably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing a novel cost function in agents' utilities so that the proposed game admits an ordinal potential function with (asymptotically) no price-of-anarchy. The game formulation naturally leads to known game-based learning rules to find a Nash equilibrium, but they are computationally inefficient and often require global information. Towards our goal of fully-distributed operation, we propose new fully-distributed learning algorithms by utilizing a unique property of CSMA that enables each link to estimate its temporary link throughput without message passing for the applied CSMA parameters. The proposed algorithms can be thought as `stochastic approximations' to the standard learning rules, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, which is a utility-optimal point, numerically evaluate their performance to support our theoretical findings and further examine various features such as convergence speed and its tradeoff with efficiency.",yung yi,Multiaccess communication,2014.0,10.1109/INFOCOM.2014.6847949,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Jang2014,False,,IEEE,Not available,Distributed learning for utility maximization over CSMA-based wireless multihop networks,233be39224ef26dcced4cb48190d398a,https://ieeexplore.ieee.org/document/6847949/
11794,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
11795,"Game-theoretic modeling and equilibrium analysis have provided valuable insights into the design of robust local control rules for the individual agents in multi-agent systems, e.g., Internet congestion control, road transportation networks, etc. In this paper, we introduce a non-cooperative MAC (Medium Access Control) game for wireless networks and propose new fully-distributed CSMA (Carrier Sense Multiple Access) learning algorithms that are probably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing a novel cost function in agents' utilities so that the proposed game admits an ordinal potential function with (asymptotically) no price-of-anarchy. The game formulation naturally leads to known game-based learning rules to find a Nash equilibrium, but they are computationally inefficient and often require global information. Towards our goal of fully-distributed operation, we propose new fully-distributed learning algorithms by utilizing a unique property of CSMA that enables each link to estimate its temporary link throughput without message passing for the applied CSMA parameters. The proposed algorithms can be thought as `stochastic approximations' to the standard learning rules, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, which is a utility-optimal point, numerically evaluate their performance to support our theoretical findings and further examine various features such as convergence speed and its tradeoff with efficiency.",yung yi,Heuristic algorithms,2014.0,10.1109/INFOCOM.2014.6847949,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Jang2014,False,,IEEE,Not available,Distributed learning for utility maximization over CSMA-based wireless multihop networks,233be39224ef26dcced4cb48190d398a,https://ieeexplore.ieee.org/document/6847949/
11796,"Game-theoretic modeling and equilibrium analysis have provided valuable insights into the design of robust local control rules for the individual agents in multi-agent systems, e.g., Internet congestion control, road transportation networks, etc. In this paper, we introduce a non-cooperative MAC (Medium Access Control) game for wireless networks and propose new fully-distributed CSMA (Carrier Sense Multiple Access) learning algorithms that are probably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing a novel cost function in agents' utilities so that the proposed game admits an ordinal potential function with (asymptotically) no price-of-anarchy. The game formulation naturally leads to known game-based learning rules to find a Nash equilibrium, but they are computationally inefficient and often require global information. Towards our goal of fully-distributed operation, we propose new fully-distributed learning algorithms by utilizing a unique property of CSMA that enables each link to estimate its temporary link throughput without message passing for the applied CSMA parameters. The proposed algorithms can be thought as `stochastic approximations' to the standard learning rules, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, which is a utility-optimal point, numerically evaluate their performance to support our theoretical findings and further examine various features such as convergence speed and its tradeoff with efficiency.",yung yi,Schedules,2014.0,10.1109/INFOCOM.2014.6847949,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Jang2014,False,,IEEE,Not available,Distributed learning for utility maximization over CSMA-based wireless multihop networks,233be39224ef26dcced4cb48190d398a,https://ieeexplore.ieee.org/document/6847949/
11797,"Game-theoretic modeling and equilibrium analysis have provided valuable insights into the design of robust local control rules for the individual agents in multi-agent systems, e.g., Internet congestion control, road transportation networks, etc. In this paper, we introduce a non-cooperative MAC (Medium Access Control) game for wireless networks and propose new fully-distributed CSMA (Carrier Sense Multiple Access) learning algorithms that are probably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing a novel cost function in agents' utilities so that the proposed game admits an ordinal potential function with (asymptotically) no price-of-anarchy. The game formulation naturally leads to known game-based learning rules to find a Nash equilibrium, but they are computationally inefficient and often require global information. Towards our goal of fully-distributed operation, we propose new fully-distributed learning algorithms by utilizing a unique property of CSMA that enables each link to estimate its temporary link throughput without message passing for the applied CSMA parameters. The proposed algorithms can be thought as `stochastic approximations' to the standard learning rules, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, which is a utility-optimal point, numerically evaluate their performance to support our theoretical findings and further examine various features such as convergence speed and its tradeoff with efficiency.",yung yi,Message passing,2014.0,10.1109/INFOCOM.2014.6847949,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Jang2014,False,,IEEE,Not available,Distributed learning for utility maximization over CSMA-based wireless multihop networks,233be39224ef26dcced4cb48190d398a,https://ieeexplore.ieee.org/document/6847949/
11798,"Game-theoretic modeling and equilibrium analysis have provided valuable insights into the design of robust local control rules for the individual agents in multi-agent systems, e.g., Internet congestion control, road transportation networks, etc. In this paper, we introduce a non-cooperative MAC (Medium Access Control) game for wireless networks and propose new fully-distributed CSMA (Carrier Sense Multiple Access) learning algorithms that are probably optimal in the sense that their long-term throughputs converge to the optimal solution of a utility maximization problem over the maximum throughput region. The most significant part of our approach lies in introducing a novel cost function in agents' utilities so that the proposed game admits an ordinal potential function with (asymptotically) no price-of-anarchy. The game formulation naturally leads to known game-based learning rules to find a Nash equilibrium, but they are computationally inefficient and often require global information. Towards our goal of fully-distributed operation, we propose new fully-distributed learning algorithms by utilizing a unique property of CSMA that enables each link to estimate its temporary link throughput without message passing for the applied CSMA parameters. The proposed algorithms can be thought as `stochastic approximations' to the standard learning rules, which is a new feature in our work, not prevalent in other traditional game-theoretic approaches. We show that they converge to a Nash equilibrium, which is a utility-optimal point, numerically evaluate their performance to support our theoretical findings and further examine various features such as convergence speed and its tradeoff with efficiency.",yung yi,Interference,2014.0,10.1109/INFOCOM.2014.6847949,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Jang2014,False,,IEEE,Not available,Distributed learning for utility maximization over CSMA-based wireless multihop networks,233be39224ef26dcced4cb48190d398a,https://ieeexplore.ieee.org/document/6847949/
11799,"For many networks (e.g. opinion consensus, cooperative estimation, distributed learning and adaptation etc.) to proliferate and efficiently operate, the participating agents need to collaborate with each other by repeatedly sharing information which is often costly while brings no direct immediate benefit for the agents. In this paper, we develop a systematic framework for designing distributed rating protocols aimed at incentivizing the strategic agents to collaborate with each other by sharing information. The proposed incentive protocols exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments through social reciprocation. Unlike existing rating protocols, the proposed protocol operates in a distributed manner, and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many deployment scenarios adopting the proposed rating protocols achieves full efficiency (i.e. price of anarchy is one) even with strategic agents.",jie xu,Information sharing,2014.0,10.1109/ICASSP.2014.6854648,"2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)",Xu2014,False,,IEEE,Not available,Incentivizing information sharing in networks,6ea4a2183419f38a35a49191e6e622eb,https://ieeexplore.ieee.org/document/6854648/
11800,"For many networks (e.g. opinion consensus, cooperative estimation, distributed learning and adaptation etc.) to proliferate and efficiently operate, the participating agents need to collaborate with each other by repeatedly sharing information which is often costly while brings no direct immediate benefit for the agents. In this paper, we develop a systematic framework for designing distributed rating protocols aimed at incentivizing the strategic agents to collaborate with each other by sharing information. The proposed incentive protocols exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments through social reciprocation. Unlike existing rating protocols, the proposed protocol operates in a distributed manner, and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many deployment scenarios adopting the proposed rating protocols achieves full efficiency (i.e. price of anarchy is one) even with strategic agents.",jie xu,repeated games,2014.0,10.1109/ICASSP.2014.6854648,"2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)",Xu2014,False,,IEEE,Not available,Incentivizing information sharing in networks,6ea4a2183419f38a35a49191e6e622eb,https://ieeexplore.ieee.org/document/6854648/
11801,"For many networks (e.g. opinion consensus, cooperative estimation, distributed learning and adaptation etc.) to proliferate and efficiently operate, the participating agents need to collaborate with each other by repeatedly sharing information which is often costly while brings no direct immediate benefit for the agents. In this paper, we develop a systematic framework for designing distributed rating protocols aimed at incentivizing the strategic agents to collaborate with each other by sharing information. The proposed incentive protocols exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments through social reciprocation. Unlike existing rating protocols, the proposed protocol operates in a distributed manner, and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many deployment scenarios adopting the proposed rating protocols achieves full efficiency (i.e. price of anarchy is one) even with strategic agents.",jie xu,distributed rating protocol,2014.0,10.1109/ICASSP.2014.6854648,"2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)",Xu2014,False,,IEEE,Not available,Incentivizing information sharing in networks,6ea4a2183419f38a35a49191e6e622eb,https://ieeexplore.ieee.org/document/6854648/
11802,"For many networks (e.g. opinion consensus, cooperative estimation, distributed learning and adaptation etc.) to proliferate and efficiently operate, the participating agents need to collaborate with each other by repeatedly sharing information which is often costly while brings no direct immediate benefit for the agents. In this paper, we develop a systematic framework for designing distributed rating protocols aimed at incentivizing the strategic agents to collaborate with each other by sharing information. The proposed incentive protocols exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments through social reciprocation. Unlike existing rating protocols, the proposed protocol operates in a distributed manner, and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many deployment scenarios adopting the proposed rating protocols achieves full efficiency (i.e. price of anarchy is one) even with strategic agents.",yangbo song,Information sharing,2014.0,10.1109/ICASSP.2014.6854648,"2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)",Xu2014,False,,IEEE,Not available,Incentivizing information sharing in networks,6ea4a2183419f38a35a49191e6e622eb,https://ieeexplore.ieee.org/document/6854648/
11803,"For many networks (e.g. opinion consensus, cooperative estimation, distributed learning and adaptation etc.) to proliferate and efficiently operate, the participating agents need to collaborate with each other by repeatedly sharing information which is often costly while brings no direct immediate benefit for the agents. In this paper, we develop a systematic framework for designing distributed rating protocols aimed at incentivizing the strategic agents to collaborate with each other by sharing information. The proposed incentive protocols exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments through social reciprocation. Unlike existing rating protocols, the proposed protocol operates in a distributed manner, and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many deployment scenarios adopting the proposed rating protocols achieves full efficiency (i.e. price of anarchy is one) even with strategic agents.",yangbo song,repeated games,2014.0,10.1109/ICASSP.2014.6854648,"2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)",Xu2014,False,,IEEE,Not available,Incentivizing information sharing in networks,6ea4a2183419f38a35a49191e6e622eb,https://ieeexplore.ieee.org/document/6854648/
11804,"For many networks (e.g. opinion consensus, cooperative estimation, distributed learning and adaptation etc.) to proliferate and efficiently operate, the participating agents need to collaborate with each other by repeatedly sharing information which is often costly while brings no direct immediate benefit for the agents. In this paper, we develop a systematic framework for designing distributed rating protocols aimed at incentivizing the strategic agents to collaborate with each other by sharing information. The proposed incentive protocols exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments through social reciprocation. Unlike existing rating protocols, the proposed protocol operates in a distributed manner, and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many deployment scenarios adopting the proposed rating protocols achieves full efficiency (i.e. price of anarchy is one) even with strategic agents.",yangbo song,distributed rating protocol,2014.0,10.1109/ICASSP.2014.6854648,"2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)",Xu2014,False,,IEEE,Not available,Incentivizing information sharing in networks,6ea4a2183419f38a35a49191e6e622eb,https://ieeexplore.ieee.org/document/6854648/
11805,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
11806,"For many networks (e.g. opinion consensus, cooperative estimation, distributed learning and adaptation etc.) to proliferate and efficiently operate, the participating agents need to collaborate with each other by repeatedly sharing information which is often costly while brings no direct immediate benefit for the agents. In this paper, we develop a systematic framework for designing distributed rating protocols aimed at incentivizing the strategic agents to collaborate with each other by sharing information. The proposed incentive protocols exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments through social reciprocation. Unlike existing rating protocols, the proposed protocol operates in a distributed manner, and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many deployment scenarios adopting the proposed rating protocols achieves full efficiency (i.e. price of anarchy is one) even with strategic agents.",mihaela schaar,Information sharing,2014.0,10.1109/ICASSP.2014.6854648,"2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)",Xu2014,False,,IEEE,Not available,Incentivizing information sharing in networks,6ea4a2183419f38a35a49191e6e622eb,https://ieeexplore.ieee.org/document/6854648/
11807,"For many networks (e.g. opinion consensus, cooperative estimation, distributed learning and adaptation etc.) to proliferate and efficiently operate, the participating agents need to collaborate with each other by repeatedly sharing information which is often costly while brings no direct immediate benefit for the agents. In this paper, we develop a systematic framework for designing distributed rating protocols aimed at incentivizing the strategic agents to collaborate with each other by sharing information. The proposed incentive protocols exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments through social reciprocation. Unlike existing rating protocols, the proposed protocol operates in a distributed manner, and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many deployment scenarios adopting the proposed rating protocols achieves full efficiency (i.e. price of anarchy is one) even with strategic agents.",mihaela schaar,repeated games,2014.0,10.1109/ICASSP.2014.6854648,"2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)",Xu2014,False,,IEEE,Not available,Incentivizing information sharing in networks,6ea4a2183419f38a35a49191e6e622eb,https://ieeexplore.ieee.org/document/6854648/
11808,"For many networks (e.g. opinion consensus, cooperative estimation, distributed learning and adaptation etc.) to proliferate and efficiently operate, the participating agents need to collaborate with each other by repeatedly sharing information which is often costly while brings no direct immediate benefit for the agents. In this paper, we develop a systematic framework for designing distributed rating protocols aimed at incentivizing the strategic agents to collaborate with each other by sharing information. The proposed incentive protocols exploit the ongoing nature of the agents' interactions to assign ratings and through them, determine future rewards and punishments through social reciprocation. Unlike existing rating protocols, the proposed protocol operates in a distributed manner, and takes into consideration the underlying interconnectivity of agents as well as their heterogeneity. We prove that in many deployment scenarios adopting the proposed rating protocols achieves full efficiency (i.e. price of anarchy is one) even with strategic agents.",mihaela schaar,distributed rating protocol,2014.0,10.1109/ICASSP.2014.6854648,"2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)",Xu2014,False,,IEEE,Not available,Incentivizing information sharing in networks,6ea4a2183419f38a35a49191e6e622eb,https://ieeexplore.ieee.org/document/6854648/
11809,"A key feature of wireless communications is the spatial reuse. However, the spatial aspect is not yet well understood for the purpose of designing efficient spectrum sharing mechanisms. In this paper, we propose a framework of spatial spectrum access games on directed interference graphs, which can model quite general interference relationship with spatial reuse in wireless networks. We show that a pure Nash equilibrium exists for the two classes of games: (1) any spatial spectrum access games on directed acyclic graphs, and (2) any games satisfying the congestion property on directed trees and directed forests. Under mild technical conditions, the spatial spectrum access games with random backoff and Aloha channel contention mechanisms on undirected graphs also have a pure Nash equilibrium. We also quantify the price of anarchy of the spatial spectrum access game. We then propose a distributed learning algorithm, which only utilizes users' local observations to adaptively adjust the spectrum access strategies. We show that the distributed learning algorithm can converge to an approximate mixed-strategy Nash equilibrium for any spatial spectrum access games. Numerical results demonstrate that the distributed learning algorithm achieves up to 100 percent performance improvement over a random access algorithm.",xu chen,Distributed spectrum access,2015.0,10.1109/TMC.2014.2326673,IEEE Transactions on Mobile Computing,Chen2015,False,,IEEE,Not available,Spatial Spectrum Access Game,e1fce4da24b515edbba4c86ab8b19095,https://ieeexplore.ieee.org/document/6824206/
11810,"A key feature of wireless communications is the spatial reuse. However, the spatial aspect is not yet well understood for the purpose of designing efficient spectrum sharing mechanisms. In this paper, we propose a framework of spatial spectrum access games on directed interference graphs, which can model quite general interference relationship with spatial reuse in wireless networks. We show that a pure Nash equilibrium exists for the two classes of games: (1) any spatial spectrum access games on directed acyclic graphs, and (2) any games satisfying the congestion property on directed trees and directed forests. Under mild technical conditions, the spatial spectrum access games with random backoff and Aloha channel contention mechanisms on undirected graphs also have a pure Nash equilibrium. We also quantify the price of anarchy of the spatial spectrum access game. We then propose a distributed learning algorithm, which only utilizes users' local observations to adaptively adjust the spectrum access strategies. We show that the distributed learning algorithm can converge to an approximate mixed-strategy Nash equilibrium for any spatial spectrum access games. Numerical results demonstrate that the distributed learning algorithm achieves up to 100 percent performance improvement over a random access algorithm.",xu chen,spatial reuse,2015.0,10.1109/TMC.2014.2326673,IEEE Transactions on Mobile Computing,Chen2015,False,,IEEE,Not available,Spatial Spectrum Access Game,e1fce4da24b515edbba4c86ab8b19095,https://ieeexplore.ieee.org/document/6824206/
11811,"A key feature of wireless communications is the spatial reuse. However, the spatial aspect is not yet well understood for the purpose of designing efficient spectrum sharing mechanisms. In this paper, we propose a framework of spatial spectrum access games on directed interference graphs, which can model quite general interference relationship with spatial reuse in wireless networks. We show that a pure Nash equilibrium exists for the two classes of games: (1) any spatial spectrum access games on directed acyclic graphs, and (2) any games satisfying the congestion property on directed trees and directed forests. Under mild technical conditions, the spatial spectrum access games with random backoff and Aloha channel contention mechanisms on undirected graphs also have a pure Nash equilibrium. We also quantify the price of anarchy of the spatial spectrum access game. We then propose a distributed learning algorithm, which only utilizes users' local observations to adaptively adjust the spectrum access strategies. We show that the distributed learning algorithm can converge to an approximate mixed-strategy Nash equilibrium for any spatial spectrum access games. Numerical results demonstrate that the distributed learning algorithm achieves up to 100 percent performance improvement over a random access algorithm.",xu chen,game theory,2015.0,10.1109/TMC.2014.2326673,IEEE Transactions on Mobile Computing,Chen2015,False,,IEEE,Not available,Spatial Spectrum Access Game,e1fce4da24b515edbba4c86ab8b19095,https://ieeexplore.ieee.org/document/6824206/
11812,"A key feature of wireless communications is the spatial reuse. However, the spatial aspect is not yet well understood for the purpose of designing efficient spectrum sharing mechanisms. In this paper, we propose a framework of spatial spectrum access games on directed interference graphs, which can model quite general interference relationship with spatial reuse in wireless networks. We show that a pure Nash equilibrium exists for the two classes of games: (1) any spatial spectrum access games on directed acyclic graphs, and (2) any games satisfying the congestion property on directed trees and directed forests. Under mild technical conditions, the spatial spectrum access games with random backoff and Aloha channel contention mechanisms on undirected graphs also have a pure Nash equilibrium. We also quantify the price of anarchy of the spatial spectrum access game. We then propose a distributed learning algorithm, which only utilizes users' local observations to adaptively adjust the spectrum access strategies. We show that the distributed learning algorithm can converge to an approximate mixed-strategy Nash equilibrium for any spatial spectrum access games. Numerical results demonstrate that the distributed learning algorithm achieves up to 100 percent performance improvement over a random access algorithm.",xu chen,Nash equilibrium,2015.0,10.1109/TMC.2014.2326673,IEEE Transactions on Mobile Computing,Chen2015,False,,IEEE,Not available,Spatial Spectrum Access Game,e1fce4da24b515edbba4c86ab8b19095,https://ieeexplore.ieee.org/document/6824206/
11813,"A key feature of wireless communications is the spatial reuse. However, the spatial aspect is not yet well understood for the purpose of designing efficient spectrum sharing mechanisms. In this paper, we propose a framework of spatial spectrum access games on directed interference graphs, which can model quite general interference relationship with spatial reuse in wireless networks. We show that a pure Nash equilibrium exists for the two classes of games: (1) any spatial spectrum access games on directed acyclic graphs, and (2) any games satisfying the congestion property on directed trees and directed forests. Under mild technical conditions, the spatial spectrum access games with random backoff and Aloha channel contention mechanisms on undirected graphs also have a pure Nash equilibrium. We also quantify the price of anarchy of the spatial spectrum access game. We then propose a distributed learning algorithm, which only utilizes users' local observations to adaptively adjust the spectrum access strategies. We show that the distributed learning algorithm can converge to an approximate mixed-strategy Nash equilibrium for any spatial spectrum access games. Numerical results demonstrate that the distributed learning algorithm achieves up to 100 percent performance improvement over a random access algorithm.",xu chen,distributed learning,2015.0,10.1109/TMC.2014.2326673,IEEE Transactions on Mobile Computing,Chen2015,False,,IEEE,Not available,Spatial Spectrum Access Game,e1fce4da24b515edbba4c86ab8b19095,https://ieeexplore.ieee.org/document/6824206/
11814,"A key feature of wireless communications is the spatial reuse. However, the spatial aspect is not yet well understood for the purpose of designing efficient spectrum sharing mechanisms. In this paper, we propose a framework of spatial spectrum access games on directed interference graphs, which can model quite general interference relationship with spatial reuse in wireless networks. We show that a pure Nash equilibrium exists for the two classes of games: (1) any spatial spectrum access games on directed acyclic graphs, and (2) any games satisfying the congestion property on directed trees and directed forests. Under mild technical conditions, the spatial spectrum access games with random backoff and Aloha channel contention mechanisms on undirected graphs also have a pure Nash equilibrium. We also quantify the price of anarchy of the spatial spectrum access game. We then propose a distributed learning algorithm, which only utilizes users' local observations to adaptively adjust the spectrum access strategies. We show that the distributed learning algorithm can converge to an approximate mixed-strategy Nash equilibrium for any spatial spectrum access games. Numerical results demonstrate that the distributed learning algorithm achieves up to 100 percent performance improvement over a random access algorithm.",jianwei huang,Distributed spectrum access,2015.0,10.1109/TMC.2014.2326673,IEEE Transactions on Mobile Computing,Chen2015,False,,IEEE,Not available,Spatial Spectrum Access Game,e1fce4da24b515edbba4c86ab8b19095,https://ieeexplore.ieee.org/document/6824206/
11815,"A key feature of wireless communications is the spatial reuse. However, the spatial aspect is not yet well understood for the purpose of designing efficient spectrum sharing mechanisms. In this paper, we propose a framework of spatial spectrum access games on directed interference graphs, which can model quite general interference relationship with spatial reuse in wireless networks. We show that a pure Nash equilibrium exists for the two classes of games: (1) any spatial spectrum access games on directed acyclic graphs, and (2) any games satisfying the congestion property on directed trees and directed forests. Under mild technical conditions, the spatial spectrum access games with random backoff and Aloha channel contention mechanisms on undirected graphs also have a pure Nash equilibrium. We also quantify the price of anarchy of the spatial spectrum access game. We then propose a distributed learning algorithm, which only utilizes users' local observations to adaptively adjust the spectrum access strategies. We show that the distributed learning algorithm can converge to an approximate mixed-strategy Nash equilibrium for any spatial spectrum access games. Numerical results demonstrate that the distributed learning algorithm achieves up to 100 percent performance improvement over a random access algorithm.",jianwei huang,spatial reuse,2015.0,10.1109/TMC.2014.2326673,IEEE Transactions on Mobile Computing,Chen2015,False,,IEEE,Not available,Spatial Spectrum Access Game,e1fce4da24b515edbba4c86ab8b19095,https://ieeexplore.ieee.org/document/6824206/
11816,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
11817,"A key feature of wireless communications is the spatial reuse. However, the spatial aspect is not yet well understood for the purpose of designing efficient spectrum sharing mechanisms. In this paper, we propose a framework of spatial spectrum access games on directed interference graphs, which can model quite general interference relationship with spatial reuse in wireless networks. We show that a pure Nash equilibrium exists for the two classes of games: (1) any spatial spectrum access games on directed acyclic graphs, and (2) any games satisfying the congestion property on directed trees and directed forests. Under mild technical conditions, the spatial spectrum access games with random backoff and Aloha channel contention mechanisms on undirected graphs also have a pure Nash equilibrium. We also quantify the price of anarchy of the spatial spectrum access game. We then propose a distributed learning algorithm, which only utilizes users' local observations to adaptively adjust the spectrum access strategies. We show that the distributed learning algorithm can converge to an approximate mixed-strategy Nash equilibrium for any spatial spectrum access games. Numerical results demonstrate that the distributed learning algorithm achieves up to 100 percent performance improvement over a random access algorithm.",jianwei huang,game theory,2015.0,10.1109/TMC.2014.2326673,IEEE Transactions on Mobile Computing,Chen2015,False,,IEEE,Not available,Spatial Spectrum Access Game,e1fce4da24b515edbba4c86ab8b19095,https://ieeexplore.ieee.org/document/6824206/
11818,"A key feature of wireless communications is the spatial reuse. However, the spatial aspect is not yet well understood for the purpose of designing efficient spectrum sharing mechanisms. In this paper, we propose a framework of spatial spectrum access games on directed interference graphs, which can model quite general interference relationship with spatial reuse in wireless networks. We show that a pure Nash equilibrium exists for the two classes of games: (1) any spatial spectrum access games on directed acyclic graphs, and (2) any games satisfying the congestion property on directed trees and directed forests. Under mild technical conditions, the spatial spectrum access games with random backoff and Aloha channel contention mechanisms on undirected graphs also have a pure Nash equilibrium. We also quantify the price of anarchy of the spatial spectrum access game. We then propose a distributed learning algorithm, which only utilizes users' local observations to adaptively adjust the spectrum access strategies. We show that the distributed learning algorithm can converge to an approximate mixed-strategy Nash equilibrium for any spatial spectrum access games. Numerical results demonstrate that the distributed learning algorithm achieves up to 100 percent performance improvement over a random access algorithm.",jianwei huang,Nash equilibrium,2015.0,10.1109/TMC.2014.2326673,IEEE Transactions on Mobile Computing,Chen2015,False,,IEEE,Not available,Spatial Spectrum Access Game,e1fce4da24b515edbba4c86ab8b19095,https://ieeexplore.ieee.org/document/6824206/
11819,"A key feature of wireless communications is the spatial reuse. However, the spatial aspect is not yet well understood for the purpose of designing efficient spectrum sharing mechanisms. In this paper, we propose a framework of spatial spectrum access games on directed interference graphs, which can model quite general interference relationship with spatial reuse in wireless networks. We show that a pure Nash equilibrium exists for the two classes of games: (1) any spatial spectrum access games on directed acyclic graphs, and (2) any games satisfying the congestion property on directed trees and directed forests. Under mild technical conditions, the spatial spectrum access games with random backoff and Aloha channel contention mechanisms on undirected graphs also have a pure Nash equilibrium. We also quantify the price of anarchy of the spatial spectrum access game. We then propose a distributed learning algorithm, which only utilizes users' local observations to adaptively adjust the spectrum access strategies. We show that the distributed learning algorithm can converge to an approximate mixed-strategy Nash equilibrium for any spatial spectrum access games. Numerical results demonstrate that the distributed learning algorithm achieves up to 100 percent performance improvement over a random access algorithm.",jianwei huang,distributed learning,2015.0,10.1109/TMC.2014.2326673,IEEE Transactions on Mobile Computing,Chen2015,False,,IEEE,Not available,Spatial Spectrum Access Game,e1fce4da24b515edbba4c86ab8b19095,https://ieeexplore.ieee.org/document/6824206/
11820,"We conduct a game theoretic analysis on the problem of scheduling jobs on computing platforms composed of several independent and selfish organizations, known as the Multi-Organization Scheduling Problem (MOSP). Each organization shares resources and jobs with others, expecting to decrease the makespan of its own jobs. We modeled MOSP as a non-cooperative game where each agent is responsible for assigning all jobs belonging to a particular organization to the available processors. The local scheduling of these jobs is defined by coordination mechanisms that first prioritize local jobs and then schedule the jobs from others according to some given priority. When different priorities are given individually to the jobs - like in classical scheduling algorithms such as LPT or SPT - then no pure e-approximate equilibrium is possible for values of e less than 2. We also prove that even deciding whether a given instance admits or not a pure Nash equilibrium is co-NP hard. When these priorities are given to entire organizations, we show the existence of an algorithm that always computes a pure ρ-approximate equilibrium using any ρ-approximation list scheduling algorithm. Finally, we prove that the price of anarchy of the MOSP game using this mechanism is asymptotically bounded by 2.",johanne cohen,scheduling,2011.0,10.1109/HiPC.2011.6152720,2011 18th International Conference on High Performance Computing,Cohen2011,False,,IEEE,Not available,Coordination mechanisms for selfish multi-organization scheduling,29ea8033f1dfacfc172d2fc486060097,https://ieeexplore.ieee.org/document/6152720/
11821,"We conduct a game theoretic analysis on the problem of scheduling jobs on computing platforms composed of several independent and selfish organizations, known as the Multi-Organization Scheduling Problem (MOSP). Each organization shares resources and jobs with others, expecting to decrease the makespan of its own jobs. We modeled MOSP as a non-cooperative game where each agent is responsible for assigning all jobs belonging to a particular organization to the available processors. The local scheduling of these jobs is defined by coordination mechanisms that first prioritize local jobs and then schedule the jobs from others according to some given priority. When different priorities are given individually to the jobs - like in classical scheduling algorithms such as LPT or SPT - then no pure e-approximate equilibrium is possible for values of e less than 2. We also prove that even deciding whether a given instance admits or not a pure Nash equilibrium is co-NP hard. When these priorities are given to entire organizations, we show the existence of an algorithm that always computes a pure ρ-approximate equilibrium using any ρ-approximation list scheduling algorithm. Finally, we prove that the price of anarchy of the MOSP game using this mechanism is asymptotically bounded by 2.",johanne cohen,multiple organizations,2011.0,10.1109/HiPC.2011.6152720,2011 18th International Conference on High Performance Computing,Cohen2011,False,,IEEE,Not available,Coordination mechanisms for selfish multi-organization scheduling,29ea8033f1dfacfc172d2fc486060097,https://ieeexplore.ieee.org/document/6152720/
11822,"We conduct a game theoretic analysis on the problem of scheduling jobs on computing platforms composed of several independent and selfish organizations, known as the Multi-Organization Scheduling Problem (MOSP). Each organization shares resources and jobs with others, expecting to decrease the makespan of its own jobs. We modeled MOSP as a non-cooperative game where each agent is responsible for assigning all jobs belonging to a particular organization to the available processors. The local scheduling of these jobs is defined by coordination mechanisms that first prioritize local jobs and then schedule the jobs from others according to some given priority. When different priorities are given individually to the jobs - like in classical scheduling algorithms such as LPT or SPT - then no pure e-approximate equilibrium is possible for values of e less than 2. We also prove that even deciding whether a given instance admits or not a pure Nash equilibrium is co-NP hard. When these priorities are given to entire organizations, we show the existence of an algorithm that always computes a pure ρ-approximate equilibrium using any ρ-approximation list scheduling algorithm. Finally, we prove that the price of anarchy of the MOSP game using this mechanism is asymptotically bounded by 2.",johanne cohen,algorithmic game theory,2011.0,10.1109/HiPC.2011.6152720,2011 18th International Conference on High Performance Computing,Cohen2011,False,,IEEE,Not available,Coordination mechanisms for selfish multi-organization scheduling,29ea8033f1dfacfc172d2fc486060097,https://ieeexplore.ieee.org/document/6152720/
11823,"We conduct a game theoretic analysis on the problem of scheduling jobs on computing platforms composed of several independent and selfish organizations, known as the Multi-Organization Scheduling Problem (MOSP). Each organization shares resources and jobs with others, expecting to decrease the makespan of its own jobs. We modeled MOSP as a non-cooperative game where each agent is responsible for assigning all jobs belonging to a particular organization to the available processors. The local scheduling of these jobs is defined by coordination mechanisms that first prioritize local jobs and then schedule the jobs from others according to some given priority. When different priorities are given individually to the jobs - like in classical scheduling algorithms such as LPT or SPT - then no pure e-approximate equilibrium is possible for values of e less than 2. We also prove that even deciding whether a given instance admits or not a pure Nash equilibrium is co-NP hard. When these priorities are given to entire organizations, we show the existence of an algorithm that always computes a pure ρ-approximate equilibrium using any ρ-approximation list scheduling algorithm. Finally, we prove that the price of anarchy of the MOSP game using this mechanism is asymptotically bounded by 2.",johanne cohen,coordination mechanisms,2011.0,10.1109/HiPC.2011.6152720,2011 18th International Conference on High Performance Computing,Cohen2011,False,,IEEE,Not available,Coordination mechanisms for selfish multi-organization scheduling,29ea8033f1dfacfc172d2fc486060097,https://ieeexplore.ieee.org/document/6152720/
11824,"We conduct a game theoretic analysis on the problem of scheduling jobs on computing platforms composed of several independent and selfish organizations, known as the Multi-Organization Scheduling Problem (MOSP). Each organization shares resources and jobs with others, expecting to decrease the makespan of its own jobs. We modeled MOSP as a non-cooperative game where each agent is responsible for assigning all jobs belonging to a particular organization to the available processors. The local scheduling of these jobs is defined by coordination mechanisms that first prioritize local jobs and then schedule the jobs from others according to some given priority. When different priorities are given individually to the jobs - like in classical scheduling algorithms such as LPT or SPT - then no pure e-approximate equilibrium is possible for values of e less than 2. We also prove that even deciding whether a given instance admits or not a pure Nash equilibrium is co-NP hard. When these priorities are given to entire organizations, we show the existence of an algorithm that always computes a pure ρ-approximate equilibrium using any ρ-approximation list scheduling algorithm. Finally, we prove that the price of anarchy of the MOSP game using this mechanism is asymptotically bounded by 2.",daniel cordeiro,scheduling,2011.0,10.1109/HiPC.2011.6152720,2011 18th International Conference on High Performance Computing,Cohen2011,False,,IEEE,Not available,Coordination mechanisms for selfish multi-organization scheduling,29ea8033f1dfacfc172d2fc486060097,https://ieeexplore.ieee.org/document/6152720/
11825,"We conduct a game theoretic analysis on the problem of scheduling jobs on computing platforms composed of several independent and selfish organizations, known as the Multi-Organization Scheduling Problem (MOSP). Each organization shares resources and jobs with others, expecting to decrease the makespan of its own jobs. We modeled MOSP as a non-cooperative game where each agent is responsible for assigning all jobs belonging to a particular organization to the available processors. The local scheduling of these jobs is defined by coordination mechanisms that first prioritize local jobs and then schedule the jobs from others according to some given priority. When different priorities are given individually to the jobs - like in classical scheduling algorithms such as LPT or SPT - then no pure e-approximate equilibrium is possible for values of e less than 2. We also prove that even deciding whether a given instance admits or not a pure Nash equilibrium is co-NP hard. When these priorities are given to entire organizations, we show the existence of an algorithm that always computes a pure ρ-approximate equilibrium using any ρ-approximation list scheduling algorithm. Finally, we prove that the price of anarchy of the MOSP game using this mechanism is asymptotically bounded by 2.",daniel cordeiro,multiple organizations,2011.0,10.1109/HiPC.2011.6152720,2011 18th International Conference on High Performance Computing,Cohen2011,False,,IEEE,Not available,Coordination mechanisms for selfish multi-organization scheduling,29ea8033f1dfacfc172d2fc486060097,https://ieeexplore.ieee.org/document/6152720/
11826,"We conduct a game theoretic analysis on the problem of scheduling jobs on computing platforms composed of several independent and selfish organizations, known as the Multi-Organization Scheduling Problem (MOSP). Each organization shares resources and jobs with others, expecting to decrease the makespan of its own jobs. We modeled MOSP as a non-cooperative game where each agent is responsible for assigning all jobs belonging to a particular organization to the available processors. The local scheduling of these jobs is defined by coordination mechanisms that first prioritize local jobs and then schedule the jobs from others according to some given priority. When different priorities are given individually to the jobs - like in classical scheduling algorithms such as LPT or SPT - then no pure e-approximate equilibrium is possible for values of e less than 2. We also prove that even deciding whether a given instance admits or not a pure Nash equilibrium is co-NP hard. When these priorities are given to entire organizations, we show the existence of an algorithm that always computes a pure ρ-approximate equilibrium using any ρ-approximation list scheduling algorithm. Finally, we prove that the price of anarchy of the MOSP game using this mechanism is asymptotically bounded by 2.",daniel cordeiro,algorithmic game theory,2011.0,10.1109/HiPC.2011.6152720,2011 18th International Conference on High Performance Computing,Cohen2011,False,,IEEE,Not available,Coordination mechanisms for selfish multi-organization scheduling,29ea8033f1dfacfc172d2fc486060097,https://ieeexplore.ieee.org/document/6152720/
11827,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
11828,"We conduct a game theoretic analysis on the problem of scheduling jobs on computing platforms composed of several independent and selfish organizations, known as the Multi-Organization Scheduling Problem (MOSP). Each organization shares resources and jobs with others, expecting to decrease the makespan of its own jobs. We modeled MOSP as a non-cooperative game where each agent is responsible for assigning all jobs belonging to a particular organization to the available processors. The local scheduling of these jobs is defined by coordination mechanisms that first prioritize local jobs and then schedule the jobs from others according to some given priority. When different priorities are given individually to the jobs - like in classical scheduling algorithms such as LPT or SPT - then no pure e-approximate equilibrium is possible for values of e less than 2. We also prove that even deciding whether a given instance admits or not a pure Nash equilibrium is co-NP hard. When these priorities are given to entire organizations, we show the existence of an algorithm that always computes a pure ρ-approximate equilibrium using any ρ-approximation list scheduling algorithm. Finally, we prove that the price of anarchy of the MOSP game using this mechanism is asymptotically bounded by 2.",daniel cordeiro,coordination mechanisms,2011.0,10.1109/HiPC.2011.6152720,2011 18th International Conference on High Performance Computing,Cohen2011,False,,IEEE,Not available,Coordination mechanisms for selfish multi-organization scheduling,29ea8033f1dfacfc172d2fc486060097,https://ieeexplore.ieee.org/document/6152720/
11829,"We conduct a game theoretic analysis on the problem of scheduling jobs on computing platforms composed of several independent and selfish organizations, known as the Multi-Organization Scheduling Problem (MOSP). Each organization shares resources and jobs with others, expecting to decrease the makespan of its own jobs. We modeled MOSP as a non-cooperative game where each agent is responsible for assigning all jobs belonging to a particular organization to the available processors. The local scheduling of these jobs is defined by coordination mechanisms that first prioritize local jobs and then schedule the jobs from others according to some given priority. When different priorities are given individually to the jobs - like in classical scheduling algorithms such as LPT or SPT - then no pure e-approximate equilibrium is possible for values of e less than 2. We also prove that even deciding whether a given instance admits or not a pure Nash equilibrium is co-NP hard. When these priorities are given to entire organizations, we show the existence of an algorithm that always computes a pure ρ-approximate equilibrium using any ρ-approximation list scheduling algorithm. Finally, we prove that the price of anarchy of the MOSP game using this mechanism is asymptotically bounded by 2.",denis trystram,scheduling,2011.0,10.1109/HiPC.2011.6152720,2011 18th International Conference on High Performance Computing,Cohen2011,False,,IEEE,Not available,Coordination mechanisms for selfish multi-organization scheduling,29ea8033f1dfacfc172d2fc486060097,https://ieeexplore.ieee.org/document/6152720/
11830,"We conduct a game theoretic analysis on the problem of scheduling jobs on computing platforms composed of several independent and selfish organizations, known as the Multi-Organization Scheduling Problem (MOSP). Each organization shares resources and jobs with others, expecting to decrease the makespan of its own jobs. We modeled MOSP as a non-cooperative game where each agent is responsible for assigning all jobs belonging to a particular organization to the available processors. The local scheduling of these jobs is defined by coordination mechanisms that first prioritize local jobs and then schedule the jobs from others according to some given priority. When different priorities are given individually to the jobs - like in classical scheduling algorithms such as LPT or SPT - then no pure e-approximate equilibrium is possible for values of e less than 2. We also prove that even deciding whether a given instance admits or not a pure Nash equilibrium is co-NP hard. When these priorities are given to entire organizations, we show the existence of an algorithm that always computes a pure ρ-approximate equilibrium using any ρ-approximation list scheduling algorithm. Finally, we prove that the price of anarchy of the MOSP game using this mechanism is asymptotically bounded by 2.",denis trystram,multiple organizations,2011.0,10.1109/HiPC.2011.6152720,2011 18th International Conference on High Performance Computing,Cohen2011,False,,IEEE,Not available,Coordination mechanisms for selfish multi-organization scheduling,29ea8033f1dfacfc172d2fc486060097,https://ieeexplore.ieee.org/document/6152720/
11831,"We conduct a game theoretic analysis on the problem of scheduling jobs on computing platforms composed of several independent and selfish organizations, known as the Multi-Organization Scheduling Problem (MOSP). Each organization shares resources and jobs with others, expecting to decrease the makespan of its own jobs. We modeled MOSP as a non-cooperative game where each agent is responsible for assigning all jobs belonging to a particular organization to the available processors. The local scheduling of these jobs is defined by coordination mechanisms that first prioritize local jobs and then schedule the jobs from others according to some given priority. When different priorities are given individually to the jobs - like in classical scheduling algorithms such as LPT or SPT - then no pure e-approximate equilibrium is possible for values of e less than 2. We also prove that even deciding whether a given instance admits or not a pure Nash equilibrium is co-NP hard. When these priorities are given to entire organizations, we show the existence of an algorithm that always computes a pure ρ-approximate equilibrium using any ρ-approximation list scheduling algorithm. Finally, we prove that the price of anarchy of the MOSP game using this mechanism is asymptotically bounded by 2.",denis trystram,algorithmic game theory,2011.0,10.1109/HiPC.2011.6152720,2011 18th International Conference on High Performance Computing,Cohen2011,False,,IEEE,Not available,Coordination mechanisms for selfish multi-organization scheduling,29ea8033f1dfacfc172d2fc486060097,https://ieeexplore.ieee.org/document/6152720/
11832,"We conduct a game theoretic analysis on the problem of scheduling jobs on computing platforms composed of several independent and selfish organizations, known as the Multi-Organization Scheduling Problem (MOSP). Each organization shares resources and jobs with others, expecting to decrease the makespan of its own jobs. We modeled MOSP as a non-cooperative game where each agent is responsible for assigning all jobs belonging to a particular organization to the available processors. The local scheduling of these jobs is defined by coordination mechanisms that first prioritize local jobs and then schedule the jobs from others according to some given priority. When different priorities are given individually to the jobs - like in classical scheduling algorithms such as LPT or SPT - then no pure e-approximate equilibrium is possible for values of e less than 2. We also prove that even deciding whether a given instance admits or not a pure Nash equilibrium is co-NP hard. When these priorities are given to entire organizations, we show the existence of an algorithm that always computes a pure ρ-approximate equilibrium using any ρ-approximation list scheduling algorithm. Finally, we prove that the price of anarchy of the MOSP game using this mechanism is asymptotically bounded by 2.",denis trystram,coordination mechanisms,2011.0,10.1109/HiPC.2011.6152720,2011 18th International Conference on High Performance Computing,Cohen2011,False,,IEEE,Not available,Coordination mechanisms for selfish multi-organization scheduling,29ea8033f1dfacfc172d2fc486060097,https://ieeexplore.ieee.org/document/6152720/
11833,"We conduct a game theoretic analysis on the problem of scheduling jobs on computing platforms composed of several independent and selfish organizations, known as the Multi-Organization Scheduling Problem (MOSP). Each organization shares resources and jobs with others, expecting to decrease the makespan of its own jobs. We modeled MOSP as a non-cooperative game where each agent is responsible for assigning all jobs belonging to a particular organization to the available processors. The local scheduling of these jobs is defined by coordination mechanisms that first prioritize local jobs and then schedule the jobs from others according to some given priority. When different priorities are given individually to the jobs - like in classical scheduling algorithms such as LPT or SPT - then no pure e-approximate equilibrium is possible for values of e less than 2. We also prove that even deciding whether a given instance admits or not a pure Nash equilibrium is co-NP hard. When these priorities are given to entire organizations, we show the existence of an algorithm that always computes a pure ρ-approximate equilibrium using any ρ-approximation list scheduling algorithm. Finally, we prove that the price of anarchy of the MOSP game using this mechanism is asymptotically bounded by 2.",frederic wagner,scheduling,2011.0,10.1109/HiPC.2011.6152720,2011 18th International Conference on High Performance Computing,Cohen2011,False,,IEEE,Not available,Coordination mechanisms for selfish multi-organization scheduling,29ea8033f1dfacfc172d2fc486060097,https://ieeexplore.ieee.org/document/6152720/
11834,"We conduct a game theoretic analysis on the problem of scheduling jobs on computing platforms composed of several independent and selfish organizations, known as the Multi-Organization Scheduling Problem (MOSP). Each organization shares resources and jobs with others, expecting to decrease the makespan of its own jobs. We modeled MOSP as a non-cooperative game where each agent is responsible for assigning all jobs belonging to a particular organization to the available processors. The local scheduling of these jobs is defined by coordination mechanisms that first prioritize local jobs and then schedule the jobs from others according to some given priority. When different priorities are given individually to the jobs - like in classical scheduling algorithms such as LPT or SPT - then no pure e-approximate equilibrium is possible for values of e less than 2. We also prove that even deciding whether a given instance admits or not a pure Nash equilibrium is co-NP hard. When these priorities are given to entire organizations, we show the existence of an algorithm that always computes a pure ρ-approximate equilibrium using any ρ-approximation list scheduling algorithm. Finally, we prove that the price of anarchy of the MOSP game using this mechanism is asymptotically bounded by 2.",frederic wagner,multiple organizations,2011.0,10.1109/HiPC.2011.6152720,2011 18th International Conference on High Performance Computing,Cohen2011,False,,IEEE,Not available,Coordination mechanisms for selfish multi-organization scheduling,29ea8033f1dfacfc172d2fc486060097,https://ieeexplore.ieee.org/document/6152720/
11835,"We conduct a game theoretic analysis on the problem of scheduling jobs on computing platforms composed of several independent and selfish organizations, known as the Multi-Organization Scheduling Problem (MOSP). Each organization shares resources and jobs with others, expecting to decrease the makespan of its own jobs. We modeled MOSP as a non-cooperative game where each agent is responsible for assigning all jobs belonging to a particular organization to the available processors. The local scheduling of these jobs is defined by coordination mechanisms that first prioritize local jobs and then schedule the jobs from others according to some given priority. When different priorities are given individually to the jobs - like in classical scheduling algorithms such as LPT or SPT - then no pure e-approximate equilibrium is possible for values of e less than 2. We also prove that even deciding whether a given instance admits or not a pure Nash equilibrium is co-NP hard. When these priorities are given to entire organizations, we show the existence of an algorithm that always computes a pure ρ-approximate equilibrium using any ρ-approximation list scheduling algorithm. Finally, we prove that the price of anarchy of the MOSP game using this mechanism is asymptotically bounded by 2.",frederic wagner,algorithmic game theory,2011.0,10.1109/HiPC.2011.6152720,2011 18th International Conference on High Performance Computing,Cohen2011,False,,IEEE,Not available,Coordination mechanisms for selfish multi-organization scheduling,29ea8033f1dfacfc172d2fc486060097,https://ieeexplore.ieee.org/document/6152720/
11836,"We conduct a game theoretic analysis on the problem of scheduling jobs on computing platforms composed of several independent and selfish organizations, known as the Multi-Organization Scheduling Problem (MOSP). Each organization shares resources and jobs with others, expecting to decrease the makespan of its own jobs. We modeled MOSP as a non-cooperative game where each agent is responsible for assigning all jobs belonging to a particular organization to the available processors. The local scheduling of these jobs is defined by coordination mechanisms that first prioritize local jobs and then schedule the jobs from others according to some given priority. When different priorities are given individually to the jobs - like in classical scheduling algorithms such as LPT or SPT - then no pure e-approximate equilibrium is possible for values of e less than 2. We also prove that even deciding whether a given instance admits or not a pure Nash equilibrium is co-NP hard. When these priorities are given to entire organizations, we show the existence of an algorithm that always computes a pure ρ-approximate equilibrium using any ρ-approximation list scheduling algorithm. Finally, we prove that the price of anarchy of the MOSP game using this mechanism is asymptotically bounded by 2.",frederic wagner,coordination mechanisms,2011.0,10.1109/HiPC.2011.6152720,2011 18th International Conference on High Performance Computing,Cohen2011,False,,IEEE,Not available,Coordination mechanisms for selfish multi-organization scheduling,29ea8033f1dfacfc172d2fc486060097,https://ieeexplore.ieee.org/document/6152720/
11837,"Fog computing, which provides low-latency computing services at the network edge, is an enabler for the emerging Internet of Things (IoT) systems. In this paper, we study the allocation of fog computing resources to the IoT users in a hierarchical computing paradigm including fog and remote cloud computing services. We formulate a computation offloading game to model the competition between IoT users and allocate the limited processing power of fog nodes efficiently. Each user aims to maximize its own quality of experience (QoE), which reflects its satisfaction of using computing services in terms of the reduction in computation energy and delay. Utilizing a potential game approach, we prove the existence of a pure Nash equilibrium (NE) and provide an upper bound for the price of anarchy. Since the time complexity to reach the equilibrium increases exponentially in the number of users, we further propose a near-optimal resource allocation mechanism and prove that in a system with N IoT users, it achieves an ε-NE in O(N/ε time. Through numerical studies, we evaluate the users' QoE as well as the equilibrium efficiency. Our results reveal that by utilizing the proposed mechanism, more users benefit from computing services in comparison to an existing offloading mechanism. We further show that our proposed mechanism significantly reduces the computation delay and enables low-latency fog computing services for delay-sensitive IoT applications.",hamed shah-mansouri,Computation offloading,2018.0,10.1109/JIOT.2018.2838022,IEEE Internet of Things Journal,Shah-Mansouri2018,False,,IEEE,Not available,Hierarchical Fog-Cloud Computing for IoT Systems: A Computation Offloading Game,42475eeb55b39b4b58359bbe398bb605,https://ieeexplore.ieee.org/document/8360511/
11838,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
11839,"Fog computing, which provides low-latency computing services at the network edge, is an enabler for the emerging Internet of Things (IoT) systems. In this paper, we study the allocation of fog computing resources to the IoT users in a hierarchical computing paradigm including fog and remote cloud computing services. We formulate a computation offloading game to model the competition between IoT users and allocate the limited processing power of fog nodes efficiently. Each user aims to maximize its own quality of experience (QoE), which reflects its satisfaction of using computing services in terms of the reduction in computation energy and delay. Utilizing a potential game approach, we prove the existence of a pure Nash equilibrium (NE) and provide an upper bound for the price of anarchy. Since the time complexity to reach the equilibrium increases exponentially in the number of users, we further propose a near-optimal resource allocation mechanism and prove that in a system with N IoT users, it achieves an ε-NE in O(N/ε time. Through numerical studies, we evaluate the users' QoE as well as the equilibrium efficiency. Our results reveal that by utilizing the proposed mechanism, more users benefit from computing services in comparison to an existing offloading mechanism. We further show that our proposed mechanism significantly reduces the computation delay and enables low-latency fog computing services for delay-sensitive IoT applications.",hamed shah-mansouri,fog computing,2018.0,10.1109/JIOT.2018.2838022,IEEE Internet of Things Journal,Shah-Mansouri2018,False,,IEEE,Not available,Hierarchical Fog-Cloud Computing for IoT Systems: A Computation Offloading Game,42475eeb55b39b4b58359bbe398bb605,https://ieeexplore.ieee.org/document/8360511/
11840,"Fog computing, which provides low-latency computing services at the network edge, is an enabler for the emerging Internet of Things (IoT) systems. In this paper, we study the allocation of fog computing resources to the IoT users in a hierarchical computing paradigm including fog and remote cloud computing services. We formulate a computation offloading game to model the competition between IoT users and allocate the limited processing power of fog nodes efficiently. Each user aims to maximize its own quality of experience (QoE), which reflects its satisfaction of using computing services in terms of the reduction in computation energy and delay. Utilizing a potential game approach, we prove the existence of a pure Nash equilibrium (NE) and provide an upper bound for the price of anarchy. Since the time complexity to reach the equilibrium increases exponentially in the number of users, we further propose a near-optimal resource allocation mechanism and prove that in a system with N IoT users, it achieves an ε-NE in O(N/ε time. Through numerical studies, we evaluate the users' QoE as well as the equilibrium efficiency. Our results reveal that by utilizing the proposed mechanism, more users benefit from computing services in comparison to an existing offloading mechanism. We further show that our proposed mechanism significantly reduces the computation delay and enables low-latency fog computing services for delay-sensitive IoT applications.",hamed shah-mansouri,Internet of Things (IoT),2018.0,10.1109/JIOT.2018.2838022,IEEE Internet of Things Journal,Shah-Mansouri2018,False,,IEEE,Not available,Hierarchical Fog-Cloud Computing for IoT Systems: A Computation Offloading Game,42475eeb55b39b4b58359bbe398bb605,https://ieeexplore.ieee.org/document/8360511/
11841,"Fog computing, which provides low-latency computing services at the network edge, is an enabler for the emerging Internet of Things (IoT) systems. In this paper, we study the allocation of fog computing resources to the IoT users in a hierarchical computing paradigm including fog and remote cloud computing services. We formulate a computation offloading game to model the competition between IoT users and allocate the limited processing power of fog nodes efficiently. Each user aims to maximize its own quality of experience (QoE), which reflects its satisfaction of using computing services in terms of the reduction in computation energy and delay. Utilizing a potential game approach, we prove the existence of a pure Nash equilibrium (NE) and provide an upper bound for the price of anarchy. Since the time complexity to reach the equilibrium increases exponentially in the number of users, we further propose a near-optimal resource allocation mechanism and prove that in a system with N IoT users, it achieves an ε-NE in O(N/ε time. Through numerical studies, we evaluate the users' QoE as well as the equilibrium efficiency. Our results reveal that by utilizing the proposed mechanism, more users benefit from computing services in comparison to an existing offloading mechanism. We further show that our proposed mechanism significantly reduces the computation delay and enables low-latency fog computing services for delay-sensitive IoT applications.",hamed shah-mansouri,potential games,2018.0,10.1109/JIOT.2018.2838022,IEEE Internet of Things Journal,Shah-Mansouri2018,False,,IEEE,Not available,Hierarchical Fog-Cloud Computing for IoT Systems: A Computation Offloading Game,42475eeb55b39b4b58359bbe398bb605,https://ieeexplore.ieee.org/document/8360511/
11842,"Fog computing, which provides low-latency computing services at the network edge, is an enabler for the emerging Internet of Things (IoT) systems. In this paper, we study the allocation of fog computing resources to the IoT users in a hierarchical computing paradigm including fog and remote cloud computing services. We formulate a computation offloading game to model the competition between IoT users and allocate the limited processing power of fog nodes efficiently. Each user aims to maximize its own quality of experience (QoE), which reflects its satisfaction of using computing services in terms of the reduction in computation energy and delay. Utilizing a potential game approach, we prove the existence of a pure Nash equilibrium (NE) and provide an upper bound for the price of anarchy. Since the time complexity to reach the equilibrium increases exponentially in the number of users, we further propose a near-optimal resource allocation mechanism and prove that in a system with N IoT users, it achieves an ε-NE in O(N/ε time. Through numerical studies, we evaluate the users' QoE as well as the equilibrium efficiency. Our results reveal that by utilizing the proposed mechanism, more users benefit from computing services in comparison to an existing offloading mechanism. We further show that our proposed mechanism significantly reduces the computation delay and enables low-latency fog computing services for delay-sensitive IoT applications.",vincent wong,Computation offloading,2018.0,10.1109/JIOT.2018.2838022,IEEE Internet of Things Journal,Shah-Mansouri2018,False,,IEEE,Not available,Hierarchical Fog-Cloud Computing for IoT Systems: A Computation Offloading Game,42475eeb55b39b4b58359bbe398bb605,https://ieeexplore.ieee.org/document/8360511/
11843,"Fog computing, which provides low-latency computing services at the network edge, is an enabler for the emerging Internet of Things (IoT) systems. In this paper, we study the allocation of fog computing resources to the IoT users in a hierarchical computing paradigm including fog and remote cloud computing services. We formulate a computation offloading game to model the competition between IoT users and allocate the limited processing power of fog nodes efficiently. Each user aims to maximize its own quality of experience (QoE), which reflects its satisfaction of using computing services in terms of the reduction in computation energy and delay. Utilizing a potential game approach, we prove the existence of a pure Nash equilibrium (NE) and provide an upper bound for the price of anarchy. Since the time complexity to reach the equilibrium increases exponentially in the number of users, we further propose a near-optimal resource allocation mechanism and prove that in a system with N IoT users, it achieves an ε-NE in O(N/ε time. Through numerical studies, we evaluate the users' QoE as well as the equilibrium efficiency. Our results reveal that by utilizing the proposed mechanism, more users benefit from computing services in comparison to an existing offloading mechanism. We further show that our proposed mechanism significantly reduces the computation delay and enables low-latency fog computing services for delay-sensitive IoT applications.",vincent wong,fog computing,2018.0,10.1109/JIOT.2018.2838022,IEEE Internet of Things Journal,Shah-Mansouri2018,False,,IEEE,Not available,Hierarchical Fog-Cloud Computing for IoT Systems: A Computation Offloading Game,42475eeb55b39b4b58359bbe398bb605,https://ieeexplore.ieee.org/document/8360511/
11844,"Fog computing, which provides low-latency computing services at the network edge, is an enabler for the emerging Internet of Things (IoT) systems. In this paper, we study the allocation of fog computing resources to the IoT users in a hierarchical computing paradigm including fog and remote cloud computing services. We formulate a computation offloading game to model the competition between IoT users and allocate the limited processing power of fog nodes efficiently. Each user aims to maximize its own quality of experience (QoE), which reflects its satisfaction of using computing services in terms of the reduction in computation energy and delay. Utilizing a potential game approach, we prove the existence of a pure Nash equilibrium (NE) and provide an upper bound for the price of anarchy. Since the time complexity to reach the equilibrium increases exponentially in the number of users, we further propose a near-optimal resource allocation mechanism and prove that in a system with N IoT users, it achieves an ε-NE in O(N/ε time. Through numerical studies, we evaluate the users' QoE as well as the equilibrium efficiency. Our results reveal that by utilizing the proposed mechanism, more users benefit from computing services in comparison to an existing offloading mechanism. We further show that our proposed mechanism significantly reduces the computation delay and enables low-latency fog computing services for delay-sensitive IoT applications.",vincent wong,Internet of Things (IoT),2018.0,10.1109/JIOT.2018.2838022,IEEE Internet of Things Journal,Shah-Mansouri2018,False,,IEEE,Not available,Hierarchical Fog-Cloud Computing for IoT Systems: A Computation Offloading Game,42475eeb55b39b4b58359bbe398bb605,https://ieeexplore.ieee.org/document/8360511/
11845,"Fog computing, which provides low-latency computing services at the network edge, is an enabler for the emerging Internet of Things (IoT) systems. In this paper, we study the allocation of fog computing resources to the IoT users in a hierarchical computing paradigm including fog and remote cloud computing services. We formulate a computation offloading game to model the competition between IoT users and allocate the limited processing power of fog nodes efficiently. Each user aims to maximize its own quality of experience (QoE), which reflects its satisfaction of using computing services in terms of the reduction in computation energy and delay. Utilizing a potential game approach, we prove the existence of a pure Nash equilibrium (NE) and provide an upper bound for the price of anarchy. Since the time complexity to reach the equilibrium increases exponentially in the number of users, we further propose a near-optimal resource allocation mechanism and prove that in a system with N IoT users, it achieves an ε-NE in O(N/ε time. Through numerical studies, we evaluate the users' QoE as well as the equilibrium efficiency. Our results reveal that by utilizing the proposed mechanism, more users benefit from computing services in comparison to an existing offloading mechanism. We further show that our proposed mechanism significantly reduces the computation delay and enables low-latency fog computing services for delay-sensitive IoT applications.",vincent wong,potential games,2018.0,10.1109/JIOT.2018.2838022,IEEE Internet of Things Journal,Shah-Mansouri2018,False,,IEEE,Not available,Hierarchical Fog-Cloud Computing for IoT Systems: A Computation Offloading Game,42475eeb55b39b4b58359bbe398bb605,https://ieeexplore.ieee.org/document/8360511/
11846,"The framework of resource allocation games is becoming an increasingly popular modeling choice for distributed control and optimization. In recent years, this approach has evolved into the paradigm of game-theoretic control, which consists of first modeling the interaction between the distributed agents as a strategic form game, and then designing local utility functions for these agents such that the resulting game possesses a stable outcome (e.g., a pure Nash equilibrium) that is efficient (e.g., good “price of anarchy” properties). One then appeals to the large, existing literature on learning in games for distributed algorithms for agents that guarantee convergence to such an equilibrium. An important first problem is to obtain a characterization of stable utility designs, that is, those that guarantee equilibrium existence for a large class of games. Recent work has explored this question in the general, multiselection context, that is, when agents are allowed to choose more than one resource at a time, showing that the only stable utility designs are the so-called “weighted Shapley values”. It remains an open problem to obtain a similar characterization in the single-selection context, which several practical problems such as vehicle target assignment, sensor coverage, etc. fall into. We survey recent work in the multi-selection scenario, and show that even though other utility designs become stable for specific single-selection applications, perhaps surprisingly, in a broader context, the limitation to “weighted Shapley value” utility design continues to prevail.",ragavendran gopalakrishnan,Games,2014.0,10.1109/CDC.2014.7039538,53rd IEEE Conference on Decision and Control,Gopalakrishnan2014,False,,IEEE,Not available,Stable utility design for distributed resource allocation,39b747e07c0736089fcd1c752b861bd2,https://ieeexplore.ieee.org/document/7039538/
11847,"The framework of resource allocation games is becoming an increasingly popular modeling choice for distributed control and optimization. In recent years, this approach has evolved into the paradigm of game-theoretic control, which consists of first modeling the interaction between the distributed agents as a strategic form game, and then designing local utility functions for these agents such that the resulting game possesses a stable outcome (e.g., a pure Nash equilibrium) that is efficient (e.g., good “price of anarchy” properties). One then appeals to the large, existing literature on learning in games for distributed algorithms for agents that guarantee convergence to such an equilibrium. An important first problem is to obtain a characterization of stable utility designs, that is, those that guarantee equilibrium existence for a large class of games. Recent work has explored this question in the general, multiselection context, that is, when agents are allowed to choose more than one resource at a time, showing that the only stable utility designs are the so-called “weighted Shapley values”. It remains an open problem to obtain a similar characterization in the single-selection context, which several practical problems such as vehicle target assignment, sensor coverage, etc. fall into. We survey recent work in the multi-selection scenario, and show that even though other utility designs become stable for specific single-selection applications, perhaps surprisingly, in a broader context, the limitation to “weighted Shapley value” utility design continues to prevail.",ragavendran gopalakrishnan,Resource management,2014.0,10.1109/CDC.2014.7039538,53rd IEEE Conference on Decision and Control,Gopalakrishnan2014,False,,IEEE,Not available,Stable utility design for distributed resource allocation,39b747e07c0736089fcd1c752b861bd2,https://ieeexplore.ieee.org/document/7039538/
11848,"The framework of resource allocation games is becoming an increasingly popular modeling choice for distributed control and optimization. In recent years, this approach has evolved into the paradigm of game-theoretic control, which consists of first modeling the interaction between the distributed agents as a strategic form game, and then designing local utility functions for these agents such that the resulting game possesses a stable outcome (e.g., a pure Nash equilibrium) that is efficient (e.g., good “price of anarchy” properties). One then appeals to the large, existing literature on learning in games for distributed algorithms for agents that guarantee convergence to such an equilibrium. An important first problem is to obtain a characterization of stable utility designs, that is, those that guarantee equilibrium existence for a large class of games. Recent work has explored this question in the general, multiselection context, that is, when agents are allowed to choose more than one resource at a time, showing that the only stable utility designs are the so-called “weighted Shapley values”. It remains an open problem to obtain a similar characterization in the single-selection context, which several practical problems such as vehicle target assignment, sensor coverage, etc. fall into. We survey recent work in the multi-selection scenario, and show that even though other utility designs become stable for specific single-selection applications, perhaps surprisingly, in a broader context, the limitation to “weighted Shapley value” utility design continues to prevail.",ragavendran gopalakrishnan,Vectors,2014.0,10.1109/CDC.2014.7039538,53rd IEEE Conference on Decision and Control,Gopalakrishnan2014,False,,IEEE,Not available,Stable utility design for distributed resource allocation,39b747e07c0736089fcd1c752b861bd2,https://ieeexplore.ieee.org/document/7039538/
11849,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
11850,"The framework of resource allocation games is becoming an increasingly popular modeling choice for distributed control and optimization. In recent years, this approach has evolved into the paradigm of game-theoretic control, which consists of first modeling the interaction between the distributed agents as a strategic form game, and then designing local utility functions for these agents such that the resulting game possesses a stable outcome (e.g., a pure Nash equilibrium) that is efficient (e.g., good “price of anarchy” properties). One then appeals to the large, existing literature on learning in games for distributed algorithms for agents that guarantee convergence to such an equilibrium. An important first problem is to obtain a characterization of stable utility designs, that is, those that guarantee equilibrium existence for a large class of games. Recent work has explored this question in the general, multiselection context, that is, when agents are allowed to choose more than one resource at a time, showing that the only stable utility designs are the so-called “weighted Shapley values”. It remains an open problem to obtain a similar characterization in the single-selection context, which several practical problems such as vehicle target assignment, sensor coverage, etc. fall into. We survey recent work in the multi-selection scenario, and show that even though other utility designs become stable for specific single-selection applications, perhaps surprisingly, in a broader context, the limitation to “weighted Shapley value” utility design continues to prevail.",ragavendran gopalakrishnan,Vehicles,2014.0,10.1109/CDC.2014.7039538,53rd IEEE Conference on Decision and Control,Gopalakrishnan2014,False,,IEEE,Not available,Stable utility design for distributed resource allocation,39b747e07c0736089fcd1c752b861bd2,https://ieeexplore.ieee.org/document/7039538/
11851,"The framework of resource allocation games is becoming an increasingly popular modeling choice for distributed control and optimization. In recent years, this approach has evolved into the paradigm of game-theoretic control, which consists of first modeling the interaction between the distributed agents as a strategic form game, and then designing local utility functions for these agents such that the resulting game possesses a stable outcome (e.g., a pure Nash equilibrium) that is efficient (e.g., good “price of anarchy” properties). One then appeals to the large, existing literature on learning in games for distributed algorithms for agents that guarantee convergence to such an equilibrium. An important first problem is to obtain a characterization of stable utility designs, that is, those that guarantee equilibrium existence for a large class of games. Recent work has explored this question in the general, multiselection context, that is, when agents are allowed to choose more than one resource at a time, showing that the only stable utility designs are the so-called “weighted Shapley values”. It remains an open problem to obtain a similar characterization in the single-selection context, which several practical problems such as vehicle target assignment, sensor coverage, etc. fall into. We survey recent work in the multi-selection scenario, and show that even though other utility designs become stable for specific single-selection applications, perhaps surprisingly, in a broader context, the limitation to “weighted Shapley value” utility design continues to prevail.",ragavendran gopalakrishnan,Nash equilibrium,2014.0,10.1109/CDC.2014.7039538,53rd IEEE Conference on Decision and Control,Gopalakrishnan2014,False,,IEEE,Not available,Stable utility design for distributed resource allocation,39b747e07c0736089fcd1c752b861bd2,https://ieeexplore.ieee.org/document/7039538/
11852,"The framework of resource allocation games is becoming an increasingly popular modeling choice for distributed control and optimization. In recent years, this approach has evolved into the paradigm of game-theoretic control, which consists of first modeling the interaction between the distributed agents as a strategic form game, and then designing local utility functions for these agents such that the resulting game possesses a stable outcome (e.g., a pure Nash equilibrium) that is efficient (e.g., good “price of anarchy” properties). One then appeals to the large, existing literature on learning in games for distributed algorithms for agents that guarantee convergence to such an equilibrium. An important first problem is to obtain a characterization of stable utility designs, that is, those that guarantee equilibrium existence for a large class of games. Recent work has explored this question in the general, multiselection context, that is, when agents are allowed to choose more than one resource at a time, showing that the only stable utility designs are the so-called “weighted Shapley values”. It remains an open problem to obtain a similar characterization in the single-selection context, which several practical problems such as vehicle target assignment, sensor coverage, etc. fall into. We survey recent work in the multi-selection scenario, and show that even though other utility designs become stable for specific single-selection applications, perhaps surprisingly, in a broader context, the limitation to “weighted Shapley value” utility design continues to prevail.",ragavendran gopalakrishnan,Equations,2014.0,10.1109/CDC.2014.7039538,53rd IEEE Conference on Decision and Control,Gopalakrishnan2014,False,,IEEE,Not available,Stable utility design for distributed resource allocation,39b747e07c0736089fcd1c752b861bd2,https://ieeexplore.ieee.org/document/7039538/
11853,"The framework of resource allocation games is becoming an increasingly popular modeling choice for distributed control and optimization. In recent years, this approach has evolved into the paradigm of game-theoretic control, which consists of first modeling the interaction between the distributed agents as a strategic form game, and then designing local utility functions for these agents such that the resulting game possesses a stable outcome (e.g., a pure Nash equilibrium) that is efficient (e.g., good “price of anarchy” properties). One then appeals to the large, existing literature on learning in games for distributed algorithms for agents that guarantee convergence to such an equilibrium. An important first problem is to obtain a characterization of stable utility designs, that is, those that guarantee equilibrium existence for a large class of games. Recent work has explored this question in the general, multiselection context, that is, when agents are allowed to choose more than one resource at a time, showing that the only stable utility designs are the so-called “weighted Shapley values”. It remains an open problem to obtain a similar characterization in the single-selection context, which several practical problems such as vehicle target assignment, sensor coverage, etc. fall into. We survey recent work in the multi-selection scenario, and show that even though other utility designs become stable for specific single-selection applications, perhaps surprisingly, in a broader context, the limitation to “weighted Shapley value” utility design continues to prevail.",ragavendran gopalakrishnan,Modeling,2014.0,10.1109/CDC.2014.7039538,53rd IEEE Conference on Decision and Control,Gopalakrishnan2014,False,,IEEE,Not available,Stable utility design for distributed resource allocation,39b747e07c0736089fcd1c752b861bd2,https://ieeexplore.ieee.org/document/7039538/
11854,"The framework of resource allocation games is becoming an increasingly popular modeling choice for distributed control and optimization. In recent years, this approach has evolved into the paradigm of game-theoretic control, which consists of first modeling the interaction between the distributed agents as a strategic form game, and then designing local utility functions for these agents such that the resulting game possesses a stable outcome (e.g., a pure Nash equilibrium) that is efficient (e.g., good “price of anarchy” properties). One then appeals to the large, existing literature on learning in games for distributed algorithms for agents that guarantee convergence to such an equilibrium. An important first problem is to obtain a characterization of stable utility designs, that is, those that guarantee equilibrium existence for a large class of games. Recent work has explored this question in the general, multiselection context, that is, when agents are allowed to choose more than one resource at a time, showing that the only stable utility designs are the so-called “weighted Shapley values”. It remains an open problem to obtain a similar characterization in the single-selection context, which several practical problems such as vehicle target assignment, sensor coverage, etc. fall into. We survey recent work in the multi-selection scenario, and show that even though other utility designs become stable for specific single-selection applications, perhaps surprisingly, in a broader context, the limitation to “weighted Shapley value” utility design continues to prevail.",sean nixon,Games,2014.0,10.1109/CDC.2014.7039538,53rd IEEE Conference on Decision and Control,Gopalakrishnan2014,False,,IEEE,Not available,Stable utility design for distributed resource allocation,39b747e07c0736089fcd1c752b861bd2,https://ieeexplore.ieee.org/document/7039538/
11855,"The framework of resource allocation games is becoming an increasingly popular modeling choice for distributed control and optimization. In recent years, this approach has evolved into the paradigm of game-theoretic control, which consists of first modeling the interaction between the distributed agents as a strategic form game, and then designing local utility functions for these agents such that the resulting game possesses a stable outcome (e.g., a pure Nash equilibrium) that is efficient (e.g., good “price of anarchy” properties). One then appeals to the large, existing literature on learning in games for distributed algorithms for agents that guarantee convergence to such an equilibrium. An important first problem is to obtain a characterization of stable utility designs, that is, those that guarantee equilibrium existence for a large class of games. Recent work has explored this question in the general, multiselection context, that is, when agents are allowed to choose more than one resource at a time, showing that the only stable utility designs are the so-called “weighted Shapley values”. It remains an open problem to obtain a similar characterization in the single-selection context, which several practical problems such as vehicle target assignment, sensor coverage, etc. fall into. We survey recent work in the multi-selection scenario, and show that even though other utility designs become stable for specific single-selection applications, perhaps surprisingly, in a broader context, the limitation to “weighted Shapley value” utility design continues to prevail.",sean nixon,Resource management,2014.0,10.1109/CDC.2014.7039538,53rd IEEE Conference on Decision and Control,Gopalakrishnan2014,False,,IEEE,Not available,Stable utility design for distributed resource allocation,39b747e07c0736089fcd1c752b861bd2,https://ieeexplore.ieee.org/document/7039538/
11856,"The framework of resource allocation games is becoming an increasingly popular modeling choice for distributed control and optimization. In recent years, this approach has evolved into the paradigm of game-theoretic control, which consists of first modeling the interaction between the distributed agents as a strategic form game, and then designing local utility functions for these agents such that the resulting game possesses a stable outcome (e.g., a pure Nash equilibrium) that is efficient (e.g., good “price of anarchy” properties). One then appeals to the large, existing literature on learning in games for distributed algorithms for agents that guarantee convergence to such an equilibrium. An important first problem is to obtain a characterization of stable utility designs, that is, those that guarantee equilibrium existence for a large class of games. Recent work has explored this question in the general, multiselection context, that is, when agents are allowed to choose more than one resource at a time, showing that the only stable utility designs are the so-called “weighted Shapley values”. It remains an open problem to obtain a similar characterization in the single-selection context, which several practical problems such as vehicle target assignment, sensor coverage, etc. fall into. We survey recent work in the multi-selection scenario, and show that even though other utility designs become stable for specific single-selection applications, perhaps surprisingly, in a broader context, the limitation to “weighted Shapley value” utility design continues to prevail.",sean nixon,Vectors,2014.0,10.1109/CDC.2014.7039538,53rd IEEE Conference on Decision and Control,Gopalakrishnan2014,False,,IEEE,Not available,Stable utility design for distributed resource allocation,39b747e07c0736089fcd1c752b861bd2,https://ieeexplore.ieee.org/document/7039538/
11857,"The framework of resource allocation games is becoming an increasingly popular modeling choice for distributed control and optimization. In recent years, this approach has evolved into the paradigm of game-theoretic control, which consists of first modeling the interaction between the distributed agents as a strategic form game, and then designing local utility functions for these agents such that the resulting game possesses a stable outcome (e.g., a pure Nash equilibrium) that is efficient (e.g., good “price of anarchy” properties). One then appeals to the large, existing literature on learning in games for distributed algorithms for agents that guarantee convergence to such an equilibrium. An important first problem is to obtain a characterization of stable utility designs, that is, those that guarantee equilibrium existence for a large class of games. Recent work has explored this question in the general, multiselection context, that is, when agents are allowed to choose more than one resource at a time, showing that the only stable utility designs are the so-called “weighted Shapley values”. It remains an open problem to obtain a similar characterization in the single-selection context, which several practical problems such as vehicle target assignment, sensor coverage, etc. fall into. We survey recent work in the multi-selection scenario, and show that even though other utility designs become stable for specific single-selection applications, perhaps surprisingly, in a broader context, the limitation to “weighted Shapley value” utility design continues to prevail.",sean nixon,Vehicles,2014.0,10.1109/CDC.2014.7039538,53rd IEEE Conference on Decision and Control,Gopalakrishnan2014,False,,IEEE,Not available,Stable utility design for distributed resource allocation,39b747e07c0736089fcd1c752b861bd2,https://ieeexplore.ieee.org/document/7039538/
11858,"The framework of resource allocation games is becoming an increasingly popular modeling choice for distributed control and optimization. In recent years, this approach has evolved into the paradigm of game-theoretic control, which consists of first modeling the interaction between the distributed agents as a strategic form game, and then designing local utility functions for these agents such that the resulting game possesses a stable outcome (e.g., a pure Nash equilibrium) that is efficient (e.g., good “price of anarchy” properties). One then appeals to the large, existing literature on learning in games for distributed algorithms for agents that guarantee convergence to such an equilibrium. An important first problem is to obtain a characterization of stable utility designs, that is, those that guarantee equilibrium existence for a large class of games. Recent work has explored this question in the general, multiselection context, that is, when agents are allowed to choose more than one resource at a time, showing that the only stable utility designs are the so-called “weighted Shapley values”. It remains an open problem to obtain a similar characterization in the single-selection context, which several practical problems such as vehicle target assignment, sensor coverage, etc. fall into. We survey recent work in the multi-selection scenario, and show that even though other utility designs become stable for specific single-selection applications, perhaps surprisingly, in a broader context, the limitation to “weighted Shapley value” utility design continues to prevail.",sean nixon,Nash equilibrium,2014.0,10.1109/CDC.2014.7039538,53rd IEEE Conference on Decision and Control,Gopalakrishnan2014,False,,IEEE,Not available,Stable utility design for distributed resource allocation,39b747e07c0736089fcd1c752b861bd2,https://ieeexplore.ieee.org/document/7039538/
11859,"The framework of resource allocation games is becoming an increasingly popular modeling choice for distributed control and optimization. In recent years, this approach has evolved into the paradigm of game-theoretic control, which consists of first modeling the interaction between the distributed agents as a strategic form game, and then designing local utility functions for these agents such that the resulting game possesses a stable outcome (e.g., a pure Nash equilibrium) that is efficient (e.g., good “price of anarchy” properties). One then appeals to the large, existing literature on learning in games for distributed algorithms for agents that guarantee convergence to such an equilibrium. An important first problem is to obtain a characterization of stable utility designs, that is, those that guarantee equilibrium existence for a large class of games. Recent work has explored this question in the general, multiselection context, that is, when agents are allowed to choose more than one resource at a time, showing that the only stable utility designs are the so-called “weighted Shapley values”. It remains an open problem to obtain a similar characterization in the single-selection context, which several practical problems such as vehicle target assignment, sensor coverage, etc. fall into. We survey recent work in the multi-selection scenario, and show that even though other utility designs become stable for specific single-selection applications, perhaps surprisingly, in a broader context, the limitation to “weighted Shapley value” utility design continues to prevail.",sean nixon,Equations,2014.0,10.1109/CDC.2014.7039538,53rd IEEE Conference on Decision and Control,Gopalakrishnan2014,False,,IEEE,Not available,Stable utility design for distributed resource allocation,39b747e07c0736089fcd1c752b861bd2,https://ieeexplore.ieee.org/document/7039538/
11860,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
11861,"The framework of resource allocation games is becoming an increasingly popular modeling choice for distributed control and optimization. In recent years, this approach has evolved into the paradigm of game-theoretic control, which consists of first modeling the interaction between the distributed agents as a strategic form game, and then designing local utility functions for these agents such that the resulting game possesses a stable outcome (e.g., a pure Nash equilibrium) that is efficient (e.g., good “price of anarchy” properties). One then appeals to the large, existing literature on learning in games for distributed algorithms for agents that guarantee convergence to such an equilibrium. An important first problem is to obtain a characterization of stable utility designs, that is, those that guarantee equilibrium existence for a large class of games. Recent work has explored this question in the general, multiselection context, that is, when agents are allowed to choose more than one resource at a time, showing that the only stable utility designs are the so-called “weighted Shapley values”. It remains an open problem to obtain a similar characterization in the single-selection context, which several practical problems such as vehicle target assignment, sensor coverage, etc. fall into. We survey recent work in the multi-selection scenario, and show that even though other utility designs become stable for specific single-selection applications, perhaps surprisingly, in a broader context, the limitation to “weighted Shapley value” utility design continues to prevail.",sean nixon,Modeling,2014.0,10.1109/CDC.2014.7039538,53rd IEEE Conference on Decision and Control,Gopalakrishnan2014,False,,IEEE,Not available,Stable utility design for distributed resource allocation,39b747e07c0736089fcd1c752b861bd2,https://ieeexplore.ieee.org/document/7039538/
11862,"The framework of resource allocation games is becoming an increasingly popular modeling choice for distributed control and optimization. In recent years, this approach has evolved into the paradigm of game-theoretic control, which consists of first modeling the interaction between the distributed agents as a strategic form game, and then designing local utility functions for these agents such that the resulting game possesses a stable outcome (e.g., a pure Nash equilibrium) that is efficient (e.g., good “price of anarchy” properties). One then appeals to the large, existing literature on learning in games for distributed algorithms for agents that guarantee convergence to such an equilibrium. An important first problem is to obtain a characterization of stable utility designs, that is, those that guarantee equilibrium existence for a large class of games. Recent work has explored this question in the general, multiselection context, that is, when agents are allowed to choose more than one resource at a time, showing that the only stable utility designs are the so-called “weighted Shapley values”. It remains an open problem to obtain a similar characterization in the single-selection context, which several practical problems such as vehicle target assignment, sensor coverage, etc. fall into. We survey recent work in the multi-selection scenario, and show that even though other utility designs become stable for specific single-selection applications, perhaps surprisingly, in a broader context, the limitation to “weighted Shapley value” utility design continues to prevail.",jason marden,Games,2014.0,10.1109/CDC.2014.7039538,53rd IEEE Conference on Decision and Control,Gopalakrishnan2014,False,,IEEE,Not available,Stable utility design for distributed resource allocation,39b747e07c0736089fcd1c752b861bd2,https://ieeexplore.ieee.org/document/7039538/
11863,"The framework of resource allocation games is becoming an increasingly popular modeling choice for distributed control and optimization. In recent years, this approach has evolved into the paradigm of game-theoretic control, which consists of first modeling the interaction between the distributed agents as a strategic form game, and then designing local utility functions for these agents such that the resulting game possesses a stable outcome (e.g., a pure Nash equilibrium) that is efficient (e.g., good “price of anarchy” properties). One then appeals to the large, existing literature on learning in games for distributed algorithms for agents that guarantee convergence to such an equilibrium. An important first problem is to obtain a characterization of stable utility designs, that is, those that guarantee equilibrium existence for a large class of games. Recent work has explored this question in the general, multiselection context, that is, when agents are allowed to choose more than one resource at a time, showing that the only stable utility designs are the so-called “weighted Shapley values”. It remains an open problem to obtain a similar characterization in the single-selection context, which several practical problems such as vehicle target assignment, sensor coverage, etc. fall into. We survey recent work in the multi-selection scenario, and show that even though other utility designs become stable for specific single-selection applications, perhaps surprisingly, in a broader context, the limitation to “weighted Shapley value” utility design continues to prevail.",jason marden,Resource management,2014.0,10.1109/CDC.2014.7039538,53rd IEEE Conference on Decision and Control,Gopalakrishnan2014,False,,IEEE,Not available,Stable utility design for distributed resource allocation,39b747e07c0736089fcd1c752b861bd2,https://ieeexplore.ieee.org/document/7039538/
11864,"The framework of resource allocation games is becoming an increasingly popular modeling choice for distributed control and optimization. In recent years, this approach has evolved into the paradigm of game-theoretic control, which consists of first modeling the interaction between the distributed agents as a strategic form game, and then designing local utility functions for these agents such that the resulting game possesses a stable outcome (e.g., a pure Nash equilibrium) that is efficient (e.g., good “price of anarchy” properties). One then appeals to the large, existing literature on learning in games for distributed algorithms for agents that guarantee convergence to such an equilibrium. An important first problem is to obtain a characterization of stable utility designs, that is, those that guarantee equilibrium existence for a large class of games. Recent work has explored this question in the general, multiselection context, that is, when agents are allowed to choose more than one resource at a time, showing that the only stable utility designs are the so-called “weighted Shapley values”. It remains an open problem to obtain a similar characterization in the single-selection context, which several practical problems such as vehicle target assignment, sensor coverage, etc. fall into. We survey recent work in the multi-selection scenario, and show that even though other utility designs become stable for specific single-selection applications, perhaps surprisingly, in a broader context, the limitation to “weighted Shapley value” utility design continues to prevail.",jason marden,Vectors,2014.0,10.1109/CDC.2014.7039538,53rd IEEE Conference on Decision and Control,Gopalakrishnan2014,False,,IEEE,Not available,Stable utility design for distributed resource allocation,39b747e07c0736089fcd1c752b861bd2,https://ieeexplore.ieee.org/document/7039538/
11865,"The framework of resource allocation games is becoming an increasingly popular modeling choice for distributed control and optimization. In recent years, this approach has evolved into the paradigm of game-theoretic control, which consists of first modeling the interaction between the distributed agents as a strategic form game, and then designing local utility functions for these agents such that the resulting game possesses a stable outcome (e.g., a pure Nash equilibrium) that is efficient (e.g., good “price of anarchy” properties). One then appeals to the large, existing literature on learning in games for distributed algorithms for agents that guarantee convergence to such an equilibrium. An important first problem is to obtain a characterization of stable utility designs, that is, those that guarantee equilibrium existence for a large class of games. Recent work has explored this question in the general, multiselection context, that is, when agents are allowed to choose more than one resource at a time, showing that the only stable utility designs are the so-called “weighted Shapley values”. It remains an open problem to obtain a similar characterization in the single-selection context, which several practical problems such as vehicle target assignment, sensor coverage, etc. fall into. We survey recent work in the multi-selection scenario, and show that even though other utility designs become stable for specific single-selection applications, perhaps surprisingly, in a broader context, the limitation to “weighted Shapley value” utility design continues to prevail.",jason marden,Vehicles,2014.0,10.1109/CDC.2014.7039538,53rd IEEE Conference on Decision and Control,Gopalakrishnan2014,False,,IEEE,Not available,Stable utility design for distributed resource allocation,39b747e07c0736089fcd1c752b861bd2,https://ieeexplore.ieee.org/document/7039538/
11866,"The framework of resource allocation games is becoming an increasingly popular modeling choice for distributed control and optimization. In recent years, this approach has evolved into the paradigm of game-theoretic control, which consists of first modeling the interaction between the distributed agents as a strategic form game, and then designing local utility functions for these agents such that the resulting game possesses a stable outcome (e.g., a pure Nash equilibrium) that is efficient (e.g., good “price of anarchy” properties). One then appeals to the large, existing literature on learning in games for distributed algorithms for agents that guarantee convergence to such an equilibrium. An important first problem is to obtain a characterization of stable utility designs, that is, those that guarantee equilibrium existence for a large class of games. Recent work has explored this question in the general, multiselection context, that is, when agents are allowed to choose more than one resource at a time, showing that the only stable utility designs are the so-called “weighted Shapley values”. It remains an open problem to obtain a similar characterization in the single-selection context, which several practical problems such as vehicle target assignment, sensor coverage, etc. fall into. We survey recent work in the multi-selection scenario, and show that even though other utility designs become stable for specific single-selection applications, perhaps surprisingly, in a broader context, the limitation to “weighted Shapley value” utility design continues to prevail.",jason marden,Nash equilibrium,2014.0,10.1109/CDC.2014.7039538,53rd IEEE Conference on Decision and Control,Gopalakrishnan2014,False,,IEEE,Not available,Stable utility design for distributed resource allocation,39b747e07c0736089fcd1c752b861bd2,https://ieeexplore.ieee.org/document/7039538/
11867,"The framework of resource allocation games is becoming an increasingly popular modeling choice for distributed control and optimization. In recent years, this approach has evolved into the paradigm of game-theoretic control, which consists of first modeling the interaction between the distributed agents as a strategic form game, and then designing local utility functions for these agents such that the resulting game possesses a stable outcome (e.g., a pure Nash equilibrium) that is efficient (e.g., good “price of anarchy” properties). One then appeals to the large, existing literature on learning in games for distributed algorithms for agents that guarantee convergence to such an equilibrium. An important first problem is to obtain a characterization of stable utility designs, that is, those that guarantee equilibrium existence for a large class of games. Recent work has explored this question in the general, multiselection context, that is, when agents are allowed to choose more than one resource at a time, showing that the only stable utility designs are the so-called “weighted Shapley values”. It remains an open problem to obtain a similar characterization in the single-selection context, which several practical problems such as vehicle target assignment, sensor coverage, etc. fall into. We survey recent work in the multi-selection scenario, and show that even though other utility designs become stable for specific single-selection applications, perhaps surprisingly, in a broader context, the limitation to “weighted Shapley value” utility design continues to prevail.",jason marden,Equations,2014.0,10.1109/CDC.2014.7039538,53rd IEEE Conference on Decision and Control,Gopalakrishnan2014,False,,IEEE,Not available,Stable utility design for distributed resource allocation,39b747e07c0736089fcd1c752b861bd2,https://ieeexplore.ieee.org/document/7039538/
11868,"The framework of resource allocation games is becoming an increasingly popular modeling choice for distributed control and optimization. In recent years, this approach has evolved into the paradigm of game-theoretic control, which consists of first modeling the interaction between the distributed agents as a strategic form game, and then designing local utility functions for these agents such that the resulting game possesses a stable outcome (e.g., a pure Nash equilibrium) that is efficient (e.g., good “price of anarchy” properties). One then appeals to the large, existing literature on learning in games for distributed algorithms for agents that guarantee convergence to such an equilibrium. An important first problem is to obtain a characterization of stable utility designs, that is, those that guarantee equilibrium existence for a large class of games. Recent work has explored this question in the general, multiselection context, that is, when agents are allowed to choose more than one resource at a time, showing that the only stable utility designs are the so-called “weighted Shapley values”. It remains an open problem to obtain a similar characterization in the single-selection context, which several practical problems such as vehicle target assignment, sensor coverage, etc. fall into. We survey recent work in the multi-selection scenario, and show that even though other utility designs become stable for specific single-selection applications, perhaps surprisingly, in a broader context, the limitation to “weighted Shapley value” utility design continues to prevail.",jason marden,Modeling,2014.0,10.1109/CDC.2014.7039538,53rd IEEE Conference on Decision and Control,Gopalakrishnan2014,False,,IEEE,Not available,Stable utility design for distributed resource allocation,39b747e07c0736089fcd1c752b861bd2,https://ieeexplore.ieee.org/document/7039538/
11869,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
11870,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
11871,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
11872,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
11873,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
11874,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
11875,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
11876,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
11877,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
11878,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
11879,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
11880,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
11881,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
11882,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11883,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
11884,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
11885,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
11886,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
11887,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
11888,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
11889,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
11890,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
11891,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
11892,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
11893,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
11894,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
11895,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
11896,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
11897,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
11898,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
11899,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
11900,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
11901,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
11902,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
11903,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
11904,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
11905,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
11906,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
11907,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
11908,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
11909,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
11910,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
11911,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
11912,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
11913,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
11914,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
11915,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
11916,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
11917,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
11918,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
11919,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
11920,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
11921,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
11922,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
11923,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
11924,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
11925,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
11926,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
11927,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
11928,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
11929,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
11930,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
11931,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
11932,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11933,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11934,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11935,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11936,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11937,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11938,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
11939,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11940,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11941,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11942,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11943,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11944,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11945,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11946,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11947,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11948,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11949,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
11950,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11951,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11952,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11953,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11954,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11955,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11956,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11957,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11958,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11959,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11960,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
11961,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11962,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11963,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11964,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11965,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11966,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11967,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11968,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11969,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11970,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11971,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
11972,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11973,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11974,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11975,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11976,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11977,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11978,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11979,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11980,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11981,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11982,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
11983,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11984,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11985,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11986,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11987,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
11988,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
11989,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
11990,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
11991,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
11992,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
11993,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
11994,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
11995,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
11996,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
11997,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
11998,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
11999,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12000,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12001,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12002,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12003,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12004,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12005,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12006,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12007,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12008,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12009,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12010,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12011,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12012,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12013,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12014,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12015,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12016,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12017,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12018,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12019,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12020,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12021,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12022,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12023,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12024,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12025,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12026,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12027,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12028,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12029,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12030,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12031,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12032,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12033,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12034,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12035,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12036,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12037,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12038,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12039,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12040,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12041,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12042,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12043,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12044,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12045,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12046,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12047,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12048,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12049,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12050,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12051,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12052,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12053,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12054,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12055,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12056,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12057,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12058,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12059,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12060,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12061,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12062,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12063,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12064,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12065,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12066,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12067,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12068,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12069,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12070,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12071,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12072,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12073,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12074,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12075,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12076,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12077,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12078,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12079,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12080,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12081,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12082,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12083,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12084,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12085,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12086,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12087,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12088,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12089,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12090,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12091,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12092,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12093,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12094,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12095,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12096,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12097,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12098,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12099,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12100,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12101,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12102,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12103,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12104,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12105,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12106,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12107,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12108,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12109,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12110,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12111,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12112,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12113,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12114,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12115,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12116,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12117,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12118,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12119,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12120,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12121,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12122,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12123,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12124,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12125,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12126,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12127,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12128,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12129,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12130,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12131,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12132,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12133,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12134,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12135,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12136,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12137,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12138,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12139,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12140,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12141,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12142,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12143,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12144,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12145,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12146,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12147,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12148,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12149,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12150,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12151,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12152,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12153,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12154,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12155,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12156,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12157,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12158,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12159,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12160,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12161,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12162,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12163,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12164,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12165,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12166,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12167,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12168,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12169,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12170,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12171,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12172,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12173,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12174,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12175,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12176,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12177,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12178,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12179,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12180,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12181,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12182,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12183,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12184,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12185,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12186,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12187,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12188,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12189,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12190,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12191,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12192,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12193,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12194,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12195,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12196,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12197,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12198,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12199,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12200,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12201,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12202,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12203,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12204,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12205,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12206,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12207,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12208,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12209,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12210,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12211,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12212,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12213,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12214,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12215,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12216,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12217,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12218,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12219,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12220,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12221,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12222,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12223,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12224,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12225,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12226,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12227,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12228,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12229,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12230,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12231,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12232,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12233,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12234,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12235,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12236,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12237,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12238,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12239,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12240,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12241,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12242,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12243,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12244,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12245,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12246,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12247,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12248,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12249,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12250,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12251,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12252,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12253,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12254,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12255,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12256,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12257,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12258,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12259,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12260,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12261,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12262,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12263,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12264,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12265,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12266,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12267,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12268,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12269,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12270,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12271,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12272,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12273,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12274,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12275,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12276,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12277,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12278,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12279,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12280,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12281,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12282,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12283,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12284,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12285,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12286,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12287,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12288,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12289,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12290,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12291,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12292,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12293,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12294,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12295,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12296,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12297,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12298,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12299,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12300,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12301,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12302,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12303,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12304,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12305,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12306,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12307,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12308,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12309,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12310,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12311,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12312,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12313,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12314,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12315,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12316,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12317,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12318,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12319,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12320,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12321,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12322,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12323,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12324,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12325,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12326,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12327,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12328,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12329,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12330,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12331,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12332,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12333,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12334,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12335,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12336,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12337,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12338,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12339,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12340,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12341,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12342,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12343,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12344,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12345,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12346,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12347,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12348,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12349,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12350,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12351,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12352,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12353,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12354,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12355,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12356,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12357,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12358,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12359,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12360,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12361,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12362,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12363,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12364,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12365,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12366,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12367,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12368,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12369,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12370,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12371,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12372,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12373,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12374,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12375,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12376,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12377,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12378,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12379,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12380,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12381,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12382,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12383,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12384,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12385,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12386,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12387,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12388,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12389,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12390,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12391,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12392,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12393,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12394,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12395,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12396,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12397,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12398,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12399,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12400,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12401,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12402,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12403,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12404,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12405,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12406,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12407,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12408,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12409,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12410,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12411,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12412,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12413,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12414,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12415,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12416,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12417,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12418,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12419,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12420,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12421,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12422,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12423,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12424,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12425,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12426,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12427,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12428,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12429,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12430,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12431,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12432,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12433,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12434,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12435,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12436,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12437,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12438,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12439,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12440,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12441,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12442,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12443,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12444,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12445,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12446,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12447,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12448,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12449,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12450,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12451,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12452,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12453,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12454,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12455,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12456,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12457,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12458,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12459,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12460,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12461,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12462,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12463,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12464,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12465,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12466,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12467,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12468,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12469,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12470,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12471,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12472,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12473,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12474,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12475,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12476,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12477,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12478,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12479,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12480,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12481,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12482,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12483,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12484,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12485,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12486,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12487,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12488,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12489,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12490,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12491,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12492,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12493,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12494,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12495,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12496,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12497,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12498,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12499,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12500,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12501,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12502,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12503,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12504,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12505,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12506,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12507,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12508,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12509,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12510,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12511,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12512,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12513,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12514,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12515,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12516,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12517,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12518,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12519,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12520,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12521,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12522,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12523,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12524,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12525,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12526,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12527,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12528,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12529,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12530,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12531,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12532,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12533,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12534,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12535,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12536,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12537,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12538,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12539,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12540,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12541,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12542,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12543,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12544,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12545,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12546,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12547,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12548,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12549,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12550,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12551,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12552,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12553,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12554,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12555,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12556,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12557,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12558,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12559,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12560,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12561,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12562,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12563,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12564,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12565,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12566,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12567,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12568,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12569,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12570,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12571,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12572,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12573,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12574,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12575,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12576,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12577,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12578,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12579,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12580,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12581,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12582,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12583,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12584,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12585,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12586,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12587,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12588,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12589,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12590,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12591,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12592,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12593,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12594,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12595,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12596,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12597,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12598,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12599,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12600,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12601,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12602,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12603,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12604,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12605,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12606,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12607,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12608,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12609,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12610,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12611,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12612,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12613,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12614,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12615,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12616,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12617,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12618,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12619,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12620,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12621,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12622,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12623,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12624,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12625,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12626,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12627,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12628,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12629,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12630,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12631,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12632,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12633,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12634,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12635,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12636,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12637,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12638,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12639,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12640,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12641,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12642,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12643,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12644,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12645,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12646,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12647,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12648,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12649,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12650,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12651,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12652,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12653,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12654,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12655,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12656,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12657,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12658,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12659,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12660,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12661,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12662,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12663,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12664,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12665,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12666,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12667,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12668,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12669,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12670,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12671,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12672,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12673,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12674,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12675,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12676,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12677,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12678,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12679,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12680,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12681,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12682,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12683,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12684,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12685,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12686,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12687,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12688,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12689,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12690,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12691,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12692,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12693,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12694,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12695,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12696,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12697,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12698,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12699,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12700,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12701,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12702,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12703,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12704,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12705,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12706,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12707,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12708,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12709,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12710,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12711,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12712,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12713,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12714,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12715,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12716,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12717,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12718,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12719,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12720,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12721,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12722,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12723,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12724,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12725,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12726,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12727,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12728,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12729,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12730,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12731,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12732,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12733,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12734,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12735,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12736,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12737,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12738,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12739,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12740,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12741,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12742,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12743,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12744,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12745,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12746,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12747,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12748,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12749,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12750,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12751,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12752,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12753,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12754,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12755,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12756,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12757,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12758,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12759,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12760,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12761,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12762,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12763,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12764,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12765,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12766,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12767,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12768,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12769,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12770,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12771,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12772,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12773,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12774,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12775,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12776,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12777,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12778,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12779,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12780,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12781,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12782,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12783,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12784,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12785,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12786,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12787,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12788,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12789,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12790,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12791,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12792,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12793,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12794,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12795,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12796,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12797,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12798,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12799,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12800,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12801,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12802,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12803,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12804,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12805,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12806,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12807,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12808,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12809,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12810,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12811,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12812,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12813,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12814,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12815,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
12816,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12817,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12818,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12819,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12820,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12821,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12822,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12823,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12824,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12825,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12826,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
12827,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12828,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12829,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12830,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12831,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12832,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12833,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12834,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12835,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
12836,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12837,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12838,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12839,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12840,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12841,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12842,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12843,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12844,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12845,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12846,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12847,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12848,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12849,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12850,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12851,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12852,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12853,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12854,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12855,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12856,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12857,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12858,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12859,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12860,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12861,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12862,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12863,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12864,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12865,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12866,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12867,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12868,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12869,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12870,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12871,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12872,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12873,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12874,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12875,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12876,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12877,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
12878,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12879,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12880,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12881,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12882,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12883,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12884,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12885,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12886,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12887,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12888,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12889,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12890,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12891,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12892,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12893,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12894,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12895,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12896,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12897,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12898,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12899,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12900,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12901,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12902,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12903,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12904,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12905,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12906,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12907,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12908,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12909,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12910,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12911,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12912,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12913,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12914,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12915,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12916,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12917,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12918,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12919,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12920,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12921,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12922,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12923,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12924,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12925,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12926,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12927,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12928,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12929,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12930,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12931,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12932,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12933,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12934,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12935,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12936,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12937,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12938,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12939,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12940,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12941,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12942,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12943,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12944,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12945,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12946,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12947,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12948,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12949,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12950,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12951,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12952,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12953,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12954,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12955,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
12956,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12957,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12958,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12959,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12960,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12961,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12962,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12963,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12964,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
12965,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12966,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12967,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12968,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12969,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12970,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12971,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12972,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12973,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12974,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12975,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12976,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12977,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12978,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12979,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12980,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12981,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12982,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12983,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12984,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12985,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12986,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12987,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12988,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12989,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12990,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
12991,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12992,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12993,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
12994,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
12995,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12996,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12997,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12998,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
12999,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13000,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13001,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13002,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13003,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13004,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13005,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13006,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13007,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13008,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13009,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13010,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13011,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13012,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13013,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13014,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13015,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13016,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13017,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13018,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13019,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13020,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13021,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13022,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13023,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13024,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13025,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13026,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13027,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13028,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13029,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13030,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13031,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13032,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13033,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13034,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13035,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13036,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13037,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13038,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13039,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13040,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13041,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13042,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13043,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13044,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13045,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13046,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13047,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13048,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13049,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13050,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13051,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13052,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13053,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
13054,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
13055,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
13056,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
13057,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
13058,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
13059,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
13060,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13061,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
13062,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
13063,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
13064,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
13065,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
13066,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
13067,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
13068,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
13069,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
13070,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
13071,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13072,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
13073,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13074,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13075,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13076,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13077,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13078,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13079,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13080,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13081,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13082,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13083,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13084,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13085,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13086,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13087,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13088,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13089,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13090,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13091,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13092,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13093,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13094,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13095,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13096,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13097,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13098,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13099,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13100,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13101,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13102,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13103,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13104,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
13105,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13106,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13107,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13108,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13109,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13110,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13111,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13112,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13113,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13114,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13115,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13116,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13117,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13118,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13119,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13120,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13121,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13122,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13123,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13124,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13125,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13126,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13127,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13128,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13129,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13130,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13131,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13132,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13133,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13134,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13135,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13136,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13137,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13138,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13139,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13140,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13141,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13142,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13143,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13144,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13145,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13146,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13147,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13148,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13149,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13150,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13151,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13152,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13153,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13154,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13155,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13156,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13157,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13158,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13159,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13160,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13161,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13162,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13163,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13164,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13165,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13166,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13167,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13168,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13169,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13170,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13171,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13172,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13173,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13174,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13175,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13176,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13177,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13178,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13179,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13180,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13181,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13182,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13183,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13184,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13185,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13186,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13187,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13188,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13189,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13190,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13191,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13192,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13193,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
13194,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13195,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
13196,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
13197,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
13198,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
13199,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
13200,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
13201,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
13202,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13203,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13204,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13205,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13206,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13207,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13208,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13209,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13210,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13211,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13212,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13213,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13214,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13215,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13216,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13217,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13218,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13219,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13220,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13221,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13222,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13223,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13224,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13225,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13226,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13227,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13228,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13229,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13230,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13231,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13232,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13233,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13234,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13235,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13236,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13237,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13238,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13239,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13240,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13241,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13242,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13243,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13244,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13245,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13246,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13247,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13248,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13249,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13250,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13251,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13252,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13253,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13254,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13255,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13256,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13257,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13258,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13259,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13260,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13261,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13262,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13263,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13264,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13265,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13266,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13267,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13268,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13269,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13270,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13271,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13272,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13273,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13274,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13275,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13276,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13277,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13278,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13279,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13280,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13281,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13282,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13283,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13284,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13285,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13286,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13287,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13288,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13289,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13290,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13291,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13292,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13293,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13294,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13295,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13296,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13297,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13298,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13299,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13300,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",xuehe wang,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13301,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13302,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13303,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13304,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13305,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13306,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13307,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13308,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13309,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13310,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13311,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13312,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13313,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13314,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13315,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13316,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13317,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13318,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13319,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13320,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13321,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13322,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13323,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13324,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13325,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13326,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13327,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13328,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13329,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13330,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13331,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13332,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13333,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13334,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13335,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13336,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13337,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13338,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13339,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13340,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13341,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13342,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13343,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13344,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13345,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13346,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",xuehe wang,Noncooperative congestion game,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
13347,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",xuehe wang,price of anarchy,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
13348,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",xuehe wang,price of total anarchy,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
13349,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",xuehe wang,road pricing,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
13350,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13351,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",xuehe wang,traffic networks,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
13352,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",nan xiao,Noncooperative congestion game,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
13353,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",nan xiao,price of anarchy,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
13354,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",nan xiao,price of total anarchy,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
13355,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",nan xiao,road pricing,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
13356,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",nan xiao,traffic networks,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
13357,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",lihua xie,Noncooperative congestion game,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
13358,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",lihua xie,price of anarchy,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
13359,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",lihua xie,price of total anarchy,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
13360,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",lihua xie,road pricing,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
13361,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13362,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",lihua xie,traffic networks,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
13363,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",emilio frazzoli,Noncooperative congestion game,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
13364,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",emilio frazzoli,price of anarchy,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
13365,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",emilio frazzoli,price of total anarchy,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
13366,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",emilio frazzoli,road pricing,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
13367,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",emilio frazzoli,traffic networks,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
13368,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",daniela rus,Noncooperative congestion game,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
13369,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",daniela rus,price of anarchy,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
13370,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",daniela rus,price of total anarchy,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
13371,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",daniela rus,road pricing,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
13372,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13373,"Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.",daniela rus,traffic networks,2017.0,10.1109/TCNS.2016.2592678,IEEE Transactions on Control of Network Systems,Wang2017,False,,IEEE,Not available,Analysis of Price of Total Anarchy in Congestion Games via Smoothness Arguments,9510a6fe91eca796c1dcf3af349c6fae,https://ieeexplore.ieee.org/document/7515192/
13374,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
13375,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
13376,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
13377,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
13378,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",chengli zheng,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
13379,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,congestion,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
13380,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,price of anarchy,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
13381,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,heterogeneity,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
13382,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,coordination,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
13383,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13384,"This article proposes a model to analyze the transporttion networks with heterogeneous agents, who contribute to congestion differently. This is the generalization of homogeneous model. It turns out that the optimum from social planning is high dependent of the distribution of the driving technique possessed by agents in the networks, both for its mean value and variance. However, the optimum from selfish view is only dependent of the mean value of driving technique. Price of anarchy analysis displays that there is more great area to operate profitably for social planning under the heterogeneity, comparative to that under the homogeneity. Because of difficulty of technique recognization for the social planner, as a signal to coordinate selfish agents to get social optimum, charge must be changed with the distribution of the driving technique possessed by agents in the networks.",yan chen,signalling,2011.0,10.1109/CSO.2011.206,2011 Fourth International Joint Conference on Computational Sciences and Optimization,Zheng2011,False,,IEEE,Not available,Price of Anarchy in Transportation Networks with Heterogeneous Agents,198b7b2c7c0b58d4de508d9124b74992,https://ieeexplore.ieee.org/document/5957610/
13385,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13386,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13387,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13388,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13389,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13390,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13391,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13392,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",huihong liao,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13393,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13394,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13395,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13396,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13397,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13398,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13399,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13400,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13401,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",guangyuan dai,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13402,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,network,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13403,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,routing strategy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13404,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,self-routing,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13405,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",nan xiao,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13406,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,optimum,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13407,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,price of anarchy,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13408,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,upper bound,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13409,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,latency function,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13410,"Uncoordinated agents in society usually assumed to take their own optimal strategies do not always achieve the social optimum. In transportation network, travelers are assumed to choose the route that minimizes their own travel costs, which will form a Nash Equilibrium called user equilibrium where no one could be better off by changing routes in the network. This type of routing strategy named self-routing is socially suboptimal. Consequently the society has to pay a price of anarchy for the lack of coordination among travelers. In this paper we revisit the definition of price of anarchy (POA) and analyze its upper bound under different latency functions. We review some simulation results of several major cities and investigate the difference between optimum and actual system performance in the real transportation network. A numerical simulation of Sioux network is conducted based on the classical computational procedures. The results indicate that the shape of POA as a function of input flow is not diatonic but rather fluctuating. Then we propose some more insights of POA.",ruoyun chen,simulation,2012.0,10.1109/FSKD.2012.6233759,2012 9th International Conference on Fuzzy Systems and Knowledge Discovery,Liao2012,False,,IEEE,Not available,Research and simulation on the upper bound of the price of network anarchy,f9aa5256b17ef9d9605cfe30fe972bcf,https://ieeexplore.ieee.org/document/6233759/
13411,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
13412,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
13413,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
13414,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
13415,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
13416,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13417,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
13418,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
13419,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
13420,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13421,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13422,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13423,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13424,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13425,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13426,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",weixuan lin,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13427,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13428,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Generators,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13429,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,ISO,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13430,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Games,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13431,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Pricing,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13432,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Production,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13433,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Nash equilibrium,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13434,"We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, while ensuring that transmission and generator capacity constraints are met. Under the stylizing assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying market, and derive a tight bound on its price of anarchy (PoA). In addition to providing a structural characterization of a generator's market power, the PoA bound we derive reveals the possibility of a Braess paradox - that is to say, the strengthening of a network's transmission capacity can lead to an increase in the total cost of generation at a Nash equilibrium.",eilyan bitar,Computers,2017.0,10.1109/CISS.2017.7926157,2017 51st Annual Conference on Information Sciences and Systems (CISS),Lin2017,False,,IEEE,Not available,The price of anarchy in networked supply function games,54f07913d73cff09f36377cc77f64d92,
13435,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13436,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13437,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13438,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13439,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13440,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13441,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13442,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13443,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13444,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13445,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13446,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13447,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13448,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13449,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13450,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13451,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13452,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13453,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13454,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13455,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13456,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13457,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13458,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13459,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13460,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13461,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13462,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",eitan altman,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
13463,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",matthew zyskowski,Cost Density-Shaping Games,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
13464,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",matthew zyskowski,Cost Cumulant Control,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
13465,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",matthew zyskowski,Price of Anarchy,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
13466,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",matthew zyskowski,Variance of Anarchy,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
13467,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",matthew zyskowski,Telecommunications,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
13468,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",matthew zyskowski,Stochastic Differential Games,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
13469,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",matthew zyskowski,Team Optimization,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
13470,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",quanyan zhu,Cost Density-Shaping Games,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
13471,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",quanyan zhu,Cost Cumulant Control,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
13472,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13473,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",quanyan zhu,Price of Anarchy,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
13474,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",quanyan zhu,Variance of Anarchy,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
13475,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",quanyan zhu,Telecommunications,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
13476,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",quanyan zhu,Stochastic Differential Games,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
13477,"This paper introduces the Variance of Anarchy (VoA) metric to compliment existing measures of efficiency loss in dynamic games due to decentralized mechanisms. The VoA is inspired by Price of Anarchy (PoA) and Price of Information (PoI) measures that have been used previously in the literature. We propose a new design procedure for decentralized control algorithms using PoA and VoA that identifies the optimal control solution for competing agents among a family of decentralized controllers by solving an optimization of a summed PoA and VoA objective function over a parameter space. The design method is illustrated with a stochastic model for queue server dynamics and two separate optimal control problems - the first involving noncooperative agents, and the second a team. For each problem, a family of density-shaping cumulant controls is computed corresponding to a parametric target cumulant set, and the optimal chosen via this new procedure. Simulation results are provided to compare the controller to a baseline 2CC control.",quanyan zhu,Team Optimization,2013.0,10.1109/CDC.2013.6760130,52nd IEEE Conference on Decision and Control,Zyskowski2013,False,,IEEE,Not available,Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games,6a7201f0d2e9d23ec72a79027cf326a4,https://ieeexplore.ieee.org/document/6760130/
13478,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13479,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13480,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13481,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13482,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13483,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13484,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13485,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",xuehe wang,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13486,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13487,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13488,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13489,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13490,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13491,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13492,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",nan xiao,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13493,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13494,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13495,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13496,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13497,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13498,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13499,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13500,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",lihua xie,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13501,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13502,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13503,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13504,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13505,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13506,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13507,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13508,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",emilio frazzoli,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13509,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Roads,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13510,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Pricing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13511,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Probability distribution,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13512,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Sensitivity,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13513,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Nash equilibrium,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13514,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Games,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13515,"In this paper, we investigate the effect of scaled marginal-cost road pricing on the price of anarchy (POA) for noncooperative congestion games in which players are divided into several groups according to their price sensitivities. The POA is defined as the worst possible ratio between the total latency of Nash flows and that of the socially optimal flow. First, the existence and uniqueness of Nash flow is considered. For a probability distribution of price sensitivities satisfying given conditions, a road pricing scheme is designed such that POA = 1. If those given conditions are not satisfied, then it holds that POA &amp;gt; 1. Finally, we apply the results to a traffic routing problem via simulations. The numerical results show that the scaled marginal-cost road pricing reduces the total latency of the network, and the optimal POA depends on the probability distribution of price sensitivities.",daniela rus,Routing,2014.0,10.1109/CDC.2014.7040405,53rd IEEE Conference on Decision and Control,Wang2014,False,,IEEE,Not available,Analysis of price of anarchy in heterogeneous price-sensitive populations,7ddbeae5a47a05931286a71628aab6b0,https://ieeexplore.ieee.org/document/7040405/
13516,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",lihua xie,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13517,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13518,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13519,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13520,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13521,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13522,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13523,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13524,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13525,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13526,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",yufang xi,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13527,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13528,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Relays,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13529,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Pricing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13530,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Telecommunication traffic,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13531,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Oligopoly,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13532,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Cost function,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13533,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Routing,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13534,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Network topology,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13535,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Forward contracts,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13536,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Wireless networks,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13537,"We study pricing games in single-layer relay networks where the source routes traffic selfishly according to the strategic bids made by relays. Each relay's bid includes a charging function and a proposed traffic share. Relays aim to maximize their individual profit from forwarding traffic. We show that the socially optimal traffic allocation can always be induced by an equilibrium where no relay can increase its profit by unilaterally changing its bids. Inefficient equilibria arise due to the monopolistic pricing power of a superior relay. This lead to a finite price of anarchy if marginal cost functions are concave, and an unbounded price of anarchy when the marginal cost functions are convex.",edmund yeh,Spread spectrum communication,2008.0,10.1109/CISS.2008.4558654,2008 42nd Annual Conference on Information Sciences and Systems,Xi2008,False,,IEEE,Not available,Equilibria and price of anarchy in parallel relay networks with node pricing,22bb2b5802d6614d351896ad1621384a,https://ieeexplore.ieee.org/document/4558654/
13538,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13539,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",jing zhang,Optimization,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
13540,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",jing zhang,Price-of-Anarchy (PoA),2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
13541,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",jing zhang,sensitivity analysis,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
13542,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",jing zhang,traffic assignment problem,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
13543,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",jing zhang,transportation networks,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
13544,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",jing zhang,variational inequalities,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
13545,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",sepideh pourazarm,Optimization,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
13546,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",sepideh pourazarm,Price-of-Anarchy (PoA),2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
13547,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",sepideh pourazarm,sensitivity analysis,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
13548,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",sepideh pourazarm,traffic assignment problem,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
13549,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13550,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13551,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",sepideh pourazarm,transportation networks,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
13552,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",sepideh pourazarm,variational inequalities,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
13553,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",christos cassandras,Optimization,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
13554,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",christos cassandras,Price-of-Anarchy (PoA),2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
13555,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",christos cassandras,sensitivity analysis,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
13556,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",christos cassandras,traffic assignment problem,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
13557,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",christos cassandras,transportation networks,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
13558,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",christos cassandras,variational inequalities,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
13559,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",ioannis paschalidis,Optimization,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
13560,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",ioannis paschalidis,Price-of-Anarchy (PoA),2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
13561,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13562,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",ioannis paschalidis,sensitivity analysis,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
13563,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",ioannis paschalidis,traffic assignment problem,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
13564,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",ioannis paschalidis,transportation networks,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
13565,"Among the many functions a smart city must support, transportation dominates in terms of resource consumption, strain on the environment, and frustration of its citizens. We study transportation networks under two different routing policies, the commonly assumed selfish user-centric routing policy and a socially optimal system-centric one. We consider a performance metric of efficiency-the Price of Anarchy (PoA)-defined as the ratio of the total travel latency cost under selfish routing over the corresponding quantity under socially optimal routing. We develop a data-driven approach to estimate the PoA, which we subsequently use to conduct a case study using extensive actual traffic data from the Eastern Massachusetts road network. To estimate the PoA, our approach learns from data a complete model of the transportation network, including origin-destination demand and user preferences. We leverage this model to propose possible strategies to reduce the PoA and increase efficiency.",ioannis paschalidis,variational inequalities,2018.0,10.1109/JPROC.2018.2790405,Proceedings of the IEEE,Zhang2018,False,,IEEE,Not available,The Price of Anarchy in Transportation Networks: Data-Driven Evaluation and Reduction Strategies,c1b532f1e544b237fb502cd9180c3e5f,https://ieeexplore.ieee.org/document/8280563/
13566,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13567,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13568,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13569,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13570,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13571,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13572,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13573,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13574,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13575,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13576,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13577,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13578,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13579,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13580,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13581,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13582,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13583,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13584,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13585,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13586,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13587,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13588,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
13589,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
13590,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
13591,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",zaher kassas,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
13592,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,navigation,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
13593,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,signals of opportunity,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
13594,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13595,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,adaptive sensing,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
13596,"Multiple receivers with a priori knowledge about their own initial states are assumed to be dropped in an unknown environment comprising multiple signals of opportunity (SOPs) transmitters. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment, which would enable the receivers to navigate accurately with the aid of the SOPs. The receivers could command their own maneuvers and such commands are computed so to maximize the information gathered about the SOPs in a greedy fashion. Several information fusion and decision making architectures are possible. This paper studies the price of anarchy in building signal landscape maps to assess the degradation in the map quality should the receivers produce their own maps and make their own maneuver decisions versus a completely centralized approach. In addition, a hierarchical architecture is proposed in which the receivers build their own maps and make their own decisions, but share relevant information. Such architecture is shown to produce maps of comparable quality to the completely centralized approach.",todd humphreys,information fusion,2013.0,10.1109/GlobalSIP.2013.6736841,2013 IEEE Global Conference on Signal and Information Processing,Kassas2013,False,,IEEE,Not available,The price of anarchy in active signal landscape map building,78e2826e6205d7a09fc5348a0112c4c9,https://ieeexplore.ieee.org/document/6736841/
13597,"We consider in this paper a simple model for human interactions as service providers of different resources over social networks, and study the dynamics of selfish behavior of such social entities using a game-theoretic model known as binary-preference capacitated selfish replication (CSR) game. It is known that such games have an associated ordinal potential function, and hence always admit a pure-strategy Nash equilibrium (NE). We study the price of anarchy of such games, and show that it is bounded above by 3; we further provide some instances for which the price of anarchy is at least 2. We also devise a quasi-polynomial algorithm O(n2+ln D) which can find, in a distributed manner, an allocation profile that is within a constant factor of the optimal allocation, and hence of any pure-strategy Nash equilibrium of the game, where the parameters n, and D denote, respectively, the number of players, and the diameter of the network. We further show that when the underlying network has a tree structure, every globally optimal allocation is a Nash equilibrium, which can be reached in only linear time.",seyed etesami,Capacitated selfish replication game,2015.0,10.1109/CDC.2015.7402771,2015 54th IEEE Conference on Decision and Control (CDC),Etesami2015,False,,IEEE,Not available,An approximation algorithm and price of anarchy for the binary-preference capacitated selfish replication game,c2ff2ca30f60e4aaa6132bc41aa2be69,https://ieeexplore.ieee.org/document/7402771/
13598,"We consider in this paper a simple model for human interactions as service providers of different resources over social networks, and study the dynamics of selfish behavior of such social entities using a game-theoretic model known as binary-preference capacitated selfish replication (CSR) game. It is known that such games have an associated ordinal potential function, and hence always admit a pure-strategy Nash equilibrium (NE). We study the price of anarchy of such games, and show that it is bounded above by 3; we further provide some instances for which the price of anarchy is at least 2. We also devise a quasi-polynomial algorithm O(n2+ln D) which can find, in a distributed manner, an allocation profile that is within a constant factor of the optimal allocation, and hence of any pure-strategy Nash equilibrium of the game, where the parameters n, and D denote, respectively, the number of players, and the diameter of the network. We further show that when the underlying network has a tree structure, every globally optimal allocation is a Nash equilibrium, which can be reached in only linear time.",seyed etesami,pure Nash equilibrium (NE),2015.0,10.1109/CDC.2015.7402771,2015 54th IEEE Conference on Decision and Control (CDC),Etesami2015,False,,IEEE,Not available,An approximation algorithm and price of anarchy for the binary-preference capacitated selfish replication game,c2ff2ca30f60e4aaa6132bc41aa2be69,https://ieeexplore.ieee.org/document/7402771/
13599,"We consider in this paper a simple model for human interactions as service providers of different resources over social networks, and study the dynamics of selfish behavior of such social entities using a game-theoretic model known as binary-preference capacitated selfish replication (CSR) game. It is known that such games have an associated ordinal potential function, and hence always admit a pure-strategy Nash equilibrium (NE). We study the price of anarchy of such games, and show that it is bounded above by 3; we further provide some instances for which the price of anarchy is at least 2. We also devise a quasi-polynomial algorithm O(n2+ln D) which can find, in a distributed manner, an allocation profile that is within a constant factor of the optimal allocation, and hence of any pure-strategy Nash equilibrium of the game, where the parameters n, and D denote, respectively, the number of players, and the diameter of the network. We further show that when the underlying network has a tree structure, every globally optimal allocation is a Nash equilibrium, which can be reached in only linear time.",seyed etesami,potential function,2015.0,10.1109/CDC.2015.7402771,2015 54th IEEE Conference on Decision and Control (CDC),Etesami2015,False,,IEEE,Not available,An approximation algorithm and price of anarchy for the binary-preference capacitated selfish replication game,c2ff2ca30f60e4aaa6132bc41aa2be69,https://ieeexplore.ieee.org/document/7402771/
13600,"We consider in this paper a simple model for human interactions as service providers of different resources over social networks, and study the dynamics of selfish behavior of such social entities using a game-theoretic model known as binary-preference capacitated selfish replication (CSR) game. It is known that such games have an associated ordinal potential function, and hence always admit a pure-strategy Nash equilibrium (NE). We study the price of anarchy of such games, and show that it is bounded above by 3; we further provide some instances for which the price of anarchy is at least 2. We also devise a quasi-polynomial algorithm O(n2+ln D) which can find, in a distributed manner, an allocation profile that is within a constant factor of the optimal allocation, and hence of any pure-strategy Nash equilibrium of the game, where the parameters n, and D denote, respectively, the number of players, and the diameter of the network. We further show that when the underlying network has a tree structure, every globally optimal allocation is a Nash equilibrium, which can be reached in only linear time.",seyed etesami,quasi-polynomial algorithm,2015.0,10.1109/CDC.2015.7402771,2015 54th IEEE Conference on Decision and Control (CDC),Etesami2015,False,,IEEE,Not available,An approximation algorithm and price of anarchy for the binary-preference capacitated selfish replication game,c2ff2ca30f60e4aaa6132bc41aa2be69,https://ieeexplore.ieee.org/document/7402771/
13601,"We consider in this paper a simple model for human interactions as service providers of different resources over social networks, and study the dynamics of selfish behavior of such social entities using a game-theoretic model known as binary-preference capacitated selfish replication (CSR) game. It is known that such games have an associated ordinal potential function, and hence always admit a pure-strategy Nash equilibrium (NE). We study the price of anarchy of such games, and show that it is bounded above by 3; we further provide some instances for which the price of anarchy is at least 2. We also devise a quasi-polynomial algorithm O(n2+ln D) which can find, in a distributed manner, an allocation profile that is within a constant factor of the optimal allocation, and hence of any pure-strategy Nash equilibrium of the game, where the parameters n, and D denote, respectively, the number of players, and the diameter of the network. We further show that when the underlying network has a tree structure, every globally optimal allocation is a Nash equilibrium, which can be reached in only linear time.",seyed etesami,price of anarchy,2015.0,10.1109/CDC.2015.7402771,2015 54th IEEE Conference on Decision and Control (CDC),Etesami2015,False,,IEEE,Not available,An approximation algorithm and price of anarchy for the binary-preference capacitated selfish replication game,c2ff2ca30f60e4aaa6132bc41aa2be69,https://ieeexplore.ieee.org/document/7402771/
13602,"We consider in this paper a simple model for human interactions as service providers of different resources over social networks, and study the dynamics of selfish behavior of such social entities using a game-theoretic model known as binary-preference capacitated selfish replication (CSR) game. It is known that such games have an associated ordinal potential function, and hence always admit a pure-strategy Nash equilibrium (NE). We study the price of anarchy of such games, and show that it is bounded above by 3; we further provide some instances for which the price of anarchy is at least 2. We also devise a quasi-polynomial algorithm O(n2+ln D) which can find, in a distributed manner, an allocation profile that is within a constant factor of the optimal allocation, and hence of any pure-strategy Nash equilibrium of the game, where the parameters n, and D denote, respectively, the number of players, and the diameter of the network. We further show that when the underlying network has a tree structure, every globally optimal allocation is a Nash equilibrium, which can be reached in only linear time.",seyed etesami,optimal allocation,2015.0,10.1109/CDC.2015.7402771,2015 54th IEEE Conference on Decision and Control (CDC),Etesami2015,False,,IEEE,Not available,An approximation algorithm and price of anarchy for the binary-preference capacitated selfish replication game,c2ff2ca30f60e4aaa6132bc41aa2be69,https://ieeexplore.ieee.org/document/7402771/
13603,"We consider in this paper a simple model for human interactions as service providers of different resources over social networks, and study the dynamics of selfish behavior of such social entities using a game-theoretic model known as binary-preference capacitated selfish replication (CSR) game. It is known that such games have an associated ordinal potential function, and hence always admit a pure-strategy Nash equilibrium (NE). We study the price of anarchy of such games, and show that it is bounded above by 3; we further provide some instances for which the price of anarchy is at least 2. We also devise a quasi-polynomial algorithm O(n2+ln D) which can find, in a distributed manner, an allocation profile that is within a constant factor of the optimal allocation, and hence of any pure-strategy Nash equilibrium of the game, where the parameters n, and D denote, respectively, the number of players, and the diameter of the network. We further show that when the underlying network has a tree structure, every globally optimal allocation is a Nash equilibrium, which can be reached in only linear time.",tamer ba&#x015f;ar,Capacitated selfish replication game,2015.0,10.1109/CDC.2015.7402771,2015 54th IEEE Conference on Decision and Control (CDC),Etesami2015,False,,IEEE,Not available,An approximation algorithm and price of anarchy for the binary-preference capacitated selfish replication game,c2ff2ca30f60e4aaa6132bc41aa2be69,https://ieeexplore.ieee.org/document/7402771/
13604,"We consider in this paper a simple model for human interactions as service providers of different resources over social networks, and study the dynamics of selfish behavior of such social entities using a game-theoretic model known as binary-preference capacitated selfish replication (CSR) game. It is known that such games have an associated ordinal potential function, and hence always admit a pure-strategy Nash equilibrium (NE). We study the price of anarchy of such games, and show that it is bounded above by 3; we further provide some instances for which the price of anarchy is at least 2. We also devise a quasi-polynomial algorithm O(n2+ln D) which can find, in a distributed manner, an allocation profile that is within a constant factor of the optimal allocation, and hence of any pure-strategy Nash equilibrium of the game, where the parameters n, and D denote, respectively, the number of players, and the diameter of the network. We further show that when the underlying network has a tree structure, every globally optimal allocation is a Nash equilibrium, which can be reached in only linear time.",tamer ba&#x015f;ar,pure Nash equilibrium (NE),2015.0,10.1109/CDC.2015.7402771,2015 54th IEEE Conference on Decision and Control (CDC),Etesami2015,False,,IEEE,Not available,An approximation algorithm and price of anarchy for the binary-preference capacitated selfish replication game,c2ff2ca30f60e4aaa6132bc41aa2be69,https://ieeexplore.ieee.org/document/7402771/
13605,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13606,"We consider in this paper a simple model for human interactions as service providers of different resources over social networks, and study the dynamics of selfish behavior of such social entities using a game-theoretic model known as binary-preference capacitated selfish replication (CSR) game. It is known that such games have an associated ordinal potential function, and hence always admit a pure-strategy Nash equilibrium (NE). We study the price of anarchy of such games, and show that it is bounded above by 3; we further provide some instances for which the price of anarchy is at least 2. We also devise a quasi-polynomial algorithm O(n2+ln D) which can find, in a distributed manner, an allocation profile that is within a constant factor of the optimal allocation, and hence of any pure-strategy Nash equilibrium of the game, where the parameters n, and D denote, respectively, the number of players, and the diameter of the network. We further show that when the underlying network has a tree structure, every globally optimal allocation is a Nash equilibrium, which can be reached in only linear time.",tamer ba&#x015f;ar,potential function,2015.0,10.1109/CDC.2015.7402771,2015 54th IEEE Conference on Decision and Control (CDC),Etesami2015,False,,IEEE,Not available,An approximation algorithm and price of anarchy for the binary-preference capacitated selfish replication game,c2ff2ca30f60e4aaa6132bc41aa2be69,https://ieeexplore.ieee.org/document/7402771/
13607,"We consider in this paper a simple model for human interactions as service providers of different resources over social networks, and study the dynamics of selfish behavior of such social entities using a game-theoretic model known as binary-preference capacitated selfish replication (CSR) game. It is known that such games have an associated ordinal potential function, and hence always admit a pure-strategy Nash equilibrium (NE). We study the price of anarchy of such games, and show that it is bounded above by 3; we further provide some instances for which the price of anarchy is at least 2. We also devise a quasi-polynomial algorithm O(n2+ln D) which can find, in a distributed manner, an allocation profile that is within a constant factor of the optimal allocation, and hence of any pure-strategy Nash equilibrium of the game, where the parameters n, and D denote, respectively, the number of players, and the diameter of the network. We further show that when the underlying network has a tree structure, every globally optimal allocation is a Nash equilibrium, which can be reached in only linear time.",tamer ba&#x015f;ar,quasi-polynomial algorithm,2015.0,10.1109/CDC.2015.7402771,2015 54th IEEE Conference on Decision and Control (CDC),Etesami2015,False,,IEEE,Not available,An approximation algorithm and price of anarchy for the binary-preference capacitated selfish replication game,c2ff2ca30f60e4aaa6132bc41aa2be69,https://ieeexplore.ieee.org/document/7402771/
13608,"We consider in this paper a simple model for human interactions as service providers of different resources over social networks, and study the dynamics of selfish behavior of such social entities using a game-theoretic model known as binary-preference capacitated selfish replication (CSR) game. It is known that such games have an associated ordinal potential function, and hence always admit a pure-strategy Nash equilibrium (NE). We study the price of anarchy of such games, and show that it is bounded above by 3; we further provide some instances for which the price of anarchy is at least 2. We also devise a quasi-polynomial algorithm O(n2+ln D) which can find, in a distributed manner, an allocation profile that is within a constant factor of the optimal allocation, and hence of any pure-strategy Nash equilibrium of the game, where the parameters n, and D denote, respectively, the number of players, and the diameter of the network. We further show that when the underlying network has a tree structure, every globally optimal allocation is a Nash equilibrium, which can be reached in only linear time.",tamer ba&#x015f;ar,price of anarchy,2015.0,10.1109/CDC.2015.7402771,2015 54th IEEE Conference on Decision and Control (CDC),Etesami2015,False,,IEEE,Not available,An approximation algorithm and price of anarchy for the binary-preference capacitated selfish replication game,c2ff2ca30f60e4aaa6132bc41aa2be69,https://ieeexplore.ieee.org/document/7402771/
13609,"We consider in this paper a simple model for human interactions as service providers of different resources over social networks, and study the dynamics of selfish behavior of such social entities using a game-theoretic model known as binary-preference capacitated selfish replication (CSR) game. It is known that such games have an associated ordinal potential function, and hence always admit a pure-strategy Nash equilibrium (NE). We study the price of anarchy of such games, and show that it is bounded above by 3; we further provide some instances for which the price of anarchy is at least 2. We also devise a quasi-polynomial algorithm O(n2+ln D) which can find, in a distributed manner, an allocation profile that is within a constant factor of the optimal allocation, and hence of any pure-strategy Nash equilibrium of the game, where the parameters n, and D denote, respectively, the number of players, and the diameter of the network. We further show that when the underlying network has a tree structure, every globally optimal allocation is a Nash equilibrium, which can be reached in only linear time.",tamer ba&#x015f;ar,optimal allocation,2015.0,10.1109/CDC.2015.7402771,2015 54th IEEE Conference on Decision and Control (CDC),Etesami2015,False,,IEEE,Not available,An approximation algorithm and price of anarchy for the binary-preference capacitated selfish replication game,c2ff2ca30f60e4aaa6132bc41aa2be69,https://ieeexplore.ieee.org/document/7402771/
13610,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",paul dutting,mechanism design,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
13611,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",paul dutting,posted prices,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
13612,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",paul dutting,price of anarchy,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
13613,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",paul dutting,prophet inequalities,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
13614,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",paul dutting,smoothness,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
13615,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",michal feldman,mechanism design,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
13616,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13617,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",michal feldman,posted prices,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
13618,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",michal feldman,price of anarchy,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
13619,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",michal feldman,prophet inequalities,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
13620,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",michal feldman,smoothness,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
13621,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",thomas kesselheim,mechanism design,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
13622,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",thomas kesselheim,posted prices,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
13623,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",thomas kesselheim,price of anarchy,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
13624,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",thomas kesselheim,prophet inequalities,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
13625,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",thomas kesselheim,smoothness,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
13626,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",brendan lucier,mechanism design,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
13627,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13628,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",brendan lucier,posted prices,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
13629,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",brendan lucier,price of anarchy,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
13630,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",brendan lucier,prophet inequalities,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
13631,"We present a general framework for stochastic online maximization problems with combinatorial feasibility constraints. The framework establishes prophet inequalities by constructing price-based online approximation algorithms, a natural extension of threshold algorithms for settings beyond binary selection. Our analysis takes the form of an extension theorem: we derive sufficient conditions on prices when all weights are known in advance, then prove that the resulting approximation guarantees extend directly to stochastic settings. Our framework unifies and simplifies much of the existing literature on prophet inequalities and posted price mechanisms, and is used to derive new and improved results for combinatorial markets (with and without complements), multi-dimensional matroids, and sparse packing problems. Finally, we highlight a surprising connection between the smoothness framework for bounding the price of anarchy of mechanisms and our framework, and show that many smooth mechanisms can be recast as posted price mechanisms with comparable performance guarantees.",brendan lucier,smoothness,2017.0,10.1109/FOCS.2017.56,2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS),Dütting2017,False,,IEEE,Not available,Prophet Inequalities Made Easy: Stochastic Optimization by Pricing Non-Stochastic Inputs,9e40013af6c3fa9d28d89bf3c1c23f21,https://ieeexplore.ieee.org/document/8104088/
13632,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",vladimir fux,Vehicles,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
13633,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",vladimir fux,Games,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
13634,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",vladimir fux,Roads,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
13635,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",vladimir fux,Pricing,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
13636,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",vladimir fux,Bandwidth,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
13637,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",vladimir fux,Wireless networks,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
13638,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13639,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",vladimir fux,Equations,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
13640,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",patrick maille,Vehicles,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
13641,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",patrick maille,Games,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
13642,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",patrick maille,Roads,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
13643,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",patrick maille,Pricing,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
13644,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",patrick maille,Bandwidth,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
13645,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",patrick maille,Wireless networks,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
13646,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",patrick maille,Equations,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
13647,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",matteo cesana,Vehicles,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
13648,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",matteo cesana,Games,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
13649,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13650,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",matteo cesana,Roads,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
13651,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",matteo cesana,Pricing,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
13652,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",matteo cesana,Bandwidth,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
13653,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",matteo cesana,Wireless networks,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
13654,"Vehicular networks, besides supporting safety-oriented applications, are nowadays expected to provide effective communication infrastructure also for supporting leisure-oriented application including content sharing, gaming and Internet access on the move. This work focuses on Vehicle to Infrastructure (V2I) scenarios, where multiple content providers own a physical infrastructure of Road Side Units (RSUs) which they use to sell contents to moving vehicles. Content provider/RSU owners compete by adapting their pricing strategies with the selfish objective to maximize their own revenues. We study the economics of the price competition between the providers by resorting to game theoretic tools. Namely, we formalize a simultaneous price game among the operators further studying the existence of Nash equilibria and their related quality in terms of Price of Anarchy and Price of Stability. The proposed game model is finally used to assess the impact onto the game equilibra of several practical factors including the vehicles' willingness to pay, the traffic densities, and the configuration of the physical networks of RSUs.",matteo cesana,Equations,2014.0,10.1109/IFIPNetworking.2014.6857112,2014 IFIP Networking Conference,Fux2014,False,,IEEE,Not available,Price competition between road side units operators in vehicular networks,8e1c28fe0e0ada61813aa6a60d09a57d,
13655,"In this paper, we consider a cognitive radio network where multiple heterogenous secondary users (SUs) compete for transmissions on idle primary channels. We model this as a singleton congestion game, where the probability for an SU to successfully access a channel decreases with the number of SUs selecting the same channel. In particular, we consider player-specific payoffs that depend not only on the shares of the channel but also on different preference constants. Such system can be modeled as a congestion game, and we study the price of anarchy (PoA) for four families of such a game: identical, player-specific symmetric, resource-specific symmetric, and asymmetric games. We characterize the worst-case PoA in terms of the number of SUs and channels, and illustrate the network scenarios under which the worse case performance is reached. We further illustrate the PoA results with two Medium Access Control (MAC) schemes: uniform MAC and slotted Aloha. For both cases, we observe that the average performance of the game equilibrium is better than the worst-case PoA. Our study sheds light on how to design stable systems with smaller efficiency loss of the equilibrium.",lok law,Cognitive radio,2012.0,10.1109/TWC.2012.083112.120371,IEEE Transactions on Wireless Communications,Law2012,False,,IEEE,Not available,Price of Anarchy for Congestion Games in Cognitive Radio Networks,d78287bf43af78c169dac2e1b5572756,https://ieeexplore.ieee.org/document/6294502/
13656,"In this paper, we consider a cognitive radio network where multiple heterogenous secondary users (SUs) compete for transmissions on idle primary channels. We model this as a singleton congestion game, where the probability for an SU to successfully access a channel decreases with the number of SUs selecting the same channel. In particular, we consider player-specific payoffs that depend not only on the shares of the channel but also on different preference constants. Such system can be modeled as a congestion game, and we study the price of anarchy (PoA) for four families of such a game: identical, player-specific symmetric, resource-specific symmetric, and asymmetric games. We characterize the worst-case PoA in terms of the number of SUs and channels, and illustrate the network scenarios under which the worse case performance is reached. We further illustrate the PoA results with two Medium Access Control (MAC) schemes: uniform MAC and slotted Aloha. For both cases, we observe that the average performance of the game equilibrium is better than the worst-case PoA. Our study sheds light on how to design stable systems with smaller efficiency loss of the equilibrium.",lok law,spectrum sharing,2012.0,10.1109/TWC.2012.083112.120371,IEEE Transactions on Wireless Communications,Law2012,False,,IEEE,Not available,Price of Anarchy for Congestion Games in Cognitive Radio Networks,d78287bf43af78c169dac2e1b5572756,https://ieeexplore.ieee.org/document/6294502/
13657,"In this paper, we consider a cognitive radio network where multiple heterogenous secondary users (SUs) compete for transmissions on idle primary channels. We model this as a singleton congestion game, where the probability for an SU to successfully access a channel decreases with the number of SUs selecting the same channel. In particular, we consider player-specific payoffs that depend not only on the shares of the channel but also on different preference constants. Such system can be modeled as a congestion game, and we study the price of anarchy (PoA) for four families of such a game: identical, player-specific symmetric, resource-specific symmetric, and asymmetric games. We characterize the worst-case PoA in terms of the number of SUs and channels, and illustrate the network scenarios under which the worse case performance is reached. We further illustrate the PoA results with two Medium Access Control (MAC) schemes: uniform MAC and slotted Aloha. For both cases, we observe that the average performance of the game equilibrium is better than the worst-case PoA. Our study sheds light on how to design stable systems with smaller efficiency loss of the equilibrium.",lok law,congestion game,2012.0,10.1109/TWC.2012.083112.120371,IEEE Transactions on Wireless Communications,Law2012,False,,IEEE,Not available,Price of Anarchy for Congestion Games in Cognitive Radio Networks,d78287bf43af78c169dac2e1b5572756,https://ieeexplore.ieee.org/document/6294502/
13658,"In this paper, we consider a cognitive radio network where multiple heterogenous secondary users (SUs) compete for transmissions on idle primary channels. We model this as a singleton congestion game, where the probability for an SU to successfully access a channel decreases with the number of SUs selecting the same channel. In particular, we consider player-specific payoffs that depend not only on the shares of the channel but also on different preference constants. Such system can be modeled as a congestion game, and we study the price of anarchy (PoA) for four families of such a game: identical, player-specific symmetric, resource-specific symmetric, and asymmetric games. We characterize the worst-case PoA in terms of the number of SUs and channels, and illustrate the network scenarios under which the worse case performance is reached. We further illustrate the PoA results with two Medium Access Control (MAC) schemes: uniform MAC and slotted Aloha. For both cases, we observe that the average performance of the game equilibrium is better than the worst-case PoA. Our study sheds light on how to design stable systems with smaller efficiency loss of the equilibrium.",lok law,price of anarchy,2012.0,10.1109/TWC.2012.083112.120371,IEEE Transactions on Wireless Communications,Law2012,False,,IEEE,Not available,Price of Anarchy for Congestion Games in Cognitive Radio Networks,d78287bf43af78c169dac2e1b5572756,https://ieeexplore.ieee.org/document/6294502/
13659,"In this paper, we consider a cognitive radio network where multiple heterogenous secondary users (SUs) compete for transmissions on idle primary channels. We model this as a singleton congestion game, where the probability for an SU to successfully access a channel decreases with the number of SUs selecting the same channel. In particular, we consider player-specific payoffs that depend not only on the shares of the channel but also on different preference constants. Such system can be modeled as a congestion game, and we study the price of anarchy (PoA) for four families of such a game: identical, player-specific symmetric, resource-specific symmetric, and asymmetric games. We characterize the worst-case PoA in terms of the number of SUs and channels, and illustrate the network scenarios under which the worse case performance is reached. We further illustrate the PoA results with two Medium Access Control (MAC) schemes: uniform MAC and slotted Aloha. For both cases, we observe that the average performance of the game equilibrium is better than the worst-case PoA. Our study sheds light on how to design stable systems with smaller efficiency loss of the equilibrium.",jianwei huang,Cognitive radio,2012.0,10.1109/TWC.2012.083112.120371,IEEE Transactions on Wireless Communications,Law2012,False,,IEEE,Not available,Price of Anarchy for Congestion Games in Cognitive Radio Networks,d78287bf43af78c169dac2e1b5572756,https://ieeexplore.ieee.org/document/6294502/
13660,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",emilio frazzoli,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13661,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13662,"In this paper, we consider a cognitive radio network where multiple heterogenous secondary users (SUs) compete for transmissions on idle primary channels. We model this as a singleton congestion game, where the probability for an SU to successfully access a channel decreases with the number of SUs selecting the same channel. In particular, we consider player-specific payoffs that depend not only on the shares of the channel but also on different preference constants. Such system can be modeled as a congestion game, and we study the price of anarchy (PoA) for four families of such a game: identical, player-specific symmetric, resource-specific symmetric, and asymmetric games. We characterize the worst-case PoA in terms of the number of SUs and channels, and illustrate the network scenarios under which the worse case performance is reached. We further illustrate the PoA results with two Medium Access Control (MAC) schemes: uniform MAC and slotted Aloha. For both cases, we observe that the average performance of the game equilibrium is better than the worst-case PoA. Our study sheds light on how to design stable systems with smaller efficiency loss of the equilibrium.",jianwei huang,spectrum sharing,2012.0,10.1109/TWC.2012.083112.120371,IEEE Transactions on Wireless Communications,Law2012,False,,IEEE,Not available,Price of Anarchy for Congestion Games in Cognitive Radio Networks,d78287bf43af78c169dac2e1b5572756,https://ieeexplore.ieee.org/document/6294502/
13663,"In this paper, we consider a cognitive radio network where multiple heterogenous secondary users (SUs) compete for transmissions on idle primary channels. We model this as a singleton congestion game, where the probability for an SU to successfully access a channel decreases with the number of SUs selecting the same channel. In particular, we consider player-specific payoffs that depend not only on the shares of the channel but also on different preference constants. Such system can be modeled as a congestion game, and we study the price of anarchy (PoA) for four families of such a game: identical, player-specific symmetric, resource-specific symmetric, and asymmetric games. We characterize the worst-case PoA in terms of the number of SUs and channels, and illustrate the network scenarios under which the worse case performance is reached. We further illustrate the PoA results with two Medium Access Control (MAC) schemes: uniform MAC and slotted Aloha. For both cases, we observe that the average performance of the game equilibrium is better than the worst-case PoA. Our study sheds light on how to design stable systems with smaller efficiency loss of the equilibrium.",jianwei huang,congestion game,2012.0,10.1109/TWC.2012.083112.120371,IEEE Transactions on Wireless Communications,Law2012,False,,IEEE,Not available,Price of Anarchy for Congestion Games in Cognitive Radio Networks,d78287bf43af78c169dac2e1b5572756,https://ieeexplore.ieee.org/document/6294502/
13664,"In this paper, we consider a cognitive radio network where multiple heterogenous secondary users (SUs) compete for transmissions on idle primary channels. We model this as a singleton congestion game, where the probability for an SU to successfully access a channel decreases with the number of SUs selecting the same channel. In particular, we consider player-specific payoffs that depend not only on the shares of the channel but also on different preference constants. Such system can be modeled as a congestion game, and we study the price of anarchy (PoA) for four families of such a game: identical, player-specific symmetric, resource-specific symmetric, and asymmetric games. We characterize the worst-case PoA in terms of the number of SUs and channels, and illustrate the network scenarios under which the worse case performance is reached. We further illustrate the PoA results with two Medium Access Control (MAC) schemes: uniform MAC and slotted Aloha. For both cases, we observe that the average performance of the game equilibrium is better than the worst-case PoA. Our study sheds light on how to design stable systems with smaller efficiency loss of the equilibrium.",jianwei huang,price of anarchy,2012.0,10.1109/TWC.2012.083112.120371,IEEE Transactions on Wireless Communications,Law2012,False,,IEEE,Not available,Price of Anarchy for Congestion Games in Cognitive Radio Networks,d78287bf43af78c169dac2e1b5572756,https://ieeexplore.ieee.org/document/6294502/
13665,"In this paper, we consider a cognitive radio network where multiple heterogenous secondary users (SUs) compete for transmissions on idle primary channels. We model this as a singleton congestion game, where the probability for an SU to successfully access a channel decreases with the number of SUs selecting the same channel. In particular, we consider player-specific payoffs that depend not only on the shares of the channel but also on different preference constants. Such system can be modeled as a congestion game, and we study the price of anarchy (PoA) for four families of such a game: identical, player-specific symmetric, resource-specific symmetric, and asymmetric games. We characterize the worst-case PoA in terms of the number of SUs and channels, and illustrate the network scenarios under which the worse case performance is reached. We further illustrate the PoA results with two Medium Access Control (MAC) schemes: uniform MAC and slotted Aloha. For both cases, we observe that the average performance of the game equilibrium is better than the worst-case PoA. Our study sheds light on how to design stable systems with smaller efficiency loss of the equilibrium.",mingyan liu,Cognitive radio,2012.0,10.1109/TWC.2012.083112.120371,IEEE Transactions on Wireless Communications,Law2012,False,,IEEE,Not available,Price of Anarchy for Congestion Games in Cognitive Radio Networks,d78287bf43af78c169dac2e1b5572756,https://ieeexplore.ieee.org/document/6294502/
13666,"In this paper, we consider a cognitive radio network where multiple heterogenous secondary users (SUs) compete for transmissions on idle primary channels. We model this as a singleton congestion game, where the probability for an SU to successfully access a channel decreases with the number of SUs selecting the same channel. In particular, we consider player-specific payoffs that depend not only on the shares of the channel but also on different preference constants. Such system can be modeled as a congestion game, and we study the price of anarchy (PoA) for four families of such a game: identical, player-specific symmetric, resource-specific symmetric, and asymmetric games. We characterize the worst-case PoA in terms of the number of SUs and channels, and illustrate the network scenarios under which the worse case performance is reached. We further illustrate the PoA results with two Medium Access Control (MAC) schemes: uniform MAC and slotted Aloha. For both cases, we observe that the average performance of the game equilibrium is better than the worst-case PoA. Our study sheds light on how to design stable systems with smaller efficiency loss of the equilibrium.",mingyan liu,spectrum sharing,2012.0,10.1109/TWC.2012.083112.120371,IEEE Transactions on Wireless Communications,Law2012,False,,IEEE,Not available,Price of Anarchy for Congestion Games in Cognitive Radio Networks,d78287bf43af78c169dac2e1b5572756,https://ieeexplore.ieee.org/document/6294502/
13667,"In this paper, we consider a cognitive radio network where multiple heterogenous secondary users (SUs) compete for transmissions on idle primary channels. We model this as a singleton congestion game, where the probability for an SU to successfully access a channel decreases with the number of SUs selecting the same channel. In particular, we consider player-specific payoffs that depend not only on the shares of the channel but also on different preference constants. Such system can be modeled as a congestion game, and we study the price of anarchy (PoA) for four families of such a game: identical, player-specific symmetric, resource-specific symmetric, and asymmetric games. We characterize the worst-case PoA in terms of the number of SUs and channels, and illustrate the network scenarios under which the worse case performance is reached. We further illustrate the PoA results with two Medium Access Control (MAC) schemes: uniform MAC and slotted Aloha. For both cases, we observe that the average performance of the game equilibrium is better than the worst-case PoA. Our study sheds light on how to design stable systems with smaller efficiency loss of the equilibrium.",mingyan liu,congestion game,2012.0,10.1109/TWC.2012.083112.120371,IEEE Transactions on Wireless Communications,Law2012,False,,IEEE,Not available,Price of Anarchy for Congestion Games in Cognitive Radio Networks,d78287bf43af78c169dac2e1b5572756,https://ieeexplore.ieee.org/document/6294502/
13668,"In this paper, we consider a cognitive radio network where multiple heterogenous secondary users (SUs) compete for transmissions on idle primary channels. We model this as a singleton congestion game, where the probability for an SU to successfully access a channel decreases with the number of SUs selecting the same channel. In particular, we consider player-specific payoffs that depend not only on the shares of the channel but also on different preference constants. Such system can be modeled as a congestion game, and we study the price of anarchy (PoA) for four families of such a game: identical, player-specific symmetric, resource-specific symmetric, and asymmetric games. We characterize the worst-case PoA in terms of the number of SUs and channels, and illustrate the network scenarios under which the worse case performance is reached. We further illustrate the PoA results with two Medium Access Control (MAC) schemes: uniform MAC and slotted Aloha. For both cases, we observe that the average performance of the game equilibrium is better than the worst-case PoA. Our study sheds light on how to design stable systems with smaller efficiency loss of the equilibrium.",mingyan liu,price of anarchy,2012.0,10.1109/TWC.2012.083112.120371,IEEE Transactions on Wireless Communications,Law2012,False,,IEEE,Not available,Price of Anarchy for Congestion Games in Cognitive Radio Networks,d78287bf43af78c169dac2e1b5572756,https://ieeexplore.ieee.org/document/6294502/
13669,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",jing zhang,Transportation networks,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
13670,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",jing zhang,variational inequalities,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
13671,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",jing zhang,price of anarchy,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
13672,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13673,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",jing zhang,smart cities,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
13674,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",jing zhang,optimization,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
13675,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",sepideh pourazarm,Transportation networks,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
13676,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",sepideh pourazarm,variational inequalities,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
13677,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",sepideh pourazarm,price of anarchy,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
13678,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",sepideh pourazarm,smart cities,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
13679,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",sepideh pourazarm,optimization,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
13680,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",christos cassandras,Transportation networks,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
13681,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",christos cassandras,variational inequalities,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
13682,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",christos cassandras,price of anarchy,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
13683,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks.,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13684,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",christos cassandras,smart cities,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
13685,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",christos cassandras,optimization,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
13686,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",ioannis paschalidis,Transportation networks,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
13687,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",ioannis paschalidis,variational inequalities,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
13688,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",ioannis paschalidis,price of anarchy,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
13689,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",ioannis paschalidis,smart cities,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
13690,"We consider a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we convert the speed data to flow data and estimate the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulate appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. Then, we formulate a system-optimum problem in order to find socially optimal flows for the network. We investigate the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city.",ioannis paschalidis,optimization,2016.0,10.1109/CDC.2016.7798364,2016 IEEE 55th Conference on Decision and Control (CDC),Zhang2016,False,,IEEE,Not available,The price of anarchy in transportation networks by estimating user cost functions from actual traffic data,18e4404e9e31cc35d23dde08a80cfeb8,https://ieeexplore.ieee.org/document/7798364/
13691,"In this letter, uncertainty in users' network selection is modeled by a Markov chain. In the presence of such uncertainty, the price competition game of wireless local area network (WLAN) service providers (SPs) is analyzed and the existence of Bayesian Nash equilibrium is proved. Using the price of anarchy as a metric of efficiency for social welfare maximization, it is shown that an increase in competition does not result in significant losses in efficiency. Compared to a monopoly, an unregulated duopoly of WLAN SPs is recommended as it results in a more equitable distribution of surplus amongst the SPs and the users.",abhinav kumar,Price competition,2013.0,10.1109/LCOMM.2013.020513.122647,IEEE Communications Letters,Kumar2013,False,,IEEE,Not available,WLAN Service Providers' Price Competition with Uncertainty in User Demand,0b320243d4678b542414fbd9dd2aeab1,https://ieeexplore.ieee.org/document/6459501/
13692,"In this letter, uncertainty in users' network selection is modeled by a Markov chain. In the presence of such uncertainty, the price competition game of wireless local area network (WLAN) service providers (SPs) is analyzed and the existence of Bayesian Nash equilibrium is proved. Using the price of anarchy as a metric of efficiency for social welfare maximization, it is shown that an increase in competition does not result in significant losses in efficiency. Compared to a monopoly, an unregulated duopoly of WLAN SPs is recommended as it results in a more equitable distribution of surplus amongst the SPs and the users.",abhinav kumar,price of anarchy (PoA),2013.0,10.1109/LCOMM.2013.020513.122647,IEEE Communications Letters,Kumar2013,False,,IEEE,Not available,WLAN Service Providers' Price Competition with Uncertainty in User Demand,0b320243d4678b542414fbd9dd2aeab1,https://ieeexplore.ieee.org/document/6459501/
13693,"In this letter, uncertainty in users' network selection is modeled by a Markov chain. In the presence of such uncertainty, the price competition game of wireless local area network (WLAN) service providers (SPs) is analyzed and the existence of Bayesian Nash equilibrium is proved. Using the price of anarchy as a metric of efficiency for social welfare maximization, it is shown that an increase in competition does not result in significant losses in efficiency. Compared to a monopoly, an unregulated duopoly of WLAN SPs is recommended as it results in a more equitable distribution of surplus amongst the SPs and the users.",abhinav kumar,service provider (SP),2013.0,10.1109/LCOMM.2013.020513.122647,IEEE Communications Letters,Kumar2013,False,,IEEE,Not available,WLAN Service Providers' Price Competition with Uncertainty in User Demand,0b320243d4678b542414fbd9dd2aeab1,https://ieeexplore.ieee.org/document/6459501/
13694,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13695,"In this letter, uncertainty in users' network selection is modeled by a Markov chain. In the presence of such uncertainty, the price competition game of wireless local area network (WLAN) service providers (SPs) is analyzed and the existence of Bayesian Nash equilibrium is proved. Using the price of anarchy as a metric of efficiency for social welfare maximization, it is shown that an increase in competition does not result in significant losses in efficiency. Compared to a monopoly, an unregulated duopoly of WLAN SPs is recommended as it results in a more equitable distribution of surplus amongst the SPs and the users.",abhinav kumar,wireless local area network (WLAN),2013.0,10.1109/LCOMM.2013.020513.122647,IEEE Communications Letters,Kumar2013,False,,IEEE,Not available,WLAN Service Providers' Price Competition with Uncertainty in User Demand,0b320243d4678b542414fbd9dd2aeab1,https://ieeexplore.ieee.org/document/6459501/
13696,"In this letter, uncertainty in users' network selection is modeled by a Markov chain. In the presence of such uncertainty, the price competition game of wireless local area network (WLAN) service providers (SPs) is analyzed and the existence of Bayesian Nash equilibrium is proved. Using the price of anarchy as a metric of efficiency for social welfare maximization, it is shown that an increase in competition does not result in significant losses in efficiency. Compared to a monopoly, an unregulated duopoly of WLAN SPs is recommended as it results in a more equitable distribution of surplus amongst the SPs and the users.",ranjan mallik,Price competition,2013.0,10.1109/LCOMM.2013.020513.122647,IEEE Communications Letters,Kumar2013,False,,IEEE,Not available,WLAN Service Providers' Price Competition with Uncertainty in User Demand,0b320243d4678b542414fbd9dd2aeab1,https://ieeexplore.ieee.org/document/6459501/
13697,"In this letter, uncertainty in users' network selection is modeled by a Markov chain. In the presence of such uncertainty, the price competition game of wireless local area network (WLAN) service providers (SPs) is analyzed and the existence of Bayesian Nash equilibrium is proved. Using the price of anarchy as a metric of efficiency for social welfare maximization, it is shown that an increase in competition does not result in significant losses in efficiency. Compared to a monopoly, an unregulated duopoly of WLAN SPs is recommended as it results in a more equitable distribution of surplus amongst the SPs and the users.",ranjan mallik,price of anarchy (PoA),2013.0,10.1109/LCOMM.2013.020513.122647,IEEE Communications Letters,Kumar2013,False,,IEEE,Not available,WLAN Service Providers' Price Competition with Uncertainty in User Demand,0b320243d4678b542414fbd9dd2aeab1,https://ieeexplore.ieee.org/document/6459501/
13698,"In this letter, uncertainty in users' network selection is modeled by a Markov chain. In the presence of such uncertainty, the price competition game of wireless local area network (WLAN) service providers (SPs) is analyzed and the existence of Bayesian Nash equilibrium is proved. Using the price of anarchy as a metric of efficiency for social welfare maximization, it is shown that an increase in competition does not result in significant losses in efficiency. Compared to a monopoly, an unregulated duopoly of WLAN SPs is recommended as it results in a more equitable distribution of surplus amongst the SPs and the users.",ranjan mallik,service provider (SP),2013.0,10.1109/LCOMM.2013.020513.122647,IEEE Communications Letters,Kumar2013,False,,IEEE,Not available,WLAN Service Providers' Price Competition with Uncertainty in User Demand,0b320243d4678b542414fbd9dd2aeab1,https://ieeexplore.ieee.org/document/6459501/
13699,"In this letter, uncertainty in users' network selection is modeled by a Markov chain. In the presence of such uncertainty, the price competition game of wireless local area network (WLAN) service providers (SPs) is analyzed and the existence of Bayesian Nash equilibrium is proved. Using the price of anarchy as a metric of efficiency for social welfare maximization, it is shown that an increase in competition does not result in significant losses in efficiency. Compared to a monopoly, an unregulated duopoly of WLAN SPs is recommended as it results in a more equitable distribution of surplus amongst the SPs and the users.",ranjan mallik,wireless local area network (WLAN),2013.0,10.1109/LCOMM.2013.020513.122647,IEEE Communications Letters,Kumar2013,False,,IEEE,Not available,WLAN Service Providers' Price Competition with Uncertainty in User Demand,0b320243d4678b542414fbd9dd2aeab1,https://ieeexplore.ieee.org/document/6459501/
13700,"In this letter, uncertainty in users' network selection is modeled by a Markov chain. In the presence of such uncertainty, the price competition game of wireless local area network (WLAN) service providers (SPs) is analyzed and the existence of Bayesian Nash equilibrium is proved. Using the price of anarchy as a metric of efficiency for social welfare maximization, it is shown that an increase in competition does not result in significant losses in efficiency. Compared to a monopoly, an unregulated duopoly of WLAN SPs is recommended as it results in a more equitable distribution of surplus amongst the SPs and the users.",robert schober,Price competition,2013.0,10.1109/LCOMM.2013.020513.122647,IEEE Communications Letters,Kumar2013,False,,IEEE,Not available,WLAN Service Providers' Price Competition with Uncertainty in User Demand,0b320243d4678b542414fbd9dd2aeab1,https://ieeexplore.ieee.org/document/6459501/
13701,"In this letter, uncertainty in users' network selection is modeled by a Markov chain. In the presence of such uncertainty, the price competition game of wireless local area network (WLAN) service providers (SPs) is analyzed and the existence of Bayesian Nash equilibrium is proved. Using the price of anarchy as a metric of efficiency for social welfare maximization, it is shown that an increase in competition does not result in significant losses in efficiency. Compared to a monopoly, an unregulated duopoly of WLAN SPs is recommended as it results in a more equitable distribution of surplus amongst the SPs and the users.",robert schober,price of anarchy (PoA),2013.0,10.1109/LCOMM.2013.020513.122647,IEEE Communications Letters,Kumar2013,False,,IEEE,Not available,WLAN Service Providers' Price Competition with Uncertainty in User Demand,0b320243d4678b542414fbd9dd2aeab1,https://ieeexplore.ieee.org/document/6459501/
13702,"In this letter, uncertainty in users' network selection is modeled by a Markov chain. In the presence of such uncertainty, the price competition game of wireless local area network (WLAN) service providers (SPs) is analyzed and the existence of Bayesian Nash equilibrium is proved. Using the price of anarchy as a metric of efficiency for social welfare maximization, it is shown that an increase in competition does not result in significant losses in efficiency. Compared to a monopoly, an unregulated duopoly of WLAN SPs is recommended as it results in a more equitable distribution of surplus amongst the SPs and the users.",robert schober,service provider (SP),2013.0,10.1109/LCOMM.2013.020513.122647,IEEE Communications Letters,Kumar2013,False,,IEEE,Not available,WLAN Service Providers' Price Competition with Uncertainty in User Demand,0b320243d4678b542414fbd9dd2aeab1,https://ieeexplore.ieee.org/document/6459501/
13703,"In this letter, uncertainty in users' network selection is modeled by a Markov chain. In the presence of such uncertainty, the price competition game of wireless local area network (WLAN) service providers (SPs) is analyzed and the existence of Bayesian Nash equilibrium is proved. Using the price of anarchy as a metric of efficiency for social welfare maximization, it is shown that an increase in competition does not result in significant losses in efficiency. Compared to a monopoly, an unregulated duopoly of WLAN SPs is recommended as it results in a more equitable distribution of surplus amongst the SPs and the users.",robert schober,wireless local area network (WLAN),2013.0,10.1109/LCOMM.2013.020513.122647,IEEE Communications Letters,Kumar2013,False,,IEEE,Not available,WLAN Service Providers' Price Competition with Uncertainty in User Demand,0b320243d4678b542414fbd9dd2aeab1,https://ieeexplore.ieee.org/document/6459501/
13704,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",jason marden,Games,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
13705,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13706,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",jason marden,Linear programming,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
13707,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",jason marden,Stability analysis,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
13708,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",jason marden,Resource management,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
13709,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",jason marden,Cost function,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
13710,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",jason marden,Decision making,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
13711,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",jason marden,Computer architecture,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
13712,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",matthew philips,Games,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
13713,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",matthew philips,Linear programming,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
13714,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",matthew philips,Stability analysis,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
13715,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",matthew philips,Resource management,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
13716,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13717,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",matthew philips,Cost function,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
13718,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",matthew philips,Decision making,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
13719,"This paper focuses on the design of local agent objective functions to optimize the efficiency of the resulting equilibria in a class of resource allocation problems with concave cost functions. Our analysis focuses on two well-studied measures of efficiency, termed the price of anarchy and price of stability, which provide worst case guarantees on the performance of the (worst or best) equilibria. The main result of this paper is a characterization of the optimal local agent objective functions for concave cost sharing games. In particular, we demonstrate that the Shapley value objective function is the unique local and anonymous agent objective functions that (i) achieves the minimum price of anarchy and (ii) achieves the minimum price of stability over all designs that achieve the minimum price of anarchy.",matthew philips,Computer architecture,2017.0,10.23919/ACC.2017.7963768,2017 American Control Conference (ACC),Marden2017,False,,IEEE,Not available,Optimizing the price of anarchy in concave cost sharing games,d8a46436b4416f9cf1a64d06ac4eb3aa,https://ieeexplore.ieee.org/document/7963768/
13720,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",jonatha anselmi,Time factors,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
13721,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",jonatha anselmi,Routing,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
13722,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",jonatha anselmi,Queueing analysis,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
13723,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",jonatha anselmi,Approximation methods,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
13724,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",jonatha anselmi,Optimization,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
13725,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",jonatha anselmi,Upper bound,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
13726,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",jonatha anselmi,Nash equilibrium,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
13727,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13728,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",bruno gaujal,Time factors,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
13729,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",bruno gaujal,Routing,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
13730,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",bruno gaujal,Queueing analysis,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
13731,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",bruno gaujal,Approximation methods,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
13732,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",bruno gaujal,Optimization,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
13733,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",bruno gaujal,Upper bound,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
13734,"We consider a network of parallel, non-observable queues and analyze the “price of anarchy”, an index measuring the worst-case performance loss of a decentralized system with respect to its centralized counterpart in presence of non-cooperative users. Our analysis is undertaken from the new point of view where the router has the memory of previous dispatching choices, which significantly complicates the nature of the problem. In the regime where the demands proportionally grow with the network capacity, we provide a tight lower bound on the socially-optimal response time and a tight upper bound on the price of anarchy by means of convex programming. Then, we exploit this result to show, by simulation, that the billiard routing scheme yields a response time which is remarkably close to our lower bound, implying that billiards minimize response time. To study the added-value of non-Bernoulli routers, we introduce the “price of forgetting” and prove that it is bounded from above by two, which is tight in heavy-traffic. Finally, other structural properties are derived numerically for the price of forgetting. These claim that the benefit of having memory in the router is independent of the network size and heterogeneity, while monotonically depending on the network load only. These properties yield simple product-forms well-approximating the socially-optimal response time.",bruno gaujal,Nash equilibrium,2010.0,10.1109/ITC.2010.5608745,2010 22nd International Teletraffic Congress (lTC 22),Anselmi2010,False,,IEEE,Not available,"Optimal routing in parallel, non-observable queues and the price of anarchy revisited",3e90c46706d5aa797c4c4a647035aae5,https://ieeexplore.ieee.org/document/5608745/
13735,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",gang wang,Price of Ararchy (PoA),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
13736,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",gang wang,Network Coding (NC),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
13737,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",gang wang,Average Cost Sharing (ACS),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
13738,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,traffic networks,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13739,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",gang wang,Affine Marginal Cost (AMC),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
13740,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",gang wang,Affine marginal cost (AMC),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
13741,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",gang wang,average cost sharing (ACS),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
13742,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",gang wang,network coding (NC),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
13743,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",gang wang,price of anarchy (PoA),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
13744,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",xia dai,Price of Ararchy (PoA),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
13745,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",xia dai,Network Coding (NC),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
13746,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",xia dai,Average Cost Sharing (ACS),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
13747,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",xia dai,Affine Marginal Cost (AMC),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
13748,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",xia dai,Affine marginal cost (AMC),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
13749,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13750,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",xia dai,average cost sharing (ACS),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
13751,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",xia dai,network coding (NC),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
13752,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",xia dai,price of anarchy (PoA),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
13753,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",yonghui li,Price of Ararchy (PoA),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
13754,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",yonghui li,Network Coding (NC),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
13755,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",yonghui li,Average Cost Sharing (ACS),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
13756,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",yonghui li,Affine Marginal Cost (AMC),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
13757,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",yonghui li,Affine marginal cost (AMC),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
13758,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",yonghui li,average cost sharing (ACS),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
13759,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",yonghui li,network coding (NC),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
13760,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13761,"In this paper, we study the congestion game for a network where mutliple network coding (NC) and routing users sharing a single common congestion link to transmit their information. The data flows using NC and routing will compete network resources, and we need to determine the optimal allocation of network resources between NC and routing data flows to maximize the network payoff. To facilitate the design, we formulate this process using a cost-sharing game model. A novel average-cost-sharing (ACS) pricing mechanism is developed to maximize the overall network payoff. We analyze the performance of ACS in terms of price of anarchy (PoA). We formulate an analytical expression to compute PoA under the ACS mechanism. In contrast to the previous affine marginal cost (AMC) mechanism, where the overall network payoff decreases when NC is applied, the proposed ACS mechanism can considerably improve the overall network payoff by optimizing the number and the spectral resource allocation of NC and routing data flows sharing the network link.",yonghui li,price of anarchy (PoA),2014.0,10.1109/TVT.2013.2291859,IEEE Transactions on Vehicular Technology,Wang2014,False,,IEEE,Not available,On the Network Sharing of Mixed Network Coding and Routing Data Flows in Congestion Networks,9454f10d434aa74ddbebecd9c663d698,https://ieeexplore.ieee.org/document/6671460/
13762,"In the context of networking, research has focused on non-cooperative games, where the selfish agents cannot reach a binding agreement on the way they would share the infrastructure. Many approaches have been proposed for mitigating the typically inefficient operating points. However, in a growing number of networking scenarios, selfish agents are able to communicate and reach an agreement. Hence, the degradation of performance should be considered at an operating point of a cooperative game. Accordingly, our goal is to lay foundations for the application of the cooperative game theory to fundamental problems in networking. We explain our choice of the Nash bargaining scheme (NBS) as the solution concept, and introduce the price of selfishness (PoS), which considers the degradation of performance at the worst NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we consider agents with identical performance objectives. We show that, while the price of anarchy (PoA) here can be large, through bargaining, all agents, and the system, strictly improve their performance. Interestingly, in a two-agent system or when all the agents have identical demands, we establish that they reach social optimality. We then consider agents with different performance objectives and demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures are unsuitable. Accordingly, we introduce the price of heterogeneity (PoH), as an extension of the PoA. We establish an upper bound on the PoH and indicate its further motivation for bargaining. Finally, we discuss network design guidelines that follow from our findings.",gideon blocq,Atomic splittable routing games,2016.0,10.1109/TNET.2016.2530308,IEEE/ACM Transactions on Networking,Blocq2016,False,,IEEE,Not available,How Good is Bargained Routing?,63d7a448b60ccf3342f9ef03180869c2,https://ieeexplore.ieee.org/document/7423806/
13763,"In the context of networking, research has focused on non-cooperative games, where the selfish agents cannot reach a binding agreement on the way they would share the infrastructure. Many approaches have been proposed for mitigating the typically inefficient operating points. However, in a growing number of networking scenarios, selfish agents are able to communicate and reach an agreement. Hence, the degradation of performance should be considered at an operating point of a cooperative game. Accordingly, our goal is to lay foundations for the application of the cooperative game theory to fundamental problems in networking. We explain our choice of the Nash bargaining scheme (NBS) as the solution concept, and introduce the price of selfishness (PoS), which considers the degradation of performance at the worst NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we consider agents with identical performance objectives. We show that, while the price of anarchy (PoA) here can be large, through bargaining, all agents, and the system, strictly improve their performance. Interestingly, in a two-agent system or when all the agents have identical demands, we establish that they reach social optimality. We then consider agents with different performance objectives and demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures are unsuitable. Accordingly, we introduce the price of heterogeneity (PoH), as an extension of the PoA. We establish an upper bound on the PoH and indicate its further motivation for bargaining. Finally, we discuss network design guidelines that follow from our findings.",gideon blocq,parallel links,2016.0,10.1109/TNET.2016.2530308,IEEE/ACM Transactions on Networking,Blocq2016,False,,IEEE,Not available,How Good is Bargained Routing?,63d7a448b60ccf3342f9ef03180869c2,https://ieeexplore.ieee.org/document/7423806/
13764,"In the context of networking, research has focused on non-cooperative games, where the selfish agents cannot reach a binding agreement on the way they would share the infrastructure. Many approaches have been proposed for mitigating the typically inefficient operating points. However, in a growing number of networking scenarios, selfish agents are able to communicate and reach an agreement. Hence, the degradation of performance should be considered at an operating point of a cooperative game. Accordingly, our goal is to lay foundations for the application of the cooperative game theory to fundamental problems in networking. We explain our choice of the Nash bargaining scheme (NBS) as the solution concept, and introduce the price of selfishness (PoS), which considers the degradation of performance at the worst NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we consider agents with identical performance objectives. We show that, while the price of anarchy (PoA) here can be large, through bargaining, all agents, and the system, strictly improve their performance. Interestingly, in a two-agent system or when all the agents have identical demands, we establish that they reach social optimality. We then consider agents with different performance objectives and demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures are unsuitable. Accordingly, we introduce the price of heterogeneity (PoH), as an extension of the PoA. We establish an upper bound on the PoH and indicate its further motivation for bargaining. Finally, we discuss network design guidelines that follow from our findings.",gideon blocq,load balancing games,2016.0,10.1109/TNET.2016.2530308,IEEE/ACM Transactions on Networking,Blocq2016,False,,IEEE,Not available,How Good is Bargained Routing?,63d7a448b60ccf3342f9ef03180869c2,https://ieeexplore.ieee.org/document/7423806/
13765,"In the context of networking, research has focused on non-cooperative games, where the selfish agents cannot reach a binding agreement on the way they would share the infrastructure. Many approaches have been proposed for mitigating the typically inefficient operating points. However, in a growing number of networking scenarios, selfish agents are able to communicate and reach an agreement. Hence, the degradation of performance should be considered at an operating point of a cooperative game. Accordingly, our goal is to lay foundations for the application of the cooperative game theory to fundamental problems in networking. We explain our choice of the Nash bargaining scheme (NBS) as the solution concept, and introduce the price of selfishness (PoS), which considers the degradation of performance at the worst NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we consider agents with identical performance objectives. We show that, while the price of anarchy (PoA) here can be large, through bargaining, all agents, and the system, strictly improve their performance. Interestingly, in a two-agent system or when all the agents have identical demands, we establish that they reach social optimality. We then consider agents with different performance objectives and demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures are unsuitable. Accordingly, we introduce the price of heterogeneity (PoH), as an extension of the PoA. We establish an upper bound on the PoH and indicate its further motivation for bargaining. Finally, we discuss network design guidelines that follow from our findings.",gideon blocq,Nash bargaining solution,2016.0,10.1109/TNET.2016.2530308,IEEE/ACM Transactions on Networking,Blocq2016,False,,IEEE,Not available,How Good is Bargained Routing?,63d7a448b60ccf3342f9ef03180869c2,https://ieeexplore.ieee.org/document/7423806/
13766,"In the context of networking, research has focused on non-cooperative games, where the selfish agents cannot reach a binding agreement on the way they would share the infrastructure. Many approaches have been proposed for mitigating the typically inefficient operating points. However, in a growing number of networking scenarios, selfish agents are able to communicate and reach an agreement. Hence, the degradation of performance should be considered at an operating point of a cooperative game. Accordingly, our goal is to lay foundations for the application of the cooperative game theory to fundamental problems in networking. We explain our choice of the Nash bargaining scheme (NBS) as the solution concept, and introduce the price of selfishness (PoS), which considers the degradation of performance at the worst NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we consider agents with identical performance objectives. We show that, while the price of anarchy (PoA) here can be large, through bargaining, all agents, and the system, strictly improve their performance. Interestingly, in a two-agent system or when all the agents have identical demands, we establish that they reach social optimality. We then consider agents with different performance objectives and demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures are unsuitable. Accordingly, we introduce the price of heterogeneity (PoH), as an extension of the PoA. We establish an upper bound on the PoH and indicate its further motivation for bargaining. Finally, we discuss network design guidelines that follow from our findings.",gideon blocq,price of selfishness,2016.0,10.1109/TNET.2016.2530308,IEEE/ACM Transactions on Networking,Blocq2016,False,,IEEE,Not available,How Good is Bargained Routing?,63d7a448b60ccf3342f9ef03180869c2,https://ieeexplore.ieee.org/document/7423806/
13767,"In the context of networking, research has focused on non-cooperative games, where the selfish agents cannot reach a binding agreement on the way they would share the infrastructure. Many approaches have been proposed for mitigating the typically inefficient operating points. However, in a growing number of networking scenarios, selfish agents are able to communicate and reach an agreement. Hence, the degradation of performance should be considered at an operating point of a cooperative game. Accordingly, our goal is to lay foundations for the application of the cooperative game theory to fundamental problems in networking. We explain our choice of the Nash bargaining scheme (NBS) as the solution concept, and introduce the price of selfishness (PoS), which considers the degradation of performance at the worst NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we consider agents with identical performance objectives. We show that, while the price of anarchy (PoA) here can be large, through bargaining, all agents, and the system, strictly improve their performance. Interestingly, in a two-agent system or when all the agents have identical demands, we establish that they reach social optimality. We then consider agents with different performance objectives and demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures are unsuitable. Accordingly, we introduce the price of heterogeneity (PoH), as an extension of the PoA. We establish an upper bound on the PoH and indicate its further motivation for bargaining. Finally, we discuss network design guidelines that follow from our findings.",gideon blocq,price of anarchy,2016.0,10.1109/TNET.2016.2530308,IEEE/ACM Transactions on Networking,Blocq2016,False,,IEEE,Not available,How Good is Bargained Routing?,63d7a448b60ccf3342f9ef03180869c2,https://ieeexplore.ieee.org/document/7423806/
13768,"In the context of networking, research has focused on non-cooperative games, where the selfish agents cannot reach a binding agreement on the way they would share the infrastructure. Many approaches have been proposed for mitigating the typically inefficient operating points. However, in a growing number of networking scenarios, selfish agents are able to communicate and reach an agreement. Hence, the degradation of performance should be considered at an operating point of a cooperative game. Accordingly, our goal is to lay foundations for the application of the cooperative game theory to fundamental problems in networking. We explain our choice of the Nash bargaining scheme (NBS) as the solution concept, and introduce the price of selfishness (PoS), which considers the degradation of performance at the worst NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we consider agents with identical performance objectives. We show that, while the price of anarchy (PoA) here can be large, through bargaining, all agents, and the system, strictly improve their performance. Interestingly, in a two-agent system or when all the agents have identical demands, we establish that they reach social optimality. We then consider agents with different performance objectives and demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures are unsuitable. Accordingly, we introduce the price of heterogeneity (PoH), as an extension of the PoA. We establish an upper bound on the PoH and indicate its further motivation for bargaining. Finally, we discuss network design guidelines that follow from our findings.",gideon blocq,price of heterogeneity,2016.0,10.1109/TNET.2016.2530308,IEEE/ACM Transactions on Networking,Blocq2016,False,,IEEE,Not available,How Good is Bargained Routing?,63d7a448b60ccf3342f9ef03180869c2,https://ieeexplore.ieee.org/document/7423806/
13769,"In the context of networking, research has focused on non-cooperative games, where the selfish agents cannot reach a binding agreement on the way they would share the infrastructure. Many approaches have been proposed for mitigating the typically inefficient operating points. However, in a growing number of networking scenarios, selfish agents are able to communicate and reach an agreement. Hence, the degradation of performance should be considered at an operating point of a cooperative game. Accordingly, our goal is to lay foundations for the application of the cooperative game theory to fundamental problems in networking. We explain our choice of the Nash bargaining scheme (NBS) as the solution concept, and introduce the price of selfishness (PoS), which considers the degradation of performance at the worst NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we consider agents with identical performance objectives. We show that, while the price of anarchy (PoA) here can be large, through bargaining, all agents, and the system, strictly improve their performance. Interestingly, in a two-agent system or when all the agents have identical demands, we establish that they reach social optimality. We then consider agents with different performance objectives and demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures are unsuitable. Accordingly, we introduce the price of heterogeneity (PoH), as an extension of the PoA. We establish an upper bound on the PoH and indicate its further motivation for bargaining. Finally, we discuss network design guidelines that follow from our findings.",ariel orda,Atomic splittable routing games,2016.0,10.1109/TNET.2016.2530308,IEEE/ACM Transactions on Networking,Blocq2016,False,,IEEE,Not available,How Good is Bargained Routing?,63d7a448b60ccf3342f9ef03180869c2,https://ieeexplore.ieee.org/document/7423806/
13770,"In the context of networking, research has focused on non-cooperative games, where the selfish agents cannot reach a binding agreement on the way they would share the infrastructure. Many approaches have been proposed for mitigating the typically inefficient operating points. However, in a growing number of networking scenarios, selfish agents are able to communicate and reach an agreement. Hence, the degradation of performance should be considered at an operating point of a cooperative game. Accordingly, our goal is to lay foundations for the application of the cooperative game theory to fundamental problems in networking. We explain our choice of the Nash bargaining scheme (NBS) as the solution concept, and introduce the price of selfishness (PoS), which considers the degradation of performance at the worst NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we consider agents with identical performance objectives. We show that, while the price of anarchy (PoA) here can be large, through bargaining, all agents, and the system, strictly improve their performance. Interestingly, in a two-agent system or when all the agents have identical demands, we establish that they reach social optimality. We then consider agents with different performance objectives and demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures are unsuitable. Accordingly, we introduce the price of heterogeneity (PoH), as an extension of the PoA. We establish an upper bound on the PoH and indicate its further motivation for bargaining. Finally, we discuss network design guidelines that follow from our findings.",ariel orda,parallel links,2016.0,10.1109/TNET.2016.2530308,IEEE/ACM Transactions on Networking,Blocq2016,False,,IEEE,Not available,How Good is Bargained Routing?,63d7a448b60ccf3342f9ef03180869c2,https://ieeexplore.ieee.org/document/7423806/
13771,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,Noncooperative congestion game,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13772,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13773,"In the context of networking, research has focused on non-cooperative games, where the selfish agents cannot reach a binding agreement on the way they would share the infrastructure. Many approaches have been proposed for mitigating the typically inefficient operating points. However, in a growing number of networking scenarios, selfish agents are able to communicate and reach an agreement. Hence, the degradation of performance should be considered at an operating point of a cooperative game. Accordingly, our goal is to lay foundations for the application of the cooperative game theory to fundamental problems in networking. We explain our choice of the Nash bargaining scheme (NBS) as the solution concept, and introduce the price of selfishness (PoS), which considers the degradation of performance at the worst NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we consider agents with identical performance objectives. We show that, while the price of anarchy (PoA) here can be large, through bargaining, all agents, and the system, strictly improve their performance. Interestingly, in a two-agent system or when all the agents have identical demands, we establish that they reach social optimality. We then consider agents with different performance objectives and demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures are unsuitable. Accordingly, we introduce the price of heterogeneity (PoH), as an extension of the PoA. We establish an upper bound on the PoH and indicate its further motivation for bargaining. Finally, we discuss network design guidelines that follow from our findings.",ariel orda,load balancing games,2016.0,10.1109/TNET.2016.2530308,IEEE/ACM Transactions on Networking,Blocq2016,False,,IEEE,Not available,How Good is Bargained Routing?,63d7a448b60ccf3342f9ef03180869c2,https://ieeexplore.ieee.org/document/7423806/
13774,"In the context of networking, research has focused on non-cooperative games, where the selfish agents cannot reach a binding agreement on the way they would share the infrastructure. Many approaches have been proposed for mitigating the typically inefficient operating points. However, in a growing number of networking scenarios, selfish agents are able to communicate and reach an agreement. Hence, the degradation of performance should be considered at an operating point of a cooperative game. Accordingly, our goal is to lay foundations for the application of the cooperative game theory to fundamental problems in networking. We explain our choice of the Nash bargaining scheme (NBS) as the solution concept, and introduce the price of selfishness (PoS), which considers the degradation of performance at the worst NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we consider agents with identical performance objectives. We show that, while the price of anarchy (PoA) here can be large, through bargaining, all agents, and the system, strictly improve their performance. Interestingly, in a two-agent system or when all the agents have identical demands, we establish that they reach social optimality. We then consider agents with different performance objectives and demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures are unsuitable. Accordingly, we introduce the price of heterogeneity (PoH), as an extension of the PoA. We establish an upper bound on the PoH and indicate its further motivation for bargaining. Finally, we discuss network design guidelines that follow from our findings.",ariel orda,Nash bargaining solution,2016.0,10.1109/TNET.2016.2530308,IEEE/ACM Transactions on Networking,Blocq2016,False,,IEEE,Not available,How Good is Bargained Routing?,63d7a448b60ccf3342f9ef03180869c2,https://ieeexplore.ieee.org/document/7423806/
13775,"In the context of networking, research has focused on non-cooperative games, where the selfish agents cannot reach a binding agreement on the way they would share the infrastructure. Many approaches have been proposed for mitigating the typically inefficient operating points. However, in a growing number of networking scenarios, selfish agents are able to communicate and reach an agreement. Hence, the degradation of performance should be considered at an operating point of a cooperative game. Accordingly, our goal is to lay foundations for the application of the cooperative game theory to fundamental problems in networking. We explain our choice of the Nash bargaining scheme (NBS) as the solution concept, and introduce the price of selfishness (PoS), which considers the degradation of performance at the worst NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we consider agents with identical performance objectives. We show that, while the price of anarchy (PoA) here can be large, through bargaining, all agents, and the system, strictly improve their performance. Interestingly, in a two-agent system or when all the agents have identical demands, we establish that they reach social optimality. We then consider agents with different performance objectives and demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures are unsuitable. Accordingly, we introduce the price of heterogeneity (PoH), as an extension of the PoA. We establish an upper bound on the PoH and indicate its further motivation for bargaining. Finally, we discuss network design guidelines that follow from our findings.",ariel orda,price of selfishness,2016.0,10.1109/TNET.2016.2530308,IEEE/ACM Transactions on Networking,Blocq2016,False,,IEEE,Not available,How Good is Bargained Routing?,63d7a448b60ccf3342f9ef03180869c2,https://ieeexplore.ieee.org/document/7423806/
13776,"In the context of networking, research has focused on non-cooperative games, where the selfish agents cannot reach a binding agreement on the way they would share the infrastructure. Many approaches have been proposed for mitigating the typically inefficient operating points. However, in a growing number of networking scenarios, selfish agents are able to communicate and reach an agreement. Hence, the degradation of performance should be considered at an operating point of a cooperative game. Accordingly, our goal is to lay foundations for the application of the cooperative game theory to fundamental problems in networking. We explain our choice of the Nash bargaining scheme (NBS) as the solution concept, and introduce the price of selfishness (PoS), which considers the degradation of performance at the worst NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we consider agents with identical performance objectives. We show that, while the price of anarchy (PoA) here can be large, through bargaining, all agents, and the system, strictly improve their performance. Interestingly, in a two-agent system or when all the agents have identical demands, we establish that they reach social optimality. We then consider agents with different performance objectives and demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures are unsuitable. Accordingly, we introduce the price of heterogeneity (PoH), as an extension of the PoA. We establish an upper bound on the PoH and indicate its further motivation for bargaining. Finally, we discuss network design guidelines that follow from our findings.",ariel orda,price of anarchy,2016.0,10.1109/TNET.2016.2530308,IEEE/ACM Transactions on Networking,Blocq2016,False,,IEEE,Not available,How Good is Bargained Routing?,63d7a448b60ccf3342f9ef03180869c2,https://ieeexplore.ieee.org/document/7423806/
13777,"In the context of networking, research has focused on non-cooperative games, where the selfish agents cannot reach a binding agreement on the way they would share the infrastructure. Many approaches have been proposed for mitigating the typically inefficient operating points. However, in a growing number of networking scenarios, selfish agents are able to communicate and reach an agreement. Hence, the degradation of performance should be considered at an operating point of a cooperative game. Accordingly, our goal is to lay foundations for the application of the cooperative game theory to fundamental problems in networking. We explain our choice of the Nash bargaining scheme (NBS) as the solution concept, and introduce the price of selfishness (PoS), which considers the degradation of performance at the worst NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we consider agents with identical performance objectives. We show that, while the price of anarchy (PoA) here can be large, through bargaining, all agents, and the system, strictly improve their performance. Interestingly, in a two-agent system or when all the agents have identical demands, we establish that they reach social optimality. We then consider agents with different performance objectives and demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures are unsuitable. Accordingly, we introduce the price of heterogeneity (PoH), as an extension of the PoA. We establish an upper bound on the PoH and indicate its further motivation for bargaining. Finally, we discuss network design guidelines that follow from our findings.",ariel orda,price of heterogeneity,2016.0,10.1109/TNET.2016.2530308,IEEE/ACM Transactions on Networking,Blocq2016,False,,IEEE,Not available,How Good is Bargained Routing?,63d7a448b60ccf3342f9ef03180869c2,https://ieeexplore.ieee.org/document/7423806/
13778,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",prasanna chaporkar,Wireless LAN,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
13779,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",prasanna chaporkar,Nash equilibrium,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
13780,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",prasanna chaporkar,Throughput,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
13781,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",prasanna chaporkar,Communications Society,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
13782,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",prasanna chaporkar,Media Access Protocol,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
13783,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13784,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",prasanna chaporkar,H infinity control,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
13785,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",prasanna chaporkar,Time factors,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
13786,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",prasanna chaporkar,Hardware,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
13787,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",prasanna chaporkar,Modulation coding,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
13788,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",prasanna chaporkar,Propagation losses,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
13789,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",alexandre proutiere,Wireless LAN,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
13790,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",alexandre proutiere,Nash equilibrium,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
13791,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",alexandre proutiere,Throughput,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
13792,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",alexandre proutiere,Communications Society,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
13793,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",alexandre proutiere,Media Access Protocol,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
13794,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13795,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",alexandre proutiere,H infinity control,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
13796,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",alexandre proutiere,Time factors,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
13797,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",alexandre proutiere,Hardware,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
13798,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",alexandre proutiere,Modulation coding,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
13799,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",alexandre proutiere,Propagation losses,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
13800,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",bozidar radunoviae,Wireless LAN,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
13801,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",bozidar radunoviae,Nash equilibrium,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
13802,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",bozidar radunoviae,Throughput,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
13803,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",bozidar radunoviae,Communications Society,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
13804,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",bozidar radunoviae,Media Access Protocol,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
13805,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13806,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",bozidar radunoviae,H infinity control,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
13807,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",bozidar radunoviae,Time factors,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
13808,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",bozidar radunoviae,Hardware,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
13809,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",bozidar radunoviae,Modulation coding,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
13810,"In Wireless LANs, users may adapt their transmission rates depending on the radio conditions of their links so as to maximize their throughput. Recently, there has been a significant research effort in developing distributed rate adaptation schemes. Unlike previous works that mainly focus on channel tracking, this paper characterizes the optimal reaction of a rate adaptation protocol to the contention information received from the MAC. We formulate this problem analytically. We study both competitive and cooperative user behaviors. In the case of competition, users selfishly adapt their rates so as to maximize their own throughput, whereas in the case of cooperation they adapt their rates so as to maximize the overall system throughput. We show that the Nash Equilibrium reached in the case of competition is inefficient (i.e. the price of anarchy goes to infinity as the number of users increases), and provide insightful properties of the socially optimal rate adaptation schemes. We find that recently proposed collision-aware rate adaptation algorithms decrease the price of anarchy. We also propose a novel collision-aware rate adaptation algorithm that further reduces the price of anarchy.",bozidar radunoviae,Propagation losses,2010.0,10.1109/INFCOM.2010.5462028,2010 Proceedings IEEE INFOCOM,Chaporkar2010,False,,IEEE,Not available,Rate Adaptation Games in Wireless LANs: Nash Equilibrium and Price of Anarchy,03718578b670db21ad9ef0a1c9c98908,https://ieeexplore.ieee.org/document/5462028/
13811,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",amir-hamed mohsenian-rad,Network coding,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13812,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",amir-hamed mohsenian-rad,Upper bound,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13813,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",amir-hamed mohsenian-rad,Communications Society,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13814,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",amir-hamed mohsenian-rad,Design engineering,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13815,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",amir-hamed mohsenian-rad,Electronic mail,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13816,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13817,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",amir-hamed mohsenian-rad,Wireless networks,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13818,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",amir-hamed mohsenian-rad,Encoding,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13819,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",amir-hamed mohsenian-rad,Unicast,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13820,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",amir-hamed mohsenian-rad,Decoding,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13821,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",amir-hamed mohsenian-rad,Nash equilibrium,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13822,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",jianwei huang,Network coding,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13823,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",jianwei huang,Upper bound,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13824,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",jianwei huang,Communications Society,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13825,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",jianwei huang,Design engineering,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13826,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",jianwei huang,Electronic mail,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13827,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13828,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",jianwei huang,Wireless networks,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13829,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",jianwei huang,Encoding,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13830,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",jianwei huang,Unicast,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13831,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",jianwei huang,Decoding,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13832,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",jianwei huang,Nash equilibrium,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13833,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",vincent wong,Network coding,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13834,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",vincent wong,Upper bound,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13835,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",vincent wong,Communications Society,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13836,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",vincent wong,Design engineering,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13837,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",vincent wong,Electronic mail,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13838,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13839,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",vincent wong,Wireless networks,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13840,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",vincent wong,Encoding,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13841,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",vincent wong,Unicast,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13842,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",vincent wong,Decoding,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13843,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",vincent wong,Nash equilibrium,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13844,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",robert schober,Network coding,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13845,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",robert schober,Upper bound,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13846,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",robert schober,Communications Society,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13847,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",robert schober,Design engineering,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13848,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",robert schober,Electronic mail,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13849,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",quanyan zhu,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13850,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",robert schober,Wireless networks,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13851,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",robert schober,Encoding,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13852,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",robert schober,Unicast,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13853,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",robert schober,Decoding,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13854,"Most of the previous work on network coding has assumed that the users are not selfish and always follow the designed coding schemes. However, recent results have shown that selfish users do not have the incentive to participate in inter-session network coding in a static non-cooperative game setting. As a result, the worst-case network efficiency (i.e., the price-of-anarchy) can be as low as 22%. In this paper, we show that if the same game is played repeatedly, then the price-of-anarchy can be significantly improved to 48%. We propose a grim-trigger strategy that encourages users to cooperate and participate in the inter-session network coding. A key challenge is to determine a common cooperative coding rate that the users should mutually agree on. We propose to resolve the conflict of interest among the users through a bargaining process. We derive a tight upper bound for the price-of-anarchy which is valid for any bargaining scheme. Moreover, we propose a simple and efficient min-max bargaining solution that can achieve this upper bound. Our results represent one of the first steps towards designing practical inter-session network coding schemes that can achieve reasonable performance for selfish users.",robert schober,Nash equilibrium,2010.0,10.1109/INFCOM.2010.5462014,2010 Proceedings IEEE INFOCOM,Mohsenian-Rad2010,False,,IEEE,Not available,Bargaining and Price-of-Anarchy in Repeated Inter-Session Network Coding Games,140520087be67e7291a02161954ba340,https://ieeexplore.ieee.org/document/5462014/
13855,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",daniel lazar,Roads,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
13856,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",daniel lazar,Cost function,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
13857,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",daniel lazar,Routing,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
13858,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",daniel lazar,Delays,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
13859,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",daniel lazar,Automobiles,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
13860,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Feedback,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13861,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",daniel lazar,Cruise control,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
13862,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",samuel coogan,Roads,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
13863,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",samuel coogan,Cost function,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
13864,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",samuel coogan,Routing,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
13865,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",samuel coogan,Delays,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
13866,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",samuel coogan,Automobiles,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
13867,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",samuel coogan,Cruise control,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
13868,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",ramtin pedarsani,Roads,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
13869,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",ramtin pedarsani,Cost function,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
13870,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",ramtin pedarsani,Routing,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
13871,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Nash equilibrium,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13872,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",ramtin pedarsani,Delays,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
13873,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",ramtin pedarsani,Automobiles,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
13874,"We study routing behavior in transportation networks with mixed autonomy, that is, networks in which a fraction of the vehicles on each road are equipped with autonomous capabilities such as adaptive cruise control that enable reduced headways and increased road capacity. Motivated by capacity models developed for such roads with mixed autonomy, we consider transportation networks in which the delay on each road or link is an affine function of two quantities: the number of vehicles with autonomous capabilities on the link and the number of regular vehicles on the link. We particularly study the price of anarchy for such networks, that is, the ratio of the total delay experienced by selfish routing to the socially optimal routing policy. Unlike the case when all vehicles are of the same type, for which the price of anarchy is known to be bounded, we first show that the price of anarchy can be arbitrarily large for such mixed autonomous networks. Next, we define a notion of asymmetry corresponding to the maximum possible travel time improvement due to the presence of autonomous vehicles. We show that when the degree of asymmetry of all links in the network is bounded by a factor less than 4, the price of anarchy is bounded. We also bound the bicriteria, which is a bound on the cost of selfishly routing traffic compared to the cost of optimally routing additional traffic. These bounds depend on the degree of asymmetry and recover classical bounds on the price of anarchy and bicriteria in the case when no asymmetry exists. Further, we show with examples that these bound are tight in particular cases.",ramtin pedarsani,Cruise control,2018.0,10.23919/ACC.2018.8431087,2018 Annual American Control Conference (ACC),Lazar2018,False,,IEEE,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy*,825b618719f8d27e50303bbb3973c63e,https://ieeexplore.ieee.org/document/8431087/
13875,"In the presence of several wireless local area network (WLAN) service providers, the users have to make a choice. The price charged and the congestion experienced by the users play an important role in making this choice. In this paper, we analyze the duopoly price competition between two WLAN service providers in the presence of four types of users. We prove that the distribution of heterogeneous user demand is governed by the Wardrop equilibrium. We also show the existence of the Nash equilibrium between competing WLAN service providers. It is further shown through analysis that the social welfare in Nash equilibrium is close to its maximal value. We find that compared to a strictly regulated monopoly, an unregulated WLAN duopoly market results in significant transfer of the surplus from service providers to users with negligible losses in efficiency.",abhinav kumar,Duopoly price competition,2012.0,10.1109/WCNC.2012.6214194,2012 IEEE Wireless Communications and Networking Conference (WCNC),Kumar2012,False,,IEEE,Not available,Duopoly price competition of WLAN service providers in presence of heterogeneous user demand,e8255e2d8e117cb16c8f478a8285a15f,https://ieeexplore.ieee.org/document/6214194/
13876,"In the presence of several wireless local area network (WLAN) service providers, the users have to make a choice. The price charged and the congestion experienced by the users play an important role in making this choice. In this paper, we analyze the duopoly price competition between two WLAN service providers in the presence of four types of users. We prove that the distribution of heterogeneous user demand is governed by the Wardrop equilibrium. We also show the existence of the Nash equilibrium between competing WLAN service providers. It is further shown through analysis that the social welfare in Nash equilibrium is close to its maximal value. We find that compared to a strictly regulated monopoly, an unregulated WLAN duopoly market results in significant transfer of the surplus from service providers to users with negligible losses in efficiency.",abhinav kumar,heterogeneous users,2012.0,10.1109/WCNC.2012.6214194,2012 IEEE Wireless Communications and Networking Conference (WCNC),Kumar2012,False,,IEEE,Not available,Duopoly price competition of WLAN service providers in presence of heterogeneous user demand,e8255e2d8e117cb16c8f478a8285a15f,https://ieeexplore.ieee.org/document/6214194/
13877,"In the presence of several wireless local area network (WLAN) service providers, the users have to make a choice. The price charged and the congestion experienced by the users play an important role in making this choice. In this paper, we analyze the duopoly price competition between two WLAN service providers in the presence of four types of users. We prove that the distribution of heterogeneous user demand is governed by the Wardrop equilibrium. We also show the existence of the Nash equilibrium between competing WLAN service providers. It is further shown through analysis that the social welfare in Nash equilibrium is close to its maximal value. We find that compared to a strictly regulated monopoly, an unregulated WLAN duopoly market results in significant transfer of the surplus from service providers to users with negligible losses in efficiency.",abhinav kumar,Nash equilibrium (NE),2012.0,10.1109/WCNC.2012.6214194,2012 IEEE Wireless Communications and Networking Conference (WCNC),Kumar2012,False,,IEEE,Not available,Duopoly price competition of WLAN service providers in presence of heterogeneous user demand,e8255e2d8e117cb16c8f478a8285a15f,https://ieeexplore.ieee.org/document/6214194/
13878,"In the presence of several wireless local area network (WLAN) service providers, the users have to make a choice. The price charged and the congestion experienced by the users play an important role in making this choice. In this paper, we analyze the duopoly price competition between two WLAN service providers in the presence of four types of users. We prove that the distribution of heterogeneous user demand is governed by the Wardrop equilibrium. We also show the existence of the Nash equilibrium between competing WLAN service providers. It is further shown through analysis that the social welfare in Nash equilibrium is close to its maximal value. We find that compared to a strictly regulated monopoly, an unregulated WLAN duopoly market results in significant transfer of the surplus from service providers to users with negligible losses in efficiency.",abhinav kumar,price of anarchy (PoA),2012.0,10.1109/WCNC.2012.6214194,2012 IEEE Wireless Communications and Networking Conference (WCNC),Kumar2012,False,,IEEE,Not available,Duopoly price competition of WLAN service providers in presence of heterogeneous user demand,e8255e2d8e117cb16c8f478a8285a15f,https://ieeexplore.ieee.org/document/6214194/
13879,"In the presence of several wireless local area network (WLAN) service providers, the users have to make a choice. The price charged and the congestion experienced by the users play an important role in making this choice. In this paper, we analyze the duopoly price competition between two WLAN service providers in the presence of four types of users. We prove that the distribution of heterogeneous user demand is governed by the Wardrop equilibrium. We also show the existence of the Nash equilibrium between competing WLAN service providers. It is further shown through analysis that the social welfare in Nash equilibrium is close to its maximal value. We find that compared to a strictly regulated monopoly, an unregulated WLAN duopoly market results in significant transfer of the surplus from service providers to users with negligible losses in efficiency.",abhinav kumar,social welfare (SW),2012.0,10.1109/WCNC.2012.6214194,2012 IEEE Wireless Communications and Networking Conference (WCNC),Kumar2012,False,,IEEE,Not available,Duopoly price competition of WLAN service providers in presence of heterogeneous user demand,e8255e2d8e117cb16c8f478a8285a15f,https://ieeexplore.ieee.org/document/6214194/
13880,"In the presence of several wireless local area network (WLAN) service providers, the users have to make a choice. The price charged and the congestion experienced by the users play an important role in making this choice. In this paper, we analyze the duopoly price competition between two WLAN service providers in the presence of four types of users. We prove that the distribution of heterogeneous user demand is governed by the Wardrop equilibrium. We also show the existence of the Nash equilibrium between competing WLAN service providers. It is further shown through analysis that the social welfare in Nash equilibrium is close to its maximal value. We find that compared to a strictly regulated monopoly, an unregulated WLAN duopoly market results in significant transfer of the surplus from service providers to users with negligible losses in efficiency.",abhinav kumar,Wardrop equilibrium (WE),2012.0,10.1109/WCNC.2012.6214194,2012 IEEE Wireless Communications and Networking Conference (WCNC),Kumar2012,False,,IEEE,Not available,Duopoly price competition of WLAN service providers in presence of heterogeneous user demand,e8255e2d8e117cb16c8f478a8285a15f,https://ieeexplore.ieee.org/document/6214194/
13881,"In the presence of several wireless local area network (WLAN) service providers, the users have to make a choice. The price charged and the congestion experienced by the users play an important role in making this choice. In this paper, we analyze the duopoly price competition between two WLAN service providers in the presence of four types of users. We prove that the distribution of heterogeneous user demand is governed by the Wardrop equilibrium. We also show the existence of the Nash equilibrium between competing WLAN service providers. It is further shown through analysis that the social welfare in Nash equilibrium is close to its maximal value. We find that compared to a strictly regulated monopoly, an unregulated WLAN duopoly market results in significant transfer of the surplus from service providers to users with negligible losses in efficiency.",abhinav kumar,wireless local area network (WLAN),2012.0,10.1109/WCNC.2012.6214194,2012 IEEE Wireless Communications and Networking Conference (WCNC),Kumar2012,False,,IEEE,Not available,Duopoly price competition of WLAN service providers in presence of heterogeneous user demand,e8255e2d8e117cb16c8f478a8285a15f,https://ieeexplore.ieee.org/document/6214194/
13882,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price of anarchy (POA),2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13883,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Resource management,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13884,"In the presence of several wireless local area network (WLAN) service providers, the users have to make a choice. The price charged and the congestion experienced by the users play an important role in making this choice. In this paper, we analyze the duopoly price competition between two WLAN service providers in the presence of four types of users. We prove that the distribution of heterogeneous user demand is governed by the Wardrop equilibrium. We also show the existence of the Nash equilibrium between competing WLAN service providers. It is further shown through analysis that the social welfare in Nash equilibrium is close to its maximal value. We find that compared to a strictly regulated monopoly, an unregulated WLAN duopoly market results in significant transfer of the surplus from service providers to users with negligible losses in efficiency.",ranjan mallik,Duopoly price competition,2012.0,10.1109/WCNC.2012.6214194,2012 IEEE Wireless Communications and Networking Conference (WCNC),Kumar2012,False,,IEEE,Not available,Duopoly price competition of WLAN service providers in presence of heterogeneous user demand,e8255e2d8e117cb16c8f478a8285a15f,https://ieeexplore.ieee.org/document/6214194/
13885,"In the presence of several wireless local area network (WLAN) service providers, the users have to make a choice. The price charged and the congestion experienced by the users play an important role in making this choice. In this paper, we analyze the duopoly price competition between two WLAN service providers in the presence of four types of users. We prove that the distribution of heterogeneous user demand is governed by the Wardrop equilibrium. We also show the existence of the Nash equilibrium between competing WLAN service providers. It is further shown through analysis that the social welfare in Nash equilibrium is close to its maximal value. We find that compared to a strictly regulated monopoly, an unregulated WLAN duopoly market results in significant transfer of the surplus from service providers to users with negligible losses in efficiency.",ranjan mallik,heterogeneous users,2012.0,10.1109/WCNC.2012.6214194,2012 IEEE Wireless Communications and Networking Conference (WCNC),Kumar2012,False,,IEEE,Not available,Duopoly price competition of WLAN service providers in presence of heterogeneous user demand,e8255e2d8e117cb16c8f478a8285a15f,https://ieeexplore.ieee.org/document/6214194/
13886,"In the presence of several wireless local area network (WLAN) service providers, the users have to make a choice. The price charged and the congestion experienced by the users play an important role in making this choice. In this paper, we analyze the duopoly price competition between two WLAN service providers in the presence of four types of users. We prove that the distribution of heterogeneous user demand is governed by the Wardrop equilibrium. We also show the existence of the Nash equilibrium between competing WLAN service providers. It is further shown through analysis that the social welfare in Nash equilibrium is close to its maximal value. We find that compared to a strictly regulated monopoly, an unregulated WLAN duopoly market results in significant transfer of the surplus from service providers to users with negligible losses in efficiency.",ranjan mallik,Nash equilibrium (NE),2012.0,10.1109/WCNC.2012.6214194,2012 IEEE Wireless Communications and Networking Conference (WCNC),Kumar2012,False,,IEEE,Not available,Duopoly price competition of WLAN service providers in presence of heterogeneous user demand,e8255e2d8e117cb16c8f478a8285a15f,https://ieeexplore.ieee.org/document/6214194/
13887,"In the presence of several wireless local area network (WLAN) service providers, the users have to make a choice. The price charged and the congestion experienced by the users play an important role in making this choice. In this paper, we analyze the duopoly price competition between two WLAN service providers in the presence of four types of users. We prove that the distribution of heterogeneous user demand is governed by the Wardrop equilibrium. We also show the existence of the Nash equilibrium between competing WLAN service providers. It is further shown through analysis that the social welfare in Nash equilibrium is close to its maximal value. We find that compared to a strictly regulated monopoly, an unregulated WLAN duopoly market results in significant transfer of the surplus from service providers to users with negligible losses in efficiency.",ranjan mallik,price of anarchy (PoA),2012.0,10.1109/WCNC.2012.6214194,2012 IEEE Wireless Communications and Networking Conference (WCNC),Kumar2012,False,,IEEE,Not available,Duopoly price competition of WLAN service providers in presence of heterogeneous user demand,e8255e2d8e117cb16c8f478a8285a15f,https://ieeexplore.ieee.org/document/6214194/
13888,"In the presence of several wireless local area network (WLAN) service providers, the users have to make a choice. The price charged and the congestion experienced by the users play an important role in making this choice. In this paper, we analyze the duopoly price competition between two WLAN service providers in the presence of four types of users. We prove that the distribution of heterogeneous user demand is governed by the Wardrop equilibrium. We also show the existence of the Nash equilibrium between competing WLAN service providers. It is further shown through analysis that the social welfare in Nash equilibrium is close to its maximal value. We find that compared to a strictly regulated monopoly, an unregulated WLAN duopoly market results in significant transfer of the surplus from service providers to users with negligible losses in efficiency.",ranjan mallik,social welfare (SW),2012.0,10.1109/WCNC.2012.6214194,2012 IEEE Wireless Communications and Networking Conference (WCNC),Kumar2012,False,,IEEE,Not available,Duopoly price competition of WLAN service providers in presence of heterogeneous user demand,e8255e2d8e117cb16c8f478a8285a15f,https://ieeexplore.ieee.org/document/6214194/
13889,"In the presence of several wireless local area network (WLAN) service providers, the users have to make a choice. The price charged and the congestion experienced by the users play an important role in making this choice. In this paper, we analyze the duopoly price competition between two WLAN service providers in the presence of four types of users. We prove that the distribution of heterogeneous user demand is governed by the Wardrop equilibrium. We also show the existence of the Nash equilibrium between competing WLAN service providers. It is further shown through analysis that the social welfare in Nash equilibrium is close to its maximal value. We find that compared to a strictly regulated monopoly, an unregulated WLAN duopoly market results in significant transfer of the surplus from service providers to users with negligible losses in efficiency.",ranjan mallik,Wardrop equilibrium (WE),2012.0,10.1109/WCNC.2012.6214194,2012 IEEE Wireless Communications and Networking Conference (WCNC),Kumar2012,False,,IEEE,Not available,Duopoly price competition of WLAN service providers in presence of heterogeneous user demand,e8255e2d8e117cb16c8f478a8285a15f,https://ieeexplore.ieee.org/document/6214194/
13890,"In the presence of several wireless local area network (WLAN) service providers, the users have to make a choice. The price charged and the congestion experienced by the users play an important role in making this choice. In this paper, we analyze the duopoly price competition between two WLAN service providers in the presence of four types of users. We prove that the distribution of heterogeneous user demand is governed by the Wardrop equilibrium. We also show the existence of the Nash equilibrium between competing WLAN service providers. It is further shown through analysis that the social welfare in Nash equilibrium is close to its maximal value. We find that compared to a strictly regulated monopoly, an unregulated WLAN duopoly market results in significant transfer of the surplus from service providers to users with negligible losses in efficiency.",ranjan mallik,wireless local area network (WLAN),2012.0,10.1109/WCNC.2012.6214194,2012 IEEE Wireless Communications and Networking Conference (WCNC),Kumar2012,False,,IEEE,Not available,Duopoly price competition of WLAN service providers in presence of heterogeneous user demand,e8255e2d8e117cb16c8f478a8285a15f,https://ieeexplore.ieee.org/document/6214194/
13891,"In the presence of several wireless local area network (WLAN) service providers, the users have to make a choice. The price charged and the congestion experienced by the users play an important role in making this choice. In this paper, we analyze the duopoly price competition between two WLAN service providers in the presence of four types of users. We prove that the distribution of heterogeneous user demand is governed by the Wardrop equilibrium. We also show the existence of the Nash equilibrium between competing WLAN service providers. It is further shown through analysis that the social welfare in Nash equilibrium is close to its maximal value. We find that compared to a strictly regulated monopoly, an unregulated WLAN duopoly market results in significant transfer of the surplus from service providers to users with negligible losses in efficiency.",robert schober,Duopoly price competition,2012.0,10.1109/WCNC.2012.6214194,2012 IEEE Wireless Communications and Networking Conference (WCNC),Kumar2012,False,,IEEE,Not available,Duopoly price competition of WLAN service providers in presence of heterogeneous user demand,e8255e2d8e117cb16c8f478a8285a15f,https://ieeexplore.ieee.org/document/6214194/
13892,"In the presence of several wireless local area network (WLAN) service providers, the users have to make a choice. The price charged and the congestion experienced by the users play an important role in making this choice. In this paper, we analyze the duopoly price competition between two WLAN service providers in the presence of four types of users. We prove that the distribution of heterogeneous user demand is governed by the Wardrop equilibrium. We also show the existence of the Nash equilibrium between competing WLAN service providers. It is further shown through analysis that the social welfare in Nash equilibrium is close to its maximal value. We find that compared to a strictly regulated monopoly, an unregulated WLAN duopoly market results in significant transfer of the surplus from service providers to users with negligible losses in efficiency.",robert schober,heterogeneous users,2012.0,10.1109/WCNC.2012.6214194,2012 IEEE Wireless Communications and Networking Conference (WCNC),Kumar2012,False,,IEEE,Not available,Duopoly price competition of WLAN service providers in presence of heterogeneous user demand,e8255e2d8e117cb16c8f478a8285a15f,https://ieeexplore.ieee.org/document/6214194/
13893,"In the presence of several wireless local area network (WLAN) service providers, the users have to make a choice. The price charged and the congestion experienced by the users play an important role in making this choice. In this paper, we analyze the duopoly price competition between two WLAN service providers in the presence of four types of users. We prove that the distribution of heterogeneous user demand is governed by the Wardrop equilibrium. We also show the existence of the Nash equilibrium between competing WLAN service providers. It is further shown through analysis that the social welfare in Nash equilibrium is close to its maximal value. We find that compared to a strictly regulated monopoly, an unregulated WLAN duopoly market results in significant transfer of the surplus from service providers to users with negligible losses in efficiency.",robert schober,Nash equilibrium (NE),2012.0,10.1109/WCNC.2012.6214194,2012 IEEE Wireless Communications and Networking Conference (WCNC),Kumar2012,False,,IEEE,Not available,Duopoly price competition of WLAN service providers in presence of heterogeneous user demand,e8255e2d8e117cb16c8f478a8285a15f,https://ieeexplore.ieee.org/document/6214194/
13894,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Communication networks,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13895,"In the presence of several wireless local area network (WLAN) service providers, the users have to make a choice. The price charged and the congestion experienced by the users play an important role in making this choice. In this paper, we analyze the duopoly price competition between two WLAN service providers in the presence of four types of users. We prove that the distribution of heterogeneous user demand is governed by the Wardrop equilibrium. We also show the existence of the Nash equilibrium between competing WLAN service providers. It is further shown through analysis that the social welfare in Nash equilibrium is close to its maximal value. We find that compared to a strictly regulated monopoly, an unregulated WLAN duopoly market results in significant transfer of the surplus from service providers to users with negligible losses in efficiency.",robert schober,price of anarchy (PoA),2012.0,10.1109/WCNC.2012.6214194,2012 IEEE Wireless Communications and Networking Conference (WCNC),Kumar2012,False,,IEEE,Not available,Duopoly price competition of WLAN service providers in presence of heterogeneous user demand,e8255e2d8e117cb16c8f478a8285a15f,https://ieeexplore.ieee.org/document/6214194/
13896,"In the presence of several wireless local area network (WLAN) service providers, the users have to make a choice. The price charged and the congestion experienced by the users play an important role in making this choice. In this paper, we analyze the duopoly price competition between two WLAN service providers in the presence of four types of users. We prove that the distribution of heterogeneous user demand is governed by the Wardrop equilibrium. We also show the existence of the Nash equilibrium between competing WLAN service providers. It is further shown through analysis that the social welfare in Nash equilibrium is close to its maximal value. We find that compared to a strictly regulated monopoly, an unregulated WLAN duopoly market results in significant transfer of the surplus from service providers to users with negligible losses in efficiency.",robert schober,social welfare (SW),2012.0,10.1109/WCNC.2012.6214194,2012 IEEE Wireless Communications and Networking Conference (WCNC),Kumar2012,False,,IEEE,Not available,Duopoly price competition of WLAN service providers in presence of heterogeneous user demand,e8255e2d8e117cb16c8f478a8285a15f,https://ieeexplore.ieee.org/document/6214194/
13897,"In the presence of several wireless local area network (WLAN) service providers, the users have to make a choice. The price charged and the congestion experienced by the users play an important role in making this choice. In this paper, we analyze the duopoly price competition between two WLAN service providers in the presence of four types of users. We prove that the distribution of heterogeneous user demand is governed by the Wardrop equilibrium. We also show the existence of the Nash equilibrium between competing WLAN service providers. It is further shown through analysis that the social welfare in Nash equilibrium is close to its maximal value. We find that compared to a strictly regulated monopoly, an unregulated WLAN duopoly market results in significant transfer of the surplus from service providers to users with negligible losses in efficiency.",robert schober,Wardrop equilibrium (WE),2012.0,10.1109/WCNC.2012.6214194,2012 IEEE Wireless Communications and Networking Conference (WCNC),Kumar2012,False,,IEEE,Not available,Duopoly price competition of WLAN service providers in presence of heterogeneous user demand,e8255e2d8e117cb16c8f478a8285a15f,https://ieeexplore.ieee.org/document/6214194/
13898,"In the presence of several wireless local area network (WLAN) service providers, the users have to make a choice. The price charged and the congestion experienced by the users play an important role in making this choice. In this paper, we analyze the duopoly price competition between two WLAN service providers in the presence of four types of users. We prove that the distribution of heterogeneous user demand is governed by the Wardrop equilibrium. We also show the existence of the Nash equilibrium between competing WLAN service providers. It is further shown through analysis that the social welfare in Nash equilibrium is close to its maximal value. We find that compared to a strictly regulated monopoly, an unregulated WLAN duopoly market results in significant transfer of the surplus from service providers to users with negligible losses in efficiency.",robert schober,wireless local area network (WLAN),2012.0,10.1109/WCNC.2012.6214194,2012 IEEE Wireless Communications and Networking Conference (WCNC),Kumar2012,False,,IEEE,Not available,Duopoly price competition of WLAN service providers in presence of heterogeneous user demand,e8255e2d8e117cb16c8f478a8285a15f,https://ieeexplore.ieee.org/document/6214194/
13899,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",u. ayesta,Load management,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
13900,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",u. ayesta,Routing,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
13901,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",u. ayesta,Nash equilibrium,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
13902,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",u. ayesta,Network servers,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
13903,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",u. ayesta,Web server,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
13904,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",u. ayesta,Costs,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
13905,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Pricing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13906,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",u. ayesta,Communications Society,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
13907,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",u. ayesta,Scalability,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
13908,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",u. ayesta,Computer architecture,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
13909,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",u. ayesta,Performance loss,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
13910,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",o. brun,Load management,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
13911,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",o. brun,Routing,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
13912,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",o. brun,Nash equilibrium,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
13913,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",o. brun,Network servers,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
13914,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",o. brun,Web server,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
13915,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",o. brun,Costs,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
13916,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Costs,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13917,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",o. brun,Communications Society,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
13918,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",o. brun,Scalability,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
13919,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",o. brun,Computer architecture,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
13920,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",o. brun,Performance loss,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
13921,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",b. prabhu,Load management,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
13922,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",b. prabhu,Routing,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
13923,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",b. prabhu,Nash equilibrium,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
13924,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",b. prabhu,Network servers,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
13925,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",b. prabhu,Web server,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
13926,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",b. prabhu,Costs,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
13927,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Performance evaluation,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13928,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",b. prabhu,Communications Society,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
13929,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",b. prabhu,Scalability,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
13930,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",b. prabhu,Computer architecture,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
13931,"We investigate the price of anarchy of a load balancing game with K dispatchers. The service rates and holding costs are assumed to depend on the server, and the service discipline is assumed to be processor-sharing at each server. The performance criterion is taken to be the weighted mean number of jobs in the system, or equivalently, the weighted mean sojourn time in the system. For this game, we first show that, for a fixed amount of total incoming traffic, the worst-case Nash equilibrium occurs when each player routes exactly the same amount of traffic, i.e., when the game is symmetric. For this symmetric game, we provide the expression for the loads on the servers at the Nash equilibrium. Using this result we then show that, for a system with two or more servers, the price of anarchy, which is the worst-case ratio of the global cost of the Nash equilibrium to the global cost of the centralized setting, is lower bounded by K/(2¿K-1) and upper bounded by ¿K, independently of the number of servers.",b. prabhu,Performance loss,2010.0,10.1109/INFCOM.2010.5462195,2010 Proceedings IEEE INFOCOM,Ayesta2010,False,,IEEE,Not available,Price of Anarchy in Non-Cooperative Load Balancing,1ee0690b1b0333bf9488d15e4b82baf1,https://ieeexplore.ieee.org/document/5462195/
13932,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",lok law,Cognitive radio,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13933,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",lok law,Nash equilibrium,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13934,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",lok law,Media Access Protocol,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13935,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",lok law,Resource management,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13936,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",lok law,Computer science,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13937,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",lok law,Information analysis,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13938,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Routing,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13939,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",lok law,Closed-form solution,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13940,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",lok law,Monitoring,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13941,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",lok law,Interference,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13942,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",lok law,Frequency,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13943,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",jianwei huang,Cognitive radio,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13944,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",jianwei huang,Nash equilibrium,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13945,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",jianwei huang,Media Access Protocol,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13946,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",jianwei huang,Resource management,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13947,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",jianwei huang,Computer science,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13948,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",jianwei huang,Information analysis,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13949,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Information security,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13950,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",jianwei huang,Closed-form solution,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13951,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",jianwei huang,Monitoring,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13952,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",jianwei huang,Interference,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13953,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",jianwei huang,Frequency,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13954,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",mingyan liu,Cognitive radio,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13955,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",mingyan liu,Nash equilibrium,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13956,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",mingyan liu,Media Access Protocol,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13957,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",mingyan liu,Resource management,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13958,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",mingyan liu,Computer science,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13959,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",mingyan liu,Information analysis,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13960,"The price of anarchy (PoA) has been widely used in static games to quantify the loss of efficiency due to noncooperation. Here, we extend this concept to a general differential games framework. In addition, we introduce the price of information (PoI) to compare game performances under different information structures. We further characterize these two relative measures of performance for a class of scalar linear quadratic differential games. We obtain bounds on the PoI and the PoA for feedback differential games. We also find their approximations in a large population regime.",tamer basar,Power measurement,2010.0,10.1109/ACC.2010.5530924,Proceedings of the 2010 American Control Conference,Zhu2010,False,,IEEE,Not available,Price of anarchy and price of information in N-person linear-quadratic differential games,7add2ad69ff807a97073ce2cdc782ec5,https://ieeexplore.ieee.org/document/5530924/
13961,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",mingyan liu,Closed-form solution,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13962,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",mingyan liu,Monitoring,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13963,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",mingyan liu,Interference,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13964,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",mingyan liu,Frequency,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13965,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",shuo-yen li,Cognitive radio,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13966,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",shuo-yen li,Nash equilibrium,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13967,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",shuo-yen li,Media Access Protocol,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13968,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",shuo-yen li,Resource management,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13969,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",shuo-yen li,Computer science,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13970,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",shuo-yen li,Information analysis,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13971,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
13972,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",shuo-yen li,Closed-form solution,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13973,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",shuo-yen li,Monitoring,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13974,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",shuo-yen li,Interference,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13975,"In this paper, we model and analyze the interactions between secondary users in a spectrum overlay cognitive system as a cognitive MAC game. In this game, each secondary user can sense (and transmit) one of several channels, the availability of each channel is determined by the activity of the corresponding primary user. We show that this game belongs to the class of congestion game and thus there exists at least one Nash Equilibrium. We focus on analyzing the worst case efficiency loss (i.e., price of anarchy) at any Nash Equilibrium of such a game. Closed-form expressions of price of anarchy are derived for both symmetric and asymmetric games, with arbitrary channel and user heterogeneity. Several insights are also derived in terms of how to design better cognitive radio systems with less severe efficiency loss.",shuo-yen li,Frequency,2009.0,10.1109/GLOCOM.2009.5425334,GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference,Law2009,False,,IEEE,Not available,Price of Anarchy for Cognitive MAC Games,d4c710e0c96d5410687481b116c4ea4d,https://ieeexplore.ieee.org/document/5425334/
13976,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",pavan nuggehalli,Pricing,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
13977,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",pavan nuggehalli,Media Access Protocol,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
13978,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",pavan nuggehalli,Resource management,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
13979,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",pavan nuggehalli,Throughput,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
13980,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",pavan nuggehalli,Springs,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
13981,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",pavan nuggehalli,Wireless networks,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
13982,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
13983,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",pavan nuggehalli,Nash equilibrium,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
13984,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",pavan nuggehalli,Access protocols,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
13985,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",pavan nuggehalli,Quality of service,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
13986,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",pavan nuggehalli,Costs,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
13987,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",jennifer price,Pricing,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
13988,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",jennifer price,Media Access Protocol,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
13989,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",jennifer price,Resource management,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
13990,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",jennifer price,Throughput,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
13991,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",jennifer price,Springs,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
13992,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",jennifer price,Wireless networks,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
13993,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,price sensitivity,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
13994,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
13995,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",jennifer price,Nash equilibrium,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
13996,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",jennifer price,Access protocols,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
13997,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",jennifer price,Quality of service,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
13998,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",jennifer price,Costs,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
13999,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",tara javidi,Pricing,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
14000,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",tara javidi,Media Access Protocol,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
14001,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",tara javidi,Resource management,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
14002,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",tara javidi,Throughput,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
14003,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",tara javidi,Springs,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
14004,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",tara javidi,Wireless networks,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
14005,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",renato leme,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
14006,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",tara javidi,Nash equilibrium,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
14007,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",tara javidi,Access protocols,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
14008,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",tara javidi,Quality of service,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
14009,"In this paper, we examine the use of pricing for distributed, incentive-compatible and socially optimal resource allocation in a QoS-differentiated random-access wireless network. We argue that QoS mechanisms in wireless networks are susceptible to misuse by self-interested users. We first present a simple pricing scheme that leads to social optimality (i.e., achieves QoS-differentiated proportional fairness) when users' utility functions are known to the AP. We then characterize the price of anarchy when users are strategic. Finally, the centerpiece of this paper is a pricing scheme that ensures socially optimal operation as a Nash equilibrium strategy among users whose utility functions are not known and who attempt to access the channel in a decentralized manner.",tara javidi,Costs,2008.0,10.1109/GLOCOM.2008.ECP.981,IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference,Nuggehalli2008,False,,IEEE,Not available,Pricing and QoS in Wireless Random Access Networks,6216216a06c527f0e920700d30e20cbf,https://ieeexplore.ieee.org/document/4698756/
14010,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pratyush chakraborty,Nash equilibrium,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
14011,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pratyush chakraborty,Decentralized control,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
14012,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pratyush chakraborty,Optimization,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
14013,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pratyush chakraborty,Games,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
14014,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pratyush chakraborty,Electric vehicles,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
14015,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pratyush chakraborty,Schedules,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
14016,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,game theory,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
14017,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pratyush chakraborty,Equations,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
14018,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pramod khargonekar,Nash equilibrium,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
14019,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pramod khargonekar,Decentralized control,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
14020,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pramod khargonekar,Optimization,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
14021,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pramod khargonekar,Games,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
14022,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pramod khargonekar,Electric vehicles,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
14023,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pramod khargonekar,Schedules,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
14024,"New sources of uncertainty and variability are being introduced into modern power grids creating new control challenges. Examples include renewable generation from solar and wind generators, electric vehicles, etc. In addition, there is compelling value in reducing the peak electric power demand as that has a direct beneficial impact of reducing the need for new capital investments in overall power sector. Introduction of new sensing, communications and computational elements offers opportunities for novel control solutions. One promising approach to addressing these problems is to exploit the inherent flexibility in many types of electric power loads and use that to accommodate the inherent variability in renewable generation and/or to reduce the peak demand. In this paper, we focus on electric vehicles(EVs) as flexible loads in the context of renewable generation. We take an intra-day time horizon where we assume we have a good prediction of renewable generation. Based on the supply schedule of thermal generators and predicted supply of renewable generation, the charging of the electric vehicles is controlled to minimize the imbalance between generation and consumption using centralized and distributed control algorithms. We develop a pricing scheme based on the proportional allocation mechanism for the distributed case. Assuming individual loads are price takers, we show that there is a time varying price which can be set by the control authority such that it's objective aligns with the individual's objective. If the users are price anticipators, the corresponding situation can be formulated in a game-theoretic setting. Distributed algorithms are developed to compute solution in both the cases. We also analyze the “price of anarchy” and show that the worst case loss of efficiency is 0.25.",pramod khargonekar,Equations,2013.0,10.1109/CDC.2013.6760225,52nd IEEE Conference on Decision and Control,Chakraborty2013,False,,IEEE,Not available,Flexible loads and renewable integration: Distributed control and price of anarchy,0755cc616db6cecfb31a4065387090f0,https://ieeexplore.ieee.org/document/6760225/
14025,"Introduction of differentiated services on the Internet has failed primarily due to many economic impediments. We focus on the provider competition aspect, and develop a multi-class queueing network game framework to study it. Each network service provider is modeled as a single-server multi-class queue. Providers post prices for various service classes. Traffic is elastic and there are multiple types of it, each traffic-type is sensitive to a different degree to Quality of Service (QoS). Arriving users choose a provider and a class for service. We study the pricing and service competition between the providers in a game-theoretic setting. We provide sufficient conditions for the existence of Nash equilibrium in the Bertrand (pricing) game between the multi-class queueing service providers. We also characterize the inefficiency (price of anarchy) due to strategic DiffServ pricing.",parijat dube,DiffServ,2010.0,10.1109/ITC.2010.5608737,2010 22nd International Teletraffic Congress (lTC 22),Dube2010,False,,IEEE,Not available,DiffServ pricing games in multi-class queueing network models,bd7fdc8eb97936de5aa44a37eaa0c381,https://ieeexplore.ieee.org/document/5608737/
14026,"Introduction of differentiated services on the Internet has failed primarily due to many economic impediments. We focus on the provider competition aspect, and develop a multi-class queueing network game framework to study it. Each network service provider is modeled as a single-server multi-class queue. Providers post prices for various service classes. Traffic is elastic and there are multiple types of it, each traffic-type is sensitive to a different degree to Quality of Service (QoS). Arriving users choose a provider and a class for service. We study the pricing and service competition between the providers in a game-theoretic setting. We provide sufficient conditions for the existence of Nash equilibrium in the Bertrand (pricing) game between the multi-class queueing service providers. We also characterize the inefficiency (price of anarchy) due to strategic DiffServ pricing.",parijat dube,Queueing networks,2010.0,10.1109/ITC.2010.5608737,2010 22nd International Teletraffic Congress (lTC 22),Dube2010,False,,IEEE,Not available,DiffServ pricing games in multi-class queueing network models,bd7fdc8eb97936de5aa44a37eaa0c381,https://ieeexplore.ieee.org/document/5608737/
14027,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,price of anarchy,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
14028,"Introduction of differentiated services on the Internet has failed primarily due to many economic impediments. We focus on the provider competition aspect, and develop a multi-class queueing network game framework to study it. Each network service provider is modeled as a single-server multi-class queue. Providers post prices for various service classes. Traffic is elastic and there are multiple types of it, each traffic-type is sensitive to a different degree to Quality of Service (QoS). Arriving users choose a provider and a class for service. We study the pricing and service competition between the providers in a game-theoretic setting. We provide sufficient conditions for the existence of Nash equilibrium in the Bertrand (pricing) game between the multi-class queueing service providers. We also characterize the inefficiency (price of anarchy) due to strategic DiffServ pricing.",parijat dube,Bertrand game,2010.0,10.1109/ITC.2010.5608737,2010 22nd International Teletraffic Congress (lTC 22),Dube2010,False,,IEEE,Not available,DiffServ pricing games in multi-class queueing network models,bd7fdc8eb97936de5aa44a37eaa0c381,https://ieeexplore.ieee.org/document/5608737/
14029,"Introduction of differentiated services on the Internet has failed primarily due to many economic impediments. We focus on the provider competition aspect, and develop a multi-class queueing network game framework to study it. Each network service provider is modeled as a single-server multi-class queue. Providers post prices for various service classes. Traffic is elastic and there are multiple types of it, each traffic-type is sensitive to a different degree to Quality of Service (QoS). Arriving users choose a provider and a class for service. We study the pricing and service competition between the providers in a game-theoretic setting. We provide sufficient conditions for the existence of Nash equilibrium in the Bertrand (pricing) game between the multi-class queueing service providers. We also characterize the inefficiency (price of anarchy) due to strategic DiffServ pricing.",parijat dube,Nash equilibrium,2010.0,10.1109/ITC.2010.5608737,2010 22nd International Teletraffic Congress (lTC 22),Dube2010,False,,IEEE,Not available,DiffServ pricing games in multi-class queueing network models,bd7fdc8eb97936de5aa44a37eaa0c381,https://ieeexplore.ieee.org/document/5608737/
14030,"Introduction of differentiated services on the Internet has failed primarily due to many economic impediments. We focus on the provider competition aspect, and develop a multi-class queueing network game framework to study it. Each network service provider is modeled as a single-server multi-class queue. Providers post prices for various service classes. Traffic is elastic and there are multiple types of it, each traffic-type is sensitive to a different degree to Quality of Service (QoS). Arriving users choose a provider and a class for service. We study the pricing and service competition between the providers in a game-theoretic setting. We provide sufficient conditions for the existence of Nash equilibrium in the Bertrand (pricing) game between the multi-class queueing service providers. We also characterize the inefficiency (price of anarchy) due to strategic DiffServ pricing.",parijat dube,Price of Anarchy,2010.0,10.1109/ITC.2010.5608737,2010 22nd International Teletraffic Congress (lTC 22),Dube2010,False,,IEEE,Not available,DiffServ pricing games in multi-class queueing network models,bd7fdc8eb97936de5aa44a37eaa0c381,https://ieeexplore.ieee.org/document/5608737/
14031,"Introduction of differentiated services on the Internet has failed primarily due to many economic impediments. We focus on the provider competition aspect, and develop a multi-class queueing network game framework to study it. Each network service provider is modeled as a single-server multi-class queue. Providers post prices for various service classes. Traffic is elastic and there are multiple types of it, each traffic-type is sensitive to a different degree to Quality of Service (QoS). Arriving users choose a provider and a class for service. We study the pricing and service competition between the providers in a game-theoretic setting. We provide sufficient conditions for the existence of Nash equilibrium in the Bertrand (pricing) game between the multi-class queueing service providers. We also characterize the inefficiency (price of anarchy) due to strategic DiffServ pricing.",rahul jain,DiffServ,2010.0,10.1109/ITC.2010.5608737,2010 22nd International Teletraffic Congress (lTC 22),Dube2010,False,,IEEE,Not available,DiffServ pricing games in multi-class queueing network models,bd7fdc8eb97936de5aa44a37eaa0c381,https://ieeexplore.ieee.org/document/5608737/
14032,"Introduction of differentiated services on the Internet has failed primarily due to many economic impediments. We focus on the provider competition aspect, and develop a multi-class queueing network game framework to study it. Each network service provider is modeled as a single-server multi-class queue. Providers post prices for various service classes. Traffic is elastic and there are multiple types of it, each traffic-type is sensitive to a different degree to Quality of Service (QoS). Arriving users choose a provider and a class for service. We study the pricing and service competition between the providers in a game-theoretic setting. We provide sufficient conditions for the existence of Nash equilibrium in the Bertrand (pricing) game between the multi-class queueing service providers. We also characterize the inefficiency (price of anarchy) due to strategic DiffServ pricing.",rahul jain,Queueing networks,2010.0,10.1109/ITC.2010.5608737,2010 22nd International Teletraffic Congress (lTC 22),Dube2010,False,,IEEE,Not available,DiffServ pricing games in multi-class queueing network models,bd7fdc8eb97936de5aa44a37eaa0c381,https://ieeexplore.ieee.org/document/5608737/
14033,"Introduction of differentiated services on the Internet has failed primarily due to many economic impediments. We focus on the provider competition aspect, and develop a multi-class queueing network game framework to study it. Each network service provider is modeled as a single-server multi-class queue. Providers post prices for various service classes. Traffic is elastic and there are multiple types of it, each traffic-type is sensitive to a different degree to Quality of Service (QoS). Arriving users choose a provider and a class for service. We study the pricing and service competition between the providers in a game-theoretic setting. We provide sufficient conditions for the existence of Nash equilibrium in the Bertrand (pricing) game between the multi-class queueing service providers. We also characterize the inefficiency (price of anarchy) due to strategic DiffServ pricing.",rahul jain,Bertrand game,2010.0,10.1109/ITC.2010.5608737,2010 22nd International Teletraffic Congress (lTC 22),Dube2010,False,,IEEE,Not available,DiffServ pricing games in multi-class queueing network models,bd7fdc8eb97936de5aa44a37eaa0c381,https://ieeexplore.ieee.org/document/5608737/
14034,"Introduction of differentiated services on the Internet has failed primarily due to many economic impediments. We focus on the provider competition aspect, and develop a multi-class queueing network game framework to study it. Each network service provider is modeled as a single-server multi-class queue. Providers post prices for various service classes. Traffic is elastic and there are multiple types of it, each traffic-type is sensitive to a different degree to Quality of Service (QoS). Arriving users choose a provider and a class for service. We study the pricing and service competition between the providers in a game-theoretic setting. We provide sufficient conditions for the existence of Nash equilibrium in the Bertrand (pricing) game between the multi-class queueing service providers. We also characterize the inefficiency (price of anarchy) due to strategic DiffServ pricing.",rahul jain,Nash equilibrium,2010.0,10.1109/ITC.2010.5608737,2010 22nd International Teletraffic Congress (lTC 22),Dube2010,False,,IEEE,Not available,DiffServ pricing games in multi-class queueing network models,bd7fdc8eb97936de5aa44a37eaa0c381,https://ieeexplore.ieee.org/document/5608737/
14035,"Introduction of differentiated services on the Internet has failed primarily due to many economic impediments. We focus on the provider competition aspect, and develop a multi-class queueing network game framework to study it. Each network service provider is modeled as a single-server multi-class queue. Providers post prices for various service classes. Traffic is elastic and there are multiple types of it, each traffic-type is sensitive to a different degree to Quality of Service (QoS). Arriving users choose a provider and a class for service. We study the pricing and service competition between the providers in a game-theoretic setting. We provide sufficient conditions for the existence of Nash equilibrium in the Bertrand (pricing) game between the multi-class queueing service providers. We also characterize the inefficiency (price of anarchy) due to strategic DiffServ pricing.",rahul jain,Price of Anarchy,2010.0,10.1109/ITC.2010.5608737,2010 22nd International Teletraffic Congress (lTC 22),Dube2010,False,,IEEE,Not available,DiffServ pricing games in multi-class queueing network models,bd7fdc8eb97936de5aa44a37eaa0c381,https://ieeexplore.ieee.org/document/5608737/
14036,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",ehsan monsef,Nash equilibrium,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
14037,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",ehsan monsef,Global Positioning System,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
14038,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,GSP,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
14039,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",ehsan monsef,Routing,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
14040,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",ehsan monsef,Quality of service,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
14041,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",ehsan monsef,Delays,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
14042,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",ehsan monsef,Cost function,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
14043,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",ehsan monsef,Games,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
14044,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",tricha anjali,Nash equilibrium,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
14045,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",tricha anjali,Global Positioning System,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
14046,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",tricha anjali,Routing,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
14047,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",tricha anjali,Quality of service,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
14048,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",tricha anjali,Delays,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
14049,"The Generalized Second Price Auction has been the main mechanism used by search companies to auction positions for advertisements on search pages. In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full information setting, socially optimal Nash equilibria are known to exist (i.e., the Price of Stability is 1). This paper is the first to prove bounds on the price of anarchy, and to give any bounds in the Bayesian setting. Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated strategies. In the full information setting we prove a bound of 1.618 for the price of anarchy for pure Nash equilibria, and a bound of 4 for mixed Nash equilibria. We also prove a bound of 8 for the price of anarchy in the Bayesian setting, when valuations are drawn independently, and the valuation is known only to the bidder and only the distributions used are common knowledge. Our proof exhibits a combinatorial structure of Nash equilibria and uses this structure to bound the price of anarchy. While establishing the structure is simple in the case of pure and mixed Nash equilibria, the extension to the Bayesian setting requires the use of novel combinatorial techniques that can be of independent interest.",eva tardos,Sponsored Search Auction,2010.0,10.1109/FOCS.2010.75,2010 IEEE 51st Annual Symposium on Foundations of Computer Science,Leme2010,False,,IEEE,Not available,Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction,e029e070cea1fc594d992be74ec2b4ce,https://ieeexplore.ieee.org/document/5671346/
14050,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",tricha anjali,Cost function,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
14051,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",tricha anjali,Games,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
14052,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",sanjiv kapoor,Nash equilibrium,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
14053,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",sanjiv kapoor,Global Positioning System,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
14054,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",sanjiv kapoor,Routing,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
14055,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",sanjiv kapoor,Quality of service,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
14056,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",sanjiv kapoor,Delays,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
14057,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",sanjiv kapoor,Cost function,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
14058,"In this paper, we consider the inefficiency of distributed routing in a network of parallel links with class-based traffic. Network link behavior is modeled by the M/M/1-GPS queue (i.e. when links use General Processor Sharing(GPS) scheduling scheme to serve packets). Each traffic type is guaranteed a minimum capacity rate on each link using GPS scheduling. We show under specific demand conditions that, among multiple equilibria the worst-case Nash equilibrium occurs when each class dispatcher utilizes all the links to fulfill its demand. Using this fact, we give an upper bound on the Price of Anarchy (PoA). Our results also indicate that, while the price of selfish behavior can be unbounded in a specific demand setting, there exist demand regimes where the bound on PoA is reasonable. These results also apply to the resource allocation or load balancing applications in the processor sharing systems.",sanjiv kapoor,Games,2014.0,10.1109/INFOCOM.2014.6848186,IEEE INFOCOM 2014 - IEEE Conference on Computer Communications,Monsef2014,False,,IEEE,Not available,Price of Anarchy in network routing with class based capacity guarantees,6942451ed20059b96c8348fcac108563,https://ieeexplore.ieee.org/document/6848186/
14059,"It is important to analyze the efficiency of resource allocation with game theory in congested networks in which the users are selfish. The results are often obtained from a one-shot game, while in reality, the transmission is frequent and occurs more than once. We develop a repeated inter-session network coding game that is based on a novel Average cost share (ACS) pricing mechanism. The users choose repeated transmission rates and transmission modes between network coding and routing to maximize their own payoffs. The Price of anarchy (PoA) is adopted to analyze the efficiency of the resource allocation. Through considering different strategies for the multiusers at the next stage, we find that network coding can improve the efficiency of resource allocation in the congested networks. We discuss trigger strategies that keep players from routing at new stages.",gang wang,,2015.0,10.1049/cje.2015.04.029,Chinese Journal of Electronics,Wang2015,False,,IEEE,Not available,Repeated Inter-Session Network Coding Games with an Average Cost Share Pricing Mechanism in Congested Networks,442279055fd3df3879d3c32d929db4cf,
14060,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
14061,"It is important to analyze the efficiency of resource allocation with game theory in congested networks in which the users are selfish. The results are often obtained from a one-shot game, while in reality, the transmission is frequent and occurs more than once. We develop a repeated inter-session network coding game that is based on a novel Average cost share (ACS) pricing mechanism. The users choose repeated transmission rates and transmission modes between network coding and routing to maximize their own payoffs. The Price of anarchy (PoA) is adopted to analyze the efficiency of the resource allocation. Through considering different strategies for the multiusers at the next stage, we find that network coding can improve the efficiency of resource allocation in the congested networks. We discuss trigger strategies that keep players from routing at new stages.",jie leng,,2015.0,10.1049/cje.2015.04.029,Chinese Journal of Electronics,Wang2015,False,,IEEE,Not available,Repeated Inter-Session Network Coding Games with an Average Cost Share Pricing Mechanism in Congested Networks,442279055fd3df3879d3c32d929db4cf,
14062,"It is important to analyze the efficiency of resource allocation with game theory in congested networks in which the users are selfish. The results are often obtained from a one-shot game, while in reality, the transmission is frequent and occurs more than once. We develop a repeated inter-session network coding game that is based on a novel Average cost share (ACS) pricing mechanism. The users choose repeated transmission rates and transmission modes between network coding and routing to maximize their own payoffs. The Price of anarchy (PoA) is adopted to analyze the efficiency of the resource allocation. Through considering different strategies for the multiusers at the next stage, we find that network coding can improve the efficiency of resource allocation in the congested networks. We discuss trigger strategies that keep players from routing at new stages.",cangzhou yuan,,2015.0,10.1049/cje.2015.04.029,Chinese Journal of Electronics,Wang2015,False,,IEEE,Not available,Repeated Inter-Session Network Coding Games with an Average Cost Share Pricing Mechanism in Congested Networks,442279055fd3df3879d3c32d929db4cf,
14063,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",john musacchio,Diffserv networks,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
14064,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",john musacchio,Telecommunication traffic,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
14065,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",john musacchio,Traffic control,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
14066,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",john musacchio,Delay,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
14067,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",john musacchio,Nash equilibrium,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
14068,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",john musacchio,Costs,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
14069,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",john musacchio,Pricing,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
14070,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",john musacchio,Routing,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
14071,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
14072,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",john musacchio,Environmental economics,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
14073,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",john musacchio,Degradation,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
14074,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",shuang wu,Diffserv networks,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
14075,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",shuang wu,Telecommunication traffic,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
14076,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",shuang wu,Traffic control,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
14077,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",shuang wu,Delay,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
14078,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",shuang wu,Nash equilibrium,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
14079,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",shuang wu,Costs,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
14080,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",shuang wu,Pricing,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
14081,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",shuang wu,Routing,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
14082,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
14083,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",shuang wu,Environmental economics,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
14084,"We investigate competition between network providers that offer service to two types of traffic differing in their sensitivity to delay. We first consider competition amongst network providers who offer differentiated services by providing a priority queue for the delay sensitive traffic. We compare this to a situation in which all the competing network providers have network architectures that treat traffic of both types the same way. Our model of competition is Cournot in that service providers choose a rate to offer traffic of each type, and in-turn the total rate offered to each type of traffic determines the price of each traffic type. We are interested in the price of anarchy in these games of competition, which is defined as the ratio of the maximum achievable social utility versus the social utility attained when service providers selfishly maximize profits and reach a Nash equilibrium. We find that the price of anarchy is no more than 4/3 in our model of competing providers who offer differentiated services. In competition with providers that do not offer preferential service to delay sensitive traffic, we find the price of anarchy can be higher than 4/3, and we derive bounds for a number of important cases.",shuang wu,Degradation,2008.0,10.1109/ALLERTON.2008.4797615,"2008 46th Annual Allerton Conference on Communication, Control, and Computing",Musacchio2008,False,,IEEE,Not available,The price of anarchy in competing differentiated services networks,379430e9b0c96d1b045e90c98aa082c0,https://ieeexplore.ieee.org/document/4797615/
14085,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",libin jiang,Pricing,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
14086,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",libin jiang,Bandwidth,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
14087,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",libin jiang,Traffic control,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
14088,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",libin jiang,Routing,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
14089,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",libin jiang,Telecommunication traffic,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
14090,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",libin jiang,Cost function,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
14091,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",libin jiang,Delay,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
14092,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",libin jiang,Computer science,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
14093,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
14094,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",libin jiang,Communication networks,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
14095,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",libin jiang,Cultural differences,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
14096,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",shyam parekh,Pricing,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
14097,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",shyam parekh,Bandwidth,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
14098,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",shyam parekh,Traffic control,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
14099,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",shyam parekh,Routing,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
14100,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",shyam parekh,Telecommunication traffic,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
14101,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",shyam parekh,Cost function,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
14102,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",shyam parekh,Delay,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
14103,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",shyam parekh,Computer science,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
14104,"In this paper, we investigate how the scaled marginal-cost road pricing improves the price of anarchy (POA) in a traffic network with one origin-destination pair, where each edge in the network is associated with a latency function. The POA is defined as the worst possible ratio between the total latency of Nash flow and that of the socially optimal flow. All players in the noncooperative congestion game are divided into groups based on their price sensitivities. First, we consider the case where all players are partitioned into two groups in a network with two routes. In this case, it is shown that the total latency of the Nash flow can always reach the total latency of the socially optimal flow if the designed road price is charged on each link. We then analyze the POA for general case. For a distribution of price sensitivities satisfying certain conditions, a road pricing scheme is designed such that the unique Nash flow can achieve the social optimal flow, i.e., $\text {POA}=1$ . An algorithm is proposed to find the price scheme that optimizes the POA for any distribution of price sensitivities and any traffic network with one origin-destination pair. Finally, the results are applied to a traffic routing problem.",daniela rus,road pricing,2015.0,10.1109/TCST.2015.2410762,IEEE Transactions on Control Systems Technology,Wang2015,False,,IEEE,Not available,Analysis of Price of Anarchy in Traffic Networks With Heterogeneous Price-Sensitivity Populations,922362900db2fc2f95aa53dd2145ab99,https://ieeexplore.ieee.org/document/7066941/
14105,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
14106,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",shyam parekh,Communication networks,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
14107,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",shyam parekh,Cultural differences,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
14108,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",jean walrand,Pricing,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
14109,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",jean walrand,Bandwidth,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
14110,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",jean walrand,Traffic control,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
14111,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",jean walrand,Routing,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
14112,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",jean walrand,Telecommunication traffic,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
14113,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",jean walrand,Cost function,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
14114,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",jean walrand,Delay,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
14115,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",jean walrand,Computer science,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
14116,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",jocelyne elias,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
14117,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",jean walrand,Communication networks,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
14118,"The usage of a network usually differs significantly at different times of a day, due to users' time-preference. This phenomenon is also prominent in the market of ""bandwidth- on-demand"", since the demand is typically higher during large events. Thus, an unselfish ""social planner"" should deploy a proper pricing scheme to reduce congestions and achieve efficient use of the network (i.e., maximize the ""social welfare""); whereas a selfish service provider (SP) can exploit the time-preference to increase its revenue. In this paper, we present a model to study the important role of time-preference in network pricing. In this model, each user chooses his access time based on his preference, the congestion level, and the price he would be charged. Without pricing, the ""price of anarchy"" (POA) can be arbitrarily bad. We then derive a simple pricing scheme to maximize the social welfare. Next, from the SP's viewpoint, we consider the revenue- maximizing pricing strategy and its effect on the social welfare. We show that if the SP can differentiate its prices over different users and times, the maximal revenue can be achieved, as well as the maximal social welfare. However, if the SP has insufficient information about the users and can only differentiate its prices over the access times, then the resulting social welfare can be much less than the optimum, especially when there are many low-utility users. Otherwise, the difference is bounded and less significant.",jean walrand,Cultural differences,2008.0,10.1109/NOMSW.2007.33,NOMS Workshops 2008 - IEEE Network Operations and Management Symposium Workshops,Jiang2008,False,,IEEE,Not available,Time-Dependent Network Pricing and Bandwidth Trading,f7a15a9f703efc5779698a9c6c0dfc5d,https://ieeexplore.ieee.org/document/4509949/
14119,"Increased variability in power generation due to large scale integration of renewable energy sources such as wind and solar power is a significant technical challenge in power systems operations and control. In addition, there is a compelling value in reducing the peak demand since it occurs only for a small fraction of time, while the power system is designed to reliably satisfy the peak demand. One promising approach to reduce variability of renewable generation and peak demand is to harness the inherent flexibility of electric power loads of consumers. Efficient control techniques are required to manage flexibility in consumer demands. Advancements in sensing, communications and computational technologies infused into the power system resulting in the cyber-physical-social electric grid, are creating opportunities for novel control solutions. In this paper, we first formulate a centralized demand side management approach. Next, we consider a decentralized approach for controlling the loads where the flexible load consumers play a non-cooperative game among each other. We show that Nash equilibria exist for this game. Our main technical result is that the demand response game in decentralized approach has the property of being a valid monotone utility game. This in turn leads to robust lower bounds on the price of anarchy (POA) for our game.",pratyush chakraborty,Games,2014.0,10.1109/SmartGridComm.2014.7007720,2014 IEEE International Conference on Smart Grid Communications (SmartGridComm),Chakraborty2014,False,,IEEE,Not available,A demand response game and its robust price of anarchy,251780ce58a1c0f564342aaae2120172,https://ieeexplore.ieee.org/document/7007720/
14120,"Increased variability in power generation due to large scale integration of renewable energy sources such as wind and solar power is a significant technical challenge in power systems operations and control. In addition, there is a compelling value in reducing the peak demand since it occurs only for a small fraction of time, while the power system is designed to reliably satisfy the peak demand. One promising approach to reduce variability of renewable generation and peak demand is to harness the inherent flexibility of electric power loads of consumers. Efficient control techniques are required to manage flexibility in consumer demands. Advancements in sensing, communications and computational technologies infused into the power system resulting in the cyber-physical-social electric grid, are creating opportunities for novel control solutions. In this paper, we first formulate a centralized demand side management approach. Next, we consider a decentralized approach for controlling the loads where the flexible load consumers play a non-cooperative game among each other. We show that Nash equilibria exist for this game. Our main technical result is that the demand response game in decentralized approach has the property of being a valid monotone utility game. This in turn leads to robust lower bounds on the price of anarchy (POA) for our game.",pratyush chakraborty,Power demand,2014.0,10.1109/SmartGridComm.2014.7007720,2014 IEEE International Conference on Smart Grid Communications (SmartGridComm),Chakraborty2014,False,,IEEE,Not available,A demand response game and its robust price of anarchy,251780ce58a1c0f564342aaae2120172,https://ieeexplore.ieee.org/document/7007720/
14121,"Increased variability in power generation due to large scale integration of renewable energy sources such as wind and solar power is a significant technical challenge in power systems operations and control. In addition, there is a compelling value in reducing the peak demand since it occurs only for a small fraction of time, while the power system is designed to reliably satisfy the peak demand. One promising approach to reduce variability of renewable generation and peak demand is to harness the inherent flexibility of electric power loads of consumers. Efficient control techniques are required to manage flexibility in consumer demands. Advancements in sensing, communications and computational technologies infused into the power system resulting in the cyber-physical-social electric grid, are creating opportunities for novel control solutions. In this paper, we first formulate a centralized demand side management approach. Next, we consider a decentralized approach for controlling the loads where the flexible load consumers play a non-cooperative game among each other. We show that Nash equilibria exist for this game. Our main technical result is that the demand response game in decentralized approach has the property of being a valid monotone utility game. This in turn leads to robust lower bounds on the price of anarchy (POA) for our game.",pratyush chakraborty,Load management,2014.0,10.1109/SmartGridComm.2014.7007720,2014 IEEE International Conference on Smart Grid Communications (SmartGridComm),Chakraborty2014,False,,IEEE,Not available,A demand response game and its robust price of anarchy,251780ce58a1c0f564342aaae2120172,https://ieeexplore.ieee.org/document/7007720/
14122,"Increased variability in power generation due to large scale integration of renewable energy sources such as wind and solar power is a significant technical challenge in power systems operations and control. In addition, there is a compelling value in reducing the peak demand since it occurs only for a small fraction of time, while the power system is designed to reliably satisfy the peak demand. One promising approach to reduce variability of renewable generation and peak demand is to harness the inherent flexibility of electric power loads of consumers. Efficient control techniques are required to manage flexibility in consumer demands. Advancements in sensing, communications and computational technologies infused into the power system resulting in the cyber-physical-social electric grid, are creating opportunities for novel control solutions. In this paper, we first formulate a centralized demand side management approach. Next, we consider a decentralized approach for controlling the loads where the flexible load consumers play a non-cooperative game among each other. We show that Nash equilibria exist for this game. Our main technical result is that the demand response game in decentralized approach has the property of being a valid monotone utility game. This in turn leads to robust lower bounds on the price of anarchy (POA) for our game.",pratyush chakraborty,Schedules,2014.0,10.1109/SmartGridComm.2014.7007720,2014 IEEE International Conference on Smart Grid Communications (SmartGridComm),Chakraborty2014,False,,IEEE,Not available,A demand response game and its robust price of anarchy,251780ce58a1c0f564342aaae2120172,https://ieeexplore.ieee.org/document/7007720/
14123,"Increased variability in power generation due to large scale integration of renewable energy sources such as wind and solar power is a significant technical challenge in power systems operations and control. In addition, there is a compelling value in reducing the peak demand since it occurs only for a small fraction of time, while the power system is designed to reliably satisfy the peak demand. One promising approach to reduce variability of renewable generation and peak demand is to harness the inherent flexibility of electric power loads of consumers. Efficient control techniques are required to manage flexibility in consumer demands. Advancements in sensing, communications and computational technologies infused into the power system resulting in the cyber-physical-social electric grid, are creating opportunities for novel control solutions. In this paper, we first formulate a centralized demand side management approach. Next, we consider a decentralized approach for controlling the loads where the flexible load consumers play a non-cooperative game among each other. We show that Nash equilibria exist for this game. Our main technical result is that the demand response game in decentralized approach has the property of being a valid monotone utility game. This in turn leads to robust lower bounds on the price of anarchy (POA) for our game.",pratyush chakraborty,Centralized control,2014.0,10.1109/SmartGridComm.2014.7007720,2014 IEEE International Conference on Smart Grid Communications (SmartGridComm),Chakraborty2014,False,,IEEE,Not available,A demand response game and its robust price of anarchy,251780ce58a1c0f564342aaae2120172,https://ieeexplore.ieee.org/document/7007720/
14124,"Increased variability in power generation due to large scale integration of renewable energy sources such as wind and solar power is a significant technical challenge in power systems operations and control. In addition, there is a compelling value in reducing the peak demand since it occurs only for a small fraction of time, while the power system is designed to reliably satisfy the peak demand. One promising approach to reduce variability of renewable generation and peak demand is to harness the inherent flexibility of electric power loads of consumers. Efficient control techniques are required to manage flexibility in consumer demands. Advancements in sensing, communications and computational technologies infused into the power system resulting in the cyber-physical-social electric grid, are creating opportunities for novel control solutions. In this paper, we first formulate a centralized demand side management approach. Next, we consider a decentralized approach for controlling the loads where the flexible load consumers play a non-cooperative game among each other. We show that Nash equilibria exist for this game. Our main technical result is that the demand response game in decentralized approach has the property of being a valid monotone utility game. This in turn leads to robust lower bounds on the price of anarchy (POA) for our game.",pratyush chakraborty,Nash equilibrium,2014.0,10.1109/SmartGridComm.2014.7007720,2014 IEEE International Conference on Smart Grid Communications (SmartGridComm),Chakraborty2014,False,,IEEE,Not available,A demand response game and its robust price of anarchy,251780ce58a1c0f564342aaae2120172,https://ieeexplore.ieee.org/document/7007720/
14125,"Increased variability in power generation due to large scale integration of renewable energy sources such as wind and solar power is a significant technical challenge in power systems operations and control. In addition, there is a compelling value in reducing the peak demand since it occurs only for a small fraction of time, while the power system is designed to reliably satisfy the peak demand. One promising approach to reduce variability of renewable generation and peak demand is to harness the inherent flexibility of electric power loads of consumers. Efficient control techniques are required to manage flexibility in consumer demands. Advancements in sensing, communications and computational technologies infused into the power system resulting in the cyber-physical-social electric grid, are creating opportunities for novel control solutions. In this paper, we first formulate a centralized demand side management approach. Next, we consider a decentralized approach for controlling the loads where the flexible load consumers play a non-cooperative game among each other. We show that Nash equilibria exist for this game. Our main technical result is that the demand response game in decentralized approach has the property of being a valid monotone utility game. This in turn leads to robust lower bounds on the price of anarchy (POA) for our game.",pramod khargonekar,Games,2014.0,10.1109/SmartGridComm.2014.7007720,2014 IEEE International Conference on Smart Grid Communications (SmartGridComm),Chakraborty2014,False,,IEEE,Not available,A demand response game and its robust price of anarchy,251780ce58a1c0f564342aaae2120172,https://ieeexplore.ieee.org/document/7007720/
14126,"Increased variability in power generation due to large scale integration of renewable energy sources such as wind and solar power is a significant technical challenge in power systems operations and control. In addition, there is a compelling value in reducing the peak demand since it occurs only for a small fraction of time, while the power system is designed to reliably satisfy the peak demand. One promising approach to reduce variability of renewable generation and peak demand is to harness the inherent flexibility of electric power loads of consumers. Efficient control techniques are required to manage flexibility in consumer demands. Advancements in sensing, communications and computational technologies infused into the power system resulting in the cyber-physical-social electric grid, are creating opportunities for novel control solutions. In this paper, we first formulate a centralized demand side management approach. Next, we consider a decentralized approach for controlling the loads where the flexible load consumers play a non-cooperative game among each other. We show that Nash equilibria exist for this game. Our main technical result is that the demand response game in decentralized approach has the property of being a valid monotone utility game. This in turn leads to robust lower bounds on the price of anarchy (POA) for our game.",pramod khargonekar,Power demand,2014.0,10.1109/SmartGridComm.2014.7007720,2014 IEEE International Conference on Smart Grid Communications (SmartGridComm),Chakraborty2014,False,,IEEE,Not available,A demand response game and its robust price of anarchy,251780ce58a1c0f564342aaae2120172,https://ieeexplore.ieee.org/document/7007720/
14127,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
14128,"Increased variability in power generation due to large scale integration of renewable energy sources such as wind and solar power is a significant technical challenge in power systems operations and control. In addition, there is a compelling value in reducing the peak demand since it occurs only for a small fraction of time, while the power system is designed to reliably satisfy the peak demand. One promising approach to reduce variability of renewable generation and peak demand is to harness the inherent flexibility of electric power loads of consumers. Efficient control techniques are required to manage flexibility in consumer demands. Advancements in sensing, communications and computational technologies infused into the power system resulting in the cyber-physical-social electric grid, are creating opportunities for novel control solutions. In this paper, we first formulate a centralized demand side management approach. Next, we consider a decentralized approach for controlling the loads where the flexible load consumers play a non-cooperative game among each other. We show that Nash equilibria exist for this game. Our main technical result is that the demand response game in decentralized approach has the property of being a valid monotone utility game. This in turn leads to robust lower bounds on the price of anarchy (POA) for our game.",pramod khargonekar,Load management,2014.0,10.1109/SmartGridComm.2014.7007720,2014 IEEE International Conference on Smart Grid Communications (SmartGridComm),Chakraborty2014,False,,IEEE,Not available,A demand response game and its robust price of anarchy,251780ce58a1c0f564342aaae2120172,https://ieeexplore.ieee.org/document/7007720/
14129,"Increased variability in power generation due to large scale integration of renewable energy sources such as wind and solar power is a significant technical challenge in power systems operations and control. In addition, there is a compelling value in reducing the peak demand since it occurs only for a small fraction of time, while the power system is designed to reliably satisfy the peak demand. One promising approach to reduce variability of renewable generation and peak demand is to harness the inherent flexibility of electric power loads of consumers. Efficient control techniques are required to manage flexibility in consumer demands. Advancements in sensing, communications and computational technologies infused into the power system resulting in the cyber-physical-social electric grid, are creating opportunities for novel control solutions. In this paper, we first formulate a centralized demand side management approach. Next, we consider a decentralized approach for controlling the loads where the flexible load consumers play a non-cooperative game among each other. We show that Nash equilibria exist for this game. Our main technical result is that the demand response game in decentralized approach has the property of being a valid monotone utility game. This in turn leads to robust lower bounds on the price of anarchy (POA) for our game.",pramod khargonekar,Schedules,2014.0,10.1109/SmartGridComm.2014.7007720,2014 IEEE International Conference on Smart Grid Communications (SmartGridComm),Chakraborty2014,False,,IEEE,Not available,A demand response game and its robust price of anarchy,251780ce58a1c0f564342aaae2120172,https://ieeexplore.ieee.org/document/7007720/
14130,"Increased variability in power generation due to large scale integration of renewable energy sources such as wind and solar power is a significant technical challenge in power systems operations and control. In addition, there is a compelling value in reducing the peak demand since it occurs only for a small fraction of time, while the power system is designed to reliably satisfy the peak demand. One promising approach to reduce variability of renewable generation and peak demand is to harness the inherent flexibility of electric power loads of consumers. Efficient control techniques are required to manage flexibility in consumer demands. Advancements in sensing, communications and computational technologies infused into the power system resulting in the cyber-physical-social electric grid, are creating opportunities for novel control solutions. In this paper, we first formulate a centralized demand side management approach. Next, we consider a decentralized approach for controlling the loads where the flexible load consumers play a non-cooperative game among each other. We show that Nash equilibria exist for this game. Our main technical result is that the demand response game in decentralized approach has the property of being a valid monotone utility game. This in turn leads to robust lower bounds on the price of anarchy (POA) for our game.",pramod khargonekar,Centralized control,2014.0,10.1109/SmartGridComm.2014.7007720,2014 IEEE International Conference on Smart Grid Communications (SmartGridComm),Chakraborty2014,False,,IEEE,Not available,A demand response game and its robust price of anarchy,251780ce58a1c0f564342aaae2120172,https://ieeexplore.ieee.org/document/7007720/
14131,"Increased variability in power generation due to large scale integration of renewable energy sources such as wind and solar power is a significant technical challenge in power systems operations and control. In addition, there is a compelling value in reducing the peak demand since it occurs only for a small fraction of time, while the power system is designed to reliably satisfy the peak demand. One promising approach to reduce variability of renewable generation and peak demand is to harness the inherent flexibility of electric power loads of consumers. Efficient control techniques are required to manage flexibility in consumer demands. Advancements in sensing, communications and computational technologies infused into the power system resulting in the cyber-physical-social electric grid, are creating opportunities for novel control solutions. In this paper, we first formulate a centralized demand side management approach. Next, we consider a decentralized approach for controlling the loads where the flexible load consumers play a non-cooperative game among each other. We show that Nash equilibria exist for this game. Our main technical result is that the demand response game in decentralized approach has the property of being a valid monotone utility game. This in turn leads to robust lower bounds on the price of anarchy (POA) for our game.",pramod khargonekar,Nash equilibrium,2014.0,10.1109/SmartGridComm.2014.7007720,2014 IEEE International Conference on Smart Grid Communications (SmartGridComm),Chakraborty2014,False,,IEEE,Not available,A demand response game and its robust price of anarchy,251780ce58a1c0f564342aaae2120172,https://ieeexplore.ieee.org/document/7007720/
14132,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",lok law,Games,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
14133,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",lok law,Nash equilibrium,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
14134,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",lok law,Optimized production technology,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
14135,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",lok law,Resource management,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
14136,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",lok law,Computational modeling,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
14137,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",lok law,Computer science,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
14138,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
14139,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",lok law,Erbium,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
14140,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",jianwei huang,Games,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
14141,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",jianwei huang,Nash equilibrium,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
14142,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",jianwei huang,Optimized production technology,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
14143,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",jianwei huang,Resource management,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
14144,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",jianwei huang,Computational modeling,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
14145,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",jianwei huang,Computer science,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
14146,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",jianwei huang,Erbium,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
14147,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",mingyan liu,Games,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
14148,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",mingyan liu,Nash equilibrium,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
14149,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,population game model,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
14150,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",mingyan liu,Optimized production technology,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
14151,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",mingyan liu,Resource management,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
14152,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",mingyan liu,Computational modeling,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
14153,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",mingyan liu,Computer science,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
14154,"We consider a resource allocation game with heterogeneous players competing for several limited resources. We model this as a congestion game, where the share of each player is a decreasing function of the number of players choosing the same resource. In particular, we consider player-specific payoffs that depend not only on the shares of resource, but also on player-specific preference constants. We study the price of anarchy (PoA) for three families of this congestion game: identical, symmetric, and asymmetric games. We characterize the exact PoA in terms of the number of players and resources. By comparing the values of PoA for different games, we show that performance loss increases with the heterogeneity of games (i.e., the identical game has a better PoA in general). From the system design point of view, we identify the worst-case Nash Equilibrium, where all players are competing for a single resource.",mingyan liu,Erbium,2011.0,10.1109/WCSP.2011.6096882,2011 International Conference on Wireless Communications and Signal Processing (WCSP),Law2011,False,,IEEE,Not available,Price of anarchy of congestion games with player-specific constants,2108d434ef00a3da24ad07ef17063e41,https://ieeexplore.ieee.org/document/6096882/
14155,"The Price of Anarchy (PoA) is a measure for the loss of optimality due to decentralized behavior. It has been studied in many settings but, surprisingly, not in the most fundamental queueing system involving customers' decisions, namely, the single server Markovian queue. We find that the loss of efficiency in such systems is bounded by 50% in most practical cases, in which the arrival rate of the customers is significantly lower than the service rate. We also find that the loss of efficiency has an interesting behavior in two aspects: first, it sharply increases as the arrival rate comes close to the service rate; second, it becomes unbounded exactly when the arrival rate is greater than the service rate, a surprising behavior because the system is always stable. Knowing these bounds is important for the queue controller, for example when considering an investment in added service capacity.",gail gilboa-freedman,Adaptive control,2014.0,10.1109/TAC.2013.2270872,IEEE Transactions on Automatic Control,Gilboa-Freedman2014,False,,IEEE,Not available,The Price of Anarchy in the Markovian Single Server Queue,f3be4782a4e01807d8aac7e3e76fedf7,https://ieeexplore.ieee.org/document/6545289/
14156,"The Price of Anarchy (PoA) is a measure for the loss of optimality due to decentralized behavior. It has been studied in many settings but, surprisingly, not in the most fundamental queueing system involving customers' decisions, namely, the single server Markovian queue. We find that the loss of efficiency in such systems is bounded by 50% in most practical cases, in which the arrival rate of the customers is significantly lower than the service rate. We also find that the loss of efficiency has an interesting behavior in two aspects: first, it sharply increases as the arrival rate comes close to the service rate; second, it becomes unbounded exactly when the arrival rate is greater than the service rate, a surprising behavior because the system is always stable. Knowing these bounds is important for the queue controller, for example when considering an investment in added service capacity.",gail gilboa-freedman,cost function,2014.0,10.1109/TAC.2013.2270872,IEEE Transactions on Automatic Control,Gilboa-Freedman2014,False,,IEEE,Not available,The Price of Anarchy in the Markovian Single Server Queue,f3be4782a4e01807d8aac7e3e76fedf7,https://ieeexplore.ieee.org/document/6545289/
14157,"The Price of Anarchy (PoA) is a measure for the loss of optimality due to decentralized behavior. It has been studied in many settings but, surprisingly, not in the most fundamental queueing system involving customers' decisions, namely, the single server Markovian queue. We find that the loss of efficiency in such systems is bounded by 50% in most practical cases, in which the arrival rate of the customers is significantly lower than the service rate. We also find that the loss of efficiency has an interesting behavior in two aspects: first, it sharply increases as the arrival rate comes close to the service rate; second, it becomes unbounded exactly when the arrival rate is greater than the service rate, a surprising behavior because the system is always stable. Knowing these bounds is important for the queue controller, for example when considering an investment in added service capacity.",gail gilboa-freedman,numerical simulation,2014.0,10.1109/TAC.2013.2270872,IEEE Transactions on Automatic Control,Gilboa-Freedman2014,False,,IEEE,Not available,The Price of Anarchy in the Markovian Single Server Queue,f3be4782a4e01807d8aac7e3e76fedf7,https://ieeexplore.ieee.org/document/6545289/
14158,"The Price of Anarchy (PoA) is a measure for the loss of optimality due to decentralized behavior. It has been studied in many settings but, surprisingly, not in the most fundamental queueing system involving customers' decisions, namely, the single server Markovian queue. We find that the loss of efficiency in such systems is bounded by 50% in most practical cases, in which the arrival rate of the customers is significantly lower than the service rate. We also find that the loss of efficiency has an interesting behavior in two aspects: first, it sharply increases as the arrival rate comes close to the service rate; second, it becomes unbounded exactly when the arrival rate is greater than the service rate, a surprising behavior because the system is always stable. Knowing these bounds is important for the queue controller, for example when considering an investment in added service capacity.",refael hassin,Adaptive control,2014.0,10.1109/TAC.2013.2270872,IEEE Transactions on Automatic Control,Gilboa-Freedman2014,False,,IEEE,Not available,The Price of Anarchy in the Markovian Single Server Queue,f3be4782a4e01807d8aac7e3e76fedf7,https://ieeexplore.ieee.org/document/6545289/
14159,"The Price of Anarchy (PoA) is a measure for the loss of optimality due to decentralized behavior. It has been studied in many settings but, surprisingly, not in the most fundamental queueing system involving customers' decisions, namely, the single server Markovian queue. We find that the loss of efficiency in such systems is bounded by 50% in most practical cases, in which the arrival rate of the customers is significantly lower than the service rate. We also find that the loss of efficiency has an interesting behavior in two aspects: first, it sharply increases as the arrival rate comes close to the service rate; second, it becomes unbounded exactly when the arrival rate is greater than the service rate, a surprising behavior because the system is always stable. Knowing these bounds is important for the queue controller, for example when considering an investment in added service capacity.",refael hassin,cost function,2014.0,10.1109/TAC.2013.2270872,IEEE Transactions on Automatic Control,Gilboa-Freedman2014,False,,IEEE,Not available,The Price of Anarchy in the Markovian Single Server Queue,f3be4782a4e01807d8aac7e3e76fedf7,https://ieeexplore.ieee.org/document/6545289/
14160,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,pricing,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
14161,"The Price of Anarchy (PoA) is a measure for the loss of optimality due to decentralized behavior. It has been studied in many settings but, surprisingly, not in the most fundamental queueing system involving customers' decisions, namely, the single server Markovian queue. We find that the loss of efficiency in such systems is bounded by 50% in most practical cases, in which the arrival rate of the customers is significantly lower than the service rate. We also find that the loss of efficiency has an interesting behavior in two aspects: first, it sharply increases as the arrival rate comes close to the service rate; second, it becomes unbounded exactly when the arrival rate is greater than the service rate, a surprising behavior because the system is always stable. Knowing these bounds is important for the queue controller, for example when considering an investment in added service capacity.",refael hassin,numerical simulation,2014.0,10.1109/TAC.2013.2270872,IEEE Transactions on Automatic Control,Gilboa-Freedman2014,False,,IEEE,Not available,The Price of Anarchy in the Markovian Single Server Queue,f3be4782a4e01807d8aac7e3e76fedf7,https://ieeexplore.ieee.org/document/6545289/
14162,"The Price of Anarchy (PoA) is a measure for the loss of optimality due to decentralized behavior. It has been studied in many settings but, surprisingly, not in the most fundamental queueing system involving customers' decisions, namely, the single server Markovian queue. We find that the loss of efficiency in such systems is bounded by 50% in most practical cases, in which the arrival rate of the customers is significantly lower than the service rate. We also find that the loss of efficiency has an interesting behavior in two aspects: first, it sharply increases as the arrival rate comes close to the service rate; second, it becomes unbounded exactly when the arrival rate is greater than the service rate, a surprising behavior because the system is always stable. Knowing these bounds is important for the queue controller, for example when considering an investment in added service capacity.",yoav kerner,Adaptive control,2014.0,10.1109/TAC.2013.2270872,IEEE Transactions on Automatic Control,Gilboa-Freedman2014,False,,IEEE,Not available,The Price of Anarchy in the Markovian Single Server Queue,f3be4782a4e01807d8aac7e3e76fedf7,https://ieeexplore.ieee.org/document/6545289/
14163,"The Price of Anarchy (PoA) is a measure for the loss of optimality due to decentralized behavior. It has been studied in many settings but, surprisingly, not in the most fundamental queueing system involving customers' decisions, namely, the single server Markovian queue. We find that the loss of efficiency in such systems is bounded by 50% in most practical cases, in which the arrival rate of the customers is significantly lower than the service rate. We also find that the loss of efficiency has an interesting behavior in two aspects: first, it sharply increases as the arrival rate comes close to the service rate; second, it becomes unbounded exactly when the arrival rate is greater than the service rate, a surprising behavior because the system is always stable. Knowing these bounds is important for the queue controller, for example when considering an investment in added service capacity.",yoav kerner,cost function,2014.0,10.1109/TAC.2013.2270872,IEEE Transactions on Automatic Control,Gilboa-Freedman2014,False,,IEEE,Not available,The Price of Anarchy in the Markovian Single Server Queue,f3be4782a4e01807d8aac7e3e76fedf7,https://ieeexplore.ieee.org/document/6545289/
14164,"The Price of Anarchy (PoA) is a measure for the loss of optimality due to decentralized behavior. It has been studied in many settings but, surprisingly, not in the most fundamental queueing system involving customers' decisions, namely, the single server Markovian queue. We find that the loss of efficiency in such systems is bounded by 50% in most practical cases, in which the arrival rate of the customers is significantly lower than the service rate. We also find that the loss of efficiency has an interesting behavior in two aspects: first, it sharply increases as the arrival rate comes close to the service rate; second, it becomes unbounded exactly when the arrival rate is greater than the service rate, a surprising behavior because the system is always stable. Knowing these bounds is important for the queue controller, for example when considering an investment in added service capacity.",yoav kerner,numerical simulation,2014.0,10.1109/TAC.2013.2270872,IEEE Transactions on Automatic Control,Gilboa-Freedman2014,False,,IEEE,Not available,The Price of Anarchy in the Markovian Single Server Queue,f3be4782a4e01807d8aac7e3e76fedf7,https://ieeexplore.ieee.org/document/6545289/
14165,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",bo gao,Mobile computing,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
14166,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",bo gao,mobile cloud computing,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
14167,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",bo gao,energy-aware,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
14168,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",bo gao,Mobile computing,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
14169,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",bo gao,mobile cloud computing,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
14170,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",bo gao,energy-aware,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
14171,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,replicator dynamics,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
14172,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",ligang he,Mobile computing,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
14173,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",ligang he,mobile cloud computing,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
14174,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",ligang he,energy-aware,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
14175,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",ligang he,Mobile computing,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
14176,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",ligang he,mobile cloud computing,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
14177,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",ligang he,energy-aware,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
14178,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",stephen jarvis,Mobile computing,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
14179,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",stephen jarvis,mobile cloud computing,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
14180,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",stephen jarvis,energy-aware,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
14181,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",stephen jarvis,Mobile computing,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
14182,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",fabio martignon,Stackelberg game,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
14183,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",stephen jarvis,mobile cloud computing,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
14184,"With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model's efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications.",stephen jarvis,energy-aware,2015.0,10.1109/ACCESS.2016.2518179,IEEE Access,Gao2015,True,,IEEE,Not available,Offload Decision Models and the Price of Anarchy in Mobile Cloud Application Ecosystems,373bfa3a30fa8cca7f2e2038ec507e7c,https://ieeexplore.ieee.org/document/7389327/
14185,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",ninoslav marina,Relays,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
14186,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",ninoslav marina,Peer to peer computing,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
14187,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",ninoslav marina,Game theory,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
14188,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",ninoslav marina,Nash equilibrium,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
14189,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",ninoslav marina,Upper bound,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
14190,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",ninoslav marina,Information analysis,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
14191,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",ninoslav marina,Performance analysis,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
14192,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",ninoslav marina,Wireless networks,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
14193,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,Cognitive radio networks (CRNs),2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
14194,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",ninoslav marina,Transmitters,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
14195,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",ninoslav marina,Information rates,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
14196,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",are hjorungnes,Relays,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
14197,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",are hjorungnes,Peer to peer computing,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
14198,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",are hjorungnes,Game theory,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
14199,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",are hjorungnes,Nash equilibrium,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
14200,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",are hjorungnes,Upper bound,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
14201,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",are hjorungnes,Information analysis,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
14202,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",are hjorungnes,Performance analysis,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
14203,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",are hjorungnes,Wireless networks,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
14204,"This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR systems.",lin chen,network selection,2013.0,10.1109/TVT.2013.2264294,IEEE Transactions on Vehicular Technology,Elias2013,False,,IEEE,Not available,"Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy",5db220d8f906310af104b033561c3c0a,https://ieeexplore.ieee.org/document/6517527/
14205,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",are hjorungnes,Transmitters,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
14206,"In this paper, we propose an idea on how game and information theoretic results can be combined to analyze the performance of wireless cooperative networks. More precisely, we consider a four node wireless network, where the transmit nodes help each other acting as relays during the periods in which they do not transmit their own information. In order to help the other node, each node has to use a part of its available power to relay the signal of the other transmitter. The network is modeled as a non-cooperative game in which each player (node) maximizes its own utility function (information rate). The goal of the game designer (network provider) is to maximize the objective function (in this case the sum rate) in order to get better network efficiency. Here, we analyze the so called equilibrium efficiency, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Using game theoretical language, it is the price of anarchy of the proposed game. In this scenario, the Nash equilibrium is achieved by selfish (non-cooperative) behavior between the players. In other words, in order to maximize its own utility function each node chooses a strategy to use its available power only for itself, and not helping the other node. Earlier, we derived an upper bound for the worst case equilibrium efficiency and in this paper we present a lower bound. From the comparisons, we conclude that for path loss coefficients that are of practical importance the proposed bounds are tight. Our results show that the worst case equilibrium efficiency for the proposed simple network is very small (below 10%). Hence, there is a large possibility for improvements if the network nodes are encouraged to cooperate by designing certain mechanisms.",are hjorungnes,Information rates,2009.0,10.1109/ISIT.2009.5205617,2009 IEEE International Symposium on Information Theory,Marina2009,False,,IEEE,Not available,Power allocation game in a four node relay network: A lower bound on the price of anarchy,90cf8092d2a786d988ebacec48c077a7,https://ieeexplore.ieee.org/document/5205617/
14207,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",benjamin grimmer,Games,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
14208,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",benjamin grimmer,Routing,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
14209,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",benjamin grimmer,Delays,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
14210,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",benjamin grimmer,Global Positioning System,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
14211,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",benjamin grimmer,Nash equilibrium,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
14212,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",benjamin grimmer,Processor scheduling,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
14213,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",benjamin grimmer,Servers,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
14214,"We consider distributed network routing for networks that support differentiated services, where services are prioritized by a proportional weighting system. We use the classical Generalized Processor Sharing (GPS) scheme for scheduling traffic on network links. In such a scheme, each type of traffic is guaranteed a minimum capacity rate based on its priority. To model the performance of this scheme and to account for autonomous routing we consider scheduling games on networks. We consider both networks with a set of parallel links (which also applies to processor scheduling) and more general scenarios where the network is a multi-graph. In each of these settings we consider two different routing schemes: Atomic and Non-Atomic. Atomic routing requires all traffic of one type to follow a single path. Non-Atomic routing splits traffic into a flow over multiple paths. For each type of game, we prove either the existence of Nash Equilibrium or give a counterexample. We consider the inefficiency of equilibrium (termed as the price of anarchy) and provide price of anarchy upper bounds under reasonable assumptions. In general, this inefficiency in queuing systems is unbounded. We also provide complexity results on computing optimal solutions and the existence of equilibrium in these games.",sanjiv kapoor,Games,2016.0,10.1109/INFOCOM.2016.7524352,IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications,Grimmer2016,False,,IEEE,Not available,Nash equilibrium and the price of anarchy in priority based network routing,7f9b90b27d4fd7a7a47bba5a29e72e8e,https://ieeexplore.ieee.org/document/7524352/
14215,"<p>We consider a Markovian queueing system with <i>N</i> heterogeneous service facilities, each of which has multiple servers available, linear holding costs, a fixed value of service and a first-come-first-serve queue discipline. Customers arriving in the system can be either rejected or sent to one of the <i>N</i> facilities. Two different types of control policies are considered, which we refer to as ‘selfishly optimal’ and ‘socially optimal’. We prove the equivalence of two different Markov Decision Process formulations, and then show that classical <i>M</i>/<i>M</i>/1 queue results from the early literature on behavioural queueing theory can be generalized to multiple dimensions in an elegant way. In particular, the state space of the continuous-time Markov process induced by a socially optimal policy is contained within that of the selfishly optimal policy. We also show that this result holds when customers are divided into an arbitrary number of heterogeneous classes, provided that the service rates remain non-discriminatory.</p>",rob shone,,2015.0,10.1057/jors.2015.98,Journal of the Operational Research Society,Shone2015,Not available,,Nature,Not available,Containment of socially optimal policies in multiple-facility Markovian queueing systems,7e14b5751602501225481ed2de4f9fb3,http://dx.doi.org/10.1057/jors.2015.98
14216,"<p>We consider a Markovian queueing system with <i>N</i> heterogeneous service facilities, each of which has multiple servers available, linear holding costs, a fixed value of service and a first-come-first-serve queue discipline. Customers arriving in the system can be either rejected or sent to one of the <i>N</i> facilities. Two different types of control policies are considered, which we refer to as ‘selfishly optimal’ and ‘socially optimal’. We prove the equivalence of two different Markov Decision Process formulations, and then show that classical <i>M</i>/<i>M</i>/1 queue results from the early literature on behavioural queueing theory can be generalized to multiple dimensions in an elegant way. In particular, the state space of the continuous-time Markov process induced by a socially optimal policy is contained within that of the selfishly optimal policy. We also show that this result holds when customers are divided into an arbitrary number of heterogeneous classes, provided that the service rates remain non-discriminatory.</p>",vincent knight,,2015.0,10.1057/jors.2015.98,Journal of the Operational Research Society,Shone2015,Not available,,Nature,Not available,Containment of socially optimal policies in multiple-facility Markovian queueing systems,7e14b5751602501225481ed2de4f9fb3,http://dx.doi.org/10.1057/jors.2015.98
14217,"<p>Facing the threats of infectious diseases, we take various actions to protect ourselves, but few studies considered an evolving system with competing strategies. In view of that, we propose an evolutionary epidemic model coupled with human behaviors, where individuals have three strategies: vaccination, self-protection and laissez faire, and could adjust their strategies according to their neighbors' strategies and payoffs at the beginning of each new season of epidemic spreading. We found a counter-intuitive phenomenon analogous to the well-known <i>Braess's Paradox</i>, namely a better condition may lead to worse performance. Specifically speaking, increasing the successful rate of self-protection does not necessarily reduce the epidemic size or improve the system payoff. The range and degree of the Braess's Paradox are sensitive to both the parameters characterizing the epidemic spreading and the strategy payoff, while the existence of the Braess's Paradox is insensitive to the network topologies. This phenomenon can be well explained by a mean-field approximation. Our study demonstrates an important fact that a better condition for individuals may yield a worse outcome for the society.</p>",zimo yang,Computational models,2013.0,10.1038/srep03292,Scientific Reports,Zhang2013,Not available,,Nature,Not available,Braess's Paradox in Epidemic Game: Better Condition Results in Less Payoff,551a0daab3513be189f0f7a0e0fd3e06,http://dx.doi.org/10.1038/srep03292
14218,"<p>Although transnational relations is a frequently employed phrase in international relations (IR) since the early debates of the 1970s, the literature in fact still shows surprisingly little theorization of the concept. Seeking to theorize ‘the transnational’ beyond what is currently on offer in mainstream IR discourse, this article argues that the field of transnational relations has in fact much to gain from the insights articulated by the transnationalist perspective elaborated within ‘transnational historical materialism’, and in particular by the ‘Amsterdam Project’ in International Political Economy. After presenting a critical review of what are interpreted as liberal, ahistorical and actor-centred perspectives on transnational relations dominating the mainstream, this article elaborates and builds upon this alternative transnationalist perspective by showing how it is grounded in a historical <i>materialism</i> emphasizing the constitutive power of transnational (economic) <i>structures</i>, while at the same time re-claiming the role of <i>class agency</i>. Briefly sketching on this basis the development of transnational relations in the global political economy, the article examines the theoretical implications of such a historical (materialist) analysis for a theory of transnational relations. Rather than viewing transnational relations as moving us beyond international relations altogether, it is concluded that the question is rather how the former gives content to the latter. Critical here, it is argued, is the process of <i>transnational class formation</i> and the role of capitalist class strategy beyond national borders in restructuring global capitalist social relations.</p>",bastiaan apeldoorn,,2004.0,10.1057/palgrave.jird.1800010,Journal of International Relations and Development,Apeldoorn2004,Not available,,Nature,Not available,Theorizing the transnational: a historical materialist approach,03a71ebfa2a91f5b6d845222fe88d7ad,http://dx.doi.org/10.1057/palgrave.jird.1800010
14219,"<p>Facing the threats of infectious diseases, we take various actions to protect ourselves, but few studies considered an evolving system with competing strategies. In view of that, we propose an evolutionary epidemic model coupled with human behaviors, where individuals have three strategies: vaccination, self-protection and laissez faire, and could adjust their strategies according to their neighbors' strategies and payoffs at the beginning of each new season of epidemic spreading. We found a counter-intuitive phenomenon analogous to the well-known <i>Braess's Paradox</i>, namely a better condition may lead to worse performance. Specifically speaking, increasing the successful rate of self-protection does not necessarily reduce the epidemic size or improve the system payoff. The range and degree of the Braess's Paradox are sensitive to both the parameters characterizing the epidemic spreading and the strategy payoff, while the existence of the Braess's Paradox is insensitive to the network topologies. This phenomenon can be well explained by a mean-field approximation. Our study demonstrates an important fact that a better condition for individuals may yield a worse outcome for the society.</p>",zimo yang,Applied mathematics,2013.0,10.1038/srep03292,Scientific Reports,Zhang2013,Not available,,Nature,Not available,Braess's Paradox in Epidemic Game: Better Condition Results in Less Payoff,551a0daab3513be189f0f7a0e0fd3e06,http://dx.doi.org/10.1038/srep03292
14220,"<p>This article analyses the impact and legacy of Niccolò Machiavelli’s thought in International Relations. It explores the various and contrasting interpretations that have characterized the ‘Machiavellian Moment’ in political theory and international studies, revisiting some of its fundamental concepts – such as <i>fortuna, virtù, cose di stato</i> – and highlighting their strong heuristic and analytical potential for International Relations. The article also serves as an Introduction to the various sections and contributions of the Special Issue.</p>",antonio cerella,,2016.0,10.1057/ip.2016.8,International Politics,Cerella2016,Not available,,Nature,Not available,Machiavelli reloaded: Perceptions and misperceptions of the ‘Prince of realism’,e25414507299e7464a09eea35de36c5e,http://dx.doi.org/10.1057/ip.2016.8
14221,"<p>This article analyses the impact and legacy of Niccolò Machiavelli’s thought in International Relations. It explores the various and contrasting interpretations that have characterized the ‘Machiavellian Moment’ in political theory and international studies, revisiting some of its fundamental concepts – such as <i>fortuna, virtù, cose di stato</i> – and highlighting their strong heuristic and analytical potential for International Relations. The article also serves as an Introduction to the various sections and contributions of the Special Issue.</p>",ernesto gallo,,2016.0,10.1057/ip.2016.8,International Politics,Cerella2016,Not available,,Nature,Not available,Machiavelli reloaded: Perceptions and misperceptions of the ‘Prince of realism’,e25414507299e7464a09eea35de36c5e,http://dx.doi.org/10.1057/ip.2016.8
14222,"<p>For scholars interested in what Jason Frank calls “the outsize authority of the Founders in our jurisprudence and our politics,” I propose reviewing the legacies of <i>The Federalist Papers</i> from the vantages offered by Toni Morrison and Herman Melville. Frank insists that understanding the politics of the <i>Federalist</i> requires grasping how the argument is felt and staged, as well as how its rhetoric constitutes the subjectivities of its readers. To that end, I linger on three words—empire, women, and slaves—that appear in Frank’s <i>Publius and Political Imagination</i> yet do more work than he explicitly allows. Passing references, omissions, elisions, and unowned contradictions reveal how the Founders evoked figures of the conquered and the enslaved to support the consolidation of the nation; they also suggest dimensions of the Founders’ imagination whose analysis could enlarge and sharpen Frank’s argument about the <i>Federalist</i>’s formative and depoliticizing work.</p>",lawrie balfour,,2015.0,10.1057/pol.2015.29,Polity,Balfour2015,Not available,,Nature,Not available,Reading Publius with Morrison and Melville,99d46b600ddd404a4303b787df82601a,http://dx.doi.org/10.1057/pol.2015.29
14223,"<p>The marketing of alcohol produces a new challenge for policy development internationally, in part because of the increase in the use of new, unmeasured technologies. Many of these new developments are, as yet, relatively invisible in the policy arena. New approaches in branding, the utilization of marketing opportunities via branded events and new products provide additional complexity to attempts to monitor and to restrict the impact of marketing on young people and other vulnerable groups. Current attempts to restrict marketing globally, which rely primarily on voluntary codes and focus on traditional media, are inadequate to these challenges. A new statutory framework is required to enable the monitoring and control of the full marketing mix in ways which match the sophistication of the marketing efforts themselves.</p>",sally casswell,,2005.0,10.1057/palgrave.jphp.3200040,Journal of Public Health Policy,Casswell2005,Not available,,Nature,Not available,Regulation of Alcohol Marketing: A Global View,dbf3fe9e6a2a6148f62c0347f1e0a064,http://dx.doi.org/10.1057/palgrave.jphp.3200040
14224,"<p>The marketing of alcohol produces a new challenge for policy development internationally, in part because of the increase in the use of new, unmeasured technologies. Many of these new developments are, as yet, relatively invisible in the policy arena. New approaches in branding, the utilization of marketing opportunities via branded events and new products provide additional complexity to attempts to monitor and to restrict the impact of marketing on young people and other vulnerable groups. Current attempts to restrict marketing globally, which rely primarily on voluntary codes and focus on traditional media, are inadequate to these challenges. A new statutory framework is required to enable the monitoring and control of the full marketing mix in ways which match the sophistication of the marketing efforts themselves.</p>",anna maxwell,,2005.0,10.1057/palgrave.jphp.3200040,Journal of Public Health Policy,Casswell2005,Not available,,Nature,Not available,Regulation of Alcohol Marketing: A Global View,dbf3fe9e6a2a6148f62c0347f1e0a064,http://dx.doi.org/10.1057/palgrave.jphp.3200040
14225,"<p>‘Normative Power Europe’, a concept introduced by Ian Manners in 2002 in order to describe the international identity of the European Union (EU), remains a lasting point of reference for academic as well as political debates. However, many contributions to this discussion tend to essentialise notions of a collective identity where normative self-depictions are uncritically used as an explanation for the EU's external actions. The main challenge, thus, is to reconstruct how a self is invented in the conduct of foreign and security policies as a discourse of locating others and articulating insecurities. These discursive processes, I will argue, are highly productive of hierarchical relations and justification narratives overlooked by most research on the EU's security and defence policies. The results of a reconstruction of EU discourse on the European Security and Defence Policy missions in the Democratic Republic of Congo lead to the preliminary conclusion that the EU might increasingly be imagined as a ‘civilising power’, partly re-activating its imperial legacies of the 19th century.</p>",gabi schlag,,2011.0,10.1057/jird.2011.17,Journal of International Relations and Development,Schlag2011,Not available,,Nature,Not available,Into the ‘Heart of Darkness’ — EU's civilising mission in the DR Congo,a24e9bc790407366d01733d53e5a416f,http://dx.doi.org/10.1057/jird.2011.17
14226,"<p>The international community appears to have embraced a new norm — that of universal access to antiretroviral drugs. The process by which this norm has found acceptance raises interesting questions about how norm entrepreneurs frame their arguments, the role of non-state actors in realizing a norm, and the importance of existent complementary norms. To understand the success of the norm of universal antiretroviral access, I examine the failure of an earlier health-related norm — that of universal primary health care. The campaign for universal antiretroviral access points to a need for a more nuanced understanding of norm evolution within the international community and a more holistic vision of which actors can facilitate the realization of a norm.</p>",jeremy youde,,2008.0,10.1057/jird.2008.10,Journal of International Relations and Development,Youde2008,Not available,,Nature,Not available,Is universal access to antiretroviral drugs an emerging international norm?,78f5ba2c671167f5bc5bdc77f41c1511,http://dx.doi.org/10.1057/jird.2008.10
14227,"<p>This article gauges the influence of transnational advocacy networks on the activities of the International Monetary Fund (IMF) throughout the 1990s. In assessing civil society's advocacy work, this article makes two main contributions. From a theoretical perspective, our case-study lends credit to the emergent literature discussing the gray zone between rational choice theory and constructivism. Indeed, as we show, IMF's changes were not due to civil society's pressures but rather to the working of the mechanism of <i>reputation</i> – which combined aspects of socialization and coercion. From an empirical perspective, our findings suggest that civil society's influence on the policies of an international economic organization might be easily overstated.</p>",roberto belloni,,2013.0,10.1057/ip.2013.14,International Politics,Belloni2013,Not available,,Nature,Not available,The IMF and civil society,5c255b06e9121c9074de5f87308ed56c,http://dx.doi.org/10.1057/ip.2013.14
14228,"<p>This article gauges the influence of transnational advocacy networks on the activities of the International Monetary Fund (IMF) throughout the 1990s. In assessing civil society's advocacy work, this article makes two main contributions. From a theoretical perspective, our case-study lends credit to the emergent literature discussing the gray zone between rational choice theory and constructivism. Indeed, as we show, IMF's changes were not due to civil society's pressures but rather to the working of the mechanism of <i>reputation</i> – which combined aspects of socialization and coercion. From an empirical perspective, our findings suggest that civil society's influence on the policies of an international economic organization might be easily overstated.</p>",manuela moschella,,2013.0,10.1057/ip.2013.14,International Politics,Belloni2013,Not available,,Nature,Not available,The IMF and civil society,5c255b06e9121c9074de5f87308ed56c,http://dx.doi.org/10.1057/ip.2013.14
14229,"<p>Facing the threats of infectious diseases, we take various actions to protect ourselves, but few studies considered an evolving system with competing strategies. In view of that, we propose an evolutionary epidemic model coupled with human behaviors, where individuals have three strategies: vaccination, self-protection and laissez faire, and could adjust their strategies according to their neighbors' strategies and payoffs at the beginning of each new season of epidemic spreading. We found a counter-intuitive phenomenon analogous to the well-known <i>Braess's Paradox</i>, namely a better condition may lead to worse performance. Specifically speaking, increasing the successful rate of self-protection does not necessarily reduce the epidemic size or improve the system payoff. The range and degree of the Braess's Paradox are sensitive to both the parameters characterizing the epidemic spreading and the strategy payoff, while the existence of the Braess's Paradox is insensitive to the network topologies. This phenomenon can be well explained by a mean-field approximation. Our study demonstrates an important fact that a better condition for individuals may yield a worse outcome for the society.</p>",zimo yang,Applied physics,2013.0,10.1038/srep03292,Scientific Reports,Zhang2013,Not available,,Nature,Not available,Braess's Paradox in Epidemic Game: Better Condition Results in Less Payoff,551a0daab3513be189f0f7a0e0fd3e06,http://dx.doi.org/10.1038/srep03292
14230,"<p>In the post-Cold War era, a voluminous literature has developed to define failed states, identify the causes and parameters of failure, and devise ways for dealing with the problems associated with state fragility and failure. While there is some theoretical diversity within this literature — notably between neoliberal institutionalists and neo-Weberian institutionalists — state failure is commonly defined in terms of state capacity. Since capacity is conceived in technical and ‘objective’ terms, the political nature of projects of state construction (and reconstruction) is masked. Whereas the existence of social and political struggles of various types is often recognized by the failed states literature, these conflicts are abstracted from political and social institutions. Such an analysis then extends into programmes that attempt to build state capacity as part of projects that seek to manage social and political conflict. Ascertaining which interests are involved and which interests are left out in such processes is essential for any understanding of the prospects or otherwise of conflict resolution.</p>",shahar hameiri,,2007.0,10.1057/palgrave.jird.1800120,Journal of International Relations and Development,Hameiri2007,Not available,,Nature,Not available,Failed states or a failed paradigm? State capacity and the limits of institutionalism,6165cc4c03ea990bc13dad894f44ffa8,http://dx.doi.org/10.1057/palgrave.jird.1800120
14231,"<p>Ruman Gechev argues that the Balkans have been one of the most dynamic regions of political developments in Europe. The intensely multicultural region stands at the crossroads of the world's major religions, cultures and economic systems. The resulting clash has led to a level of violence since 1992 that Gechev argues has been exacerbated by outside interventions and misplaced economic and political policies by what he calls the great powers of the US, EU and the UN. Nevertheless, he sees the solution in an integration of the region into the EU with the promise of peace underscored by economic integration and political cooperation.</p>",rumen gechev,,2004.0,10.1057/palgrave.development.1100002,Development,Gechev2004,Not available,,Nature,Not available,"Violence, Political Turbulence and Economic Development in the Balkans",00dff8a2a36e5fa19816863161050137,http://dx.doi.org/10.1057/palgrave.development.1100002
14232,"<p>Rapid urbanization and increasing demand for transportation burdens urban road infrastructures. The interplay of number of vehicles and available road capacity on their routes determines the level of congestion. Although approaches to modify demand and capacity exist, the possible limits of congestion alleviation by only modifying route choices have not been systematically studied. Here we couple the road networks of five diverse cities with the travel demand profiles in the morning peak hour obtained from billions of mobile phone traces to comprehensively analyse urban traffic. We present that a dimensionless ratio of the road supply to the travel demand explains the percentage of time lost in congestion. Finally, we examine congestion relief under a centralized routing scheme with varying levels of awareness of social good and quantify the benefits to show that moderate levels are enough to achieve significant collective travel time savings.</p>",serdar colak,Theoretical physics,2016.0,10.1038/ncomms10793,Nature Communications,Çolak2016,Not available,,Nature,Not available,Understanding congested travel in urban areas,c7051bac5c66a8cf3c5e3309f99b17a5,http://dx.doi.org/10.1038/ncomms10793
14233,"<p>Rapid urbanization and increasing demand for transportation burdens urban road infrastructures. The interplay of number of vehicles and available road capacity on their routes determines the level of congestion. Although approaches to modify demand and capacity exist, the possible limits of congestion alleviation by only modifying route choices have not been systematically studied. Here we couple the road networks of five diverse cities with the travel demand profiles in the morning peak hour obtained from billions of mobile phone traces to comprehensively analyse urban traffic. We present that a dimensionless ratio of the road supply to the travel demand explains the percentage of time lost in congestion. Finally, we examine congestion relief under a centralized routing scheme with varying levels of awareness of social good and quantify the benefits to show that moderate levels are enough to achieve significant collective travel time savings.</p>",antonio lima,Theoretical physics,2016.0,10.1038/ncomms10793,Nature Communications,Çolak2016,Not available,,Nature,Not available,Understanding congested travel in urban areas,c7051bac5c66a8cf3c5e3309f99b17a5,http://dx.doi.org/10.1038/ncomms10793
14234,"<p>Rapid urbanization and increasing demand for transportation burdens urban road infrastructures. The interplay of number of vehicles and available road capacity on their routes determines the level of congestion. Although approaches to modify demand and capacity exist, the possible limits of congestion alleviation by only modifying route choices have not been systematically studied. Here we couple the road networks of five diverse cities with the travel demand profiles in the morning peak hour obtained from billions of mobile phone traces to comprehensively analyse urban traffic. We present that a dimensionless ratio of the road supply to the travel demand explains the percentage of time lost in congestion. Finally, we examine congestion relief under a centralized routing scheme with varying levels of awareness of social good and quantify the benefits to show that moderate levels are enough to achieve significant collective travel time savings.</p>",marta gonzalez,Theoretical physics,2016.0,10.1038/ncomms10793,Nature Communications,Çolak2016,Not available,,Nature,Not available,Understanding congested travel in urban areas,c7051bac5c66a8cf3c5e3309f99b17a5,http://dx.doi.org/10.1038/ncomms10793
14235,"<p>This article suggests that it is by exploring the work of George Liska, the once influential yet today almost forgotten realist scholar, that we can find answers to the question of the compatibility between classical realism and its purported neoclassical offspring. Firstly, although Liska is not widely read today and his recent books are only rarely cited, the evolution of his work reveals that the tension between normativity and politics is an inseparable part of classical realist thinking. Secondly, even though he started from a purely historicist version of realism, as demonstrated in his treatment of empire and international order, Liska came to be one of the first realist scholars to try to develop a theory combining historicism and a structural approach to international relations. To those general reasons one may add a particular third one, specifically interesting for <i>Journal of International Relations and Development</i>. Even though Liska spent most of his scholarly career in the United States, he belonged to the group of émigrés from Central Europe (in his case from Czechoslovakia); and this heritage leaves a special mark on all his works dedicated to the Soviet Union, and Eastern and Central Europe. His work is thus an interesting testimony to the rise and fall of realist hegemony over the field of international relations; hence, ironically reinforcing Liska's own notion of the historical contingency of all human cognition.</p>",petr kratochvil,,2007.0,10.1057/palgrave.jird.1800123,Journal of International Relations and Development,Kratochvíl2007,Not available,,Nature,Not available,"George Liska and political realism: on the tension between history and structure, and between norms and power",2f0bd53ddf902a684639cd3eb20b854a,http://dx.doi.org/10.1057/palgrave.jird.1800123
14236,"<p>A generic system embodies basic principles and insights that are common to a set of diverse cases and situations. This paper presents a new generic system that we name the dynastic cycle structure. It is based on a stylized model of events from the Chinese history. The model describes resource allocation between social, asocial and control uses in political economies, markets and firms that experience cyclical behaviour and homeostasis symbolizing low levels of performance. Numerical simulations with the model are used to understand the internal dynamics and to test several policy scenarios.</p>",k saeed,,2007.0,10.1057/palgrave.jors.2602456,Journal of the Operational Research Society,Saeed2007,Not available,,Nature,Not available,"Dynastic cycle: a generic structure describing resource allocation in political economies, markets and firms",7bd86366c68842214fcfa5e1448ccb3a,http://dx.doi.org/10.1057/palgrave.jors.2602456
14237,"<p>A generic system embodies basic principles and insights that are common to a set of diverse cases and situations. This paper presents a new generic system that we name the dynastic cycle structure. It is based on a stylized model of events from the Chinese history. The model describes resource allocation between social, asocial and control uses in political economies, markets and firms that experience cyclical behaviour and homeostasis symbolizing low levels of performance. Numerical simulations with the model are used to understand the internal dynamics and to test several policy scenarios.</p>",o pavlov,,2007.0,10.1057/palgrave.jors.2602456,Journal of the Operational Research Society,Saeed2007,Not available,,Nature,Not available,"Dynastic cycle: a generic structure describing resource allocation in political economies, markets and firms",7bd86366c68842214fcfa5e1448ccb3a,http://dx.doi.org/10.1057/palgrave.jors.2602456
14238,"<p>This article uses fieldwork conducted among North American and Ugandan HIV researchers to track the evolution of molecular HIV science in the global context. The recent initiation of programs funding free antiretroviral treatment in sub-Saharan Africa has both forestalled the deaths of millions of patients and brought molecular medicine to the continent on a massive scale. However, in the years leading up to this development, scientists and policymakers engaged in heated debates over whether HIV treatment in Africa could succeed, with many arguing that economic and ‘cultural’ factors would lead to missed pills and the rapid development of drug-resistant HIV strains. This article describes how the molecular ‘maps’ upon which knowledge claims about HIV were made (including claims about treatment and drug resistance) are based on HIV strains found primarily in patients in North America and Europe, and raises questions about what this implies for patients and scientists in Africa and other regions in the global South. Borrowing from the insights of critical geographers, I argue that our genetic maps of HIV are partial and contingent and reflect a ‘molecular politics’ in which the global inequalities of the AIDS epidemic are manifest at the most minute scale, embedded within the very materials and tools scientists use to study HIV. The consequences of this fact are at once clinical, political and epistemological.</p>",johanna crane,,2011.0,10.1057/biosoc.2010.37,BioSocieties,Crane2011,Not available,,Nature,Not available,Viral cartographies: Mapping the molecular politics of global HIV,c8bfe81f442a33e08092ae0934979e35,http://dx.doi.org/10.1057/biosoc.2010.37
14239,"<p>Facing the threats of infectious diseases, we take various actions to protect ourselves, but few studies considered an evolving system with competing strategies. In view of that, we propose an evolutionary epidemic model coupled with human behaviors, where individuals have three strategies: vaccination, self-protection and laissez faire, and could adjust their strategies according to their neighbors' strategies and payoffs at the beginning of each new season of epidemic spreading. We found a counter-intuitive phenomenon analogous to the well-known <i>Braess's Paradox</i>, namely a better condition may lead to worse performance. Specifically speaking, increasing the successful rate of self-protection does not necessarily reduce the epidemic size or improve the system payoff. The range and degree of the Braess's Paradox are sensitive to both the parameters characterizing the epidemic spreading and the strategy payoff, while the existence of the Braess's Paradox is insensitive to the network topologies. This phenomenon can be well explained by a mean-field approximation. Our study demonstrates an important fact that a better condition for individuals may yield a worse outcome for the society.</p>",zimo yang,Complex networks,2013.0,10.1038/srep03292,Scientific Reports,Zhang2013,Not available,,Nature,Not available,Braess's Paradox in Epidemic Game: Better Condition Results in Less Payoff,551a0daab3513be189f0f7a0e0fd3e06,http://dx.doi.org/10.1038/srep03292
14240,"<p>In this essay, I make the case that the Cold War was caused by a competition of ideas rather than by a struggle for power or a failure of international institutions. The Cold War started when two sets of ideas diverged sufficiently – capitalism and communism – that they precluded either a realist – spheres of influence – or liberal – United Nations – solution to postwar differences in Europe. It ended when one set of ideas prevailed, and democracy and markets spread throughout the whole of Europe, eclipsing realist and liberal outcomes. The Soviet Union disappeared, which realists never expected; whereas the United Nations, which functioned briefly as a classic liberal collective security operation in the first Persian Gulf War, was quickly replaced by a democratic NATO in Bosnia and Kosovo. The competition of ideas did not end in the 1990s, however. It continues today in other forms and will shape the contours of military conflict and international cooperation in tomorrow's world, no less that it did during the Cold War.</p>",henry nau,,2011.0,10.1057/ip.2011.19,International Politics,Nau2011,Not available,,Nature,Not available,Ideas have consequences: The Cold War and today,6f832375bf55d5c73584386d104067a8,http://dx.doi.org/10.1057/ip.2011.19
14241,"<p>This article argues that constructivism in International Relations (IR) suffers from certain important shortcomings in its analysis of the idea of social context. Specifically it is argued that constructivists fail to adequately engage with ‘social structural’ forces in world politics. While constructivists have pitched themselves as theorists who aim to account for the role of social context in world political inquiry, their conceptual focus on ideational factors – rules, norms and inter-subjective beliefs – has resulted in an inadequate, or incomplete, conceptualisation of social structure. Constructivists, it is argued here, tend to leave the role of materially embodied social structures theoretically and empirically unexplored. The limitations of constructivist treatments of social context have significant consequences for their analysis of world politics, for example, for recent constructivist attempts to deal with international law. Constructivist interventions into analysis of law remain deficient in important senses because of their failure to conceive of international law in social structural terms and because of their inability to explore in depth law's relationship with other social structures, such as patriarchy or capitalism. This entails that the structured systems of inequality and hierarchy embodied in law fail to be adequately recognised. Recognising the ‘incompleteness’ of the constructivist accounts of social context, we argue, is important in highlighting the often un-noted limitations of constructivist scholarship and in potentially redirecting constructivist scholarship towards closer engagement with ‘critical theory’ investigations into IR and law.</p>",milja kurki,,2009.0,10.1057/ip.2009.29,International Politics,Kurki2009,Not available,,Nature,Not available,Hidden in plain sight: Constructivist treatment of social context and its limitations,8fed322dfe2b1efe6f2b20efa11d61fa,http://dx.doi.org/10.1057/ip.2009.29
14242,"<p>This article argues that constructivism in International Relations (IR) suffers from certain important shortcomings in its analysis of the idea of social context. Specifically it is argued that constructivists fail to adequately engage with ‘social structural’ forces in world politics. While constructivists have pitched themselves as theorists who aim to account for the role of social context in world political inquiry, their conceptual focus on ideational factors – rules, norms and inter-subjective beliefs – has resulted in an inadequate, or incomplete, conceptualisation of social structure. Constructivists, it is argued here, tend to leave the role of materially embodied social structures theoretically and empirically unexplored. The limitations of constructivist treatments of social context have significant consequences for their analysis of world politics, for example, for recent constructivist attempts to deal with international law. Constructivist interventions into analysis of law remain deficient in important senses because of their failure to conceive of international law in social structural terms and because of their inability to explore in depth law's relationship with other social structures, such as patriarchy or capitalism. This entails that the structured systems of inequality and hierarchy embodied in law fail to be adequately recognised. Recognising the ‘incompleteness’ of the constructivist accounts of social context, we argue, is important in highlighting the often un-noted limitations of constructivist scholarship and in potentially redirecting constructivist scholarship towards closer engagement with ‘critical theory’ investigations into IR and law.</p>",adriana sinclair,,2009.0,10.1057/ip.2009.29,International Politics,Kurki2009,Not available,,Nature,Not available,Hidden in plain sight: Constructivist treatment of social context and its limitations,8fed322dfe2b1efe6f2b20efa11d61fa,http://dx.doi.org/10.1057/ip.2009.29
14243,"<p>Claudia Aradau addresses important issues within the securitization approach of the Copenhagen School. Discussions of security, securitization and desecuritization always involve implicit or explicit stances on political preferences. Unsatisfied with both desecuritization and the identification of security with emancipation, she goes on to develop an alternative take on the problem. De-coupling emancipation from security, Aradau tries to locate emancipation as the counter-strategy to securitization in a realm beyond and outside the reach of exceptional politics, sovereign authority and exclusionary moves. What Aradau underestimates is the central, indeed constitutive, role that security plays in the ontotheology of politics.</p>",andreas behnke,,2006.0,10.1057/palgrave.jird.1800070,Journal of International Relations and Development,Behnke2006,Not available,,Nature,Not available,"No way out: desecuritization, emancipation and the eternal return of the political — a reply to Aradau",3c5bd4137fdb0232db53f13ec097ff62,http://dx.doi.org/10.1057/palgrave.jird.1800070
14244,"<p>Nitasha Kaul argues that economic violence refers not only to violence caused for economic reasons, but also to violence caused by spurious economics. It is economic violence when people lose their jobs and livelihoods, when they witness massively divergent rewards for work and when they see an endless perpetuation of inequality around them. Such involuntary unemployment in the long run leads to social breakdown and community fragmentation.</p>",nitasha kaul,,2009.0,10.1057/dev.2009.43,Development,Kaul2009,Not available,,Nature,Not available,The Economics of Turning People into Things<tlnref><sup>1</sup></tlnref>,b131ffa4800c9aa7073bb1b1ecc469cd,http://dx.doi.org/10.1057/dev.2009.43
14245,"<p>This article examines the concepts of globalisation and imperialism, both in terms of their explanatory status, and in the light of changes in the international order since the end of the Cold War. It does so both through detailed theoretical and empirical analysis, and in part through focusing on a key contributor to this debate, Justin Rosenberg. It is argued that Rosenberg's <i>theoretical</i> post-mortem for globalisation is correct. However, it is also argued that Rosenberg's <i>historical</i> post-mortem is far less convincing, not least when related to his subsequent attempts to draw on the concept of uneven and combined development in order to explain the reality of geopolitical conflict in the international order. It is here that the concept of imperialism enters the picture, and the article suggests that attempts to update theories of geopolitical competition based on Lenin and Bukharin's work on imperialism are unconvincing, as they fail to take full account of the changes in the international order since 1945. These changes — the internationalisation of capital and rise of global production networks, the rise of manufacturing in the developing world, the internationalisation of the state, cooperation between developed capitalist powers, and US hegemony — are well described, if not necessarily explained by the concept of globalisation. However, this does not mean that the concept of imperialism is no longer of use, and the idea is defended through a discussion of the hierarchies associated with the globalisation of production. It is further illustrated by relating liberal military intervention to this continued reality of global hierarchy and inequality in the international order. The article concludes by defending the ideas of imperialism and uneven and combined development, but argues that these cannot be used to explain the nature of the international <i>state</i> system (or geo-politics), but rather the hierarchies associated with the international <i>capitalist</i> order (or political economy).</p>",ray kiely,,2013.0,10.1057/jird.2013.2,Journal of International Relations and Development,Kiely2013,Not available,,Nature,Not available,Imperialism or globalisation? … Or imperialism and globalisation: Theorising the international after Rosenberg's ‘post-mortem’,fc9bb8b5972c04275d83933440cfe916,http://dx.doi.org/10.1057/jird.2013.2
14246,"<p>Facing the threats of infectious diseases, we take various actions to protect ourselves, but few studies considered an evolving system with competing strategies. In view of that, we propose an evolutionary epidemic model coupled with human behaviors, where individuals have three strategies: vaccination, self-protection and laissez faire, and could adjust their strategies according to their neighbors' strategies and payoffs at the beginning of each new season of epidemic spreading. We found a counter-intuitive phenomenon analogous to the well-known <i>Braess's Paradox</i>, namely a better condition may lead to worse performance. Specifically speaking, increasing the successful rate of self-protection does not necessarily reduce the epidemic size or improve the system payoff. The range and degree of the Braess's Paradox are sensitive to both the parameters characterizing the epidemic spreading and the strategy payoff, while the existence of the Braess's Paradox is insensitive to the network topologies. This phenomenon can be well explained by a mean-field approximation. Our study demonstrates an important fact that a better condition for individuals may yield a worse outcome for the society.</p>",zhi-xi wu,Computational models,2013.0,10.1038/srep03292,Scientific Reports,Zhang2013,Not available,,Nature,Not available,Braess's Paradox in Epidemic Game: Better Condition Results in Less Payoff,551a0daab3513be189f0f7a0e0fd3e06,http://dx.doi.org/10.1038/srep03292
14247,"<p>Realists characterize the contemporary international system as a field of competing units of various sizes and capabilities, struggling by means of strategies of self-advancement to achieve goals that are sometimes common, sometimes contradictory. The nation-state is the fundamental unit in the realist constellation of actors. Large and resourceful states can achieve their goals through partnership, influence, alliance, demand, and coercion. Small and less resourceful states find the strategies at their disposal more constrained. Hence small states are encouraged by realist doctrine to pursue strategies of aggregation, coalition-formation, and integration. Thus, realist prescriptions for the small state encourage strategies that run counter to the realist explanation of international dynamics. Are realist policy prescriptions for the small state necessarily anti-realist? This paper addresses this question through an analysis of realist theory with respect to the foreign policy strategies of a small Central Asian state, Kyrgyzstan.</p>",gregory gleason,,2007.0,10.1057/palgrave.ip.8800218,International Politics,Gleason2007,Not available,,Nature,Not available,Realism and the Small State: Evidence from Kyrgyzstan,927773e287b41c7c25ca0717a5126d38,http://dx.doi.org/10.1057/palgrave.ip.8800218
14248,"<p>Realists characterize the contemporary international system as a field of competing units of various sizes and capabilities, struggling by means of strategies of self-advancement to achieve goals that are sometimes common, sometimes contradictory. The nation-state is the fundamental unit in the realist constellation of actors. Large and resourceful states can achieve their goals through partnership, influence, alliance, demand, and coercion. Small and less resourceful states find the strategies at their disposal more constrained. Hence small states are encouraged by realist doctrine to pursue strategies of aggregation, coalition-formation, and integration. Thus, realist prescriptions for the small state encourage strategies that run counter to the realist explanation of international dynamics. Are realist policy prescriptions for the small state necessarily anti-realist? This paper addresses this question through an analysis of realist theory with respect to the foreign policy strategies of a small Central Asian state, Kyrgyzstan.</p>",asel kerimbekova,,2007.0,10.1057/palgrave.ip.8800218,International Politics,Gleason2007,Not available,,Nature,Not available,Realism and the Small State: Evidence from Kyrgyzstan,927773e287b41c7c25ca0717a5126d38,http://dx.doi.org/10.1057/palgrave.ip.8800218
14249,"<p>Realists characterize the contemporary international system as a field of competing units of various sizes and capabilities, struggling by means of strategies of self-advancement to achieve goals that are sometimes common, sometimes contradictory. The nation-state is the fundamental unit in the realist constellation of actors. Large and resourceful states can achieve their goals through partnership, influence, alliance, demand, and coercion. Small and less resourceful states find the strategies at their disposal more constrained. Hence small states are encouraged by realist doctrine to pursue strategies of aggregation, coalition-formation, and integration. Thus, realist prescriptions for the small state encourage strategies that run counter to the realist explanation of international dynamics. Are realist policy prescriptions for the small state necessarily anti-realist? This paper addresses this question through an analysis of realist theory with respect to the foreign policy strategies of a small Central Asian state, Kyrgyzstan.</p>",svetlana kozhirova,,2007.0,10.1057/palgrave.ip.8800218,International Politics,Gleason2007,Not available,,Nature,Not available,Realism and the Small State: Evidence from Kyrgyzstan,927773e287b41c7c25ca0717a5126d38,http://dx.doi.org/10.1057/palgrave.ip.8800218
14250,"<p>Clinical governance was introduced in <i>The New NHS: Modern, Dependable</i> in 1997. Through changing structures and systems around the management of risk, knowledge and performance, the policy essentially seeks to mould the working culture of the NHS, yet there is inconclusive evidence as to its success, with many studies suggesting its impact has been highly limited. While modifying the system and structures within which practitioners operate is straightforward, cultures of shared norms and values cannot be so easily, or indeed successfully, shaped. Applying Habermasian social theory as an analytical framework, clinical governance is seen as responding to a <i>constructed</i> legitimacy crisis following NHS dysfunctions such as Bristol Royal Infirmary. Paradoxically, this misnomer has led to a policy that undermines its own legitimation among the professionals it seeks to control through its separation of purposive-rational interests from norms and values. Thus, a reliance on sanctions rather than norms to orient the actions of individuals working within the NHS elicits superficial rather than substantive compliance, undermining the effectiveness of auditing/accountability mechanisms. Whereas intra-organizational trust is more efficient in managing transactions, clinical governance, as it functions currently, represents a form of control which is not only more expensive, but ultimately ineffective and self-defeating.</p>",patrick brown,,2008.0,10.1057/sth.2008.3,Social Theory & Health,Brown2008,Not available,,Nature,Not available,Legitimacy Chasing its Own Tail: Theorizing Clinical Governance through a Critique of Instrumental Reason,5f6d7501f3be3ad0eeb98b965664b8eb,http://dx.doi.org/10.1057/sth.2008.3
14251,"<p>The severance of the relationship between liberalism and nationalism and liberalism and self-determination as well as an underestimation of substantive legitimacy led to confusion about the relationship between democracy and security in liberal theory. Based on the liberal view that democracies are inherently peaceful, democracy promotion is seen as a means of conflict resolution that is able to create both security and legitimacy. Similarly, the globalization of democracy is seen as the guarantee of peace and security in a post-sovereign international order. Against this view, the present article argues that the imposition of democracy without the prior creation of security and legitimacy can exacerbate conflicts and undermine peace. Civic nationalism, in this view, is a consequence of security, while ethnic nationalism is a consequence of insecurity. The article argues that both conflict resolution and democracy would be better served by taking a more reflexive stance on boundaries. This would have the further beneficial consequence of putting an end to a situation when no legitimate means of change exists in international relations, a situation persisting since the end of the First World War. International practice to this effect could lead to the termination of protracted conflicts and towards sophisticated procedures of peaceful change in the future.</p>",katalin sarvary,,2008.0,10.1057/jird.2008.24,Journal of International Relations and Development,Sárváry2008,Not available,,Nature,Not available,Democracy and international relations: the theory of István Bibó (1911–1979),0eb73506a241002377d9808e345372c1,http://dx.doi.org/10.1057/jird.2008.24
14252,"<p>Over the last 20 years, historical sociology has become an increasingly conspicuous part of the broader field of International Relations (IR) theory, with advocates making a series of interventions in subjects as diverse as the origins and varieties of international systems over time and place, to work on the co-constitutive relationship between the international realm and state–society relations in the processes of radical change. However, even as historical sociology in IR (HSIR) has produced substantial gains, so there has also been a concomitant watering down of the underlying approach itself. As a result, it is no longer clear what exactly HSIR entails: should it be seen as operating within the existing pool of available theories or as an attempt to reconvene the discipline on new foundations? This article sets out an identifiable set of assumptions and precepts for HSIR based on deep ontological realism, epistemological relationism, a methodological free range, and an overt normative engagement with the events and processes that make up contemporary world politics. As such, HSIR can be seen as operating as an open society, a research programme and a vocation.</p>",george lawson,,2007.0,10.1057/palgrave.ip.8800195,International Politics,Lawson2007,Not available,,Nature,Not available,"Historical Sociology in International Relations: Open Society, Research Programme and Vocation",d42cb2c1f2ef07d4399a9fcea0e569bf,http://dx.doi.org/10.1057/palgrave.ip.8800195
14253,"<p>To the editor: Global momentum to expand access to antiretroviral therapy (ART) in developing countries has accelerated over the last 18 months, triggered in large part by activist pressure and rapidly falling prices for ART. The World Health Organization has added several ART compounds to its list of essential medicines, and the organization in 2002 published guidelines on scaling up ART programs in resource-limited settings.</p>",daniel kuritzkes,,2003.0,10.1038/nm1103-1343b,Nature Medicine,Kuritzkes2003,Not available,,Nature,Not available,World Bank meeting concludes drug resistance should not prevent distribution of antiretroviral therapy to poor countries,1d5a542ff96e1a21759ba51a85a4a2ac,http://dx.doi.org/10.1038/nm1103-1343b
14254,"<p>Facing the threats of infectious diseases, we take various actions to protect ourselves, but few studies considered an evolving system with competing strategies. In view of that, we propose an evolutionary epidemic model coupled with human behaviors, where individuals have three strategies: vaccination, self-protection and laissez faire, and could adjust their strategies according to their neighbors' strategies and payoffs at the beginning of each new season of epidemic spreading. We found a counter-intuitive phenomenon analogous to the well-known <i>Braess's Paradox</i>, namely a better condition may lead to worse performance. Specifically speaking, increasing the successful rate of self-protection does not necessarily reduce the epidemic size or improve the system payoff. The range and degree of the Braess's Paradox are sensitive to both the parameters characterizing the epidemic spreading and the strategy payoff, while the existence of the Braess's Paradox is insensitive to the network topologies. This phenomenon can be well explained by a mean-field approximation. Our study demonstrates an important fact that a better condition for individuals may yield a worse outcome for the society.</p>",zhi-xi wu,Applied mathematics,2013.0,10.1038/srep03292,Scientific Reports,Zhang2013,Not available,,Nature,Not available,Braess's Paradox in Epidemic Game: Better Condition Results in Less Payoff,551a0daab3513be189f0f7a0e0fd3e06,http://dx.doi.org/10.1038/srep03292
14255,"<p>To the editor: Global momentum to expand access to antiretroviral therapy (ART) in developing countries has accelerated over the last 18 months, triggered in large part by activist pressure and rapidly falling prices for ART. The World Health Organization has added several ART compounds to its list of essential medicines, and the organization in 2002 published guidelines on scaling up ART programs in resource-limited settings.</p>",joep lange,,2003.0,10.1038/nm1103-1343b,Nature Medicine,Kuritzkes2003,Not available,,Nature,Not available,World Bank meeting concludes drug resistance should not prevent distribution of antiretroviral therapy to poor countries,1d5a542ff96e1a21759ba51a85a4a2ac,http://dx.doi.org/10.1038/nm1103-1343b
14256,"<p>To the editor: Global momentum to expand access to antiretroviral therapy (ART) in developing countries has accelerated over the last 18 months, triggered in large part by activist pressure and rapidly falling prices for ART. The World Health Organization has added several ART compounds to its list of essential medicines, and the organization in 2002 published guidelines on scaling up ART programs in resource-limited settings.</p>",debrework zewdie,,2003.0,10.1038/nm1103-1343b,Nature Medicine,Kuritzkes2003,Not available,,Nature,Not available,World Bank meeting concludes drug resistance should not prevent distribution of antiretroviral therapy to poor countries,1d5a542ff96e1a21759ba51a85a4a2ac,http://dx.doi.org/10.1038/nm1103-1343b
14257,"<p>A new era in international politics is gradually taking shape in which the legacy of the Cold War is gradually fading, but in which new lines of division are emerging. The major institutions of the Cold War period are undergoing a long decay although the political processes associated with them are becoming increasingly dysfunctional. New forms of multi-polarity are taking shape accompanied by the struggle between defenders of the <i>status quo</i> and those ready to adapt to the structural revisionism inherent in the new pattern of international politics. In all of this, Russia acts as the bellwether, developing as a distinct and separate pole in the international system rather than joining the Western constellation, as was anticipated after the end of the Cold War. Russia's great power identity in the international system is accompanied by domestic systemic specificities, which reinforce differentiation at the structural level. Russia's neo-revisionism does not repudiate the present balance in international order, but seeks to create what it considers to be a more comprehensive and equal system. This can be seen in its various forms of interaction and modes of engagement with ‘the international’. In methodological terms, the attempt to analyse these changes through a Cold War lens is a categorical error that perpetuates anachronistic paradigms. By disaggregating Russia's engagement with the international into a number of distinct processes, we can delineate more clearly the interaction of structural and systemic factors that sustain Russia's neo-revisionism.</p>",richard sakwa,,2012.0,10.1057/ip.2012.10,International Politics,Sakwa2012,Not available,,Nature,Not available,The problem of ‘the international’ in Russian identity formation,cce62bd8f07621f425267697010697e9,http://dx.doi.org/10.1057/ip.2012.10
14258,Can the behaviour of complex systems from cells to planetary climates be explained by the idea that they're driven to produce the maximum amount of disorder? John Whitfield investigates.,john whitfield,,2005.0,10.1038/436905a,Nature,Whitfield2005,Not available,,Nature,Not available,Complex systems:  Order out of chaos,ef20a9158d57149c39cdcb5fe06db365,http://dx.doi.org/10.1038/436905a
14259,<p>I have taught and researched about politics for what I now realise is a long time. I have never felt as strongly as I do now that our discipline needs a period of intellectual stocktaking and reflection on the problems and issues it should study.</p>,paul hirst,,2003.0,10.1057/eps.2003.34,European Political Science,Hirst2003,Not available,,Nature,Not available,the future of political studies<tlnref><sup>a</sup></tlnref>,c08dc844473462a6a354aa73218ae9e4,http://dx.doi.org/10.1057/eps.2003.34
14260,"<p>As man and woman ‘are supposed to be different’, one being from Mars and the other from Venus as Gray put it, so it is important to recognize that Europe and the United States are supposed to be different. While there are many connectors between the two, these are not sufficient to bridge the gap that has developed between them. Kagan argues that Europe is weak — that because it lacks force (what he calls power) it comes with the arguments and rhetoric of the weak. Yet reading Kagan's argument more closely, one finds that it is not one of power, but of force. This article takes issue with this understanding of power, and attempts to clarify the language on power and force.</p>",christopher jones,,2008.0,10.1057/ip.2008.3,International Politics,Jones2008,Not available,,Nature,Not available,"Seduce Me: Kagan, Power, the US and Europe",c17c0373f678c70da7dc1e1de792a256,http://dx.doi.org/10.1057/ip.2008.3
14261,<p>Mark Duffield analyzes how the conventional understanding of the new wars establishes both a justification and legitimacy for external intervention. He argues that the encounter of global liberal governance with resistance is shaping the post-Cold War reuniting of aid and politics.</p>,mark duffield,,2005.0,10.1057/palgrave.development.1100164,Development,Duffield2005,Not available,,Nature,Not available,Social Reconstruction: The reuniting of aid and politics<tlnref><sup>1</sup></tlnref>,d4c2bfde64d057d8690505d410e878bc,http://dx.doi.org/10.1057/palgrave.development.1100164
14262,"<p>Facing the threats of infectious diseases, we take various actions to protect ourselves, but few studies considered an evolving system with competing strategies. In view of that, we propose an evolutionary epidemic model coupled with human behaviors, where individuals have three strategies: vaccination, self-protection and laissez faire, and could adjust their strategies according to their neighbors' strategies and payoffs at the beginning of each new season of epidemic spreading. We found a counter-intuitive phenomenon analogous to the well-known <i>Braess's Paradox</i>, namely a better condition may lead to worse performance. Specifically speaking, increasing the successful rate of self-protection does not necessarily reduce the epidemic size or improve the system payoff. The range and degree of the Braess's Paradox are sensitive to both the parameters characterizing the epidemic spreading and the strategy payoff, while the existence of the Braess's Paradox is insensitive to the network topologies. This phenomenon can be well explained by a mean-field approximation. Our study demonstrates an important fact that a better condition for individuals may yield a worse outcome for the society.</p>",zhi-xi wu,Applied physics,2013.0,10.1038/srep03292,Scientific Reports,Zhang2013,Not available,,Nature,Not available,Braess's Paradox in Epidemic Game: Better Condition Results in Less Payoff,551a0daab3513be189f0f7a0e0fd3e06,http://dx.doi.org/10.1038/srep03292
14263,"<p>In this paper, the author considers that the large-group dynamics in certain war-torn, hot spots throughout the world are symptoms of a “geopolitical identity disorder.” He extrapolates from the model of the severely traumatized psyche in dissociative identity disorder in which there is so much intolerable emotion, destructive aggression and conflict that different selves with different identities develop which are unable to recognize how interdependent and related they actually are. In the most extreme cases, one dissociated self tries to kill off “the other” in order to gain exclusive control of the body and make it comply with his or her wishes and vision. In actuality, however, such an attempt is a dissociated suicide plan with lethal implications. This model is applied to the Palestinian/Israeli situation where there is a deadly battle over the land. A clinical vignette is offered to illustrate these ideas and offer possibilities for help.</p>",ira brenner,,2009.0,10.1057/ajp.2008.42,The American Journal of Psychoanalysis,Brenner2009,Not available,,Nature,Not available,The Palestinian/Israeli Conflict: A Geopolitical Identity Disorder,761cdcb65089787027dc2e059bee6e40,http://dx.doi.org/10.1057/ajp.2008.42
14264,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",nathaniel comfort,Arts,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14265,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",nathaniel comfort,Culture,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14266,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",nathaniel comfort,Mathematics and computing,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14267,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",nathaniel comfort,Evolution,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14268,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",kevin padian,Arts,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14269,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",kevin padian,Culture,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14270,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",kevin padian,Mathematics and computing,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14271,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",kevin padian,Evolution,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14272,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",michael harris,Arts,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14273,"<p>Facing the threats of infectious diseases, we take various actions to protect ourselves, but few studies considered an evolving system with competing strategies. In view of that, we propose an evolutionary epidemic model coupled with human behaviors, where individuals have three strategies: vaccination, self-protection and laissez faire, and could adjust their strategies according to their neighbors' strategies and payoffs at the beginning of each new season of epidemic spreading. We found a counter-intuitive phenomenon analogous to the well-known <i>Braess's Paradox</i>, namely a better condition may lead to worse performance. Specifically speaking, increasing the successful rate of self-protection does not necessarily reduce the epidemic size or improve the system payoff. The range and degree of the Braess's Paradox are sensitive to both the parameters characterizing the epidemic spreading and the strategy payoff, while the existence of the Braess's Paradox is insensitive to the network topologies. This phenomenon can be well explained by a mean-field approximation. Our study demonstrates an important fact that a better condition for individuals may yield a worse outcome for the society.</p>",zhi-xi wu,Complex networks,2013.0,10.1038/srep03292,Scientific Reports,Zhang2013,Not available,,Nature,Not available,Braess's Paradox in Epidemic Game: Better Condition Results in Less Payoff,551a0daab3513be189f0f7a0e0fd3e06,http://dx.doi.org/10.1038/srep03292
14274,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",michael harris,Culture,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14275,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",michael harris,Mathematics and computing,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14276,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",michael harris,Evolution,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14277,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",jane maienschein,Arts,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14278,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",jane maienschein,Culture,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14279,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",jane maienschein,Mathematics and computing,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14280,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",jane maienschein,Evolution,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14281,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",tilli tansey,Arts,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14282,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",tilli tansey,Culture,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14283,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",tilli tansey,Mathematics and computing,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14284,"<p>Facing the threats of infectious diseases, we take various actions to protect ourselves, but few studies considered an evolving system with competing strategies. In view of that, we propose an evolutionary epidemic model coupled with human behaviors, where individuals have three strategies: vaccination, self-protection and laissez faire, and could adjust their strategies according to their neighbors' strategies and payoffs at the beginning of each new season of epidemic spreading. We found a counter-intuitive phenomenon analogous to the well-known <i>Braess's Paradox</i>, namely a better condition may lead to worse performance. Specifically speaking, increasing the successful rate of self-protection does not necessarily reduce the epidemic size or improve the system payoff. The range and degree of the Braess's Paradox are sensitive to both the parameters characterizing the epidemic spreading and the strategy payoff, while the existence of the Braess's Paradox is insensitive to the network topologies. This phenomenon can be well explained by a mean-field approximation. Our study demonstrates an important fact that a better condition for individuals may yield a worse outcome for the society.</p>",bing-hong wang,Computational models,2013.0,10.1038/srep03292,Scientific Reports,Zhang2013,Not available,,Nature,Not available,Braess's Paradox in Epidemic Game: Better Condition Results in Less Payoff,551a0daab3513be189f0f7a0e0fd3e06,http://dx.doi.org/10.1038/srep03292
14285,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",tilli tansey,Evolution,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14286,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",xu xing,Arts,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14287,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",xu xing,Culture,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14288,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",xu xing,Mathematics and computing,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14289,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",xu xing,Evolution,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14290,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",jennifer rampling,Arts,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14291,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",jennifer rampling,Culture,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14292,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",jennifer rampling,Mathematics and computing,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14293,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",jennifer rampling,Evolution,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14294,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",jon butterworth,Arts,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14295,"<p>Facing the threats of infectious diseases, we take various actions to protect ourselves, but few studies considered an evolving system with competing strategies. In view of that, we propose an evolutionary epidemic model coupled with human behaviors, where individuals have three strategies: vaccination, self-protection and laissez faire, and could adjust their strategies according to their neighbors' strategies and payoffs at the beginning of each new season of epidemic spreading. We found a counter-intuitive phenomenon analogous to the well-known <i>Braess's Paradox</i>, namely a better condition may lead to worse performance. Specifically speaking, increasing the successful rate of self-protection does not necessarily reduce the epidemic size or improve the system payoff. The range and degree of the Braess's Paradox are sensitive to both the parameters characterizing the epidemic spreading and the strategy payoff, while the existence of the Braess's Paradox is insensitive to the network topologies. This phenomenon can be well explained by a mean-field approximation. Our study demonstrates an important fact that a better condition for individuals may yield a worse outcome for the society.</p>",bing-hong wang,Applied mathematics,2013.0,10.1038/srep03292,Scientific Reports,Zhang2013,Not available,,Nature,Not available,Braess's Paradox in Epidemic Game: Better Condition Results in Less Payoff,551a0daab3513be189f0f7a0e0fd3e06,http://dx.doi.org/10.1038/srep03292
14296,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",jon butterworth,Culture,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14297,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",jon butterworth,Mathematics and computing,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14298,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",jon butterworth,Evolution,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14299,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",daniel cressey,Arts,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14300,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",daniel cressey,Culture,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14301,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",daniel cressey,Mathematics and computing,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14302,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",daniel cressey,Evolution,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14303,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",kelly krause,Arts,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14304,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",kelly krause,Culture,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14305,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",kelly krause,Mathematics and computing,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14306,"<p>We consider a Markovian queueing system with <i>N</i> heterogeneous service facilities, each of which has multiple servers available, linear holding costs, a fixed value of service and a first-come-first-serve queue discipline. Customers arriving in the system can be either rejected or sent to one of the <i>N</i> facilities. Two different types of control policies are considered, which we refer to as ‘selfishly optimal’ and ‘socially optimal’. We prove the equivalence of two different Markov Decision Process formulations, and then show that classical <i>M</i>/<i>M</i>/1 queue results from the early literature on behavioural queueing theory can be generalized to multiple dimensions in an elegant way. In particular, the state space of the continuous-time Markov process induced by a socially optimal policy is contained within that of the selfishly optimal policy. We also show that this result holds when customers are divided into an arbitrary number of heterogeneous classes, provided that the service rates remain non-discriminatory.</p>",paul harper,,2015.0,10.1057/jors.2015.98,Journal of the Operational Research Society,Shone2015,Not available,,Nature,Not available,Containment of socially optimal policies in multiple-facility Markovian queueing systems,7e14b5751602501225481ed2de4f9fb3,http://dx.doi.org/10.1057/jors.2015.98
14307,"<p>Facing the threats of infectious diseases, we take various actions to protect ourselves, but few studies considered an evolving system with competing strategies. In view of that, we propose an evolutionary epidemic model coupled with human behaviors, where individuals have three strategies: vaccination, self-protection and laissez faire, and could adjust their strategies according to their neighbors' strategies and payoffs at the beginning of each new season of epidemic spreading. We found a counter-intuitive phenomenon analogous to the well-known <i>Braess's Paradox</i>, namely a better condition may lead to worse performance. Specifically speaking, increasing the successful rate of self-protection does not necessarily reduce the epidemic size or improve the system payoff. The range and degree of the Braess's Paradox are sensitive to both the parameters characterizing the epidemic spreading and the strategy payoff, while the existence of the Braess's Paradox is insensitive to the network topologies. This phenomenon can be well explained by a mean-field approximation. Our study demonstrates an important fact that a better condition for individuals may yield a worse outcome for the society.</p>",bing-hong wang,Applied physics,2013.0,10.1038/srep03292,Scientific Reports,Zhang2013,Not available,,Nature,Not available,Braess's Paradox in Epidemic Game: Better Condition Results in Less Payoff,551a0daab3513be189f0f7a0e0fd3e06,http://dx.doi.org/10.1038/srep03292
14308,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",kelly krause,Evolution,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14309,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",richard noorden,Arts,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14310,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",richard noorden,Culture,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14311,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",richard noorden,Mathematics and computing,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14312,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",richard noorden,Evolution,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14313,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",monica contestabile,Arts,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14314,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",monica contestabile,Culture,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14315,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",monica contestabile,Mathematics and computing,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14316,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",monica contestabile,Evolution,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14317,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",emily banham,Arts,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14318,"<p>Facing the threats of infectious diseases, we take various actions to protect ourselves, but few studies considered an evolving system with competing strategies. In view of that, we propose an evolutionary epidemic model coupled with human behaviors, where individuals have three strategies: vaccination, self-protection and laissez faire, and could adjust their strategies according to their neighbors' strategies and payoffs at the beginning of each new season of epidemic spreading. We found a counter-intuitive phenomenon analogous to the well-known <i>Braess's Paradox</i>, namely a better condition may lead to worse performance. Specifically speaking, increasing the successful rate of self-protection does not necessarily reduce the epidemic size or improve the system payoff. The range and degree of the Braess's Paradox are sensitive to both the parameters characterizing the epidemic spreading and the strategy payoff, while the existence of the Braess's Paradox is insensitive to the network topologies. This phenomenon can be well explained by a mean-field approximation. Our study demonstrates an important fact that a better condition for individuals may yield a worse outcome for the society.</p>",bing-hong wang,Complex networks,2013.0,10.1038/srep03292,Scientific Reports,Zhang2013,Not available,,Nature,Not available,Braess's Paradox in Epidemic Game: Better Condition Results in Less Payoff,551a0daab3513be189f0f7a0e0fd3e06,http://dx.doi.org/10.1038/srep03292
14319,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",emily banham,Culture,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14320,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",emily banham,Mathematics and computing,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14321,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",emily banham,Evolution,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14322,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",anna armstrong,Arts,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14323,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",anna armstrong,Culture,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14324,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",anna armstrong,Mathematics and computing,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14325,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",anna armstrong,Evolution,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14326,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",barbara kiser,Arts,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14327,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",barbara kiser,Culture,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14328,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",barbara kiser,Mathematics and computing,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14329,"<p>Facing the threats of infectious diseases, we take various actions to protect ourselves, but few studies considered an evolving system with competing strategies. In view of that, we propose an evolutionary epidemic model coupled with human behaviors, where individuals have three strategies: vaccination, self-protection and laissez faire, and could adjust their strategies according to their neighbors' strategies and payoffs at the beginning of each new season of epidemic spreading. We found a counter-intuitive phenomenon analogous to the well-known <i>Braess's Paradox</i>, namely a better condition may lead to worse performance. Specifically speaking, increasing the successful rate of self-protection does not necessarily reduce the epidemic size or improve the system payoff. The range and degree of the Braess's Paradox are sensitive to both the parameters characterizing the epidemic spreading and the strategy payoff, while the existence of the Braess's Paradox is insensitive to the network topologies. This phenomenon can be well explained by a mean-field approximation. Our study demonstrates an important fact that a better condition for individuals may yield a worse outcome for the society.</p>",tao zhou,Computational models,2013.0,10.1038/srep03292,Scientific Reports,Zhang2013,Not available,,Nature,Not available,Braess's Paradox in Epidemic Game: Better Condition Results in Less Payoff,551a0daab3513be189f0f7a0e0fd3e06,http://dx.doi.org/10.1038/srep03292
14330,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",barbara kiser,Evolution,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14331,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",sara abdulla,Arts,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14332,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",sara abdulla,Culture,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14333,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",sara abdulla,Mathematics and computing,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14334,"Plunge into a profusion of brilliant summer reads suggested by regular reviewers and editors, far away from the lab and lecture hall.",sara abdulla,Evolution,2015.0,10.1038/523528a,Nature,Comfort2015,Not available,,Nature,Not available,Summer books,9dc9cd0a2fddaf0df5eedd9a04ad334d,http://dx.doi.org/10.1038/523528a
14335,<p>This paper attempts to portray a synthesis of what has been learned in the past 10 years with regard to the transition process. It contrasts the mainstream “Washington consensus” view of transition with the “evolutionary institutionalist” perspective. It argues that the latter gives a more adequate and complete picture both of the transition processes and of economic systems and is of better help to prevent serious transition failures.</p>,gerard roland,,2001.0,10.2307/4621689,IMF Staff Papers,Roland2001,Not available,,Nature,Not available,Ten Years after ... Transition and Economics,a504ed5c9ad31062c0b261089d564521,http://dx.doi.org/10.2307/4621689
14336,"<p>Over the last decade, the world economy has been characterised by escalating global current account imbalances between the United States (US) and East Asia in particular. This article argues that US monetary hegemony has been a necessary condition for the emergence of these imbalances. It is contended that the notion of structural power is indispensable to understanding the nature of US monetary hegemony and its relation to the imbalances. US monetary structural power has both induced East Asian states to increase their accumulation of dollar-denominated assets and allowed the US to decrease its savings. The article also shows that the mechanisms of US structural monetary power contain several contradictory dynamics that are able to undermine its own purpose, which is to avoid the burden of adjustment to balance-of-payments disequilibria.</p>",mattias vermeiren,,2010.0,10.1057/jird.2009.36,Journal of International Relations and Development,Vermeiren2010,Not available,,Nature,Not available,The global imbalances and the contradictions of US monetary hegemony,396f5db3afa1f9a09c036fe8a99ab8d3,http://dx.doi.org/10.1057/jird.2009.36
14337,"<p>Using a multiple case study design, we investigate the issue of inter-firm IT governance and its impact on information sharing in buyer–supplier dyadic relationships. We interviewed 38 managers of operations, purchasing, and IT in five dyadic relationships, and identified and examined one type of inter-firm IT governance: unilateral IT governance. In this type of IT governance, one party of the dyad dominates the relationship and the decision rights regarding inter-firm IT systems and data sharing. We find that unilateral inter-firm IT governance develops under contract-based and relationship-supplemented inter-firm governance arrangements in which significant power imbalance exists. However, contrary to the prediction of resource dependence theory, power-imbalanced governance can survive and thrive over a long period of time. We find that the inter-firm relational norms and trust that develop between these dyads constrain opportunistic and myopic behaviors in both parties, thus sustaining the seemingly unstable unilateral inter-firm IT governance. We also find that the operational necessity of the buyers and the IT capability of the suppliers are two primary factors that constrain inter-firm information sharing in these dyads. On the basis of these findings, we propose a process model for understanding and managing this type of inter-firm IT governance.</p>",jinghua xiao,,2012.0,10.1057/ejis.2012.40,European Journal of Information Systems,Xiao2012,Not available,,Nature,Not available,Inter-firm IT governance in power-imbalanced buyer–supplier dyads: exploring how it works and why it lasts,f2e5853b3ae9fcdecc4c204d9d8910bb,http://dx.doi.org/10.1057/ejis.2012.40
14338,"<p>Facing the threats of infectious diseases, we take various actions to protect ourselves, but few studies considered an evolving system with competing strategies. In view of that, we propose an evolutionary epidemic model coupled with human behaviors, where individuals have three strategies: vaccination, self-protection and laissez faire, and could adjust their strategies according to their neighbors' strategies and payoffs at the beginning of each new season of epidemic spreading. We found a counter-intuitive phenomenon analogous to the well-known <i>Braess's Paradox</i>, namely a better condition may lead to worse performance. Specifically speaking, increasing the successful rate of self-protection does not necessarily reduce the epidemic size or improve the system payoff. The range and degree of the Braess's Paradox are sensitive to both the parameters characterizing the epidemic spreading and the strategy payoff, while the existence of the Braess's Paradox is insensitive to the network topologies. This phenomenon can be well explained by a mean-field approximation. Our study demonstrates an important fact that a better condition for individuals may yield a worse outcome for the society.</p>",tao zhou,Applied mathematics,2013.0,10.1038/srep03292,Scientific Reports,Zhang2013,Not available,,Nature,Not available,Braess's Paradox in Epidemic Game: Better Condition Results in Less Payoff,551a0daab3513be189f0f7a0e0fd3e06,http://dx.doi.org/10.1038/srep03292
14339,"<p>Using a multiple case study design, we investigate the issue of inter-firm IT governance and its impact on information sharing in buyer–supplier dyadic relationships. We interviewed 38 managers of operations, purchasing, and IT in five dyadic relationships, and identified and examined one type of inter-firm IT governance: unilateral IT governance. In this type of IT governance, one party of the dyad dominates the relationship and the decision rights regarding inter-firm IT systems and data sharing. We find that unilateral inter-firm IT governance develops under contract-based and relationship-supplemented inter-firm governance arrangements in which significant power imbalance exists. However, contrary to the prediction of resource dependence theory, power-imbalanced governance can survive and thrive over a long period of time. We find that the inter-firm relational norms and trust that develop between these dyads constrain opportunistic and myopic behaviors in both parties, thus sustaining the seemingly unstable unilateral inter-firm IT governance. We also find that the operational necessity of the buyers and the IT capability of the suppliers are two primary factors that constrain inter-firm information sharing in these dyads. On the basis of these findings, we propose a process model for understanding and managing this type of inter-firm IT governance.</p>",kang xie,,2012.0,10.1057/ejis.2012.40,European Journal of Information Systems,Xiao2012,Not available,,Nature,Not available,Inter-firm IT governance in power-imbalanced buyer–supplier dyads: exploring how it works and why it lasts,f2e5853b3ae9fcdecc4c204d9d8910bb,http://dx.doi.org/10.1057/ejis.2012.40
14340,"<p>Using a multiple case study design, we investigate the issue of inter-firm IT governance and its impact on information sharing in buyer–supplier dyadic relationships. We interviewed 38 managers of operations, purchasing, and IT in five dyadic relationships, and identified and examined one type of inter-firm IT governance: unilateral IT governance. In this type of IT governance, one party of the dyad dominates the relationship and the decision rights regarding inter-firm IT systems and data sharing. We find that unilateral inter-firm IT governance develops under contract-based and relationship-supplemented inter-firm governance arrangements in which significant power imbalance exists. However, contrary to the prediction of resource dependence theory, power-imbalanced governance can survive and thrive over a long period of time. We find that the inter-firm relational norms and trust that develop between these dyads constrain opportunistic and myopic behaviors in both parties, thus sustaining the seemingly unstable unilateral inter-firm IT governance. We also find that the operational necessity of the buyers and the IT capability of the suppliers are two primary factors that constrain inter-firm information sharing in these dyads. On the basis of these findings, we propose a process model for understanding and managing this type of inter-firm IT governance.</p>",qing hu,,2012.0,10.1057/ejis.2012.40,European Journal of Information Systems,Xiao2012,Not available,,Nature,Not available,Inter-firm IT governance in power-imbalanced buyer–supplier dyads: exploring how it works and why it lasts,f2e5853b3ae9fcdecc4c204d9d8910bb,http://dx.doi.org/10.1057/ejis.2012.40
14341,"<p>Individuals change their behavior during an epidemic in response to whether they and/or those they interact with are healthy or sick. Healthy individuals may utilize protective measures to avoid contracting a disease. Sick individuals may utilize preemptive measures to avoid spreading a disease. Yet, in practice both protective and preemptive changes in behavior come with costs. This paper proposes a stochastic network disease game model that captures the self-interests of individuals during the spread of a susceptible-infected-susceptible disease. In this model, individuals strategically modify their behavior based on current disease conditions. These reactions influence disease spread. We show that there is a critical level of concern, i.e., empathy, by the sick individuals above which disease is eradicated rapidly. Furthermore, we find that risk averse behavior by the healthy individuals cannot eradicate the disease without the preemptive measures of the sick individuals. Empathy is more effective than risk-aversion because when infectious individuals change behavior, they reduce all of their potential infections, whereas when healthy individuals change behavior, they reduce only a small portion of potential infections. This imbalance in the role played by the response of the infected versus the susceptible individuals on disease eradication affords critical policy insights.</p>",ceyhun eksin,Nonlinear dynamics,2017.0,10.1038/srep44122,Scientific Reports,Eksin2017,Not available,,Nature,Not available,Disease dynamics in a stochastic network game: a little empathy goes a long way in averting outbreaks,2c38b74a5b1882290d79b3d932061783,http://dx.doi.org/10.1038/srep44122
14342,"<p>Individuals change their behavior during an epidemic in response to whether they and/or those they interact with are healthy or sick. Healthy individuals may utilize protective measures to avoid contracting a disease. Sick individuals may utilize preemptive measures to avoid spreading a disease. Yet, in practice both protective and preemptive changes in behavior come with costs. This paper proposes a stochastic network disease game model that captures the self-interests of individuals during the spread of a susceptible-infected-susceptible disease. In this model, individuals strategically modify their behavior based on current disease conditions. These reactions influence disease spread. We show that there is a critical level of concern, i.e., empathy, by the sick individuals above which disease is eradicated rapidly. Furthermore, we find that risk averse behavior by the healthy individuals cannot eradicate the disease without the preemptive measures of the sick individuals. Empathy is more effective than risk-aversion because when infectious individuals change behavior, they reduce all of their potential infections, whereas when healthy individuals change behavior, they reduce only a small portion of potential infections. This imbalance in the role played by the response of the infected versus the susceptible individuals on disease eradication affords critical policy insights.</p>",ceyhun eksin,Population dynamics,2017.0,10.1038/srep44122,Scientific Reports,Eksin2017,Not available,,Nature,Not available,Disease dynamics in a stochastic network game: a little empathy goes a long way in averting outbreaks,2c38b74a5b1882290d79b3d932061783,http://dx.doi.org/10.1038/srep44122
14343,"<p>Individuals change their behavior during an epidemic in response to whether they and/or those they interact with are healthy or sick. Healthy individuals may utilize protective measures to avoid contracting a disease. Sick individuals may utilize preemptive measures to avoid spreading a disease. Yet, in practice both protective and preemptive changes in behavior come with costs. This paper proposes a stochastic network disease game model that captures the self-interests of individuals during the spread of a susceptible-infected-susceptible disease. In this model, individuals strategically modify their behavior based on current disease conditions. These reactions influence disease spread. We show that there is a critical level of concern, i.e., empathy, by the sick individuals above which disease is eradicated rapidly. Furthermore, we find that risk averse behavior by the healthy individuals cannot eradicate the disease without the preemptive measures of the sick individuals. Empathy is more effective than risk-aversion because when infectious individuals change behavior, they reduce all of their potential infections, whereas when healthy individuals change behavior, they reduce only a small portion of potential infections. This imbalance in the role played by the response of the infected versus the susceptible individuals on disease eradication affords critical policy insights.</p>",ceyhun eksin,Stochastic modelling,2017.0,10.1038/srep44122,Scientific Reports,Eksin2017,Not available,,Nature,Not available,Disease dynamics in a stochastic network game: a little empathy goes a long way in averting outbreaks,2c38b74a5b1882290d79b3d932061783,http://dx.doi.org/10.1038/srep44122
14344,"<p>Individuals change their behavior during an epidemic in response to whether they and/or those they interact with are healthy or sick. Healthy individuals may utilize protective measures to avoid contracting a disease. Sick individuals may utilize preemptive measures to avoid spreading a disease. Yet, in practice both protective and preemptive changes in behavior come with costs. This paper proposes a stochastic network disease game model that captures the self-interests of individuals during the spread of a susceptible-infected-susceptible disease. In this model, individuals strategically modify their behavior based on current disease conditions. These reactions influence disease spread. We show that there is a critical level of concern, i.e., empathy, by the sick individuals above which disease is eradicated rapidly. Furthermore, we find that risk averse behavior by the healthy individuals cannot eradicate the disease without the preemptive measures of the sick individuals. Empathy is more effective than risk-aversion because when infectious individuals change behavior, they reduce all of their potential infections, whereas when healthy individuals change behavior, they reduce only a small portion of potential infections. This imbalance in the role played by the response of the infected versus the susceptible individuals on disease eradication affords critical policy insights.</p>",ceyhun eksin,Epidemiology,2017.0,10.1038/srep44122,Scientific Reports,Eksin2017,Not available,,Nature,Not available,Disease dynamics in a stochastic network game: a little empathy goes a long way in averting outbreaks,2c38b74a5b1882290d79b3d932061783,http://dx.doi.org/10.1038/srep44122
14345,"<p>Individuals change their behavior during an epidemic in response to whether they and/or those they interact with are healthy or sick. Healthy individuals may utilize protective measures to avoid contracting a disease. Sick individuals may utilize preemptive measures to avoid spreading a disease. Yet, in practice both protective and preemptive changes in behavior come with costs. This paper proposes a stochastic network disease game model that captures the self-interests of individuals during the spread of a susceptible-infected-susceptible disease. In this model, individuals strategically modify their behavior based on current disease conditions. These reactions influence disease spread. We show that there is a critical level of concern, i.e., empathy, by the sick individuals above which disease is eradicated rapidly. Furthermore, we find that risk averse behavior by the healthy individuals cannot eradicate the disease without the preemptive measures of the sick individuals. Empathy is more effective than risk-aversion because when infectious individuals change behavior, they reduce all of their potential infections, whereas when healthy individuals change behavior, they reduce only a small portion of potential infections. This imbalance in the role played by the response of the infected versus the susceptible individuals on disease eradication affords critical policy insights.</p>",jeff shamma,Nonlinear dynamics,2017.0,10.1038/srep44122,Scientific Reports,Eksin2017,Not available,,Nature,Not available,Disease dynamics in a stochastic network game: a little empathy goes a long way in averting outbreaks,2c38b74a5b1882290d79b3d932061783,http://dx.doi.org/10.1038/srep44122
14346,"<p>Individuals change their behavior during an epidemic in response to whether they and/or those they interact with are healthy or sick. Healthy individuals may utilize protective measures to avoid contracting a disease. Sick individuals may utilize preemptive measures to avoid spreading a disease. Yet, in practice both protective and preemptive changes in behavior come with costs. This paper proposes a stochastic network disease game model that captures the self-interests of individuals during the spread of a susceptible-infected-susceptible disease. In this model, individuals strategically modify their behavior based on current disease conditions. These reactions influence disease spread. We show that there is a critical level of concern, i.e., empathy, by the sick individuals above which disease is eradicated rapidly. Furthermore, we find that risk averse behavior by the healthy individuals cannot eradicate the disease without the preemptive measures of the sick individuals. Empathy is more effective than risk-aversion because when infectious individuals change behavior, they reduce all of their potential infections, whereas when healthy individuals change behavior, they reduce only a small portion of potential infections. This imbalance in the role played by the response of the infected versus the susceptible individuals on disease eradication affords critical policy insights.</p>",jeff shamma,Population dynamics,2017.0,10.1038/srep44122,Scientific Reports,Eksin2017,Not available,,Nature,Not available,Disease dynamics in a stochastic network game: a little empathy goes a long way in averting outbreaks,2c38b74a5b1882290d79b3d932061783,http://dx.doi.org/10.1038/srep44122
14347,"<p>Individuals change their behavior during an epidemic in response to whether they and/or those they interact with are healthy or sick. Healthy individuals may utilize protective measures to avoid contracting a disease. Sick individuals may utilize preemptive measures to avoid spreading a disease. Yet, in practice both protective and preemptive changes in behavior come with costs. This paper proposes a stochastic network disease game model that captures the self-interests of individuals during the spread of a susceptible-infected-susceptible disease. In this model, individuals strategically modify their behavior based on current disease conditions. These reactions influence disease spread. We show that there is a critical level of concern, i.e., empathy, by the sick individuals above which disease is eradicated rapidly. Furthermore, we find that risk averse behavior by the healthy individuals cannot eradicate the disease without the preemptive measures of the sick individuals. Empathy is more effective than risk-aversion because when infectious individuals change behavior, they reduce all of their potential infections, whereas when healthy individuals change behavior, they reduce only a small portion of potential infections. This imbalance in the role played by the response of the infected versus the susceptible individuals on disease eradication affords critical policy insights.</p>",jeff shamma,Stochastic modelling,2017.0,10.1038/srep44122,Scientific Reports,Eksin2017,Not available,,Nature,Not available,Disease dynamics in a stochastic network game: a little empathy goes a long way in averting outbreaks,2c38b74a5b1882290d79b3d932061783,http://dx.doi.org/10.1038/srep44122
14348,"<p>Facing the threats of infectious diseases, we take various actions to protect ourselves, but few studies considered an evolving system with competing strategies. In view of that, we propose an evolutionary epidemic model coupled with human behaviors, where individuals have three strategies: vaccination, self-protection and laissez faire, and could adjust their strategies according to their neighbors' strategies and payoffs at the beginning of each new season of epidemic spreading. We found a counter-intuitive phenomenon analogous to the well-known <i>Braess's Paradox</i>, namely a better condition may lead to worse performance. Specifically speaking, increasing the successful rate of self-protection does not necessarily reduce the epidemic size or improve the system payoff. The range and degree of the Braess's Paradox are sensitive to both the parameters characterizing the epidemic spreading and the strategy payoff, while the existence of the Braess's Paradox is insensitive to the network topologies. This phenomenon can be well explained by a mean-field approximation. Our study demonstrates an important fact that a better condition for individuals may yield a worse outcome for the society.</p>",tao zhou,Applied physics,2013.0,10.1038/srep03292,Scientific Reports,Zhang2013,Not available,,Nature,Not available,Braess's Paradox in Epidemic Game: Better Condition Results in Less Payoff,551a0daab3513be189f0f7a0e0fd3e06,http://dx.doi.org/10.1038/srep03292
14349,"<p>Individuals change their behavior during an epidemic in response to whether they and/or those they interact with are healthy or sick. Healthy individuals may utilize protective measures to avoid contracting a disease. Sick individuals may utilize preemptive measures to avoid spreading a disease. Yet, in practice both protective and preemptive changes in behavior come with costs. This paper proposes a stochastic network disease game model that captures the self-interests of individuals during the spread of a susceptible-infected-susceptible disease. In this model, individuals strategically modify their behavior based on current disease conditions. These reactions influence disease spread. We show that there is a critical level of concern, i.e., empathy, by the sick individuals above which disease is eradicated rapidly. Furthermore, we find that risk averse behavior by the healthy individuals cannot eradicate the disease without the preemptive measures of the sick individuals. Empathy is more effective than risk-aversion because when infectious individuals change behavior, they reduce all of their potential infections, whereas when healthy individuals change behavior, they reduce only a small portion of potential infections. This imbalance in the role played by the response of the infected versus the susceptible individuals on disease eradication affords critical policy insights.</p>",jeff shamma,Epidemiology,2017.0,10.1038/srep44122,Scientific Reports,Eksin2017,Not available,,Nature,Not available,Disease dynamics in a stochastic network game: a little empathy goes a long way in averting outbreaks,2c38b74a5b1882290d79b3d932061783,http://dx.doi.org/10.1038/srep44122
14350,"<p>Individuals change their behavior during an epidemic in response to whether they and/or those they interact with are healthy or sick. Healthy individuals may utilize protective measures to avoid contracting a disease. Sick individuals may utilize preemptive measures to avoid spreading a disease. Yet, in practice both protective and preemptive changes in behavior come with costs. This paper proposes a stochastic network disease game model that captures the self-interests of individuals during the spread of a susceptible-infected-susceptible disease. In this model, individuals strategically modify their behavior based on current disease conditions. These reactions influence disease spread. We show that there is a critical level of concern, i.e., empathy, by the sick individuals above which disease is eradicated rapidly. Furthermore, we find that risk averse behavior by the healthy individuals cannot eradicate the disease without the preemptive measures of the sick individuals. Empathy is more effective than risk-aversion because when infectious individuals change behavior, they reduce all of their potential infections, whereas when healthy individuals change behavior, they reduce only a small portion of potential infections. This imbalance in the role played by the response of the infected versus the susceptible individuals on disease eradication affords critical policy insights.</p>",joshua weitz,Nonlinear dynamics,2017.0,10.1038/srep44122,Scientific Reports,Eksin2017,Not available,,Nature,Not available,Disease dynamics in a stochastic network game: a little empathy goes a long way in averting outbreaks,2c38b74a5b1882290d79b3d932061783,http://dx.doi.org/10.1038/srep44122
14351,"<p>Individuals change their behavior during an epidemic in response to whether they and/or those they interact with are healthy or sick. Healthy individuals may utilize protective measures to avoid contracting a disease. Sick individuals may utilize preemptive measures to avoid spreading a disease. Yet, in practice both protective and preemptive changes in behavior come with costs. This paper proposes a stochastic network disease game model that captures the self-interests of individuals during the spread of a susceptible-infected-susceptible disease. In this model, individuals strategically modify their behavior based on current disease conditions. These reactions influence disease spread. We show that there is a critical level of concern, i.e., empathy, by the sick individuals above which disease is eradicated rapidly. Furthermore, we find that risk averse behavior by the healthy individuals cannot eradicate the disease without the preemptive measures of the sick individuals. Empathy is more effective than risk-aversion because when infectious individuals change behavior, they reduce all of their potential infections, whereas when healthy individuals change behavior, they reduce only a small portion of potential infections. This imbalance in the role played by the response of the infected versus the susceptible individuals on disease eradication affords critical policy insights.</p>",joshua weitz,Population dynamics,2017.0,10.1038/srep44122,Scientific Reports,Eksin2017,Not available,,Nature,Not available,Disease dynamics in a stochastic network game: a little empathy goes a long way in averting outbreaks,2c38b74a5b1882290d79b3d932061783,http://dx.doi.org/10.1038/srep44122
14352,"<p>Individuals change their behavior during an epidemic in response to whether they and/or those they interact with are healthy or sick. Healthy individuals may utilize protective measures to avoid contracting a disease. Sick individuals may utilize preemptive measures to avoid spreading a disease. Yet, in practice both protective and preemptive changes in behavior come with costs. This paper proposes a stochastic network disease game model that captures the self-interests of individuals during the spread of a susceptible-infected-susceptible disease. In this model, individuals strategically modify their behavior based on current disease conditions. These reactions influence disease spread. We show that there is a critical level of concern, i.e., empathy, by the sick individuals above which disease is eradicated rapidly. Furthermore, we find that risk averse behavior by the healthy individuals cannot eradicate the disease without the preemptive measures of the sick individuals. Empathy is more effective than risk-aversion because when infectious individuals change behavior, they reduce all of their potential infections, whereas when healthy individuals change behavior, they reduce only a small portion of potential infections. This imbalance in the role played by the response of the infected versus the susceptible individuals on disease eradication affords critical policy insights.</p>",joshua weitz,Stochastic modelling,2017.0,10.1038/srep44122,Scientific Reports,Eksin2017,Not available,,Nature,Not available,Disease dynamics in a stochastic network game: a little empathy goes a long way in averting outbreaks,2c38b74a5b1882290d79b3d932061783,http://dx.doi.org/10.1038/srep44122
14353,"<p>Individuals change their behavior during an epidemic in response to whether they and/or those they interact with are healthy or sick. Healthy individuals may utilize protective measures to avoid contracting a disease. Sick individuals may utilize preemptive measures to avoid spreading a disease. Yet, in practice both protective and preemptive changes in behavior come with costs. This paper proposes a stochastic network disease game model that captures the self-interests of individuals during the spread of a susceptible-infected-susceptible disease. In this model, individuals strategically modify their behavior based on current disease conditions. These reactions influence disease spread. We show that there is a critical level of concern, i.e., empathy, by the sick individuals above which disease is eradicated rapidly. Furthermore, we find that risk averse behavior by the healthy individuals cannot eradicate the disease without the preemptive measures of the sick individuals. Empathy is more effective than risk-aversion because when infectious individuals change behavior, they reduce all of their potential infections, whereas when healthy individuals change behavior, they reduce only a small portion of potential infections. This imbalance in the role played by the response of the infected versus the susceptible individuals on disease eradication affords critical policy insights.</p>",joshua weitz,Epidemiology,2017.0,10.1038/srep44122,Scientific Reports,Eksin2017,Not available,,Nature,Not available,Disease dynamics in a stochastic network game: a little empathy goes a long way in averting outbreaks,2c38b74a5b1882290d79b3d932061783,http://dx.doi.org/10.1038/srep44122
14354,"<p>Following Kohut, the psychoanalytic literature has usually discussed revenge in terms of narcissistic rage evoked in response to narcissistic injury. In this paper, I draw on Bion to present an alternative reading of revenge. This interpretation is illustrated through von Kleist's <i>Michael Kohlhaas</i> and Moore and Lloyd's <i>V for Vendetta</i>.</p>",yair neuman,,2012.0,10.1057/pcs.2012.4,"Psychoanalysis, Culture & Society",Neuman2012,Not available,,Nature,Not available,On revenge,b2cac4dfcca00c24299321b2bf043e63,http://dx.doi.org/10.1057/pcs.2012.4
14355,"<p>Facing the threats of infectious diseases, we take various actions to protect ourselves, but few studies considered an evolving system with competing strategies. In view of that, we propose an evolutionary epidemic model coupled with human behaviors, where individuals have three strategies: vaccination, self-protection and laissez faire, and could adjust their strategies according to their neighbors' strategies and payoffs at the beginning of each new season of epidemic spreading. We found a counter-intuitive phenomenon analogous to the well-known <i>Braess's Paradox</i>, namely a better condition may lead to worse performance. Specifically speaking, increasing the successful rate of self-protection does not necessarily reduce the epidemic size or improve the system payoff. The range and degree of the Braess's Paradox are sensitive to both the parameters characterizing the epidemic spreading and the strategy payoff, while the existence of the Braess's Paradox is insensitive to the network topologies. This phenomenon can be well explained by a mean-field approximation. Our study demonstrates an important fact that a better condition for individuals may yield a worse outcome for the society.</p>",tao zhou,Complex networks,2013.0,10.1038/srep03292,Scientific Reports,Zhang2013,Not available,,Nature,Not available,Braess's Paradox in Epidemic Game: Better Condition Results in Less Payoff,551a0daab3513be189f0f7a0e0fd3e06,http://dx.doi.org/10.1038/srep03292
14356,"<p>Russia has been the leading proponent of transforming the BRICs from an investment strategy into a recognized coalition of emerging powers bearing significant implications for international relations. Since the end of the Cold War, Moscow has tried to deny the realities of unipolarity while grudgingly adjusting to its constraints. Now that American primacy is waning, Russia, the perennial outsider, aims to become an insider and a rule maker in the international system. Despite questioning the existing order's durability and legitimacy, Russia and the other BRICs seek to be among its managing directors, not to overthrow it. Russia has simultaneously sought to renegotiate the terms of its accommodation to the Euro-Atlantic order, drawing on its preference for cooperation without domestic conditionality requirements. Moscow's BRICs diplomacy has been one of its most successful international initiatives, although the group's future existence will probably be determined by China, the real contender for polar power status.</p>",cynthia roberts,,2009.0,10.1057/pol.2009.18,Polity,Roberts2009,Not available,,Nature,Not available,Russia's BRICs Diplomacy: Rising Outsider with Dreams of an Insider,2163e685980dd29d043a6bab6c74835c,http://dx.doi.org/10.1057/pol.2009.18
14357,"<p>Sadig Rasheed argues that strong commitment to international development co-operation is visibly faltering, precisely at the historical juncture when such commitment and creative vision on strengthened global partnership are most needed. He proposes a reinstatement of the North–South dialogue that moves beyond an uncritical monologue on the virtues and benefits of globalization and free markets, focusing on Africa as the ‘priority of the priorities’.</p>",sadig rasheed,,2007.0,10.1057/palgrave.development.1100393,Development,Rasheed2007,Not available,,Nature,Not available,Poorest Nations and Development Co-operation: In search of an elusive ethic,e51c4c6ac8e41fbf9664c1ba2f8c8736,http://dx.doi.org/10.1057/palgrave.development.1100393
14358,"<p>Within the theoretical framework of the mixed-motive model of public relations, this case study of President Obama's speech in Prague, calling for ‘a world without nuclear weapons’, analyzes the dynamics of rhetoric of public diplomacy in the mixed-motive situation. The analysis shows that the speech presented a two-way symmetrical worldview. At the same time, it made asymmetrical advocacy by stressing the US leadership, continuing the containment theme and justifying the continued possession of the nuclear arsenals by the United States, corroborating the mixed-motive model's assumption of divided loyalty. To reduce the tensions caused by such mixed motives, the speech presented a constructivist worldview that emphasized on the power of ideas, morality, norms and the possibility of change. Its emphasis on the long-term nature of the cause echoed Grunig's (2001) argument that in the mixed-motive model asymmetrical tactics may be used within the win-win zone because such practices are bounded by a symmetrical worldview that ‘respects long-term relationships’. In the speech, President Obama mostly relied on ethos to make his call credible. Pathos is the second major rhetorical strategy by appealing to fear and shame. The least used appeal is logos. The varied weight of the appeals revealed potential rhetorical strategies in a mixed-motive situation. The findings of the research confirm Gilboa's (2008) argument that application of the constructivism approach to public diplomacy may produce fresh insights. This research contributes to the research in the Excellence Theory and public diplomacy.</p>",juyan zhang,,2010.0,10.1057/pb.2010.31,Place Branding and Public Diplomacy,Zhang2010,Not available,,Nature,Not available,Exploring rhetoric of public diplomacy in the mixed-motive situation: Using the case of President Obama's ‘nuclear-free world’ speech in Prague,52ccc9cd9ffab03d03239c465007ad24,http://dx.doi.org/10.1057/pb.2010.31
14359,"<p>Universities are living a triple crisis of hegemony, of legitimacy and institutional. This crisis is coterminous with the fiscal crisis of the state and the crisis of the welfare state. The loss of legitimacy of the welfare state gave rise to an increasing role of the market and to the change of the university from a ‘social institution’ to a mere ‘social organization’ while new managerial values seem to be replacing the traditional modes of academic governance. It is necessary for higher education to be reinvented and for academics to present again the case for higher education. But this needs to be a new case, not a restatement of the former.</p>",alberto amaral,,2003.0,10.1057/palgrave.hep.8300018,Higher Education Policy,Amaral2003,Not available,,Nature,Not available,The Triple Crisis of the University and its Reinvention,5c6c78218dd5756e86557d0e5312a9b4,http://dx.doi.org/10.1057/palgrave.hep.8300018
14360,"<p>Universities are living a triple crisis of hegemony, of legitimacy and institutional. This crisis is coterminous with the fiscal crisis of the state and the crisis of the welfare state. The loss of legitimacy of the welfare state gave rise to an increasing role of the market and to the change of the university from a ‘social institution’ to a mere ‘social organization’ while new managerial values seem to be replacing the traditional modes of academic governance. It is necessary for higher education to be reinvented and for academics to present again the case for higher education. But this needs to be a new case, not a restatement of the former.</p>",antonio magalhaes,,2003.0,10.1057/palgrave.hep.8300018,Higher Education Policy,Amaral2003,Not available,,Nature,Not available,The Triple Crisis of the University and its Reinvention,5c6c78218dd5756e86557d0e5312a9b4,http://dx.doi.org/10.1057/palgrave.hep.8300018
14361,"<p>Without HIV, the tuberculosis (TB) epidemic would now be in decline almost everywhere. However, instead of looking forward to the demise of TB, countries that are badly affected by HIV are struggling against a rising tide of HIV-infected patients with TB. As a consequence, global TB control policies have had to be revised and control of TB now demands increased investment. This paper assesses what is being done to address the issue and what remains to be done.</p>",paul nunn,,2005.0,10.1038/nri1704,Nature Reviews Immunology,Nunn2005,Not available,,Nature,Not available,Tuberculosis control in the era of HIV,c37a29cf47540c62b3ae9184d92f359d,http://dx.doi.org/10.1038/nri1704
14362,"<p>The Paris Agreement culminates a six-year transition towards an international climate policy architecture based on parties submitting national pledges every five years. An important policy task will be to assess and compare these contributions. We use four integrated assessment models to produce metrics of Paris Agreement pledges, and show differentiated effort across countries: wealthier countries pledge to undertake greater emission reductions with higher costs. The pledges fall in the lower end of the distributions of the social cost of carbon and the cost-minimizing path to limiting warming to 2 °C, suggesting insufficient global ambition in light of leaders’ climate goals. Countries’ marginal abatement costs vary by two orders of magnitude, illustrating that large efficiency gains are available through joint mitigation efforts and/or carbon price coordination. Marginal costs rise almost proportionally with income, but full policy costs reveal more complex regional patterns due to terms of trade effects.</p>",joseph aldy,Climate-change mitigation,2016.0,10.1038/nclimate3106,Nature Climate Change,Aldy2016,Not available,,Nature,Not available,Economic tools to promote transparency and comparability in the Paris Agreement,d92c835ca77655002e12fde37413751c,http://dx.doi.org/10.1038/nclimate3106
14363,"<p>The Paris Agreement culminates a six-year transition towards an international climate policy architecture based on parties submitting national pledges every five years. An important policy task will be to assess and compare these contributions. We use four integrated assessment models to produce metrics of Paris Agreement pledges, and show differentiated effort across countries: wealthier countries pledge to undertake greater emission reductions with higher costs. The pledges fall in the lower end of the distributions of the social cost of carbon and the cost-minimizing path to limiting warming to 2 °C, suggesting insufficient global ambition in light of leaders’ climate goals. Countries’ marginal abatement costs vary by two orders of magnitude, illustrating that large efficiency gains are available through joint mitigation efforts and/or carbon price coordination. Marginal costs rise almost proportionally with income, but full policy costs reveal more complex regional patterns due to terms of trade effects.</p>",joseph aldy,Environmental economics,2016.0,10.1038/nclimate3106,Nature Climate Change,Aldy2016,Not available,,Nature,Not available,Economic tools to promote transparency and comparability in the Paris Agreement,d92c835ca77655002e12fde37413751c,http://dx.doi.org/10.1038/nclimate3106
14364,"<p>The Paris Agreement culminates a six-year transition towards an international climate policy architecture based on parties submitting national pledges every five years. An important policy task will be to assess and compare these contributions. We use four integrated assessment models to produce metrics of Paris Agreement pledges, and show differentiated effort across countries: wealthier countries pledge to undertake greater emission reductions with higher costs. The pledges fall in the lower end of the distributions of the social cost of carbon and the cost-minimizing path to limiting warming to 2 °C, suggesting insufficient global ambition in light of leaders’ climate goals. Countries’ marginal abatement costs vary by two orders of magnitude, illustrating that large efficiency gains are available through joint mitigation efforts and/or carbon price coordination. Marginal costs rise almost proportionally with income, but full policy costs reveal more complex regional patterns due to terms of trade effects.</p>",william pizer,Climate-change mitigation,2016.0,10.1038/nclimate3106,Nature Climate Change,Aldy2016,Not available,,Nature,Not available,Economic tools to promote transparency and comparability in the Paris Agreement,d92c835ca77655002e12fde37413751c,http://dx.doi.org/10.1038/nclimate3106
14365,"<p>The Paris Agreement culminates a six-year transition towards an international climate policy architecture based on parties submitting national pledges every five years. An important policy task will be to assess and compare these contributions. We use four integrated assessment models to produce metrics of Paris Agreement pledges, and show differentiated effort across countries: wealthier countries pledge to undertake greater emission reductions with higher costs. The pledges fall in the lower end of the distributions of the social cost of carbon and the cost-minimizing path to limiting warming to 2 °C, suggesting insufficient global ambition in light of leaders’ climate goals. Countries’ marginal abatement costs vary by two orders of magnitude, illustrating that large efficiency gains are available through joint mitigation efforts and/or carbon price coordination. Marginal costs rise almost proportionally with income, but full policy costs reveal more complex regional patterns due to terms of trade effects.</p>",william pizer,Environmental economics,2016.0,10.1038/nclimate3106,Nature Climate Change,Aldy2016,Not available,,Nature,Not available,Economic tools to promote transparency and comparability in the Paris Agreement,d92c835ca77655002e12fde37413751c,http://dx.doi.org/10.1038/nclimate3106
14366,"<p>The Paris Agreement culminates a six-year transition towards an international climate policy architecture based on parties submitting national pledges every five years. An important policy task will be to assess and compare these contributions. We use four integrated assessment models to produce metrics of Paris Agreement pledges, and show differentiated effort across countries: wealthier countries pledge to undertake greater emission reductions with higher costs. The pledges fall in the lower end of the distributions of the social cost of carbon and the cost-minimizing path to limiting warming to 2 °C, suggesting insufficient global ambition in light of leaders’ climate goals. Countries’ marginal abatement costs vary by two orders of magnitude, illustrating that large efficiency gains are available through joint mitigation efforts and/or carbon price coordination. Marginal costs rise almost proportionally with income, but full policy costs reveal more complex regional patterns due to terms of trade effects.</p>",massimo tavoni,Climate-change mitigation,2016.0,10.1038/nclimate3106,Nature Climate Change,Aldy2016,Not available,,Nature,Not available,Economic tools to promote transparency and comparability in the Paris Agreement,d92c835ca77655002e12fde37413751c,http://dx.doi.org/10.1038/nclimate3106
14367,"<p>The Paris Agreement culminates a six-year transition towards an international climate policy architecture based on parties submitting national pledges every five years. An important policy task will be to assess and compare these contributions. We use four integrated assessment models to produce metrics of Paris Agreement pledges, and show differentiated effort across countries: wealthier countries pledge to undertake greater emission reductions with higher costs. The pledges fall in the lower end of the distributions of the social cost of carbon and the cost-minimizing path to limiting warming to 2 °C, suggesting insufficient global ambition in light of leaders’ climate goals. Countries’ marginal abatement costs vary by two orders of magnitude, illustrating that large efficiency gains are available through joint mitigation efforts and/or carbon price coordination. Marginal costs rise almost proportionally with income, but full policy costs reveal more complex regional patterns due to terms of trade effects.</p>",massimo tavoni,Environmental economics,2016.0,10.1038/nclimate3106,Nature Climate Change,Aldy2016,Not available,,Nature,Not available,Economic tools to promote transparency and comparability in the Paris Agreement,d92c835ca77655002e12fde37413751c,http://dx.doi.org/10.1038/nclimate3106
14368,"<p>Without HIV, the tuberculosis (TB) epidemic would now be in decline almost everywhere. However, instead of looking forward to the demise of TB, countries that are badly affected by HIV are struggling against a rising tide of HIV-infected patients with TB. As a consequence, global TB control policies have had to be revised and control of TB now demands increased investment. This paper assesses what is being done to address the issue and what remains to be done.</p>",brian williams,,2005.0,10.1038/nri1704,Nature Reviews Immunology,Nunn2005,Not available,,Nature,Not available,Tuberculosis control in the era of HIV,c37a29cf47540c62b3ae9184d92f359d,http://dx.doi.org/10.1038/nri1704
14369,"<p>The Paris Agreement culminates a six-year transition towards an international climate policy architecture based on parties submitting national pledges every five years. An important policy task will be to assess and compare these contributions. We use four integrated assessment models to produce metrics of Paris Agreement pledges, and show differentiated effort across countries: wealthier countries pledge to undertake greater emission reductions with higher costs. The pledges fall in the lower end of the distributions of the social cost of carbon and the cost-minimizing path to limiting warming to 2 °C, suggesting insufficient global ambition in light of leaders’ climate goals. Countries’ marginal abatement costs vary by two orders of magnitude, illustrating that large efficiency gains are available through joint mitigation efforts and/or carbon price coordination. Marginal costs rise almost proportionally with income, but full policy costs reveal more complex regional patterns due to terms of trade effects.</p>",lara reis,Climate-change mitigation,2016.0,10.1038/nclimate3106,Nature Climate Change,Aldy2016,Not available,,Nature,Not available,Economic tools to promote transparency and comparability in the Paris Agreement,d92c835ca77655002e12fde37413751c,http://dx.doi.org/10.1038/nclimate3106
14370,"<p>The Paris Agreement culminates a six-year transition towards an international climate policy architecture based on parties submitting national pledges every five years. An important policy task will be to assess and compare these contributions. We use four integrated assessment models to produce metrics of Paris Agreement pledges, and show differentiated effort across countries: wealthier countries pledge to undertake greater emission reductions with higher costs. The pledges fall in the lower end of the distributions of the social cost of carbon and the cost-minimizing path to limiting warming to 2 °C, suggesting insufficient global ambition in light of leaders’ climate goals. Countries’ marginal abatement costs vary by two orders of magnitude, illustrating that large efficiency gains are available through joint mitigation efforts and/or carbon price coordination. Marginal costs rise almost proportionally with income, but full policy costs reveal more complex regional patterns due to terms of trade effects.</p>",lara reis,Environmental economics,2016.0,10.1038/nclimate3106,Nature Climate Change,Aldy2016,Not available,,Nature,Not available,Economic tools to promote transparency and comparability in the Paris Agreement,d92c835ca77655002e12fde37413751c,http://dx.doi.org/10.1038/nclimate3106
14371,"<p>The Paris Agreement culminates a six-year transition towards an international climate policy architecture based on parties submitting national pledges every five years. An important policy task will be to assess and compare these contributions. We use four integrated assessment models to produce metrics of Paris Agreement pledges, and show differentiated effort across countries: wealthier countries pledge to undertake greater emission reductions with higher costs. The pledges fall in the lower end of the distributions of the social cost of carbon and the cost-minimizing path to limiting warming to 2 °C, suggesting insufficient global ambition in light of leaders’ climate goals. Countries’ marginal abatement costs vary by two orders of magnitude, illustrating that large efficiency gains are available through joint mitigation efforts and/or carbon price coordination. Marginal costs rise almost proportionally with income, but full policy costs reveal more complex regional patterns due to terms of trade effects.</p>",keigo akimoto,Climate-change mitigation,2016.0,10.1038/nclimate3106,Nature Climate Change,Aldy2016,Not available,,Nature,Not available,Economic tools to promote transparency and comparability in the Paris Agreement,d92c835ca77655002e12fde37413751c,http://dx.doi.org/10.1038/nclimate3106
14372,"<p>The Paris Agreement culminates a six-year transition towards an international climate policy architecture based on parties submitting national pledges every five years. An important policy task will be to assess and compare these contributions. We use four integrated assessment models to produce metrics of Paris Agreement pledges, and show differentiated effort across countries: wealthier countries pledge to undertake greater emission reductions with higher costs. The pledges fall in the lower end of the distributions of the social cost of carbon and the cost-minimizing path to limiting warming to 2 °C, suggesting insufficient global ambition in light of leaders’ climate goals. Countries’ marginal abatement costs vary by two orders of magnitude, illustrating that large efficiency gains are available through joint mitigation efforts and/or carbon price coordination. Marginal costs rise almost proportionally with income, but full policy costs reveal more complex regional patterns due to terms of trade effects.</p>",keigo akimoto,Environmental economics,2016.0,10.1038/nclimate3106,Nature Climate Change,Aldy2016,Not available,,Nature,Not available,Economic tools to promote transparency and comparability in the Paris Agreement,d92c835ca77655002e12fde37413751c,http://dx.doi.org/10.1038/nclimate3106
14373,"<p>The Paris Agreement culminates a six-year transition towards an international climate policy architecture based on parties submitting national pledges every five years. An important policy task will be to assess and compare these contributions. We use four integrated assessment models to produce metrics of Paris Agreement pledges, and show differentiated effort across countries: wealthier countries pledge to undertake greater emission reductions with higher costs. The pledges fall in the lower end of the distributions of the social cost of carbon and the cost-minimizing path to limiting warming to 2 °C, suggesting insufficient global ambition in light of leaders’ climate goals. Countries’ marginal abatement costs vary by two orders of magnitude, illustrating that large efficiency gains are available through joint mitigation efforts and/or carbon price coordination. Marginal costs rise almost proportionally with income, but full policy costs reveal more complex regional patterns due to terms of trade effects.</p>",geoffrey blanford,Climate-change mitigation,2016.0,10.1038/nclimate3106,Nature Climate Change,Aldy2016,Not available,,Nature,Not available,Economic tools to promote transparency and comparability in the Paris Agreement,d92c835ca77655002e12fde37413751c,http://dx.doi.org/10.1038/nclimate3106
14374,"<p>The Paris Agreement culminates a six-year transition towards an international climate policy architecture based on parties submitting national pledges every five years. An important policy task will be to assess and compare these contributions. We use four integrated assessment models to produce metrics of Paris Agreement pledges, and show differentiated effort across countries: wealthier countries pledge to undertake greater emission reductions with higher costs. The pledges fall in the lower end of the distributions of the social cost of carbon and the cost-minimizing path to limiting warming to 2 °C, suggesting insufficient global ambition in light of leaders’ climate goals. Countries’ marginal abatement costs vary by two orders of magnitude, illustrating that large efficiency gains are available through joint mitigation efforts and/or carbon price coordination. Marginal costs rise almost proportionally with income, but full policy costs reveal more complex regional patterns due to terms of trade effects.</p>",geoffrey blanford,Environmental economics,2016.0,10.1038/nclimate3106,Nature Climate Change,Aldy2016,Not available,,Nature,Not available,Economic tools to promote transparency and comparability in the Paris Agreement,d92c835ca77655002e12fde37413751c,http://dx.doi.org/10.1038/nclimate3106
14375,"<p>The Paris Agreement culminates a six-year transition towards an international climate policy architecture based on parties submitting national pledges every five years. An important policy task will be to assess and compare these contributions. We use four integrated assessment models to produce metrics of Paris Agreement pledges, and show differentiated effort across countries: wealthier countries pledge to undertake greater emission reductions with higher costs. The pledges fall in the lower end of the distributions of the social cost of carbon and the cost-minimizing path to limiting warming to 2 °C, suggesting insufficient global ambition in light of leaders’ climate goals. Countries’ marginal abatement costs vary by two orders of magnitude, illustrating that large efficiency gains are available through joint mitigation efforts and/or carbon price coordination. Marginal costs rise almost proportionally with income, but full policy costs reveal more complex regional patterns due to terms of trade effects.</p>",carlo carraro,Climate-change mitigation,2016.0,10.1038/nclimate3106,Nature Climate Change,Aldy2016,Not available,,Nature,Not available,Economic tools to promote transparency and comparability in the Paris Agreement,d92c835ca77655002e12fde37413751c,http://dx.doi.org/10.1038/nclimate3106
14376,"<p>The Paris Agreement culminates a six-year transition towards an international climate policy architecture based on parties submitting national pledges every five years. An important policy task will be to assess and compare these contributions. We use four integrated assessment models to produce metrics of Paris Agreement pledges, and show differentiated effort across countries: wealthier countries pledge to undertake greater emission reductions with higher costs. The pledges fall in the lower end of the distributions of the social cost of carbon and the cost-minimizing path to limiting warming to 2 °C, suggesting insufficient global ambition in light of leaders’ climate goals. Countries’ marginal abatement costs vary by two orders of magnitude, illustrating that large efficiency gains are available through joint mitigation efforts and/or carbon price coordination. Marginal costs rise almost proportionally with income, but full policy costs reveal more complex regional patterns due to terms of trade effects.</p>",carlo carraro,Environmental economics,2016.0,10.1038/nclimate3106,Nature Climate Change,Aldy2016,Not available,,Nature,Not available,Economic tools to promote transparency and comparability in the Paris Agreement,d92c835ca77655002e12fde37413751c,http://dx.doi.org/10.1038/nclimate3106
14377,"<p>The Paris Agreement culminates a six-year transition towards an international climate policy architecture based on parties submitting national pledges every five years. An important policy task will be to assess and compare these contributions. We use four integrated assessment models to produce metrics of Paris Agreement pledges, and show differentiated effort across countries: wealthier countries pledge to undertake greater emission reductions with higher costs. The pledges fall in the lower end of the distributions of the social cost of carbon and the cost-minimizing path to limiting warming to 2 °C, suggesting insufficient global ambition in light of leaders’ climate goals. Countries’ marginal abatement costs vary by two orders of magnitude, illustrating that large efficiency gains are available through joint mitigation efforts and/or carbon price coordination. Marginal costs rise almost proportionally with income, but full policy costs reveal more complex regional patterns due to terms of trade effects.</p>",leon clarke,Climate-change mitigation,2016.0,10.1038/nclimate3106,Nature Climate Change,Aldy2016,Not available,,Nature,Not available,Economic tools to promote transparency and comparability in the Paris Agreement,d92c835ca77655002e12fde37413751c,http://dx.doi.org/10.1038/nclimate3106
14378,"<p>The Paris Agreement culminates a six-year transition towards an international climate policy architecture based on parties submitting national pledges every five years. An important policy task will be to assess and compare these contributions. We use four integrated assessment models to produce metrics of Paris Agreement pledges, and show differentiated effort across countries: wealthier countries pledge to undertake greater emission reductions with higher costs. The pledges fall in the lower end of the distributions of the social cost of carbon and the cost-minimizing path to limiting warming to 2 °C, suggesting insufficient global ambition in light of leaders’ climate goals. Countries’ marginal abatement costs vary by two orders of magnitude, illustrating that large efficiency gains are available through joint mitigation efforts and/or carbon price coordination. Marginal costs rise almost proportionally with income, but full policy costs reveal more complex regional patterns due to terms of trade effects.</p>",leon clarke,Environmental economics,2016.0,10.1038/nclimate3106,Nature Climate Change,Aldy2016,Not available,,Nature,Not available,Economic tools to promote transparency and comparability in the Paris Agreement,d92c835ca77655002e12fde37413751c,http://dx.doi.org/10.1038/nclimate3106
14379,"<p>Without HIV, the tuberculosis (TB) epidemic would now be in decline almost everywhere. However, instead of looking forward to the demise of TB, countries that are badly affected by HIV are struggling against a rising tide of HIV-infected patients with TB. As a consequence, global TB control policies have had to be revised and control of TB now demands increased investment. This paper assesses what is being done to address the issue and what remains to be done.</p>",katherine floyd,,2005.0,10.1038/nri1704,Nature Reviews Immunology,Nunn2005,Not available,,Nature,Not available,Tuberculosis control in the era of HIV,c37a29cf47540c62b3ae9184d92f359d,http://dx.doi.org/10.1038/nri1704
14380,"<p>The Paris Agreement culminates a six-year transition towards an international climate policy architecture based on parties submitting national pledges every five years. An important policy task will be to assess and compare these contributions. We use four integrated assessment models to produce metrics of Paris Agreement pledges, and show differentiated effort across countries: wealthier countries pledge to undertake greater emission reductions with higher costs. The pledges fall in the lower end of the distributions of the social cost of carbon and the cost-minimizing path to limiting warming to 2 °C, suggesting insufficient global ambition in light of leaders’ climate goals. Countries’ marginal abatement costs vary by two orders of magnitude, illustrating that large efficiency gains are available through joint mitigation efforts and/or carbon price coordination. Marginal costs rise almost proportionally with income, but full policy costs reveal more complex regional patterns due to terms of trade effects.</p>",james edmonds,Climate-change mitigation,2016.0,10.1038/nclimate3106,Nature Climate Change,Aldy2016,Not available,,Nature,Not available,Economic tools to promote transparency and comparability in the Paris Agreement,d92c835ca77655002e12fde37413751c,http://dx.doi.org/10.1038/nclimate3106
14381,"<p>The Paris Agreement culminates a six-year transition towards an international climate policy architecture based on parties submitting national pledges every five years. An important policy task will be to assess and compare these contributions. We use four integrated assessment models to produce metrics of Paris Agreement pledges, and show differentiated effort across countries: wealthier countries pledge to undertake greater emission reductions with higher costs. The pledges fall in the lower end of the distributions of the social cost of carbon and the cost-minimizing path to limiting warming to 2 °C, suggesting insufficient global ambition in light of leaders’ climate goals. Countries’ marginal abatement costs vary by two orders of magnitude, illustrating that large efficiency gains are available through joint mitigation efforts and/or carbon price coordination. Marginal costs rise almost proportionally with income, but full policy costs reveal more complex regional patterns due to terms of trade effects.</p>",james edmonds,Environmental economics,2016.0,10.1038/nclimate3106,Nature Climate Change,Aldy2016,Not available,,Nature,Not available,Economic tools to promote transparency and comparability in the Paris Agreement,d92c835ca77655002e12fde37413751c,http://dx.doi.org/10.1038/nclimate3106
14382,"<p>The Paris Agreement culminates a six-year transition towards an international climate policy architecture based on parties submitting national pledges every five years. An important policy task will be to assess and compare these contributions. We use four integrated assessment models to produce metrics of Paris Agreement pledges, and show differentiated effort across countries: wealthier countries pledge to undertake greater emission reductions with higher costs. The pledges fall in the lower end of the distributions of the social cost of carbon and the cost-minimizing path to limiting warming to 2 °C, suggesting insufficient global ambition in light of leaders’ climate goals. Countries’ marginal abatement costs vary by two orders of magnitude, illustrating that large efficiency gains are available through joint mitigation efforts and/or carbon price coordination. Marginal costs rise almost proportionally with income, but full policy costs reveal more complex regional patterns due to terms of trade effects.</p>",gokul iyer,Climate-change mitigation,2016.0,10.1038/nclimate3106,Nature Climate Change,Aldy2016,Not available,,Nature,Not available,Economic tools to promote transparency and comparability in the Paris Agreement,d92c835ca77655002e12fde37413751c,http://dx.doi.org/10.1038/nclimate3106
14383,"<p>The Paris Agreement culminates a six-year transition towards an international climate policy architecture based on parties submitting national pledges every five years. An important policy task will be to assess and compare these contributions. We use four integrated assessment models to produce metrics of Paris Agreement pledges, and show differentiated effort across countries: wealthier countries pledge to undertake greater emission reductions with higher costs. The pledges fall in the lower end of the distributions of the social cost of carbon and the cost-minimizing path to limiting warming to 2 °C, suggesting insufficient global ambition in light of leaders’ climate goals. Countries’ marginal abatement costs vary by two orders of magnitude, illustrating that large efficiency gains are available through joint mitigation efforts and/or carbon price coordination. Marginal costs rise almost proportionally with income, but full policy costs reveal more complex regional patterns due to terms of trade effects.</p>",gokul iyer,Environmental economics,2016.0,10.1038/nclimate3106,Nature Climate Change,Aldy2016,Not available,,Nature,Not available,Economic tools to promote transparency and comparability in the Paris Agreement,d92c835ca77655002e12fde37413751c,http://dx.doi.org/10.1038/nclimate3106
14384,"<p>The Paris Agreement culminates a six-year transition towards an international climate policy architecture based on parties submitting national pledges every five years. An important policy task will be to assess and compare these contributions. We use four integrated assessment models to produce metrics of Paris Agreement pledges, and show differentiated effort across countries: wealthier countries pledge to undertake greater emission reductions with higher costs. The pledges fall in the lower end of the distributions of the social cost of carbon and the cost-minimizing path to limiting warming to 2 °C, suggesting insufficient global ambition in light of leaders’ climate goals. Countries’ marginal abatement costs vary by two orders of magnitude, illustrating that large efficiency gains are available through joint mitigation efforts and/or carbon price coordination. Marginal costs rise almost proportionally with income, but full policy costs reveal more complex regional patterns due to terms of trade effects.</p>",haewon mcjeon,Climate-change mitigation,2016.0,10.1038/nclimate3106,Nature Climate Change,Aldy2016,Not available,,Nature,Not available,Economic tools to promote transparency and comparability in the Paris Agreement,d92c835ca77655002e12fde37413751c,http://dx.doi.org/10.1038/nclimate3106
14385,"<p>The Paris Agreement culminates a six-year transition towards an international climate policy architecture based on parties submitting national pledges every five years. An important policy task will be to assess and compare these contributions. We use four integrated assessment models to produce metrics of Paris Agreement pledges, and show differentiated effort across countries: wealthier countries pledge to undertake greater emission reductions with higher costs. The pledges fall in the lower end of the distributions of the social cost of carbon and the cost-minimizing path to limiting warming to 2 °C, suggesting insufficient global ambition in light of leaders’ climate goals. Countries’ marginal abatement costs vary by two orders of magnitude, illustrating that large efficiency gains are available through joint mitigation efforts and/or carbon price coordination. Marginal costs rise almost proportionally with income, but full policy costs reveal more complex regional patterns due to terms of trade effects.</p>",haewon mcjeon,Environmental economics,2016.0,10.1038/nclimate3106,Nature Climate Change,Aldy2016,Not available,,Nature,Not available,Economic tools to promote transparency and comparability in the Paris Agreement,d92c835ca77655002e12fde37413751c,http://dx.doi.org/10.1038/nclimate3106
14386,"<p>The Paris Agreement culminates a six-year transition towards an international climate policy architecture based on parties submitting national pledges every five years. An important policy task will be to assess and compare these contributions. We use four integrated assessment models to produce metrics of Paris Agreement pledges, and show differentiated effort across countries: wealthier countries pledge to undertake greater emission reductions with higher costs. The pledges fall in the lower end of the distributions of the social cost of carbon and the cost-minimizing path to limiting warming to 2 °C, suggesting insufficient global ambition in light of leaders’ climate goals. Countries’ marginal abatement costs vary by two orders of magnitude, illustrating that large efficiency gains are available through joint mitigation efforts and/or carbon price coordination. Marginal costs rise almost proportionally with income, but full policy costs reveal more complex regional patterns due to terms of trade effects.</p>",richard richels,Climate-change mitigation,2016.0,10.1038/nclimate3106,Nature Climate Change,Aldy2016,Not available,,Nature,Not available,Economic tools to promote transparency and comparability in the Paris Agreement,d92c835ca77655002e12fde37413751c,http://dx.doi.org/10.1038/nclimate3106
14387,"<p>The Paris Agreement culminates a six-year transition towards an international climate policy architecture based on parties submitting national pledges every five years. An important policy task will be to assess and compare these contributions. We use four integrated assessment models to produce metrics of Paris Agreement pledges, and show differentiated effort across countries: wealthier countries pledge to undertake greater emission reductions with higher costs. The pledges fall in the lower end of the distributions of the social cost of carbon and the cost-minimizing path to limiting warming to 2 °C, suggesting insufficient global ambition in light of leaders’ climate goals. Countries’ marginal abatement costs vary by two orders of magnitude, illustrating that large efficiency gains are available through joint mitigation efforts and/or carbon price coordination. Marginal costs rise almost proportionally with income, but full policy costs reveal more complex regional patterns due to terms of trade effects.</p>",richard richels,Environmental economics,2016.0,10.1038/nclimate3106,Nature Climate Change,Aldy2016,Not available,,Nature,Not available,Economic tools to promote transparency and comparability in the Paris Agreement,d92c835ca77655002e12fde37413751c,http://dx.doi.org/10.1038/nclimate3106
14388,"<p>The Paris Agreement culminates a six-year transition towards an international climate policy architecture based on parties submitting national pledges every five years. An important policy task will be to assess and compare these contributions. We use four integrated assessment models to produce metrics of Paris Agreement pledges, and show differentiated effort across countries: wealthier countries pledge to undertake greater emission reductions with higher costs. The pledges fall in the lower end of the distributions of the social cost of carbon and the cost-minimizing path to limiting warming to 2 °C, suggesting insufficient global ambition in light of leaders’ climate goals. Countries’ marginal abatement costs vary by two orders of magnitude, illustrating that large efficiency gains are available through joint mitigation efforts and/or carbon price coordination. Marginal costs rise almost proportionally with income, but full policy costs reveal more complex regional patterns due to terms of trade effects.</p>",steven rose,Climate-change mitigation,2016.0,10.1038/nclimate3106,Nature Climate Change,Aldy2016,Not available,,Nature,Not available,Economic tools to promote transparency and comparability in the Paris Agreement,d92c835ca77655002e12fde37413751c,http://dx.doi.org/10.1038/nclimate3106
14389,"<p>The Paris Agreement culminates a six-year transition towards an international climate policy architecture based on parties submitting national pledges every five years. An important policy task will be to assess and compare these contributions. We use four integrated assessment models to produce metrics of Paris Agreement pledges, and show differentiated effort across countries: wealthier countries pledge to undertake greater emission reductions with higher costs. The pledges fall in the lower end of the distributions of the social cost of carbon and the cost-minimizing path to limiting warming to 2 °C, suggesting insufficient global ambition in light of leaders’ climate goals. Countries’ marginal abatement costs vary by two orders of magnitude, illustrating that large efficiency gains are available through joint mitigation efforts and/or carbon price coordination. Marginal costs rise almost proportionally with income, but full policy costs reveal more complex regional patterns due to terms of trade effects.</p>",steven rose,Environmental economics,2016.0,10.1038/nclimate3106,Nature Climate Change,Aldy2016,Not available,,Nature,Not available,Economic tools to promote transparency and comparability in the Paris Agreement,d92c835ca77655002e12fde37413751c,http://dx.doi.org/10.1038/nclimate3106
14390,"<p>Without HIV, the tuberculosis (TB) epidemic would now be in decline almost everywhere. However, instead of looking forward to the demise of TB, countries that are badly affected by HIV are struggling against a rising tide of HIV-infected patients with TB. As a consequence, global TB control policies have had to be revised and control of TB now demands increased investment. This paper assesses what is being done to address the issue and what remains to be done.</p>",christopher dye,,2005.0,10.1038/nri1704,Nature Reviews Immunology,Nunn2005,Not available,,Nature,Not available,Tuberculosis control in the era of HIV,c37a29cf47540c62b3ae9184d92f359d,http://dx.doi.org/10.1038/nri1704
14391,"<p>The Paris Agreement culminates a six-year transition towards an international climate policy architecture based on parties submitting national pledges every five years. An important policy task will be to assess and compare these contributions. We use four integrated assessment models to produce metrics of Paris Agreement pledges, and show differentiated effort across countries: wealthier countries pledge to undertake greater emission reductions with higher costs. The pledges fall in the lower end of the distributions of the social cost of carbon and the cost-minimizing path to limiting warming to 2 °C, suggesting insufficient global ambition in light of leaders’ climate goals. Countries’ marginal abatement costs vary by two orders of magnitude, illustrating that large efficiency gains are available through joint mitigation efforts and/or carbon price coordination. Marginal costs rise almost proportionally with income, but full policy costs reveal more complex regional patterns due to terms of trade effects.</p>",fuminori sano,Climate-change mitigation,2016.0,10.1038/nclimate3106,Nature Climate Change,Aldy2016,Not available,,Nature,Not available,Economic tools to promote transparency and comparability in the Paris Agreement,d92c835ca77655002e12fde37413751c,http://dx.doi.org/10.1038/nclimate3106
14392,"<p>The Paris Agreement culminates a six-year transition towards an international climate policy architecture based on parties submitting national pledges every five years. An important policy task will be to assess and compare these contributions. We use four integrated assessment models to produce metrics of Paris Agreement pledges, and show differentiated effort across countries: wealthier countries pledge to undertake greater emission reductions with higher costs. The pledges fall in the lower end of the distributions of the social cost of carbon and the cost-minimizing path to limiting warming to 2 °C, suggesting insufficient global ambition in light of leaders’ climate goals. Countries’ marginal abatement costs vary by two orders of magnitude, illustrating that large efficiency gains are available through joint mitigation efforts and/or carbon price coordination. Marginal costs rise almost proportionally with income, but full policy costs reveal more complex regional patterns due to terms of trade effects.</p>",fuminori sano,Environmental economics,2016.0,10.1038/nclimate3106,Nature Climate Change,Aldy2016,Not available,,Nature,Not available,Economic tools to promote transparency and comparability in the Paris Agreement,d92c835ca77655002e12fde37413751c,http://dx.doi.org/10.1038/nclimate3106
14393,"<p>In academic circles, laissez-faire is perceived as a largely discredited idea. Yet an element of the argument—that only unencumbered markets provide societies with a truly neutral means of allocating resources—has, despite years of critique, remained intact. I argue (a) that this element is conceptually false, (b) that it is so for reasons previous critiques have overlooked, and (c) that this oversight explains why laissez-faire, in spite of its perceived discrediting, has maintained a persistent influence over debates about distributive justice.</p>",peter lindsay,,2005.0,10.1057/palgrave.polity.2300015,Polity,Lindsay2005,Not available,,Nature,Not available,Exposing the Invisible Hand: The Roots of Laissez-faire's Hidden Influence<tlnref><sup>*</sup></tlnref>,f530b0d39963df7960aa297d1e2492f4,http://dx.doi.org/10.1057/palgrave.polity.2300015
14394,"<p>When it comes to the impact of institutions such as electoral systems, parliamentary or presidential systems and executive–legislature relations, political science has predominately been preoccupied with their political effects, such as whether they lead to two-party or multi-party systems and whether stable governments result. What has been less discussed and researched are the policy implications of different electoral systems. Do they lead to more economic growth? Does Proportional Representation lead to higher budget deficits? Do majoritarian systems lead to more or less political violence? The shortage of research analysing these questions is surprising. This article critically outlines the research to date, summarises the main results and points to methodological problems in the literature before it outlines a framework for future research analysing how the choice of electoral system affects policy output. The main recommendation is that, before trying to connect policy outputs to broad labels such as ‘Proportional Representation’, which can cover significantly different systems, one should investigate the connection of policy outputs to intervening variables such as the effective number of parties and the mean duration of cabinets.</p>",rein taagepera,,2011.0,10.1057/eps.2011.35,European Political Science,Taagepera2011,Not available,,Nature,Not available,"Who Gets What, When, How – Through Which Electoral System?",1ee1ed9eb41e0e04f2680e2f78803241,http://dx.doi.org/10.1057/eps.2011.35
14395,"<p>We consider a Markovian queueing system with <i>N</i> heterogeneous service facilities, each of which has multiple servers available, linear holding costs, a fixed value of service and a first-come-first-serve queue discipline. Customers arriving in the system can be either rejected or sent to one of the <i>N</i> facilities. Two different types of control policies are considered, which we refer to as ‘selfishly optimal’ and ‘socially optimal’. We prove the equivalence of two different Markov Decision Process formulations, and then show that classical <i>M</i>/<i>M</i>/1 queue results from the early literature on behavioural queueing theory can be generalized to multiple dimensions in an elegant way. In particular, the state space of the continuous-time Markov process induced by a socially optimal policy is contained within that of the selfishly optimal policy. We also show that this result holds when customers are divided into an arbitrary number of heterogeneous classes, provided that the service rates remain non-discriminatory.</p>",janet williams,,2015.0,10.1057/jors.2015.98,Journal of the Operational Research Society,Shone2015,Not available,,Nature,Not available,Containment of socially optimal policies in multiple-facility Markovian queueing systems,7e14b5751602501225481ed2de4f9fb3,http://dx.doi.org/10.1057/jors.2015.98
14396,"<p>Without HIV, the tuberculosis (TB) epidemic would now be in decline almost everywhere. However, instead of looking forward to the demise of TB, countries that are badly affected by HIV are struggling against a rising tide of HIV-infected patients with TB. As a consequence, global TB control policies have had to be revised and control of TB now demands increased investment. This paper assesses what is being done to address the issue and what remains to be done.</p>",gijs elzinga,,2005.0,10.1038/nri1704,Nature Reviews Immunology,Nunn2005,Not available,,Nature,Not available,Tuberculosis control in the era of HIV,c37a29cf47540c62b3ae9184d92f359d,http://dx.doi.org/10.1038/nri1704
14397,"<p>When it comes to the impact of institutions such as electoral systems, parliamentary or presidential systems and executive–legislature relations, political science has predominately been preoccupied with their political effects, such as whether they lead to two-party or multi-party systems and whether stable governments result. What has been less discussed and researched are the policy implications of different electoral systems. Do they lead to more economic growth? Does Proportional Representation lead to higher budget deficits? Do majoritarian systems lead to more or less political violence? The shortage of research analysing these questions is surprising. This article critically outlines the research to date, summarises the main results and points to methodological problems in the literature before it outlines a framework for future research analysing how the choice of electoral system affects policy output. The main recommendation is that, before trying to connect policy outputs to broad labels such as ‘Proportional Representation’, which can cover significantly different systems, one should investigate the connection of policy outputs to intervening variables such as the effective number of parties and the mean duration of cabinets.</p>",matt qvortrup,,2011.0,10.1057/eps.2011.35,European Political Science,Taagepera2011,Not available,,Nature,Not available,"Who Gets What, When, How – Through Which Electoral System?",1ee1ed9eb41e0e04f2680e2f78803241,http://dx.doi.org/10.1057/eps.2011.35
14398,"<p>This paper describes a taxi scheduling system, which aims to improve the overall efficiency of the system, both from the perspective of the drivers and the customers. This is of particular relevance to Chinese cities, where hailing a taxi on the street is by far the most common way in which taxis are requested, since the majority of taxi drivers operate independently, rather than working for a company. The mobile phone and Global Positioning System-based taxi scheduling system, which is described in this paper, aims to provide a decision support system for taxi drivers and facilitates direct information exchange between taxi drivers and passengers, while allowing drivers to remain independent. The taxi scheduling problem is considered to be a non-cooperative game between taxi drivers and a description of this problem is given. We adopt an efficient algorithm to discover a Nash equilibrium, such that each taxi driver and passenger cannot benefit from changing their assigned partner. Two computational examples are given to illustrate the effectiveness of the approach.</p>",ruibin bai,,2013.0,10.1057/jors.2013.96,Journal of the Operational Research Society,Bai2013,Not available,,Nature,Not available,A novel approach to independent taxi scheduling problem based on stable matching,e7476d8ce5ef478ef765fef7b11ec587,http://dx.doi.org/10.1057/jors.2013.96
14399,"<p>This paper describes a taxi scheduling system, which aims to improve the overall efficiency of the system, both from the perspective of the drivers and the customers. This is of particular relevance to Chinese cities, where hailing a taxi on the street is by far the most common way in which taxis are requested, since the majority of taxi drivers operate independently, rather than working for a company. The mobile phone and Global Positioning System-based taxi scheduling system, which is described in this paper, aims to provide a decision support system for taxi drivers and facilitates direct information exchange between taxi drivers and passengers, while allowing drivers to remain independent. The taxi scheduling problem is considered to be a non-cooperative game between taxi drivers and a description of this problem is given. We adopt an efficient algorithm to discover a Nash equilibrium, such that each taxi driver and passenger cannot benefit from changing their assigned partner. Two computational examples are given to illustrate the effectiveness of the approach.</p>",jiawei li,,2013.0,10.1057/jors.2013.96,Journal of the Operational Research Society,Bai2013,Not available,,Nature,Not available,A novel approach to independent taxi scheduling problem based on stable matching,e7476d8ce5ef478ef765fef7b11ec587,http://dx.doi.org/10.1057/jors.2013.96
14400,"<p>This paper describes a taxi scheduling system, which aims to improve the overall efficiency of the system, both from the perspective of the drivers and the customers. This is of particular relevance to Chinese cities, where hailing a taxi on the street is by far the most common way in which taxis are requested, since the majority of taxi drivers operate independently, rather than working for a company. The mobile phone and Global Positioning System-based taxi scheduling system, which is described in this paper, aims to provide a decision support system for taxi drivers and facilitates direct information exchange between taxi drivers and passengers, while allowing drivers to remain independent. The taxi scheduling problem is considered to be a non-cooperative game between taxi drivers and a description of this problem is given. We adopt an efficient algorithm to discover a Nash equilibrium, such that each taxi driver and passenger cannot benefit from changing their assigned partner. Two computational examples are given to illustrate the effectiveness of the approach.</p>",jason atkin,,2013.0,10.1057/jors.2013.96,Journal of the Operational Research Society,Bai2013,Not available,,Nature,Not available,A novel approach to independent taxi scheduling problem based on stable matching,e7476d8ce5ef478ef765fef7b11ec587,http://dx.doi.org/10.1057/jors.2013.96
14401,"<p>This paper describes a taxi scheduling system, which aims to improve the overall efficiency of the system, both from the perspective of the drivers and the customers. This is of particular relevance to Chinese cities, where hailing a taxi on the street is by far the most common way in which taxis are requested, since the majority of taxi drivers operate independently, rather than working for a company. The mobile phone and Global Positioning System-based taxi scheduling system, which is described in this paper, aims to provide a decision support system for taxi drivers and facilitates direct information exchange between taxi drivers and passengers, while allowing drivers to remain independent. The taxi scheduling problem is considered to be a non-cooperative game between taxi drivers and a description of this problem is given. We adopt an efficient algorithm to discover a Nash equilibrium, such that each taxi driver and passenger cannot benefit from changing their assigned partner. Two computational examples are given to illustrate the effectiveness of the approach.</p>",graham kendall,,2013.0,10.1057/jors.2013.96,Journal of the Operational Research Society,Bai2013,Not available,,Nature,Not available,A novel approach to independent taxi scheduling problem based on stable matching,e7476d8ce5ef478ef765fef7b11ec587,http://dx.doi.org/10.1057/jors.2013.96
14402,"<p>Reagan's rhetoric and actions in the arms race triggered considerable opposition, which was necessary to establish a counter-discourse in particular through the peace movements in the West, which then impacted upon the discussions in Moscow. It enabled Gorbachev to overcome his considerable domestic opposition and to make the necessary concessions, which started to bring the cold war to an end. In this sense, the peace movements won the cold war, too. The end of the cold war was as much a discursive struggle over ideas about international order and the right mix of deterrence and détente as the East–West conflict itself. It is a matter of good fortune that the cold war had a relatively happy ending and that Europe was reunited. Claiming victory for one side or the other seems to be beside the point, even 20 years later.</p>",thomas risse,,2011.0,10.1057/ip.2011.20,International Politics,Risse2011,Not available,,Nature,Not available,"Ideas, discourse, power and the end of the cold war: 20 years on",3d2e33464d97111febf231a5543cd19f,http://dx.doi.org/10.1057/ip.2011.20
14403,"<p>Without HIV, the tuberculosis (TB) epidemic would now be in decline almost everywhere. However, instead of looking forward to the demise of TB, countries that are badly affected by HIV are struggling against a rising tide of HIV-infected patients with TB. As a consequence, global TB control policies have had to be revised and control of TB now demands increased investment. This paper assesses what is being done to address the issue and what remains to be done.</p>",mario raviglione,,2005.0,10.1038/nri1704,Nature Reviews Immunology,Nunn2005,Not available,,Nature,Not available,Tuberculosis control in the era of HIV,c37a29cf47540c62b3ae9184d92f359d,http://dx.doi.org/10.1038/nri1704
14404,<p>Cho Khong describes a Royal Dutch Shell scenarios exercise in Nigeria in the late 1990s. He argues that the exercise created the space for an important dialogue at a time when hope and spirits were low. Vision 2010 illustrates how the private sector could work together to support a country undergoing major social and political transition.</p>,cho khong,,2004.0,10.1057/palgrave.development.1100090,Development,Khong2004,Not available,,Nature,Not available,Nigeria: Private sector creates a public space,afc5dc6e991e45006bd99c87bbb28690,http://dx.doi.org/10.1057/palgrave.development.1100090
14405,"<p>Does there exist a genuine threat to the continuation of a broadly liberal international (and domestic) order, driven by the re-emergence of religious and secular fundamentalisms? This article assesses this issue in the context of first the rise of territorial power and then its fate in a period of globalization and the revival of religious intolerance. The twin concepts of sovereign-power and bio-power are deployed to investigate the emergence of territorial engineering in the 17th century. A key feature of modern fundamentalisms is that they promote and trade on the deterritorialization of social, political, cultural and economic activity. It is argued that this is a manifestation of a new form of ‘spirited martial power’. The risks associated with these developments should not be over-exaggerated but they exist nonetheless. If this is the case, the problem becomes one of how to re-territorialize the activities and disputes engendered by this reappearance and re-emergence of spirited martial power in the international system, with all its attendant links to religious fundamentalisms. Here the argument is that this requires a re-examination of the nature of international borders, and indeed a re-emphasis on their role, not just in respect to containing disorder and restoring the capacity for governance, but also as a way of re-configuring international toleration and of righting a wrong.</p>",grahame thompson,,2007.0,10.1057/palgrave.ip.8800203,International Politics,Thompson2007,Not available,,Nature,Not available,The Fate of Territorial Engineering: Mechanisms of Territorial Power and Post-Liberal Forms of International Governance,610a9e18b2184c433df7ec71961c3099,http://dx.doi.org/10.1057/palgrave.ip.8800203
14406,"<p>Critical rationalism is the philosophy developed by Karl Popper during the middle of the 20th century. Popper's approach is based on the naturalistic idea that society has developed through a process of solving problems using trial and error. The natural and social sciences have been born out of such problem solving and progressed by subjecting potential theories to vigorous testing and criticism. Falsified theories are rejected. Popper calls for a society which is conducive to such problem solving, a society which permits bold theorizing followed by unfettered criticism, a society in which there is a genuine possibility of change in the light of criticism: an <i>open society</i>. Popper's ideas provide a doorway for accessing philosophical ideas and debates relevant to OR. For some such as Boothroyd it has proved inspirational, for others such as Ulrich it has provided a critical point of departure.</p>",r ormerod,,2008.0,10.1057/palgrave.jors.2602573,Journal of the Operational Research Society,Ormerod2008,Not available,,Nature,Not available,The history and ideas of critical rationalism: the philosophy of Karl Popper and its implications for OR,f5f41e361e68ad687c5b4d05d08dad25,http://dx.doi.org/10.1057/palgrave.jors.2602573
14407,"<p>This paper assesses American neoconservative policy prescriptions for democratizing political Islam and considers the sources of the neoconservative understanding of the Arab Muslim world. Neoconservative analyses of the Middle East are almost exclusively normative, arguing what US policy toward the region <i>should</i> be. Their aims are ambitious and inherently controversial. The paper examines what various neoconservatives have said and written about Islam and its democratic potential. The paper concerns itself with the neoconservative conceptualization of Middle East politics. The paper argues that presently only American neoconservatism, despite its variations, and despite some obvious flaws, offers tenable prescriptions for regime destabilization and an attendant political liberalization of Arab politics.</p>",timothy lynch,,2008.0,10.1057/palgrave.ip.8800227,International Politics,Lynch2008,Not available,,Nature,Not available,<i>Kristol Balls</i>: Neoconservative Visions of Islam and the Middle East,33705afe1b3cbe4afec2312d40c11d96,http://dx.doi.org/10.1057/palgrave.ip.8800227
14408,"<p>The Conservatives appear to have established a clear and consistent opinion poll lead over the Labour government. Some would suggest that this change of fortunes is connected to the ‘modernization’ undertaken by David Cameron. This article examines the extent to which the Conservative Party can be said to have changed in a manner that political scientists might regard as significant. From the comparative literature on party change, it derives five dimensions and associated indicators of change; it then proceeds to measure the Conservative Party against them. It finds that the extent of change — both actual and perceived — is easily overstated, partly because ‘Team Cameron’ has always had to tread carefully and particularly given significant adjustments made to the Party's course after the difficult summer of 2007. When it comes to the relationship between change and success, only a modicum of the former may be needed to achieve the latter given that elections are as much lost by governments as they are won by oppositions.</p>",tim bale,,2008.0,10.1057/bp.2008.7,British Politics,Bale2008,Not available,,Nature,Not available,‘A Bit Less Bunny-Hugging and a Bit More Bunny-Boiling’? Qualifying Conservative Party Change under David Cameron,fb4af8b360f61052605677cd500c7fb3,http://dx.doi.org/10.1057/bp.2008.7
14409,"<p>Analysts commonly view emotion as irrational, as part of human nature, and therefore as part of a first-image approach to politics. However, emotion is necessary to rationality and first-image and human nature arguments are not synonymous. A first-image explanation can be independent of human nature, and a human nature argument can be used at different levels-of-analysis. This essay first explores the relationship between emotion and rationality and breaks the literature on emotion down into four groups: as epiphenomenal, as a source of irrationality, as a tool for savvy strategic actors, and as a necessary aspect of rationality. After developing different approaches to emotion, the essay explores three uses of emotion at different levels-of-analysis.</p>",jonathan mercer,,2006.0,10.1057/palgrave.jird.1800091,Journal of International Relations and Development,Mercer2006,Not available,,Nature,Not available,Human nature and the first image: emotion in international politics,5998992436371ce765b6419c81057624,http://dx.doi.org/10.1057/palgrave.jird.1800091
14410,"<p>Against the easy presupposition that such a thing as ‘democratic taxation’ not only exists but is also practicable, this paper points to the dilemma posed by what I call ‘quantifiable action.’ The essay develops an approach to theorizing the place of taxation in political theory that counters trends in fiscal sociology, political science, and liberal theory by highlighting how taxation presumably violates the requirement that self-government includes an absence of instrumental rationality on the part of democratic citizens. For this reason, taxation presents a persistent problem for any concept of self-government, and may usefully be regarded as a technology of the self, conventional with democracy but at most ambiguous in its capability to be genuinely democratic, both theoretically and practically.</p>",mindy peden,,2008.0,10.1057/cpt.2008.14,Contemporary Political Theory,Peden2008,Not available,,Nature,Not available,‘Democratic Taxation’ and Quantifiable Action: Scientizing Dilemmas,d5d1f6c0043500a2724c909b7d715f05,http://dx.doi.org/10.1057/cpt.2008.14
14411,"<p>The International Campaign to Ban Landmines (ICBL) is a global network of organisations working to eradicate ‘anti-personnel’ mines. It was founded by six NGOs (Handicap International, Human Rights Watch, Medico International, Mines Advisory Group, Physicians for Human Rights and Vietnam Veterans of America Foundation), which came together in October 1992 to discuss the necessity of coordinating initiatives and calls for a ban on ‘anti-personnel’ landmines.</p>",javier villacampa,,2008.0,10.1057/eps.2008.30,European Political Science,Villacampa2008,Not available,,Nature,Not available,"The Mine Ban Treaty, New Diplomacy and Human Security Ten Years Later",e830b12b2169634d94d2c2f4c888b810,http://dx.doi.org/10.1057/eps.2008.30
14412,"<p>The compensation to victims of nuclear accidents is based on a Paris (OECD) and a Vienna (UN) convention. A problem with the system is that a strictly liable, but insolvent or uninsured plant owner leaves victims without compensation. In this paper, it is argued that a system could be better organised by, for example, the European Union (EU). A State that permits a nuclear reactor on its territory should be strictly liable. Benefits are: (i) States are able to compensate large damages; (ii) theory suggests that stepwise modified risk-sharing could be made beneficial for risk-averse States; (iii) the EU can enforce sharing agreements by Member States; (iv) a State can limit its financial burden by redressing some liability to the domestic nuclear industry. The incentive created hereby, as well as regulations on location and safety may prevent accidents. A European nuclear accident pool will have a collective interest in accident prevention.</p>",goran skogh,,2008.0,10.1057/gpp.2008.8,The Geneva Papers on Risk and Insurance Issues and Practice,Skogh2008,Not available,,Nature,Not available,A European Nuclear Accident Pool<tlnref><sup>*</sup></tlnref>,055c4886c063b1c99b73e05f0eac0942,http://dx.doi.org/10.1057/gpp.2008.8
14413,"<p>The vulnerability to real-life networks against small initial attacks has been one of outstanding challenges in the study of interrelated networks. We study cascading failures in two interrelated networks <b><i>S</i></b> and <b><i>B</i></b> composed from dependency chains and connectivity links respectively. This work proposes a realistic model for cascading failures based on the redistribution of traffic flow. We study the Barabási-Albert networks (<b><i>BA</i></b>) and Erdős-Rényi graphs (<b><i>ER</i></b>) with such structure, and found that the efficiency sharply decreases with increasing percentages of the dependency nodes for removing a node randomly. Furthermore, we study the robustness of interrelated traffic networks, especially the subway and bus network in Beijing. By analyzing different attacking strategies, we uncover that the efficiency of the city traffic system has a non-equilibrium phase transition at low capacity of the networks. This explains why the pressure of the traffic overload is relaxed by singly increasing the number of small buses during rush hours. We also found that the increment of some buses may release traffic jam caused by removing a node of the bus network randomly if the damage is limited. However, the efficiencies to transfer people flow will sharper increase when the capacity of the subway network <b><i>α<sub>S</sub></i> > <i>α</i><sub>0</sub></b>.</p>",zhen su,Complex networks,2014.0,10.1038/srep05413,Scientific Reports,Su2014,Not available,,Nature,Not available,Robustness of Interrelated Traffic Networks to Cascading Failures,4840ca15ebd58b9a2e9f7ee719c39054,http://dx.doi.org/10.1038/srep05413
14414,"<p>This article develops a new conceptual framework of ‘moral power’ by arguing that the ‘civilian’/‘normative’ power Europe paradigms are insufficient for understanding the essence of the conflict resolution policy of the European Union (EU) in the South Caucasus. Analysing the conflicts of Abkhazia, South Ossetia and Nagorno-Karabakh, the study reveals that until the August 2008 war, the EU was an incoherent actor in terms of the interplay among its institutions and member-states. The EU's policy has been devoid of a long-term peace-focused strategy, making it inconsequential; as a result, the EU has merely dealt with, rather than managed, the conflicts. Its rhetoric has been inconsistent with practice. Often the EU has subordinated its values to material and power-related interests. Moreover, the EU has hardly been normatively stable in its approach to the Nagorno-Karabakh conflict. Bypassing inclusiveness until the launch of the Geneva talks pertaining to the Abkhazian and South Ossetian conflicts, the EU has not enjoyed much legitimacy by the <i>de facto</i> states. Whereas the EU has largely failed to resolve the South Caucasian conflicts, it has achieved partial success by putting a halt to the 2008 hostilities between Russia and Georgia. Overall, having faltered as a ‘civilian’/‘normative’ power it still has to fare as a ‘moral power’.</p>",syuzanna vasilyan,,2013.0,10.1057/jird.2013.10,Journal of International Relations and Development,Vasilyan2013,Not available,,Nature,Not available,‘Moral power’ as objectification of the ‘civilian’/‘normative’ ‘EUlogy’: the European Union as a conflict-dealer in the South Caucasus,5e4f4600207472289e908a5637880e96,http://dx.doi.org/10.1057/jird.2013.10
14415,"<p>Many of the debates and controversies over the causes and cures of financial-economic crisis of 2007–2008 that continues to plague the world economy in 2010 echo ideas put forth in the 1930s by John Maynard Keynes, Friedrich von Hayek, and Joseph Schumpeter. As capitalism reconstituted itself in the aftermath of the Second World War it was their ideas which molded institutions and attitudes.</p>",duncan foley,,2010.0,10.1057/eej.2010.20,Eastern Economic Journal,Foley2010,Not available,,Nature,Not available,"Lineages of Crisis Economics from the 1930s: Keynes, Hayek, and Schumpeter",f3cd4b7e6bdef6f61be0e88218ca9328,http://dx.doi.org/10.1057/eej.2010.20
14416,"<p>The vulnerability to real-life networks against small initial attacks has been one of outstanding challenges in the study of interrelated networks. We study cascading failures in two interrelated networks <b><i>S</i></b> and <b><i>B</i></b> composed from dependency chains and connectivity links respectively. This work proposes a realistic model for cascading failures based on the redistribution of traffic flow. We study the Barabási-Albert networks (<b><i>BA</i></b>) and Erdős-Rényi graphs (<b><i>ER</i></b>) with such structure, and found that the efficiency sharply decreases with increasing percentages of the dependency nodes for removing a node randomly. Furthermore, we study the robustness of interrelated traffic networks, especially the subway and bus network in Beijing. By analyzing different attacking strategies, we uncover that the efficiency of the city traffic system has a non-equilibrium phase transition at low capacity of the networks. This explains why the pressure of the traffic overload is relaxed by singly increasing the number of small buses during rush hours. We also found that the increment of some buses may release traffic jam caused by removing a node of the bus network randomly if the damage is limited. However, the efficiencies to transfer people flow will sharper increase when the capacity of the subway network <b><i>α<sub>S</sub></i> > <i>α</i><sub>0</sub></b>.</p>",zhen su,Nonlinear phenomena,2014.0,10.1038/srep05413,Scientific Reports,Su2014,Not available,,Nature,Not available,Robustness of Interrelated Traffic Networks to Cascading Failures,4840ca15ebd58b9a2e9f7ee719c39054,http://dx.doi.org/10.1038/srep05413
14417,"<p>The explanatory power of structural realism in the post-Cold War world has been hotly debated in the international relations literature. Critics pronounce the death of structural realism in this new world order, whereas proponents maintain that this approach still manages to shed a great deal of light on international affairs, even after the end of the Cold War. In this article, the two main branches of structural realism, Kenneth Waltz’s defensive realism and John Mearsheimer’s offensive realism, are challenged on their own terms to assess whether they are still useful in explaining world politics in the post-Cold War era. The results indicate that neither Waltz’s defensive realism nor Mearsheimer’s offensive realism can account for international politics under hegemony or unipolarity, and that their theories have consequently had no explanatory power since the end of the Cold War.</p>",arash pashakhanlou,,2014.0,10.1057/ip.2014.16,International Politics,Pashakhanlou2014,Not available,,Nature,Not available,"‘Waltz, Mearsheimer and the post-Cold War world: The rise of America and the fall of structural realism’",0a0db32fab145044c00e8317e13b56a2,http://dx.doi.org/10.1057/ip.2014.16
14418,"<p>In 1944, two seminal works of political and social theory appeared: F.A. Hayek’s <i>The Road to Serfdom</i> and Karl Polanyi’s <i>The Great Transformation</i>. Both works focused on society’s spontaneous resistance to the “marketization” of life. Yet, the authors arrived at opposite normative conclusions. This article attributes the normative distance to a methodological clash over the role and limits of normative theorizing in the concrete and sometimes uncooperative world of politics. This clash, in turn, illuminates recent debates about “ideal” and “non-ideal” theory, and suggests limits to the applicability of the former.</p>",peter lindsay,,2015.0,10.1057/pol.2015.14,Polity,Lindsay2015,Not available,,Nature,Not available,"Polanyi, Hayek, and the Impossibility of Libertarian Ideal Theory",009c71b165506a71831babad3377f04f,http://dx.doi.org/10.1057/pol.2015.14
14419,"<p>Non-governmental organisation (NGO) activism on the arms trade is emblematic of the significant and emancipatory role attributed to civil society in post-Cold War international politics. Discussions of NGOs’ efforts are marked by a distinctively liberal understanding of civil society as an increasingly global sphere separate from the state and market, promoting progressive and non-violent social relations. However, there are significant conceptual and empirical problems with these claims, which I illustrate using examples from contemporary NGO activism on the international production of and trade in conventional weaponry. First, liberal accounts underplay the mutual dependence between the state, market and civil society. NGO agency is both constrained and enabled by its historical, structural grounding. Second, I argue for a more ambivalent understanding of NGOs’ progressive political value. While some NGOs may play a role in counter-hegemonic struggle, overall they are more likely to contribute to hegemonic social formations. Third, liberal accounts of a global civil society inadequately capture the reproduction of hierarchy in international relations, downplaying ongoing, systematic patterns of North-South asymmetry. Fourth, the emphasis on the non-violent nature of global civil society sidelines the violence of capitalism and the state system, and serves as a means of disciplining dissent and activism.</p>",anna stavrianakis,,2011.0,10.1057/jird.2011.22,Journal of International Relations and Development,Stavrianakis2011,Not available,,Nature,Not available,"Missing the target: NGOs, global civil society and the arms trade",040a50de2721757a00518dc0456fd568,http://dx.doi.org/10.1057/jird.2011.22
14420,"<p>The European Council has instigated an energy policy for Europe, largely in order to address external challenges and to ensure a more reliable flow of hydrocarbons into the European Union. This article seeks to explain why member-states have apparently decided to delegate a number of significant responsibilities to the European Commission within this new energy framework. Evaluating the explanatory power of Liberal Intergovernmentalism and Historical Institutionalism, it is argued that the Commission has played an active role in expanding its initially vague and modest energy related powers to a degree originally not envisaged by member-states. Beyond seizing on external crises, it has utilized path-dependent dynamics to capture authorities and to establish itself as a significant international player in the energy field. Evolving informal rules and Commission practices have significantly paved the way for formal assignments. They have gained credibility, and were eventually considered acceptable from a member-state perspective.</p>",sebastian mayer,,2008.0,10.1057/jird.2008.12,Journal of International Relations and Development,Mayer2008,Not available,,Nature,Not available,Path dependence and Commission activism in the evolution of the European Union's external energy policy,38a703f762145a1cc56f57ab075a0ad4,http://dx.doi.org/10.1057/jird.2008.12
14421,"<p>This paper addresses two related puzzles confronting students of regional and international integration: Why do states willingly pool and delegate sovereignty within international institutions? What accounts for the timing and content of regional integration agreements? Most theories of integration suggest that states integrate in order to solve problems of incomplete information and reduce transaction costs and other barriers to economic growth. In contrast, I argue that integration can serve to establish a credible commitment that rules out the risk of future conflict among states of unequal power. Specifically, I suggest that integration presents an alternative to preventive war as a means to preclude a rising revisionist power from establishing a regional hegemony. The implication is that it is not countries that enjoy stable and peaceful relations that are most likely to pursue integration, but rather countries that find themselves caught in a regional security dilemma, which they hope to break out of by means of institutionalized cooperation. I evaluate this proposition against evidence from two historical cases of regional integration: the German Zollverein and the European Communities.</p>",mette eilstrup-sangiovanni,,2008.0,10.1057/palgrave.cep.6110122,Comparative European Politics,Eilstrup-Sangiovanni2008,Not available,,Nature,Not available,Uneven Power and the Pursuit of Peace: How Regional Power Transitions Motivate Integration,c3d7a5803d31f151eed4aa1a5a19425f,http://dx.doi.org/10.1057/palgrave.cep.6110122
14422,"<p>Constructivism is often identified as the legitimate occupant of the middle ground between rationalism and reflectivism that emerged from the Third Debate in international relations (IR) theory. Indeed, the rationalist–constructivist debate is already being framed as the next dominant debate with the IR community. This paper evaluates the bridge-building project as initiated by Alexander Wendt, and takes issue with the via media as proposed by the so-called conventional constructivists. It is claimed that the rationalist–constructivist debate has been limited to a discussion of ontology, which has brought about a contradiction between ontology and epistemology. Returning to the pressing epistemological issues that were put on the table by reflectivist scholars, this article refocuses the current debate by taking up the Kuhnian link between substance and science. It elaborates a view of science as a communal practice built on intersubjective conventions and argumentative procedures. This leads to an alternative conception of the middle ground as a communicative space.</p>",tanja aalberts,,2008.0,10.1057/ip.2008.26,International Politics,Aalberts2008,Not available,,Nature,Not available,From Wendt to Kuhn: Reviving the ‘Third Debate’ in International Relations,966a5d3183b3040fa0093fc0eab8d70f,http://dx.doi.org/10.1057/ip.2008.26
14423,"<p>The vulnerability to real-life networks against small initial attacks has been one of outstanding challenges in the study of interrelated networks. We study cascading failures in two interrelated networks <b><i>S</i></b> and <b><i>B</i></b> composed from dependency chains and connectivity links respectively. This work proposes a realistic model for cascading failures based on the redistribution of traffic flow. We study the Barabási-Albert networks (<b><i>BA</i></b>) and Erdős-Rényi graphs (<b><i>ER</i></b>) with such structure, and found that the efficiency sharply decreases with increasing percentages of the dependency nodes for removing a node randomly. Furthermore, we study the robustness of interrelated traffic networks, especially the subway and bus network in Beijing. By analyzing different attacking strategies, we uncover that the efficiency of the city traffic system has a non-equilibrium phase transition at low capacity of the networks. This explains why the pressure of the traffic overload is relaxed by singly increasing the number of small buses during rush hours. We also found that the increment of some buses may release traffic jam caused by removing a node of the bus network randomly if the damage is limited. However, the efficiencies to transfer people flow will sharper increase when the capacity of the subway network <b><i>α<sub>S</sub></i> > <i>α</i><sub>0</sub></b>.</p>",zhen su,Statistical physics,2014.0,10.1038/srep05413,Scientific Reports,Su2014,Not available,,Nature,Not available,Robustness of Interrelated Traffic Networks to Cascading Failures,4840ca15ebd58b9a2e9f7ee719c39054,http://dx.doi.org/10.1038/srep05413
14424,"<p>Constructivism is often identified as the legitimate occupant of the middle ground between rationalism and reflectivism that emerged from the Third Debate in international relations (IR) theory. Indeed, the rationalist–constructivist debate is already being framed as the next dominant debate with the IR community. This paper evaluates the bridge-building project as initiated by Alexander Wendt, and takes issue with the via media as proposed by the so-called conventional constructivists. It is claimed that the rationalist–constructivist debate has been limited to a discussion of ontology, which has brought about a contradiction between ontology and epistemology. Returning to the pressing epistemological issues that were put on the table by reflectivist scholars, this article refocuses the current debate by taking up the Kuhnian link between substance and science. It elaborates a view of science as a communal practice built on intersubjective conventions and argumentative procedures. This leads to an alternative conception of the middle ground as a communicative space.</p>",rens munster,,2008.0,10.1057/ip.2008.26,International Politics,Aalberts2008,Not available,,Nature,Not available,From Wendt to Kuhn: Reviving the ‘Third Debate’ in International Relations,966a5d3183b3040fa0093fc0eab8d70f,http://dx.doi.org/10.1057/ip.2008.26
14425,"<p>In terms of understanding the state, British political elites have traditionally drawn from the framework of the Westminster model which offers a ‘hard’ notion of Westphalian sovereignty. Over the last few decades, this notion of indivisible sovereignty has become increasingly unsustainable as the nature of both domestic and international politics has been transformed. This article argues that the recent Labour Government, unlike its Conservative predecessors, was able to respond to these changes by redefining and developing its conception of sovereignty to suit the material reality of the twenty-first century. Their approach to sovereignty moved beyond the traditional interpretation offered by the Westminster model. They appealed to more multi-dimensional and nuanced understandings which invite parallels from within Labour's own ideological tradition with the pluralist and guild socialist conceptions of sovereignty.</p>",david richards,,2010.0,10.1057/bp.2010.7,British Politics,Richards2010,Not available,,Nature,Not available,"Back to the future: New Labour, sovereignty and the plurality of the party's ideological tradition",a25f637e05861a5c1a3d6fa0f4b55c1f,http://dx.doi.org/10.1057/bp.2010.7
14426,"<p>In terms of understanding the state, British political elites have traditionally drawn from the framework of the Westminster model which offers a ‘hard’ notion of Westphalian sovereignty. Over the last few decades, this notion of indivisible sovereignty has become increasingly unsustainable as the nature of both domestic and international politics has been transformed. This article argues that the recent Labour Government, unlike its Conservative predecessors, was able to respond to these changes by redefining and developing its conception of sovereignty to suit the material reality of the twenty-first century. Their approach to sovereignty moved beyond the traditional interpretation offered by the Westminster model. They appealed to more multi-dimensional and nuanced understandings which invite parallels from within Labour's own ideological tradition with the pluralist and guild socialist conceptions of sovereignty.</p>",martin smith,,2010.0,10.1057/bp.2010.7,British Politics,Richards2010,Not available,,Nature,Not available,"Back to the future: New Labour, sovereignty and the plurality of the party's ideological tradition",a25f637e05861a5c1a3d6fa0f4b55c1f,http://dx.doi.org/10.1057/bp.2010.7
14427,"<p>The orientation of Russian domestic and foreign policies has steadied since the advent of president Putin in 2000, following upon the erratic shifts of his predecessor Yeltsin in the crisis ridden 1990s. His domestic policies reasserted centralised Kremlin rule, put a clique of security service ( siloviki ) acquaintances from St. Petersburg into power, suppressed the opposition, press freedom, regional self-government, civic society and an independent judiciary, and moved the economic system from oligarchial capitalism back to state monopoly capitalism.</p>",albrecht rothacher,,2008.0,10.1057/eps.2008.44,European Political Science,Rothacher2008,Not available,,Nature,Not available,Putin's Russia: Spy Rule and Post-Soviet Transformation,1526f67644c8921819735355b0ad51d5,http://dx.doi.org/10.1057/eps.2008.44
14428,"<p>Some theorists have argued recently that Berlinian value pluralism points not to liberalism, as Berlin supposed, but, in effect, to some form of communitarianism. To what extent is this true, and, to the extent that it is true, what kind of communitarianism fits best with the pluralist outlook? I argue that pluralists should acknowledge community as an important source of value and as a substantial value in itself, but they should also be prepared to question traditions and to respect values other than community. In particular, pluralism points to personal autonomy as playing a special role when we must choose among incommensurable goods in conflict. Consequently, the pluralist outlook is at odds with conservative communitarianisms that tend to place existing traditions beyond question, and with radical variants of communitarianism, such as Marxism and classical anarchism, which look forward to future communities in which the need to cope with hard public choices has largely been eliminated. Rather, Berlinian pluralism fits best with a liberal or moderate kind of communitarianism that balances community with other goods, especially personal autonomy.</p>",george crowder,,2006.0,10.1057/palgrave.cpt.9300249,Contemporary Political Theory,Crowder2006,Not available,,Nature,Not available,Value Pluralism and Communitarianism,2d4a6671122ef0c3167a72a9e8ea78d2,http://dx.doi.org/10.1057/palgrave.cpt.9300249
14429,"<p>In 1991, India liberalized its regulatory market system, the ‘License Raj’, and opened up to global competition. This eliminated the chronic supply gap characterizing the Indian market and introduced efficiency, quality and innovation to a competitiveness previously based on political ‘connectivity'. However, the largely nationalized banking sector has been unable to change in tune with the market environment. Pre-liberalization, banks mainly served as a credit distribution infrastructure, since investment approval was in government hands. Liberalization shifted this responsibility to banks; but lacking the infrastructure, professionals and tools to analyse market developments, to manage market risk, they paradoxically rely on consultants with reliable reputations. This paper explores two issues. Firstly, it shows that market liberalization requires an infrastructure of professional business services to analyse the market forces unleashed and to equip market parties with appropriate tools. Indian banks have so far failed to change from ‘credit administrators' into market analysts. Secondly, the paper discusses the implications of this failure for other professional business services and industry generally. The banks' inability to distinguish between sophisticated business plans and frauds corrupts the market for business consultancy, while lending unguided by market analysis facilitates cut-throat competition in a saturated market.</p>",harald bekkers,,2003.0,10.1057/palgrave.abm.9200044,Asian Business & Management,Bekkers2003,Not available,,Nature,Not available,Growing Dependence of Public Banking on Private Consultants for Market Expertise and Risk Management in India,9f009b5903abdbc3969601c648772c0f,http://dx.doi.org/10.1057/palgrave.abm.9200044
14430,"<p>The revelations the Bush administration employed torture in ‘black sites’ and outsourced torture through the ‘extraordinary rendition’ programme demonstrated how the torture prohibition, or torture taboo, failed to constrain the United States (US) and other complicit states from engaging in torture in the fight against terrorism. Yet despite this violation of the taboo, this article makes the paradoxical argument that studying the taboo’s violation shows the strength of the norm’s legitimacy, not its weakness. The humanitarian pressures from the torture taboo continued to operate on the US even while the norm was being violated, shaping US identity, interests and actions during the ‘war on terror’.</p>",jamal barnes,,2016.0,10.1057/ip.2015.46,International Politics,Barnes2016,Not available,,Nature,Not available,"Black sites, ‘extraordinary renditions’ and the legitimacy of the torture taboo",b526d5933cc8e5a04e533d6d9dd3c6cd,http://dx.doi.org/10.1057/ip.2015.46
14431,"<p>Hybrid zones are found wherever two populations distinguishable on the basis of heritable characters overlap spatially and temporally and hybridization occurs. If hybrids have lower fitness than the parental types a tension zone may emerge, in which there is a barrier to gene flow between the two parental populations. Here we discuss a hybrid zone between two honeybee subspecies, <i>Apis mellifera capensis</i> and <i>A. m. scutellata</i> and argue that this zone is an example of a tension zone. This tension zone is particularly interesting because <i>A. m. capensis</i> can be a lethal social parasite of <i>A. m. scutellata</i>. However, despite its parasitic potential, <i>A. m. capensis</i> appears to be unable to increase its natural range unassisted. We propose three interlinked mechanisms that could maintain the South African honeybee hybrid zone: (1) low fitness of intercrossed and genetically mixed colonies arising from inadequate regulation of worker reproduction; (2) higher reproductive success of <i>A. m. scutellata</i> via both high dispersal rates into the hybrid zone and increased competitiveness of males, countered by (3) the parasitic nature of <i>A. m. capensis</i>.</p>",m beekman,,2007.0,10.1038/sj.hdy.6801058,Heredity,Beekman2007,Not available,,Nature,Not available,Factors affecting the dynamics of the honeybee (<i>Apis mellifera</i>) hybrid zone of South Africa,625467454a88c51f0a7a51a3792f2743,http://dx.doi.org/10.1038/sj.hdy.6801058
14432,"<p>Hybrid zones are found wherever two populations distinguishable on the basis of heritable characters overlap spatially and temporally and hybridization occurs. If hybrids have lower fitness than the parental types a tension zone may emerge, in which there is a barrier to gene flow between the two parental populations. Here we discuss a hybrid zone between two honeybee subspecies, <i>Apis mellifera capensis</i> and <i>A. m. scutellata</i> and argue that this zone is an example of a tension zone. This tension zone is particularly interesting because <i>A. m. capensis</i> can be a lethal social parasite of <i>A. m. scutellata</i>. However, despite its parasitic potential, <i>A. m. capensis</i> appears to be unable to increase its natural range unassisted. We propose three interlinked mechanisms that could maintain the South African honeybee hybrid zone: (1) low fitness of intercrossed and genetically mixed colonies arising from inadequate regulation of worker reproduction; (2) higher reproductive success of <i>A. m. scutellata</i> via both high dispersal rates into the hybrid zone and increased competitiveness of males, countered by (3) the parasitic nature of <i>A. m. capensis</i>.</p>",m allsopp,,2007.0,10.1038/sj.hdy.6801058,Heredity,Beekman2007,Not available,,Nature,Not available,Factors affecting the dynamics of the honeybee (<i>Apis mellifera</i>) hybrid zone of South Africa,625467454a88c51f0a7a51a3792f2743,http://dx.doi.org/10.1038/sj.hdy.6801058
14433,"<p>Hybrid zones are found wherever two populations distinguishable on the basis of heritable characters overlap spatially and temporally and hybridization occurs. If hybrids have lower fitness than the parental types a tension zone may emerge, in which there is a barrier to gene flow between the two parental populations. Here we discuss a hybrid zone between two honeybee subspecies, <i>Apis mellifera capensis</i> and <i>A. m. scutellata</i> and argue that this zone is an example of a tension zone. This tension zone is particularly interesting because <i>A. m. capensis</i> can be a lethal social parasite of <i>A. m. scutellata</i>. However, despite its parasitic potential, <i>A. m. capensis</i> appears to be unable to increase its natural range unassisted. We propose three interlinked mechanisms that could maintain the South African honeybee hybrid zone: (1) low fitness of intercrossed and genetically mixed colonies arising from inadequate regulation of worker reproduction; (2) higher reproductive success of <i>A. m. scutellata</i> via both high dispersal rates into the hybrid zone and increased competitiveness of males, countered by (3) the parasitic nature of <i>A. m. capensis</i>.</p>",t wossler,,2007.0,10.1038/sj.hdy.6801058,Heredity,Beekman2007,Not available,,Nature,Not available,Factors affecting the dynamics of the honeybee (<i>Apis mellifera</i>) hybrid zone of South Africa,625467454a88c51f0a7a51a3792f2743,http://dx.doi.org/10.1038/sj.hdy.6801058
14434,"<p>The vulnerability to real-life networks against small initial attacks has been one of outstanding challenges in the study of interrelated networks. We study cascading failures in two interrelated networks <b><i>S</i></b> and <b><i>B</i></b> composed from dependency chains and connectivity links respectively. This work proposes a realistic model for cascading failures based on the redistribution of traffic flow. We study the Barabási-Albert networks (<b><i>BA</i></b>) and Erdős-Rényi graphs (<b><i>ER</i></b>) with such structure, and found that the efficiency sharply decreases with increasing percentages of the dependency nodes for removing a node randomly. Furthermore, we study the robustness of interrelated traffic networks, especially the subway and bus network in Beijing. By analyzing different attacking strategies, we uncover that the efficiency of the city traffic system has a non-equilibrium phase transition at low capacity of the networks. This explains why the pressure of the traffic overload is relaxed by singly increasing the number of small buses during rush hours. We also found that the increment of some buses may release traffic jam caused by removing a node of the bus network randomly if the damage is limited. However, the efficiencies to transfer people flow will sharper increase when the capacity of the subway network <b><i>α<sub>S</sub></i> > <i>α</i><sub>0</sub></b>.</p>",lixiang li,Complex networks,2014.0,10.1038/srep05413,Scientific Reports,Su2014,Not available,,Nature,Not available,Robustness of Interrelated Traffic Networks to Cascading Failures,4840ca15ebd58b9a2e9f7ee719c39054,http://dx.doi.org/10.1038/srep05413
14435,"<p>Hybrid zones are found wherever two populations distinguishable on the basis of heritable characters overlap spatially and temporally and hybridization occurs. If hybrids have lower fitness than the parental types a tension zone may emerge, in which there is a barrier to gene flow between the two parental populations. Here we discuss a hybrid zone between two honeybee subspecies, <i>Apis mellifera capensis</i> and <i>A. m. scutellata</i> and argue that this zone is an example of a tension zone. This tension zone is particularly interesting because <i>A. m. capensis</i> can be a lethal social parasite of <i>A. m. scutellata</i>. However, despite its parasitic potential, <i>A. m. capensis</i> appears to be unable to increase its natural range unassisted. We propose three interlinked mechanisms that could maintain the South African honeybee hybrid zone: (1) low fitness of intercrossed and genetically mixed colonies arising from inadequate regulation of worker reproduction; (2) higher reproductive success of <i>A. m. scutellata</i> via both high dispersal rates into the hybrid zone and increased competitiveness of males, countered by (3) the parasitic nature of <i>A. m. capensis</i>.</p>",b oldroyd,,2007.0,10.1038/sj.hdy.6801058,Heredity,Beekman2007,Not available,,Nature,Not available,Factors affecting the dynamics of the honeybee (<i>Apis mellifera</i>) hybrid zone of South Africa,625467454a88c51f0a7a51a3792f2743,http://dx.doi.org/10.1038/sj.hdy.6801058
14436,"<p>Socialism is defined as a normative property of an allocation: that the allocation of labor and output be Pareto efficient, and that output received by individuals be proportional to the value of the labor they expended in production. Social democracy is an institution: the redistribution of income through taxation, with a system of private ownership of capital. We present a stylized parameterization of the US economy and compute its (unique) socialist allocation, and the Gini coefficient of the income distribution in that allocation. We compute the Gini coefficient of after-tax income in the present US “social democracy” and show that it is <i>lower</i> than in the socialist allocation. Hence, socialists must choose between two mutually exclusive alternatives: eliminating exploitation in the Marxian sense (achieving socialism, as defined above), or equalizing income. We propose that egalitarians must go beyond socialism, as it has been classically conceived.</p>",john roemer,,2007.0,10.1057/palgrave.eej.9050011,Eastern Economic Journal,Roemer2007,Not available,,Nature,Not available,Socialism vs Social Democracy as Income-Equalizing Institutions,6c135d0b46aec0546e269b86101a7e36,http://dx.doi.org/10.1057/palgrave.eej.9050011
14437,"<p>Some green theorists have criticized John Locke's theory of property as the source of liberalism's failure to address environmental degradation. Yet when properly read, Locke's Second Treatise provides a fruitful source for constructing an environmentally sensitive and sustainable twenty-first-century liberalism. This article contends that Locke's economic, political, and social circumstances sensitized him to issues of scarcity and the importance of material resources that are critical to a twenty-first-century environmental liberalism. His theory of property limits individual rights by establishing rules of fair play (enough and as good), prohibiting waste (spoilage), and requiring the support of the poor (sufficiency). His text—particularly, the “enough and as good proviso”—connects equality, fairness, and the common good to the natural world.</p>",susan liebell,,2011.0,10.1057/pol.2010.28,Polity,Liebell2011,Not available,,Nature,Not available,The Text and Context of “Enough and as Good”: John Locke as the Foundation of an Environmental Liberalism,02f104c87d345f5a81f8f3c9616a107a,http://dx.doi.org/10.1057/pol.2010.28
14438,"<p>This article argues that neoclassical realism (NCR), though it presents one of the most intuitively attractive frameworks for understanding states’ actions, continues to struggle with a central conceptual tension. Some have argued that NCR is compatible with a structural realist approach, even that it is a ‘logical extension’ of it. Yet in seeking to identify law-like patterns of state behaviour arising from the varied features of states themselves, NCR appears to breach the outer limits of what Kenneth Waltz, the founding father of structural International Relations theory, thought tolerable in a theory of international politics. Thus, NCR arguably faces a fork in the road as to its future agenda and theoretical identity: should it limit itself essentially to chronicling anomalous occurrences within a fundamentally Waltzian paradigm, or try to map new rules of state behaviour on a scale that ultimately calls the primacy of Waltz's ‘systemic imperatives’ into question?</p>",adam quinn,,2013.0,10.1057/ip.2013.5,International Politics,Quinn2013,Not available,,Nature,Not available,"Kenneth Waltz, Adam Smith and the Limits of Science: Hard choices for neoclassical realism",09346e06f6071f9c1f2294fb4b9f5f5e,http://dx.doi.org/10.1057/ip.2013.5
14439,"<p>This article revisits the question of aid effectiveness on economic growth by introducing a country’s legal origin in the debate. We provide compelling evidence to show that both quantity and quality of aid disbursed to Africa’s least developed countries matter and that these effects differ based on a country’s legal origin. A quadratic specification of the total aid variable and source-based proxies are used to capture the effects of quantity and quality of aid, respectively. The aid effects are evaluated in a dynamic framework using system GMM. Our results are robust to different model specifications and estimation techniques.</p>",evelyn wamboye,,2013.0,10.1057/dev.2013.24,Development,Wamboye2013,Not available,,Nature,Not available,Economic Growth and the Role of Foreign Aid in Selected African Countries,d366de3eec2af2a7a061d1d7197af527,http://dx.doi.org/10.1057/dev.2013.24
14440,"<p>This article revisits the question of aid effectiveness on economic growth by introducing a country’s legal origin in the debate. We provide compelling evidence to show that both quantity and quality of aid disbursed to Africa’s least developed countries matter and that these effects differ based on a country’s legal origin. A quadratic specification of the total aid variable and source-based proxies are used to capture the effects of quantity and quality of aid, respectively. The aid effects are evaluated in a dynamic framework using system GMM. Our results are robust to different model specifications and estimation techniques.</p>",abel adekola,,2013.0,10.1057/dev.2013.24,Development,Wamboye2013,Not available,,Nature,Not available,Economic Growth and the Role of Foreign Aid in Selected African Countries,d366de3eec2af2a7a061d1d7197af527,http://dx.doi.org/10.1057/dev.2013.24
14441,"<p>This article revisits the question of aid effectiveness on economic growth by introducing a country’s legal origin in the debate. We provide compelling evidence to show that both quantity and quality of aid disbursed to Africa’s least developed countries matter and that these effects differ based on a country’s legal origin. A quadratic specification of the total aid variable and source-based proxies are used to capture the effects of quantity and quality of aid, respectively. The aid effects are evaluated in a dynamic framework using system GMM. Our results are robust to different model specifications and estimation techniques.</p>",bruno sergi,,2013.0,10.1057/dev.2013.24,Development,Wamboye2013,Not available,,Nature,Not available,Economic Growth and the Role of Foreign Aid in Selected African Countries,d366de3eec2af2a7a061d1d7197af527,http://dx.doi.org/10.1057/dev.2013.24
14442,"<p>This paper demonstrates the value of political metaphor analysis as a tool for answering constitutive questions in International Relations (IR) theory, questions that attend to how the subjects of international politics are constituted by encounters with other subjects through representational and interactional processes. To this end, I examine the key metaphors within American political discourse that guided and structured early Sino-American interactions, focusing on US Secretary of State John Hay's Open Door notes and the contemporaneous Chinese Exclusion Acts. Viewed from a social constructivist metaphor perspective, this metaphorical protection of free trade and great power privilege hid the assumption that China was unable to act as its own doorkeeper, obscuring debates in the domestic and international spheres as to the meaning of ‘Chinese’ and the appropriate strategy for managing the encounter. A second approach, the cognitive perspective, builds on the seminal IR applications of cognitive linguistics and cognitive metaphor theory to reveal the deeper conceptual basis, specifically the <span>CONTAINER</span> schema, upon which this encounter was predicated. Used in tandem, these two approaches to the constitutive role of political metaphor illuminate the processes by which metaphors win out over competing discourses to become durable features of international social relations.</p>",eric blanchard,,2012.0,10.1057/jird.2012.12,Journal of International Relations and Development,Blanchard2012,Not available,,Nature,Not available,Constituting China: the role of metaphor in the discourses of early Sino-American relations,e8f1eb5c59c1b8091136899d3e71c44b,http://dx.doi.org/10.1057/jird.2012.12
14443,"<p>How to make sense of the singular power of the United States and the distinctive role it now plays in world politics has become a pressing challenge to scholars and analysts of international politics. This article argues that attempts to characterize the US role in the international system as, variously, hegemonic, an empire or a traditional great power are not compelling. This is especially evident when placed in the specific regional context of the Asia-Pacific. These broad approaches all tend to overstate the capacity of the US to shape outcomes in its favour. Instead, it argues that Raymond Aron's depiction of the United States as an imperial republic provides a more useful basis on which to build analysis of America's international role and from this starting point sets out a distinctive characterization of regional international order. The article is in three parts, the first assesses different ways of conceptualizing American power, with particular attention paid to the argument about hegemony and empire. The second puts forward the case for the utility of Aron's concept of the imperial republic, and the third then develops a characterization of regional international order that does not rely on a determinative assessment of American power. This section argues that order is the product of four distinct forces: the nature and character of the relations between the major powers; the character and dynamism of economic relations, particularly international trade and investment; the series of bilateral security alliances that structure the security system; and socio-cultural factors, particularly, the growth of nationalism and the continuing impact of the colonial experience.</p>",nick bisley,,2006.0,10.1057/palgrave.ip.8800140,International Politics,Bisley2006,Not available,,Nature,Not available,Neither Empire nor Republic: American Power and Regional Order in the Asia-Pacific<tlnref><sup>1</sup></tlnref>,106007ac51f7fd1218c1becdefcc0b98,http://dx.doi.org/10.1057/palgrave.ip.8800140
14444,"<p>Norbert Elias's sociological analysis of ‘the civilizing process’ — the process by which modern European societies have been pacified over the last five centuries and emotional identification between the inhabitants of each society has increased — has much to contribute to historical–sociological approaches to International Relations. Elias analysed dominant attitudes towards cruelty and suffering in different phases of human history in his study of the civilizing process, his central purpose being to demonstrate the existence of a long-term trend to lower the ‘threshold of repugnance’ against public acts of violence within modern states. His observations about international relations were principally Hobbesian in nature, although Grotian and Kantian themes also permeated his writings. The latter are evident in his reflections on whether cosmopolitan emotions are stronger in the modern era than in earlier epochs. An empirical analysis of dominant global attitudes towards cruelty in world politics and an investigation of levels of emotional identification between different societies can extend Elias's study of the civilizing process. This form of inquiry can also contribute to the development of Martin Wight's pioneering essays on the sociology of states-systems and enlarge the English School's analysis of ‘civility’ and the ‘civilizing process’ in international relations. More broadly, new linkages between historical sociology and International Relations can be developed around an investigation of the dominant responses to cruelty and suffering — and levels of cosmopolitan identification — in different states-systems.</p>",andrew linklater,,2004.0,10.1057/palgrave.ip.8800067,International Politics,Linklater2004,Not available,,Nature,Not available,"Norbert Elias, The ‘Civilizing Process’ and the Sociology of International Relations",c60ec2b758d4454f288686076c4d2fd6,http://dx.doi.org/10.1057/palgrave.ip.8800067
14445,"<p>The vulnerability to real-life networks against small initial attacks has been one of outstanding challenges in the study of interrelated networks. We study cascading failures in two interrelated networks <b><i>S</i></b> and <b><i>B</i></b> composed from dependency chains and connectivity links respectively. This work proposes a realistic model for cascading failures based on the redistribution of traffic flow. We study the Barabási-Albert networks (<b><i>BA</i></b>) and Erdős-Rényi graphs (<b><i>ER</i></b>) with such structure, and found that the efficiency sharply decreases with increasing percentages of the dependency nodes for removing a node randomly. Furthermore, we study the robustness of interrelated traffic networks, especially the subway and bus network in Beijing. By analyzing different attacking strategies, we uncover that the efficiency of the city traffic system has a non-equilibrium phase transition at low capacity of the networks. This explains why the pressure of the traffic overload is relaxed by singly increasing the number of small buses during rush hours. We also found that the increment of some buses may release traffic jam caused by removing a node of the bus network randomly if the damage is limited. However, the efficiencies to transfer people flow will sharper increase when the capacity of the subway network <b><i>α<sub>S</sub></i> > <i>α</i><sub>0</sub></b>.</p>",lixiang li,Nonlinear phenomena,2014.0,10.1038/srep05413,Scientific Reports,Su2014,Not available,,Nature,Not available,Robustness of Interrelated Traffic Networks to Cascading Failures,4840ca15ebd58b9a2e9f7ee719c39054,http://dx.doi.org/10.1038/srep05413
14446,"<p>Cities globally are focusing on place branding to set one locale apart from another. Normal touch points, such as websites, fliers, magazines, brochures, press releases and more are used often. One document not typically thought of as marketing or public relations piece that could extend the place brand is the municipal budget. The document, not the process necessarily, offers an opportunity to extend the place brand. In this study, 20 US cities were examined to understand variation among cities when presenting budgets. Findings revealed that, although cities are using the documents to a certain promotional extent, there still remains room for innovation in the area of budget book presentation.</p>",staci zavattaro,,2013.0,10.1057/pb.2012.26,Place Branding and Public Diplomacy,Zavattaro2013,Not available,,Nature,Not available,Exploring how US cities use budget documents as marketing and public relations tools,bb70dc2ec8d8264f5832fd7f838b32d9,http://dx.doi.org/10.1057/pb.2012.26
14447,"<p>This essay discusses the policy debate concerning optimal taxation and the distribution of income. It begins with a brief overview of trends in income inequality, the leading hypothesis to explain these trends, and the distribution of the tax burden. It then considers the normative question of how the tax system should be designed. The conventional utilitarian framework is found to be wanting, as it leads to prescriptions that conflict with many individuals’ moral intuitions. The essay then explores an alternative normative framework, dubbed the Just Deserts Theory, according to which an individual's compensation should reflect his or her social contribution.</p>",n mankiw,,2010.0,10.1057/eej.2010.22,Eastern Economic Journal,Mankiw2010,Not available,,Nature,Not available,Spreading the Wealth Around: Reflections Inspired by Joe the Plumber,9244d039a59b4a7b50cc13ee43427961,http://dx.doi.org/10.1057/eej.2010.22
14448,"<p>At the 2010 OR Society Simulation Workshop, there was a lively panel discussion entitled ‘Discrete-event simulation is dead, long live agent-based simulation!’, which was subsequently written up as a position paper for the <i>Journal of Simulation</i> (Siebers <i>et al</i>, 2010). This paper continues that discussion and, to quote Mark Twain, argues that rumours of the death of discrete-event simulation (DES) are greatly exaggerated. There has undoubtedly been a recent surge of interest within the mainstream OR community in the use of agent-based modelling, but this paper suggests that many of the cited benefits of agent-based simulation (ABS) can be achieved through the use of a traditional DES approach. These arguments are illustrated by several examples where DES has been used successfully to tackle ‘ABS-type’ problems.</p>",sally brailsford,,2013.0,10.1057/jos.2013.13,Journal of Simulation,Brailsford2013,Not available,,Nature,Not available,Discrete-event simulation is alive and kicking!,98d00b71fa74e3a4486e8d50fb9dddc3,http://dx.doi.org/10.1057/jos.2013.13
14449,"<p>This book is another product of the Copenhagen School's cumulative endeavours to develop a comprehensive framework for analyzing and understanding international security. This voluminous study builds on the arguments of a number of texts published over the last 15 years, some of which are true landmarks in security studies and International Relations (IR) (e.g.  Buzan 1991 ;  Wæver  et al.  1993 ;  Buzan  et al.  1998 ;  Buzan and Little 2000 ).</p>",jiri sedivy,,2004.0,10.1057/palgrave.jird.1800026,Journal of International Relations and Development,Šedivý2004,Not available,,Nature,Not available,Regions and Powers: The Structure of International Security,26641be7c8a844a2e24aa4db3d9d0ead,http://dx.doi.org/10.1057/palgrave.jird.1800026
14450,"<p>When we read a manuscript, look at a monument, or engage other signs of history, we experience them as always having more to tell us. We can therefore call them ‘voices’ even if their original enunciators are no longer here directly to add to what they have said.</p>",fred evans,,2014.0,10.1057/pmed.2014.25,postmedieval: a journal of medieval cultural studies,Evans2014,Not available,,Nature,Not available,Ethics and the voices of the past,0c5fe4faed2370cf9f8187e3f1da5902,http://dx.doi.org/10.1057/pmed.2014.25
14451,"Vested interests are redefining, rebranding and co-opting what is 'biopharmaceutical'. This is not just a matter of semantics—the core identity of the biotech industry and its products is at stake.",ronald rader,,2008.0,10.1038/nbt0708-743,Nature Biotechnology,Rader2008,Not available,,Nature,Not available,(Re)defining biopharmaceutical,9e39b3d77e0b9cd34225a8f3876313b3,http://dx.doi.org/10.1038/nbt0708-743
14452,"<p>This paper argues that brands need to find ways of becoming more responsive to emerging consumer trends. It proposes using scenario planning techniques for creating future narratives that can articulate a range of different consumer futures. Adopting this approach would arm brand managers and planners with new mental maps of their markets that would have two key benefits. First, it would enable them to make sense of the mass of in-coming, often contradictory information. Second, it would enable them to recognise the inherent significance of market developments as the unfolding of particular future narratives or patterns that they have already considered.</p>",richard woods,,1999.0,10.1057/bm.1999.35,Journal of Brand Management,Woods1999,Not available,,Nature,Not available,Providing the human and cultural context for brands: Using ‘memories of the future’ to create Future Narratives,0d004de39e6745cc5f7a287e63ec319a,http://dx.doi.org/10.1057/bm.1999.35
14453,"<p>The vulnerability to real-life networks against small initial attacks has been one of outstanding challenges in the study of interrelated networks. We study cascading failures in two interrelated networks <b><i>S</i></b> and <b><i>B</i></b> composed from dependency chains and connectivity links respectively. This work proposes a realistic model for cascading failures based on the redistribution of traffic flow. We study the Barabási-Albert networks (<b><i>BA</i></b>) and Erdős-Rényi graphs (<b><i>ER</i></b>) with such structure, and found that the efficiency sharply decreases with increasing percentages of the dependency nodes for removing a node randomly. Furthermore, we study the robustness of interrelated traffic networks, especially the subway and bus network in Beijing. By analyzing different attacking strategies, we uncover that the efficiency of the city traffic system has a non-equilibrium phase transition at low capacity of the networks. This explains why the pressure of the traffic overload is relaxed by singly increasing the number of small buses during rush hours. We also found that the increment of some buses may release traffic jam caused by removing a node of the bus network randomly if the damage is limited. However, the efficiencies to transfer people flow will sharper increase when the capacity of the subway network <b><i>α<sub>S</sub></i> > <i>α</i><sub>0</sub></b>.</p>",lixiang li,Statistical physics,2014.0,10.1038/srep05413,Scientific Reports,Su2014,Not available,,Nature,Not available,Robustness of Interrelated Traffic Networks to Cascading Failures,4840ca15ebd58b9a2e9f7ee719c39054,http://dx.doi.org/10.1038/srep05413
14454,"<p>While the major feature defining United States’ (US) foreign policy since the Cold War has been the use of coercive means such as military power and economic sanctions, the European Union (EU) international role, despite recent attempts to develop military capabilities, remains that of a civilian power. The literature on transatlantic relations has explained this difference by stressing the different positions of the two actors in the international balance of power and pointing at their divergent value and normative frameworks. This article, by comparing the EU and US policy-making processes, introduces a further explanation. It argues that, although the two polities share the features of Compound Democracies, the different institutional organization of their foreign policy-making processes has generated powerful incentives for pursuing different kinds of international action.</p>",sergio fabbrini,,2008.0,10.1057/ip.2008.5,International Politics,Fabbrini2008,Not available,,Nature,Not available,Bringing Policy-Making Structure Back In: Why are the US and the EU Pursuing Different Foreign Policies?,909f5bdcbe343f931508b3a01bf827c1,http://dx.doi.org/10.1057/ip.2008.5
14455,"<p>While the major feature defining United States’ (US) foreign policy since the Cold War has been the use of coercive means such as military power and economic sanctions, the European Union (EU) international role, despite recent attempts to develop military capabilities, remains that of a civilian power. The literature on transatlantic relations has explained this difference by stressing the different positions of the two actors in the international balance of power and pointing at their divergent value and normative frameworks. This article, by comparing the EU and US policy-making processes, introduces a further explanation. It argues that, although the two polities share the features of Compound Democracies, the different institutional organization of their foreign policy-making processes has generated powerful incentives for pursuing different kinds of international action.</p>",daniela sicurelli,,2008.0,10.1057/ip.2008.5,International Politics,Fabbrini2008,Not available,,Nature,Not available,Bringing Policy-Making Structure Back In: Why are the US and the EU Pursuing Different Foreign Policies?,909f5bdcbe343f931508b3a01bf827c1,http://dx.doi.org/10.1057/ip.2008.5
14456,"<p>The vulnerability to real-life networks against small initial attacks has been one of outstanding challenges in the study of interrelated networks. We study cascading failures in two interrelated networks <b><i>S</i></b> and <b><i>B</i></b> composed from dependency chains and connectivity links respectively. This work proposes a realistic model for cascading failures based on the redistribution of traffic flow. We study the Barabási-Albert networks (<b><i>BA</i></b>) and Erdős-Rényi graphs (<b><i>ER</i></b>) with such structure, and found that the efficiency sharply decreases with increasing percentages of the dependency nodes for removing a node randomly. Furthermore, we study the robustness of interrelated traffic networks, especially the subway and bus network in Beijing. By analyzing different attacking strategies, we uncover that the efficiency of the city traffic system has a non-equilibrium phase transition at low capacity of the networks. This explains why the pressure of the traffic overload is relaxed by singly increasing the number of small buses during rush hours. We also found that the increment of some buses may release traffic jam caused by removing a node of the bus network randomly if the damage is limited. However, the efficiencies to transfer people flow will sharper increase when the capacity of the subway network <b><i>α<sub>S</sub></i> > <i>α</i><sub>0</sub></b>.</p>",haipeng peng,Complex networks,2014.0,10.1038/srep05413,Scientific Reports,Su2014,Not available,,Nature,Not available,Robustness of Interrelated Traffic Networks to Cascading Failures,4840ca15ebd58b9a2e9f7ee719c39054,http://dx.doi.org/10.1038/srep05413
14457,"<p>This paper extends and builds on Ronen and Shenkar’s synthesized cultural clustering of countries based on similarity and dissimilarity in work-related attitudes. The new map uses an updated dataset, and expands coverage to world areas that were non-accessible at the time. Cluster boundaries are drawn empirically rather than intuitively, and the plot obtained is triple nested, indicating three levels of similarity across given country pairs. Also delineated are cluster adjacency and cluster cohesiveness, which vary from the highly cohesive Arab and Anglo clusters to the least cohesive Confucian and Far Eastern clusters. Exploring predictors of cluster formation, we draw on the ecocultural perspective and other inputs, and examine the combined role of language, religion, and geography in generating cluster formation. We find that these forces play a prominent yet complex role: for instance, the religion and language brought by the Spanish fail to create a singular, cohesive Latin American cluster akin to the Anglo cluster. The role of economic variables is similarly considered. Finally, comparing the current map with that of 1985, we find strong support for the divergence (vs convergence) argument. Implications for international business are delineated.</p>",simcha ronen,,2013.0,10.1057/jibs.2013.42,Journal of International Business Studies,Ronen2013,Not available,,Nature,Not available,"Mapping world cultures: Cluster formation, sources and implications",d570f184aa76669cf384425cef300dd5,http://dx.doi.org/10.1057/jibs.2013.42
14458,"<p>This paper extends and builds on Ronen and Shenkar’s synthesized cultural clustering of countries based on similarity and dissimilarity in work-related attitudes. The new map uses an updated dataset, and expands coverage to world areas that were non-accessible at the time. Cluster boundaries are drawn empirically rather than intuitively, and the plot obtained is triple nested, indicating three levels of similarity across given country pairs. Also delineated are cluster adjacency and cluster cohesiveness, which vary from the highly cohesive Arab and Anglo clusters to the least cohesive Confucian and Far Eastern clusters. Exploring predictors of cluster formation, we draw on the ecocultural perspective and other inputs, and examine the combined role of language, religion, and geography in generating cluster formation. We find that these forces play a prominent yet complex role: for instance, the religion and language brought by the Spanish fail to create a singular, cohesive Latin American cluster akin to the Anglo cluster. The role of economic variables is similarly considered. Finally, comparing the current map with that of 1985, we find strong support for the divergence (vs convergence) argument. Implications for international business are delineated.</p>",oded shenkar,,2013.0,10.1057/jibs.2013.42,Journal of International Business Studies,Ronen2013,Not available,,Nature,Not available,"Mapping world cultures: Cluster formation, sources and implications",d570f184aa76669cf384425cef300dd5,http://dx.doi.org/10.1057/jibs.2013.42
14459,"<p>The traditional understanding of the origins of international relations (IR) is on the ropes. The old vision of a discipline that was born under an idealist star and matured through a first ‘Great Debate’ is no longer credible. This article offers an alternative understanding: viz. that a scholarly study of IR emerged during the decades prior to World War I, that the emergence represents an international movement, and that it was occasioned by major changes in Great Power economic and political affairs. By posing a few simple questions — who were the first scholarly IR-authors? where and why they write? — this article identifies some of the formative forces that produced the first (now largely lost) generation of IR scholars. It proposes a historically grounded, alternative to our traditional (largely British and mythological) understanding of early IR scholarship.</p>",torbjorn knutsen,,2008.0,10.1057/ip.2008.30,International Politics,Knutsen2008,Not available,,Nature,Not available,A Lost Generation? IR Scholarship before World War I,19b4ead453f2d0e395ebe378fe72d0af,http://dx.doi.org/10.1057/ip.2008.30
14460,"<p>This article introduces an innovative approach to the role-play teaching technique: one driven by the presence of substance incentives. We analyse the effectiveness of this incentive-driven role-play approach in the engagement of students with International Relations and Security Studies seminars. We assess its usefulness on multiple fronts. We propose that incentive-driven role-play is an effective method of teaching that caters for students’ different learning styles, particularly in theory topics. Its interactive component makes theory tangible for students, allowing them to grasp why certain actions are taken and the consequences of these actions. The use of incentives was found to be important in ensuring motivation, participation and providing easily understandable outcomes that can be transferred to the theory they were studying. This article also highlights the practicalities involved in incentive-driven role-play exercises, noting the importance of clear instructions and precursor lectures on the subject matter.</p>",sophia dingli,,2013.0,10.1057/eps.2013.19,European Political Science,dingli2013,Not available,,Nature,Not available,The Effectiveness of Incentive-Driven Role-Play,5604ae10f0763e371594a20311e6449e,http://dx.doi.org/10.1057/eps.2013.19
14461,"<p>This article introduces an innovative approach to the role-play teaching technique: one driven by the presence of substance incentives. We analyse the effectiveness of this incentive-driven role-play approach in the engagement of students with International Relations and Security Studies seminars. We assess its usefulness on multiple fronts. We propose that incentive-driven role-play is an effective method of teaching that caters for students’ different learning styles, particularly in theory topics. Its interactive component makes theory tangible for students, allowing them to grasp why certain actions are taken and the consequences of these actions. The use of incentives was found to be important in ensuring motivation, participation and providing easily understandable outcomes that can be transferred to the theory they were studying. This article also highlights the practicalities involved in incentive-driven role-play exercises, noting the importance of clear instructions and precursor lectures on the subject matter.</p>",sameera khalfey,,2013.0,10.1057/eps.2013.19,European Political Science,dingli2013,Not available,,Nature,Not available,The Effectiveness of Incentive-Driven Role-Play,5604ae10f0763e371594a20311e6449e,http://dx.doi.org/10.1057/eps.2013.19
14462,"<p>This article introduces an innovative approach to the role-play teaching technique: one driven by the presence of substance incentives. We analyse the effectiveness of this incentive-driven role-play approach in the engagement of students with International Relations and Security Studies seminars. We assess its usefulness on multiple fronts. We propose that incentive-driven role-play is an effective method of teaching that caters for students’ different learning styles, particularly in theory topics. Its interactive component makes theory tangible for students, allowing them to grasp why certain actions are taken and the consequences of these actions. The use of incentives was found to be important in ensuring motivation, participation and providing easily understandable outcomes that can be transferred to the theory they were studying. This article also highlights the practicalities involved in incentive-driven role-play exercises, noting the importance of clear instructions and precursor lectures on the subject matter.</p>",cristina leston-bandeira,,2013.0,10.1057/eps.2013.19,European Political Science,dingli2013,Not available,,Nature,Not available,The Effectiveness of Incentive-Driven Role-Play,5604ae10f0763e371594a20311e6449e,http://dx.doi.org/10.1057/eps.2013.19
14463,"<p>This article explores the political meanings of a relatively unexplored dimension of Edmund Burke's thought: the monster. After first showing the extent to which the figure of the monster appears throughout Burke's work, the article speculates on some of the political reasons for Burke's use of the metaphor of the monstrous. These reasons are rooted in the categories of the aesthetic developed in the <i>Philosophical Enquiry into the Origin of our Ideas of the Sublime and Beautiful</i>, and also in his political fear of a new collective entity only beginning to emerge on the historical stage: the proletariat. The article therefore has three aims: first, to contribute to the developing body of literature on Burke's aesthetic ideology; second, to deepen our knowledge of the Gothic tropes in Burke's writings; and third, to broaden our conception of the way conservative ideology conceptualizes order and the threats to that order.</p>",mark neocleous,,2004.0,10.1057/palgrave.cpt.9300110,Contemporary Political Theory,Neocleous2004,Not available,,Nature,Not available,The Monstrous Multitude: Edmund Burke's Political Teratology,616b1d6e6cbbe0fc2d16cf1a58896f6e,http://dx.doi.org/10.1057/palgrave.cpt.9300110
14464,"<p>In this article, I present a neoclassical realist theory of climate change politics that challenges the idea that cooperation on climate change is compelled alone by shared norms and interests emanating from the international level and questions if instead material factors also play a significant constraining role. Relative-gains concerns incited by the international resource transfers implicit in climate change policy may compel some states to be prudent in their international climate change efforts and conserve resources domestically for future contingencies, including their own adaptation and resiliency. Neoclassical realism recognises such systemic constraints while also identifying international and domestic factors — a ‘two-level game’ — that explain variation in state sensitivity to relative gains. As a preliminary test of this theory, I compare the latest data on the magnitude, distribution and financial ‘additionality’ of climate funds and carbon markets. Climate funds are found to be more vulnerable to systemic forces identified by neoclassical realism because they are largely drawn from existing official development assistance budgets despite international commitments that funds are ‘new and additional’. Carbon markets engage a relatively broader number of states and, contrary to moral hazard concerns, have been used to a greater degree by states reducing emissions domestically. While there are concerns about whether carbon credits represent genuine emission reductions, the effectiveness of climate funds is equally, if not more, dubious. I conclude that, while imperfect, carbon markets have too often been unfairly compared with an ideal climate finance mechanism that assumes few political constraints on international resource transfers for climate change.</p>
<span><i>Journal of International Relations and Development</i> advance online publication, 26 April 2013; doi:<span>10.1057/jird.2013.5</span></span>",mark purdon,,2013.0,10.1057/jird.2013.5,Journal of International Relations and Development,Purdon2013,Not available,,Nature,Not available,Neoclassical realism and international climate change politics: moral imperative and political constraint in international climate finance,506f7d9b30dc989be6136e9f9f16be76,http://dx.doi.org/10.1057/jird.2013.5
14465,"<p>The vulnerability to real-life networks against small initial attacks has been one of outstanding challenges in the study of interrelated networks. We study cascading failures in two interrelated networks <b><i>S</i></b> and <b><i>B</i></b> composed from dependency chains and connectivity links respectively. This work proposes a realistic model for cascading failures based on the redistribution of traffic flow. We study the Barabási-Albert networks (<b><i>BA</i></b>) and Erdős-Rényi graphs (<b><i>ER</i></b>) with such structure, and found that the efficiency sharply decreases with increasing percentages of the dependency nodes for removing a node randomly. Furthermore, we study the robustness of interrelated traffic networks, especially the subway and bus network in Beijing. By analyzing different attacking strategies, we uncover that the efficiency of the city traffic system has a non-equilibrium phase transition at low capacity of the networks. This explains why the pressure of the traffic overload is relaxed by singly increasing the number of small buses during rush hours. We also found that the increment of some buses may release traffic jam caused by removing a node of the bus network randomly if the damage is limited. However, the efficiencies to transfer people flow will sharper increase when the capacity of the subway network <b><i>α<sub>S</sub></i> > <i>α</i><sub>0</sub></b>.</p>",haipeng peng,Nonlinear phenomena,2014.0,10.1038/srep05413,Scientific Reports,Su2014,Not available,,Nature,Not available,Robustness of Interrelated Traffic Networks to Cascading Failures,4840ca15ebd58b9a2e9f7ee719c39054,http://dx.doi.org/10.1038/srep05413
14466,"<p>International Relations's (IR's) intellectual history is almost always treated as a history of ideas in isolation from both those discursive and political economies which provide its disciplinary and wider (political) context. This paper contributes to this wider analysis by focusing on the impact of the field's discursive economy. Specifically, using Foucaultian archaeologico-genealogical strategy of problematization to analyse the emergence and disciplinary trajectories of Constructivism in IR, this paper argues that Constructivism has been brought gradually closer to its mainstream Neo-utilitarian counterpart through a process of normalization, and investigates how it was possible for Constructivism to be purged of its early critical potential, both theoretical and practical. The first part of the paper shows how the intellectual configuration of Constructivism and its disciplinary fortunes are inseparable from far-from-unproblematic readings of the Philosophy of Social Science: the choices made at this level are neither as intellectually neutral nor as disciplinarily inconsequential as they are presented. The second and third parts chart the genealogies of Constructivism, showing how its overall normalization occurred in two stages, each revolving around particular practices and events. The second part concentrates on older genealogies, analysing the politics of early classificatory practices regarding Constructivism, and showing how these permitted the distillation and immunization of Constructivism – and thus of the rest of the mainstream scholarship which it was depicted as compatible with – against more radical Postmodernist/Post-structuralist critiques. Finally, the third part focuses attention on recent genealogies, revealing new attempts to reconstruct and reformulate Constructivism: here, indirect neutralization practices such as the elaboration of ‘Pragmatist’ Constructivism, as well as the direct neutralization such as the formulation of ‘Realist’ Constructivism, are key events in Constructivism's normalization. These apparently ‘critical’ alternatives that aim to ‘provide the identity variable’ in fact remain close to Neo-utilitarianism, but their successful representation as ‘critical’ help neutralize calls for greater openness in mainstream IR. Rather than a simple intellectual history, it is this complex process of (re)reading and (re)producing that counts as ‘Constructivism’, which explains both the normalization of Constructivism and the continued marginalization of Postmodernist/Post-structuralist approaches in mainstream IR's infra-disciplinary balance of intellectual power.</p>",nik hynek,,2010.0,10.1057/cpt.2008.49,Contemporary Political Theory,Hynek2010,Not available,,Nature,Not available,Saving identity from postmodernism? The normalization of constructivism in International Relations,849341dc7a08170c891dcd356822257e,http://dx.doi.org/10.1057/cpt.2008.49
14467,"<p>International Relations's (IR's) intellectual history is almost always treated as a history of ideas in isolation from both those discursive and political economies which provide its disciplinary and wider (political) context. This paper contributes to this wider analysis by focusing on the impact of the field's discursive economy. Specifically, using Foucaultian archaeologico-genealogical strategy of problematization to analyse the emergence and disciplinary trajectories of Constructivism in IR, this paper argues that Constructivism has been brought gradually closer to its mainstream Neo-utilitarian counterpart through a process of normalization, and investigates how it was possible for Constructivism to be purged of its early critical potential, both theoretical and practical. The first part of the paper shows how the intellectual configuration of Constructivism and its disciplinary fortunes are inseparable from far-from-unproblematic readings of the Philosophy of Social Science: the choices made at this level are neither as intellectually neutral nor as disciplinarily inconsequential as they are presented. The second and third parts chart the genealogies of Constructivism, showing how its overall normalization occurred in two stages, each revolving around particular practices and events. The second part concentrates on older genealogies, analysing the politics of early classificatory practices regarding Constructivism, and showing how these permitted the distillation and immunization of Constructivism – and thus of the rest of the mainstream scholarship which it was depicted as compatible with – against more radical Postmodernist/Post-structuralist critiques. Finally, the third part focuses attention on recent genealogies, revealing new attempts to reconstruct and reformulate Constructivism: here, indirect neutralization practices such as the elaboration of ‘Pragmatist’ Constructivism, as well as the direct neutralization such as the formulation of ‘Realist’ Constructivism, are key events in Constructivism's normalization. These apparently ‘critical’ alternatives that aim to ‘provide the identity variable’ in fact remain close to Neo-utilitarianism, but their successful representation as ‘critical’ help neutralize calls for greater openness in mainstream IR. Rather than a simple intellectual history, it is this complex process of (re)reading and (re)producing that counts as ‘Constructivism’, which explains both the normalization of Constructivism and the continued marginalization of Postmodernist/Post-structuralist approaches in mainstream IR's infra-disciplinary balance of intellectual power.</p>",andrea teti,,2010.0,10.1057/cpt.2008.49,Contemporary Political Theory,Hynek2010,Not available,,Nature,Not available,Saving identity from postmodernism? The normalization of constructivism in International Relations,849341dc7a08170c891dcd356822257e,http://dx.doi.org/10.1057/cpt.2008.49
14468,"<p>‘Globalization’ was the <i>Zeitgeist</i> of the 1990s. In the social sciences, it gave rise to the claim that deepening interconnectedness was fundamentally transforming the nature of human society, and was replacing the sovereign state system with a multi-layered, multilateral system of ‘global governance’. A decade later, however, these expectations appear already falsified by the course of world affairs. The idea of ‘globalization’ no longer captures the ‘spirit of the times’: the ‘age of globalization’ is unexpectedly over. Why has this happened? This article argues that ‘Globalization Theory’ always suffered from basic flaws: as a general social theory; as a historical sociological argument about the nature of modern international relations; and as a guide to the interpretation of empirical events. However, it also offers an alternative, ‘conjunctural analysis’ of the 1990s, in order both to explain the rise and fall of ‘globalization’ itself, and to illustrate the enduring potential for International Relations of those classical approaches which Globalization Theory had sought to displace.</p>",justin rosenberg,,2005.0,10.1057/palgrave.ip.8800098,International Politics,Rosenberg2005,Not available,,Nature,Not available,Globalization Theory: A Post Mortem,ce94c94a4c446eed539277f92567a818,http://dx.doi.org/10.1057/palgrave.ip.8800098
14469,"<p>Taking Robert Kagan's imagery of US-Mars and Europe-Venus as a point of departure, this article probes into how the naturalised reproduction of Europe <i>in the text of the</i> European Security Strategy (ESS) discursively occurs through intermeshing gendered and racialised discourses. The article therefore offers a narrative that has been largely silenced in conversations about the EU as a global security actor. By paying attention to embedded ‘sticky’ gendered and racialised signs in the text of the ESS, the article argues that the delineations drawn to secure Europe in the text of the ESS also engender ‘Europe’ as multiply masculine by dividing the world into sharp spatio-temporal distinctions. Echoing Europe's colonial past, the ESS represents its ‘Others’ as both feminised and subordinate. In this sense, the article argues that the European project of security-development as written in the ESS is both civilising (normative) and violently exclusionary — in contradistinction to many contemporary depictions of Europe as a normative power and a harbour of tolerance. The gendered and colonial grammar of these spatial and temporal distinctions work to naturalise a certain (re)production of ‘Europe’, yet haunt the secure Europe and the better world promised in the strategy.</p>",maria stern,,2011.0,10.1057/jird.2010.7,Journal of International Relations and Development,Stern2011,Not available,,Nature,Not available,Gender and race in the European security strategy: Europe as a ‘force for good’?,82d8f1454341dac434f3657d278f1222,http://dx.doi.org/10.1057/jird.2010.7
14470,"<p>This article replies to an earlier forum <i>(International Politics</i> (42.3) on ‘Globalization Theory: a Post Mortem’. Whereas the ’Post Mortem’ had criticized Globalization Theory largely for its neglect of Classical Social Theory's <i>achievements,</i> the current paper emphasizes its reproduction of one of Classical Social Theory's greatest <i>limitations:</i> the failure to incorporate ‘the international’ into its theorization of historical development. This limitation, it is argued, may be overcome using the idea of ’uneven and combined development’, an idea which is first reformulated (in order to re-connect the premises of social and international theory), and then used as a vantage point from which to respond to criticisms of the ‘Post Mortem’. ‘The international’, it turns out, is not the fading reality postulated by Globalization Theory but rather a fundamental dimension of social existence that IR, uniquely among the social sciences, encounters as its core subject matter.</p>",justin rosenberg,,2007.0,10.1057/palgrave.ip.8800200,International Politics,Rosenberg2007,Not available,,Nature,Not available,International Relations — The ‘Higher Bullshit’: A Reply to the Globalization Theory Debate,6adbece98d892d9cf952244451db7b26,http://dx.doi.org/10.1057/palgrave.ip.8800200
14471,"<p>Obsessional politics gives name to what remains unsaid and under-examined within the contemporary political situation. If obsessional politics may be taken to refer to those tendencies within the political field whose symptomatic condition concerns a demand for novelty, and an avoidance of the goal of authentic novelty via the aim of repetition, it may be further assumed that obsessional politics operates according to the trinity of the obsessional neurotic: self-mastery, repetition, and novelty. Taken together, these three rings form the knot of obsessional politics. This article sets out to demonstrate that it is possible to form a post-obsessional knot by way of Jacques Lacan’s concept of “style,” Slavoj Žižek’s “act,” and Alain Badiou’s “event.”</p>
<span><i>Psychoanalysis, Culture & Society</i> advance online publication, 3 December 2015; doi:<span>10.1057/pcs.2015.62</span></span>",duane rousselle,,2015.0,10.1057/pcs.2015.62,"Psychoanalysis, Culture & Society",Rousselle2015,Not available,,Nature,Not available,Obsession & politics: A contribution to Lacanian political psychoanalysis,cf9302b622511a42ec495de5cb55a270,http://dx.doi.org/10.1057/pcs.2015.62
14472,"<p>This article aims at showing that a plausible conception of global equality of opportunity can be constructed. It starts from the observation that abandoning any egalitarian commitments at the global level would amount to leaving the potential unfairness of global market competitions unaddressed. It then argues that one of the most important objections that has been raised to the ideal of global equality of opportunity — namely, the unavailability of an adequate cross-cultural standard of comparison — can be avoided (at least to a certain extent) if we adopt a ‘competitive’ conception of equality of opportunity. Applied to the global economic context, this conception demands that all equally talented and motivated persons who participate in the global economic order should have a roughly equal chance to enjoy the fruits of global economic interactions, irrespective of the society to which they belong. It places two kinds of demands upon the global rich: (1) ensuring that global economic rules duly represent the interests of all the parties concerned, and (2) ensuring that all the persons who participate in the global economic order are given the capacity to acquire the talents that predict success in the global marketplace.</p>",sylvie loriaux,,2008.0,10.1057/palgrave.jird.1800145,Journal of International Relations and Development,Loriaux2008,Not available,,Nature,Not available,Global equality of opportunity: a proposal,ce6c598693cb07b040d03d6ca20b8268,http://dx.doi.org/10.1057/palgrave.jird.1800145
14473,"<p>The security environment of the Soviet state during the Gorbachev period was distinctly different from earlier periods. The increased number of non-aggressive states in the Soviet Union's international environment further enhanced the security of the regime in historically unprecedented ways. Nuclear weapons freed the Soviet Union from fears of territorial aggression, while making its own expansion too costly. The achievement of military parity with the West gave the Soviets a further enhanced sense of security. Nuclear weapons also created significant common threats from nuclear war, providing strong incentives for accommodation and cooperation. Looking from the post-Cold War era, both Reagan and Gorbachev finally turned out to be anomalies. The particular circumstances that had created the opportunities for extraordinary breakthroughs by the diplomacy of these two men disappeared almost as quickly as they had arisen.</p>",daniel deudney,,2011.0,10.1057/ip.2011.23,International Politics,Deudney2011,Not available,,Nature,Not available,"Pushing and pulling: The Western system, nuclear weapons and Soviet change",49aabea02a2e90a13cdfbb40c325e75f,http://dx.doi.org/10.1057/ip.2011.23
14474,"<p>The security environment of the Soviet state during the Gorbachev period was distinctly different from earlier periods. The increased number of non-aggressive states in the Soviet Union's international environment further enhanced the security of the regime in historically unprecedented ways. Nuclear weapons freed the Soviet Union from fears of territorial aggression, while making its own expansion too costly. The achievement of military parity with the West gave the Soviets a further enhanced sense of security. Nuclear weapons also created significant common threats from nuclear war, providing strong incentives for accommodation and cooperation. Looking from the post-Cold War era, both Reagan and Gorbachev finally turned out to be anomalies. The particular circumstances that had created the opportunities for extraordinary breakthroughs by the diplomacy of these two men disappeared almost as quickly as they had arisen.</p>",g ikenberry,,2011.0,10.1057/ip.2011.23,International Politics,Deudney2011,Not available,,Nature,Not available,"Pushing and pulling: The Western system, nuclear weapons and Soviet change",49aabea02a2e90a13cdfbb40c325e75f,http://dx.doi.org/10.1057/ip.2011.23
14475,"<p>In this paper, we combine the most complete record of daily mobility, based on large-scale mobile phone data, with detailed Geographic Information System (GIS) data, uncovering previously hidden patterns in urban road usage. We find that the major usage of each road segment can be traced to its own - surprisingly few - driver sources. Based on this finding we propose a <i>network of road usage</i> by defining a bipartite network framework, demonstrating that in contrast to traditional approaches, which define road importance solely by topological measures, the role of a road segment depends on both: its betweeness and its degree in the road usage network. Moreover, our ability to pinpoint the few driver sources contributing to the major traffic flow allows us to create a strategy that achieves a significant reduction of the travel time across the entire road system, compared to a benchmark approach.</p>",pu wang,Applied physics,2012.0,10.1038/srep01001,Scientific Reports,Wang2012,Not available,,Nature,Not available,Understanding Road Usage Patterns in Urban Areas,596ebfb66d72795539b3a31b2a2e3428,http://dx.doi.org/10.1038/srep01001
14476,"<p>We consider a Markovian queueing system with <i>N</i> heterogeneous service facilities, each of which has multiple servers available, linear holding costs, a fixed value of service and a first-come-first-serve queue discipline. Customers arriving in the system can be either rejected or sent to one of the <i>N</i> facilities. Two different types of control policies are considered, which we refer to as ‘selfishly optimal’ and ‘socially optimal’. We prove the equivalence of two different Markov Decision Process formulations, and then show that classical <i>M</i>/<i>M</i>/1 queue results from the early literature on behavioural queueing theory can be generalized to multiple dimensions in an elegant way. In particular, the state space of the continuous-time Markov process induced by a socially optimal policy is contained within that of the selfishly optimal policy. We also show that this result holds when customers are divided into an arbitrary number of heterogeneous classes, provided that the service rates remain non-discriminatory.</p>",john minty,,2015.0,10.1057/jors.2015.98,Journal of the Operational Research Society,Shone2015,Not available,,Nature,Not available,Containment of socially optimal policies in multiple-facility Markovian queueing systems,7e14b5751602501225481ed2de4f9fb3,http://dx.doi.org/10.1057/jors.2015.98
14477,"<p>The vulnerability to real-life networks against small initial attacks has been one of outstanding challenges in the study of interrelated networks. We study cascading failures in two interrelated networks <b><i>S</i></b> and <b><i>B</i></b> composed from dependency chains and connectivity links respectively. This work proposes a realistic model for cascading failures based on the redistribution of traffic flow. We study the Barabási-Albert networks (<b><i>BA</i></b>) and Erdős-Rényi graphs (<b><i>ER</i></b>) with such structure, and found that the efficiency sharply decreases with increasing percentages of the dependency nodes for removing a node randomly. Furthermore, we study the robustness of interrelated traffic networks, especially the subway and bus network in Beijing. By analyzing different attacking strategies, we uncover that the efficiency of the city traffic system has a non-equilibrium phase transition at low capacity of the networks. This explains why the pressure of the traffic overload is relaxed by singly increasing the number of small buses during rush hours. We also found that the increment of some buses may release traffic jam caused by removing a node of the bus network randomly if the damage is limited. However, the efficiencies to transfer people flow will sharper increase when the capacity of the subway network <b><i>α<sub>S</sub></i> > <i>α</i><sub>0</sub></b>.</p>",haipeng peng,Statistical physics,2014.0,10.1038/srep05413,Scientific Reports,Su2014,Not available,,Nature,Not available,Robustness of Interrelated Traffic Networks to Cascading Failures,4840ca15ebd58b9a2e9f7ee719c39054,http://dx.doi.org/10.1038/srep05413
14478,"<p>In this paper, we combine the most complete record of daily mobility, based on large-scale mobile phone data, with detailed Geographic Information System (GIS) data, uncovering previously hidden patterns in urban road usage. We find that the major usage of each road segment can be traced to its own - surprisingly few - driver sources. Based on this finding we propose a <i>network of road usage</i> by defining a bipartite network framework, demonstrating that in contrast to traditional approaches, which define road importance solely by topological measures, the role of a road segment depends on both: its betweeness and its degree in the road usage network. Moreover, our ability to pinpoint the few driver sources contributing to the major traffic flow allows us to create a strategy that achieves a significant reduction of the travel time across the entire road system, compared to a benchmark approach.</p>",pu wang,Civil engineering,2012.0,10.1038/srep01001,Scientific Reports,Wang2012,Not available,,Nature,Not available,Understanding Road Usage Patterns in Urban Areas,596ebfb66d72795539b3a31b2a2e3428,http://dx.doi.org/10.1038/srep01001
14479,"<p>In this paper, we combine the most complete record of daily mobility, based on large-scale mobile phone data, with detailed Geographic Information System (GIS) data, uncovering previously hidden patterns in urban road usage. We find that the major usage of each road segment can be traced to its own - surprisingly few - driver sources. Based on this finding we propose a <i>network of road usage</i> by defining a bipartite network framework, demonstrating that in contrast to traditional approaches, which define road importance solely by topological measures, the role of a road segment depends on both: its betweeness and its degree in the road usage network. Moreover, our ability to pinpoint the few driver sources contributing to the major traffic flow allows us to create a strategy that achieves a significant reduction of the travel time across the entire road system, compared to a benchmark approach.</p>",pu wang,Statistical physics  thermodynamics and nonlinear dynamics,2012.0,10.1038/srep01001,Scientific Reports,Wang2012,Not available,,Nature,Not available,Understanding Road Usage Patterns in Urban Areas,596ebfb66d72795539b3a31b2a2e3428,http://dx.doi.org/10.1038/srep01001
14480,"<p>In this paper, we combine the most complete record of daily mobility, based on large-scale mobile phone data, with detailed Geographic Information System (GIS) data, uncovering previously hidden patterns in urban road usage. We find that the major usage of each road segment can be traced to its own - surprisingly few - driver sources. Based on this finding we propose a <i>network of road usage</i> by defining a bipartite network framework, demonstrating that in contrast to traditional approaches, which define road importance solely by topological measures, the role of a road segment depends on both: its betweeness and its degree in the road usage network. Moreover, our ability to pinpoint the few driver sources contributing to the major traffic flow allows us to create a strategy that achieves a significant reduction of the travel time across the entire road system, compared to a benchmark approach.</p>",pu wang,Statistics,2012.0,10.1038/srep01001,Scientific Reports,Wang2012,Not available,,Nature,Not available,Understanding Road Usage Patterns in Urban Areas,596ebfb66d72795539b3a31b2a2e3428,http://dx.doi.org/10.1038/srep01001
14481,"<p>In this paper, we combine the most complete record of daily mobility, based on large-scale mobile phone data, with detailed Geographic Information System (GIS) data, uncovering previously hidden patterns in urban road usage. We find that the major usage of each road segment can be traced to its own - surprisingly few - driver sources. Based on this finding we propose a <i>network of road usage</i> by defining a bipartite network framework, demonstrating that in contrast to traditional approaches, which define road importance solely by topological measures, the role of a road segment depends on both: its betweeness and its degree in the road usage network. Moreover, our ability to pinpoint the few driver sources contributing to the major traffic flow allows us to create a strategy that achieves a significant reduction of the travel time across the entire road system, compared to a benchmark approach.</p>",timothy hunter,Applied physics,2012.0,10.1038/srep01001,Scientific Reports,Wang2012,Not available,,Nature,Not available,Understanding Road Usage Patterns in Urban Areas,596ebfb66d72795539b3a31b2a2e3428,http://dx.doi.org/10.1038/srep01001
14482,"<p>In this paper, we combine the most complete record of daily mobility, based on large-scale mobile phone data, with detailed Geographic Information System (GIS) data, uncovering previously hidden patterns in urban road usage. We find that the major usage of each road segment can be traced to its own - surprisingly few - driver sources. Based on this finding we propose a <i>network of road usage</i> by defining a bipartite network framework, demonstrating that in contrast to traditional approaches, which define road importance solely by topological measures, the role of a road segment depends on both: its betweeness and its degree in the road usage network. Moreover, our ability to pinpoint the few driver sources contributing to the major traffic flow allows us to create a strategy that achieves a significant reduction of the travel time across the entire road system, compared to a benchmark approach.</p>",timothy hunter,Civil engineering,2012.0,10.1038/srep01001,Scientific Reports,Wang2012,Not available,,Nature,Not available,Understanding Road Usage Patterns in Urban Areas,596ebfb66d72795539b3a31b2a2e3428,http://dx.doi.org/10.1038/srep01001
14483,"<p>In this paper, we combine the most complete record of daily mobility, based on large-scale mobile phone data, with detailed Geographic Information System (GIS) data, uncovering previously hidden patterns in urban road usage. We find that the major usage of each road segment can be traced to its own - surprisingly few - driver sources. Based on this finding we propose a <i>network of road usage</i> by defining a bipartite network framework, demonstrating that in contrast to traditional approaches, which define road importance solely by topological measures, the role of a road segment depends on both: its betweeness and its degree in the road usage network. Moreover, our ability to pinpoint the few driver sources contributing to the major traffic flow allows us to create a strategy that achieves a significant reduction of the travel time across the entire road system, compared to a benchmark approach.</p>",timothy hunter,Statistical physics  thermodynamics and nonlinear dynamics,2012.0,10.1038/srep01001,Scientific Reports,Wang2012,Not available,,Nature,Not available,Understanding Road Usage Patterns in Urban Areas,596ebfb66d72795539b3a31b2a2e3428,http://dx.doi.org/10.1038/srep01001
14484,"<p>In this paper, we combine the most complete record of daily mobility, based on large-scale mobile phone data, with detailed Geographic Information System (GIS) data, uncovering previously hidden patterns in urban road usage. We find that the major usage of each road segment can be traced to its own - surprisingly few - driver sources. Based on this finding we propose a <i>network of road usage</i> by defining a bipartite network framework, demonstrating that in contrast to traditional approaches, which define road importance solely by topological measures, the role of a road segment depends on both: its betweeness and its degree in the road usage network. Moreover, our ability to pinpoint the few driver sources contributing to the major traffic flow allows us to create a strategy that achieves a significant reduction of the travel time across the entire road system, compared to a benchmark approach.</p>",timothy hunter,Statistics,2012.0,10.1038/srep01001,Scientific Reports,Wang2012,Not available,,Nature,Not available,Understanding Road Usage Patterns in Urban Areas,596ebfb66d72795539b3a31b2a2e3428,http://dx.doi.org/10.1038/srep01001
14485,"<p>In this paper, we combine the most complete record of daily mobility, based on large-scale mobile phone data, with detailed Geographic Information System (GIS) data, uncovering previously hidden patterns in urban road usage. We find that the major usage of each road segment can be traced to its own - surprisingly few - driver sources. Based on this finding we propose a <i>network of road usage</i> by defining a bipartite network framework, demonstrating that in contrast to traditional approaches, which define road importance solely by topological measures, the role of a road segment depends on both: its betweeness and its degree in the road usage network. Moreover, our ability to pinpoint the few driver sources contributing to the major traffic flow allows us to create a strategy that achieves a significant reduction of the travel time across the entire road system, compared to a benchmark approach.</p>",alexandre bayen,Applied physics,2012.0,10.1038/srep01001,Scientific Reports,Wang2012,Not available,,Nature,Not available,Understanding Road Usage Patterns in Urban Areas,596ebfb66d72795539b3a31b2a2e3428,http://dx.doi.org/10.1038/srep01001
14486,"<p>In this paper, we combine the most complete record of daily mobility, based on large-scale mobile phone data, with detailed Geographic Information System (GIS) data, uncovering previously hidden patterns in urban road usage. We find that the major usage of each road segment can be traced to its own - surprisingly few - driver sources. Based on this finding we propose a <i>network of road usage</i> by defining a bipartite network framework, demonstrating that in contrast to traditional approaches, which define road importance solely by topological measures, the role of a road segment depends on both: its betweeness and its degree in the road usage network. Moreover, our ability to pinpoint the few driver sources contributing to the major traffic flow allows us to create a strategy that achieves a significant reduction of the travel time across the entire road system, compared to a benchmark approach.</p>",alexandre bayen,Civil engineering,2012.0,10.1038/srep01001,Scientific Reports,Wang2012,Not available,,Nature,Not available,Understanding Road Usage Patterns in Urban Areas,596ebfb66d72795539b3a31b2a2e3428,http://dx.doi.org/10.1038/srep01001
14487,"<p>In this paper, we combine the most complete record of daily mobility, based on large-scale mobile phone data, with detailed Geographic Information System (GIS) data, uncovering previously hidden patterns in urban road usage. We find that the major usage of each road segment can be traced to its own - surprisingly few - driver sources. Based on this finding we propose a <i>network of road usage</i> by defining a bipartite network framework, demonstrating that in contrast to traditional approaches, which define road importance solely by topological measures, the role of a road segment depends on both: its betweeness and its degree in the road usage network. Moreover, our ability to pinpoint the few driver sources contributing to the major traffic flow allows us to create a strategy that achieves a significant reduction of the travel time across the entire road system, compared to a benchmark approach.</p>",alexandre bayen,Statistical physics  thermodynamics and nonlinear dynamics,2012.0,10.1038/srep01001,Scientific Reports,Wang2012,Not available,,Nature,Not available,Understanding Road Usage Patterns in Urban Areas,596ebfb66d72795539b3a31b2a2e3428,http://dx.doi.org/10.1038/srep01001
14488,"<p>The vulnerability to real-life networks against small initial attacks has been one of outstanding challenges in the study of interrelated networks. We study cascading failures in two interrelated networks <b><i>S</i></b> and <b><i>B</i></b> composed from dependency chains and connectivity links respectively. This work proposes a realistic model for cascading failures based on the redistribution of traffic flow. We study the Barabási-Albert networks (<b><i>BA</i></b>) and Erdős-Rényi graphs (<b><i>ER</i></b>) with such structure, and found that the efficiency sharply decreases with increasing percentages of the dependency nodes for removing a node randomly. Furthermore, we study the robustness of interrelated traffic networks, especially the subway and bus network in Beijing. By analyzing different attacking strategies, we uncover that the efficiency of the city traffic system has a non-equilibrium phase transition at low capacity of the networks. This explains why the pressure of the traffic overload is relaxed by singly increasing the number of small buses during rush hours. We also found that the increment of some buses may release traffic jam caused by removing a node of the bus network randomly if the damage is limited. However, the efficiencies to transfer people flow will sharper increase when the capacity of the subway network <b><i>α<sub>S</sub></i> > <i>α</i><sub>0</sub></b>.</p>",jurgen kurths,Complex networks,2014.0,10.1038/srep05413,Scientific Reports,Su2014,Not available,,Nature,Not available,Robustness of Interrelated Traffic Networks to Cascading Failures,4840ca15ebd58b9a2e9f7ee719c39054,http://dx.doi.org/10.1038/srep05413
14489,"<p>In this paper, we combine the most complete record of daily mobility, based on large-scale mobile phone data, with detailed Geographic Information System (GIS) data, uncovering previously hidden patterns in urban road usage. We find that the major usage of each road segment can be traced to its own - surprisingly few - driver sources. Based on this finding we propose a <i>network of road usage</i> by defining a bipartite network framework, demonstrating that in contrast to traditional approaches, which define road importance solely by topological measures, the role of a road segment depends on both: its betweeness and its degree in the road usage network. Moreover, our ability to pinpoint the few driver sources contributing to the major traffic flow allows us to create a strategy that achieves a significant reduction of the travel time across the entire road system, compared to a benchmark approach.</p>",alexandre bayen,Statistics,2012.0,10.1038/srep01001,Scientific Reports,Wang2012,Not available,,Nature,Not available,Understanding Road Usage Patterns in Urban Areas,596ebfb66d72795539b3a31b2a2e3428,http://dx.doi.org/10.1038/srep01001
14490,"<p>In this paper, we combine the most complete record of daily mobility, based on large-scale mobile phone data, with detailed Geographic Information System (GIS) data, uncovering previously hidden patterns in urban road usage. We find that the major usage of each road segment can be traced to its own - surprisingly few - driver sources. Based on this finding we propose a <i>network of road usage</i> by defining a bipartite network framework, demonstrating that in contrast to traditional approaches, which define road importance solely by topological measures, the role of a road segment depends on both: its betweeness and its degree in the road usage network. Moreover, our ability to pinpoint the few driver sources contributing to the major traffic flow allows us to create a strategy that achieves a significant reduction of the travel time across the entire road system, compared to a benchmark approach.</p>",katja schechtner,Applied physics,2012.0,10.1038/srep01001,Scientific Reports,Wang2012,Not available,,Nature,Not available,Understanding Road Usage Patterns in Urban Areas,596ebfb66d72795539b3a31b2a2e3428,http://dx.doi.org/10.1038/srep01001
14491,"<p>In this paper, we combine the most complete record of daily mobility, based on large-scale mobile phone data, with detailed Geographic Information System (GIS) data, uncovering previously hidden patterns in urban road usage. We find that the major usage of each road segment can be traced to its own - surprisingly few - driver sources. Based on this finding we propose a <i>network of road usage</i> by defining a bipartite network framework, demonstrating that in contrast to traditional approaches, which define road importance solely by topological measures, the role of a road segment depends on both: its betweeness and its degree in the road usage network. Moreover, our ability to pinpoint the few driver sources contributing to the major traffic flow allows us to create a strategy that achieves a significant reduction of the travel time across the entire road system, compared to a benchmark approach.</p>",katja schechtner,Civil engineering,2012.0,10.1038/srep01001,Scientific Reports,Wang2012,Not available,,Nature,Not available,Understanding Road Usage Patterns in Urban Areas,596ebfb66d72795539b3a31b2a2e3428,http://dx.doi.org/10.1038/srep01001
14492,"<p>In this paper, we combine the most complete record of daily mobility, based on large-scale mobile phone data, with detailed Geographic Information System (GIS) data, uncovering previously hidden patterns in urban road usage. We find that the major usage of each road segment can be traced to its own - surprisingly few - driver sources. Based on this finding we propose a <i>network of road usage</i> by defining a bipartite network framework, demonstrating that in contrast to traditional approaches, which define road importance solely by topological measures, the role of a road segment depends on both: its betweeness and its degree in the road usage network. Moreover, our ability to pinpoint the few driver sources contributing to the major traffic flow allows us to create a strategy that achieves a significant reduction of the travel time across the entire road system, compared to a benchmark approach.</p>",katja schechtner,Statistical physics  thermodynamics and nonlinear dynamics,2012.0,10.1038/srep01001,Scientific Reports,Wang2012,Not available,,Nature,Not available,Understanding Road Usage Patterns in Urban Areas,596ebfb66d72795539b3a31b2a2e3428,http://dx.doi.org/10.1038/srep01001
14493,"<p>In this paper, we combine the most complete record of daily mobility, based on large-scale mobile phone data, with detailed Geographic Information System (GIS) data, uncovering previously hidden patterns in urban road usage. We find that the major usage of each road segment can be traced to its own - surprisingly few - driver sources. Based on this finding we propose a <i>network of road usage</i> by defining a bipartite network framework, demonstrating that in contrast to traditional approaches, which define road importance solely by topological measures, the role of a road segment depends on both: its betweeness and its degree in the road usage network. Moreover, our ability to pinpoint the few driver sources contributing to the major traffic flow allows us to create a strategy that achieves a significant reduction of the travel time across the entire road system, compared to a benchmark approach.</p>",katja schechtner,Statistics,2012.0,10.1038/srep01001,Scientific Reports,Wang2012,Not available,,Nature,Not available,Understanding Road Usage Patterns in Urban Areas,596ebfb66d72795539b3a31b2a2e3428,http://dx.doi.org/10.1038/srep01001
14494,"<p>In this paper, we combine the most complete record of daily mobility, based on large-scale mobile phone data, with detailed Geographic Information System (GIS) data, uncovering previously hidden patterns in urban road usage. We find that the major usage of each road segment can be traced to its own - surprisingly few - driver sources. Based on this finding we propose a <i>network of road usage</i> by defining a bipartite network framework, demonstrating that in contrast to traditional approaches, which define road importance solely by topological measures, the role of a road segment depends on both: its betweeness and its degree in the road usage network. Moreover, our ability to pinpoint the few driver sources contributing to the major traffic flow allows us to create a strategy that achieves a significant reduction of the travel time across the entire road system, compared to a benchmark approach.</p>",marta gonzalez,Applied physics,2012.0,10.1038/srep01001,Scientific Reports,Wang2012,Not available,,Nature,Not available,Understanding Road Usage Patterns in Urban Areas,596ebfb66d72795539b3a31b2a2e3428,http://dx.doi.org/10.1038/srep01001
14495,"<p>In this paper, we combine the most complete record of daily mobility, based on large-scale mobile phone data, with detailed Geographic Information System (GIS) data, uncovering previously hidden patterns in urban road usage. We find that the major usage of each road segment can be traced to its own - surprisingly few - driver sources. Based on this finding we propose a <i>network of road usage</i> by defining a bipartite network framework, demonstrating that in contrast to traditional approaches, which define road importance solely by topological measures, the role of a road segment depends on both: its betweeness and its degree in the road usage network. Moreover, our ability to pinpoint the few driver sources contributing to the major traffic flow allows us to create a strategy that achieves a significant reduction of the travel time across the entire road system, compared to a benchmark approach.</p>",marta gonzalez,Civil engineering,2012.0,10.1038/srep01001,Scientific Reports,Wang2012,Not available,,Nature,Not available,Understanding Road Usage Patterns in Urban Areas,596ebfb66d72795539b3a31b2a2e3428,http://dx.doi.org/10.1038/srep01001
14496,"<p>In this paper, we combine the most complete record of daily mobility, based on large-scale mobile phone data, with detailed Geographic Information System (GIS) data, uncovering previously hidden patterns in urban road usage. We find that the major usage of each road segment can be traced to its own - surprisingly few - driver sources. Based on this finding we propose a <i>network of road usage</i> by defining a bipartite network framework, demonstrating that in contrast to traditional approaches, which define road importance solely by topological measures, the role of a road segment depends on both: its betweeness and its degree in the road usage network. Moreover, our ability to pinpoint the few driver sources contributing to the major traffic flow allows us to create a strategy that achieves a significant reduction of the travel time across the entire road system, compared to a benchmark approach.</p>",marta gonzalez,Statistical physics  thermodynamics and nonlinear dynamics,2012.0,10.1038/srep01001,Scientific Reports,Wang2012,Not available,,Nature,Not available,Understanding Road Usage Patterns in Urban Areas,596ebfb66d72795539b3a31b2a2e3428,http://dx.doi.org/10.1038/srep01001
14497,"<p>In this paper, we combine the most complete record of daily mobility, based on large-scale mobile phone data, with detailed Geographic Information System (GIS) data, uncovering previously hidden patterns in urban road usage. We find that the major usage of each road segment can be traced to its own - surprisingly few - driver sources. Based on this finding we propose a <i>network of road usage</i> by defining a bipartite network framework, demonstrating that in contrast to traditional approaches, which define road importance solely by topological measures, the role of a road segment depends on both: its betweeness and its degree in the road usage network. Moreover, our ability to pinpoint the few driver sources contributing to the major traffic flow allows us to create a strategy that achieves a significant reduction of the travel time across the entire road system, compared to a benchmark approach.</p>",marta gonzalez,Statistics,2012.0,10.1038/srep01001,Scientific Reports,Wang2012,Not available,,Nature,Not available,Understanding Road Usage Patterns in Urban Areas,596ebfb66d72795539b3a31b2a2e3428,http://dx.doi.org/10.1038/srep01001
14498,"<p>This article examines how external third parties, particularly international organizations, can facilitate the development of security community and international integration within post-conflict societies. Focusing on seven countries in the Western Balkan region, this study offers unique insight into how and why feelings of trust and a sense of community can be encouraged by external actors – the EU and NATO in this case – and how and if trust and community can filter down to the most local levels within post-conflict societies. Ultimately, we argue that both the EU and NATO have, primarily through membership requirements to engage in regional interaction and cooperation, significantly contributed to the development of security community among Western Balkan neighbors at the elite level. However, we also find that feelings of trust and belongingness are still very much lacking among the general population of the Western Balkan region. Such insights will further efforts to enhance conflict resolution and post-conflict reconstruction in the Western Balkans and elsewhere.</p>",suzette grillot,,2009.0,10.1057/ip.2009.26,International Politics,Grillot2009,Not available,,Nature,Not available,Developing security community in the Western Balkans: The role of the EU and NATO,64a8e7f08b63d76612e52ba249629b51,http://dx.doi.org/10.1057/ip.2009.26
14499,"<p>The vulnerability to real-life networks against small initial attacks has been one of outstanding challenges in the study of interrelated networks. We study cascading failures in two interrelated networks <b><i>S</i></b> and <b><i>B</i></b> composed from dependency chains and connectivity links respectively. This work proposes a realistic model for cascading failures based on the redistribution of traffic flow. We study the Barabási-Albert networks (<b><i>BA</i></b>) and Erdős-Rényi graphs (<b><i>ER</i></b>) with such structure, and found that the efficiency sharply decreases with increasing percentages of the dependency nodes for removing a node randomly. Furthermore, we study the robustness of interrelated traffic networks, especially the subway and bus network in Beijing. By analyzing different attacking strategies, we uncover that the efficiency of the city traffic system has a non-equilibrium phase transition at low capacity of the networks. This explains why the pressure of the traffic overload is relaxed by singly increasing the number of small buses during rush hours. We also found that the increment of some buses may release traffic jam caused by removing a node of the bus network randomly if the damage is limited. However, the efficiencies to transfer people flow will sharper increase when the capacity of the subway network <b><i>α<sub>S</sub></i> > <i>α</i><sub>0</sub></b>.</p>",jurgen kurths,Nonlinear phenomena,2014.0,10.1038/srep05413,Scientific Reports,Su2014,Not available,,Nature,Not available,Robustness of Interrelated Traffic Networks to Cascading Failures,4840ca15ebd58b9a2e9f7ee719c39054,http://dx.doi.org/10.1038/srep05413
14500,"<p>This article examines how external third parties, particularly international organizations, can facilitate the development of security community and international integration within post-conflict societies. Focusing on seven countries in the Western Balkan region, this study offers unique insight into how and why feelings of trust and a sense of community can be encouraged by external actors – the EU and NATO in this case – and how and if trust and community can filter down to the most local levels within post-conflict societies. Ultimately, we argue that both the EU and NATO have, primarily through membership requirements to engage in regional interaction and cooperation, significantly contributed to the development of security community among Western Balkan neighbors at the elite level. However, we also find that feelings of trust and belongingness are still very much lacking among the general population of the Western Balkan region. Such insights will further efforts to enhance conflict resolution and post-conflict reconstruction in the Western Balkans and elsewhere.</p>",rebecca cruise,,2009.0,10.1057/ip.2009.26,International Politics,Grillot2009,Not available,,Nature,Not available,Developing security community in the Western Balkans: The role of the EU and NATO,64a8e7f08b63d76612e52ba249629b51,http://dx.doi.org/10.1057/ip.2009.26
14501,"<p>This article examines how external third parties, particularly international organizations, can facilitate the development of security community and international integration within post-conflict societies. Focusing on seven countries in the Western Balkan region, this study offers unique insight into how and why feelings of trust and a sense of community can be encouraged by external actors – the EU and NATO in this case – and how and if trust and community can filter down to the most local levels within post-conflict societies. Ultimately, we argue that both the EU and NATO have, primarily through membership requirements to engage in regional interaction and cooperation, significantly contributed to the development of security community among Western Balkan neighbors at the elite level. However, we also find that feelings of trust and belongingness are still very much lacking among the general population of the Western Balkan region. Such insights will further efforts to enhance conflict resolution and post-conflict reconstruction in the Western Balkans and elsewhere.</p>",valerie d'erman,,2009.0,10.1057/ip.2009.26,International Politics,Grillot2009,Not available,,Nature,Not available,Developing security community in the Western Balkans: The role of the EU and NATO,64a8e7f08b63d76612e52ba249629b51,http://dx.doi.org/10.1057/ip.2009.26
14502,"<p>This article argues that the American empire cannot be fully understood without reference to the ways in which American imperial identities have been associated with the historical experience of England/Britain. To make this argument, the article considers four discourses of identity in particular – Anglo-Protestantism (religion), Anglo-Saxonism (ethnicity/race), Anglo-Saxon capitalism (institutions) and English (language). US imperial development was conditioned by many forces, but none match the aggregate power of America's ‘Anglo-ness’. Although it is too early to assess the ways in which these discourses are negotiated, critiqued and reproduced in the ‘age of Obama’, the American empire is likely to continue to protect and project Anglo-ness <i>vis-à-vis</i> to the rest of the world.</p>",srdjan vucetic,,2011.0,10.1057/ip.2011.14,International Politics,Vucetic2011,Not available,,Nature,Not available,What is so American about the American empire?,1e182871f74671795b6e028466543f57,http://dx.doi.org/10.1057/ip.2011.14
14503,"<p>Common sense suggests that networks are not random mazes of purposeless connections, but that these connections are organized so that networks can perform their functions well. One function common to many networks is targeted transport or navigation. Here, using game theory, we show that minimalistic networks designed to maximize the navigation efficiency at minimal cost share basic structural properties with real networks. These idealistic networks are Nash equilibria of a network construction game whose purpose is to find an optimal trade-off between the network cost and navigability. We show that these skeletons are present in the Internet, metabolic, English word, US airport, Hungarian road networks, and in a structural network of the human brain. The knowledge of these skeletons allows one to identify the minimal number of edges, by altering which one can efficiently improve or paralyse navigation in the network.</p>",andras gulyas,Networks and systems biology,2015.0,10.1038/ncomms8651,Nature Communications,Gulyás2015,Not available,,Nature,Not available,Navigable networks as Nash equilibria of navigation games,86c95a66d686df043fc8390df8eb33e5,http://dx.doi.org/10.1038/ncomms8651
14504,"<p>Common sense suggests that networks are not random mazes of purposeless connections, but that these connections are organized so that networks can perform their functions well. One function common to many networks is targeted transport or navigation. Here, using game theory, we show that minimalistic networks designed to maximize the navigation efficiency at minimal cost share basic structural properties with real networks. These idealistic networks are Nash equilibria of a network construction game whose purpose is to find an optimal trade-off between the network cost and navigability. We show that these skeletons are present in the Internet, metabolic, English word, US airport, Hungarian road networks, and in a structural network of the human brain. The knowledge of these skeletons allows one to identify the minimal number of edges, by altering which one can efficiently improve or paralyse navigation in the network.</p>",andras gulyas,Theoretical physics,2015.0,10.1038/ncomms8651,Nature Communications,Gulyás2015,Not available,,Nature,Not available,Navigable networks as Nash equilibria of navigation games,86c95a66d686df043fc8390df8eb33e5,http://dx.doi.org/10.1038/ncomms8651
14505,"<p>Common sense suggests that networks are not random mazes of purposeless connections, but that these connections are organized so that networks can perform their functions well. One function common to many networks is targeted transport or navigation. Here, using game theory, we show that minimalistic networks designed to maximize the navigation efficiency at minimal cost share basic structural properties with real networks. These idealistic networks are Nash equilibria of a network construction game whose purpose is to find an optimal trade-off between the network cost and navigability. We show that these skeletons are present in the Internet, metabolic, English word, US airport, Hungarian road networks, and in a structural network of the human brain. The knowledge of these skeletons allows one to identify the minimal number of edges, by altering which one can efficiently improve or paralyse navigation in the network.</p>",jozsef biro,Networks and systems biology,2015.0,10.1038/ncomms8651,Nature Communications,Gulyás2015,Not available,,Nature,Not available,Navigable networks as Nash equilibria of navigation games,86c95a66d686df043fc8390df8eb33e5,http://dx.doi.org/10.1038/ncomms8651
14506,"<p>Common sense suggests that networks are not random mazes of purposeless connections, but that these connections are organized so that networks can perform their functions well. One function common to many networks is targeted transport or navigation. Here, using game theory, we show that minimalistic networks designed to maximize the navigation efficiency at minimal cost share basic structural properties with real networks. These idealistic networks are Nash equilibria of a network construction game whose purpose is to find an optimal trade-off between the network cost and navigability. We show that these skeletons are present in the Internet, metabolic, English word, US airport, Hungarian road networks, and in a structural network of the human brain. The knowledge of these skeletons allows one to identify the minimal number of edges, by altering which one can efficiently improve or paralyse navigation in the network.</p>",jozsef biro,Theoretical physics,2015.0,10.1038/ncomms8651,Nature Communications,Gulyás2015,Not available,,Nature,Not available,Navigable networks as Nash equilibria of navigation games,86c95a66d686df043fc8390df8eb33e5,http://dx.doi.org/10.1038/ncomms8651
14507,"<p>Common sense suggests that networks are not random mazes of purposeless connections, but that these connections are organized so that networks can perform their functions well. One function common to many networks is targeted transport or navigation. Here, using game theory, we show that minimalistic networks designed to maximize the navigation efficiency at minimal cost share basic structural properties with real networks. These idealistic networks are Nash equilibria of a network construction game whose purpose is to find an optimal trade-off between the network cost and navigability. We show that these skeletons are present in the Internet, metabolic, English word, US airport, Hungarian road networks, and in a structural network of the human brain. The knowledge of these skeletons allows one to identify the minimal number of edges, by altering which one can efficiently improve or paralyse navigation in the network.</p>",attila korosi,Networks and systems biology,2015.0,10.1038/ncomms8651,Nature Communications,Gulyás2015,Not available,,Nature,Not available,Navigable networks as Nash equilibria of navigation games,86c95a66d686df043fc8390df8eb33e5,http://dx.doi.org/10.1038/ncomms8651
14508,"<p>Common sense suggests that networks are not random mazes of purposeless connections, but that these connections are organized so that networks can perform their functions well. One function common to many networks is targeted transport or navigation. Here, using game theory, we show that minimalistic networks designed to maximize the navigation efficiency at minimal cost share basic structural properties with real networks. These idealistic networks are Nash equilibria of a network construction game whose purpose is to find an optimal trade-off between the network cost and navigability. We show that these skeletons are present in the Internet, metabolic, English word, US airport, Hungarian road networks, and in a structural network of the human brain. The knowledge of these skeletons allows one to identify the minimal number of edges, by altering which one can efficiently improve or paralyse navigation in the network.</p>",attila korosi,Theoretical physics,2015.0,10.1038/ncomms8651,Nature Communications,Gulyás2015,Not available,,Nature,Not available,Navigable networks as Nash equilibria of navigation games,86c95a66d686df043fc8390df8eb33e5,http://dx.doi.org/10.1038/ncomms8651
14509,"<p>Common sense suggests that networks are not random mazes of purposeless connections, but that these connections are organized so that networks can perform their functions well. One function common to many networks is targeted transport or navigation. Here, using game theory, we show that minimalistic networks designed to maximize the navigation efficiency at minimal cost share basic structural properties with real networks. These idealistic networks are Nash equilibria of a network construction game whose purpose is to find an optimal trade-off between the network cost and navigability. We show that these skeletons are present in the Internet, metabolic, English word, US airport, Hungarian road networks, and in a structural network of the human brain. The knowledge of these skeletons allows one to identify the minimal number of edges, by altering which one can efficiently improve or paralyse navigation in the network.</p>",gabor retvari,Networks and systems biology,2015.0,10.1038/ncomms8651,Nature Communications,Gulyás2015,Not available,,Nature,Not available,Navigable networks as Nash equilibria of navigation games,86c95a66d686df043fc8390df8eb33e5,http://dx.doi.org/10.1038/ncomms8651
14510,"<p>The vulnerability to real-life networks against small initial attacks has been one of outstanding challenges in the study of interrelated networks. We study cascading failures in two interrelated networks <b><i>S</i></b> and <b><i>B</i></b> composed from dependency chains and connectivity links respectively. This work proposes a realistic model for cascading failures based on the redistribution of traffic flow. We study the Barabási-Albert networks (<b><i>BA</i></b>) and Erdős-Rényi graphs (<b><i>ER</i></b>) with such structure, and found that the efficiency sharply decreases with increasing percentages of the dependency nodes for removing a node randomly. Furthermore, we study the robustness of interrelated traffic networks, especially the subway and bus network in Beijing. By analyzing different attacking strategies, we uncover that the efficiency of the city traffic system has a non-equilibrium phase transition at low capacity of the networks. This explains why the pressure of the traffic overload is relaxed by singly increasing the number of small buses during rush hours. We also found that the increment of some buses may release traffic jam caused by removing a node of the bus network randomly if the damage is limited. However, the efficiencies to transfer people flow will sharper increase when the capacity of the subway network <b><i>α<sub>S</sub></i> > <i>α</i><sub>0</sub></b>.</p>",jurgen kurths,Statistical physics,2014.0,10.1038/srep05413,Scientific Reports,Su2014,Not available,,Nature,Not available,Robustness of Interrelated Traffic Networks to Cascading Failures,4840ca15ebd58b9a2e9f7ee719c39054,http://dx.doi.org/10.1038/srep05413
14511,"<p>Common sense suggests that networks are not random mazes of purposeless connections, but that these connections are organized so that networks can perform their functions well. One function common to many networks is targeted transport or navigation. Here, using game theory, we show that minimalistic networks designed to maximize the navigation efficiency at minimal cost share basic structural properties with real networks. These idealistic networks are Nash equilibria of a network construction game whose purpose is to find an optimal trade-off between the network cost and navigability. We show that these skeletons are present in the Internet, metabolic, English word, US airport, Hungarian road networks, and in a structural network of the human brain. The knowledge of these skeletons allows one to identify the minimal number of edges, by altering which one can efficiently improve or paralyse navigation in the network.</p>",gabor retvari,Theoretical physics,2015.0,10.1038/ncomms8651,Nature Communications,Gulyás2015,Not available,,Nature,Not available,Navigable networks as Nash equilibria of navigation games,86c95a66d686df043fc8390df8eb33e5,http://dx.doi.org/10.1038/ncomms8651
14512,"<p>Common sense suggests that networks are not random mazes of purposeless connections, but that these connections are organized so that networks can perform their functions well. One function common to many networks is targeted transport or navigation. Here, using game theory, we show that minimalistic networks designed to maximize the navigation efficiency at minimal cost share basic structural properties with real networks. These idealistic networks are Nash equilibria of a network construction game whose purpose is to find an optimal trade-off between the network cost and navigability. We show that these skeletons are present in the Internet, metabolic, English word, US airport, Hungarian road networks, and in a structural network of the human brain. The knowledge of these skeletons allows one to identify the minimal number of edges, by altering which one can efficiently improve or paralyse navigation in the network.</p>",dmitri krioukov,Networks and systems biology,2015.0,10.1038/ncomms8651,Nature Communications,Gulyás2015,Not available,,Nature,Not available,Navigable networks as Nash equilibria of navigation games,86c95a66d686df043fc8390df8eb33e5,http://dx.doi.org/10.1038/ncomms8651
14513,"<p>Common sense suggests that networks are not random mazes of purposeless connections, but that these connections are organized so that networks can perform their functions well. One function common to many networks is targeted transport or navigation. Here, using game theory, we show that minimalistic networks designed to maximize the navigation efficiency at minimal cost share basic structural properties with real networks. These idealistic networks are Nash equilibria of a network construction game whose purpose is to find an optimal trade-off between the network cost and navigability. We show that these skeletons are present in the Internet, metabolic, English word, US airport, Hungarian road networks, and in a structural network of the human brain. The knowledge of these skeletons allows one to identify the minimal number of edges, by altering which one can efficiently improve or paralyse navigation in the network.</p>",dmitri krioukov,Theoretical physics,2015.0,10.1038/ncomms8651,Nature Communications,Gulyás2015,Not available,,Nature,Not available,Navigable networks as Nash equilibria of navigation games,86c95a66d686df043fc8390df8eb33e5,http://dx.doi.org/10.1038/ncomms8651
14514,"<p>The Kantian peace theory emphasises the mutually enforcing pacifying effects of democracy and economic interdependence. Nevertheless, the last decade, which has seen record levels of interdependence and democratisation, provides anecdotal evidence that challenges the simplicity of the democracy–interdependence–peace argument. In this paper, I contrast Kant’s approach to this conundrum with that of Rousseau’s. While Kant’s well-known argument suggests a mutually reinforcing relation between democracy, interdependence and peace, Rousseau postulates that the pacifying effects of democracy are not sustainable under conditions of heightened interdependence. Rousseau’s analysis adds complexity to the familiar Kantian argument by qualifying the conditions under which we can expect democracy and/or democratisation to reduce the probability of conflict, and by adding an important social and ideational component to the largely material approach of the Kantian peace theory.</p>
<span><i>Journal of International Relations and Development</i> advance online publication, 29 May 2015; doi:<span>10.1057/jird.2015.3</span></span>",lilach gilady,,2015.0,10.1057/jird.2015.3,Journal of International Relations and Development,Gilady2015,Not available,,Nature,Not available,Triangle or ‘trilemma’: Rousseau and the ‘Kantian peace’,057fa2a8bd6600e697af0e75d95e1116,http://dx.doi.org/10.1057/jird.2015.3
14515,"<p>Self-organization and pattern formation in network-organized systems emerges from the collective activation and interaction of many interconnected units. A striking feature of these non-equilibrium structures is that they are often localized and robust: only a small subset of the nodes, or cell assembly, is activated. Understanding the role of cell assemblies as basic functional units in neural networks and socio-technical systems emerges as a fundamental challenge in network theory. A key open question is how these elementary building blocks emerge, and how they operate, linking structure and function in complex networks. Here we show that a network analogue of the Swift-Hohenberg continuum model—a minimal-ingredients model of nodal activation and interaction within a complex network—is able to produce a complex suite of localized patterns. Hence, the spontaneous formation of robust operational cell assemblies in complex networks can be explained as the result of self-organization, even in the absence of synaptic reinforcements.</p>",christos nicolaides,Information theory and computation,2016.0,10.1038/srep21360,Scientific Reports,Nicolaides2016,Not available,,Nature,Not available,Self-organization of network dynamics into local quantized states,a97ca062c51b4cacc7c9f0cfacd779df,http://dx.doi.org/10.1038/srep21360
14516,"<p>Self-organization and pattern formation in network-organized systems emerges from the collective activation and interaction of many interconnected units. A striking feature of these non-equilibrium structures is that they are often localized and robust: only a small subset of the nodes, or cell assembly, is activated. Understanding the role of cell assemblies as basic functional units in neural networks and socio-technical systems emerges as a fundamental challenge in network theory. A key open question is how these elementary building blocks emerge, and how they operate, linking structure and function in complex networks. Here we show that a network analogue of the Swift-Hohenberg continuum model—a minimal-ingredients model of nodal activation and interaction within a complex network—is able to produce a complex suite of localized patterns. Hence, the spontaneous formation of robust operational cell assemblies in complex networks can be explained as the result of self-organization, even in the absence of synaptic reinforcements.</p>",christos nicolaides,Complex networks,2016.0,10.1038/srep21360,Scientific Reports,Nicolaides2016,Not available,,Nature,Not available,Self-organization of network dynamics into local quantized states,a97ca062c51b4cacc7c9f0cfacd779df,http://dx.doi.org/10.1038/srep21360
14517,"<p>Self-organization and pattern formation in network-organized systems emerges from the collective activation and interaction of many interconnected units. A striking feature of these non-equilibrium structures is that they are often localized and robust: only a small subset of the nodes, or cell assembly, is activated. Understanding the role of cell assemblies as basic functional units in neural networks and socio-technical systems emerges as a fundamental challenge in network theory. A key open question is how these elementary building blocks emerge, and how they operate, linking structure and function in complex networks. Here we show that a network analogue of the Swift-Hohenberg continuum model—a minimal-ingredients model of nodal activation and interaction within a complex network—is able to produce a complex suite of localized patterns. Hence, the spontaneous formation of robust operational cell assemblies in complex networks can be explained as the result of self-organization, even in the absence of synaptic reinforcements.</p>",ruben juanes,Information theory and computation,2016.0,10.1038/srep21360,Scientific Reports,Nicolaides2016,Not available,,Nature,Not available,Self-organization of network dynamics into local quantized states,a97ca062c51b4cacc7c9f0cfacd779df,http://dx.doi.org/10.1038/srep21360
14518,"<p>Self-organization and pattern formation in network-organized systems emerges from the collective activation and interaction of many interconnected units. A striking feature of these non-equilibrium structures is that they are often localized and robust: only a small subset of the nodes, or cell assembly, is activated. Understanding the role of cell assemblies as basic functional units in neural networks and socio-technical systems emerges as a fundamental challenge in network theory. A key open question is how these elementary building blocks emerge, and how they operate, linking structure and function in complex networks. Here we show that a network analogue of the Swift-Hohenberg continuum model—a minimal-ingredients model of nodal activation and interaction within a complex network—is able to produce a complex suite of localized patterns. Hence, the spontaneous formation of robust operational cell assemblies in complex networks can be explained as the result of self-organization, even in the absence of synaptic reinforcements.</p>",ruben juanes,Complex networks,2016.0,10.1038/srep21360,Scientific Reports,Nicolaides2016,Not available,,Nature,Not available,Self-organization of network dynamics into local quantized states,a97ca062c51b4cacc7c9f0cfacd779df,http://dx.doi.org/10.1038/srep21360
14519,"<p>Self-organization and pattern formation in network-organized systems emerges from the collective activation and interaction of many interconnected units. A striking feature of these non-equilibrium structures is that they are often localized and robust: only a small subset of the nodes, or cell assembly, is activated. Understanding the role of cell assemblies as basic functional units in neural networks and socio-technical systems emerges as a fundamental challenge in network theory. A key open question is how these elementary building blocks emerge, and how they operate, linking structure and function in complex networks. Here we show that a network analogue of the Swift-Hohenberg continuum model—a minimal-ingredients model of nodal activation and interaction within a complex network—is able to produce a complex suite of localized patterns. Hence, the spontaneous formation of robust operational cell assemblies in complex networks can be explained as the result of self-organization, even in the absence of synaptic reinforcements.</p>",luis cueto-felgueroso,Information theory and computation,2016.0,10.1038/srep21360,Scientific Reports,Nicolaides2016,Not available,,Nature,Not available,Self-organization of network dynamics into local quantized states,a97ca062c51b4cacc7c9f0cfacd779df,http://dx.doi.org/10.1038/srep21360
14520,"<p>Self-organization and pattern formation in network-organized systems emerges from the collective activation and interaction of many interconnected units. A striking feature of these non-equilibrium structures is that they are often localized and robust: only a small subset of the nodes, or cell assembly, is activated. Understanding the role of cell assemblies as basic functional units in neural networks and socio-technical systems emerges as a fundamental challenge in network theory. A key open question is how these elementary building blocks emerge, and how they operate, linking structure and function in complex networks. Here we show that a network analogue of the Swift-Hohenberg continuum model—a minimal-ingredients model of nodal activation and interaction within a complex network—is able to produce a complex suite of localized patterns. Hence, the spontaneous formation of robust operational cell assemblies in complex networks can be explained as the result of self-organization, even in the absence of synaptic reinforcements.</p>",luis cueto-felgueroso,Complex networks,2016.0,10.1038/srep21360,Scientific Reports,Nicolaides2016,Not available,,Nature,Not available,Self-organization of network dynamics into local quantized states,a97ca062c51b4cacc7c9f0cfacd779df,http://dx.doi.org/10.1038/srep21360
14521,"<p>The vulnerability to real-life networks against small initial attacks has been one of outstanding challenges in the study of interrelated networks. We study cascading failures in two interrelated networks <b><i>S</i></b> and <b><i>B</i></b> composed from dependency chains and connectivity links respectively. This work proposes a realistic model for cascading failures based on the redistribution of traffic flow. We study the Barabási-Albert networks (<b><i>BA</i></b>) and Erdős-Rényi graphs (<b><i>ER</i></b>) with such structure, and found that the efficiency sharply decreases with increasing percentages of the dependency nodes for removing a node randomly. Furthermore, we study the robustness of interrelated traffic networks, especially the subway and bus network in Beijing. By analyzing different attacking strategies, we uncover that the efficiency of the city traffic system has a non-equilibrium phase transition at low capacity of the networks. This explains why the pressure of the traffic overload is relaxed by singly increasing the number of small buses during rush hours. We also found that the increment of some buses may release traffic jam caused by removing a node of the bus network randomly if the damage is limited. However, the efficiencies to transfer people flow will sharper increase when the capacity of the subway network <b><i>α<sub>S</sub></i> > <i>α</i><sub>0</sub></b>.</p>",jinghua xiao,Complex networks,2014.0,10.1038/srep05413,Scientific Reports,Su2014,Not available,,Nature,Not available,Robustness of Interrelated Traffic Networks to Cascading Failures,4840ca15ebd58b9a2e9f7ee719c39054,http://dx.doi.org/10.1038/srep05413
14522,"<p>When tensioned, ordinary materials expand along the direction of the applied force. Here, we explore network concepts to design metamaterials exhibiting negative compressibility transitions, during which a material undergoes contraction when tensioned (or expansion when pressured). Continuous contraction of a material in the same direction of an applied tension, and in response to this tension, is inherently unstable. The conceptually similar effect we demonstrate can be achieved, however, through destabilizations of (meta)stable equilibria of the constituents. These destabilizations give rise to a stress-induced solid–solid phase transition associated with a twisted hysteresis curve for the stress–strain relationship. The strain-driven counterpart of negative compressibility transitions is a force amplification phenomenon, where an increase in deformation induces a discontinuous increase in response force. We suggest that the proposed materials could be useful for the design of actuators, force amplifiers, micromechanical controls, and protective devices.</p>",zachary nicolaou,Mechanical properties,2012.0,10.1038/nmat3331,Nature Materials,Nicolaou2012,Not available,,Nature,Not available,Mechanical metamaterials with negative compressibility transitions,0d780fb1641eef54da0117dded0ba274,http://dx.doi.org/10.1038/nmat3331
14523,"<p>When tensioned, ordinary materials expand along the direction of the applied force. Here, we explore network concepts to design metamaterials exhibiting negative compressibility transitions, during which a material undergoes contraction when tensioned (or expansion when pressured). Continuous contraction of a material in the same direction of an applied tension, and in response to this tension, is inherently unstable. The conceptually similar effect we demonstrate can be achieved, however, through destabilizations of (meta)stable equilibria of the constituents. These destabilizations give rise to a stress-induced solid–solid phase transition associated with a twisted hysteresis curve for the stress–strain relationship. The strain-driven counterpart of negative compressibility transitions is a force amplification phenomenon, where an increase in deformation induces a discontinuous increase in response force. We suggest that the proposed materials could be useful for the design of actuators, force amplifiers, micromechanical controls, and protective devices.</p>",adilson motter,Mechanical properties,2012.0,10.1038/nmat3331,Nature Materials,Nicolaou2012,Not available,,Nature,Not available,Mechanical metamaterials with negative compressibility transitions,0d780fb1641eef54da0117dded0ba274,http://dx.doi.org/10.1038/nmat3331
14524,"<p>CCN5/WISP-2 is an anti-invasive molecule and prevents breast cancer (BC) progression. However, it is not well understood how CCN5 prevents invasive phenotypes of BC cells. CCN5 protein expression is detected in estrogen receptor-α (ER-α) -positive normal breast epithelial cells as well as BC cells, which are weakly invasive and rarely metastasize depending on the functional status of ER-α. A unique molecular relation between CCN5 and ER-α has been established as the components of the same signaling pathway that coordinate some essential signals associated with the proliferation as well as delaying the disease progression from a non-invasive to invasive phenotypes. Given the importance of this connection, we determined the role of CCN5 in regulation of ER-α in different cellular settings and their functional relationship. In a genetically engineered mouse model, induced expression of CCN5 in the mammary ductal epithelial cells by doxycycline promotes ER-α expression. Similarly, CCN5 regulates ER-α expression and activity in normal and neoplastic breast cells, as documented in various <i>in vitro</i> settings such as mouse mammary gland culture, human mammary epithelial cell and different BC cell cultures in the presence or absence of human recombinant CCN5 (hrCCN5) protein. Mechanistically, at least in the BC cells, CCN5 is sufficient to induce ER-α expression at the transcription level via interacting with integrins-α6β1 and suppressing Akt followed by activation of FOXO3a. Moreover, <i>in vitro</i> and <i>in vivo</i> functional assays indicate that CCN5 treatment promotes response to tamoxifen in triple-negative BC (TNBC) cells possibly via restoring ER-α. Collectively, these studies implicates that the combination treatments of CCN5 (via activation of CCN5 or hrCCN5 treatment) and tamoxifen as potential therapies for TNBC.</p>",s sarkar,Breast cancer,2017.0,10.1038/oncsis.2017.43,Oncogenesis,Sarkar2017,Not available,,Nature,Not available,CCN5/WISP-2 restores ER-∝ in normal and neoplastic breast cells and sensitizes triple negative breast cancer cells to tamoxifen,6e4c8cc522c98fbb348321464f602e57,http://dx.doi.org/10.1038/oncsis.2017.43
14525,"<p>CCN5/WISP-2 is an anti-invasive molecule and prevents breast cancer (BC) progression. However, it is not well understood how CCN5 prevents invasive phenotypes of BC cells. CCN5 protein expression is detected in estrogen receptor-α (ER-α) -positive normal breast epithelial cells as well as BC cells, which are weakly invasive and rarely metastasize depending on the functional status of ER-α. A unique molecular relation between CCN5 and ER-α has been established as the components of the same signaling pathway that coordinate some essential signals associated with the proliferation as well as delaying the disease progression from a non-invasive to invasive phenotypes. Given the importance of this connection, we determined the role of CCN5 in regulation of ER-α in different cellular settings and their functional relationship. In a genetically engineered mouse model, induced expression of CCN5 in the mammary ductal epithelial cells by doxycycline promotes ER-α expression. Similarly, CCN5 regulates ER-α expression and activity in normal and neoplastic breast cells, as documented in various <i>in vitro</i> settings such as mouse mammary gland culture, human mammary epithelial cell and different BC cell cultures in the presence or absence of human recombinant CCN5 (hrCCN5) protein. Mechanistically, at least in the BC cells, CCN5 is sufficient to induce ER-α expression at the transcription level via interacting with integrins-α6β1 and suppressing Akt followed by activation of FOXO3a. Moreover, <i>in vitro</i> and <i>in vivo</i> functional assays indicate that CCN5 treatment promotes response to tamoxifen in triple-negative BC (TNBC) cells possibly via restoring ER-α. Collectively, these studies implicates that the combination treatments of CCN5 (via activation of CCN5 or hrCCN5 treatment) and tamoxifen as potential therapies for TNBC.</p>",s sarkar,Hormone receptors,2017.0,10.1038/oncsis.2017.43,Oncogenesis,Sarkar2017,Not available,,Nature,Not available,CCN5/WISP-2 restores ER-∝ in normal and neoplastic breast cells and sensitizes triple negative breast cancer cells to tamoxifen,6e4c8cc522c98fbb348321464f602e57,http://dx.doi.org/10.1038/oncsis.2017.43
14526,"<p>CCN5/WISP-2 is an anti-invasive molecule and prevents breast cancer (BC) progression. However, it is not well understood how CCN5 prevents invasive phenotypes of BC cells. CCN5 protein expression is detected in estrogen receptor-α (ER-α) -positive normal breast epithelial cells as well as BC cells, which are weakly invasive and rarely metastasize depending on the functional status of ER-α. A unique molecular relation between CCN5 and ER-α has been established as the components of the same signaling pathway that coordinate some essential signals associated with the proliferation as well as delaying the disease progression from a non-invasive to invasive phenotypes. Given the importance of this connection, we determined the role of CCN5 in regulation of ER-α in different cellular settings and their functional relationship. In a genetically engineered mouse model, induced expression of CCN5 in the mammary ductal epithelial cells by doxycycline promotes ER-α expression. Similarly, CCN5 regulates ER-α expression and activity in normal and neoplastic breast cells, as documented in various <i>in vitro</i> settings such as mouse mammary gland culture, human mammary epithelial cell and different BC cell cultures in the presence or absence of human recombinant CCN5 (hrCCN5) protein. Mechanistically, at least in the BC cells, CCN5 is sufficient to induce ER-α expression at the transcription level via interacting with integrins-α6β1 and suppressing Akt followed by activation of FOXO3a. Moreover, <i>in vitro</i> and <i>in vivo</i> functional assays indicate that CCN5 treatment promotes response to tamoxifen in triple-negative BC (TNBC) cells possibly via restoring ER-α. Collectively, these studies implicates that the combination treatments of CCN5 (via activation of CCN5 or hrCCN5 treatment) and tamoxifen as potential therapies for TNBC.</p>",a ghosh,Breast cancer,2017.0,10.1038/oncsis.2017.43,Oncogenesis,Sarkar2017,Not available,,Nature,Not available,CCN5/WISP-2 restores ER-∝ in normal and neoplastic breast cells and sensitizes triple negative breast cancer cells to tamoxifen,6e4c8cc522c98fbb348321464f602e57,http://dx.doi.org/10.1038/oncsis.2017.43
14527,"<p>CCN5/WISP-2 is an anti-invasive molecule and prevents breast cancer (BC) progression. However, it is not well understood how CCN5 prevents invasive phenotypes of BC cells. CCN5 protein expression is detected in estrogen receptor-α (ER-α) -positive normal breast epithelial cells as well as BC cells, which are weakly invasive and rarely metastasize depending on the functional status of ER-α. A unique molecular relation between CCN5 and ER-α has been established as the components of the same signaling pathway that coordinate some essential signals associated with the proliferation as well as delaying the disease progression from a non-invasive to invasive phenotypes. Given the importance of this connection, we determined the role of CCN5 in regulation of ER-α in different cellular settings and their functional relationship. In a genetically engineered mouse model, induced expression of CCN5 in the mammary ductal epithelial cells by doxycycline promotes ER-α expression. Similarly, CCN5 regulates ER-α expression and activity in normal and neoplastic breast cells, as documented in various <i>in vitro</i> settings such as mouse mammary gland culture, human mammary epithelial cell and different BC cell cultures in the presence or absence of human recombinant CCN5 (hrCCN5) protein. Mechanistically, at least in the BC cells, CCN5 is sufficient to induce ER-α expression at the transcription level via interacting with integrins-α6β1 and suppressing Akt followed by activation of FOXO3a. Moreover, <i>in vitro</i> and <i>in vivo</i> functional assays indicate that CCN5 treatment promotes response to tamoxifen in triple-negative BC (TNBC) cells possibly via restoring ER-α. Collectively, these studies implicates that the combination treatments of CCN5 (via activation of CCN5 or hrCCN5 treatment) and tamoxifen as potential therapies for TNBC.</p>",a ghosh,Hormone receptors,2017.0,10.1038/oncsis.2017.43,Oncogenesis,Sarkar2017,Not available,,Nature,Not available,CCN5/WISP-2 restores ER-∝ in normal and neoplastic breast cells and sensitizes triple negative breast cancer cells to tamoxifen,6e4c8cc522c98fbb348321464f602e57,http://dx.doi.org/10.1038/oncsis.2017.43
14528,"<p>CCN5/WISP-2 is an anti-invasive molecule and prevents breast cancer (BC) progression. However, it is not well understood how CCN5 prevents invasive phenotypes of BC cells. CCN5 protein expression is detected in estrogen receptor-α (ER-α) -positive normal breast epithelial cells as well as BC cells, which are weakly invasive and rarely metastasize depending on the functional status of ER-α. A unique molecular relation between CCN5 and ER-α has been established as the components of the same signaling pathway that coordinate some essential signals associated with the proliferation as well as delaying the disease progression from a non-invasive to invasive phenotypes. Given the importance of this connection, we determined the role of CCN5 in regulation of ER-α in different cellular settings and their functional relationship. In a genetically engineered mouse model, induced expression of CCN5 in the mammary ductal epithelial cells by doxycycline promotes ER-α expression. Similarly, CCN5 regulates ER-α expression and activity in normal and neoplastic breast cells, as documented in various <i>in vitro</i> settings such as mouse mammary gland culture, human mammary epithelial cell and different BC cell cultures in the presence or absence of human recombinant CCN5 (hrCCN5) protein. Mechanistically, at least in the BC cells, CCN5 is sufficient to induce ER-α expression at the transcription level via interacting with integrins-α6β1 and suppressing Akt followed by activation of FOXO3a. Moreover, <i>in vitro</i> and <i>in vivo</i> functional assays indicate that CCN5 treatment promotes response to tamoxifen in triple-negative BC (TNBC) cells possibly via restoring ER-α. Collectively, these studies implicates that the combination treatments of CCN5 (via activation of CCN5 or hrCCN5 treatment) and tamoxifen as potential therapies for TNBC.</p>",s banerjee,Breast cancer,2017.0,10.1038/oncsis.2017.43,Oncogenesis,Sarkar2017,Not available,,Nature,Not available,CCN5/WISP-2 restores ER-∝ in normal and neoplastic breast cells and sensitizes triple negative breast cancer cells to tamoxifen,6e4c8cc522c98fbb348321464f602e57,http://dx.doi.org/10.1038/oncsis.2017.43
14529,"<p>CCN5/WISP-2 is an anti-invasive molecule and prevents breast cancer (BC) progression. However, it is not well understood how CCN5 prevents invasive phenotypes of BC cells. CCN5 protein expression is detected in estrogen receptor-α (ER-α) -positive normal breast epithelial cells as well as BC cells, which are weakly invasive and rarely metastasize depending on the functional status of ER-α. A unique molecular relation between CCN5 and ER-α has been established as the components of the same signaling pathway that coordinate some essential signals associated with the proliferation as well as delaying the disease progression from a non-invasive to invasive phenotypes. Given the importance of this connection, we determined the role of CCN5 in regulation of ER-α in different cellular settings and their functional relationship. In a genetically engineered mouse model, induced expression of CCN5 in the mammary ductal epithelial cells by doxycycline promotes ER-α expression. Similarly, CCN5 regulates ER-α expression and activity in normal and neoplastic breast cells, as documented in various <i>in vitro</i> settings such as mouse mammary gland culture, human mammary epithelial cell and different BC cell cultures in the presence or absence of human recombinant CCN5 (hrCCN5) protein. Mechanistically, at least in the BC cells, CCN5 is sufficient to induce ER-α expression at the transcription level via interacting with integrins-α6β1 and suppressing Akt followed by activation of FOXO3a. Moreover, <i>in vitro</i> and <i>in vivo</i> functional assays indicate that CCN5 treatment promotes response to tamoxifen in triple-negative BC (TNBC) cells possibly via restoring ER-α. Collectively, these studies implicates that the combination treatments of CCN5 (via activation of CCN5 or hrCCN5 treatment) and tamoxifen as potential therapies for TNBC.</p>",s banerjee,Hormone receptors,2017.0,10.1038/oncsis.2017.43,Oncogenesis,Sarkar2017,Not available,,Nature,Not available,CCN5/WISP-2 restores ER-∝ in normal and neoplastic breast cells and sensitizes triple negative breast cancer cells to tamoxifen,6e4c8cc522c98fbb348321464f602e57,http://dx.doi.org/10.1038/oncsis.2017.43
14530,"<p>CCN5/WISP-2 is an anti-invasive molecule and prevents breast cancer (BC) progression. However, it is not well understood how CCN5 prevents invasive phenotypes of BC cells. CCN5 protein expression is detected in estrogen receptor-α (ER-α) -positive normal breast epithelial cells as well as BC cells, which are weakly invasive and rarely metastasize depending on the functional status of ER-α. A unique molecular relation between CCN5 and ER-α has been established as the components of the same signaling pathway that coordinate some essential signals associated with the proliferation as well as delaying the disease progression from a non-invasive to invasive phenotypes. Given the importance of this connection, we determined the role of CCN5 in regulation of ER-α in different cellular settings and their functional relationship. In a genetically engineered mouse model, induced expression of CCN5 in the mammary ductal epithelial cells by doxycycline promotes ER-α expression. Similarly, CCN5 regulates ER-α expression and activity in normal and neoplastic breast cells, as documented in various <i>in vitro</i> settings such as mouse mammary gland culture, human mammary epithelial cell and different BC cell cultures in the presence or absence of human recombinant CCN5 (hrCCN5) protein. Mechanistically, at least in the BC cells, CCN5 is sufficient to induce ER-α expression at the transcription level via interacting with integrins-α6β1 and suppressing Akt followed by activation of FOXO3a. Moreover, <i>in vitro</i> and <i>in vivo</i> functional assays indicate that CCN5 treatment promotes response to tamoxifen in triple-negative BC (TNBC) cells possibly via restoring ER-α. Collectively, these studies implicates that the combination treatments of CCN5 (via activation of CCN5 or hrCCN5 treatment) and tamoxifen as potential therapies for TNBC.</p>",g maity,Breast cancer,2017.0,10.1038/oncsis.2017.43,Oncogenesis,Sarkar2017,Not available,,Nature,Not available,CCN5/WISP-2 restores ER-∝ in normal and neoplastic breast cells and sensitizes triple negative breast cancer cells to tamoxifen,6e4c8cc522c98fbb348321464f602e57,http://dx.doi.org/10.1038/oncsis.2017.43
14531,"<p>CCN5/WISP-2 is an anti-invasive molecule and prevents breast cancer (BC) progression. However, it is not well understood how CCN5 prevents invasive phenotypes of BC cells. CCN5 protein expression is detected in estrogen receptor-α (ER-α) -positive normal breast epithelial cells as well as BC cells, which are weakly invasive and rarely metastasize depending on the functional status of ER-α. A unique molecular relation between CCN5 and ER-α has been established as the components of the same signaling pathway that coordinate some essential signals associated with the proliferation as well as delaying the disease progression from a non-invasive to invasive phenotypes. Given the importance of this connection, we determined the role of CCN5 in regulation of ER-α in different cellular settings and their functional relationship. In a genetically engineered mouse model, induced expression of CCN5 in the mammary ductal epithelial cells by doxycycline promotes ER-α expression. Similarly, CCN5 regulates ER-α expression and activity in normal and neoplastic breast cells, as documented in various <i>in vitro</i> settings such as mouse mammary gland culture, human mammary epithelial cell and different BC cell cultures in the presence or absence of human recombinant CCN5 (hrCCN5) protein. Mechanistically, at least in the BC cells, CCN5 is sufficient to induce ER-α expression at the transcription level via interacting with integrins-α6β1 and suppressing Akt followed by activation of FOXO3a. Moreover, <i>in vitro</i> and <i>in vivo</i> functional assays indicate that CCN5 treatment promotes response to tamoxifen in triple-negative BC (TNBC) cells possibly via restoring ER-α. Collectively, these studies implicates that the combination treatments of CCN5 (via activation of CCN5 or hrCCN5 treatment) and tamoxifen as potential therapies for TNBC.</p>",g maity,Hormone receptors,2017.0,10.1038/oncsis.2017.43,Oncogenesis,Sarkar2017,Not available,,Nature,Not available,CCN5/WISP-2 restores ER-∝ in normal and neoplastic breast cells and sensitizes triple negative breast cancer cells to tamoxifen,6e4c8cc522c98fbb348321464f602e57,http://dx.doi.org/10.1038/oncsis.2017.43
14532,"<p>The vulnerability to real-life networks against small initial attacks has been one of outstanding challenges in the study of interrelated networks. We study cascading failures in two interrelated networks <b><i>S</i></b> and <b><i>B</i></b> composed from dependency chains and connectivity links respectively. This work proposes a realistic model for cascading failures based on the redistribution of traffic flow. We study the Barabási-Albert networks (<b><i>BA</i></b>) and Erdős-Rényi graphs (<b><i>ER</i></b>) with such structure, and found that the efficiency sharply decreases with increasing percentages of the dependency nodes for removing a node randomly. Furthermore, we study the robustness of interrelated traffic networks, especially the subway and bus network in Beijing. By analyzing different attacking strategies, we uncover that the efficiency of the city traffic system has a non-equilibrium phase transition at low capacity of the networks. This explains why the pressure of the traffic overload is relaxed by singly increasing the number of small buses during rush hours. We also found that the increment of some buses may release traffic jam caused by removing a node of the bus network randomly if the damage is limited. However, the efficiencies to transfer people flow will sharper increase when the capacity of the subway network <b><i>α<sub>S</sub></i> > <i>α</i><sub>0</sub></b>.</p>",jinghua xiao,Nonlinear phenomena,2014.0,10.1038/srep05413,Scientific Reports,Su2014,Not available,,Nature,Not available,Robustness of Interrelated Traffic Networks to Cascading Failures,4840ca15ebd58b9a2e9f7ee719c39054,http://dx.doi.org/10.1038/srep05413
14533,"<p>CCN5/WISP-2 is an anti-invasive molecule and prevents breast cancer (BC) progression. However, it is not well understood how CCN5 prevents invasive phenotypes of BC cells. CCN5 protein expression is detected in estrogen receptor-α (ER-α) -positive normal breast epithelial cells as well as BC cells, which are weakly invasive and rarely metastasize depending on the functional status of ER-α. A unique molecular relation between CCN5 and ER-α has been established as the components of the same signaling pathway that coordinate some essential signals associated with the proliferation as well as delaying the disease progression from a non-invasive to invasive phenotypes. Given the importance of this connection, we determined the role of CCN5 in regulation of ER-α in different cellular settings and their functional relationship. In a genetically engineered mouse model, induced expression of CCN5 in the mammary ductal epithelial cells by doxycycline promotes ER-α expression. Similarly, CCN5 regulates ER-α expression and activity in normal and neoplastic breast cells, as documented in various <i>in vitro</i> settings such as mouse mammary gland culture, human mammary epithelial cell and different BC cell cultures in the presence or absence of human recombinant CCN5 (hrCCN5) protein. Mechanistically, at least in the BC cells, CCN5 is sufficient to induce ER-α expression at the transcription level via interacting with integrins-α6β1 and suppressing Akt followed by activation of FOXO3a. Moreover, <i>in vitro</i> and <i>in vivo</i> functional assays indicate that CCN5 treatment promotes response to tamoxifen in triple-negative BC (TNBC) cells possibly via restoring ER-α. Collectively, these studies implicates that the combination treatments of CCN5 (via activation of CCN5 or hrCCN5 treatment) and tamoxifen as potential therapies for TNBC.</p>",a das,Breast cancer,2017.0,10.1038/oncsis.2017.43,Oncogenesis,Sarkar2017,Not available,,Nature,Not available,CCN5/WISP-2 restores ER-∝ in normal and neoplastic breast cells and sensitizes triple negative breast cancer cells to tamoxifen,6e4c8cc522c98fbb348321464f602e57,http://dx.doi.org/10.1038/oncsis.2017.43
14534,"<p>CCN5/WISP-2 is an anti-invasive molecule and prevents breast cancer (BC) progression. However, it is not well understood how CCN5 prevents invasive phenotypes of BC cells. CCN5 protein expression is detected in estrogen receptor-α (ER-α) -positive normal breast epithelial cells as well as BC cells, which are weakly invasive and rarely metastasize depending on the functional status of ER-α. A unique molecular relation between CCN5 and ER-α has been established as the components of the same signaling pathway that coordinate some essential signals associated with the proliferation as well as delaying the disease progression from a non-invasive to invasive phenotypes. Given the importance of this connection, we determined the role of CCN5 in regulation of ER-α in different cellular settings and their functional relationship. In a genetically engineered mouse model, induced expression of CCN5 in the mammary ductal epithelial cells by doxycycline promotes ER-α expression. Similarly, CCN5 regulates ER-α expression and activity in normal and neoplastic breast cells, as documented in various <i>in vitro</i> settings such as mouse mammary gland culture, human mammary epithelial cell and different BC cell cultures in the presence or absence of human recombinant CCN5 (hrCCN5) protein. Mechanistically, at least in the BC cells, CCN5 is sufficient to induce ER-α expression at the transcription level via interacting with integrins-α6β1 and suppressing Akt followed by activation of FOXO3a. Moreover, <i>in vitro</i> and <i>in vivo</i> functional assays indicate that CCN5 treatment promotes response to tamoxifen in triple-negative BC (TNBC) cells possibly via restoring ER-α. Collectively, these studies implicates that the combination treatments of CCN5 (via activation of CCN5 or hrCCN5 treatment) and tamoxifen as potential therapies for TNBC.</p>",a das,Hormone receptors,2017.0,10.1038/oncsis.2017.43,Oncogenesis,Sarkar2017,Not available,,Nature,Not available,CCN5/WISP-2 restores ER-∝ in normal and neoplastic breast cells and sensitizes triple negative breast cancer cells to tamoxifen,6e4c8cc522c98fbb348321464f602e57,http://dx.doi.org/10.1038/oncsis.2017.43
14535,"<p>CCN5/WISP-2 is an anti-invasive molecule and prevents breast cancer (BC) progression. However, it is not well understood how CCN5 prevents invasive phenotypes of BC cells. CCN5 protein expression is detected in estrogen receptor-α (ER-α) -positive normal breast epithelial cells as well as BC cells, which are weakly invasive and rarely metastasize depending on the functional status of ER-α. A unique molecular relation between CCN5 and ER-α has been established as the components of the same signaling pathway that coordinate some essential signals associated with the proliferation as well as delaying the disease progression from a non-invasive to invasive phenotypes. Given the importance of this connection, we determined the role of CCN5 in regulation of ER-α in different cellular settings and their functional relationship. In a genetically engineered mouse model, induced expression of CCN5 in the mammary ductal epithelial cells by doxycycline promotes ER-α expression. Similarly, CCN5 regulates ER-α expression and activity in normal and neoplastic breast cells, as documented in various <i>in vitro</i> settings such as mouse mammary gland culture, human mammary epithelial cell and different BC cell cultures in the presence or absence of human recombinant CCN5 (hrCCN5) protein. Mechanistically, at least in the BC cells, CCN5 is sufficient to induce ER-α expression at the transcription level via interacting with integrins-α6β1 and suppressing Akt followed by activation of FOXO3a. Moreover, <i>in vitro</i> and <i>in vivo</i> functional assays indicate that CCN5 treatment promotes response to tamoxifen in triple-negative BC (TNBC) cells possibly via restoring ER-α. Collectively, these studies implicates that the combination treatments of CCN5 (via activation of CCN5 or hrCCN5 treatment) and tamoxifen as potential therapies for TNBC.</p>",m larson,Breast cancer,2017.0,10.1038/oncsis.2017.43,Oncogenesis,Sarkar2017,Not available,,Nature,Not available,CCN5/WISP-2 restores ER-∝ in normal and neoplastic breast cells and sensitizes triple negative breast cancer cells to tamoxifen,6e4c8cc522c98fbb348321464f602e57,http://dx.doi.org/10.1038/oncsis.2017.43
14536,"<p>CCN5/WISP-2 is an anti-invasive molecule and prevents breast cancer (BC) progression. However, it is not well understood how CCN5 prevents invasive phenotypes of BC cells. CCN5 protein expression is detected in estrogen receptor-α (ER-α) -positive normal breast epithelial cells as well as BC cells, which are weakly invasive and rarely metastasize depending on the functional status of ER-α. A unique molecular relation between CCN5 and ER-α has been established as the components of the same signaling pathway that coordinate some essential signals associated with the proliferation as well as delaying the disease progression from a non-invasive to invasive phenotypes. Given the importance of this connection, we determined the role of CCN5 in regulation of ER-α in different cellular settings and their functional relationship. In a genetically engineered mouse model, induced expression of CCN5 in the mammary ductal epithelial cells by doxycycline promotes ER-α expression. Similarly, CCN5 regulates ER-α expression and activity in normal and neoplastic breast cells, as documented in various <i>in vitro</i> settings such as mouse mammary gland culture, human mammary epithelial cell and different BC cell cultures in the presence or absence of human recombinant CCN5 (hrCCN5) protein. Mechanistically, at least in the BC cells, CCN5 is sufficient to induce ER-α expression at the transcription level via interacting with integrins-α6β1 and suppressing Akt followed by activation of FOXO3a. Moreover, <i>in vitro</i> and <i>in vivo</i> functional assays indicate that CCN5 treatment promotes response to tamoxifen in triple-negative BC (TNBC) cells possibly via restoring ER-α. Collectively, these studies implicates that the combination treatments of CCN5 (via activation of CCN5 or hrCCN5 treatment) and tamoxifen as potential therapies for TNBC.</p>",m larson,Hormone receptors,2017.0,10.1038/oncsis.2017.43,Oncogenesis,Sarkar2017,Not available,,Nature,Not available,CCN5/WISP-2 restores ER-∝ in normal and neoplastic breast cells and sensitizes triple negative breast cancer cells to tamoxifen,6e4c8cc522c98fbb348321464f602e57,http://dx.doi.org/10.1038/oncsis.2017.43
14537,"<p>CCN5/WISP-2 is an anti-invasive molecule and prevents breast cancer (BC) progression. However, it is not well understood how CCN5 prevents invasive phenotypes of BC cells. CCN5 protein expression is detected in estrogen receptor-α (ER-α) -positive normal breast epithelial cells as well as BC cells, which are weakly invasive and rarely metastasize depending on the functional status of ER-α. A unique molecular relation between CCN5 and ER-α has been established as the components of the same signaling pathway that coordinate some essential signals associated with the proliferation as well as delaying the disease progression from a non-invasive to invasive phenotypes. Given the importance of this connection, we determined the role of CCN5 in regulation of ER-α in different cellular settings and their functional relationship. In a genetically engineered mouse model, induced expression of CCN5 in the mammary ductal epithelial cells by doxycycline promotes ER-α expression. Similarly, CCN5 regulates ER-α expression and activity in normal and neoplastic breast cells, as documented in various <i>in vitro</i> settings such as mouse mammary gland culture, human mammary epithelial cell and different BC cell cultures in the presence or absence of human recombinant CCN5 (hrCCN5) protein. Mechanistically, at least in the BC cells, CCN5 is sufficient to induce ER-α expression at the transcription level via interacting with integrins-α6β1 and suppressing Akt followed by activation of FOXO3a. Moreover, <i>in vitro</i> and <i>in vivo</i> functional assays indicate that CCN5 treatment promotes response to tamoxifen in triple-negative BC (TNBC) cells possibly via restoring ER-α. Collectively, these studies implicates that the combination treatments of CCN5 (via activation of CCN5 or hrCCN5 treatment) and tamoxifen as potential therapies for TNBC.</p>",v gupta,Breast cancer,2017.0,10.1038/oncsis.2017.43,Oncogenesis,Sarkar2017,Not available,,Nature,Not available,CCN5/WISP-2 restores ER-∝ in normal and neoplastic breast cells and sensitizes triple negative breast cancer cells to tamoxifen,6e4c8cc522c98fbb348321464f602e57,http://dx.doi.org/10.1038/oncsis.2017.43
14538,"<p>CCN5/WISP-2 is an anti-invasive molecule and prevents breast cancer (BC) progression. However, it is not well understood how CCN5 prevents invasive phenotypes of BC cells. CCN5 protein expression is detected in estrogen receptor-α (ER-α) -positive normal breast epithelial cells as well as BC cells, which are weakly invasive and rarely metastasize depending on the functional status of ER-α. A unique molecular relation between CCN5 and ER-α has been established as the components of the same signaling pathway that coordinate some essential signals associated with the proliferation as well as delaying the disease progression from a non-invasive to invasive phenotypes. Given the importance of this connection, we determined the role of CCN5 in regulation of ER-α in different cellular settings and their functional relationship. In a genetically engineered mouse model, induced expression of CCN5 in the mammary ductal epithelial cells by doxycycline promotes ER-α expression. Similarly, CCN5 regulates ER-α expression and activity in normal and neoplastic breast cells, as documented in various <i>in vitro</i> settings such as mouse mammary gland culture, human mammary epithelial cell and different BC cell cultures in the presence or absence of human recombinant CCN5 (hrCCN5) protein. Mechanistically, at least in the BC cells, CCN5 is sufficient to induce ER-α expression at the transcription level via interacting with integrins-α6β1 and suppressing Akt followed by activation of FOXO3a. Moreover, <i>in vitro</i> and <i>in vivo</i> functional assays indicate that CCN5 treatment promotes response to tamoxifen in triple-negative BC (TNBC) cells possibly via restoring ER-α. Collectively, these studies implicates that the combination treatments of CCN5 (via activation of CCN5 or hrCCN5 treatment) and tamoxifen as potential therapies for TNBC.</p>",v gupta,Hormone receptors,2017.0,10.1038/oncsis.2017.43,Oncogenesis,Sarkar2017,Not available,,Nature,Not available,CCN5/WISP-2 restores ER-∝ in normal and neoplastic breast cells and sensitizes triple negative breast cancer cells to tamoxifen,6e4c8cc522c98fbb348321464f602e57,http://dx.doi.org/10.1038/oncsis.2017.43
14539,"<p>CCN5/WISP-2 is an anti-invasive molecule and prevents breast cancer (BC) progression. However, it is not well understood how CCN5 prevents invasive phenotypes of BC cells. CCN5 protein expression is detected in estrogen receptor-α (ER-α) -positive normal breast epithelial cells as well as BC cells, which are weakly invasive and rarely metastasize depending on the functional status of ER-α. A unique molecular relation between CCN5 and ER-α has been established as the components of the same signaling pathway that coordinate some essential signals associated with the proliferation as well as delaying the disease progression from a non-invasive to invasive phenotypes. Given the importance of this connection, we determined the role of CCN5 in regulation of ER-α in different cellular settings and their functional relationship. In a genetically engineered mouse model, induced expression of CCN5 in the mammary ductal epithelial cells by doxycycline promotes ER-α expression. Similarly, CCN5 regulates ER-α expression and activity in normal and neoplastic breast cells, as documented in various <i>in vitro</i> settings such as mouse mammary gland culture, human mammary epithelial cell and different BC cell cultures in the presence or absence of human recombinant CCN5 (hrCCN5) protein. Mechanistically, at least in the BC cells, CCN5 is sufficient to induce ER-α expression at the transcription level via interacting with integrins-α6β1 and suppressing Akt followed by activation of FOXO3a. Moreover, <i>in vitro</i> and <i>in vivo</i> functional assays indicate that CCN5 treatment promotes response to tamoxifen in triple-negative BC (TNBC) cells possibly via restoring ER-α. Collectively, these studies implicates that the combination treatments of CCN5 (via activation of CCN5 or hrCCN5 treatment) and tamoxifen as potential therapies for TNBC.</p>",i haque,Breast cancer,2017.0,10.1038/oncsis.2017.43,Oncogenesis,Sarkar2017,Not available,,Nature,Not available,CCN5/WISP-2 restores ER-∝ in normal and neoplastic breast cells and sensitizes triple negative breast cancer cells to tamoxifen,6e4c8cc522c98fbb348321464f602e57,http://dx.doi.org/10.1038/oncsis.2017.43
14540,"<p>CCN5/WISP-2 is an anti-invasive molecule and prevents breast cancer (BC) progression. However, it is not well understood how CCN5 prevents invasive phenotypes of BC cells. CCN5 protein expression is detected in estrogen receptor-α (ER-α) -positive normal breast epithelial cells as well as BC cells, which are weakly invasive and rarely metastasize depending on the functional status of ER-α. A unique molecular relation between CCN5 and ER-α has been established as the components of the same signaling pathway that coordinate some essential signals associated with the proliferation as well as delaying the disease progression from a non-invasive to invasive phenotypes. Given the importance of this connection, we determined the role of CCN5 in regulation of ER-α in different cellular settings and their functional relationship. In a genetically engineered mouse model, induced expression of CCN5 in the mammary ductal epithelial cells by doxycycline promotes ER-α expression. Similarly, CCN5 regulates ER-α expression and activity in normal and neoplastic breast cells, as documented in various <i>in vitro</i> settings such as mouse mammary gland culture, human mammary epithelial cell and different BC cell cultures in the presence or absence of human recombinant CCN5 (hrCCN5) protein. Mechanistically, at least in the BC cells, CCN5 is sufficient to induce ER-α expression at the transcription level via interacting with integrins-α6β1 and suppressing Akt followed by activation of FOXO3a. Moreover, <i>in vitro</i> and <i>in vivo</i> functional assays indicate that CCN5 treatment promotes response to tamoxifen in triple-negative BC (TNBC) cells possibly via restoring ER-α. Collectively, these studies implicates that the combination treatments of CCN5 (via activation of CCN5 or hrCCN5 treatment) and tamoxifen as potential therapies for TNBC.</p>",i haque,Hormone receptors,2017.0,10.1038/oncsis.2017.43,Oncogenesis,Sarkar2017,Not available,,Nature,Not available,CCN5/WISP-2 restores ER-∝ in normal and neoplastic breast cells and sensitizes triple negative breast cancer cells to tamoxifen,6e4c8cc522c98fbb348321464f602e57,http://dx.doi.org/10.1038/oncsis.2017.43
14541,"<p>CCN5/WISP-2 is an anti-invasive molecule and prevents breast cancer (BC) progression. However, it is not well understood how CCN5 prevents invasive phenotypes of BC cells. CCN5 protein expression is detected in estrogen receptor-α (ER-α) -positive normal breast epithelial cells as well as BC cells, which are weakly invasive and rarely metastasize depending on the functional status of ER-α. A unique molecular relation between CCN5 and ER-α has been established as the components of the same signaling pathway that coordinate some essential signals associated with the proliferation as well as delaying the disease progression from a non-invasive to invasive phenotypes. Given the importance of this connection, we determined the role of CCN5 in regulation of ER-α in different cellular settings and their functional relationship. In a genetically engineered mouse model, induced expression of CCN5 in the mammary ductal epithelial cells by doxycycline promotes ER-α expression. Similarly, CCN5 regulates ER-α expression and activity in normal and neoplastic breast cells, as documented in various <i>in vitro</i> settings such as mouse mammary gland culture, human mammary epithelial cell and different BC cell cultures in the presence or absence of human recombinant CCN5 (hrCCN5) protein. Mechanistically, at least in the BC cells, CCN5 is sufficient to induce ER-α expression at the transcription level via interacting with integrins-α6β1 and suppressing Akt followed by activation of FOXO3a. Moreover, <i>in vitro</i> and <i>in vivo</i> functional assays indicate that CCN5 treatment promotes response to tamoxifen in triple-negative BC (TNBC) cells possibly via restoring ER-α. Collectively, these studies implicates that the combination treatments of CCN5 (via activation of CCN5 or hrCCN5 treatment) and tamoxifen as potential therapies for TNBC.</p>",o tawfik,Breast cancer,2017.0,10.1038/oncsis.2017.43,Oncogenesis,Sarkar2017,Not available,,Nature,Not available,CCN5/WISP-2 restores ER-∝ in normal and neoplastic breast cells and sensitizes triple negative breast cancer cells to tamoxifen,6e4c8cc522c98fbb348321464f602e57,http://dx.doi.org/10.1038/oncsis.2017.43
14542,"<p>CCN5/WISP-2 is an anti-invasive molecule and prevents breast cancer (BC) progression. However, it is not well understood how CCN5 prevents invasive phenotypes of BC cells. CCN5 protein expression is detected in estrogen receptor-α (ER-α) -positive normal breast epithelial cells as well as BC cells, which are weakly invasive and rarely metastasize depending on the functional status of ER-α. A unique molecular relation between CCN5 and ER-α has been established as the components of the same signaling pathway that coordinate some essential signals associated with the proliferation as well as delaying the disease progression from a non-invasive to invasive phenotypes. Given the importance of this connection, we determined the role of CCN5 in regulation of ER-α in different cellular settings and their functional relationship. In a genetically engineered mouse model, induced expression of CCN5 in the mammary ductal epithelial cells by doxycycline promotes ER-α expression. Similarly, CCN5 regulates ER-α expression and activity in normal and neoplastic breast cells, as documented in various <i>in vitro</i> settings such as mouse mammary gland culture, human mammary epithelial cell and different BC cell cultures in the presence or absence of human recombinant CCN5 (hrCCN5) protein. Mechanistically, at least in the BC cells, CCN5 is sufficient to induce ER-α expression at the transcription level via interacting with integrins-α6β1 and suppressing Akt followed by activation of FOXO3a. Moreover, <i>in vitro</i> and <i>in vivo</i> functional assays indicate that CCN5 treatment promotes response to tamoxifen in triple-negative BC (TNBC) cells possibly via restoring ER-α. Collectively, these studies implicates that the combination treatments of CCN5 (via activation of CCN5 or hrCCN5 treatment) and tamoxifen as potential therapies for TNBC.</p>",o tawfik,Hormone receptors,2017.0,10.1038/oncsis.2017.43,Oncogenesis,Sarkar2017,Not available,,Nature,Not available,CCN5/WISP-2 restores ER-∝ in normal and neoplastic breast cells and sensitizes triple negative breast cancer cells to tamoxifen,6e4c8cc522c98fbb348321464f602e57,http://dx.doi.org/10.1038/oncsis.2017.43
14543,"<p>The vulnerability to real-life networks against small initial attacks has been one of outstanding challenges in the study of interrelated networks. We study cascading failures in two interrelated networks <b><i>S</i></b> and <b><i>B</i></b> composed from dependency chains and connectivity links respectively. This work proposes a realistic model for cascading failures based on the redistribution of traffic flow. We study the Barabási-Albert networks (<b><i>BA</i></b>) and Erdős-Rényi graphs (<b><i>ER</i></b>) with such structure, and found that the efficiency sharply decreases with increasing percentages of the dependency nodes for removing a node randomly. Furthermore, we study the robustness of interrelated traffic networks, especially the subway and bus network in Beijing. By analyzing different attacking strategies, we uncover that the efficiency of the city traffic system has a non-equilibrium phase transition at low capacity of the networks. This explains why the pressure of the traffic overload is relaxed by singly increasing the number of small buses during rush hours. We also found that the increment of some buses may release traffic jam caused by removing a node of the bus network randomly if the damage is limited. However, the efficiencies to transfer people flow will sharper increase when the capacity of the subway network <b><i>α<sub>S</sub></i> > <i>α</i><sub>0</sub></b>.</p>",jinghua xiao,Statistical physics,2014.0,10.1038/srep05413,Scientific Reports,Su2014,Not available,,Nature,Not available,Robustness of Interrelated Traffic Networks to Cascading Failures,4840ca15ebd58b9a2e9f7ee719c39054,http://dx.doi.org/10.1038/srep05413
14544,"<p>CCN5/WISP-2 is an anti-invasive molecule and prevents breast cancer (BC) progression. However, it is not well understood how CCN5 prevents invasive phenotypes of BC cells. CCN5 protein expression is detected in estrogen receptor-α (ER-α) -positive normal breast epithelial cells as well as BC cells, which are weakly invasive and rarely metastasize depending on the functional status of ER-α. A unique molecular relation between CCN5 and ER-α has been established as the components of the same signaling pathway that coordinate some essential signals associated with the proliferation as well as delaying the disease progression from a non-invasive to invasive phenotypes. Given the importance of this connection, we determined the role of CCN5 in regulation of ER-α in different cellular settings and their functional relationship. In a genetically engineered mouse model, induced expression of CCN5 in the mammary ductal epithelial cells by doxycycline promotes ER-α expression. Similarly, CCN5 regulates ER-α expression and activity in normal and neoplastic breast cells, as documented in various <i>in vitro</i> settings such as mouse mammary gland culture, human mammary epithelial cell and different BC cell cultures in the presence or absence of human recombinant CCN5 (hrCCN5) protein. Mechanistically, at least in the BC cells, CCN5 is sufficient to induce ER-α expression at the transcription level via interacting with integrins-α6β1 and suppressing Akt followed by activation of FOXO3a. Moreover, <i>in vitro</i> and <i>in vivo</i> functional assays indicate that CCN5 treatment promotes response to tamoxifen in triple-negative BC (TNBC) cells possibly via restoring ER-α. Collectively, these studies implicates that the combination treatments of CCN5 (via activation of CCN5 or hrCCN5 treatment) and tamoxifen as potential therapies for TNBC.</p>",s banerjee,Breast cancer,2017.0,10.1038/oncsis.2017.43,Oncogenesis,Sarkar2017,Not available,,Nature,Not available,CCN5/WISP-2 restores ER-∝ in normal and neoplastic breast cells and sensitizes triple negative breast cancer cells to tamoxifen,6e4c8cc522c98fbb348321464f602e57,http://dx.doi.org/10.1038/oncsis.2017.43
14545,"<p>CCN5/WISP-2 is an anti-invasive molecule and prevents breast cancer (BC) progression. However, it is not well understood how CCN5 prevents invasive phenotypes of BC cells. CCN5 protein expression is detected in estrogen receptor-α (ER-α) -positive normal breast epithelial cells as well as BC cells, which are weakly invasive and rarely metastasize depending on the functional status of ER-α. A unique molecular relation between CCN5 and ER-α has been established as the components of the same signaling pathway that coordinate some essential signals associated with the proliferation as well as delaying the disease progression from a non-invasive to invasive phenotypes. Given the importance of this connection, we determined the role of CCN5 in regulation of ER-α in different cellular settings and their functional relationship. In a genetically engineered mouse model, induced expression of CCN5 in the mammary ductal epithelial cells by doxycycline promotes ER-α expression. Similarly, CCN5 regulates ER-α expression and activity in normal and neoplastic breast cells, as documented in various <i>in vitro</i> settings such as mouse mammary gland culture, human mammary epithelial cell and different BC cell cultures in the presence or absence of human recombinant CCN5 (hrCCN5) protein. Mechanistically, at least in the BC cells, CCN5 is sufficient to induce ER-α expression at the transcription level via interacting with integrins-α6β1 and suppressing Akt followed by activation of FOXO3a. Moreover, <i>in vitro</i> and <i>in vivo</i> functional assays indicate that CCN5 treatment promotes response to tamoxifen in triple-negative BC (TNBC) cells possibly via restoring ER-α. Collectively, these studies implicates that the combination treatments of CCN5 (via activation of CCN5 or hrCCN5 treatment) and tamoxifen as potential therapies for TNBC.</p>",s banerjee,Hormone receptors,2017.0,10.1038/oncsis.2017.43,Oncogenesis,Sarkar2017,Not available,,Nature,Not available,CCN5/WISP-2 restores ER-∝ in normal and neoplastic breast cells and sensitizes triple negative breast cancer cells to tamoxifen,6e4c8cc522c98fbb348321464f602e57,http://dx.doi.org/10.1038/oncsis.2017.43
14546,"<p>This article seeks to explain the relationship between the European Union (EU) and one of its Middle Eastern neighbors: Lebanon. By conducting an in-depth empirical single case study and engaging in competitive theory testing, this article shows that the EU in Lebanon behaves at the same time as a normative and a realist power. This article challenges both the scholarship on the EU that sees the EU as a normative power as well as scholarship that focuses on structural neorealism to explain the EU's role in its neighborhood. This article adopts an approach that is different from the mainstream approaches in two ways. First, it focuses on the entire set of policies that the EU has implemented or not in Lebanon. Second, it provides an in-depth case study centered on the interaction between the EU and Lebanon, while also looking at the regional dynamics and at the domestic tensions within Lebanon. By doing so, it shows that the EU is a ‘realist-normative’ power in the specific case of Lebanon. Thus, these two frameworks are a false dichotomy and the argument shall be tested on other cases to make it generalizable. This suggests that the constructivist-realist divide coexists in practice.</p>",chiara ruffa,,2011.0,10.1057/cep.2011.17,Comparative European Politics,Ruffa2011,Not available,,Nature,Not available,Realist-normative power Europe? Explaining EU policies toward Lebanon from an IR perspective,feee1bcca8c66d0a27a934f0b52331aa,http://dx.doi.org/10.1057/cep.2011.17
14547,"<p>Daniel Deudney's impressive reformulation of republican security theory has rightly garnered a great deal of attention from scholars of international politics. However, a close examination of Deudney's theory reveals that it rests on a series of weaknesses. His defense of a novel form of world state depends on a one-sided interpretation of state sovereignty according to which it functions chiefly as a protective device against external foes, an idiosyncratic rereading of modern republican theory and the US framers, and a highly tendentious view of US history. Notwithstanding his noteworthy attempt to break free from the insularity of US political and intellectual life, Deudney reproduces some elements of it.</p>",william scheuerman,,2010.0,10.1057/ip.2010.22,International Politics,Scheuerman2010,Not available,,Nature,Not available,‘Deudney's neorepublicanism: One-world or America first?’,08b73a1faa4f171c721d45a404c2cda9,http://dx.doi.org/10.1057/ip.2010.22
14548,"<p>This article argues that the distinction between international system and international society within the English School of International Relations theory, originally put forward by Bull and Watson, should not be abandoned. The distinction is shown to correspond to complementary etic and emic approaches to the study of social reality. The former approach is most appropriate for studying the unintended emergence of patterns of social organisation, the latter approach for the study of intersubjective negotiations over shared rules and norms within a bounded social context. Elaborating, rather than eliminating, the notion of international system suggests the adoption of the concept of ‘world system’ to complement the English School’s concept of world society. Drawing on the neo-Weberian sociology of Mann and Tilly, the article suggests that the concept of world system is not only theoretically coherent but also congruent with conceptualisations of large-scale change offered by contemporary world historians and historical sociologists.</p>",nicholas lees,,2014.0,10.1057/jird.2014.20,Journal of International Relations and Development,Lees2014,Not available,,Nature,Not available,International society is to international system as world society is to …? Systemic and societal processes in English School theory,9a738715d53fe7a7308d4fc42cbc7f28,http://dx.doi.org/10.1057/jird.2014.20
14549,"<p>The paper investigates the extent to which capacity investment considerations interact with the double marginalization effect in a simple supply chain governed by a wholesale price contract. To do so, a non-cooperative differential game model is formulated to study the pricing and capacity investment decisions in a supply chain, which consists of a supplier and a manufacturer. In such a game, there are different decision rules—open-loop, closed-loop, feedback—that are available to the supply chain participants, depending on the observability of the current state of the supply chain. While closed-loop and feedback equilibrium strategies involve the observability of other chain member’s production capacity, open-loop equilibrium strategies do not have such requirement. We examine how the supplier and the manufacturer determine, with the different decision rules, their production capacities and pricing policies to maximize their profits over an infinite planning horizon, and determine how the observability of other supply chain’s members’ production capacity affects the magnitude of the double marginalization effect. Our study suggests that the observability of other chain member’s current production capacity entails a lower production efficiency that results in a greater double marginalization effect. This allows us to conclude that observability of other chain member’s current production capacity is associated with a greater double marginalization effect.</p>",fouad ouardighi,,2014.0,10.1057/jors.2014.99,Journal of the Operational Research Society,Ouardighi2014,Not available,,Nature,Not available,Production capacity buildup and double marginalization mitigation in a dynamic supply chain,58a6714d6203e607fa0a77cdba14bcf4,http://dx.doi.org/10.1057/jors.2014.99
14550,"<p>The paper investigates the extent to which capacity investment considerations interact with the double marginalization effect in a simple supply chain governed by a wholesale price contract. To do so, a non-cooperative differential game model is formulated to study the pricing and capacity investment decisions in a supply chain, which consists of a supplier and a manufacturer. In such a game, there are different decision rules—open-loop, closed-loop, feedback—that are available to the supply chain participants, depending on the observability of the current state of the supply chain. While closed-loop and feedback equilibrium strategies involve the observability of other chain member’s production capacity, open-loop equilibrium strategies do not have such requirement. We examine how the supplier and the manufacturer determine, with the different decision rules, their production capacities and pricing policies to maximize their profits over an infinite planning horizon, and determine how the observability of other supply chain’s members’ production capacity affects the magnitude of the double marginalization effect. Our study suggests that the observability of other chain member’s current production capacity entails a lower production efficiency that results in a greater double marginalization effect. This allows us to conclude that observability of other chain member’s current production capacity is associated with a greater double marginalization effect.</p>",gary erickson,,2014.0,10.1057/jors.2014.99,Journal of the Operational Research Society,Ouardighi2014,Not available,,Nature,Not available,Production capacity buildup and double marginalization mitigation in a dynamic supply chain,58a6714d6203e607fa0a77cdba14bcf4,http://dx.doi.org/10.1057/jors.2014.99
14551,"<p>The vulnerability to real-life networks against small initial attacks has been one of outstanding challenges in the study of interrelated networks. We study cascading failures in two interrelated networks <b><i>S</i></b> and <b><i>B</i></b> composed from dependency chains and connectivity links respectively. This work proposes a realistic model for cascading failures based on the redistribution of traffic flow. We study the Barabási-Albert networks (<b><i>BA</i></b>) and Erdős-Rényi graphs (<b><i>ER</i></b>) with such structure, and found that the efficiency sharply decreases with increasing percentages of the dependency nodes for removing a node randomly. Furthermore, we study the robustness of interrelated traffic networks, especially the subway and bus network in Beijing. By analyzing different attacking strategies, we uncover that the efficiency of the city traffic system has a non-equilibrium phase transition at low capacity of the networks. This explains why the pressure of the traffic overload is relaxed by singly increasing the number of small buses during rush hours. We also found that the increment of some buses may release traffic jam caused by removing a node of the bus network randomly if the damage is limited. However, the efficiencies to transfer people flow will sharper increase when the capacity of the subway network <b><i>α<sub>S</sub></i> > <i>α</i><sub>0</sub></b>.</p>",yixian yang,Complex networks,2014.0,10.1038/srep05413,Scientific Reports,Su2014,Not available,,Nature,Not available,Robustness of Interrelated Traffic Networks to Cascading Failures,4840ca15ebd58b9a2e9f7ee719c39054,http://dx.doi.org/10.1038/srep05413
14552,"<p>The current literature on market socialism neglects the issues of social dividend payment and bureaucratization. Socialism replaces private dividends and financial markets with social dividends and central planning of investment. Socialization of dividends also leads to bureaucratization. Social dividends relate to the Principal–Principal problem of forming rational investment plans. Market Socialists address Principal–Agent problems, but do not address the Principal–Principal problem of forming investment plans.</p>
<span><i>Eastern Economic Journal</i> advance online publication, 14 March 2016; doi:<span>10.1057/eej.2016.5</span></span>",douglas mackenzie,,2016.0,10.1057/eej.2016.5,Eastern Economic Journal,MacKenzie2016,Not available,,Nature,Not available,"Social Dividends, Entrepreneurial Discretion, and Bureaucratic Rules",130b42ab6af9ea38efa8a13e17b36e76,http://dx.doi.org/10.1057/eej.2016.5
14553,"<p>This paper examines the Sachs and Woo hypothesis that the experience of Vietnam's 1989 reforms shows that China would have grown faster had she followed the ‘big bang’ approach to reform instead of the gradual approach. The paper scrutinises this hypothesis from the viewpoint of accuracy of facts, appropriateness of characterisation, and acceptability of the hypothesis. The paper finds that Sachs and Woo fall short of meeting these criteria. The paper next examines the possible source of Sachs' and Woo's pitfalls and shows that the source lies in the authors’ subjective preference for the big bang approach to reform.</p>",nazrul islam,,2008.0,10.1057/palgrave.ces.8100238,Comparative Economic Studies,Islam2008,Not available,,Nature,Not available,Vietnam's Lesson for China: An Examination of the Sachs–Woo Hypothesis,cb35ca39c049a9726f91c76433849242,http://dx.doi.org/10.1057/palgrave.ces.8100238
14554,"<p>This paper investigates the design and implementation of Kosovo’s post-war privatisation regime with reference to the policy <i>ideas</i> developed and negotiated within the bounds of Kosovo’s international transitional administration (UNMIK). Drawing on constructivist analyses of institutional change, we rely on semi-structured interviews with international officials and a review of legal documents to argue that the process of institutional change was driven largely by a contest between conflicting legal norms, rather than a contest between politically organised interest-based groups. International legal experts mobilised various competing normative paradigms residing in the background of policy debates to persuade domestic political actors that privatisation was in their interest, and to legitimise or disqualify the proposed neoliberal privatisation programme. However, the lack of consensus on the background paradigm ushered in a protracted period of ideational contestation. Privatisation in post-war Kosovo was essentially about the ‘politics of law’, as the legalisation of privatisation policy led inevitably to the contentious politicisation of legal norms.</p>
<span><i>Journal of International Relations and Development</i> advance online publication, 27 February 2015; doi:<span>10.1057/jird.2015.4</span></span>",maj grasten,,2015.0,10.1057/jird.2015.4,Journal of International Relations and Development,Grasten2015,Not available,,Nature,Not available,The politics of law in a post-conflict UN protectorate: privatisation and property rights in Kosovo (1999–2008),0090163e94e82bd559b7a6b9f2f68914,http://dx.doi.org/10.1057/jird.2015.4
14555,"<p>This paper investigates the design and implementation of Kosovo’s post-war privatisation regime with reference to the policy <i>ideas</i> developed and negotiated within the bounds of Kosovo’s international transitional administration (UNMIK). Drawing on constructivist analyses of institutional change, we rely on semi-structured interviews with international officials and a review of legal documents to argue that the process of institutional change was driven largely by a contest between conflicting legal norms, rather than a contest between politically organised interest-based groups. International legal experts mobilised various competing normative paradigms residing in the background of policy debates to persuade domestic political actors that privatisation was in their interest, and to legitimise or disqualify the proposed neoliberal privatisation programme. However, the lack of consensus on the background paradigm ushered in a protracted period of ideational contestation. Privatisation in post-war Kosovo was essentially about the ‘politics of law’, as the legalisation of privatisation policy led inevitably to the contentious politicisation of legal norms.</p>
<span><i>Journal of International Relations and Development</i> advance online publication, 27 February 2015; doi:<span>10.1057/jird.2015.4</span></span>",luca uberti,,2015.0,10.1057/jird.2015.4,Journal of International Relations and Development,Grasten2015,Not available,,Nature,Not available,The politics of law in a post-conflict UN protectorate: privatisation and property rights in Kosovo (1999–2008),0090163e94e82bd559b7a6b9f2f68914,http://dx.doi.org/10.1057/jird.2015.4
14556,"<p>One of the most pressing dilemmas of the moment concerns pluralism and the issue of justification: how does one defend a commitment to any particular position? The fear is that pluralism undercuts our ability to justify our moral and political views, and thereby leads to relativism. As I argue here, Isaiah Berlin provides an exemplary argument concerning the ties between pluralism and liberalism. Although Berlin admits there is no logical link between pluralism and liberalism, he nevertheless highlights plausible ties between pluralism and the fields of philosophy, history and politics, all of which provide good reasons for him to endorse liberalism. Moreover, these arguments indicate how pluralism differs from relativism, so that pluralists such as Berlin are not guilty of the charge of moral subjectivism. A reconsideration of Berlin's position thus provides insight into the problem of justification in a pluralist condition, one that illuminates certain features of pluralism, as well as exemplifies its compatibility with liberalism.</p>",jason ferrell,,2009.0,10.1057/cpt.2009.2,Contemporary Political Theory,Ferrell2009,Not available,,Nature,Not available,Isaiah Berlin: Liberalism and pluralism in theory and practice,dde25a9409373c4631fae46853fbcd3c,http://dx.doi.org/10.1057/cpt.2009.2
14557,"<p>This paper seeks to provide a historically informed analysis of Europe, understood as an ‘essentially contested concept’, whereby Turkey is interpreted as a critical point of reference that evokes different discursive constructions of Europe, either including or excluding Turkey. At first, the theoretical-methodological section of this paper will introduce a discourse analytical research programme which utilizes the radically constructivist notion of communication as formulated by Niklas Luhmann in order to analyze the processes of inclusion and exclusion built into various constructions of Europe. Then, the empirical section of this paper analyzes more than 40 years of British and German news coverage (1960–2004). One of the main empirical findings is that Turkey is neither seen as a stable European ‘Other’ nor as a European ‘Self’. Instead, Turkey is predominantly interpreted as ‘the thing on the (European) doorstep’, thereby stimulating various differing constructions of Europe.</p>",jochen walter,,2009.0,10.1057/jird.2009.13,Journal of International Relations and Development,Walter2009,Not available,,Nature,Not available,Turkey on the European doorstep: British and German debates about Turkey in the European Communities,a06e4229bc4ed4abbfac23adb1d0d13e,http://dx.doi.org/10.1057/jird.2009.13
14558,"<p>This paper seeks to provide a historically informed analysis of Europe, understood as an ‘essentially contested concept’, whereby Turkey is interpreted as a critical point of reference that evokes different discursive constructions of Europe, either including or excluding Turkey. At first, the theoretical-methodological section of this paper will introduce a discourse analytical research programme which utilizes the radically constructivist notion of communication as formulated by Niklas Luhmann in order to analyze the processes of inclusion and exclusion built into various constructions of Europe. Then, the empirical section of this paper analyzes more than 40 years of British and German news coverage (1960–2004). One of the main empirical findings is that Turkey is neither seen as a stable European ‘Other’ nor as a European ‘Self’. Instead, Turkey is predominantly interpreted as ‘the thing on the (European) doorstep’, thereby stimulating various differing constructions of Europe.</p>",mathias albert,,2009.0,10.1057/jird.2009.13,Journal of International Relations and Development,Walter2009,Not available,,Nature,Not available,Turkey on the European doorstep: British and German debates about Turkey in the European Communities,a06e4229bc4ed4abbfac23adb1d0d13e,http://dx.doi.org/10.1057/jird.2009.13
14559,"<p>This paper answers the question, under which conditions compliance with a supranational agreement can be obtained in cases in which a member state is unwilling to comply. It shows that the willingness to implement depends on the economic and ideological costs of policy change and on the amount of pressure exercised by societal actors. An unwilling state decides to comply when its prestige is at risk and it is ‘squeezed between pincers’, put under pressure by supranational and domestic actors simultaneously. An analysis of the implementation of EU gender equality policies in France, Germany, and the Netherlands between 1958 and 2000, shows that, depending on their identity, member states valued their prestige and were sensitive to pressure by the European Commission and the European Court. However, when their concern about prestige was not matched by domestic pressure, implementation remained predominantly rhetorical. Therefore, the Commission and the Court actively support political and judicial actors at the transnational and domestic level in order to make the ‘pincers’ work and obtain implementation in spite of high costs.</p>",anna vleuten,,2005.0,10.1057/palgrave.cep.6110066,Comparative European Politics,Vleuten2005,Not available,,Nature,Not available,Pincers and Prestige: Explaining the Implementation of EU Gender Equality Legislation,ed093bdc1168e1880f149cc5e1684b9d,http://dx.doi.org/10.1057/palgrave.cep.6110066
14560,"<p>The article proposes an alternative principal-agent-based approach for explaining the development of the relation between member states and the European Union (EU). It argues that existing accounts have drawn excessively on information-based models of delegation derived from American domestic experience, which leads them to underplay both the significance of distributional conflict between member state ‘principals’ and the nature of states as actors. The article proposes an approach which, emphasizing the particular nature of member states as principals, leads to a different conceptualization of the relation between member states and EU institutions. Building on this, it goes on to outline and explain the dynamic nature of this relationship, which culminates in what is here referred to as the institutionalization of intergovernmentalism within the EU.</p>",anand menon,,2003.0,10.1057/palgrave.cep.6110011,Comparative European Politics,Menon2003,Not available,,Nature,Not available,Member States and International Institutions: Institutionalizing Intergovernmentalism in the European Union,e6b93638621878cfaba7ddfaa97a565f,http://dx.doi.org/10.1057/palgrave.cep.6110011
14561,"<p>The vulnerability to real-life networks against small initial attacks has been one of outstanding challenges in the study of interrelated networks. We study cascading failures in two interrelated networks <b><i>S</i></b> and <b><i>B</i></b> composed from dependency chains and connectivity links respectively. This work proposes a realistic model for cascading failures based on the redistribution of traffic flow. We study the Barabási-Albert networks (<b><i>BA</i></b>) and Erdős-Rényi graphs (<b><i>ER</i></b>) with such structure, and found that the efficiency sharply decreases with increasing percentages of the dependency nodes for removing a node randomly. Furthermore, we study the robustness of interrelated traffic networks, especially the subway and bus network in Beijing. By analyzing different attacking strategies, we uncover that the efficiency of the city traffic system has a non-equilibrium phase transition at low capacity of the networks. This explains why the pressure of the traffic overload is relaxed by singly increasing the number of small buses during rush hours. We also found that the increment of some buses may release traffic jam caused by removing a node of the bus network randomly if the damage is limited. However, the efficiencies to transfer people flow will sharper increase when the capacity of the subway network <b><i>α<sub>S</sub></i> > <i>α</i><sub>0</sub></b>.</p>",yixian yang,Nonlinear phenomena,2014.0,10.1038/srep05413,Scientific Reports,Su2014,Not available,,Nature,Not available,Robustness of Interrelated Traffic Networks to Cascading Failures,4840ca15ebd58b9a2e9f7ee719c39054,http://dx.doi.org/10.1038/srep05413
14562,"<p>This article seeks to systematise and advance the theoretical debate on the causes and conditions for the privatisation of security. Drawing on previous research on private military and security companies (PMSCs) and theories from International Relations and Comparative Politics, it reconstructs functionalist, political-instrumentalist and ideationist explanations for why and under what conditions even ‘strong’ and democratic Organisation for Economic Co-operation and Development states (extensively) use PMSCs. An analysis of inter-temporal and cross-national (United States, British, German and French) patterns of security privatisation indicates that all the three theoretical models point out causes and conditions that are relevant for a comprehensive explanation, but none is sufficient alone. Therefore, the article uses both the models and the empirical evidence to propose a synthetic perspective, which treats different explanatory conditions and logics as complementary, rather than rival. Going beyond the atheoretical conclusion that a multitude of disconnected factors are in some way relevant for a comprehensive explanation of security privatisation, I develop a thin and a thick synthesis that rely on a domain-of-application approach and sequencing, respectively. The thin synthesis spells out how different explanatory factors operate in specific domains, whereas the thick synthesis elaborates how different conditions and mechanisms apply to different phases of security privatisation and how they interrelate.</p>",andreas kruck,,2013.0,10.1057/jird.2013.4,Journal of International Relations and Development,Kruck2013,Not available,,Nature,Not available,Theorising the use of private military and security companies: a synthetic perspective,f2aae61cdba3cd26a445690449b8df7b,http://dx.doi.org/10.1057/jird.2013.4
14563,"<p>Recognising that the world into which students emerge upon graduation is characterised by constant change, we embrace a critical pedagogy that can be implemented in the classroom through the use of freehand drawing. Freehand drawing is a technique that can stimulate a critical stance, as visual representations allow us to comprehend the world differently, while permitting us see how others understand the world. First year students, in their first lecture, were asked to draw their interpretations of Irish politics and to explain in writing what they had drawn. The students were then placed in groups and asked to note what they saw in each other's drawings, allowing for the identification of general patterns and themes. In this context, freehand drawing facilitates our ability to: ‘see’ how we understand a topic and that there are multiple ways of understanding; test theories, orthodoxies and accepted truths; scrutinise tacit assumptions; and ponder other possibilities. In employing freehand drawing in this manner, our aim is to create a learning environment where students develop their capacity for critical self-reflection.</p>",paul donnelly,,2013.0,10.1057/eps.2013.12,European Political Science,donnelly2013,Not available,,Nature,Not available,Engaging Students in the Classroom: ‘How Can I Know What I Think Until I See What I Draw?’,b90f68e6c3f5b4c05f397c19a9caf3df,http://dx.doi.org/10.1057/eps.2013.12
14564,"<p>Recognising that the world into which students emerge upon graduation is characterised by constant change, we embrace a critical pedagogy that can be implemented in the classroom through the use of freehand drawing. Freehand drawing is a technique that can stimulate a critical stance, as visual representations allow us to comprehend the world differently, while permitting us see how others understand the world. First year students, in their first lecture, were asked to draw their interpretations of Irish politics and to explain in writing what they had drawn. The students were then placed in groups and asked to note what they saw in each other's drawings, allowing for the identification of general patterns and themes. In this context, freehand drawing facilitates our ability to: ‘see’ how we understand a topic and that there are multiple ways of understanding; test theories, orthodoxies and accepted truths; scrutinise tacit assumptions; and ponder other possibilities. In employing freehand drawing in this manner, our aim is to create a learning environment where students develop their capacity for critical self-reflection.</p>",john hogan,,2013.0,10.1057/eps.2013.12,European Political Science,donnelly2013,Not available,,Nature,Not available,Engaging Students in the Classroom: ‘How Can I Know What I Think Until I See What I Draw?’,b90f68e6c3f5b4c05f397c19a9caf3df,http://dx.doi.org/10.1057/eps.2013.12
14565,"<p>The European Union is often presented as an entity that has ‘moved beyond’ the model of organising political life along the way of the modern sovereign state. This paper questions this understanding by engaging a set of texts that could be understood as exemplary of the EU's official discourse of Europe: EU's failed Constitutional Treaty and Javier Solana's collected speeches. A paradox is herein identified: the values that are said to sustain Europe's identity and upon which Europe is founded are simultaneously presented as distinctly European <i>and</i> universal. It is suggested that Europe is being crafted in a pendular oscillation between particularising and universalising the values upon which Europe allegedly rests. By drawing on critical International Relations theory, the paper suggests that this very contradictory oscillation between particularising and universalising Europe's values to an important extent mirrors modern statecraft. One should therefore think twice before announcing the construction of the European Union as something qualitatively different from, or ‘gentler’ than, modern statecraft.</p>",stefan borg,,2013.0,10.1057/jird.2013.8,Journal of International Relations and Development,Borg2013,Not available,,Nature,Not available,"European integration and the problem of the state: universality, particularity, and exemplarity in the crafting of the European Union",36c7ad5ace13b53a24aac005c063fc8c,http://dx.doi.org/10.1057/jird.2013.8
14566,"<p>This article investigates whether or not the dominance of neo-liberalism in the European Union’s (EU’s) trade and development politics has been moderated by the global economic crisis and the changing global economic order. It combines the methods of Critical Discourse Analysis (CDA) with critical forms of international political economy. It demonstrates how neo-liberalism has infused the EU’s approach, and the concept of interdiscursivity is used to analyse how neo-liberalism is articulated with other discourses, and how this has evolved. Key policy discourses and nodal discourses are traced in two major EU texts on trade and development. The one from 2002 articulates a strongly neo-liberal vision of globalisation, free market reform and inter-regional integration. In the 2012 document, the sense of a neo-liberal trajectory is downplayed and a more realist geoeconomic discourse emerges. A review of the EU’s other texts and its behaviour reveals a tougher approach, which creates a new subset of worthy developing countries and treats the others as emerging rivals. In conclusion, the core tenets of neo-liberalism are still present, however, they are embedded in a new policy configuration and geoeconomic context.</p>
<span><i>Journal of International Relations and Development</i> advance online publication, 3 April 2015; doi:<span>10.1057/jird.2015.10</span></span>",patrick holden,,2015.0,10.1057/jird.2015.10,Journal of International Relations and Development,Holden2015,Not available,,Nature,Not available,Neo-liberalism by default? The European Union’s trade and development policy in an era of crisis,692ad75b99c87f7c3bdbe98594d4642c,http://dx.doi.org/10.1057/jird.2015.10
14567,"<p>For nearly 50 years, powerful politically connected criminal actors called ‘dons’ (or area leaders) have occupied – Mafia style – some of Jamaica's deprived urban communities, and enacted new, outlaw forms of community leadership. In these communities, notoriously labelled ‘garrisons’, dons have ‘manufactured consent’ for their illicit rule, using coercive tactics and by positioning themselves as legitimate civic leaders. In the process, these rogue actors have not only gained acceptance among significant numbers of the subaltern class but also (tacit) political recognition in the wider society. Genuine civil society has been eclipsed in Jamaica's urban garrisons due to the persistence of this rogue leadership. Still, a more hopeful outlook for Jamaica may be possible. Drawing upon previous research outlining the widespread struggle against the Mafia led by members of Italian civil society, and the ensuing decline in its omnipotence in that country, the paper considers the implications of the positive developments in Italy for the noticeable movement towards degarrisonisation in Jamaica, and contemplates what role a resurrected Jamaican civil society might play in this process.</p>",hume johnson,,2010.0,10.1057/cpcs.2009.18,Crime Prevention and Community Safety: An International Journal,Johnson2010,Not available,,Nature,Not available,Towards degarrisonisation in Jamaica: A place for civil society,577a1bc3e85efef4c656785de920e56c,http://dx.doi.org/10.1057/cpcs.2009.18
14568,"<p>The paper reconstructs Ferenczi’s unique and largely neglected <i>physiology of pleasure</i>. It highlights the prominent place of the libido in Ferenczi’s writings, the transition from the <i>physiology of use</i> to the <i>physiology of pleasure</i> and the role of trauma in Ferenczi’s work with a special emphasis on the beauty and plasticity of the body, the relations between its organs as well as the adaptive potential, the <i>Orphic powers</i>, and the natural vigor of the human organism. Ferenczi’s theoretical assumptions and his powerful images of the human organism are examined in the light of Goethe’s, Schopenhauer’s, and Nietzsche’s philosophies.</p>",galina hristeva,,2013.0,10.1057/ajp.2013.23,The American Journal of Psychoanalysis,Hristeva2013,Not available,,Nature,Not available,“Uterus Loquitur”: Trauma and the Human Organism in Ferenczi’s “Physiology of Pleasure”<tlnref><sup>∗</sup></tlnref>,c2b105042e08efa8c9a3ecb2d4ae93b2,http://dx.doi.org/10.1057/ajp.2013.23
14569,"<p>In responding to the critics of my Tartu lecture, I firstly examine a little further the ‘community’ aspect of science as a practice, because I do not quite share Lebows's optimism that ‘ethics’ applied to the scientific enterprise are powerful enough to prevent its derailments. Secondly, I admit that a lack of an explicit historical dimension in my lectures noticed by Suganami was dictated more by circumstances than by an oversight or a denial of its importance. While Suganami believes that a sense of history, as well as some criticism of both international relations (IR) and history on the meta level, are sufficient for a new and fruitful beginning of IR analysis, I'm emphasizing the contribution which ordinary language philosophy could make to a new type of social analysis and, in particular, the theory of speech acts and of ‘institutions’ <i>à la</i> Searle. Thirdly, instead of putting up a straw man and knocking him down, as Wight has done in his misunderstanding of my position, I'm addressing the issue of ‘scientific realism’ and its alleged predominance in the philosophy of science, the question of ontology and epistemology and, finally, the issue of whether the claims that ‘nature’ directly speaks to us is of any help in explaining actions rather than events.</p>",friedrich kratochwil,,2007.0,10.1057/palgrave.jird.1800113,Journal of International Relations and Development,Kratochwil2007,Not available,,Nature,Not available,"Of communities, gangs, historicity and the problem of Santa Claus: replies to my critics",3bbf272f3b08aa9696efa7a9283e5414,http://dx.doi.org/10.1057/palgrave.jird.1800113
14570,"<p>Introduction There are presently three English language bibliographies for the study of Dutch politics: Daalder (1989) and Andeweg and Cohen de Lare (1999a, b). Andeweg and Cohen de Lara (1999b) is an abridged version of their (1999a) bibliography, to be used in conjunction with Daalder (1989).</p>",jaap woldendorp,,2008.0,10.1057/ap.2008.13,Acta Politica,Woldendorp2008,Not available,,Nature,Not available,English Language Sources for the Study of Dutch Politics 1998–2008,da6275b4a4a0ead025de864f02a7734b,http://dx.doi.org/10.1057/ap.2008.13
14571,"<p>The vulnerability to real-life networks against small initial attacks has been one of outstanding challenges in the study of interrelated networks. We study cascading failures in two interrelated networks <b><i>S</i></b> and <b><i>B</i></b> composed from dependency chains and connectivity links respectively. This work proposes a realistic model for cascading failures based on the redistribution of traffic flow. We study the Barabási-Albert networks (<b><i>BA</i></b>) and Erdős-Rényi graphs (<b><i>ER</i></b>) with such structure, and found that the efficiency sharply decreases with increasing percentages of the dependency nodes for removing a node randomly. Furthermore, we study the robustness of interrelated traffic networks, especially the subway and bus network in Beijing. By analyzing different attacking strategies, we uncover that the efficiency of the city traffic system has a non-equilibrium phase transition at low capacity of the networks. This explains why the pressure of the traffic overload is relaxed by singly increasing the number of small buses during rush hours. We also found that the increment of some buses may release traffic jam caused by removing a node of the bus network randomly if the damage is limited. However, the efficiencies to transfer people flow will sharper increase when the capacity of the subway network <b><i>α<sub>S</sub></i> > <i>α</i><sub>0</sub></b>.</p>",yixian yang,Statistical physics,2014.0,10.1038/srep05413,Scientific Reports,Su2014,Not available,,Nature,Not available,Robustness of Interrelated Traffic Networks to Cascading Failures,4840ca15ebd58b9a2e9f7ee719c39054,http://dx.doi.org/10.1038/srep05413
14572,"<p>Responding to the special issue editors request, I conduct a retrospective evaluation of my own scholarship on realism and the end of the Cold War. I reprise the main arguments in light of what appears to be the most probative new evidence. I find that ,even though almost all scholars who write about the Cold War's end either dismiss or denounce explanations informed by realist theory, these explanations actually have stood the test of time and new evidence.</p>",william wohlforth,,2011.0,10.1057/ip.2011.17,International Politics,Wohlforth2011,Not available,,Nature,Not available,No one loves a realist explanation,99faa11e56cfec0583fba2cd65a87a8f,http://dx.doi.org/10.1057/ip.2011.17
14573,"<p>The visibility of public health in world politics has increased because of epidemics, such as HIV/AIDS, and tensions between public health and international trade, including those related to patents and access to essential medicines. Advocacy for raising the profile of public health on diplomatic agendas raises fundamental theoretical questions about public health: why should public health be higher on global diplomatic agendas, and how should the pursuit of better public health globally be structured and implemented? This article explores answers to these questions provided by traditional theory on public health and analyzes the problems the anarchical context of international relations poses for such answers. A major part of this analysis utilizes theories from the discipline of international relations – realism, institutionalism, liberalism, and social constructivism – to illuminate theoretical challenges global health advocacy faces in making public health more important in world politics. These theories help identify a theoretical conundrum that public health faces, and the article considers various ways in which to handle this conundrum in light of the desire to increase the role public health plays in international relations.</p>",david fidler,,2003.0,10.1057/palgrave.sth.8700003,Social Theory & Health,Fidler2003,Not available,,Nature,Not available,Disease and Globalized <span>Anarchy</span>: Theoretical Perspectives on the Pursuit of Global Health,ac828049e89681248c4ab23350f92bc0,http://dx.doi.org/10.1057/palgrave.sth.8700003
14574,"<p>This paper argues that a political theory of global distributive justice, as envisaged by neo-Rawlsian cosmopolitans, makes no sense. Political theorists such as Charles Beitz, Thomas Pogge, and Darrel Moellendorf have argued that John Rawls's egalitarian conception of distributive justice should be applied globally, despite Rawls's own insistence on its limited applicability to domestic society. Against this position, two main arguments for skepticism about global egalitarian distributive justice are offered. First, the world cannot plausibly be understood in terms of a society in Rawls's sense, and a Rawlsian global original position cannot generate politically meaningful principles of distributive justice. Second, global distributive justice cannot serve as an achievable goal of international political endeavor within an environment that is, and should remain, anarchic; the utopian world government that it requires seems unrealistic, and in any event is politically undesirable from a liberal perspective. The cosmopolitan ideal of global distributive justice should have no weight in moral reasoning about international political choice.</p>",menno kamminga,,2006.0,10.1057/palgrave.ap.5500136,Acta Politica,Kamminga2006,Not available,,Nature,Not available,Why Global Distributive Justice Cannot Work,f2f5073b37c25c401169b4a1c7d34b4f,http://dx.doi.org/10.1057/palgrave.ap.5500136
14575,"<p>This study deploys a structuralist framework of analysis, modified by elements from other theories, to examine the place of the Middle East in the world hierarchy. It surveys the origins of the regional system in imperialism's peripheralisation and fragmentation of the region, the core-periphery clientalist hierarchy thereby established, regional agency within the system, including the foreign policies of dependent and rebellious states, and the on-going struggle over the hierarchical order between revisionist forces in the Middle East and the global hegemons.</p>",raymond hinnebusch,,2011.0,10.1057/jird.2010.3,Journal of International Relations and Development,Hinnebusch2011,Not available,,Nature,Not available,The Middle East in the world hierarchy: imperialism and resistance,c270e51b2d23c0260c2e57d0824c4144,http://dx.doi.org/10.1057/jird.2010.3
14576,"<p>This article critically examines neo-republican democratic theory, as articulated by Philip Pettit, with respect to its capacity to address some of the pressing challenges of our times. While the neo-republican focus on domination has great promise, it mistakenly commits to the position that democracy—the primary tool with which we fight domination—is limited to state activity. Examining this error helps us make sense of two additional problems with his theory: an overestimation of the capacity of legislative bodies to identify sufficient responses to practices of domination, and the potential conflict between avoiding state domination of the general citizenry and avoiding state domination of a part of it. Minimizing domination is simply too demanding and complex a task for us to rely on one institutional structure, no matter how well designed, to accomplish.</p>",david watkins,,2015.0,10.1057/pol.2015.18,Polity,Watkins2015,Not available,,Nature,Not available,Institutionalizing Freedom as Non-Domination: Democracy and the Role of the State,f9a9be01ba1dd64ae644aaa6d0fe5f34,http://dx.doi.org/10.1057/pol.2015.18
14577,"<p>Liberal internationalism represents a package of evolving and contending commitments, and this article traces the development within it of one practice with a longer history, namely the allocation of special responsibilities. Responsibilities are those things for which actors are held accountable and, internationally, these have negotiated between sovereign equality and material inequality, in search of a means of more effectively dealing with global problems. The definition of these responsibilities generates an intense politics and these are reviewed through the remit of the Security Council. The article considers the basis for the allocation of traditional special responsibilities for security to the Council and then tracks their extension in recent years to the issue of humanitarian protection. The vehicle for this has been the transformation of a practice about the use of the veto, towards one that calls for its non-use in humanitarian cases. This analysis of special responsibilities unsettles the separation between order and justice, and points to the challenges currently facing liberal internationalism.</p>",ian clark,,2012.0,10.1057/ip.2012.27,International Politics,Clark2012,Not available,,Nature,Not available,"Liberal internationalism, the practice of special responsibilities and evolving politics of the security council",ba3132f20eb525f020561ef196c856d5,http://dx.doi.org/10.1057/ip.2012.27
14578,"<p>This article traces the current state of dominant theories or international relations (IR), particularly structural realism, liberal theories of preference, and rational choice theory to six foundation assumptions regarding human nature located in the canonical liberal texts from which neoclassical economics also proceeds. These assumptions are deductively and empirically critiques and their limitations for social theorizing are explicated. An alternative view of ‘the human condition’ more fruitful for constructivist theorizing in IR is generated with recourse to the Aristotelian analysis of Hannah Arendt.</p>",rodney hall,,2006.0,10.1057/palgrave.jird.1800090,Journal of International Relations and Development,Hall2006,Not available,,Nature,Not available,Human nature as behaviour and action in economics and international relations theory,842a63bbb5957c3018d88d7f80945a33,http://dx.doi.org/10.1057/palgrave.jird.1800090
14579,"<p>This paper qualitatively revisits the thesis that rentier regimes can draw on their non-tax revenues to buy political legitimacy and stability. Exploring the material/moral interplay in Mideast rentier politics, I show why and how rents may provide for provisional, but not sustainable, stability for authoritarian rentier regimes. I propose distinguishing between negative and positive political legitimacy, the former being about ‘what is legitimate’ (liberty <i>vs</i> security), and the latter about ‘who is the legitimator’ (divine/hereditary right <i>vs</i> popular sovereignty). Sustainable stability is predicated on having both legitimacies. Rentier regimes, however, often draw exclusively on negative political legitimacy. These regimes can use rents to buy time — through coercion and expediency — contriving an imagery of a lusty Leviathan. But due to the diversity of rents and the temporal shifts in their revenues, this social contract is materially contingent and morally frail — rendering authoritarian rentier regimes, not least in the Middle East, more mortal than they, and many observers, are ready to admit.</p>
<span><i>Journal of International Relations and Development</i> advance online publication, 20 February 2015; doi:<span>10.1057/jird.2014.32</span></span>",uriel abulof,,2015.0,10.1057/jird.2014.32,Journal of International Relations and Development,Abulof2015,Not available,,Nature,Not available,‘Can’t buy me legitimacy’: the elusive stability of Mideast rentier regimes,7b64b0dfdb08982c75ba4cba6208da0c,http://dx.doi.org/10.1057/jird.2014.32
14580,"<p>What lessons can be drawn from the unprecedented growth and spectacular collapse of financial pyramid schemes in Albania? This paper discusses the origins of the pyramid schemes and the way the authorities handled them. It also analyzes the economic effects of the pyramid schemes, concluding that despite the descent into anarchy triggered by the schemes' collapse, their direct effects on the economy are difficult to specify and appear to have been limited. Finally, the paper argues that prevention of pyramid schemes is better than cure and that governments and international financial institutions should be vigilant in clamping down on frauds.</p>",chris jarvis,,2000.0,10.2307/3867623,IMF Staff Papers,Jarvis2000,Not available,,Nature,Not available,The Rise and Fall of the Pyramid Schemes in Albania,277d5fd6004564bd9c1854d133d6c418,http://dx.doi.org/10.2307/3867623
14581,"<p>Morgenthau’s characterizations of the politics among nations in the twentieth century remain a contested, but still compelling, vision of international relations in the twenty-first century. Hence, different strains of ‘critical theory’ are needed as the means of crisis detection, interpretation and legitimation. Without accepting the terms of Morgenthau’s analysis uncritically, this article looks at how critical theory insights, as developed in different streams of Frankfurt School-inspired critique, can arguably guide new discourse coalitions and policy experts in coping with the challenges of crises in the post-Cold War world. The contradictions posed by the inequities of social wealth’s production and distribution are profound and obdurate. Exerting verdictive power, like Morgenthau, in managing the global crises, national security challenges or financial instability conflicts, can be useful.</p>",timothy luke,,2013.0,10.1057/ip.2013.36,International Politics,Luke2013,Not available,,Nature,Not available,"Working towards critical realism: Scientific man, power politics and democratic decline",ee70cf0e5c59efb13df796219934e3cc,http://dx.doi.org/10.1057/ip.2013.36
14582,How closing streets and removing traffic lights speed up urban travel,linda baker,,2009.0,10.1038/scientificamerican0209-20,Scientific American,Baker2009,Not available,,Nature,Not available,Detours by Design,39db9e40434a0ea0b027ed6d4c9fed7e,http://dx.doi.org/10.1038/scientificamerican0209-20
14583,"<p>This paper examines the Sachs-Woo hypothesis that the gradual approach to reform, though successful in China, was not possible in the USSR because of structural differences between these two economies. To examine this hypothesis, this paper abstracts from the issue of structural differences by focusing on the industrial sector only and compares the state-owned enterprise (SOE) reforms in China under Deng and in the USSR under Gorbachev. Apart from concerning the same sector, these reforms were roughly contemporaneous, and hence their comparison provides a suitable test of the Sachs-Woo hypothesis. The test shows that the hypothesis does not live up to it.</p>",nazrul islam,,2011.0,10.1057/ces.2010.30,Comparative Economic Studies,Islam2011,Not available,,Nature,Not available,Was the Gradual Approach Not Possible in the USSR? A Critique of the Sachs-Woo ‘Impossibility Hypothesis’,0d19334356c74faa862b79043e398baa,http://dx.doi.org/10.1057/ces.2010.30
14584,"<p>Recent spikes in international food prices and the occurrence of food riots in the period 2007–2008 have led many researchers to investigate more closely the links between rising food prices and conflict or political instability. However, this emerging literature suffers from a number of shortcomings. The objective of this article is to analyze these shortcomings further, highlight their theoretical and empirical implications, and offer ways of addressing them. I focus on three main issues. First, I look at the recurring lack of precision in the use of concepts such as political instability and conflict, and in particular the food riot concept itself. Second, I examine the often uncritical data gathering based on framing by media sources without a closer analysis of the events that took place on the ground. And third, I focus on the issue of presupposed and understudied economic as well as political causal mechanisms.</p>",leila demarest,,2014.0,10.1057/ejdr.2014.52,European Journal of Development Research,Demarest2014,Not available,,Nature,Not available,Food <span>Price</span> Rises and Political Instability: Problematizing a Complex Relationship,29f39eedd996a4dae011f1ed4d506577,http://dx.doi.org/10.1057/ejdr.2014.52
14585,"<p>This article explores and criticizes key assumptions of contemporary cosmopolitanism, not least the notion of post-sovereignty, trying to understand how the cosmopolitan power and sovereignty critique may be very compatible with present-day reconfigurations and relegitimizations of state power and sovereignty. Through a critique of how cosmopolitans sketch out a problematic nation state's past and a more factual efficient and morally appropriate post-nation state condition the article claims that cosmopolitanism may come to serve as legitimizing cover for a new sovereigntist language and practice wielded by the same powers who were dominant in the nation state age, namely the Western states. The purpose of the article is to ask whether cosmopolitanism and humanitarianism have become the new sovereigntist language uniting state officials and state-critical scholars?</p>",mikkel thorup,,2010.0,10.1057/ip.2010.30,International Politics,Thorup2010,Not available,,Nature,Not available,Cosmopolitanism: Sovereignty denied or sovereignty restated?,8ce2a1d2057ffc25710290a1a397cc53,http://dx.doi.org/10.1057/ip.2010.30
14586,"<p>This article revisits the figure of the ‘third world sweatshop worker’, long iconic of the excesses of the global expansion of flexible accumulation in late twentieth-century capitalism. I am interested in how feminist activists concerned with the uneven impact of neo-liberal policies can engage in progressive political interventions without participating in the ‘culture of global moralism’ that continues to surround conventional representations of third world workers. I situate my analysis in the national space of Bangladesh, where the economy is heavily dependent on the labour of women factory workers in the garment industry and where local feminist understandings of the ‘sweatshop economy’ have not always converged with global feminist/left concerns about the exploitation inherent in the (now not so new) New International Division of Labor. The tensions or disjunctures between ‘global’ and ‘local’ feminist viewpoints animate the concerns of this article. I argue that de-contextualized critiques derived from abstract notions of individual rights, and corresponding calls for change from above – calls on the conscience of the feminist and the consumer, for instance – can entail troubling analytical simplifications. They highlight some relations of power while erasing others, thereby enacting a different kind of violence and at times undermining mobilizations on the ground. I draw attention to the multiple fields of power through which much of the activism across borders continues to be produced and reproduced discursively. This kind of framing fits all too easily into existing cultural scripts about gender and race elsewhere, and produces ethical obligations to ‘save’ women workers.</p>",dina siddiqi,,2009.0,10.1057/fr.2008.55,Feminist Review,Siddiqi2009,Not available,,Nature,Not available,do Bangladeshi factory workers need saving? Sisterhood in the post-sweatshop era<footref><sup>1</sup></footref>,c2ad1cad392894f53a7f9fc0ad926c08,http://dx.doi.org/10.1057/fr.2008.55
14587,"<p>Liberal internationalism represents a package of evolving and contending commitments, and this article traces the development within it of one practice with a longer history, namely the allocation of special responsibilities. Responsibilities are those things for which actors are held accountable and, internationally, these have negotiated between sovereign equality and material inequality, in search of a means of more effectively dealing with global problems. The definition of these responsibilities generates an intense politics and these are reviewed through the remit of the Security Council. The article considers the basis for the allocation of traditional special responsibilities for security to the Council and then tracks their extension in recent years to the issue of humanitarian protection. The vehicle for this has been the transformation of a practice about the use of the veto, towards one that calls for its non-use in humanitarian cases. This analysis of special responsibilities unsettles the separation between order and justice, and points to the challenges currently facing liberal internationalism.</p>",christian reus-smit,,2012.0,10.1057/ip.2012.27,International Politics,Clark2012,Not available,,Nature,Not available,"Liberal internationalism, the practice of special responsibilities and evolving politics of the security council",ba3132f20eb525f020561ef196c856d5,http://dx.doi.org/10.1057/ip.2012.27
14588,"<p>Contrary to the conventional wisdom, we argue that democratic institutions are not a prerequisite to an independent judiciary. Rather, the need for foreign investment is a necessary and, in some cases, perhaps sufficient condition for the establishment of at least nominally independent judicial institutions. We consider Chile immediately after Pinochet and the Philippines at the outset of the Marcos regime. We consider the similarity of court reforms implemented by these two regimes. These cases illustrate two distinct points in the life span of an authoritarian government. The Chilean case features the time period that begins a transition to democracy prior to consolidation. The Philippine case features the time period of ascension of the authoritarian. Despite the different environments, both regimes implemented court reforms primarily designed to attract foreign direct investment into their troubled economies.</p>",charles smith,,2010.0,10.1057/jird.2009.34,Journal of International Relations and Development,Smith2010,Not available,,Nature,Not available,Court reform in transitional states: Chile and the Philippines,a08a869dbde4e131b25e2cea295dda5c,http://dx.doi.org/10.1057/jird.2009.34
14589,"<p>Contrary to the conventional wisdom, we argue that democratic institutions are not a prerequisite to an independent judiciary. Rather, the need for foreign investment is a necessary and, in some cases, perhaps sufficient condition for the establishment of at least nominally independent judicial institutions. We consider Chile immediately after Pinochet and the Philippines at the outset of the Marcos regime. We consider the similarity of court reforms implemented by these two regimes. These cases illustrate two distinct points in the life span of an authoritarian government. The Chilean case features the time period that begins a transition to democracy prior to consolidation. The Philippine case features the time period of ascension of the authoritarian. Despite the different environments, both regimes implemented court reforms primarily designed to attract foreign direct investment into their troubled economies.</p>",mark farrales,,2010.0,10.1057/jird.2009.34,Journal of International Relations and Development,Smith2010,Not available,,Nature,Not available,Court reform in transitional states: Chile and the Philippines,a08a869dbde4e131b25e2cea295dda5c,http://dx.doi.org/10.1057/jird.2009.34
14590,"<p>Mainstream critiques of human security theory and practice have criticized how human security is being conceptualized, with a specific focus on how the absence of a precise and universally accepted definition hinders its practical application. Rejecting these critiques as an explanation for the policy failures of human security agendas, this article argues that the difficulties experienced in operationalizing human security lie in the myriad ways human security policies have revealed themselves to be subordinate to an existing, well-established and equally diffuse policy agenda: neoliberalism. The specific case study examines Canada, a prominent member of the human security vanguard, and its unwillingness to regulate transnational corporate conduct that contributes to human insecurity.</p>",kyle grayson,,2010.0,10.1057/ip.2010.20,International Politics,Grayson2010,Not available,,Nature,Not available,"Human security, neoliberalism and corporate social responsibility",ebaaf0ec309a523b32bbc61e71005847,http://dx.doi.org/10.1057/ip.2010.20
14591,"<p>The paper begins with research studying the concept and nature of Intellectual Capital (IC), as well as how close IC firms are to the stochastic frontier. Then basic concepts of complexity theory – such as agents, self-organized criticality (SOC), connectivities, fractals, and power laws (PLs) – are used to distinguish between two kinds of IC firms’ success: traditional SOC applications to how firms maintain their position in a changing industry <i>vs</i>. how an IC firm (such as Apple) creates a new stochastic frontier. The research sets up PLs as indicators of whether or not firms and industries are SOC-effective and includes propositions about: (1) How IC firms benefit from complexity dynamics and SOC; (2) How PL distributions are indicators of efficacious SOC and adaptivity; and (3) Why IC attributes serve to create more transient dynamics pertaining to the stochastic frontier and the rest of the industry's rank/frequency distribution.</p>",bill mckelvey,,2013.0,10.1057/kmrp.2013.18,Knowledge Management Research & Practice,McKelvey2013,Not available,,Nature,Not available,Towards an econophysics view of intellectual capital dynamics: from self-organized criticality to the stochastic frontier,d52b2af1154ddd19953d375771b1a682,http://dx.doi.org/10.1057/kmrp.2013.18
14592,"<p>The paper begins with research studying the concept and nature of Intellectual Capital (IC), as well as how close IC firms are to the stochastic frontier. Then basic concepts of complexity theory – such as agents, self-organized criticality (SOC), connectivities, fractals, and power laws (PLs) – are used to distinguish between two kinds of IC firms’ success: traditional SOC applications to how firms maintain their position in a changing industry <i>vs</i>. how an IC firm (such as Apple) creates a new stochastic frontier. The research sets up PLs as indicators of whether or not firms and industries are SOC-effective and includes propositions about: (1) How IC firms benefit from complexity dynamics and SOC; (2) How PL distributions are indicators of efficacious SOC and adaptivity; and (3) Why IC attributes serve to create more transient dynamics pertaining to the stochastic frontier and the rest of the industry's rank/frequency distribution.</p>",maria salmador,,2013.0,10.1057/kmrp.2013.18,Knowledge Management Research & Practice,McKelvey2013,Not available,,Nature,Not available,Towards an econophysics view of intellectual capital dynamics: from self-organized criticality to the stochastic frontier,d52b2af1154ddd19953d375771b1a682,http://dx.doi.org/10.1057/kmrp.2013.18
14593,"<p>The paper begins with research studying the concept and nature of Intellectual Capital (IC), as well as how close IC firms are to the stochastic frontier. Then basic concepts of complexity theory – such as agents, self-organized criticality (SOC), connectivities, fractals, and power laws (PLs) – are used to distinguish between two kinds of IC firms’ success: traditional SOC applications to how firms maintain their position in a changing industry <i>vs</i>. how an IC firm (such as Apple) creates a new stochastic frontier. The research sets up PLs as indicators of whether or not firms and industries are SOC-effective and includes propositions about: (1) How IC firms benefit from complexity dynamics and SOC; (2) How PL distributions are indicators of efficacious SOC and adaptivity; and (3) Why IC attributes serve to create more transient dynamics pertaining to the stochastic frontier and the rest of the industry's rank/frequency distribution.</p>",patricio morcillo,,2013.0,10.1057/kmrp.2013.18,Knowledge Management Research & Practice,McKelvey2013,Not available,,Nature,Not available,Towards an econophysics view of intellectual capital dynamics: from self-organized criticality to the stochastic frontier,d52b2af1154ddd19953d375771b1a682,http://dx.doi.org/10.1057/kmrp.2013.18
14594,"<p>The paper begins with research studying the concept and nature of Intellectual Capital (IC), as well as how close IC firms are to the stochastic frontier. Then basic concepts of complexity theory – such as agents, self-organized criticality (SOC), connectivities, fractals, and power laws (PLs) – are used to distinguish between two kinds of IC firms’ success: traditional SOC applications to how firms maintain their position in a changing industry <i>vs</i>. how an IC firm (such as Apple) creates a new stochastic frontier. The research sets up PLs as indicators of whether or not firms and industries are SOC-effective and includes propositions about: (1) How IC firms benefit from complexity dynamics and SOC; (2) How PL distributions are indicators of efficacious SOC and adaptivity; and (3) Why IC attributes serve to create more transient dynamics pertaining to the stochastic frontier and the rest of the industry's rank/frequency distribution.</p>",jose rodriguez-anton,,2013.0,10.1057/kmrp.2013.18,Knowledge Management Research & Practice,McKelvey2013,Not available,,Nature,Not available,Towards an econophysics view of intellectual capital dynamics: from self-organized criticality to the stochastic frontier,d52b2af1154ddd19953d375771b1a682,http://dx.doi.org/10.1057/kmrp.2013.18
14595,"<p>This article assesses the extent to which the emergence of New Labour represented a critical juncture in Labour thinking in relation to small business and enterprise policy. It does this through an assessment of attitudes to enterprise expressed in general election manifestos over the course of the twentieth century. These show that while the emergence of New Labour marked a shift from its immediate past, there is evidence of broad continuities with periods prior to the 1980s. In particular there is some evidence of a distinct ‘Labour’ approach to building and sustaining small business-led regional economies which have policy implications today.</p>",richard beresford,,2015.0,10.1057/bp.2015.7,British Politics,Beresford2015,Not available,,Nature,Not available,New Labour and enterprise policy: Continuity or change? Evidence from general election manifestos,fac036c88d28ea6016143049698d3b34,http://dx.doi.org/10.1057/bp.2015.7
14596,"<p>In their attempt to explain change in international politics, an emerging group of scholars in the 1990s emphasised the importance of ‘non-material factors’. Questions about the creation, evolution, and impact of norms obtained a prominent place in their theorising. Cast in a constructivist frame, this norm research promised to be a viable alternative to established approaches and while it has indeed broadened the perspective on state behaviour in International Relations, we argue that at the same time it entailed major conceptual and methodological problems which have not yet been spelled out comprehensively. Mainly, the insight that norms are constantly renegotiated in social interaction has been lost in the translation of social-theoretical claims of early constructivism into empirical research agendas. The ensuing research is best characterised as a cultural-determinist framework which is ultimately ill-equipped for the initial proposition of explaining change. We develop this critique by reconstructing the theoretical and methodological decisions of constructivist norm research. We then propose to re-conceptualise the connection between norms and action and suggest an interpretive methodology that allows delivering on the ambitious promise to explain processes of normative change in international politics. We illustrate this claim by reviewing constructivist norm research on ‘humanitarian interventions’ and by outlining a relational-processualist perspective on this issue.</p>",matthias hofferberth,,2014.0,10.1057/jird.2014.1,Journal of International Relations and Development,Hofferberth2014,Not available,,Nature,Not available,<i>Lost in translation</i>: a critique of constructivist norm research,2d7a64242f35ac66f9a7b44e18ef1ed1,http://dx.doi.org/10.1057/jird.2014.1
14597,"<p>In their attempt to explain change in international politics, an emerging group of scholars in the 1990s emphasised the importance of ‘non-material factors’. Questions about the creation, evolution, and impact of norms obtained a prominent place in their theorising. Cast in a constructivist frame, this norm research promised to be a viable alternative to established approaches and while it has indeed broadened the perspective on state behaviour in International Relations, we argue that at the same time it entailed major conceptual and methodological problems which have not yet been spelled out comprehensively. Mainly, the insight that norms are constantly renegotiated in social interaction has been lost in the translation of social-theoretical claims of early constructivism into empirical research agendas. The ensuing research is best characterised as a cultural-determinist framework which is ultimately ill-equipped for the initial proposition of explaining change. We develop this critique by reconstructing the theoretical and methodological decisions of constructivist norm research. We then propose to re-conceptualise the connection between norms and action and suggest an interpretive methodology that allows delivering on the ambitious promise to explain processes of normative change in international politics. We illustrate this claim by reviewing constructivist norm research on ‘humanitarian interventions’ and by outlining a relational-processualist perspective on this issue.</p>",christian weber,,2014.0,10.1057/jird.2014.1,Journal of International Relations and Development,Hofferberth2014,Not available,,Nature,Not available,<i>Lost in translation</i>: a critique of constructivist norm research,2d7a64242f35ac66f9a7b44e18ef1ed1,http://dx.doi.org/10.1057/jird.2014.1
14598,"<p>Research on the ‘democratic peace’ has neglected the fact that democracies fight wars that no one else would, particularly to preserve international law and to prevent human disasters and large-scale violations of human rights. What is more, data on average probabilities of democratic war involvement have obscured that there have been vast differences in democracies' use of military force. This article demonstrates that the causal mechanisms of established approaches to the democratic peace do not preclude democracies' involvement in war. Most importantly, the ambivalence of the Kantian tradition allows for two competing logics of appropriateness that can be used to construct two ideal types: whereas, militant democracies conceive of their entire relation to non-democracies as antagonistic, and frequently fight wars to de-throne dictators, pacifist democracies believe in a <i>modus vivendi</i> with autocracies and try to assist their transformation into democracies.</p>",harald muller,,2004.0,10.1057/palgrave.ip.8800089,International Politics,Müller2004,Not available,,Nature,Not available,The Antinomy of Democratic Peace,f7508641c067c265a1760f4722573221,http://dx.doi.org/10.1057/palgrave.ip.8800089
14599,"<p>This article argues that ‘middle-ground’ constructivism is based on an uneasy tension between mental causality and rump materialism that shows itself as a conflict between upward determination of ideas and their downward causation on the material world. Even Alexander Wendt's recent turn to quantum and a holographic model of society does not solve this problem. Instead, his turn shows that the more mental causality and thus an autonomy of ‘consciousness’ is granted, the more an ontologically based constructivism becomes implausible. In clarifying differences and similarities between different strands of constructivism, this article argues for a reorientation of our focus on the mind–body problem. From this perspective, however, constructivism presents itself not as some middle ground, but is rather characterized by its attempt to overcome Cartesian categories.</p>",oliver kessler,,2007.0,10.1057/palgrave.jird.1800131,Journal of International Relations and Development,Kessler2007,Not available,,Nature,Not available,"From agents and structures to minds and bodies: of supervenience, quantum, and the linguistic turn",89ffc802b4f84a53e89ed95be2c9e59f,http://dx.doi.org/10.1057/palgrave.jird.1800131
14600,"<p>The rise of state dissidence has challenged the hegemony of Western liberalism on the international relations stage. Russia’s ongoing involvement in the Ukraine crisis is a case in point. Russia’s dissidence threatens not only the already fragile European order, but also the potency of liberalism as a system of international norms. Hence, a great deal of attention has been given to trying to determine the possible failures and solutions of global governance in dealing with Russia. In contrast, this article argues for the need to understand state resistance from the perspective of the dissenting state. By drawing upon Carl Schmitt’s influential critique of globalizing liberalism, the article attempts to analyse what Russia’s resistance reveals about the subtle mechanisms of global liberal governance. On the basis of Schmitt’s theory, the article establishes that Russia’s dissidence can be an attempt to preserve state sovereignty and its unique “way of life”, as well as state pluralism on the global arena. In fact, to eradicate conflict, liberal governance attempts to suppress state pluralism as a potential cause of conflict. In the long run, however, this risks provoking radical resistance in response. The article then analyses the “hybrid” strategy of Russia’s resistance employed in the Ukraine crisis, based on which it identifies the major weaknesses of liberal governance. The article concludes that the inadequacy of international law to deal with unconventional forms of warfare and refusal to acknowledge the possibility of animosity can significantly debilitate liberal governance. This article is published as part of a collection on global governance.</p>",bohdana kurylo,Politics and international relations,2016.0,10.1057/palcomms.2016.96,Palgrave Communications,Kurylo2016,Not available,,Nature,Not available,Russia and Carl Schmitt: the hybridity of resistance in the globalised world,dddc18b1b99b50021b7f717f554d2466,http://dx.doi.org/10.1057/palcomms.2016.96
14601,"<p>The rise of state dissidence has challenged the hegemony of Western liberalism on the international relations stage. Russia’s ongoing involvement in the Ukraine crisis is a case in point. Russia’s dissidence threatens not only the already fragile European order, but also the potency of liberalism as a system of international norms. Hence, a great deal of attention has been given to trying to determine the possible failures and solutions of global governance in dealing with Russia. In contrast, this article argues for the need to understand state resistance from the perspective of the dissenting state. By drawing upon Carl Schmitt’s influential critique of globalizing liberalism, the article attempts to analyse what Russia’s resistance reveals about the subtle mechanisms of global liberal governance. On the basis of Schmitt’s theory, the article establishes that Russia’s dissidence can be an attempt to preserve state sovereignty and its unique “way of life”, as well as state pluralism on the global arena. In fact, to eradicate conflict, liberal governance attempts to suppress state pluralism as a potential cause of conflict. In the long run, however, this risks provoking radical resistance in response. The article then analyses the “hybrid” strategy of Russia’s resistance employed in the Ukraine crisis, based on which it identifies the major weaknesses of liberal governance. The article concludes that the inadequacy of international law to deal with unconventional forms of warfare and refusal to acknowledge the possibility of animosity can significantly debilitate liberal governance. This article is published as part of a collection on global governance.</p>",bohdana kurylo,History,2016.0,10.1057/palcomms.2016.96,Palgrave Communications,Kurylo2016,Not available,,Nature,Not available,Russia and Carl Schmitt: the hybridity of resistance in the globalised world,dddc18b1b99b50021b7f717f554d2466,http://dx.doi.org/10.1057/palcomms.2016.96
14602,"<p>Drawing on Michael Barnett and Raymond Duvall’s concept of institutional power, this article presents the empirically ascertained asymmetries created by the World Trade Organisation (WTO) to investigate the Uruguay Round from a power standpoint. The argument is that developing countries, especially least developed nations, only accepted the WTO as a choice for the lesser of two evils. They are worse-off with the WTO trade regime, in contradiction to the positive-sum view of normative settings laid out by mainstream International Relations (IR) since the 1980s. The concept of institutional power is broken down into the sub-categories of ‘go-it-alone’ power, market power and forum-shifting power to demonstrate how the United States and the European Communities relied on their huge markets to shift the forum in charge of intellectual property and impose on developing countries a choice between accepting the WTO Agreement and being denied access to the world’s two largest markets. Developing countries thus rationally became members of an organisation that entails absolute losses to them. The argument that institutions such as the WTO are desirable because they are agreed to does not reflect the realities of power and is ultimately an ideological stance that precludes mainstream IR from grasping how institutions (re)produce inequalities.</p>",igor souza,,2013.0,10.1057/jird.2013.18,Journal of International Relations and Development,Souza2013,Not available,,Nature,Not available,An offer developing countries could not refuse: how powerful states created the World Trade Organisation,3d5a10cea917f4fac78b0943aa49077e,http://dx.doi.org/10.1057/jird.2013.18
14603,"<p>Existing neopositivist approaches to causal explanation focus their time and effort on the evaluation of nomothetic causal claims, and spend very little energy on the question of how, precisely, a nomothetic generalization explains a particular observed outcome. Against this approach I develop a more <i>pragmatic</i> analysis of the act of explanation in order to flesh out the context of causal explanation more broadly. Causal explanation, I argue, responds to a problem-situation in which the challenge involves <i>how to do</i> something, and unfolds by clarifying why and how some outcome rather than some other outcome came about — thus giving instructions on how to make the desired outcome happen. The resulting account of causal explanation encompasses a wide variety of explanatory strategies including the appeal to causal mechanisms, dispositional properties, everyday experiences, and even nomothetic generalisations; as such, it provides a better and broader basis for thinking about causal explanation in international studies than the restrictive neopositivist models presently on offer.</p>
<span><i>Journal of International Relations and Development</i> advance online publication, 20 May 2016; doi:<span>10.1057/jird.2016.13</span></span>",patrick jackson,,2016.0,10.1057/jird.2016.13,Journal of International Relations and Development,Jackson2016,Not available,,Nature,Not available,Causal claims and causal explanation in international studies,3831a3cec41ed87ef2c562b371fae9d3,http://dx.doi.org/10.1057/jird.2016.13
14604,"<p>The future of European integration is inextricably linked with the continued anchoring of Germany to EU multilateral structures. The institutionalist faith that integration will continue to accommodate diverse perspectives and goals through incremental reform is questionable. Rather than the new agenda of expansion and constitutionalism, older issues of sovereignty and national identity most constrain further development. This analysis shows that European integration is at a crossroads, compelling governments to make ever more painful choices between national and European identities. Structuralist and constructivist insights lead to the conclusion that the greatest tensions facing Europe arise from the old problem of embedding Europe's most powerful actor, Germany. Integration may not be able to produce a new balance between the institutional developments necessary to embrace Germany and the national sovereignty states want to preserve. Yet for Germany to remain solidly anchored in Europe's multilateral institutions, integration must move towards greater Europeanization of the nation-state. The question is how much Europe <i>everyone</i> must accept in order to sustain a political order that effectively embraces Europe's most powerful state.</p>",regina karp,,2003.0,10.1057/palgrave.ip.8800039,International Politics,Karp2003,Not available,,Nature,Not available,"Identities and Structural Change since the End of the Cold War: Germany, Europe, and the Limits of Integration",c155019c6cb690b3769c5b2a6acb2cb9,http://dx.doi.org/10.1057/palgrave.ip.8800039
14605,"<p>This article examines whether the nuclear non-proliferation regime is in crisis. I argue that the nuclear non-proliferation treaty (NPT) is suffering a crisis of legitimacy in domestic US politics and a chronic legitimacy deficit globally, but this does not in and of itself mean that there is a crisis in the non-proliferation regime <i>per se</i>, so long as there are actors with the ability and will to pay the costs of coercive and diplomatic bargaining instruments to maintain the loss of voluntary compliance. Policies addressing nuclear non-proliferation by the nuclear weapons states and their allies have been overwhelmingly ensconced within those latter two mechanisms of compliance rather than addressing the chronic legitimacy deficit of the NPT caused by the continued possession of nuclear arsenals by the nuclear weapons states. The US under the Bush administration, however, has led the way in an attempt to reconstitute the social relations underpinning the non-proliferation regime by recognizing India as a responsible nuclear power. This recalibration portends a more fundamental challenge to a regime of universal nuclear non-proliferation than the approach of nuclear powers to date, which has been to neglect legitimacy concerns in favour of diplomatic carrots and sticks and, with the Bush administration in particular, the threat and use of force. I argue that it is likely to deepen the chronic legitimacy deficit of the NPT, thus requiring greater investment in war, or in diplomatic carrots and sticks that have sometimes proven insufficient, though it is possible a new nuclear condominium could settle that proves at least as stable as the past if not more, with but another addition or two. But even if it does, this strategy of re-legitimation puts further off rather than nearer attainment of the central principle and purposes of the regime.</p>",richard price,,2007.0,10.1057/palgrave.ip.8800186,International Politics,Price2007,Not available,,Nature,Not available,"Nuclear Weapons Don't Kill People, Rogues Do",70656bf333c784bddd99a5d0772f57b1,http://dx.doi.org/10.1057/palgrave.ip.8800186
14606,"<p>From the time cities first evolved, they have been subject to human intervention at every level of activity – in other words they have been designed. The following paper argues that since this process was formalized at the beginning of the 20th century as <i>urban design,</i> its rationale as a discipline has been fraught with consequence. It has been continuously defined as <i>other</i> – half way between the two professions of architecture and urban planning. This unjustified otherness has been reflected in approaches to urban design theory. Even the middle ground which urban design is supposed to occupy is an amalgam of architectural and planning ideologies and practices. The following paper takes a hard look at the last 50 years, exposing the most serious attempts to synthesize or theorize significant urban design paradigms. While each attempt has much to commend it, variously exhibiting great insight, dedication, knowledge and scholarship, I feel that the collective result has been a generalized anarchy of creative ideas that bear little coherence, either internally or collectively. Whether this is ‘good’ or ‘bad’ is beside the point, it is where evolution has brought us. Nor does this situation signify any immunity on my part to the uses of disorder, chance and chaos, in the spirit that ‘there is no idea, however ancient and absurd, that is not capable of improving our knowledge’ (<span>Feyerabend, 1975</span>, p. 33). The hypothesis explored below proposes that the failure has an obvious cause – there has been no concerted attempt within the discipline to link the material creation or ‘designing’ of urban space and form to fundamental societal processes. More importantly, this linkage is desirable, and can be made. The fracture has many causes – historical, professional, ideological, academic, egocentric, as well as misplaced idealism. Rather than pursuing the quest for an integrated theory which has little possibility of success, I argue that a better outcome already exists in spatial political economy, itself a somewhat anarchistic pursuit, but one of better quality. The framework of ideas which it encompasses offers urban design both legitimation and theoretical coherence. In so doing, urban design can exit the nefarious middle ground allocated to it by architecture and planning. Instead, it can connect directly to the economic, political, social and cultural processes which structure social life.</p>",alexander cuthbert,,2008.0,10.1057/palgrave.udi.9000200,URBAN DESIGN International,Cuthbert2008,Not available,,Nature,Not available,Urban design: requiem for an era – review and critique of the last 50 years,3912823e868eb8d76d305da7adbba3e3,http://dx.doi.org/10.1057/palgrave.udi.9000200
14607,"<p>Contemporary scholarship focused on the International Monetary Fund (IMF) has identified various external and internal actors involved in individual cases of Low-Income Country (LIC) reform. Currently underdeveloped in the literature is comparative exploration of how these actors inform policy shifts in the institution. This paper addresses this concern through a study of four cases of LIC reform from 1996 to 2010. Evidence from these cases suggests that a significant policy shift only occurs when a successful coalition is constructed between or among ‘primary’ (powerful states, the IMF Managing Director (MD), IMF staff) and ‘secondary’ (poor states, non-governmental organisations (NGOs), the US Congress) actors. As such, while the actors may change, coalition formation is a necessary condition for LIC policy reform. Data drawn from the cases also supports several assumptions of principal-agent and sociological organisational theory. With regard to the former, LIC staff and the MD exhibited greater agency in policy formation when powerful state preferences were divided. When the reform in question challenged organisational culture, the MD and/or senior staff in the Strategy Policy and Review Department took on the role of strategic ‘norm entrepreneur’ through persuading others to join coalitions of change. Inclusion of the most recent case of LIC change following the 2008 crisis also highlights the evolving relationship between NGOs and IMF LIC policy outcomes. While NGOs were centrally involved in LIC reform efforts in the late 1990s, they were not significant agents of change in the post-2008 period.</p>",mark hibben,,2013.0,10.1057/jird.2013.20,Journal of International Relations and Development,Hibben2013,Not available,,Nature,Not available,Coalitions of change: explaining IMF low-income country reform in the post-Washington Consensus,bdf1b028c143448063f158cbac4b20c6,http://dx.doi.org/10.1057/jird.2013.20
14608,"<p>The international relations subfield within political science does some of the same work in furthering the liberal arts that the other subfields do, and it does some unique work. Like other political science courses, international relations courses teach competing explanations for the same event or process. Indeed, international relations courses are about the way in which the relevance of acts depends on assertions and assumptions about causation, as well as the way a problem is framed. International relations is also uniquely positioned to raise questions about political circumstances that the other subfields of political science take for granted. Because international relations is defined in terms of anarchy, without a sovereign or legitimate center, its processes lack the prima facie legitimacy of political processes within countries. The nature and enforcement of law, the autonomy of institutions, the distribution of wealth and opportunity: when posed from outside the state, elements of political life that are taken for granted within the state become variables, and are relativized. Because its subject matter is elemental and its “units” so varied, international relations cannot avoid foregrounding the interrelationship of assumptions, categories, and facts. It is, therefore, well suited to the liberal arts.</p>",cheryl shanks,,2013.0,10.1057/pol.2013.28,Polity,Shanks2013,Not available,,Nature,Not available,International Relations in the Liberal Arts,68f0e0322dbd6c46a55a3b1abf7ad8c0,http://dx.doi.org/10.1057/pol.2013.28
14609,"<p>The idea that there are biases, blind spots or exclusionary if not oppressive forces in the very way scientific endeavour is organised still appears to be a rather strange idea. It runs counter to the ingrained idea that science is reflective.</p>",oliver kessler,,2011.0,10.1057/jird.2011.29,Journal of International Relations and Development,Kessler2011,Not available,,Nature,Not available,Everyday practices of international relations: people in organizations,f3eb5daa6de2d1b058196f6290f902cb,http://dx.doi.org/10.1057/jird.2011.29
14610,"<p>The idea that there are biases, blind spots or exclusionary if not oppressive forces in the very way scientific endeavour is organised still appears to be a rather strange idea. It runs counter to the ingrained idea that science is reflective.</p>",xavier guillaume,,2011.0,10.1057/jird.2011.29,Journal of International Relations and Development,Kessler2011,Not available,,Nature,Not available,Everyday practices of international relations: people in organizations,f3eb5daa6de2d1b058196f6290f902cb,http://dx.doi.org/10.1057/jird.2011.29
14611,"<p>Why have two successive US administrations concluded that fighting terrorism must involve democracy promotion? This assumption became prevalent in US political discourse following the events of September 11 despite the fact that the empirical evidence linking democracy and terrorism is weak or ambiguous. More strikingly, it has persisted even after the missions to establish democracies in Afghanistan and Iraq have led to increasing violence, including a worldwide increase in terrorist attacks. This article argues that the link between democracy and terrorism was established by the combined effect of three factors: (a) the framing of the September 11 attacks in a way that increased the receptivity to this conceptual opposition between freedom and fear; (b) the ideological influence of the Wilsonian tradition, as manifested today in an unusual consensus between modern neo-conservatives and liberal internationalists on the desirability of democratic reform as a means of changing foreign policy behaviour; and (c) a powerful bipartisan domestic constituency in favour of democracy promotion. Owing to these three factors, the contraposition of democracy and terrorism in American political discourse is effectively over-determined because it mirrors the dominant ideological and political preferences of American elites. This fixed preference for democracy promotion explains why the Obama Administration has remained wedded to the binary distinction between freedom and fear in its public statements despite its efforts to break in style and substance with the policies of its predecessor.</p>",michael boyle,,2011.0,10.1057/ip.2011.1,International Politics,Boyle2011,Not available,,Nature,Not available,Between freedom and fear: Explaining the consensus on terrorism and democracy in US foreign policy,5d5963fb70b34767b450c106aa93d3a1,http://dx.doi.org/10.1057/ip.2011.1
14612,"<p>Explanations of states’ security decisions prioritise structural — systemic, institutional and cultural — constraints that characterise foreign security decisions as a function of external/international, domestic/institutional, or normative/cultural factors. By examining Turkey’s 1990–1991 and 2003 Iraq war decisions systematically, we problematise this prioritisation of structure, and we investigate the dynamic relationship between structural constraints and leaders in their decision-making environments. In these cases, while the structural constraints remain constant or indeterminate, the decision outcomes and the decision-making process differ significantly. Our findings, based on structured-focused comparison, process tracing, and leadership trait analysis, suggest that the leaders’ personalities and how they react to constraints account for this difference and that dependence on only one set of factors leads to an incomplete understanding of security policies and international politics. We contribute to the broader understanding of leaders’ personalities by suggesting that self-confidence and cognitive complexity are the key traits distinguishing leaders’ orientations towards structural constraints.</p>
<span><i>Journal of International Relations and Development</i> advance online publication, 20 February 2015; doi:<span>10.1057/jird.2014.31</span></span>",esra cuhadar,,2015.0,10.1057/jird.2014.31,Journal of International Relations and Development,Cuhadar2015,Not available,,Nature,Not available,Examining leaders’ orientations to structural constraints: Turkey’s 1991 and 2003 Iraq war decisions,a059e457f10a428100e84f09d626a116,http://dx.doi.org/10.1057/jird.2014.31
14613,"<p>Explanations of states’ security decisions prioritise structural — systemic, institutional and cultural — constraints that characterise foreign security decisions as a function of external/international, domestic/institutional, or normative/cultural factors. By examining Turkey’s 1990–1991 and 2003 Iraq war decisions systematically, we problematise this prioritisation of structure, and we investigate the dynamic relationship between structural constraints and leaders in their decision-making environments. In these cases, while the structural constraints remain constant or indeterminate, the decision outcomes and the decision-making process differ significantly. Our findings, based on structured-focused comparison, process tracing, and leadership trait analysis, suggest that the leaders’ personalities and how they react to constraints account for this difference and that dependence on only one set of factors leads to an incomplete understanding of security policies and international politics. We contribute to the broader understanding of leaders’ personalities by suggesting that self-confidence and cognitive complexity are the key traits distinguishing leaders’ orientations towards structural constraints.</p>
<span><i>Journal of International Relations and Development</i> advance online publication, 20 February 2015; doi:<span>10.1057/jird.2014.31</span></span>",juliet kaarbo,,2015.0,10.1057/jird.2014.31,Journal of International Relations and Development,Cuhadar2015,Not available,,Nature,Not available,Examining leaders’ orientations to structural constraints: Turkey’s 1991 and 2003 Iraq war decisions,a059e457f10a428100e84f09d626a116,http://dx.doi.org/10.1057/jird.2014.31
14614,"<p>This article argues that low horizontal inequalities, or inequalities among groups, should form an intrinsic aspect of a shared society. It argues, on the basis of several philosophical analyses, that horizontal inequalities are not only unjust, but they also contribute to violent conflict and lack of social cohesion. Although low horizontal inequalities appear to be an implicit aspect of the shared society project it would be an advantage to include them explicitly, from the perspective of assessing and measuring progress.</p>",frances stewart,,2014.0,10.1057/dev.2014.30,Development,Stewart2014,Not available,,Nature,Not available,Why Horizontal Inequalities are Important for a Shared Society,4cd2982e66b69bc1f55df9d2b29556d5,http://dx.doi.org/10.1057/dev.2014.30
14615,"<p>Explanations of states’ security decisions prioritise structural — systemic, institutional and cultural — constraints that characterise foreign security decisions as a function of external/international, domestic/institutional, or normative/cultural factors. By examining Turkey’s 1990–1991 and 2003 Iraq war decisions systematically, we problematise this prioritisation of structure, and we investigate the dynamic relationship between structural constraints and leaders in their decision-making environments. In these cases, while the structural constraints remain constant or indeterminate, the decision outcomes and the decision-making process differ significantly. Our findings, based on structured-focused comparison, process tracing, and leadership trait analysis, suggest that the leaders’ personalities and how they react to constraints account for this difference and that dependence on only one set of factors leads to an incomplete understanding of security policies and international politics. We contribute to the broader understanding of leaders’ personalities by suggesting that self-confidence and cognitive complexity are the key traits distinguishing leaders’ orientations towards structural constraints.</p>
<span><i>Journal of International Relations and Development</i> advance online publication, 20 February 2015; doi:<span>10.1057/jird.2014.31</span></span>",baris kesgin,,2015.0,10.1057/jird.2014.31,Journal of International Relations and Development,Cuhadar2015,Not available,,Nature,Not available,Examining leaders’ orientations to structural constraints: Turkey’s 1991 and 2003 Iraq war decisions,a059e457f10a428100e84f09d626a116,http://dx.doi.org/10.1057/jird.2014.31
14616,"<p>Explanations of states’ security decisions prioritise structural — systemic, institutional and cultural — constraints that characterise foreign security decisions as a function of external/international, domestic/institutional, or normative/cultural factors. By examining Turkey’s 1990–1991 and 2003 Iraq war decisions systematically, we problematise this prioritisation of structure, and we investigate the dynamic relationship between structural constraints and leaders in their decision-making environments. In these cases, while the structural constraints remain constant or indeterminate, the decision outcomes and the decision-making process differ significantly. Our findings, based on structured-focused comparison, process tracing, and leadership trait analysis, suggest that the leaders’ personalities and how they react to constraints account for this difference and that dependence on only one set of factors leads to an incomplete understanding of security policies and international politics. We contribute to the broader understanding of leaders’ personalities by suggesting that self-confidence and cognitive complexity are the key traits distinguishing leaders’ orientations towards structural constraints.</p>
<span><i>Journal of International Relations and Development</i> advance online publication, 20 February 2015; doi:<span>10.1057/jird.2014.31</span></span>",binnur ozkececi-taner,,2015.0,10.1057/jird.2014.31,Journal of International Relations and Development,Cuhadar2015,Not available,,Nature,Not available,Examining leaders’ orientations to structural constraints: Turkey’s 1991 and 2003 Iraq war decisions,a059e457f10a428100e84f09d626a116,http://dx.doi.org/10.1057/jird.2014.31
14617,"<p>This article argues that a range of child welfare interventions that sought to relocate children away from their birth families and home communities between the middle decades of the nineteenth and twentieth centuries drew on a common moral frame. These interventions – child migration schemes, assimilationist policies towards indigenous children, institutions of corrective confinement and the child protection movement – have typically been previously studied as isolated national or organisational phenomena. However, this article outlines a common moral frame to which they made reference structured around the figure of the redeemable child, vulnerable to the effects of polluted social environments, seen as needing to be re-located to new environments that would enable their civic, moral and spiritual redemption. This argument is situated within a discussion of the articulation of moral meanings as a social practice, which addresses both the central elements of this moral frame and the contexts in which it was articulated. This moral frame did not determine child-care practices within these schemes, but was one source of influence on them. In particular, the article examines the role of economic rationality in the management of these schemes, arguing that the sacralised status of the child within the family discussed in the work of Vivianna Zelizer was not extended to the children to whom these schemes were addressed. The article concludes by identifying key areas for future comparative study of these diverse schemes in relation to these shared moral meanings.</p>",gordon lynch,,2014.0,10.1057/ajcs.2014.5,American Journal of Cultural Sociology,Lynch2014,Not available,,Nature,Not available,"Saving the child for the sake of the nation: Moral framing and the civic, moral and religious redemption of children",714a5709c9618b860dbca31077163b3e,http://dx.doi.org/10.1057/ajcs.2014.5
14618,"<p>In this article, I explore recent discussions among American public health professionals over how to protect the health of the nation in a state of emergency. My focus is specifically on questions of preventative strategy and population management, examining intensive debates around the prioritization of protective vaccine for pandemic influenza. Drawing on ethnographic research, I show how the mode of circulation, distribution and allocation of pandemic vaccine was gradually refashioned in the United States over the past 2 years. When government officials launched public engagement meetings reformulating in ethical terms the crucial question of how to dispense a scarce pharmaceutical resource in a public health emergency, a distinctive set of priorities emerged. My aim, in this article, is to examine this ethical refashioning and to interrogate the curious logics of public-ness that are increasingly embedded in a growing number of approaches of public health professionals. How are populations gathered into the fold of pharmaceutical prevention today?</p>",carlo caduff,,2010.0,10.1057/biosoc.2010.1,BioSocieties,Caduff2010,Not available,,Nature,Not available,"Public prophylaxis: Pandemic influenza, pharmaceutical prevention and participatory governance",cf605694a89790fec8411bc4be5effcf,http://dx.doi.org/10.1057/biosoc.2010.1
14619,"<p>While the concept of friendship has been largely invisible within Western political debate, in the international political domain, ‘friendship’ and the language of friends have been prominent in treaties and alliances between nations. Database searches on the topic of ‘politics and friendship’ locate predominantly references concerning relationships between states. However, it has been war and enmity rather than friendship that has dominated analysis in international relations literature. In this article we provide a history of international treaties, focusing in particular on those named as friendship treaties. We will discuss the use of concepts and terminology related to friendship and the nomenclature associated with international alliances. It will be argued that friendship is more a tool of public relations and spin, rather than diplomacy and peace-building, and the cynical use of friendship does not sit easily with the Nehruvian concept of friendship as an important method of diplomacy that can act as a path to peace, goodwill and understanding between states and nations.</p>",heather devere,,2010.0,10.1057/ip.2010.34,International Politics,Devere2010,Not available,,Nature,Not available,A history of the language of friendship in international treaties,2e4d05b51644d0492d6516fbe98d166d,http://dx.doi.org/10.1057/ip.2010.34
14620,"<p>While the concept of friendship has been largely invisible within Western political debate, in the international political domain, ‘friendship’ and the language of friends have been prominent in treaties and alliances between nations. Database searches on the topic of ‘politics and friendship’ locate predominantly references concerning relationships between states. However, it has been war and enmity rather than friendship that has dominated analysis in international relations literature. In this article we provide a history of international treaties, focusing in particular on those named as friendship treaties. We will discuss the use of concepts and terminology related to friendship and the nomenclature associated with international alliances. It will be argued that friendship is more a tool of public relations and spin, rather than diplomacy and peace-building, and the cynical use of friendship does not sit easily with the Nehruvian concept of friendship as an important method of diplomacy that can act as a path to peace, goodwill and understanding between states and nations.</p>",simon mark,,2010.0,10.1057/ip.2010.34,International Politics,Devere2010,Not available,,Nature,Not available,A history of the language of friendship in international treaties,2e4d05b51644d0492d6516fbe98d166d,http://dx.doi.org/10.1057/ip.2010.34
14621,"<p>While the concept of friendship has been largely invisible within Western political debate, in the international political domain, ‘friendship’ and the language of friends have been prominent in treaties and alliances between nations. Database searches on the topic of ‘politics and friendship’ locate predominantly references concerning relationships between states. However, it has been war and enmity rather than friendship that has dominated analysis in international relations literature. In this article we provide a history of international treaties, focusing in particular on those named as friendship treaties. We will discuss the use of concepts and terminology related to friendship and the nomenclature associated with international alliances. It will be argued that friendship is more a tool of public relations and spin, rather than diplomacy and peace-building, and the cynical use of friendship does not sit easily with the Nehruvian concept of friendship as an important method of diplomacy that can act as a path to peace, goodwill and understanding between states and nations.</p>",jane verbitsky,,2010.0,10.1057/ip.2010.34,International Politics,Devere2010,Not available,,Nature,Not available,A history of the language of friendship in international treaties,2e4d05b51644d0492d6516fbe98d166d,http://dx.doi.org/10.1057/ip.2010.34
14622,"<p>The idea behind this article is to employ a series of Deleuzo-Guattarian principles, primarily the concept of the rhizome, to the articulation and development of Realism as a theory of IR. The article makes the claim that using rhizomatics allows those interested in Realism to reconceptualise the relationship between Realism and Neorealism. The article argues that the publication of <i>The Twenty Years’ Crisis</i> by E.H. Carr and <i>Theory of International Politics</i> by Ken Waltz represent two ‘intense’ moments in the descent of Realism. The article argues that despite the attempted ‘territorialisation’ of Realism into the static, paradigmatic Neorealism, Realism remains a heterogeneous set of concepts. The territorialisation process has met with some resistance; for example, just as Waltz was trying to territorialise Realism, his theory was being deterritorialised by Richard Ashley. The article also examines James Der Derian's attempt to save realism by deconstructing it, advocating an ‘affirmative leap into the imaginary’. The article concludes that despite the Neorealist moment, attempts to splice together constructivism and realism provide evidence that Realism remains mutative, heterogeneous, open and vital.</p>",sean molloy,,2010.0,10.1057/jird.2010.15,Journal of International Relations and Development,Molloy2010,Not available,,Nature,Not available,From <i>The Twenty Years’ Crisis</i> to <i>Theory of International Politics</i>: a rhizomatic reading of realism,b9aa9d46feeb2da237f5764d0beb8ec1,http://dx.doi.org/10.1057/jird.2010.15
14623,"<p>This article explains some of the recent changes in German foreign policy, namely the shift in preferences for institution building in the European Security and Defence Policy (ESDP). The empirical exploration compares the phase before the European Union's (EU) Intergovernmental Conference in the mid-1990s with the Convention negotiations in 2002/2003. While the German government used to be a strong defender of NATO's primacy and supported a modest scope for the EU, it then began to promote high-intensity crisis management for ESDP and wanted to see the EU on an equal footing with NATO. Building on neoclassical realist thought, the paper argues that a two-stage analysis of the <i>power context</i> offers a comprehensive explanation of these changes. It refers to power in a materialist sense <i>and</i> its cognitive understanding on behalf of the political actors. Based on the assessment of uncertainty stemming from its interpretation of the power context, the German government formed its preferences on what the EU's responsibilities for European security should be and how it should relate to NATO. More specifically, the mixture of isolationist and unilateralist signals sent by the United States increased German concerns about the latter's commitment. The German government adapted to the uncertain power context by promoting stronger responsibilities for ESDP.</p>",moritz weiss,,2009.0,10.1057/jird.2009.15,Journal of International Relations and Development,Weiss2009,Not available,,Nature,Not available,Power and signals: explaining the German approach to European security,01c92428ac38bfce39235ec110a75e1a,http://dx.doi.org/10.1057/jird.2009.15
14624,"<p>The global environmental agenda, alongside the broad neoliberal agenda, may be viewed by developing states and societies as a neo-imperialist adventure to be resisted. This paper argues that while the idea of ‘eco-imperialism’ reflects the uncertain location of politics, the ambivalent role of states, and unchallenged state-centred assumptions about world politics, it also introduces conceptual confusion. It is an unusual case of imperialism, in so far as it involves diverse actors who may not be pursuing the same objectives. It appears that eco-imperialism may be both hegemonic force and anti-capitalist movement. In order to explain this apparent contradiction, we must note the contradictions in globalisation, but also how the mix of underlying political orientations create strange bed-fellows of, for example, developing country activists and oil company executives. In doing so, a nuanced view of the dynamics of global environmental policy and the prospects for matching these to particular political contexts may be discerned. While the exploitative and dominating aspects of global environmental policy deserve to be challenged and studied, these may have less bearing on global governance <i>per se</i> than on the globalised world in which it occurs. In recognising the intent of the critique, one must also note the mutual constitution of governance and resistance, local-global reverberations, and the prospects for bottom-up support identified by ‘environmentality’. Hence, any signs of eco-imperialism imply ‘participatory empire’ at worst, which should inform rather than obstruct global environmental governance.</p>",hugh dyer,,2011.0,10.1057/jird.2011.2,Journal of International Relations and Development,Dyer2011,Not available,,Nature,Not available,"Eco-imperialism: governance, resistance, hierarchy",98c2522601ebbfa16e265a4b111adc76,http://dx.doi.org/10.1057/jird.2011.2
14625,"<p>Islamic exceptionalism (IE), or the discourse of Islam's inassimilable difference, legitimizes post-9/11 encounters with Islam and strategies of political and cultural domestication of the Islamic cultural zones (ICZs). It may also furnish new grounds for exclusions, enclosures and securitization. The aim of this paper is to explore the principal vectors of the field of vision generated by IE; to draw out any possible connections between IE and a presumed global exception (GE); and more broadly, to delineate how IE speaks to the perils of International Relations (IR)'s occlusion of the political in ICZs. In exploring the nexus between IE and GE, both the recursive character of GE and its constraints are noted, with an appreciation of cultural mappings nourishing GE. The key implication drawn is the need to avoid the temptation of an abstract notion of GE without ample recognition of its particularized instantiations, notably in reference to Islam.</p>",mustapha pasha,,2009.0,10.1057/ip.2009.13,International Politics,Pasha2009,Not available,,Nature,Not available,Global exception and Islamic exceptionalism,a245987c062036959a5d4f37c9c6f450,http://dx.doi.org/10.1057/ip.2009.13
14626,"<p>In July 2015 an agreement on the so-called Joint Comprehensive Plan of Action regarding Iran’s nuclear program was announced between Iran and the permanent members of the UNSC, Germany and the EU. The Iranian decision to comply with the results of the negotiations attracted much focus, both at the policy level and in scholarly debates. However, the foreign and security policy interests and possibilities of Iran in the MENA region have not been discussed very intensively, nor has there been much attention paid to how the international actors and in particular the EU were able to influence the Iranian policies and decisions. This article seeks to take up this challenge: firstly by analyzing to what degree the sanctions influenced the Iranian decisions on the nuclear issue; and secondly, by discussing how the sanctions regime affected the relations between Iran and the international actors, with a specific focus on the EU and the ability of Iran to pursue its foreign policy interests in the Levant and the Gulf. This article is published as part of a collection on analysing security complexes in a changing Middle East.</p>",peter seeberg,History,2016.0,10.1057/palcomms.2016.80,Palgrave Communications,Seeberg2016,Not available,,Nature,Not available,"The EU and the international sanctions against Iran: European and Iranian foreign and security policy interests, and a changing Middle East",7f0ef28c52b24a7a2118b9422718b352,http://dx.doi.org/10.1057/palcomms.2016.80
14627,"<p>In July 2015 an agreement on the so-called Joint Comprehensive Plan of Action regarding Iran’s nuclear program was announced between Iran and the permanent members of the UNSC, Germany and the EU. The Iranian decision to comply with the results of the negotiations attracted much focus, both at the policy level and in scholarly debates. However, the foreign and security policy interests and possibilities of Iran in the MENA region have not been discussed very intensively, nor has there been much attention paid to how the international actors and in particular the EU were able to influence the Iranian policies and decisions. This article seeks to take up this challenge: firstly by analyzing to what degree the sanctions influenced the Iranian decisions on the nuclear issue; and secondly, by discussing how the sanctions regime affected the relations between Iran and the international actors, with a specific focus on the EU and the ability of Iran to pursue its foreign policy interests in the Levant and the Gulf. This article is published as part of a collection on analysing security complexes in a changing Middle East.</p>",peter seeberg,Politics and international relations,2016.0,10.1057/palcomms.2016.80,Palgrave Communications,Seeberg2016,Not available,,Nature,Not available,"The EU and the international sanctions against Iran: European and Iranian foreign and security policy interests, and a changing Middle East",7f0ef28c52b24a7a2118b9422718b352,http://dx.doi.org/10.1057/palcomms.2016.80
14628,"<p>Since the end of the Cold War various attempts at post-conflict peacebuilding have collapsed. In recent years, many scholars have claimed that the failure to weaken spoilers' shadow trade war economies has seriously undermined efforts at implementing peace treaties and building stable peace during the 1990s and early 2000s. However, empirical research carried out so far has largely concentrated on illustrating the assumed link between the proliferation of natural resources trafficking as a means to fund warfare and peacebuilding failure, rather than conducting case studies that may challenge and potentially falsify this link. In order to fill this gap, this article presents four brief case studies on the role of war economies in the peacebuilding processes in Cambodia, Angola, Sierra Leone and Afghanistan. In doing so, the article provides empirical evidence in support of the claim that spoilers' unhampered access to war economies strongly impairs peacebuilding. Further, it demonstrates that the application of strategies to prevent spoilers from drawing on revenues gained from trafficking in natural resources to fund military operations can be highly instrumental in ending warfare and facilitating peacebuilding. Thus, far from offering a monocausal explanation of the success or failure of peacebuilding, the article empirically substantiates a distinct perspective on peacebuilding that complements other approaches and thus contributes to establishing a more comprehensive account of the determinants of peacebuilding.</p>",monika heupel,,2006.0,10.1057/palgrave.jird.1800085,Journal of International Relations and Development,Heupel2006,Not available,,Nature,Not available,Shadow trade war economies and their challenge to peacebuilding,ab01e1444f8e86b5217663e7c7d17c34,http://dx.doi.org/10.1057/palgrave.jird.1800085
14629,"<p>Why are some free trade agreements (FTAs) in the western hemisphere successfully negotiated and implemented while others seem to stagnate during negotiations? FTAs are more likely to develop when there is an asymmetrical power relationship and potential partners are satisfied with projected trade patterns. The European Union (EU) and United States have been successful in negotiating agreements with the Caribbean and Central American (CCA) countries. However, current bilateral and multilateral trade talks between the EU, the Common Market of the South (MERCOSUR), and United States are at a standstill. Although all four sets of trade negotiations include dissatisfactory conditions for the Latin American countries, the two negotiations with the CCA countries were successful completed, but the two involving MERCOSUR countries have not. These results are partially due to two factors: the economic size differential between the CCA countries and MERCOSUR <i>vis-à-vis</i> the EU and United States, and MERCOSUR's growing economic ties with China. MERCOSUR's medium-size economy and ties with China allows it to forgo FTAs with the EU and United States until more favorable conditions are met. However the CCA countries’ immensely smaller size and economic ties with China do not allow for such abstention.</p>",gaspare genna,,2010.0,10.1057/ip.2010.28,International Politics,Genna2010,Not available,,Nature,Not available,Economic size and the changing international political economy of trade: The development of western hemispheric FTAs,2d7bdc3127a758f3c4faa16cbfa9e273,http://dx.doi.org/10.1057/ip.2010.28
14630,"<p>In this article we aim to reduce the force of the expensive tastes objection to equality of welfare by constructing a pluralist welfare egalitarian theory which is not defeated by it. In the first part, we argue that Cohen’s condition of responsibility-sensitiveness is not able to provide a satisfactory rebuttal of the expensive tastes objection for at least a class of theories of justice, namely those that adhere to a methodologically fact-sensitive view. In the second part, we explore the possibility of constructing a welfare egalitarian theory that gives weight to both equality and efficiency. We propose two alternatives, which integrate a utilitarian constraint and a Weak Pareto constraint on equality and show that both theories consistently differentiate between compensable and non-compensable expensive tastes, but should ultimately be rejected because of other unattractive implications. Finally, we develop a fairness-constrained theory of welfare egalitarianism and suggest that it can distinguish between compensable and non-compensable expensive tastes in both a conceptually consistent and a morally plausible manner, without generating decisive additional objections.</p>",alexandru volacu,,2015.0,10.1057/cpt.2015.67,Contemporary Political Theory,Volacu2015,Not available,,Nature,Not available,Pluralist welfare egalitarianism and the expensive tastes objection,2a0ea608c170ec81462acba05b240715,http://dx.doi.org/10.1057/cpt.2015.67
14631,"<p>In this article we aim to reduce the force of the expensive tastes objection to equality of welfare by constructing a pluralist welfare egalitarian theory which is not defeated by it. In the first part, we argue that Cohen’s condition of responsibility-sensitiveness is not able to provide a satisfactory rebuttal of the expensive tastes objection for at least a class of theories of justice, namely those that adhere to a methodologically fact-sensitive view. In the second part, we explore the possibility of constructing a welfare egalitarian theory that gives weight to both equality and efficiency. We propose two alternatives, which integrate a utilitarian constraint and a Weak Pareto constraint on equality and show that both theories consistently differentiate between compensable and non-compensable expensive tastes, but should ultimately be rejected because of other unattractive implications. Finally, we develop a fairness-constrained theory of welfare egalitarianism and suggest that it can distinguish between compensable and non-compensable expensive tastes in both a conceptually consistent and a morally plausible manner, without generating decisive additional objections.</p>",oana-alexandra dervis,,2015.0,10.1057/cpt.2015.67,Contemporary Political Theory,Volacu2015,Not available,,Nature,Not available,Pluralist welfare egalitarianism and the expensive tastes objection,2a0ea608c170ec81462acba05b240715,http://dx.doi.org/10.1057/cpt.2015.67
14632,"<p>This article focuses on the moral assumptions underpinning the notion of social responsibility implied in the above slogan. It critically examines arguments which derive obligations to meet needs from shared moral agency and from social relations of reciprocity. Obligations to contribute according to ability are established by a series of arguments which justify regarding undeserved natural abilities and socially produced abilities as common assets, and which demonstrate that under certain conditions the maxim ‘ought implies can’ is reversible as ‘can implies ought’. The problem of motivation and voluntary action is tackled by arguing that there are intrinsic and extrinsic incentives to contribute unconnected with special rewards and that moral incentives replace material incentives to produce.</p>
<p>The notion of responsibility is an essential concept for social life, but since its justification and adoption depends on an inclusive moral community with overlapping ends and purposes, it is not surprising that the duty to contribute is absent from liberal theory, and had no positive connotations in liberal society. Politicians of every hue are increasingly appealing to the responsibilities citizens are expected to fulfil; yet they fail to account for the conditions for their development and exercise. For this reason, the assumptions expressed in the socialist slogan are an important corrective to liberal perspectives.</p>",maureen ramsay,,2002.0,10.1057/palgrave.cpt.9300020,Contemporary Political Theory,Ramsay2002,Not available,,Nature,Not available,Just Contribution,230ded59314d4204c0c0fed89934ad2a,http://dx.doi.org/10.1057/palgrave.cpt.9300020
14633,"<p>Facing the threats of infectious diseases, we take various actions to protect ourselves, but few studies considered an evolving system with competing strategies. In view of that, we propose an evolutionary epidemic model coupled with human behaviors, where individuals have three strategies: vaccination, self-protection and laissez faire, and could adjust their strategies according to their neighbors' strategies and payoffs at the beginning of each new season of epidemic spreading. We found a counter-intuitive phenomenon analogous to the well-known <i>Braess's Paradox</i>, namely a better condition may lead to worse performance. Specifically speaking, increasing the successful rate of self-protection does not necessarily reduce the epidemic size or improve the system payoff. The range and degree of the Braess's Paradox are sensitive to both the parameters characterizing the epidemic spreading and the strategy payoff, while the existence of the Braess's Paradox is insensitive to the network topologies. This phenomenon can be well explained by a mean-field approximation. Our study demonstrates an important fact that a better condition for individuals may yield a worse outcome for the society.</p>",hai-feng zhang,Computational models,2013.0,10.1038/srep03292,Scientific Reports,Zhang2013,Not available,,Nature,Not available,Braess's Paradox in Epidemic Game: Better Condition Results in Less Payoff,551a0daab3513be189f0f7a0e0fd3e06,http://dx.doi.org/10.1038/srep03292
14634,"<p>Introduction The books reviewed in this essay address whether transboundary water relations are more explicable as material or social phenomena. As the volume edited by Joachim Blatter and Helen Ingram inquires, ‘How much are natural or ecological imperatives…based on objective realities and how much are they creations of the human imagination’ (p. 15)?</p>",paul williams,,2003.0,10.1057/palgrave.ip.8800004,International Politics,Williams2003,Not available,,Nature,Not available,Global (Mis)Governance of Regional Water Relations,2712af7379ad3fd72066c7857d96b5b5,http://dx.doi.org/10.1057/palgrave.ip.8800004
14635,"<p>During a stay in South Africa in 2002–2003, we learned that public sector nurses dealt with serious community and workplace impacts from the HIV/AIDS epidemic; and were reluctant to report occupational exposures to HIV or take a short-course of antiretroviral post-exposure prophylaxis to prevent HIV infection. In May 2003, in South Africa's KwaZulu Natal province, we explored perspectives of 34 public hospital nurses in nine group interviews on workplace safety; the impact of HIV/AIDS on nurses' work environments; and, hospital and government policy. The information they provided illustrates that the views of nurses are vitally important to policy-making. We conclude that seeking nurses' views and involving them in policy processes could contribute to worker health, to addressing the dramatic shortage of nurses, recently identified as the largest threat to providing HIV/AIDS treatment in sub-Saharan Africa, and to improving quality of care.</p>",jennifer zelnick,,2005.0,10.1057/palgrave.jphp.3200021,Journal of Public Health Policy,Zelnick2005,Not available,,Nature,Not available,"The Impact of the HIV/AIDS Epidemic on Hospital Nurses in KwaZulu Natal, South Africa: Nurses' Perspectives and Implications for Health Policy",941c3e28cb71b9e5a66365b0f82a2338,http://dx.doi.org/10.1057/palgrave.jphp.3200021
14636,"<p>During a stay in South Africa in 2002–2003, we learned that public sector nurses dealt with serious community and workplace impacts from the HIV/AIDS epidemic; and were reluctant to report occupational exposures to HIV or take a short-course of antiretroviral post-exposure prophylaxis to prevent HIV infection. In May 2003, in South Africa's KwaZulu Natal province, we explored perspectives of 34 public hospital nurses in nine group interviews on workplace safety; the impact of HIV/AIDS on nurses' work environments; and, hospital and government policy. The information they provided illustrates that the views of nurses are vitally important to policy-making. We conclude that seeking nurses' views and involving them in policy processes could contribute to worker health, to addressing the dramatic shortage of nurses, recently identified as the largest threat to providing HIV/AIDS treatment in sub-Saharan Africa, and to improving quality of care.</p>",max o'donnell,,2005.0,10.1057/palgrave.jphp.3200021,Journal of Public Health Policy,Zelnick2005,Not available,,Nature,Not available,"The Impact of the HIV/AIDS Epidemic on Hospital Nurses in KwaZulu Natal, South Africa: Nurses' Perspectives and Implications for Health Policy",941c3e28cb71b9e5a66365b0f82a2338,http://dx.doi.org/10.1057/palgrave.jphp.3200021
14637,"Prior to the XIII<sup>th</sup> World AIDS Conference in Durban, debate raged in the community over the practicalities, cost and ethics of delivering antiretroviral drugs to the developing world. Two years on, that discussion is history. Political and financial forces will now deliver these drugs to such nations. How then can we expect their arrival to alter the HIV landscape?",geoff garnett,,2002.0,10.1038/nm0702-651,Nature Medicine,Garnett2002,Not available,,Nature,Not available,Antiretroviral therapy to treat and prevent HIV/AIDS in resource-poor settings,fe7489e94d61b929773972712d8e845b,http://dx.doi.org/10.1038/nm0702-651
14638,"Prior to the XIII<sup>th</sup> World AIDS Conference in Durban, debate raged in the community over the practicalities, cost and ethics of delivering antiretroviral drugs to the developing world. Two years on, that discussion is history. Political and financial forces will now deliver these drugs to such nations. How then can we expect their arrival to alter the HIV landscape?",lucy bartley,,2002.0,10.1038/nm0702-651,Nature Medicine,Garnett2002,Not available,,Nature,Not available,Antiretroviral therapy to treat and prevent HIV/AIDS in resource-poor settings,fe7489e94d61b929773972712d8e845b,http://dx.doi.org/10.1038/nm0702-651
14639,"Prior to the XIII<sup>th</sup> World AIDS Conference in Durban, debate raged in the community over the practicalities, cost and ethics of delivering antiretroviral drugs to the developing world. Two years on, that discussion is history. Political and financial forces will now deliver these drugs to such nations. How then can we expect their arrival to alter the HIV landscape?",nicholas grassly,,2002.0,10.1038/nm0702-651,Nature Medicine,Garnett2002,Not available,,Nature,Not available,Antiretroviral therapy to treat and prevent HIV/AIDS in resource-poor settings,fe7489e94d61b929773972712d8e845b,http://dx.doi.org/10.1038/nm0702-651
14640,"Prior to the XIII<sup>th</sup> World AIDS Conference in Durban, debate raged in the community over the practicalities, cost and ethics of delivering antiretroviral drugs to the developing world. Two years on, that discussion is history. Political and financial forces will now deliver these drugs to such nations. How then can we expect their arrival to alter the HIV landscape?",roy anderson,,2002.0,10.1038/nm0702-651,Nature Medicine,Garnett2002,Not available,,Nature,Not available,Antiretroviral therapy to treat and prevent HIV/AIDS in resource-poor settings,fe7489e94d61b929773972712d8e845b,http://dx.doi.org/10.1038/nm0702-651
14641,"<p>The Wassenaar Arrangement (WA) is a multilateral regime designed to control exports of conventional arms and dual-use goods and technologies to contribute to regional and international security and stability. Unlike traditional arms control and disarmament agreements WA is not legally binding. It has to rely on cooperation and voluntary compliance of the actors concerned – principally states and industries. For them the WA provides guidance for cooperation and compliance. The question is whether the actors involved are interested in complying with the guidelines. The article applies two IR theories to address this question, liberal institutionalism and realism. One argument of liberal institutionalism is that international institutions and regimes not only have a vital catalytic role to play in promoting cooperation among states, but they also develop synergetic effects and reinforce each other in the framework of effective multilateralism. In many ways this might well be the case, but the opposite is also true. The economic interests of member states and jealousy between them have long hampered cooperation among the various regimes that have been designed to act as the multilayered export control and non-proliferation system that all involved have agreed is necessary. But it is not only liberal institutionalism that fails to explain the behavior of states, international institutions and regimes. For realists, it is states’ interests that matter, with common norms, rules and principles mattering less, if at all. But contrary to the realist argument, states do also support the general guidelines and best practices of the international institutions that have been created to avoid the destabilizing effects of the accumulation of certain categories of conventional arms and the proliferation of dangerous weapons. Neither realism nor liberal institutionalism is fully able to capture the complex relationship between the interests of individual countries and general principles and norms. The diplomatic delegations in multilateral fora have the difficult task of identifying the cumulative interests of the countries they represent. They have to support and reject cooperation with states and other export control regimes and institutions, often at the same time.</p>",heinz gartner,,2009.0,10.1057/ip.2009.25,International Politics,Gärtner2009,Not available,,Nature,Not available,Towards a theory of arms export control,efed7b7d8a76d46370b41ee5eb924aed,http://dx.doi.org/10.1057/ip.2009.25
14642,"<p>European integration can be seen as a largely ‘liberal’ project. Since its inception, this project has, however, strongly emphasised the features of economic liberalism, neglecting other essential elements of the liberal tradition, including the limitation of political power, the defence of individual freedoms (not only in the economic sphere) and the promotion of life chances for all the members of the polity. The ‘economistic sliding’ of European liberalism is partly responsible for the current malaise of the European Union and should be countered by launching a comprehensive agenda of ‘liberal’ transformation, in the richer and wider sense of the word.</p>",maurizio ferrera,,2009.0,10.1057/eps.2008.55,European Political Science,Ferrera2009,Not available,,Nature,Not available,"A Less Fragile, if More Liberal Europe",97a0ff025615ae3177803a004fde022f,http://dx.doi.org/10.1057/eps.2008.55
14643,"<p>Does the liberal state have the legitimate power to shape the moral character of its citizenry? One common liberal answer, which draws on a traditional reading of Kant's distinction between morality and right, is “no”: the scope of state authority extends only to the external actions of individuals, not to their inner, moral lives. This article explores an alternative reading of Kant in which the liberal state defends individual rights yet also has the duty to supply the preconditions for enjoying those rights. One precondition is the moral character of the citizenry, even though the government's provision of this precondition would seem to undermine the “external freedom” of citizens. The article thus both challenges a traditional interpretation of Kant's view of the state, and develops a liberal line of reasoning about moral character within a secular, pluralistic regime.</p>",jeffrey church,,2012.0,10.1057/pol.2012.32,Polity,Church2012,Not available,,Nature,Not available,The Political Cultivation of Moral Character: Kant on Public Moral Feeling as a Precondition for Right,5757b2fb510a83248bdf8db9539bb89b,http://dx.doi.org/10.1057/pol.2012.32
14644,"<p>Facing the threats of infectious diseases, we take various actions to protect ourselves, but few studies considered an evolving system with competing strategies. In view of that, we propose an evolutionary epidemic model coupled with human behaviors, where individuals have three strategies: vaccination, self-protection and laissez faire, and could adjust their strategies according to their neighbors' strategies and payoffs at the beginning of each new season of epidemic spreading. We found a counter-intuitive phenomenon analogous to the well-known <i>Braess's Paradox</i>, namely a better condition may lead to worse performance. Specifically speaking, increasing the successful rate of self-protection does not necessarily reduce the epidemic size or improve the system payoff. The range and degree of the Braess's Paradox are sensitive to both the parameters characterizing the epidemic spreading and the strategy payoff, while the existence of the Braess's Paradox is insensitive to the network topologies. This phenomenon can be well explained by a mean-field approximation. Our study demonstrates an important fact that a better condition for individuals may yield a worse outcome for the society.</p>",hai-feng zhang,Applied mathematics,2013.0,10.1038/srep03292,Scientific Reports,Zhang2013,Not available,,Nature,Not available,Braess's Paradox in Epidemic Game: Better Condition Results in Less Payoff,551a0daab3513be189f0f7a0e0fd3e06,http://dx.doi.org/10.1038/srep03292
14645,"<p>The case shows how a technology services company shaped and reshaped – and reshaped again – its IT governance structure to better integrate the IT function with business clients. The company is a large Italian telematics provider – Octo Telematics – which is specialized in the provision of telematic services and systems for the insurance and automotive markets. During the period described in this case, the company was growing and globalizing rapidly. The desired alignment between IT and the business units is needed to promote behaviors consistent with the organization’s mission and strategy. As Octo experimented with new processes, committees and reorganizations the company ‘traveled’ through several governance archetypes.</p>",giovanni vaia,,2013.0,10.1057/jittc.2013.8,Journal of Information Technology Teaching Cases,Vaia2013,Not available,,Nature,Not available,Reshaping the IT governance in Octo Telematics to gain IT–business alignment,8fe5175d1d710085c800e11c0cc2f742,http://dx.doi.org/10.1057/jittc.2013.8
14646,"<p>The case shows how a technology services company shaped and reshaped – and reshaped again – its IT governance structure to better integrate the IT function with business clients. The company is a large Italian telematics provider – Octo Telematics – which is specialized in the provision of telematic services and systems for the insurance and automotive markets. During the period described in this case, the company was growing and globalizing rapidly. The desired alignment between IT and the business units is needed to promote behaviors consistent with the organization’s mission and strategy. As Octo experimented with new processes, committees and reorganizations the company ‘traveled’ through several governance archetypes.</p>",erran carmel,,2013.0,10.1057/jittc.2013.8,Journal of Information Technology Teaching Cases,Vaia2013,Not available,,Nature,Not available,Reshaping the IT governance in Octo Telematics to gain IT–business alignment,8fe5175d1d710085c800e11c0cc2f742,http://dx.doi.org/10.1057/jittc.2013.8
14647,"<p>Using road GIS (geographical information systems) data and travel demand data for two U.S. urban areas, the dynamical driver sources of each road segment were located. A method to target road clusters closely related to urban traffic congestion was then developed to improve road network efficiency. The targeted road clusters show different spatial distributions at different times of a day, indicating that our method can encapsulate dynamical travel demand information into the road networks. As a proof of concept, when we lowered the speed limit or increased the capacity of road segments in the targeted road clusters, we found that both the number of congested roads and extra travel time were effectively reduced. In addition, the proposed modeling framework provided new insights on the optimization of transport efficiency in any infrastructure network with a specific supply and demand distribution.</p>",junjie wang,Phase transitions and critical phenomena,2014.0,10.1038/srep04141,Scientific Reports,Wang2014,Not available,,Nature,Not available,Encapsulating Urban Traffic Rhythms into Road Networks,adb25e6000d05d517194b51d9551436d,http://dx.doi.org/10.1038/srep04141
14648,"<p>Using road GIS (geographical information systems) data and travel demand data for two U.S. urban areas, the dynamical driver sources of each road segment were located. A method to target road clusters closely related to urban traffic congestion was then developed to improve road network efficiency. The targeted road clusters show different spatial distributions at different times of a day, indicating that our method can encapsulate dynamical travel demand information into the road networks. As a proof of concept, when we lowered the speed limit or increased the capacity of road segments in the targeted road clusters, we found that both the number of congested roads and extra travel time were effectively reduced. In addition, the proposed modeling framework provided new insights on the optimization of transport efficiency in any infrastructure network with a specific supply and demand distribution.</p>",junjie wang,Applied physics,2014.0,10.1038/srep04141,Scientific Reports,Wang2014,Not available,,Nature,Not available,Encapsulating Urban Traffic Rhythms into Road Networks,adb25e6000d05d517194b51d9551436d,http://dx.doi.org/10.1038/srep04141
14649,"<p>Using road GIS (geographical information systems) data and travel demand data for two U.S. urban areas, the dynamical driver sources of each road segment were located. A method to target road clusters closely related to urban traffic congestion was then developed to improve road network efficiency. The targeted road clusters show different spatial distributions at different times of a day, indicating that our method can encapsulate dynamical travel demand information into the road networks. As a proof of concept, when we lowered the speed limit or increased the capacity of road segments in the targeted road clusters, we found that both the number of congested roads and extra travel time were effectively reduced. In addition, the proposed modeling framework provided new insights on the optimization of transport efficiency in any infrastructure network with a specific supply and demand distribution.</p>",junjie wang,Civil engineering,2014.0,10.1038/srep04141,Scientific Reports,Wang2014,Not available,,Nature,Not available,Encapsulating Urban Traffic Rhythms into Road Networks,adb25e6000d05d517194b51d9551436d,http://dx.doi.org/10.1038/srep04141
14650,"<p>Using road GIS (geographical information systems) data and travel demand data for two U.S. urban areas, the dynamical driver sources of each road segment were located. A method to target road clusters closely related to urban traffic congestion was then developed to improve road network efficiency. The targeted road clusters show different spatial distributions at different times of a day, indicating that our method can encapsulate dynamical travel demand information into the road networks. As a proof of concept, when we lowered the speed limit or increased the capacity of road segments in the targeted road clusters, we found that both the number of congested roads and extra travel time were effectively reduced. In addition, the proposed modeling framework provided new insights on the optimization of transport efficiency in any infrastructure network with a specific supply and demand distribution.</p>",junjie wang,Complex networks,2014.0,10.1038/srep04141,Scientific Reports,Wang2014,Not available,,Nature,Not available,Encapsulating Urban Traffic Rhythms into Road Networks,adb25e6000d05d517194b51d9551436d,http://dx.doi.org/10.1038/srep04141
14651,"<p>Using road GIS (geographical information systems) data and travel demand data for two U.S. urban areas, the dynamical driver sources of each road segment were located. A method to target road clusters closely related to urban traffic congestion was then developed to improve road network efficiency. The targeted road clusters show different spatial distributions at different times of a day, indicating that our method can encapsulate dynamical travel demand information into the road networks. As a proof of concept, when we lowered the speed limit or increased the capacity of road segments in the targeted road clusters, we found that both the number of congested roads and extra travel time were effectively reduced. In addition, the proposed modeling framework provided new insights on the optimization of transport efficiency in any infrastructure network with a specific supply and demand distribution.</p>",dong wei,Phase transitions and critical phenomena,2014.0,10.1038/srep04141,Scientific Reports,Wang2014,Not available,,Nature,Not available,Encapsulating Urban Traffic Rhythms into Road Networks,adb25e6000d05d517194b51d9551436d,http://dx.doi.org/10.1038/srep04141
14652,"<p>Using road GIS (geographical information systems) data and travel demand data for two U.S. urban areas, the dynamical driver sources of each road segment were located. A method to target road clusters closely related to urban traffic congestion was then developed to improve road network efficiency. The targeted road clusters show different spatial distributions at different times of a day, indicating that our method can encapsulate dynamical travel demand information into the road networks. As a proof of concept, when we lowered the speed limit or increased the capacity of road segments in the targeted road clusters, we found that both the number of congested roads and extra travel time were effectively reduced. In addition, the proposed modeling framework provided new insights on the optimization of transport efficiency in any infrastructure network with a specific supply and demand distribution.</p>",dong wei,Applied physics,2014.0,10.1038/srep04141,Scientific Reports,Wang2014,Not available,,Nature,Not available,Encapsulating Urban Traffic Rhythms into Road Networks,adb25e6000d05d517194b51d9551436d,http://dx.doi.org/10.1038/srep04141
14653,"<p>Using road GIS (geographical information systems) data and travel demand data for two U.S. urban areas, the dynamical driver sources of each road segment were located. A method to target road clusters closely related to urban traffic congestion was then developed to improve road network efficiency. The targeted road clusters show different spatial distributions at different times of a day, indicating that our method can encapsulate dynamical travel demand information into the road networks. As a proof of concept, when we lowered the speed limit or increased the capacity of road segments in the targeted road clusters, we found that both the number of congested roads and extra travel time were effectively reduced. In addition, the proposed modeling framework provided new insights on the optimization of transport efficiency in any infrastructure network with a specific supply and demand distribution.</p>",dong wei,Civil engineering,2014.0,10.1038/srep04141,Scientific Reports,Wang2014,Not available,,Nature,Not available,Encapsulating Urban Traffic Rhythms into Road Networks,adb25e6000d05d517194b51d9551436d,http://dx.doi.org/10.1038/srep04141
14654,"<p>Using road GIS (geographical information systems) data and travel demand data for two U.S. urban areas, the dynamical driver sources of each road segment were located. A method to target road clusters closely related to urban traffic congestion was then developed to improve road network efficiency. The targeted road clusters show different spatial distributions at different times of a day, indicating that our method can encapsulate dynamical travel demand information into the road networks. As a proof of concept, when we lowered the speed limit or increased the capacity of road segments in the targeted road clusters, we found that both the number of congested roads and extra travel time were effectively reduced. In addition, the proposed modeling framework provided new insights on the optimization of transport efficiency in any infrastructure network with a specific supply and demand distribution.</p>",dong wei,Complex networks,2014.0,10.1038/srep04141,Scientific Reports,Wang2014,Not available,,Nature,Not available,Encapsulating Urban Traffic Rhythms into Road Networks,adb25e6000d05d517194b51d9551436d,http://dx.doi.org/10.1038/srep04141
14655,"<p>Facing the threats of infectious diseases, we take various actions to protect ourselves, but few studies considered an evolving system with competing strategies. In view of that, we propose an evolutionary epidemic model coupled with human behaviors, where individuals have three strategies: vaccination, self-protection and laissez faire, and could adjust their strategies according to their neighbors' strategies and payoffs at the beginning of each new season of epidemic spreading. We found a counter-intuitive phenomenon analogous to the well-known <i>Braess's Paradox</i>, namely a better condition may lead to worse performance. Specifically speaking, increasing the successful rate of self-protection does not necessarily reduce the epidemic size or improve the system payoff. The range and degree of the Braess's Paradox are sensitive to both the parameters characterizing the epidemic spreading and the strategy payoff, while the existence of the Braess's Paradox is insensitive to the network topologies. This phenomenon can be well explained by a mean-field approximation. Our study demonstrates an important fact that a better condition for individuals may yield a worse outcome for the society.</p>",hai-feng zhang,Applied physics,2013.0,10.1038/srep03292,Scientific Reports,Zhang2013,Not available,,Nature,Not available,Braess's Paradox in Epidemic Game: Better Condition Results in Less Payoff,551a0daab3513be189f0f7a0e0fd3e06,http://dx.doi.org/10.1038/srep03292
14656,"<p>Using road GIS (geographical information systems) data and travel demand data for two U.S. urban areas, the dynamical driver sources of each road segment were located. A method to target road clusters closely related to urban traffic congestion was then developed to improve road network efficiency. The targeted road clusters show different spatial distributions at different times of a day, indicating that our method can encapsulate dynamical travel demand information into the road networks. As a proof of concept, when we lowered the speed limit or increased the capacity of road segments in the targeted road clusters, we found that both the number of congested roads and extra travel time were effectively reduced. In addition, the proposed modeling framework provided new insights on the optimization of transport efficiency in any infrastructure network with a specific supply and demand distribution.</p>",kun he,Phase transitions and critical phenomena,2014.0,10.1038/srep04141,Scientific Reports,Wang2014,Not available,,Nature,Not available,Encapsulating Urban Traffic Rhythms into Road Networks,adb25e6000d05d517194b51d9551436d,http://dx.doi.org/10.1038/srep04141
14657,"<p>Using road GIS (geographical information systems) data and travel demand data for two U.S. urban areas, the dynamical driver sources of each road segment were located. A method to target road clusters closely related to urban traffic congestion was then developed to improve road network efficiency. The targeted road clusters show different spatial distributions at different times of a day, indicating that our method can encapsulate dynamical travel demand information into the road networks. As a proof of concept, when we lowered the speed limit or increased the capacity of road segments in the targeted road clusters, we found that both the number of congested roads and extra travel time were effectively reduced. In addition, the proposed modeling framework provided new insights on the optimization of transport efficiency in any infrastructure network with a specific supply and demand distribution.</p>",kun he,Applied physics,2014.0,10.1038/srep04141,Scientific Reports,Wang2014,Not available,,Nature,Not available,Encapsulating Urban Traffic Rhythms into Road Networks,adb25e6000d05d517194b51d9551436d,http://dx.doi.org/10.1038/srep04141
14658,"<p>Using road GIS (geographical information systems) data and travel demand data for two U.S. urban areas, the dynamical driver sources of each road segment were located. A method to target road clusters closely related to urban traffic congestion was then developed to improve road network efficiency. The targeted road clusters show different spatial distributions at different times of a day, indicating that our method can encapsulate dynamical travel demand information into the road networks. As a proof of concept, when we lowered the speed limit or increased the capacity of road segments in the targeted road clusters, we found that both the number of congested roads and extra travel time were effectively reduced. In addition, the proposed modeling framework provided new insights on the optimization of transport efficiency in any infrastructure network with a specific supply and demand distribution.</p>",kun he,Civil engineering,2014.0,10.1038/srep04141,Scientific Reports,Wang2014,Not available,,Nature,Not available,Encapsulating Urban Traffic Rhythms into Road Networks,adb25e6000d05d517194b51d9551436d,http://dx.doi.org/10.1038/srep04141
14659,"<p>Using road GIS (geographical information systems) data and travel demand data for two U.S. urban areas, the dynamical driver sources of each road segment were located. A method to target road clusters closely related to urban traffic congestion was then developed to improve road network efficiency. The targeted road clusters show different spatial distributions at different times of a day, indicating that our method can encapsulate dynamical travel demand information into the road networks. As a proof of concept, when we lowered the speed limit or increased the capacity of road segments in the targeted road clusters, we found that both the number of congested roads and extra travel time were effectively reduced. In addition, the proposed modeling framework provided new insights on the optimization of transport efficiency in any infrastructure network with a specific supply and demand distribution.</p>",kun he,Complex networks,2014.0,10.1038/srep04141,Scientific Reports,Wang2014,Not available,,Nature,Not available,Encapsulating Urban Traffic Rhythms into Road Networks,adb25e6000d05d517194b51d9551436d,http://dx.doi.org/10.1038/srep04141
14660,"<p>Using road GIS (geographical information systems) data and travel demand data for two U.S. urban areas, the dynamical driver sources of each road segment were located. A method to target road clusters closely related to urban traffic congestion was then developed to improve road network efficiency. The targeted road clusters show different spatial distributions at different times of a day, indicating that our method can encapsulate dynamical travel demand information into the road networks. As a proof of concept, when we lowered the speed limit or increased the capacity of road segments in the targeted road clusters, we found that both the number of congested roads and extra travel time were effectively reduced. In addition, the proposed modeling framework provided new insights on the optimization of transport efficiency in any infrastructure network with a specific supply and demand distribution.</p>",hang gong,Phase transitions and critical phenomena,2014.0,10.1038/srep04141,Scientific Reports,Wang2014,Not available,,Nature,Not available,Encapsulating Urban Traffic Rhythms into Road Networks,adb25e6000d05d517194b51d9551436d,http://dx.doi.org/10.1038/srep04141
14661,"<p>Using road GIS (geographical information systems) data and travel demand data for two U.S. urban areas, the dynamical driver sources of each road segment were located. A method to target road clusters closely related to urban traffic congestion was then developed to improve road network efficiency. The targeted road clusters show different spatial distributions at different times of a day, indicating that our method can encapsulate dynamical travel demand information into the road networks. As a proof of concept, when we lowered the speed limit or increased the capacity of road segments in the targeted road clusters, we found that both the number of congested roads and extra travel time were effectively reduced. In addition, the proposed modeling framework provided new insights on the optimization of transport efficiency in any infrastructure network with a specific supply and demand distribution.</p>",hang gong,Applied physics,2014.0,10.1038/srep04141,Scientific Reports,Wang2014,Not available,,Nature,Not available,Encapsulating Urban Traffic Rhythms into Road Networks,adb25e6000d05d517194b51d9551436d,http://dx.doi.org/10.1038/srep04141
14662,"<p>Using road GIS (geographical information systems) data and travel demand data for two U.S. urban areas, the dynamical driver sources of each road segment were located. A method to target road clusters closely related to urban traffic congestion was then developed to improve road network efficiency. The targeted road clusters show different spatial distributions at different times of a day, indicating that our method can encapsulate dynamical travel demand information into the road networks. As a proof of concept, when we lowered the speed limit or increased the capacity of road segments in the targeted road clusters, we found that both the number of congested roads and extra travel time were effectively reduced. In addition, the proposed modeling framework provided new insights on the optimization of transport efficiency in any infrastructure network with a specific supply and demand distribution.</p>",hang gong,Civil engineering,2014.0,10.1038/srep04141,Scientific Reports,Wang2014,Not available,,Nature,Not available,Encapsulating Urban Traffic Rhythms into Road Networks,adb25e6000d05d517194b51d9551436d,http://dx.doi.org/10.1038/srep04141
14663,"<p>Using road GIS (geographical information systems) data and travel demand data for two U.S. urban areas, the dynamical driver sources of each road segment were located. A method to target road clusters closely related to urban traffic congestion was then developed to improve road network efficiency. The targeted road clusters show different spatial distributions at different times of a day, indicating that our method can encapsulate dynamical travel demand information into the road networks. As a proof of concept, when we lowered the speed limit or increased the capacity of road segments in the targeted road clusters, we found that both the number of congested roads and extra travel time were effectively reduced. In addition, the proposed modeling framework provided new insights on the optimization of transport efficiency in any infrastructure network with a specific supply and demand distribution.</p>",hang gong,Complex networks,2014.0,10.1038/srep04141,Scientific Reports,Wang2014,Not available,,Nature,Not available,Encapsulating Urban Traffic Rhythms into Road Networks,adb25e6000d05d517194b51d9551436d,http://dx.doi.org/10.1038/srep04141
14664,"<p>Using road GIS (geographical information systems) data and travel demand data for two U.S. urban areas, the dynamical driver sources of each road segment were located. A method to target road clusters closely related to urban traffic congestion was then developed to improve road network efficiency. The targeted road clusters show different spatial distributions at different times of a day, indicating that our method can encapsulate dynamical travel demand information into the road networks. As a proof of concept, when we lowered the speed limit or increased the capacity of road segments in the targeted road clusters, we found that both the number of congested roads and extra travel time were effectively reduced. In addition, the proposed modeling framework provided new insights on the optimization of transport efficiency in any infrastructure network with a specific supply and demand distribution.</p>",pu wang,Phase transitions and critical phenomena,2014.0,10.1038/srep04141,Scientific Reports,Wang2014,Not available,,Nature,Not available,Encapsulating Urban Traffic Rhythms into Road Networks,adb25e6000d05d517194b51d9551436d,http://dx.doi.org/10.1038/srep04141
14665,"<p>Using road GIS (geographical information systems) data and travel demand data for two U.S. urban areas, the dynamical driver sources of each road segment were located. A method to target road clusters closely related to urban traffic congestion was then developed to improve road network efficiency. The targeted road clusters show different spatial distributions at different times of a day, indicating that our method can encapsulate dynamical travel demand information into the road networks. As a proof of concept, when we lowered the speed limit or increased the capacity of road segments in the targeted road clusters, we found that both the number of congested roads and extra travel time were effectively reduced. In addition, the proposed modeling framework provided new insights on the optimization of transport efficiency in any infrastructure network with a specific supply and demand distribution.</p>",pu wang,Applied physics,2014.0,10.1038/srep04141,Scientific Reports,Wang2014,Not available,,Nature,Not available,Encapsulating Urban Traffic Rhythms into Road Networks,adb25e6000d05d517194b51d9551436d,http://dx.doi.org/10.1038/srep04141
14666,"<p>Facing the threats of infectious diseases, we take various actions to protect ourselves, but few studies considered an evolving system with competing strategies. In view of that, we propose an evolutionary epidemic model coupled with human behaviors, where individuals have three strategies: vaccination, self-protection and laissez faire, and could adjust their strategies according to their neighbors' strategies and payoffs at the beginning of each new season of epidemic spreading. We found a counter-intuitive phenomenon analogous to the well-known <i>Braess's Paradox</i>, namely a better condition may lead to worse performance. Specifically speaking, increasing the successful rate of self-protection does not necessarily reduce the epidemic size or improve the system payoff. The range and degree of the Braess's Paradox are sensitive to both the parameters characterizing the epidemic spreading and the strategy payoff, while the existence of the Braess's Paradox is insensitive to the network topologies. This phenomenon can be well explained by a mean-field approximation. Our study demonstrates an important fact that a better condition for individuals may yield a worse outcome for the society.</p>",hai-feng zhang,Complex networks,2013.0,10.1038/srep03292,Scientific Reports,Zhang2013,Not available,,Nature,Not available,Braess's Paradox in Epidemic Game: Better Condition Results in Less Payoff,551a0daab3513be189f0f7a0e0fd3e06,http://dx.doi.org/10.1038/srep03292
14667,"<p>Using road GIS (geographical information systems) data and travel demand data for two U.S. urban areas, the dynamical driver sources of each road segment were located. A method to target road clusters closely related to urban traffic congestion was then developed to improve road network efficiency. The targeted road clusters show different spatial distributions at different times of a day, indicating that our method can encapsulate dynamical travel demand information into the road networks. As a proof of concept, when we lowered the speed limit or increased the capacity of road segments in the targeted road clusters, we found that both the number of congested roads and extra travel time were effectively reduced. In addition, the proposed modeling framework provided new insights on the optimization of transport efficiency in any infrastructure network with a specific supply and demand distribution.</p>",pu wang,Civil engineering,2014.0,10.1038/srep04141,Scientific Reports,Wang2014,Not available,,Nature,Not available,Encapsulating Urban Traffic Rhythms into Road Networks,adb25e6000d05d517194b51d9551436d,http://dx.doi.org/10.1038/srep04141
14668,"<p>Using road GIS (geographical information systems) data and travel demand data for two U.S. urban areas, the dynamical driver sources of each road segment were located. A method to target road clusters closely related to urban traffic congestion was then developed to improve road network efficiency. The targeted road clusters show different spatial distributions at different times of a day, indicating that our method can encapsulate dynamical travel demand information into the road networks. As a proof of concept, when we lowered the speed limit or increased the capacity of road segments in the targeted road clusters, we found that both the number of congested roads and extra travel time were effectively reduced. In addition, the proposed modeling framework provided new insights on the optimization of transport efficiency in any infrastructure network with a specific supply and demand distribution.</p>",pu wang,Complex networks,2014.0,10.1038/srep04141,Scientific Reports,Wang2014,Not available,,Nature,Not available,Encapsulating Urban Traffic Rhythms into Road Networks,adb25e6000d05d517194b51d9551436d,http://dx.doi.org/10.1038/srep04141
14669,"<p>After unification in 1990, German foreign policy has received unprecedented attention from the most prominent journals of International Relations (IR) theory. This paper argues that this was due largely to the function which the German ‘case’ served in the discourse of IR/foreign policy theory. Realists as well as liberals and constructivists were heavily enticed by it since it seemed an excellent case for all of them to prove the worth of their theories. In doing so, however, the subsumtionist logic applied did not only foster identical exclusionist theoretical claims. It also cultivated a systematicity view of thought and action which was wholly unreceptive for potentially novel foreign policy practices to appear. The paper documents and critiques these trends as a typical phenomenon of a paradigmatic discipline. It then outlines an alternative pragmatist approach to foreign policy analysis which emphasizes the contingency and situated creativity of social action. It is argued, in particular, that this approach provides for a more adequate description of the changes which German foreign policy has undergone. Moreover, by drawing on the insights of allegedly incommensurable paradigms and by systematically integrating the inherent contingency of social action, it also shows how a logic of reconstruction can open up avenues for cross-paradigmatic dialogue.</p>",gunther hellmann,,2009.0,10.1057/jird.2009.11,Journal of International Relations and Development,Hellmann2009,Not available,,Nature,Not available,Fatal attraction? German foreign policy and IR/foreign policy theory,2d139d1d7508a3182a7b66af8e791df1,http://dx.doi.org/10.1057/jird.2009.11
14670,"<p>Practicing managers live in a world of ‘extremes’, but international business and management research is based on Gaussian statistics that rule out such extremes. On occasion, positive feedback processes among interactive data points cause extreme events characterized by power laws. They seem ubiquitous; we list 80 kinds of them – half each among natural and social phenomena. We use imposed tension and Per Bak's ‘self-organized criticality’ to argue that Pareto-based science and statistics (based on interdependence, positive feedback, scalability, (nearly) infinite variance, and emphasizing extremes) should parallel the traditional dominance of Gaussian statistics (based on independent data points, finite variance and emphasizing averages). We question quantitative journal publications depending on Gaussian statistics. The cost is inaccurate science and irrelevance to practitioners. In conclusion, no statistical findings should be accepted into business studies if they gain significance via some assumption device by which extreme events and (nearly) infinite variance are ignored. Accordingly, we suggest redirecting international business studies, and management research in general.</p>",pierpaolo andriani,,2007.0,10.1057/palgrave.jibs.8400324,Journal of International Business Studies,Andriani2007,Not available,,Nature,Not available,Beyond Gaussian averages: redirecting international business and management research toward extreme events and power laws,b15cda113385d0589766bc8dff20063c,http://dx.doi.org/10.1057/palgrave.jibs.8400324
14671,"<p>Practicing managers live in a world of ‘extremes’, but international business and management research is based on Gaussian statistics that rule out such extremes. On occasion, positive feedback processes among interactive data points cause extreme events characterized by power laws. They seem ubiquitous; we list 80 kinds of them – half each among natural and social phenomena. We use imposed tension and Per Bak's ‘self-organized criticality’ to argue that Pareto-based science and statistics (based on interdependence, positive feedback, scalability, (nearly) infinite variance, and emphasizing extremes) should parallel the traditional dominance of Gaussian statistics (based on independent data points, finite variance and emphasizing averages). We question quantitative journal publications depending on Gaussian statistics. The cost is inaccurate science and irrelevance to practitioners. In conclusion, no statistical findings should be accepted into business studies if they gain significance via some assumption device by which extreme events and (nearly) infinite variance are ignored. Accordingly, we suggest redirecting international business studies, and management research in general.</p>",bill mckelvey,,2007.0,10.1057/palgrave.jibs.8400324,Journal of International Business Studies,Andriani2007,Not available,,Nature,Not available,Beyond Gaussian averages: redirecting international business and management research toward extreme events and power laws,b15cda113385d0589766bc8dff20063c,http://dx.doi.org/10.1057/palgrave.jibs.8400324
14672,"<p>While the practice of reinventing realism is by no means novel, recent reinventions have taken a decidedly reflexive turn. This article examines how three particular scholars — Anthony Lang, Michael Williams, and Richard Ned Lebow — have revived some important and relatively obscured principles from classical realists, thereby recovering some practical ethics important for contemporary world politics. The article outlines the principles held in common by this scholarship. Reflexive realism has also resurrected and re-emphasized a once obscured critical voice of realists like Hans Morgenthau. In the process, it has served as a launching pad for a serious critique of eschatological-based philosophy, including neoconservatism. Several avenues for the future development of reflexive realism are also identified.</p>",brent steele,,2007.0,10.1057/palgrave.jird.1800130,Journal of International Relations and Development,Steele2007,Not available,,Nature,Not available,‘Eavesdropping on honored ghosts’: from classical to reflexive realism,db307029eefee20b289cf2211c186331,http://dx.doi.org/10.1057/palgrave.jird.1800130
14673,"<p>Michael Moon interviews Terry White, Chief Innovator for Amway Japan, on Amway's journey through brand and identity, innovation, analytics, mobile devices and best practices for building global brands through social networking.</p>",terry white,,2008.0,10.1057/dam.2008.9,Journal of Digital Asset Management,White2008,Not available,,Nature,Not available,"How to be friended and influenced by people — Interview with Terry White, Chief Innovator for Amway Japan",8fe322d2837321e26de653fd4ac2f222,http://dx.doi.org/10.1057/dam.2008.9
14674,"<p>The European Union likes to portray itself as a postmodern entity that does not require war to establish itself as a political player. This breaks a pattern, as war and violence have historically played a major part in state formation and shaping the national interest. Europe’s public disavowal of power gained political prominence after Robert Kagan’s influential essay <i>Power and Weakness</i>. Kagan’s depiction of Europe as a postmodern Kantian space was not unjustified, but his conclusion that a more military-capable Europe would close the transatlantic power gap, and hence make US–European cooperation easier, remains controversial. Robert Cooper nuanced Kagan’s point by claiming that ‘Europe may have chosen to neglect power politics because it is militarily weak; but it is also true that it is militarily weak because it has chosen to abandon power politics’. Commentators have frequently summarized this ‘chicken-and-egg’ dilemma by quipping that ‘if all you have is a hammer, everything looks like a nail’, or, alternatively, ‘when all you have is a pen, every problem looks like a treaty’. What may at first glance sound like a silly, somewhat trivial, debate is actually a profound and fundamental question about the relationship between military power and foreign policy in general, and between war and identity in particular.</p>",peter ham,,2010.0,10.1057/ip.2010.31,International Politics,Ham2010,Not available,,Nature,Not available,The power of war: Why Europe needs it,957dd411284294f3230bacd48218c8c3,http://dx.doi.org/10.1057/ip.2010.31
14675,"<p>This article is a study of Canada's foreign policy towards Africa from the earliest beginnings after the Second World War until 2012. The argument is that Canada has tried to ensure it is well regarded by Africa as a player, partner and friend. This would permit Canada to (1) build constituencies of support with Africans when interests converge on issues of common concern; and (2) ensure Canada is not alienated from Africa, and African states are not alienated from the West. Since 2006, however, Prime Minister Stephen Harper has over-emphasized the trade (player) aspect of the Africa policy, with potentially serious consequences for Canada's reputation and position in Africa against competitors like China.</p>",grant dawson,,2013.0,10.1057/ip.2013.8,International Politics,Dawson2013,Not available,,Nature,Not available,"Player, partner and friend: Canada's Africa policy since 1945",458624f5095b2ed7af09017ff413ecff,http://dx.doi.org/10.1057/ip.2013.8
14676,"  We consider the well-studied game-theoretic version of machine scheduling in
which jobs correspond to self-interested users and machines correspond to
resources. Here each user chooses a machine trying to minimize her own cost,
and such selfish behavior typically results in some equilibrium which is not
globally optimal: An equilibrium is an allocation where no user can reduce her
own cost by moving to another machine, which in general need not minimize the
makespan, i.e., the maximum load over the machines.
  We provide tight bounds on two well-studied notions in algorithmic game
theory, namely, the price of anarchy and the strong price of anarchy on machine
scheduling setting which lies in between the related and the unrelated machine
case. Both notions study the social cost (makespan) of the worst equilibrium
compared to the optimum, with the strong price of anarchy restricting to a
stronger form of equilibria. Our results extend a prior study comparing the
price of anarchy to the strong price of anarchy for two related machines
(Epstein, Acta Informatica 2010), thus providing further insights on the
relation between these concepts. Our exact bounds give a qualitative and
quantitative comparison between the two models. The bounds also show that the
setting is indeed easier than the two unrelated machines: In the latter, the
strong price of anarchy is $2$, while in ours it is strictly smaller.
",cong chen,,2017.0,,arXiv,Chen2017,True,,arXiv,Not available,"Selfish Jobs with Favorite Machines: Price of Anarchy vs Strong Price of
  Anarchy",2e346561b331f1e9787c035fd7877512,http://arxiv.org/abs/1709.06367v1
14677,"  The congestion pricing is an efficient allocation approach to mediate demand
and supply of network resources. Different from the previous pricing using
Affine Marginal Cost (AMC), we focus on studying the game between network
coding and routing flows sharing a single link when users are price
anticipating based on an Average Cost Sharing (ACS) pricing mechanism. We
characterize the worst-case efficiency bounds of the game compared with the
optimal, i.e., the price-of anarchy (POA), which can be low bound 50% with
routing only. When both network coding and routing are applied, the POA can be
as low as 4/9. Therefore, network coding cannot improve the POA significantly
under the ACS. Moreover, for more efficient use of limited resources, it
indicates the sharing users have a higher tendency to choose network coding.
",dai xia,,2011.0,,arXiv,Gang2011,True,,arXiv,Not available,"The Price of Anarchy (POA) of network coding and routing based on
  average pricing mechanism",a0e7cdbbea82825b12d0fd725dfcc644,http://arxiv.org/abs/1110.4175v1
14678,"  We generalize the notions of user equilibrium and system optimum to
non-atomic congestion games with stochastic demands. We establish upper bounds
on the price of anarchy for three different settings of link cost functions and
demand distributions, namely, (a) affine cost functions and general
distributions, (b) polynomial cost functions and general positive-valued
distributions, and (c) polynomial cost functions and the normal distributions.
All the upper bounds are tight in some special cases, including the case of
deterministic demands.
",chenlan wang,,2013.0,,arXiv,Wang2013,True,,arXiv,Not available,Price of Anarchy for Non-atomic Congestion Games with Stochastic Demands,39c018e2806cbe8809675f1bc41b60e6,http://arxiv.org/abs/1310.4874v1
14679,"  We generalize the notions of user equilibrium and system optimum to
non-atomic congestion games with stochastic demands. We establish upper bounds
on the price of anarchy for three different settings of link cost functions and
demand distributions, namely, (a) affine cost functions and general
distributions, (b) polynomial cost functions and general positive-valued
distributions, and (c) polynomial cost functions and the normal distributions.
All the upper bounds are tight in some special cases, including the case of
deterministic demands.
",xuan doan,,2013.0,,arXiv,Wang2013,True,,arXiv,Not available,Price of Anarchy for Non-atomic Congestion Games with Stochastic Demands,39c018e2806cbe8809675f1bc41b60e6,http://arxiv.org/abs/1310.4874v1
14680,"  We generalize the notions of user equilibrium and system optimum to
non-atomic congestion games with stochastic demands. We establish upper bounds
on the price of anarchy for three different settings of link cost functions and
demand distributions, namely, (a) affine cost functions and general
distributions, (b) polynomial cost functions and general positive-valued
distributions, and (c) polynomial cost functions and the normal distributions.
All the upper bounds are tight in some special cases, including the case of
deterministic demands.
",bo chen,,2013.0,,arXiv,Wang2013,True,,arXiv,Not available,Price of Anarchy for Non-atomic Congestion Games with Stochastic Demands,39c018e2806cbe8809675f1bc41b60e6,http://arxiv.org/abs/1310.4874v1
14681,"  We analyze the network congestion game with atomic players, asymmetric
strategies, and the maximum latency among all players as social cost. This
important social cost function is much less understood than the average
latency. We show that the price of anarchy is at most two, when the network is
a ring and the link latencies are linear. Our bound is tight. This is the first
sharp bound for the maximum latency objective.
",xujin chen,,2012.0,,arXiv,Chen2012,True,,arXiv,Not available,The Price of Anarchy for Selfish Ring Routing is Two,9d5d796d15264303550b419ebcd8d6e9,http://arxiv.org/abs/1210.0230v1
14682,"  We analyze the network congestion game with atomic players, asymmetric
strategies, and the maximum latency among all players as social cost. This
important social cost function is much less understood than the average
latency. We show that the price of anarchy is at most two, when the network is
a ring and the link latencies are linear. Our bound is tight. This is the first
sharp bound for the maximum latency objective.
",benjamin doerr,,2012.0,,arXiv,Chen2012,True,,arXiv,Not available,The Price of Anarchy for Selfish Ring Routing is Two,9d5d796d15264303550b419ebcd8d6e9,http://arxiv.org/abs/1210.0230v1
14683,"  We analyze the network congestion game with atomic players, asymmetric
strategies, and the maximum latency among all players as social cost. This
important social cost function is much less understood than the average
latency. We show that the price of anarchy is at most two, when the network is
a ring and the link latencies are linear. Our bound is tight. This is the first
sharp bound for the maximum latency objective.
",xiaodong hu,,2012.0,,arXiv,Chen2012,True,,arXiv,Not available,The Price of Anarchy for Selfish Ring Routing is Two,9d5d796d15264303550b419ebcd8d6e9,http://arxiv.org/abs/1210.0230v1
14684,"  We analyze the network congestion game with atomic players, asymmetric
strategies, and the maximum latency among all players as social cost. This
important social cost function is much less understood than the average
latency. We show that the price of anarchy is at most two, when the network is
a ring and the link latencies are linear. Our bound is tight. This is the first
sharp bound for the maximum latency objective.
",weidong ma,,2012.0,,arXiv,Chen2012,True,,arXiv,Not available,The Price of Anarchy for Selfish Ring Routing is Two,9d5d796d15264303550b419ebcd8d6e9,http://arxiv.org/abs/1210.0230v1
14685,"  We analyze the network congestion game with atomic players, asymmetric
strategies, and the maximum latency among all players as social cost. This
important social cost function is much less understood than the average
latency. We show that the price of anarchy is at most two, when the network is
a ring and the link latencies are linear. Our bound is tight. This is the first
sharp bound for the maximum latency objective.
",rob stee,,2012.0,,arXiv,Chen2012,True,,arXiv,Not available,The Price of Anarchy for Selfish Ring Routing is Two,9d5d796d15264303550b419ebcd8d6e9,http://arxiv.org/abs/1210.0230v1
14686,"  We analyze the network congestion game with atomic players, asymmetric
strategies, and the maximum latency among all players as social cost. This
important social cost function is much less understood than the average
latency. We show that the price of anarchy is at most two, when the network is
a ring and the link latencies are linear. Our bound is tight. This is the first
sharp bound for the maximum latency objective.
",carola winzen,,2012.0,,arXiv,Chen2012,True,,arXiv,Not available,The Price of Anarchy for Selfish Ring Routing is Two,9d5d796d15264303550b419ebcd8d6e9,http://arxiv.org/abs/1210.0230v1
14687,"  We consider the well-studied game-theoretic version of machine scheduling in
which jobs correspond to self-interested users and machines correspond to
resources. Here each user chooses a machine trying to minimize her own cost,
and such selfish behavior typically results in some equilibrium which is not
globally optimal: An equilibrium is an allocation where no user can reduce her
own cost by moving to another machine, which in general need not minimize the
makespan, i.e., the maximum load over the machines.
  We provide tight bounds on two well-studied notions in algorithmic game
theory, namely, the price of anarchy and the strong price of anarchy on machine
scheduling setting which lies in between the related and the unrelated machine
case. Both notions study the social cost (makespan) of the worst equilibrium
compared to the optimum, with the strong price of anarchy restricting to a
stronger form of equilibria. Our results extend a prior study comparing the
price of anarchy to the strong price of anarchy for two related machines
(Epstein, Acta Informatica 2010), thus providing further insights on the
relation between these concepts. Our exact bounds give a qualitative and
quantitative comparison between the two models. The bounds also show that the
setting is indeed easier than the two unrelated machines: In the latter, the
strong price of anarchy is $2$, while in ours it is strictly smaller.
",paolo penna,,2017.0,,arXiv,Chen2017,True,,arXiv,Not available,"Selfish Jobs with Favorite Machines: Price of Anarchy vs Strong Price of
  Anarchy",2e346561b331f1e9787c035fd7877512,http://arxiv.org/abs/1709.06367v1
14688,"  We study the efficiency of mechanisms for allocating a divisible resource.
Given scalar signals submitted by all users, such a mechanism decides the
fraction of the resource that each user will receive and a payment that will be
collected from her. Users are self-interested and aim to maximize their utility
(defined as their value for the resource fraction they receive minus their
payment). Starting with the seminal work of Johari and Tsitsiklis [Operations
Research, 2004], a long list of papers studied the price of anarchy (in terms
of the social welfare --- the total users' value) of resource allocation
mechanisms for a variety of allocation and payment rules. Here, we further
assume that each user has a budget constraint that invalidates strategies that
yield a payment that is higher than the user's budget. This subtle assumption,
which is arguably more realistic, constitutes the traditional price of anarchy
analysis meaningless as the set of equilibria may change drastically and their
social welfare can be arbitrarily far from optimal. Instead, we study the price
of anarchy using the liquid welfare benchmark that measures efficiency taking
budget constraints into account. We show a tight bound of 2 on the liquid price
of anarchy of the well-known Kelly mechanism and prove that this result is
essentially best possible among all multi-user resource allocation mechanisms.
This comes in sharp contrast to the no-budget setting where there are
mechanisms that considerably outperform Kelly in terms of social welfare and
even achieve full efficiency. In our proofs, we exploit the particular
structure of worst-case games and equilibria, which also allows us to design
(nearly) optimal two-player mechanisms by solving simple differential
equations.
",ioannis caragiannis,,2017.0,,arXiv,Caragiannis2017,True,,arXiv,Not available,"The efficiency of resource allocation mechanisms for budget-constrained
  users",73ffd441ec695896f2b22b9886e582a2,http://arxiv.org/abs/1707.03551v2
14689,"  We study the efficiency of mechanisms for allocating a divisible resource.
Given scalar signals submitted by all users, such a mechanism decides the
fraction of the resource that each user will receive and a payment that will be
collected from her. Users are self-interested and aim to maximize their utility
(defined as their value for the resource fraction they receive minus their
payment). Starting with the seminal work of Johari and Tsitsiklis [Operations
Research, 2004], a long list of papers studied the price of anarchy (in terms
of the social welfare --- the total users' value) of resource allocation
mechanisms for a variety of allocation and payment rules. Here, we further
assume that each user has a budget constraint that invalidates strategies that
yield a payment that is higher than the user's budget. This subtle assumption,
which is arguably more realistic, constitutes the traditional price of anarchy
analysis meaningless as the set of equilibria may change drastically and their
social welfare can be arbitrarily far from optimal. Instead, we study the price
of anarchy using the liquid welfare benchmark that measures efficiency taking
budget constraints into account. We show a tight bound of 2 on the liquid price
of anarchy of the well-known Kelly mechanism and prove that this result is
essentially best possible among all multi-user resource allocation mechanisms.
This comes in sharp contrast to the no-budget setting where there are
mechanisms that considerably outperform Kelly in terms of social welfare and
even achieve full efficiency. In our proofs, we exploit the particular
structure of worst-case games and equilibria, which also allows us to design
(nearly) optimal two-player mechanisms by solving simple differential
equations.
",alexandros voudouris,,2017.0,,arXiv,Caragiannis2017,True,,arXiv,Not available,"The efficiency of resource allocation mechanisms for budget-constrained
  users",73ffd441ec695896f2b22b9886e582a2,http://arxiv.org/abs/1707.03551v2
14690,"  We consider a game-theoretical problem called selfish 2-dimensional bin
packing game, a generalization of the 1-dimensional case already treated in the
literature. In this game, the items to be packed are rectangles, and the bins
are unit squares. The game starts with a set of items arbitrarily packed in
bins. The cost of an item is defined as the ratio between its area and the
total occupied area of the respective bin. Each item is a selfish player that
wants to minimize its cost. A migration of an item to another bin is allowed
only when its cost is decreased. We show that this game always converges to a
Nash equilibrium (a stable packing where no single item can decrease its cost
by migrating to another bin). We show that the pure price of anarchy of this
game is unbounded, so we address the particular case where all items are
squares. We show that the pure price of anarchy of the selfish square packing
game is at least 2.3634 and at most 2.6875. We also present analogous results
for the strong Nash equilibrium (a stable packing where no nonempty set of
items can simultaneously migrate to another common bin and decrease the cost of
each item in the set). We show that the strong price of anarchy when all items
are squares is at least 2.0747 and at most 2.3605.
",cristina fernandes,,2017.0,,arXiv,Fernandes2017,True,,arXiv,Not available,Prices of anarchy of selfish 2D bin packing games,a08777f5569b5d925bc74a5b7e1ded65,http://arxiv.org/abs/1707.07882v1
14691,"  We consider a game-theoretical problem called selfish 2-dimensional bin
packing game, a generalization of the 1-dimensional case already treated in the
literature. In this game, the items to be packed are rectangles, and the bins
are unit squares. The game starts with a set of items arbitrarily packed in
bins. The cost of an item is defined as the ratio between its area and the
total occupied area of the respective bin. Each item is a selfish player that
wants to minimize its cost. A migration of an item to another bin is allowed
only when its cost is decreased. We show that this game always converges to a
Nash equilibrium (a stable packing where no single item can decrease its cost
by migrating to another bin). We show that the pure price of anarchy of this
game is unbounded, so we address the particular case where all items are
squares. We show that the pure price of anarchy of the selfish square packing
game is at least 2.3634 and at most 2.6875. We also present analogous results
for the strong Nash equilibrium (a stable packing where no nonempty set of
items can simultaneously migrate to another common bin and decrease the cost of
each item in the set). We show that the strong price of anarchy when all items
are squares is at least 2.0747 and at most 2.3605.
",carlos ferreira,,2017.0,,arXiv,Fernandes2017,True,,arXiv,Not available,Prices of anarchy of selfish 2D bin packing games,a08777f5569b5d925bc74a5b7e1ded65,http://arxiv.org/abs/1707.07882v1
14692,"  We consider a game-theoretical problem called selfish 2-dimensional bin
packing game, a generalization of the 1-dimensional case already treated in the
literature. In this game, the items to be packed are rectangles, and the bins
are unit squares. The game starts with a set of items arbitrarily packed in
bins. The cost of an item is defined as the ratio between its area and the
total occupied area of the respective bin. Each item is a selfish player that
wants to minimize its cost. A migration of an item to another bin is allowed
only when its cost is decreased. We show that this game always converges to a
Nash equilibrium (a stable packing where no single item can decrease its cost
by migrating to another bin). We show that the pure price of anarchy of this
game is unbounded, so we address the particular case where all items are
squares. We show that the pure price of anarchy of the selfish square packing
game is at least 2.3634 and at most 2.6875. We also present analogous results
for the strong Nash equilibrium (a stable packing where no nonempty set of
items can simultaneously migrate to another common bin and decrease the cost of
each item in the set). We show that the strong price of anarchy when all items
are squares is at least 2.0747 and at most 2.3605.
",flavio miyazawa,,2017.0,,arXiv,Fernandes2017,True,,arXiv,Not available,Prices of anarchy of selfish 2D bin packing games,a08777f5569b5d925bc74a5b7e1ded65,http://arxiv.org/abs/1707.07882v1
14693,"  We consider a game-theoretical problem called selfish 2-dimensional bin
packing game, a generalization of the 1-dimensional case already treated in the
literature. In this game, the items to be packed are rectangles, and the bins
are unit squares. The game starts with a set of items arbitrarily packed in
bins. The cost of an item is defined as the ratio between its area and the
total occupied area of the respective bin. Each item is a selfish player that
wants to minimize its cost. A migration of an item to another bin is allowed
only when its cost is decreased. We show that this game always converges to a
Nash equilibrium (a stable packing where no single item can decrease its cost
by migrating to another bin). We show that the pure price of anarchy of this
game is unbounded, so we address the particular case where all items are
squares. We show that the pure price of anarchy of the selfish square packing
game is at least 2.3634 and at most 2.6875. We also present analogous results
for the strong Nash equilibrium (a stable packing where no nonempty set of
items can simultaneously migrate to another common bin and decrease the cost of
each item in the set). We show that the strong price of anarchy when all items
are squares is at least 2.0747 and at most 2.3605.
",yoshiko wakabayashi,,2017.0,,arXiv,Fernandes2017,True,,arXiv,Not available,Prices of anarchy of selfish 2D bin packing games,a08777f5569b5d925bc74a5b7e1ded65,http://arxiv.org/abs/1707.07882v1
14694,"  We model the formation of networks as the result of a game where by players
act selfishly to get the portfolio of links they desire most. The integration
of player strategies into the network formation model is appropriate for
organizational networks because in these smaller networks, dynamics are not
random, but the result of intentional actions carried through by players
maximizing their own objectives. This model is a better framework for the
analysis of influences upon a network because it integrates the strategies of
the players involved. We present an Integer Program that calculates the price
of anarchy of this game by finding the worst stable graph and the best
coordinated graph for this game. We simulate the formation of the network and
calculated the simulated price of anarchy, which we find tends to be rather
low.
",shaun lichter,,2011.0,,arXiv,Lichter2011,True,,arXiv,Not available,"The Calculation and Simulation of the Price of Anarchy for Network
  Formation Games",4c51f321c4d44cae6c28c44271499b26,http://arxiv.org/abs/1108.4115v2
14695,"  We model the formation of networks as the result of a game where by players
act selfishly to get the portfolio of links they desire most. The integration
of player strategies into the network formation model is appropriate for
organizational networks because in these smaller networks, dynamics are not
random, but the result of intentional actions carried through by players
maximizing their own objectives. This model is a better framework for the
analysis of influences upon a network because it integrates the strategies of
the players involved. We present an Integer Program that calculates the price
of anarchy of this game by finding the worst stable graph and the best
coordinated graph for this game. We simulate the formation of the network and
calculated the simulated price of anarchy, which we find tends to be rather
low.
",christopher griffin,,2011.0,,arXiv,Lichter2011,True,,arXiv,Not available,"The Calculation and Simulation of the Price of Anarchy for Network
  Formation Games",4c51f321c4d44cae6c28c44271499b26,http://arxiv.org/abs/1108.4115v2
14696,"  We model the formation of networks as the result of a game where by players
act selfishly to get the portfolio of links they desire most. The integration
of player strategies into the network formation model is appropriate for
organizational networks because in these smaller networks, dynamics are not
random, but the result of intentional actions carried through by players
maximizing their own objectives. This model is a better framework for the
analysis of influences upon a network because it integrates the strategies of
the players involved. We present an Integer Program that calculates the price
of anarchy of this game by finding the worst stable graph and the best
coordinated graph for this game. We simulate the formation of the network and
calculated the simulated price of anarchy, which we find tends to be rather
low.
",terry friesz,,2011.0,,arXiv,Lichter2011,True,,arXiv,Not available,"The Calculation and Simulation of the Price of Anarchy for Network
  Formation Games",4c51f321c4d44cae6c28c44271499b26,http://arxiv.org/abs/1108.4115v2
14697,"  The price of anarchy (PoA) has been widely used in static games to quantify
the loss of efficiency due to noncooperation. Here, we extend this concept to a
general differential games framework. In addition, we introduce the price of
information (PoI) to characterize comparative game performances under different
information structures, as well as the price of cooperation to capture the
extent of benefit or loss a player accrues as a result of altruistic behavior.
We further characterize PoA and PoI for a class of scalar linear quadratic
differential games under open-loop and closed-loop feedback information
structures. We also obtain some explicit bounds on these indices in a large
population regime.
",tamer basar,,2011.0,,arXiv,Basar2011,True,,arXiv,Not available,"Prices of Anarchy, Information, and Cooperation in Differential Games",b99994dc98f6268f776fd0f00d7a22f5,http://arxiv.org/abs/1103.2579v1
14698,"  We consider the well-studied game-theoretic version of machine scheduling in
which jobs correspond to self-interested users and machines correspond to
resources. Here each user chooses a machine trying to minimize her own cost,
and such selfish behavior typically results in some equilibrium which is not
globally optimal: An equilibrium is an allocation where no user can reduce her
own cost by moving to another machine, which in general need not minimize the
makespan, i.e., the maximum load over the machines.
  We provide tight bounds on two well-studied notions in algorithmic game
theory, namely, the price of anarchy and the strong price of anarchy on machine
scheduling setting which lies in between the related and the unrelated machine
case. Both notions study the social cost (makespan) of the worst equilibrium
compared to the optimum, with the strong price of anarchy restricting to a
stronger form of equilibria. Our results extend a prior study comparing the
price of anarchy to the strong price of anarchy for two related machines
(Epstein, Acta Informatica 2010), thus providing further insights on the
relation between these concepts. Our exact bounds give a qualitative and
quantitative comparison between the two models. The bounds also show that the
setting is indeed easier than the two unrelated machines: In the latter, the
strong price of anarchy is $2$, while in ours it is strictly smaller.
",yinfeng xu,,2017.0,,arXiv,Chen2017,True,,arXiv,Not available,"Selfish Jobs with Favorite Machines: Price of Anarchy vs Strong Price of
  Anarchy",2e346561b331f1e9787c035fd7877512,http://arxiv.org/abs/1709.06367v1
14699,"  The price of anarchy (PoA) has been widely used in static games to quantify
the loss of efficiency due to noncooperation. Here, we extend this concept to a
general differential games framework. In addition, we introduce the price of
information (PoI) to characterize comparative game performances under different
information structures, as well as the price of cooperation to capture the
extent of benefit or loss a player accrues as a result of altruistic behavior.
We further characterize PoA and PoI for a class of scalar linear quadratic
differential games under open-loop and closed-loop feedback information
structures. We also obtain some explicit bounds on these indices in a large
population regime.
",quanyan zhu,,2011.0,,arXiv,Basar2011,True,,arXiv,Not available,"Prices of Anarchy, Information, and Cooperation in Differential Games",b99994dc98f6268f776fd0f00d7a22f5,http://arxiv.org/abs/1103.2579v1
14700,"  We analyze the network congestion game with atomic players, asymmetric
strategies, and the maximum latency among all players as social cost. This
important social cost function is much less understood than the average
latency. We show that the price of anarchy is at most two, when the network is
a ring and the link latencies are linear. Our bound is tight. This is the first
sharp bound for the maximum latency objective.
",xujin chen,,2012.0,,arXiv,Chen2012,True,,arXiv,Not available,The Price of Anarchy for Selfish Ring Routing is Two,9d5d796d15264303550b419ebcd8d6e9,http://arxiv.org/abs/1210.0230v1
14701,"  We analyze the network congestion game with atomic players, asymmetric
strategies, and the maximum latency among all players as social cost. This
important social cost function is much less understood than the average
latency. We show that the price of anarchy is at most two, when the network is
a ring and the link latencies are linear. Our bound is tight. This is the first
sharp bound for the maximum latency objective.
",benjamin doerr,,2012.0,,arXiv,Chen2012,True,,arXiv,Not available,The Price of Anarchy for Selfish Ring Routing is Two,9d5d796d15264303550b419ebcd8d6e9,http://arxiv.org/abs/1210.0230v1
14702,"  We analyze the network congestion game with atomic players, asymmetric
strategies, and the maximum latency among all players as social cost. This
important social cost function is much less understood than the average
latency. We show that the price of anarchy is at most two, when the network is
a ring and the link latencies are linear. Our bound is tight. This is the first
sharp bound for the maximum latency objective.
",xiaodong hu,,2012.0,,arXiv,Chen2012,True,,arXiv,Not available,The Price of Anarchy for Selfish Ring Routing is Two,9d5d796d15264303550b419ebcd8d6e9,http://arxiv.org/abs/1210.0230v1
14703,"  We analyze the network congestion game with atomic players, asymmetric
strategies, and the maximum latency among all players as social cost. This
important social cost function is much less understood than the average
latency. We show that the price of anarchy is at most two, when the network is
a ring and the link latencies are linear. Our bound is tight. This is the first
sharp bound for the maximum latency objective.
",weidong ma,,2012.0,,arXiv,Chen2012,True,,arXiv,Not available,The Price of Anarchy for Selfish Ring Routing is Two,9d5d796d15264303550b419ebcd8d6e9,http://arxiv.org/abs/1210.0230v1
14704,"  We analyze the network congestion game with atomic players, asymmetric
strategies, and the maximum latency among all players as social cost. This
important social cost function is much less understood than the average
latency. We show that the price of anarchy is at most two, when the network is
a ring and the link latencies are linear. Our bound is tight. This is the first
sharp bound for the maximum latency objective.
",rob stee,,2012.0,,arXiv,Chen2012,True,,arXiv,Not available,The Price of Anarchy for Selfish Ring Routing is Two,9d5d796d15264303550b419ebcd8d6e9,http://arxiv.org/abs/1210.0230v1
14705,"  We analyze the network congestion game with atomic players, asymmetric
strategies, and the maximum latency among all players as social cost. This
important social cost function is much less understood than the average
latency. We show that the price of anarchy is at most two, when the network is
a ring and the link latencies are linear. Our bound is tight. This is the first
sharp bound for the maximum latency objective.
",carola winzen,,2012.0,,arXiv,Chen2012,True,,arXiv,Not available,The Price of Anarchy for Selfish Ring Routing is Two,9d5d796d15264303550b419ebcd8d6e9,http://arxiv.org/abs/1210.0230v1
14706,"  We consider a game-theoretical problem called selfish 2-dimensional bin
packing game, a generalization of the 1-dimensional case already treated in the
literature. In this game, the items to be packed are rectangles, and the bins
are unit squares. The game starts with a set of items arbitrarily packed in
bins. The cost of an item is defined as the ratio between its area and the
total occupied area of the respective bin. Each item is a selfish player that
wants to minimize its cost. A migration of an item to another bin is allowed
only when its cost is decreased. We show that this game always converges to a
Nash equilibrium (a stable packing where no single item can decrease its cost
by migrating to another bin). We show that the pure price of anarchy of this
game is unbounded, so we address the particular case where all items are
squares. We show that the pure price of anarchy of the selfish square packing
game is at least 2.3634 and at most 2.6875. We also present analogous results
for the strong Nash equilibrium (a stable packing where no nonempty set of
items can simultaneously migrate to another common bin and decrease the cost of
each item in the set). We show that the strong price of anarchy when all items
are squares is at least 2.0747 and at most 2.3605.
",cristina fernandes,,2017.0,,arXiv,Fernandes2017,True,,arXiv,Not available,Prices of anarchy of selfish 2D bin packing games,a08777f5569b5d925bc74a5b7e1ded65,http://arxiv.org/abs/1707.07882v1
14707,"  We consider a game-theoretical problem called selfish 2-dimensional bin
packing game, a generalization of the 1-dimensional case already treated in the
literature. In this game, the items to be packed are rectangles, and the bins
are unit squares. The game starts with a set of items arbitrarily packed in
bins. The cost of an item is defined as the ratio between its area and the
total occupied area of the respective bin. Each item is a selfish player that
wants to minimize its cost. A migration of an item to another bin is allowed
only when its cost is decreased. We show that this game always converges to a
Nash equilibrium (a stable packing where no single item can decrease its cost
by migrating to another bin). We show that the pure price of anarchy of this
game is unbounded, so we address the particular case where all items are
squares. We show that the pure price of anarchy of the selfish square packing
game is at least 2.3634 and at most 2.6875. We also present analogous results
for the strong Nash equilibrium (a stable packing where no nonempty set of
items can simultaneously migrate to another common bin and decrease the cost of
each item in the set). We show that the strong price of anarchy when all items
are squares is at least 2.0747 and at most 2.3605.
",carlos ferreira,,2017.0,,arXiv,Fernandes2017,True,,arXiv,Not available,Prices of anarchy of selfish 2D bin packing games,a08777f5569b5d925bc74a5b7e1ded65,http://arxiv.org/abs/1707.07882v1
14708,"  We consider a game-theoretical problem called selfish 2-dimensional bin
packing game, a generalization of the 1-dimensional case already treated in the
literature. In this game, the items to be packed are rectangles, and the bins
are unit squares. The game starts with a set of items arbitrarily packed in
bins. The cost of an item is defined as the ratio between its area and the
total occupied area of the respective bin. Each item is a selfish player that
wants to minimize its cost. A migration of an item to another bin is allowed
only when its cost is decreased. We show that this game always converges to a
Nash equilibrium (a stable packing where no single item can decrease its cost
by migrating to another bin). We show that the pure price of anarchy of this
game is unbounded, so we address the particular case where all items are
squares. We show that the pure price of anarchy of the selfish square packing
game is at least 2.3634 and at most 2.6875. We also present analogous results
for the strong Nash equilibrium (a stable packing where no nonempty set of
items can simultaneously migrate to another common bin and decrease the cost of
each item in the set). We show that the strong price of anarchy when all items
are squares is at least 2.0747 and at most 2.3605.
",flavio miyazawa,,2017.0,,arXiv,Fernandes2017,True,,arXiv,Not available,Prices of anarchy of selfish 2D bin packing games,a08777f5569b5d925bc74a5b7e1ded65,http://arxiv.org/abs/1707.07882v1
14709,"  We consider auctions in which greedy algorithms, paired with first-price or
critical-price payment rules, are used to resolve multi-parameter combinatorial
allocation problems. We study the price of anarchy for social welfare in such
auctions. We show for a variety of equilibrium concepts, including Bayes-Nash
equilibrium and correlated equilibrium, the resulting price of anarchy bound is
close to the approximation factor of the underlying greedy algorithm.
",brendan lucier,,2009.0,,arXiv,Lucier2009,True,,arXiv,Not available,Price of Anarchy for Greedy Auctions,def5707856fe837896222751ea1b7d1a,http://arxiv.org/abs/0909.0892v2
14710,"  We consider a game-theoretical problem called selfish 2-dimensional bin
packing game, a generalization of the 1-dimensional case already treated in the
literature. In this game, the items to be packed are rectangles, and the bins
are unit squares. The game starts with a set of items arbitrarily packed in
bins. The cost of an item is defined as the ratio between its area and the
total occupied area of the respective bin. Each item is a selfish player that
wants to minimize its cost. A migration of an item to another bin is allowed
only when its cost is decreased. We show that this game always converges to a
Nash equilibrium (a stable packing where no single item can decrease its cost
by migrating to another bin). We show that the pure price of anarchy of this
game is unbounded, so we address the particular case where all items are
squares. We show that the pure price of anarchy of the selfish square packing
game is at least 2.3634 and at most 2.6875. We also present analogous results
for the strong Nash equilibrium (a stable packing where no nonempty set of
items can simultaneously migrate to another common bin and decrease the cost of
each item in the set). We show that the strong price of anarchy when all items
are squares is at least 2.0747 and at most 2.3605.
",yoshiko wakabayashi,,2017.0,,arXiv,Fernandes2017,True,,arXiv,Not available,Prices of anarchy of selfish 2D bin packing games,a08777f5569b5d925bc74a5b7e1ded65,http://arxiv.org/abs/1707.07882v1
14711,"  We study the price of anarchy of mechanisms in the presence of risk-averse
agents. Previous work has focused on agents with quasilinear utilities,
possibly with a budget. Our model subsumes this as a special case but also
captures that agents might be less sensitive to payments than in the
risk-neutral model. We show that many positive price-of-anarchy results proved
in the smoothness framework continue to hold in the more general risk-averse
setting. A sufficient condition is that agents can never end up with negative
quasilinear utility after playing an undominated strategy. This is true, e.g.,
for first-price and second-price auctions. For all-pay auctions, similar
results do not hold: We show that there are Bayes-Nash equilibria with
arbitrarily bad social welfare compared to the optimum.
",thomas kesselheim,,2018.0,,arXiv,Kesselheim2018,True,,arXiv,Not available,Price of Anarchy for Mechanisms with Risk-Averse Agents,ad484a322aaaa22a7888e231d66590dc,http://arxiv.org/abs/1804.09468v1
14712,"  We study the price of anarchy of mechanisms in the presence of risk-averse
agents. Previous work has focused on agents with quasilinear utilities,
possibly with a budget. Our model subsumes this as a special case but also
captures that agents might be less sensitive to payments than in the
risk-neutral model. We show that many positive price-of-anarchy results proved
in the smoothness framework continue to hold in the more general risk-averse
setting. A sufficient condition is that agents can never end up with negative
quasilinear utility after playing an undominated strategy. This is true, e.g.,
for first-price and second-price auctions. For all-pay auctions, similar
results do not hold: We show that there are Bayes-Nash equilibria with
arbitrarily bad social welfare compared to the optimum.
",bojana kodric,,2018.0,,arXiv,Kesselheim2018,True,,arXiv,Not available,Price of Anarchy for Mechanisms with Risk-Averse Agents,ad484a322aaaa22a7888e231d66590dc,http://arxiv.org/abs/1804.09468v1
14713,"  This paper develops tools for welfare and revenue analyses of Bayes-Nash
equilibria in asymmetric auctions with single-dimensional agents. We employ
these tools to derive price of anarchy results for social welfare and revenue.
Our approach separates the standard smoothness framework into two distinct
parts, isolating the analysis common to any auction from the analysis specific
to a given auction. The first part relates a bidder's contribution to welfare
in equilibrium to their contribution to welfare in the optimal auction using
the price the bidder faces for additional allocation. Intuitively, either an
agent's utility and hence contribution to welfare is high, or the price she has
to pay for additional allocation is high relative to her value. We call this
condition value covering; it holds in every Bayes-Nash equilibrium of any
auction. The second part, revenue covering, relates the prices bidders face for
additional allocation to the revenue of the auction, using an auction's rules
and feasibility constraints. Combining the two parts gives approximation
results to the optimal welfare, and, under the right conditions, the optimal
revenue. In mechanisms with reserve prices, our welfare results show
approximation with respect to the optimal mechanism with the same reserves.
  As a center-piece result, we analyze the single-item first-price auction with
individual monopoly reserves. When each distribution satisfies a regularity
condition the auction's revenue is at least a $2e/(e-1) \approx 3.16$
approximation to the revenue of the optimal auction. We also give bounds for
matroid auctions with first-price or all-pay semantics, and the generalized
first-price position auction. Finally, we give an extension theorem for
simultaneous composition, i.e., when multiple auctions are run simultaneously,
with single-valued, unit-demand agents.
",jason hartline,,2014.0,,arXiv,Hartline2014,True,,arXiv,Not available,Price of Anarchy for Auction Revenue,6b23ba5b6289ca042dfc4c540eec947f,http://arxiv.org/abs/1404.5943v4
14714,"  This paper develops tools for welfare and revenue analyses of Bayes-Nash
equilibria in asymmetric auctions with single-dimensional agents. We employ
these tools to derive price of anarchy results for social welfare and revenue.
Our approach separates the standard smoothness framework into two distinct
parts, isolating the analysis common to any auction from the analysis specific
to a given auction. The first part relates a bidder's contribution to welfare
in equilibrium to their contribution to welfare in the optimal auction using
the price the bidder faces for additional allocation. Intuitively, either an
agent's utility and hence contribution to welfare is high, or the price she has
to pay for additional allocation is high relative to her value. We call this
condition value covering; it holds in every Bayes-Nash equilibrium of any
auction. The second part, revenue covering, relates the prices bidders face for
additional allocation to the revenue of the auction, using an auction's rules
and feasibility constraints. Combining the two parts gives approximation
results to the optimal welfare, and, under the right conditions, the optimal
revenue. In mechanisms with reserve prices, our welfare results show
approximation with respect to the optimal mechanism with the same reserves.
  As a center-piece result, we analyze the single-item first-price auction with
individual monopoly reserves. When each distribution satisfies a regularity
condition the auction's revenue is at least a $2e/(e-1) \approx 3.16$
approximation to the revenue of the optimal auction. We also give bounds for
matroid auctions with first-price or all-pay semantics, and the generalized
first-price position auction. Finally, we give an extension theorem for
simultaneous composition, i.e., when multiple auctions are run simultaneously,
with single-valued, unit-demand agents.
",darrell hoy,,2014.0,,arXiv,Hartline2014,True,,arXiv,Not available,Price of Anarchy for Auction Revenue,6b23ba5b6289ca042dfc4c540eec947f,http://arxiv.org/abs/1404.5943v4
14715,"  This paper develops tools for welfare and revenue analyses of Bayes-Nash
equilibria in asymmetric auctions with single-dimensional agents. We employ
these tools to derive price of anarchy results for social welfare and revenue.
Our approach separates the standard smoothness framework into two distinct
parts, isolating the analysis common to any auction from the analysis specific
to a given auction. The first part relates a bidder's contribution to welfare
in equilibrium to their contribution to welfare in the optimal auction using
the price the bidder faces for additional allocation. Intuitively, either an
agent's utility and hence contribution to welfare is high, or the price she has
to pay for additional allocation is high relative to her value. We call this
condition value covering; it holds in every Bayes-Nash equilibrium of any
auction. The second part, revenue covering, relates the prices bidders face for
additional allocation to the revenue of the auction, using an auction's rules
and feasibility constraints. Combining the two parts gives approximation
results to the optimal welfare, and, under the right conditions, the optimal
revenue. In mechanisms with reserve prices, our welfare results show
approximation with respect to the optimal mechanism with the same reserves.
  As a center-piece result, we analyze the single-item first-price auction with
individual monopoly reserves. When each distribution satisfies a regularity
condition the auction's revenue is at least a $2e/(e-1) \approx 3.16$
approximation to the revenue of the optimal auction. We also give bounds for
matroid auctions with first-price or all-pay semantics, and the generalized
first-price position auction. Finally, we give an extension theorem for
simultaneous composition, i.e., when multiple auctions are run simultaneously,
with single-valued, unit-demand agents.
",sam taggart,,2014.0,,arXiv,Hartline2014,True,,arXiv,Not available,Price of Anarchy for Auction Revenue,6b23ba5b6289ca042dfc4c540eec947f,http://arxiv.org/abs/1404.5943v4
14716,"  We study the price of anarchy in a class of graph coloring games (a subclass
of polymatrix common-payoff games). In those games, players are vertices of an
undirected, simple graph, and the strategy space of each player is the set of
colors from $1$ to $k$. A tight bound on the price of anarchy of
$\frac{k}{k-1}$ is known (Hoefer 2007, Kun et al. 2013), for the case that each
player's payoff is the number of her neighbors with different color than
herself. The study of more complex payoff functions was left as an open
problem.
  We compute payoff for a player by determining the distance of her color to
the color of each of her neighbors, applying a non-negative, real-valued,
concave function $f$ to each of those distances, and then summing up the
resulting values. This includes the payoff functions suggested by Kun et al.
(2013) for future work as special cases.
  Denote $f^*$ the maximum value that $f$ attains on the possible distances
$0,\dots,k-1$. We prove an upper bound of $2$ on the price of anarchy for
concave functions $f$ that are non-decreasing or which assume $f^*$ at a
distance on or below $\lfloor\frac{k}{2}\rfloor$. Matching lower bounds are
given for the monotone case and for the case that $f^*$ is assumed in
$\frac{k}{2}$ for even $k$. For general concave functions, we prove an upper
bound of $3$. We use a simple but powerful technique: we obtain an upper bound
of $\lambda \geq 1$ on the price of anarchy if we manage to give a splitting
$\lambda_1 + \dots + \lambda_k = \lambda$ such that $\sum_{s=1}^k \lambda_s
\cdot f(|s-p|) \geq f^*$ for all $p \in \{1,\dots,k\}$. The discovery of
working splittings can be supported by computer experiments. We show how, once
we have an idea what kind of splittings work, this technique helps in giving
simple proofs, which mainly work by case distinctions, algebraic manipulations,
and real calculus.
",lasse kliemann,,2015.0,,arXiv,Kliemann2015,True,,arXiv,Not available,Price of Anarchy for Graph Coloring Games with Concave Payoff,99769338b155748b29edbae1e37b760b,http://arxiv.org/abs/1507.08249v2
14717,"  We study the price of anarchy in a class of graph coloring games (a subclass
of polymatrix common-payoff games). In those games, players are vertices of an
undirected, simple graph, and the strategy space of each player is the set of
colors from $1$ to $k$. A tight bound on the price of anarchy of
$\frac{k}{k-1}$ is known (Hoefer 2007, Kun et al. 2013), for the case that each
player's payoff is the number of her neighbors with different color than
herself. The study of more complex payoff functions was left as an open
problem.
  We compute payoff for a player by determining the distance of her color to
the color of each of her neighbors, applying a non-negative, real-valued,
concave function $f$ to each of those distances, and then summing up the
resulting values. This includes the payoff functions suggested by Kun et al.
(2013) for future work as special cases.
  Denote $f^*$ the maximum value that $f$ attains on the possible distances
$0,\dots,k-1$. We prove an upper bound of $2$ on the price of anarchy for
concave functions $f$ that are non-decreasing or which assume $f^*$ at a
distance on or below $\lfloor\frac{k}{2}\rfloor$. Matching lower bounds are
given for the monotone case and for the case that $f^*$ is assumed in
$\frac{k}{2}$ for even $k$. For general concave functions, we prove an upper
bound of $3$. We use a simple but powerful technique: we obtain an upper bound
of $\lambda \geq 1$ on the price of anarchy if we manage to give a splitting
$\lambda_1 + \dots + \lambda_k = \lambda$ such that $\sum_{s=1}^k \lambda_s
\cdot f(|s-p|) \geq f^*$ for all $p \in \{1,\dots,k\}$. The discovery of
working splittings can be supported by computer experiments. We show how, once
we have an idea what kind of splittings work, this technique helps in giving
simple proofs, which mainly work by case distinctions, algebraic manipulations,
and real calculus.
",elmira sheykhdarabadi,,2015.0,,arXiv,Kliemann2015,True,,arXiv,Not available,Price of Anarchy for Graph Coloring Games with Concave Payoff,99769338b155748b29edbae1e37b760b,http://arxiv.org/abs/1507.08249v2
14718,"  We study the price of anarchy in a class of graph coloring games (a subclass
of polymatrix common-payoff games). In those games, players are vertices of an
undirected, simple graph, and the strategy space of each player is the set of
colors from $1$ to $k$. A tight bound on the price of anarchy of
$\frac{k}{k-1}$ is known (Hoefer 2007, Kun et al. 2013), for the case that each
player's payoff is the number of her neighbors with different color than
herself. The study of more complex payoff functions was left as an open
problem.
  We compute payoff for a player by determining the distance of her color to
the color of each of her neighbors, applying a non-negative, real-valued,
concave function $f$ to each of those distances, and then summing up the
resulting values. This includes the payoff functions suggested by Kun et al.
(2013) for future work as special cases.
  Denote $f^*$ the maximum value that $f$ attains on the possible distances
$0,\dots,k-1$. We prove an upper bound of $2$ on the price of anarchy for
concave functions $f$ that are non-decreasing or which assume $f^*$ at a
distance on or below $\lfloor\frac{k}{2}\rfloor$. Matching lower bounds are
given for the monotone case and for the case that $f^*$ is assumed in
$\frac{k}{2}$ for even $k$. For general concave functions, we prove an upper
bound of $3$. We use a simple but powerful technique: we obtain an upper bound
of $\lambda \geq 1$ on the price of anarchy if we manage to give a splitting
$\lambda_1 + \dots + \lambda_k = \lambda$ such that $\sum_{s=1}^k \lambda_s
\cdot f(|s-p|) \geq f^*$ for all $p \in \{1,\dots,k\}$. The discovery of
working splittings can be supported by computer experiments. We show how, once
we have an idea what kind of splittings work, this technique helps in giving
simple proofs, which mainly work by case distinctions, algebraic manipulations,
and real calculus.
",anand srivastav,,2015.0,,arXiv,Kliemann2015,True,,arXiv,Not available,Price of Anarchy for Graph Coloring Games with Concave Payoff,99769338b155748b29edbae1e37b760b,http://arxiv.org/abs/1507.08249v2
14719,"  This survey outlines a general and modular theory for proving approximation
guarantees for equilibria of auctions in complex settings. This theory
complements traditional economic techniques, which generally focus on exact and
optimal solutions and are accordingly limited to relatively stylized settings.
  We highlight three user-friendly analytical tools: smoothness-type
inequalities, which immediately yield approximation guarantees for many auction
formats of interest in the special case of complete information and
deterministic strategies; extension theorems, which extend such guarantees to
randomized strategies, no-regret learning outcomes, and incomplete-information
settings; and composition theorems, which extend such guarantees from simpler
to more complex auctions. Combining these tools yields tight worst-case
approximation guarantees for the equilibria of many widely-used auction
formats.
",tim roughgarden,,2016.0,,arXiv,Roughgarden2016,True,,arXiv,Not available,The Price of Anarchy in Auctions,b50c6b44abd49fbc9c5119dfbcf531c4,http://arxiv.org/abs/1607.07684v1
14720,"  We consider auctions in which greedy algorithms, paired with first-price or
critical-price payment rules, are used to resolve multi-parameter combinatorial
allocation problems. We study the price of anarchy for social welfare in such
auctions. We show for a variety of equilibrium concepts, including Bayes-Nash
equilibrium and correlated equilibrium, the resulting price of anarchy bound is
close to the approximation factor of the underlying greedy algorithm.
",allan borodin,,2009.0,,arXiv,Lucier2009,True,,arXiv,Not available,Price of Anarchy for Greedy Auctions,def5707856fe837896222751ea1b7d1a,http://arxiv.org/abs/0909.0892v2
14721,"  This survey outlines a general and modular theory for proving approximation
guarantees for equilibria of auctions in complex settings. This theory
complements traditional economic techniques, which generally focus on exact and
optimal solutions and are accordingly limited to relatively stylized settings.
  We highlight three user-friendly analytical tools: smoothness-type
inequalities, which immediately yield approximation guarantees for many auction
formats of interest in the special case of complete information and
deterministic strategies; extension theorems, which extend such guarantees to
randomized strategies, no-regret learning outcomes, and incomplete-information
settings; and composition theorems, which extend such guarantees from simpler
to more complex auctions. Combining these tools yields tight worst-case
approximation guarantees for the equilibria of many widely-used auction
formats.
",vasilis syrgkanis,,2016.0,,arXiv,Roughgarden2016,True,,arXiv,Not available,The Price of Anarchy in Auctions,b50c6b44abd49fbc9c5119dfbcf531c4,http://arxiv.org/abs/1607.07684v1
14722,"  This survey outlines a general and modular theory for proving approximation
guarantees for equilibria of auctions in complex settings. This theory
complements traditional economic techniques, which generally focus on exact and
optimal solutions and are accordingly limited to relatively stylized settings.
  We highlight three user-friendly analytical tools: smoothness-type
inequalities, which immediately yield approximation guarantees for many auction
formats of interest in the special case of complete information and
deterministic strategies; extension theorems, which extend such guarantees to
randomized strategies, no-regret learning outcomes, and incomplete-information
settings; and composition theorems, which extend such guarantees from simpler
to more complex auctions. Combining these tools yields tight worst-case
approximation guarantees for the equilibria of many widely-used auction
formats.
",eva tardos,,2016.0,,arXiv,Roughgarden2016,True,,arXiv,Not available,The Price of Anarchy in Auctions,b50c6b44abd49fbc9c5119dfbcf531c4,http://arxiv.org/abs/1607.07684v1
14723,"  One of the main results shown through Roughgarden's notions of smooth games
and robust price of anarchy is that, for any sum-bounded utilitarian social
function, the worst-case price of anarchy of coarse correlated equilibria
coincides with that of pure Nash equilibria in the class of weighted congestion
games with non-negative and non-decreasing latency functions and that such a
value can always be derived through the, so called, smoothness argument. We
significantly extend this result by proving that, for a variety of (even
non-sum-bounded) utilitarian and egalitarian social functions and for a broad
generalization of the class of weighted congestion games with non-negative (and
possibly decreasing) latency functions, the worst-case price of anarchy of
$\epsilon$-approximate coarse correlated equilibria still coincides with that
of $\epsilon$-approximate pure Nash equilibria, for any $\epsilon\geq 0$. As a
byproduct of our proof, it also follows that such a value can always be
determined by making use of the primal-dual method we introduced in a previous
work. It is important to note that our scenario of investigation is beyond the
scope of application of the robust price of anarchy (for as it is currently
defined), so that our result seems unlikely to be alternatively proved via the
smoothness framework.
",vittorio bilo,,2014.0,,arXiv,Bilò2014,True,,arXiv,Not available,"On the Robustness of the Approximate Price of Anarchy in Generalized
  Congestion Games",b3824cf34c3bebf933438e9bfca9df90,http://arxiv.org/abs/1412.0845v1
14724,"  In opinion formation games with directed graphs, a bounded price of anarchy
is only known for weighted Eulerian graphs. Thus, we bound the price of anarchy
for a more general class of directed graphs with conditions intuitively meaning
that each node does not influence the others more than she is influenced, where
the bounds depend on such difference (in a ratio). We also show that there
exists an example just slightly violating the conditions with an unbounded
price of anarchy.
",po-an chen,,2016.0,,arXiv,Chen2016,True,,arXiv,Not available,"Bounds on the Price of Anarchy for a More General Class of Directed
  Graphs in Opinion Formation Games",71498db9becfc458fbea1323a91a1554,http://arxiv.org/abs/1602.02527v2
14725,"  In opinion formation games with directed graphs, a bounded price of anarchy
is only known for weighted Eulerian graphs. Thus, we bound the price of anarchy
for a more general class of directed graphs with conditions intuitively meaning
that each node does not influence the others more than she is influenced, where
the bounds depend on such difference (in a ratio). We also show that there
exists an example just slightly violating the conditions with an unbounded
price of anarchy.
",yi-le chen,,2016.0,,arXiv,Chen2016,True,,arXiv,Not available,"Bounds on the Price of Anarchy for a More General Class of Directed
  Graphs in Opinion Formation Games",71498db9becfc458fbea1323a91a1554,http://arxiv.org/abs/1602.02527v2
14726,"  In opinion formation games with directed graphs, a bounded price of anarchy
is only known for weighted Eulerian graphs. Thus, we bound the price of anarchy
for a more general class of directed graphs with conditions intuitively meaning
that each node does not influence the others more than she is influenced, where
the bounds depend on such difference (in a ratio). We also show that there
exists an example just slightly violating the conditions with an unbounded
price of anarchy.
",chi-jen lu,,2016.0,,arXiv,Chen2016,True,,arXiv,Not available,"Bounds on the Price of Anarchy for a More General Class of Directed
  Graphs in Opinion Formation Games",71498db9becfc458fbea1323a91a1554,http://arxiv.org/abs/1602.02527v2
14727,"  We study {\em bottleneck routing games} where the social cost is determined
by the worst congestion on any edge in the network. In the literature,
bottleneck games assume player utility costs determined by the worst congested
edge in their paths. However, the Nash equilibria of such games are inefficient
since the price of anarchy can be very high and proportional to the size of the
network. In order to obtain smaller price of anarchy we introduce {\em
exponential bottleneck games} where the utility costs of the players are
exponential functions of their congestions. We find that exponential bottleneck
games are very efficient and give a poly-log bound on the price of anarchy:
$O(\log L \cdot \log |E|)$, where $L$ is the largest path length in the
players' strategy sets and $E$ is the set of edges in the graph. By adjusting
the exponential utility costs with a logarithm we obtain games whose player
costs are almost identical to those in regular bottleneck games, and at the
same time have the good price of anarchy of exponential games.
",rajgopal kannan,,2010.0,10.1007/978-3-642-16170-4_20,arXiv,Kannan2010,True,,arXiv,Not available,Bottleneck Routing Games with Low Price of Anarchy,9e3676835c35143114e69790cc570af5,http://arxiv.org/abs/1003.4307v1
14728,"  The Generalized Second Price auction (GSP) has been widely used by search
engines to sell ad slots. Previous studies have shown that the pure Price Of
Anarchy (POA) of GSP is 1.25 when there are two ad slots and 1.259 when three
ad slots. For the cases with more than three ad slots, however, only some
untight upper bounds of the pure POA were obtained. In this work, we improve
previous results in two aspects: (1) We prove that the pure POA for GSP is
1.259 when there are four ad slots, and (2) We show that the pure POA for GSP
with more than four ad slots is also 1.259 given the bidders are ranked
according to a particular permutation.
",wenkui ding,,2013.0,,arXiv,Ding2013,True,,arXiv,Not available,Pure Price of Anarchy for Generalized Second Price Auction,888d14a291ca172734368475b7e23927,http://arxiv.org/abs/1305.5404v1
14729,"  We study {\em bottleneck routing games} where the social cost is determined
by the worst congestion on any edge in the network. In the literature,
bottleneck games assume player utility costs determined by the worst congested
edge in their paths. However, the Nash equilibria of such games are inefficient
since the price of anarchy can be very high and proportional to the size of the
network. In order to obtain smaller price of anarchy we introduce {\em
exponential bottleneck games} where the utility costs of the players are
exponential functions of their congestions. We find that exponential bottleneck
games are very efficient and give a poly-log bound on the price of anarchy:
$O(\log L \cdot \log |E|)$, where $L$ is the largest path length in the
players' strategy sets and $E$ is the set of edges in the graph. By adjusting
the exponential utility costs with a logarithm we obtain games whose player
costs are almost identical to those in regular bottleneck games, and at the
same time have the good price of anarchy of exponential games.
",costas busch,,2010.0,10.1007/978-3-642-16170-4_20,arXiv,Kannan2010,True,,arXiv,Not available,Bottleneck Routing Games with Low Price of Anarchy,9e3676835c35143114e69790cc570af5,http://arxiv.org/abs/1003.4307v1
14730,"  We study routing behavior in transportation networks with mixed autonomy,
that is, networks in which a fraction of the vehicles on each road are equipped
with autonomous capabilities such as adaptive cruise control that enable
reduced headways and increased road capacity. Motivated by capacity models
developed for such roads with mixed autonomy, we consider transportation
networks in which the delay on each road or link is an affine function of two
quantities: the number of vehicles with autonomous capabilities on the link and
the number of regular vehicles on the link. We particularly study the price of
anarchy for such networks, that is, the ratio of the total delay experienced by
selfish routing to the socially optimal routing policy. Unlike the case when
all vehicles are of the same type, for which the price of anarchy is known to
be bounded, we first show that the price of anarchy can be arbitrarily large
for such mixed autonomous networks. Next, we define a notion of asymmetry equal
to the maximum possible travel time improvement due to the presence of
autonomous vehicles. We show that when the degree of asymmetry of all links in
the network is bounded by a factor less than 4, the price of anarchy is
bounded. We also bound the bicriteria, which is a bound on the cost of
selfishly routing traffic compared to the cost of optimally routing additional
traffic. These bounds depend on the degree of asymmetry and recover classical
bounds on the price of anarchy and bicriteria in the case when no asymmetry
exists. Further, we show with examples that these bound are tight in particular
cases.
",daniel lazar,,2017.0,,arXiv,Lazar2017,True,,arXiv,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy,77131436034b7eb15cda554fd65c5bbc,http://arxiv.org/abs/1710.07867v1
14731,"  We study routing behavior in transportation networks with mixed autonomy,
that is, networks in which a fraction of the vehicles on each road are equipped
with autonomous capabilities such as adaptive cruise control that enable
reduced headways and increased road capacity. Motivated by capacity models
developed for such roads with mixed autonomy, we consider transportation
networks in which the delay on each road or link is an affine function of two
quantities: the number of vehicles with autonomous capabilities on the link and
the number of regular vehicles on the link. We particularly study the price of
anarchy for such networks, that is, the ratio of the total delay experienced by
selfish routing to the socially optimal routing policy. Unlike the case when
all vehicles are of the same type, for which the price of anarchy is known to
be bounded, we first show that the price of anarchy can be arbitrarily large
for such mixed autonomous networks. Next, we define a notion of asymmetry equal
to the maximum possible travel time improvement due to the presence of
autonomous vehicles. We show that when the degree of asymmetry of all links in
the network is bounded by a factor less than 4, the price of anarchy is
bounded. We also bound the bicriteria, which is a bound on the cost of
selfishly routing traffic compared to the cost of optimally routing additional
traffic. These bounds depend on the degree of asymmetry and recover classical
bounds on the price of anarchy and bicriteria in the case when no asymmetry
exists. Further, we show with examples that these bound are tight in particular
cases.
",samuel coogan,,2017.0,,arXiv,Lazar2017,True,,arXiv,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy,77131436034b7eb15cda554fd65c5bbc,http://arxiv.org/abs/1710.07867v1
14732,"  We study routing behavior in transportation networks with mixed autonomy,
that is, networks in which a fraction of the vehicles on each road are equipped
with autonomous capabilities such as adaptive cruise control that enable
reduced headways and increased road capacity. Motivated by capacity models
developed for such roads with mixed autonomy, we consider transportation
networks in which the delay on each road or link is an affine function of two
quantities: the number of vehicles with autonomous capabilities on the link and
the number of regular vehicles on the link. We particularly study the price of
anarchy for such networks, that is, the ratio of the total delay experienced by
selfish routing to the socially optimal routing policy. Unlike the case when
all vehicles are of the same type, for which the price of anarchy is known to
be bounded, we first show that the price of anarchy can be arbitrarily large
for such mixed autonomous networks. Next, we define a notion of asymmetry equal
to the maximum possible travel time improvement due to the presence of
autonomous vehicles. We show that when the degree of asymmetry of all links in
the network is bounded by a factor less than 4, the price of anarchy is
bounded. We also bound the bicriteria, which is a bound on the cost of
selfishly routing traffic compared to the cost of optimally routing additional
traffic. These bounds depend on the degree of asymmetry and recover classical
bounds on the price of anarchy and bicriteria in the case when no asymmetry
exists. Further, we show with examples that these bound are tight in particular
cases.
",ramtin pedarsani,,2017.0,,arXiv,Lazar2017,True,,arXiv,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy,77131436034b7eb15cda554fd65c5bbc,http://arxiv.org/abs/1710.07867v1
14733,"  We analyze the setting of minimum-cost perfect matchings with selfish
vertices through the price of anarchy (PoA) and price of stability (PoS) lens.
The underlying solution concept used for this analysis is the Gale-Shapley
stable matching notion, where the preferences are determined so that each
player (vertex) wishes to minimize the cost of her own matching edge.
",yuval emek,,2011.0,,arXiv,Emek2011,True,,arXiv,Not available,The Price of Matching Selfish Vertices,6f1b35d200042f2710cdb9fe93ef905b,http://arxiv.org/abs/1112.4632v4
14734,"  We analyze the setting of minimum-cost perfect matchings with selfish
vertices through the price of anarchy (PoA) and price of stability (PoS) lens.
The underlying solution concept used for this analysis is the Gale-Shapley
stable matching notion, where the preferences are determined so that each
player (vertex) wishes to minimize the cost of her own matching edge.
",tobias langner,,2011.0,,arXiv,Emek2011,True,,arXiv,Not available,The Price of Matching Selfish Vertices,6f1b35d200042f2710cdb9fe93ef905b,http://arxiv.org/abs/1112.4632v4
14735,"  We analyze the setting of minimum-cost perfect matchings with selfish
vertices through the price of anarchy (PoA) and price of stability (PoS) lens.
The underlying solution concept used for this analysis is the Gale-Shapley
stable matching notion, where the preferences are determined so that each
player (vertex) wishes to minimize the cost of her own matching edge.
",roger wattenhofer,,2011.0,,arXiv,Emek2011,True,,arXiv,Not available,The Price of Matching Selfish Vertices,6f1b35d200042f2710cdb9fe93ef905b,http://arxiv.org/abs/1112.4632v4
14736,"  Optimizing the performance of a basketball offense may be viewed as a network
problem, wherein each play represents a ""pathway"" through which the ball and
players may move from origin (the in-bounds pass) to goal (the basket).
Effective field goal percentages from the resulting shot attempts can be used
to characterize the efficiency of each pathway. Inspired by recent discussions
of the ""price of anarchy"" in traffic networks, this paper makes a formal
analogy between a basketball offense and a simplified traffic network. The
analysis suggests that there may be a significant difference between taking the
highest-percentage shot each time down the court and playing the most efficient
possible game. There may also be an analogue of Braess's Paradox in basketball,
such that removing a key player from a team can result in the improvement of
the team's offensive efficiency.
",brian skinner,,2009.0,10.2202/1559-0410.1217,"Journal of Quantitative Analysis in Sports 6(1), 3 (2010)",Skinner2009,True,,arXiv,Not available,The price of anarchy in basketball,869e6a8adb75ca574a7a064c6e72d659,http://arxiv.org/abs/0908.1801v4
14737,"  We present a new class of vertex cover and set cover games. The price of
anarchy bounds match the best known constant factor approximation guarantees
for the centralized optimization problems for linear and also for submodular
costs -- in contrast to all previously studied covering games, where the price
of anarchy cannot be bounded by a constant (e.g. [6, 7, 11, 5, 2]). In
particular, we describe a vertex cover game with a price of anarchy of 2. The
rules of the games capture the structure of the linear programming relaxations
of the underlying optimization problems, and our bounds are established by
analyzing these relaxations. Furthermore, for linear costs we exhibit linear
time best response dynamics that converge to these almost optimal Nash
equilibria. These dynamics mimic the classical greedy approximation algorithm
of Bar-Yehuda and Even [3].
",georgios piliouras,,2012.0,,arXiv,Piliouras2012,True,,arXiv,Not available,LP-based Covering Games with Low Price of Anarchy,bfe323321ed7081918544235a10439a8,http://arxiv.org/abs/1203.0050v1
14738,"  We present a new class of vertex cover and set cover games. The price of
anarchy bounds match the best known constant factor approximation guarantees
for the centralized optimization problems for linear and also for submodular
costs -- in contrast to all previously studied covering games, where the price
of anarchy cannot be bounded by a constant (e.g. [6, 7, 11, 5, 2]). In
particular, we describe a vertex cover game with a price of anarchy of 2. The
rules of the games capture the structure of the linear programming relaxations
of the underlying optimization problems, and our bounds are established by
analyzing these relaxations. Furthermore, for linear costs we exhibit linear
time best response dynamics that converge to these almost optimal Nash
equilibria. These dynamics mimic the classical greedy approximation algorithm
of Bar-Yehuda and Even [3].
",tomas valla,,2012.0,,arXiv,Piliouras2012,True,,arXiv,Not available,LP-based Covering Games with Low Price of Anarchy,bfe323321ed7081918544235a10439a8,http://arxiv.org/abs/1203.0050v1
14739,"  The Generalized Second Price auction (GSP) has been widely used by search
engines to sell ad slots. Previous studies have shown that the pure Price Of
Anarchy (POA) of GSP is 1.25 when there are two ad slots and 1.259 when three
ad slots. For the cases with more than three ad slots, however, only some
untight upper bounds of the pure POA were obtained. In this work, we improve
previous results in two aspects: (1) We prove that the pure POA for GSP is
1.259 when there are four ad slots, and (2) We show that the pure POA for GSP
with more than four ad slots is also 1.259 given the bidders are ranked
according to a particular permutation.
",tao wu,,2013.0,,arXiv,Ding2013,True,,arXiv,Not available,Pure Price of Anarchy for Generalized Second Price Auction,888d14a291ca172734368475b7e23927,http://arxiv.org/abs/1305.5404v1
14740,"  We present a new class of vertex cover and set cover games. The price of
anarchy bounds match the best known constant factor approximation guarantees
for the centralized optimization problems for linear and also for submodular
costs -- in contrast to all previously studied covering games, where the price
of anarchy cannot be bounded by a constant (e.g. [6, 7, 11, 5, 2]). In
particular, we describe a vertex cover game with a price of anarchy of 2. The
rules of the games capture the structure of the linear programming relaxations
of the underlying optimization problems, and our bounds are established by
analyzing these relaxations. Furthermore, for linear costs we exhibit linear
time best response dynamics that converge to these almost optimal Nash
equilibria. These dynamics mimic the classical greedy approximation algorithm
of Bar-Yehuda and Even [3].
",laszlo vegh,,2012.0,,arXiv,Piliouras2012,True,,arXiv,Not available,LP-based Covering Games with Low Price of Anarchy,bfe323321ed7081918544235a10439a8,http://arxiv.org/abs/1203.0050v1
14741,"  We study {\em bottleneck congestion games} where the social cost is
determined by the worst congestion of any resource. These games directly relate
to network routing problems and also job-shop scheduling problems. In typical
bottleneck congestion games, the utility costs of the players are determined by
the worst congested resources that they use. However, the resulting Nash
equilibria are inefficient, since the price of anarchy is proportional on the
number of resources which can be high. Here we show that we can get smaller
price of anarchy with the bottleneck social cost metric. We introduce the {\em
polynomial bottleneck games} where the utility costs of the players are
polynomial functions of the congestion of the resources that they use. In
particular, the delay function for any resource $r$ is $C_{r}^\M$, where $C_r$
is the congestion measured as the number of players that use $r$, and $\M \geq
1$ is an integer constant that defines the degree of the polynomial. The
utility cost of a player is the sum of the individual delays of the resources
that it uses. The social cost of the game remains the same, namely, it is the
worst bottleneck resource congestion: $\max_{r} C_r$. We show that polynomial
bottleneck games are very efficient and give price of anarchy
$O(|R|^{1/(\M+1)})$, where $R$ is the set of resources. This price of anarchy
is tight, since we demonstrate a game with price of anarchy
$\Omega(|R|^{1/(\M+1)})$, for any $\M \geq 1$. We obtain our tight bounds by
using two proof techniques: {\em transformation}, which we use to convert
arbitrary games to simpler games, and {\em expansion}, which we use to bound
the price of anarchy in a simpler game.
",rajgopal kannan,,2010.0,,arXiv,Kannan2010,True,,arXiv,Not available,Polynomial Bottleneck Congestion Games with Optimal Price of Anarchy,1abcadede6a3253a6cc12bedfe8712f1,http://arxiv.org/abs/1010.4812v1
14742,"  We study {\em bottleneck congestion games} where the social cost is
determined by the worst congestion of any resource. These games directly relate
to network routing problems and also job-shop scheduling problems. In typical
bottleneck congestion games, the utility costs of the players are determined by
the worst congested resources that they use. However, the resulting Nash
equilibria are inefficient, since the price of anarchy is proportional on the
number of resources which can be high. Here we show that we can get smaller
price of anarchy with the bottleneck social cost metric. We introduce the {\em
polynomial bottleneck games} where the utility costs of the players are
polynomial functions of the congestion of the resources that they use. In
particular, the delay function for any resource $r$ is $C_{r}^\M$, where $C_r$
is the congestion measured as the number of players that use $r$, and $\M \geq
1$ is an integer constant that defines the degree of the polynomial. The
utility cost of a player is the sum of the individual delays of the resources
that it uses. The social cost of the game remains the same, namely, it is the
worst bottleneck resource congestion: $\max_{r} C_r$. We show that polynomial
bottleneck games are very efficient and give price of anarchy
$O(|R|^{1/(\M+1)})$, where $R$ is the set of resources. This price of anarchy
is tight, since we demonstrate a game with price of anarchy
$\Omega(|R|^{1/(\M+1)})$, for any $\M \geq 1$. We obtain our tight bounds by
using two proof techniques: {\em transformation}, which we use to convert
arbitrary games to simpler games, and {\em expansion}, which we use to bound
the price of anarchy in a simpler game.
",costas busch,,2010.0,,arXiv,Kannan2010,True,,arXiv,Not available,Polynomial Bottleneck Congestion Games with Optimal Price of Anarchy,1abcadede6a3253a6cc12bedfe8712f1,http://arxiv.org/abs/1010.4812v1
14743,"  We study {\em bottleneck congestion games} where the social cost is
determined by the worst congestion of any resource. These games directly relate
to network routing problems and also job-shop scheduling problems. In typical
bottleneck congestion games, the utility costs of the players are determined by
the worst congested resources that they use. However, the resulting Nash
equilibria are inefficient, since the price of anarchy is proportional on the
number of resources which can be high. Here we show that we can get smaller
price of anarchy with the bottleneck social cost metric. We introduce the {\em
polynomial bottleneck games} where the utility costs of the players are
polynomial functions of the congestion of the resources that they use. In
particular, the delay function for any resource $r$ is $C_{r}^\M$, where $C_r$
is the congestion measured as the number of players that use $r$, and $\M \geq
1$ is an integer constant that defines the degree of the polynomial. The
utility cost of a player is the sum of the individual delays of the resources
that it uses. The social cost of the game remains the same, namely, it is the
worst bottleneck resource congestion: $\max_{r} C_r$. We show that polynomial
bottleneck games are very efficient and give price of anarchy
$O(|R|^{1/(\M+1)})$, where $R$ is the set of resources. This price of anarchy
is tight, since we demonstrate a game with price of anarchy
$\Omega(|R|^{1/(\M+1)})$, for any $\M \geq 1$. We obtain our tight bounds by
using two proof techniques: {\em transformation}, which we use to convert
arbitrary games to simpler games, and {\em expansion}, which we use to bound
the price of anarchy in a simpler game.
",athanasios vasilakos,,2010.0,,arXiv,Kannan2010,True,,arXiv,Not available,Polynomial Bottleneck Congestion Games with Optimal Price of Anarchy,1abcadede6a3253a6cc12bedfe8712f1,http://arxiv.org/abs/1010.4812v1
14744,"  Price of anarchy quantifies the degradation of social welfare in games due to
the lack of a centralized authority that can enforce the optimal outcome. At
its antipodes, mechanism design studies how to ameliorate these effects by
incentivizing socially desirable behavior and implementing the optimal state as
equilibrium. In practice, the responsiveness to such measures depends on the
wealth of each individual. This leads to a natural, but largely unexplored,
question. Does optimal mechanism design entrench, or maybe even exacerbate,
social inequality?
  We study this question in nonatomic congestion games, arguably one of the
most thoroughly studied settings from the perspectives of price of anarchy as
well as mechanism design. We introduce a new model that incorporates the wealth
distribution of the population and captures the income elasticity of travel
time. This allows us to argue about the equality of wealth distribution both
before and after employing a mechanism. We start our analysis by establishing a
broad qualitative result, showing that tolls always increase inequality in
symmetric congestion games under any reasonable metric of inequality, e.g., the
Gini index. Next, we introduce the iniquity index, a novel measure for
quantifying the magnitude of these forces towards a more unbalanced wealth
distribution and show it has good normative properties (robustness to scaling
of income, no-regret learning). We analyze iniquity both in theoretical
settings (Pigou's network under various wealth distributions) as well as
experimental ones (based on a large scale field experiment in Singapore).
Finally, we provide an algorithm for computing optimal tolls for any point of
the trade-off of relative importance of efficiency and equality. We conclude
with a discussion of our findings in the context of theories of justice as
developed in contemporary social sciences.
",kurtulus gemici,,2018.0,,arXiv,Gemici2018,True,,arXiv,Not available,Wealth Inequality and the Price of Anarchy,e9037e4885948d7fe7006fd3b7e22f1d,http://arxiv.org/abs/1802.09269v1
14745,"  Price of anarchy quantifies the degradation of social welfare in games due to
the lack of a centralized authority that can enforce the optimal outcome. At
its antipodes, mechanism design studies how to ameliorate these effects by
incentivizing socially desirable behavior and implementing the optimal state as
equilibrium. In practice, the responsiveness to such measures depends on the
wealth of each individual. This leads to a natural, but largely unexplored,
question. Does optimal mechanism design entrench, or maybe even exacerbate,
social inequality?
  We study this question in nonatomic congestion games, arguably one of the
most thoroughly studied settings from the perspectives of price of anarchy as
well as mechanism design. We introduce a new model that incorporates the wealth
distribution of the population and captures the income elasticity of travel
time. This allows us to argue about the equality of wealth distribution both
before and after employing a mechanism. We start our analysis by establishing a
broad qualitative result, showing that tolls always increase inequality in
symmetric congestion games under any reasonable metric of inequality, e.g., the
Gini index. Next, we introduce the iniquity index, a novel measure for
quantifying the magnitude of these forces towards a more unbalanced wealth
distribution and show it has good normative properties (robustness to scaling
of income, no-regret learning). We analyze iniquity both in theoretical
settings (Pigou's network under various wealth distributions) as well as
experimental ones (based on a large scale field experiment in Singapore).
Finally, we provide an algorithm for computing optimal tolls for any point of
the trade-off of relative importance of efficiency and equality. We conclude
with a discussion of our findings in the context of theories of justice as
developed in contemporary social sciences.
",elias koutsoupias,,2018.0,,arXiv,Gemici2018,True,,arXiv,Not available,Wealth Inequality and the Price of Anarchy,e9037e4885948d7fe7006fd3b7e22f1d,http://arxiv.org/abs/1802.09269v1
14746,"  Price of anarchy quantifies the degradation of social welfare in games due to
the lack of a centralized authority that can enforce the optimal outcome. At
its antipodes, mechanism design studies how to ameliorate these effects by
incentivizing socially desirable behavior and implementing the optimal state as
equilibrium. In practice, the responsiveness to such measures depends on the
wealth of each individual. This leads to a natural, but largely unexplored,
question. Does optimal mechanism design entrench, or maybe even exacerbate,
social inequality?
  We study this question in nonatomic congestion games, arguably one of the
most thoroughly studied settings from the perspectives of price of anarchy as
well as mechanism design. We introduce a new model that incorporates the wealth
distribution of the population and captures the income elasticity of travel
time. This allows us to argue about the equality of wealth distribution both
before and after employing a mechanism. We start our analysis by establishing a
broad qualitative result, showing that tolls always increase inequality in
symmetric congestion games under any reasonable metric of inequality, e.g., the
Gini index. Next, we introduce the iniquity index, a novel measure for
quantifying the magnitude of these forces towards a more unbalanced wealth
distribution and show it has good normative properties (robustness to scaling
of income, no-regret learning). We analyze iniquity both in theoretical
settings (Pigou's network under various wealth distributions) as well as
experimental ones (based on a large scale field experiment in Singapore).
Finally, we provide an algorithm for computing optimal tolls for any point of
the trade-off of relative importance of efficiency and equality. We conclude
with a discussion of our findings in the context of theories of justice as
developed in contemporary social sciences.
",barnabe monnot,,2018.0,,arXiv,Gemici2018,True,,arXiv,Not available,Wealth Inequality and the Price of Anarchy,e9037e4885948d7fe7006fd3b7e22f1d,http://arxiv.org/abs/1802.09269v1
14747,"  Price of anarchy quantifies the degradation of social welfare in games due to
the lack of a centralized authority that can enforce the optimal outcome. At
its antipodes, mechanism design studies how to ameliorate these effects by
incentivizing socially desirable behavior and implementing the optimal state as
equilibrium. In practice, the responsiveness to such measures depends on the
wealth of each individual. This leads to a natural, but largely unexplored,
question. Does optimal mechanism design entrench, or maybe even exacerbate,
social inequality?
  We study this question in nonatomic congestion games, arguably one of the
most thoroughly studied settings from the perspectives of price of anarchy as
well as mechanism design. We introduce a new model that incorporates the wealth
distribution of the population and captures the income elasticity of travel
time. This allows us to argue about the equality of wealth distribution both
before and after employing a mechanism. We start our analysis by establishing a
broad qualitative result, showing that tolls always increase inequality in
symmetric congestion games under any reasonable metric of inequality, e.g., the
Gini index. Next, we introduce the iniquity index, a novel measure for
quantifying the magnitude of these forces towards a more unbalanced wealth
distribution and show it has good normative properties (robustness to scaling
of income, no-regret learning). We analyze iniquity both in theoretical
settings (Pigou's network under various wealth distributions) as well as
experimental ones (based on a large scale field experiment in Singapore).
Finally, we provide an algorithm for computing optimal tolls for any point of
the trade-off of relative importance of efficiency and equality. We conclude
with a discussion of our findings in the context of theories of justice as
developed in contemporary social sciences.
",christos papadimitriou,,2018.0,,arXiv,Gemici2018,True,,arXiv,Not available,Wealth Inequality and the Price of Anarchy,e9037e4885948d7fe7006fd3b7e22f1d,http://arxiv.org/abs/1802.09269v1
14748,"  Price of anarchy quantifies the degradation of social welfare in games due to
the lack of a centralized authority that can enforce the optimal outcome. At
its antipodes, mechanism design studies how to ameliorate these effects by
incentivizing socially desirable behavior and implementing the optimal state as
equilibrium. In practice, the responsiveness to such measures depends on the
wealth of each individual. This leads to a natural, but largely unexplored,
question. Does optimal mechanism design entrench, or maybe even exacerbate,
social inequality?
  We study this question in nonatomic congestion games, arguably one of the
most thoroughly studied settings from the perspectives of price of anarchy as
well as mechanism design. We introduce a new model that incorporates the wealth
distribution of the population and captures the income elasticity of travel
time. This allows us to argue about the equality of wealth distribution both
before and after employing a mechanism. We start our analysis by establishing a
broad qualitative result, showing that tolls always increase inequality in
symmetric congestion games under any reasonable metric of inequality, e.g., the
Gini index. Next, we introduce the iniquity index, a novel measure for
quantifying the magnitude of these forces towards a more unbalanced wealth
distribution and show it has good normative properties (robustness to scaling
of income, no-regret learning). We analyze iniquity both in theoretical
settings (Pigou's network under various wealth distributions) as well as
experimental ones (based on a large scale field experiment in Singapore).
Finally, we provide an algorithm for computing optimal tolls for any point of
the trade-off of relative importance of efficiency and equality. We conclude
with a discussion of our findings in the context of theories of justice as
developed in contemporary social sciences.
",georgios piliouras,,2018.0,,arXiv,Gemici2018,True,,arXiv,Not available,Wealth Inequality and the Price of Anarchy,e9037e4885948d7fe7006fd3b7e22f1d,http://arxiv.org/abs/1802.09269v1
14749,"  We study the Price of Anarchy of simultaneous first-price auctions for buyers
with submodular and subadditive valuations. The current best upper bounds for
the Bayesian Price of Anarchy of these auctions are e/(e-1) [Syrgkanis and
Tardos 2013] and 2 [Feldman et al. 2013], respectively. We provide matching
lower bounds for both cases even for the case of full information and for mixed
Nash equilibria via an explicit construction.
  We present an alternative proof of the upper bound of e/(e-1) for first-price
auctions with fractionally subadditive valuations which reveals the worst-case
price distribution, that is used as a building block for the matching lower
bound construction.
  We generalize our results to a general class of item bidding auctions that we
call bid-dependent auctions (including first-price auctions and all-pay
auctions) where the winner is always the highest bidder and each bidder's
payment depends only on his own bid.
  Finally, we apply our techniques to discriminatory price multi-unit auctions.
We complement the results of [de Keijzer et al. 2013] for the case of
subadditive valuations, by providing a matching lower bound of 2. For the case
of submodular valuations, we provide a lower bound of 1.109. For the same class
of valuations, we were able to reproduce the upper bound of e/(e-1) using our
non-smooth approach.
",george christodoulou,,2013.0,,arXiv,Christodoulou2013,True,,arXiv,Not available,"Tight Bounds for the Price of Anarchy of Simultaneous First Price
  Auctions",d63eed1ac82b5d665751b5bd2483ebe6,http://arxiv.org/abs/1312.2371v3
14750,"  The Generalized Second Price auction (GSP) has been widely used by search
engines to sell ad slots. Previous studies have shown that the pure Price Of
Anarchy (POA) of GSP is 1.25 when there are two ad slots and 1.259 when three
ad slots. For the cases with more than three ad slots, however, only some
untight upper bounds of the pure POA were obtained. In this work, we improve
previous results in two aspects: (1) We prove that the pure POA for GSP is
1.259 when there are four ad slots, and (2) We show that the pure POA for GSP
with more than four ad slots is also 1.259 given the bidders are ranked
according to a particular permutation.
",tao qin,,2013.0,,arXiv,Ding2013,True,,arXiv,Not available,Pure Price of Anarchy for Generalized Second Price Auction,888d14a291ca172734368475b7e23927,http://arxiv.org/abs/1305.5404v1
14751,"  We study the Price of Anarchy of simultaneous first-price auctions for buyers
with submodular and subadditive valuations. The current best upper bounds for
the Bayesian Price of Anarchy of these auctions are e/(e-1) [Syrgkanis and
Tardos 2013] and 2 [Feldman et al. 2013], respectively. We provide matching
lower bounds for both cases even for the case of full information and for mixed
Nash equilibria via an explicit construction.
  We present an alternative proof of the upper bound of e/(e-1) for first-price
auctions with fractionally subadditive valuations which reveals the worst-case
price distribution, that is used as a building block for the matching lower
bound construction.
  We generalize our results to a general class of item bidding auctions that we
call bid-dependent auctions (including first-price auctions and all-pay
auctions) where the winner is always the highest bidder and each bidder's
payment depends only on his own bid.
  Finally, we apply our techniques to discriminatory price multi-unit auctions.
We complement the results of [de Keijzer et al. 2013] for the case of
subadditive valuations, by providing a matching lower bound of 2. For the case
of submodular valuations, we provide a lower bound of 1.109. For the same class
of valuations, we were able to reproduce the upper bound of e/(e-1) using our
non-smooth approach.
",annamaria kovacs,,2013.0,,arXiv,Christodoulou2013,True,,arXiv,Not available,"Tight Bounds for the Price of Anarchy of Simultaneous First Price
  Auctions",d63eed1ac82b5d665751b5bd2483ebe6,http://arxiv.org/abs/1312.2371v3
14752,"  We study the Price of Anarchy of simultaneous first-price auctions for buyers
with submodular and subadditive valuations. The current best upper bounds for
the Bayesian Price of Anarchy of these auctions are e/(e-1) [Syrgkanis and
Tardos 2013] and 2 [Feldman et al. 2013], respectively. We provide matching
lower bounds for both cases even for the case of full information and for mixed
Nash equilibria via an explicit construction.
  We present an alternative proof of the upper bound of e/(e-1) for first-price
auctions with fractionally subadditive valuations which reveals the worst-case
price distribution, that is used as a building block for the matching lower
bound construction.
  We generalize our results to a general class of item bidding auctions that we
call bid-dependent auctions (including first-price auctions and all-pay
auctions) where the winner is always the highest bidder and each bidder's
payment depends only on his own bid.
  Finally, we apply our techniques to discriminatory price multi-unit auctions.
We complement the results of [de Keijzer et al. 2013] for the case of
subadditive valuations, by providing a matching lower bound of 2. For the case
of submodular valuations, we provide a lower bound of 1.109. For the same class
of valuations, we were able to reproduce the upper bound of e/(e-1) using our
non-smooth approach.
",alkmini sgouritsa,,2013.0,,arXiv,Christodoulou2013,True,,arXiv,Not available,"Tight Bounds for the Price of Anarchy of Simultaneous First Price
  Auctions",d63eed1ac82b5d665751b5bd2483ebe6,http://arxiv.org/abs/1312.2371v3
14753,"  We study the Price of Anarchy of simultaneous first-price auctions for buyers
with submodular and subadditive valuations. The current best upper bounds for
the Bayesian Price of Anarchy of these auctions are e/(e-1) [Syrgkanis and
Tardos 2013] and 2 [Feldman et al. 2013], respectively. We provide matching
lower bounds for both cases even for the case of full information and for mixed
Nash equilibria via an explicit construction.
  We present an alternative proof of the upper bound of e/(e-1) for first-price
auctions with fractionally subadditive valuations which reveals the worst-case
price distribution, that is used as a building block for the matching lower
bound construction.
  We generalize our results to a general class of item bidding auctions that we
call bid-dependent auctions (including first-price auctions and all-pay
auctions) where the winner is always the highest bidder and each bidder's
payment depends only on his own bid.
  Finally, we apply our techniques to discriminatory price multi-unit auctions.
We complement the results of [de Keijzer et al. 2013] for the case of
subadditive valuations, by providing a matching lower bound of 2. For the case
of submodular valuations, we provide a lower bound of 1.109. For the same class
of valuations, we were able to reproduce the upper bound of e/(e-1) using our
non-smooth approach.
",bo tang,,2013.0,,arXiv,Christodoulou2013,True,,arXiv,Not available,"Tight Bounds for the Price of Anarchy of Simultaneous First Price
  Auctions",d63eed1ac82b5d665751b5bd2483ebe6,http://arxiv.org/abs/1312.2371v3
14754,"  Globally operating suppliers face the rising challenge of wholesale pricing
under scarce data about retail demand, in contrast to better informed, locally
operating retailers. At the same time, as local businesses proliferate, markets
congest and retail competition increases. To capture these strategic
considerations, we employ the classic Cournot model and extend it to a
two-stage supply chain with an upstream supplier who operates under demand
uncertainty and multiple downstream retailers who compete over quantity. The
supplier's belief about retail demand is modeled via a continuous probability
distribution function F. If F has the decreasing generalized mean residual life
property, then the supplier's optimal pricing policy exists and is the unique
fixed point of the mean residual life function. We evaluate the realized Price
of Uncertainty and show that there exist demand levels for which market
performs better when the supplier prices under demand uncertainty. In general,
performance worsens for lower values of realized demand. We examine the effects
of increasing competition on supply chain efficiency via the realized Price of
Anarchy and complement our findings with numerical results.
",costis melolidakis,,2018.0,,arXiv,Melolidakis2018,True,,arXiv,Not available,"Measuring Market Performance with Stochastic Demand: Price of Anarchy
  and Price of Uncertainty",0e5c02fa1e961208e06a0a9d9fe884c3,http://arxiv.org/abs/1808.04701v1
14755,"  Globally operating suppliers face the rising challenge of wholesale pricing
under scarce data about retail demand, in contrast to better informed, locally
operating retailers. At the same time, as local businesses proliferate, markets
congest and retail competition increases. To capture these strategic
considerations, we employ the classic Cournot model and extend it to a
two-stage supply chain with an upstream supplier who operates under demand
uncertainty and multiple downstream retailers who compete over quantity. The
supplier's belief about retail demand is modeled via a continuous probability
distribution function F. If F has the decreasing generalized mean residual life
property, then the supplier's optimal pricing policy exists and is the unique
fixed point of the mean residual life function. We evaluate the realized Price
of Uncertainty and show that there exist demand levels for which market
performs better when the supplier prices under demand uncertainty. In general,
performance worsens for lower values of realized demand. We examine the effects
of increasing competition on supply chain efficiency via the realized Price of
Anarchy and complement our findings with numerical results.
",stefanos leonardos,,2018.0,,arXiv,Melolidakis2018,True,,arXiv,Not available,"Measuring Market Performance with Stochastic Demand: Price of Anarchy
  and Price of Uncertainty",0e5c02fa1e961208e06a0a9d9fe884c3,http://arxiv.org/abs/1808.04701v1
14756,"  Globally operating suppliers face the rising challenge of wholesale pricing
under scarce data about retail demand, in contrast to better informed, locally
operating retailers. At the same time, as local businesses proliferate, markets
congest and retail competition increases. To capture these strategic
considerations, we employ the classic Cournot model and extend it to a
two-stage supply chain with an upstream supplier who operates under demand
uncertainty and multiple downstream retailers who compete over quantity. The
supplier's belief about retail demand is modeled via a continuous probability
distribution function F. If F has the decreasing generalized mean residual life
property, then the supplier's optimal pricing policy exists and is the unique
fixed point of the mean residual life function. We evaluate the realized Price
of Uncertainty and show that there exist demand levels for which market
performs better when the supplier prices under demand uncertainty. In general,
performance worsens for lower values of realized demand. We examine the effects
of increasing competition on supply chain efficiency via the realized Price of
Anarchy and complement our findings with numerical results.
",constandina koki,,2018.0,,arXiv,Melolidakis2018,True,,arXiv,Not available,"Measuring Market Performance with Stochastic Demand: Price of Anarchy
  and Price of Uncertainty",0e5c02fa1e961208e06a0a9d9fe884c3,http://arxiv.org/abs/1808.04701v1
14757,"  The congestion pricing is an efficient allocation approach to mediate demand
and supply of network resources. Different from the previous pricing using
Affine Marginal Cost (AMC), we focus on studying the game between network
coding and routing flows sharing a single link when users are price
anticipating based on an Average Cost Sharing (ACS) pricing mechanism. We
characterize the worst-case efficiency bounds of the game compared with the
optimal, i.e., the price-of anarchy (POA), which can be low bound 50% with
routing only. When both network coding and routing are applied, the POA can be
as low as 4/9. Therefore, network coding cannot improve the POA significantly
under the ACS. Moreover, for more efficient use of limited resources, it
indicates the sharing users have a higher tendency to choose network coding.
",wang gang,,2011.0,,arXiv,Gang2011,True,,arXiv,Not available,"The Price of Anarchy (POA) of network coding and routing based on
  average pricing mechanism",a0e7cdbbea82825b12d0fd725dfcc644,http://arxiv.org/abs/1110.4175v1
14758,"  The congestion pricing is an efficient allocation approach to mediate demand
and supply of network resources. Different from the previous pricing using
Affine Marginal Cost (AMC), we focus on studying the game between network
coding and routing flows sharing a single link when users are price
anticipating based on an Average Cost Sharing (ACS) pricing mechanism. We
characterize the worst-case efficiency bounds of the game compared with the
optimal, i.e., the price-of anarchy (POA), which can be low bound 50% with
routing only. When both network coding and routing are applied, the POA can be
as low as 4/9. Therefore, network coding cannot improve the POA significantly
under the ACS. Moreover, for more efficient use of limited resources, it
indicates the sharing users have a higher tendency to choose network coding.
",dai xia,,2011.0,,arXiv,Gang2011,True,,arXiv,Not available,"The Price of Anarchy (POA) of network coding and routing based on
  average pricing mechanism",a0e7cdbbea82825b12d0fd725dfcc644,http://arxiv.org/abs/1110.4175v1
14759,"  We study a static game played by a finite number of agents, in which agents
are assigned independent and identically distributed random types and each
agent minimizes its objective function by choosing from a set of admissible
actions that depends on its type. The game is anonymous in the sense that the
objective function of each agent depends on the actions of other agents only
through the empirical distribution of their type-action pairs. We study the
asymptotic behavior of Nash equilibria, as the number of agents tends to
infinity, first by deriving laws of large numbers characterizes almost sure
limit points of Nash equilibria in terms of so-called Cournot-Nash equilibria
of an associated nonatomic game. Our main results are large deviation
principles that characterize the probability of rare Nash equilibria and
associated conditional limit theorems describing the behavior of equilibria
conditioned on a rare event. The results cover situations when neither the
finite-player game nor the associated nonatomic game has a unique equilibrium.
In addition, we study the asymptotic behavior of the price of anarchy,
complementing existing worst-case bounds with new probabilistic bounds in the
context of congestion games, which are used to model traffic routing in
networks.
",daniel lacker,,2017.0,,arXiv,Lacker2017,True,,arXiv,Not available,Rare Nash Equilibria and the Price of Anarchy in Large Static Games,1caa3d9838c1aac43c25e87e65ec060e,http://arxiv.org/abs/1702.02113v1
14760,"  We study a static game played by a finite number of agents, in which agents
are assigned independent and identically distributed random types and each
agent minimizes its objective function by choosing from a set of admissible
actions that depends on its type. The game is anonymous in the sense that the
objective function of each agent depends on the actions of other agents only
through the empirical distribution of their type-action pairs. We study the
asymptotic behavior of Nash equilibria, as the number of agents tends to
infinity, first by deriving laws of large numbers characterizes almost sure
limit points of Nash equilibria in terms of so-called Cournot-Nash equilibria
of an associated nonatomic game. Our main results are large deviation
principles that characterize the probability of rare Nash equilibria and
associated conditional limit theorems describing the behavior of equilibria
conditioned on a rare event. The results cover situations when neither the
finite-player game nor the associated nonatomic game has a unique equilibrium.
In addition, we study the asymptotic behavior of the price of anarchy,
complementing existing worst-case bounds with new probabilistic bounds in the
context of congestion games, which are used to model traffic routing in
networks.
",kavita ramanan,,2017.0,,arXiv,Lacker2017,True,,arXiv,Not available,Rare Nash Equilibria and the Price of Anarchy in Large Static Games,1caa3d9838c1aac43c25e87e65ec060e,http://arxiv.org/abs/1702.02113v1
14761,"  The Generalized Second Price auction (GSP) has been widely used by search
engines to sell ad slots. Previous studies have shown that the pure Price Of
Anarchy (POA) of GSP is 1.25 when there are two ad slots and 1.259 when three
ad slots. For the cases with more than three ad slots, however, only some
untight upper bounds of the pure POA were obtained. In this work, we improve
previous results in two aspects: (1) We prove that the pure POA for GSP is
1.259 when there are four ad slots, and (2) We show that the pure POA for GSP
with more than four ad slots is also 1.259 given the bidders are ranked
according to a particular permutation.
",tie-yan liu,,2013.0,,arXiv,Ding2013,True,,arXiv,Not available,Pure Price of Anarchy for Generalized Second Price Auction,888d14a291ca172734368475b7e23927,http://arxiv.org/abs/1305.5404v1
14762,"  We consider the problem of optimal charging of plug-in electric vehicles
(PEVs). We treat this problem as a multi-agent game, where vehicles/agents are
heterogeneous since they are subject to possibly different constraints. Under
the assumption that electricity price is affine in total demand, we show that,
for any finite number of heterogeneous agents, the PEV charging control game
admits a unique Nash equilibrium, which is the optimizer of an auxiliary
minimization program. We are also able to quantify the asymptotic behaviour of
the price of anarchy for this class of games. More precisely, we prove that if
the parameters defining the constraints of each vehicle are drawn randomly from
a given distribution, then, the value of the game converges almost surely to
the optimum of the cooperative problem counterpart as the number of agents
tends to infinity. In the case of a discrete probability distribution, we
provide a systematic way to abstract agents in homogeneous groups and show
that, as the number of agents tends to infinity, the value of the game tends to
a deterministic quantity.
",luca deori,,2016.0,,arXiv,Deori2016,True,,arXiv,Not available,"Price of anarchy in electric vehicle charging control games: When Nash
  equilibria achieve social welfare",bea650d7b11d60cabed793488a4ab65c,http://arxiv.org/abs/1612.01342v2
14763,"  We consider the problem of optimal charging of plug-in electric vehicles
(PEVs). We treat this problem as a multi-agent game, where vehicles/agents are
heterogeneous since they are subject to possibly different constraints. Under
the assumption that electricity price is affine in total demand, we show that,
for any finite number of heterogeneous agents, the PEV charging control game
admits a unique Nash equilibrium, which is the optimizer of an auxiliary
minimization program. We are also able to quantify the asymptotic behaviour of
the price of anarchy for this class of games. More precisely, we prove that if
the parameters defining the constraints of each vehicle are drawn randomly from
a given distribution, then, the value of the game converges almost surely to
the optimum of the cooperative problem counterpart as the number of agents
tends to infinity. In the case of a discrete probability distribution, we
provide a systematic way to abstract agents in homogeneous groups and show
that, as the number of agents tends to infinity, the value of the game tends to
a deterministic quantity.
",kostas margellos,,2016.0,,arXiv,Deori2016,True,,arXiv,Not available,"Price of anarchy in electric vehicle charging control games: When Nash
  equilibria achieve social welfare",bea650d7b11d60cabed793488a4ab65c,http://arxiv.org/abs/1612.01342v2
14764,"  We consider the problem of optimal charging of plug-in electric vehicles
(PEVs). We treat this problem as a multi-agent game, where vehicles/agents are
heterogeneous since they are subject to possibly different constraints. Under
the assumption that electricity price is affine in total demand, we show that,
for any finite number of heterogeneous agents, the PEV charging control game
admits a unique Nash equilibrium, which is the optimizer of an auxiliary
minimization program. We are also able to quantify the asymptotic behaviour of
the price of anarchy for this class of games. More precisely, we prove that if
the parameters defining the constraints of each vehicle are drawn randomly from
a given distribution, then, the value of the game converges almost surely to
the optimum of the cooperative problem counterpart as the number of agents
tends to infinity. In the case of a discrete probability distribution, we
provide a systematic way to abstract agents in homogeneous groups and show
that, as the number of agents tends to infinity, the value of the game tends to
a deterministic quantity.
",maria prandini,,2016.0,,arXiv,Deori2016,True,,arXiv,Not available,"Price of anarchy in electric vehicle charging control games: When Nash
  equilibria achieve social welfare",bea650d7b11d60cabed793488a4ab65c,http://arxiv.org/abs/1612.01342v2
14765,"  We consider the capacitated selfish replication (CSR) game with binary
preferences, over general undirected networks. We first show that such games
have an associated ordinary potential function, and hence always admit a
pure-strategy Nash equilibrium (NE). Further, when the minimum degree of the
network and the number of resources are of the same order, there exists an
exact polynomial time algorithm which can find a NE. Following this, we study
the price of anarchy of such games, and show that it is bounded above by 3; we
further provide some instances for which the price of anarchy is at least 2. We
develop a quasi-polynomial algorithm O(n^2D^{ln n}), where n is the number of
players and D is the diameter of the network, which can find, in a distributed
manner, an allocation profile that is within a constant factor of the optimal
allocation, and hence of any pure-strategy NE of the game. Proof of this result
uses a novel potential function.
",seyed etesami,,2015.0,,arXiv,Etesami2015,True,,arXiv,Not available,"Approximation Algorithm for the Binary-Preference Capacitated Selfish
  Replication Game and a Tight Bound on its Price of Anarchy",bc69988ecb7fac476fa425b78a244adb,http://arxiv.org/abs/1506.04047v2
14766,"  We consider the capacitated selfish replication (CSR) game with binary
preferences, over general undirected networks. We first show that such games
have an associated ordinary potential function, and hence always admit a
pure-strategy Nash equilibrium (NE). Further, when the minimum degree of the
network and the number of resources are of the same order, there exists an
exact polynomial time algorithm which can find a NE. Following this, we study
the price of anarchy of such games, and show that it is bounded above by 3; we
further provide some instances for which the price of anarchy is at least 2. We
develop a quasi-polynomial algorithm O(n^2D^{ln n}), where n is the number of
players and D is the diameter of the network, which can find, in a distributed
manner, an allocation profile that is within a constant factor of the optimal
allocation, and hence of any pure-strategy NE of the game. Proof of this result
uses a novel potential function.
",tamer basar,,2015.0,,arXiv,Etesami2015,True,,arXiv,Not available,"Approximation Algorithm for the Binary-Preference Capacitated Selfish
  Replication Game and a Tight Bound on its Price of Anarchy",bc69988ecb7fac476fa425b78a244adb,http://arxiv.org/abs/1506.04047v2
14767,"  The reliability and security of a user in an interconnected system depends on
all users' collective effort in security. Consequently, investments in security
technologies by strategic users is typically modeled as a public good problem,
known as the Interdependent Security (IDS) game. The equilibria for such games
are often inefficient, as selfish users free-ride on positive externalities of
others' contributions. In this paper, we present a mechanism that implements
the socially optimal equilibrium in an IDS game through a message exchange
process, in which users submit proposals about the security investment and
tax/price profiles of one another. This mechanism is different from existing
solutions in that (1) it results in socially optimal levels of investment,
closing the Price of Anarchy gap in the IDS game, (2) it is applicable to a
general model of user interdependencies. We further consider the issue of
individual rationality, often a trivial condition to satisfy in many resource
allocation problems, and argue that with positive externality, the incentive to
stay out and free-ride on others' investment can make individual rationality
much harder to satisfy in designing a mechanism.
",parinaz naghizadeh,,2013.0,,arXiv,Naghizadeh2013,True,,arXiv,Not available,Closing the Price of Anarchy Gap in the Interdependent Security Game,17e75ac400756e5c42b283de95d63733,http://arxiv.org/abs/1308.0979v2
14768,"  The reliability and security of a user in an interconnected system depends on
all users' collective effort in security. Consequently, investments in security
technologies by strategic users is typically modeled as a public good problem,
known as the Interdependent Security (IDS) game. The equilibria for such games
are often inefficient, as selfish users free-ride on positive externalities of
others' contributions. In this paper, we present a mechanism that implements
the socially optimal equilibrium in an IDS game through a message exchange
process, in which users submit proposals about the security investment and
tax/price profiles of one another. This mechanism is different from existing
solutions in that (1) it results in socially optimal levels of investment,
closing the Price of Anarchy gap in the IDS game, (2) it is applicable to a
general model of user interdependencies. We further consider the issue of
individual rationality, often a trivial condition to satisfy in many resource
allocation problems, and argue that with positive externality, the incentive to
stay out and free-ride on others' investment can make individual rationality
much harder to satisfy in designing a mechanism.
",mingyan liu,,2013.0,,arXiv,Naghizadeh2013,True,,arXiv,Not available,Closing the Price of Anarchy Gap in the Interdependent Security Game,17e75ac400756e5c42b283de95d63733,http://arxiv.org/abs/1308.0979v2
14769,"  We study a pricing game in multi-hop relay networks where nodes price their
services and route their traffic selfishly and strategically. In this game,
each node (1) announces pricing functions which specify the payments it demands
from its respective customers depending on the amount of traffic they route to
it and (2) allocates the total traffic it receives to its service providers.
The profit of a node is the difference between the revenue earned from
servicing others and the cost of using others' services. We show that the
socially optimal routing of such a game can always be induced by an equilibrium
where no node can increase its profit by unilaterally changing its pricing
functions or routing decision. On the other hand, there may also exist
inefficient equilibria. We characterize the loss of efficiency by deriving the
price of anarchy at inefficient equilibria. We show that the price of anarchy
is finite for oligopolies with concave marginal cost functions, while it is
infinite for general topologies and cost functions.
",yufang xi,,2007.0,,arXiv,Xi2007,True,,arXiv,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in
  Multi-hop Relay Networks",e983f63277e6307e3324b1309d3f6ca9,http://arxiv.org/abs/0709.2721v2
14770,"  We study a pricing game in multi-hop relay networks where nodes price their
services and route their traffic selfishly and strategically. In this game,
each node (1) announces pricing functions which specify the payments it demands
from its respective customers depending on the amount of traffic they route to
it and (2) allocates the total traffic it receives to its service providers.
The profit of a node is the difference between the revenue earned from
servicing others and the cost of using others' services. We show that the
socially optimal routing of such a game can always be induced by an equilibrium
where no node can increase its profit by unilaterally changing its pricing
functions or routing decision. On the other hand, there may also exist
inefficient equilibria. We characterize the loss of efficiency by deriving the
price of anarchy at inefficient equilibria. We show that the price of anarchy
is finite for oligopolies with concave marginal cost functions, while it is
infinite for general topologies and cost functions.
",edmund yeh,,2007.0,,arXiv,Xi2007,True,,arXiv,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in
  Multi-hop Relay Networks",e983f63277e6307e3324b1309d3f6ca9,http://arxiv.org/abs/0709.2721v2
14771,"  Among the many functions a Smart City must support, transportation dominates
in terms of resource consumption, strain on the environment, and frustration of
its citizens. We study transportation networks under two different routing
policies, the commonly assumed selfish user-centric routing policy and a
socially-optimal system-centric one. We consider a performance metric of
efficiency - the Price of Anarchy (PoA) - defined as the ratio of the total
travel latency cost under selfish routing over the corresponding quantity under
socially-optimal routing. We develop a data-driven approach to estimate the
PoA, which we subsequently use to conduct a case study using extensive actual
traffic data from the Eastern Massachusetts road network. To estimate the PoA,
our approach learns from data a complete model of the transportation network,
including origin-destination demand and user preferences. We leverage this
model to propose possible strategies to reduce the PoA and increase efficiency.
",jing zhang,,2016.0,,arXiv,Zhang2016,True,,arXiv,Not available,"The Price of Anarchy in Transportation Networks: Data-Driven Evaluation
  and Reduction Strategies",37f20cc035a6df70f94408dc139497e3,http://arxiv.org/abs/1606.02194v2
14772,"  In this paper we consider the price of anarchy (PoA) in multi-commodity flows
where the latency or delay function on an edge has a heterogeneous dependency
on the flow commodities, i.e. when the delay on each link is dependent on the
flow of individual commodities, rather than on the aggregate flow. An
application of this study is the performance analysis of a network with
differentiated traffic that may arise when traffic is prioritized according to
some type classification. This study has implications in the debate on
net-neutrality. We provide price of anarchy bounds for networks with $k$ (types
of) commodities where each link is associated with heterogeneous polynomial
delays, i.e. commodity $i$ on edge $e$ faces delay specified by
$g_{i1}(e)f^{\theta}_1(e) + g_{i2}(e)f^{\theta}_2(e) + \ldots +
g_{ik}(e)f^{\theta}_k(e) + c_i(e), $ where $f_i(e)$ is the flow of the $i$th
commodity through edge $e$, $\theta \in {\cal N}$, $g_{i1}(e), g_{i2}(e),
\ldots, g_{ik}(e)$ and $c_i(e)$ are nonnegative constants. We consider both
atomic and non-atomic flows.
  For networks with decomposable delay functions where the delay induced by a
particular commodity is the same, i.e. delays on edge $e$ are defined by
$a_1(e)f_1^\theta(e) + a_2(e)f_2^\theta(e) + \ldots + c(e)$ where $\forall j ,
\forall e: g_{1j}(e) = g_{2j}(e) = \ldots = a_j(e)$, we show an improved bound
on the price of anarchy.
  Further, we show bounds on the price of anarchy for uniform latency functions
where each edge of the network has the same delay function.
",sanjiv kapoor,,2014.0,,arXiv,Kapoor2014,True,,arXiv,Not available,Price of Anarchy with Heterogeneous Latency Functions,15021d47109106236ab81620aa165e96,http://arxiv.org/abs/1407.2991v2
14773,"  Among the many functions a Smart City must support, transportation dominates
in terms of resource consumption, strain on the environment, and frustration of
its citizens. We study transportation networks under two different routing
policies, the commonly assumed selfish user-centric routing policy and a
socially-optimal system-centric one. We consider a performance metric of
efficiency - the Price of Anarchy (PoA) - defined as the ratio of the total
travel latency cost under selfish routing over the corresponding quantity under
socially-optimal routing. We develop a data-driven approach to estimate the
PoA, which we subsequently use to conduct a case study using extensive actual
traffic data from the Eastern Massachusetts road network. To estimate the PoA,
our approach learns from data a complete model of the transportation network,
including origin-destination demand and user preferences. We leverage this
model to propose possible strategies to reduce the PoA and increase efficiency.
",sepideh pourazarm,,2016.0,,arXiv,Zhang2016,True,,arXiv,Not available,"The Price of Anarchy in Transportation Networks: Data-Driven Evaluation
  and Reduction Strategies",37f20cc035a6df70f94408dc139497e3,http://arxiv.org/abs/1606.02194v2
14774,"  Among the many functions a Smart City must support, transportation dominates
in terms of resource consumption, strain on the environment, and frustration of
its citizens. We study transportation networks under two different routing
policies, the commonly assumed selfish user-centric routing policy and a
socially-optimal system-centric one. We consider a performance metric of
efficiency - the Price of Anarchy (PoA) - defined as the ratio of the total
travel latency cost under selfish routing over the corresponding quantity under
socially-optimal routing. We develop a data-driven approach to estimate the
PoA, which we subsequently use to conduct a case study using extensive actual
traffic data from the Eastern Massachusetts road network. To estimate the PoA,
our approach learns from data a complete model of the transportation network,
including origin-destination demand and user preferences. We leverage this
model to propose possible strategies to reduce the PoA and increase efficiency.
",christos cassandras,,2016.0,,arXiv,Zhang2016,True,,arXiv,Not available,"The Price of Anarchy in Transportation Networks: Data-Driven Evaluation
  and Reduction Strategies",37f20cc035a6df70f94408dc139497e3,http://arxiv.org/abs/1606.02194v2
14775,"  Among the many functions a Smart City must support, transportation dominates
in terms of resource consumption, strain on the environment, and frustration of
its citizens. We study transportation networks under two different routing
policies, the commonly assumed selfish user-centric routing policy and a
socially-optimal system-centric one. We consider a performance metric of
efficiency - the Price of Anarchy (PoA) - defined as the ratio of the total
travel latency cost under selfish routing over the corresponding quantity under
socially-optimal routing. We develop a data-driven approach to estimate the
PoA, which we subsequently use to conduct a case study using extensive actual
traffic data from the Eastern Massachusetts road network. To estimate the PoA,
our approach learns from data a complete model of the transportation network,
including origin-destination demand and user preferences. We leverage this
model to propose possible strategies to reduce the PoA and increase efficiency.
",ioannis paschalidis,,2016.0,,arXiv,Zhang2016,True,,arXiv,Not available,"The Price of Anarchy in Transportation Networks: Data-Driven Evaluation
  and Reduction Strategies",37f20cc035a6df70f94408dc139497e3,http://arxiv.org/abs/1606.02194v2
14776,"  We study network formation with the bilateral link formation rule (Jackson
and Wolinsky 1996) with $n$ players and link cost $\alpha>0$. After the network
is built, an adversary randomly destroys one link according to a certain
probability distribution. Cost for player $v$ incorporates the expected number
of players to which $v$ will become disconnected. This model was previously
studied for unilateral link formation (K. 2011).
  We prove existence of pairwise Nash equilibria under moderate assumptions on
the adversary and $n\geq 9$. As the main result, we prove bounds on the price
of anarchy for two special adversaries: one destroys a link chosen uniformly at
random, while the other destroys a link that causes a maximum number of player
pairs to be separated. We prove bounds tight up to constants, namely $O(1)$ for
one adversary (if $\alpha>1/2$), and $\Theta(n)$ for the other (if $\alpha>2$
considered constant and $n \geq 9$). The latter is the worst that can happen
for any adversary in this model (if $\alpha=\Omega(1)$).
",lasse kliemann,,2013.0,,arXiv,Kliemann2013,True,,arXiv,Not available,"The Price of Anarchy in Bilateral Network Formation in an Adversary
  Model",3185076bbbab8376b5192198c89c955f,http://arxiv.org/abs/1308.1832v1
14777,"  Game theory has emerged as a novel approach for the coordination of
multiagent systems. A fundamental component of this approach is the design of a
local utility function for each agent so that their selfish maximization
achieves the global objective. In this paper we propose a novel framework to
characterize and optimize the worst case performance (price of anarchy) of any
resulting equilibrium as a function of the chosen utilities, thus providing a
performance certificate for a large class of algorithms. More specifically, we
consider a class of resource allocation problems, where each agent selects a
subset of the resources with the goal of maximizing a welfare function. First,
we show that any smoothness argument is inconclusive for the design problems
considered. Motivated by this, we introduce a new approach providing a tight
expression for the price of anarchy (PoA) as a function of the chosen utility
functions. Leveraging this result, we show how to design the utilities so as to
maximize the PoA through a tractable linear program. In Part II we specialize
the results to submodular and supermodular welfare functions, discuss
complexity issues and provide two applications.
",dario paccagnan,,2018.0,,arXiv,Paccagnan2018,True,,arXiv,Not available,"Distributed resource allocation through utility design - Part I:
  optimizing the performance certificates via the price of anarchy",1a4c9645d24cd1667f73141121ca914e,http://arxiv.org/abs/1807.01333v1
14778,"  Game theory has emerged as a novel approach for the coordination of
multiagent systems. A fundamental component of this approach is the design of a
local utility function for each agent so that their selfish maximization
achieves the global objective. In this paper we propose a novel framework to
characterize and optimize the worst case performance (price of anarchy) of any
resulting equilibrium as a function of the chosen utilities, thus providing a
performance certificate for a large class of algorithms. More specifically, we
consider a class of resource allocation problems, where each agent selects a
subset of the resources with the goal of maximizing a welfare function. First,
we show that any smoothness argument is inconclusive for the design problems
considered. Motivated by this, we introduce a new approach providing a tight
expression for the price of anarchy (PoA) as a function of the chosen utility
functions. Leveraging this result, we show how to design the utilities so as to
maximize the PoA through a tractable linear program. In Part II we specialize
the results to submodular and supermodular welfare functions, discuss
complexity issues and provide two applications.
",rahul chandan,,2018.0,,arXiv,Paccagnan2018,True,,arXiv,Not available,"Distributed resource allocation through utility design - Part I:
  optimizing the performance certificates via the price of anarchy",1a4c9645d24cd1667f73141121ca914e,http://arxiv.org/abs/1807.01333v1
14779,"  Game theory has emerged as a novel approach for the coordination of
multiagent systems. A fundamental component of this approach is the design of a
local utility function for each agent so that their selfish maximization
achieves the global objective. In this paper we propose a novel framework to
characterize and optimize the worst case performance (price of anarchy) of any
resulting equilibrium as a function of the chosen utilities, thus providing a
performance certificate for a large class of algorithms. More specifically, we
consider a class of resource allocation problems, where each agent selects a
subset of the resources with the goal of maximizing a welfare function. First,
we show that any smoothness argument is inconclusive for the design problems
considered. Motivated by this, we introduce a new approach providing a tight
expression for the price of anarchy (PoA) as a function of the chosen utility
functions. Leveraging this result, we show how to design the utilities so as to
maximize the PoA through a tractable linear program. In Part II we specialize
the results to submodular and supermodular welfare functions, discuss
complexity issues and provide two applications.
",jason marden,,2018.0,,arXiv,Paccagnan2018,True,,arXiv,Not available,"Distributed resource allocation through utility design - Part I:
  optimizing the performance certificates via the price of anarchy",1a4c9645d24cd1667f73141121ca914e,http://arxiv.org/abs/1807.01333v1
14780,"  We prove a tight lower bound on the asymptotic performance ratio $\rho$ of
the bounded space online $d$-hypercube bin packing problem, solving an open
question raised in 2005. In the classic $d$-hypercube bin packing problem, we
are given a sequence of $d$-dimensional hypercubes and we have an unlimited
number of bins, each of which is a $d$-dimensional unit hypercube. The goal is
to pack (orthogonally) the given hypercubes into the minimum possible number of
bins, in such a way that no two hypercubes in the same bin overlap. The bounded
space online $d$-hypercube bin packing problem is a variant of the
$d$-hypercube bin packing problem, in which the hypercubes arrive online and
each one must be packed in an open bin without the knowledge of the next
hypercubes. Moreover, at each moment, only a constant number of open bins are
allowed (whenever a new bin is used, it is considered open, and it remains so
until it is considered closed, in which case, it is not allowed to accept new
hypercubes). Epstein and van Stee [SIAM J. Comput. 35 (2005), no. 2, 431-448]
showed that $\rho$ is $\Omega(\log d)$ and $O(d/\log d)$, and conjectured that
it is $\Theta(\log d)$. We show that $\rho$ is in fact $\Theta(d/\log d)$. To
obtain this result, we elaborate on some ideas presented by those authors, and
go one step further showing how to obtain better (offline) packings of certain
special instances for which one knows how many bins any bounded space algorithm
has to use. Our main contribution establishes the existence of such packings,
for large enough $d$, using probabilistic arguments. Such packings also lead to
lower bounds for the prices of anarchy of the selfish $d$-hypercube bin packing
game. We present a lower bound of $\Omega(d/\log d)$ for the pure price of
anarchy of this game, and we also give a lower bound of $\Omega(\log d)$ for
its strong price of anarchy.
",y. kohayakawa,,2017.0,,arXiv,Kohayakawa2017,True,,arXiv,Not available,"A tight lower bound for an online hypercube packing problem and bounds
  for prices of anarchy of a related game",b75b3216705de60ed5e100021dfead24,http://arxiv.org/abs/1712.06763v1
14781,"  We prove a tight lower bound on the asymptotic performance ratio $\rho$ of
the bounded space online $d$-hypercube bin packing problem, solving an open
question raised in 2005. In the classic $d$-hypercube bin packing problem, we
are given a sequence of $d$-dimensional hypercubes and we have an unlimited
number of bins, each of which is a $d$-dimensional unit hypercube. The goal is
to pack (orthogonally) the given hypercubes into the minimum possible number of
bins, in such a way that no two hypercubes in the same bin overlap. The bounded
space online $d$-hypercube bin packing problem is a variant of the
$d$-hypercube bin packing problem, in which the hypercubes arrive online and
each one must be packed in an open bin without the knowledge of the next
hypercubes. Moreover, at each moment, only a constant number of open bins are
allowed (whenever a new bin is used, it is considered open, and it remains so
until it is considered closed, in which case, it is not allowed to accept new
hypercubes). Epstein and van Stee [SIAM J. Comput. 35 (2005), no. 2, 431-448]
showed that $\rho$ is $\Omega(\log d)$ and $O(d/\log d)$, and conjectured that
it is $\Theta(\log d)$. We show that $\rho$ is in fact $\Theta(d/\log d)$. To
obtain this result, we elaborate on some ideas presented by those authors, and
go one step further showing how to obtain better (offline) packings of certain
special instances for which one knows how many bins any bounded space algorithm
has to use. Our main contribution establishes the existence of such packings,
for large enough $d$, using probabilistic arguments. Such packings also lead to
lower bounds for the prices of anarchy of the selfish $d$-hypercube bin packing
game. We present a lower bound of $\Omega(d/\log d)$ for the pure price of
anarchy of this game, and we also give a lower bound of $\Omega(\log d)$ for
its strong price of anarchy.
",f. miyazawa,,2017.0,,arXiv,Kohayakawa2017,True,,arXiv,Not available,"A tight lower bound for an online hypercube packing problem and bounds
  for prices of anarchy of a related game",b75b3216705de60ed5e100021dfead24,http://arxiv.org/abs/1712.06763v1
14782,"  We prove a tight lower bound on the asymptotic performance ratio $\rho$ of
the bounded space online $d$-hypercube bin packing problem, solving an open
question raised in 2005. In the classic $d$-hypercube bin packing problem, we
are given a sequence of $d$-dimensional hypercubes and we have an unlimited
number of bins, each of which is a $d$-dimensional unit hypercube. The goal is
to pack (orthogonally) the given hypercubes into the minimum possible number of
bins, in such a way that no two hypercubes in the same bin overlap. The bounded
space online $d$-hypercube bin packing problem is a variant of the
$d$-hypercube bin packing problem, in which the hypercubes arrive online and
each one must be packed in an open bin without the knowledge of the next
hypercubes. Moreover, at each moment, only a constant number of open bins are
allowed (whenever a new bin is used, it is considered open, and it remains so
until it is considered closed, in which case, it is not allowed to accept new
hypercubes). Epstein and van Stee [SIAM J. Comput. 35 (2005), no. 2, 431-448]
showed that $\rho$ is $\Omega(\log d)$ and $O(d/\log d)$, and conjectured that
it is $\Theta(\log d)$. We show that $\rho$ is in fact $\Theta(d/\log d)$. To
obtain this result, we elaborate on some ideas presented by those authors, and
go one step further showing how to obtain better (offline) packings of certain
special instances for which one knows how many bins any bounded space algorithm
has to use. Our main contribution establishes the existence of such packings,
for large enough $d$, using probabilistic arguments. Such packings also lead to
lower bounds for the prices of anarchy of the selfish $d$-hypercube bin packing
game. We present a lower bound of $\Omega(d/\log d)$ for the pure price of
anarchy of this game, and we also give a lower bound of $\Omega(\log d)$ for
its strong price of anarchy.
",y. wakabayashi,,2017.0,,arXiv,Kohayakawa2017,True,,arXiv,Not available,"A tight lower bound for an online hypercube packing problem and bounds
  for prices of anarchy of a related game",b75b3216705de60ed5e100021dfead24,http://arxiv.org/abs/1712.06763v1
14783,"  In this paper we consider the price of anarchy (PoA) in multi-commodity flows
where the latency or delay function on an edge has a heterogeneous dependency
on the flow commodities, i.e. when the delay on each link is dependent on the
flow of individual commodities, rather than on the aggregate flow. An
application of this study is the performance analysis of a network with
differentiated traffic that may arise when traffic is prioritized according to
some type classification. This study has implications in the debate on
net-neutrality. We provide price of anarchy bounds for networks with $k$ (types
of) commodities where each link is associated with heterogeneous polynomial
delays, i.e. commodity $i$ on edge $e$ faces delay specified by
$g_{i1}(e)f^{\theta}_1(e) + g_{i2}(e)f^{\theta}_2(e) + \ldots +
g_{ik}(e)f^{\theta}_k(e) + c_i(e), $ where $f_i(e)$ is the flow of the $i$th
commodity through edge $e$, $\theta \in {\cal N}$, $g_{i1}(e), g_{i2}(e),
\ldots, g_{ik}(e)$ and $c_i(e)$ are nonnegative constants. We consider both
atomic and non-atomic flows.
  For networks with decomposable delay functions where the delay induced by a
particular commodity is the same, i.e. delays on edge $e$ are defined by
$a_1(e)f_1^\theta(e) + a_2(e)f_2^\theta(e) + \ldots + c(e)$ where $\forall j ,
\forall e: g_{1j}(e) = g_{2j}(e) = \ldots = a_j(e)$, we show an improved bound
on the price of anarchy.
  Further, we show bounds on the price of anarchy for uniform latency functions
where each edge of the network has the same delay function.
",junghwan shin,,2014.0,,arXiv,Kapoor2014,True,,arXiv,Not available,Price of Anarchy with Heterogeneous Latency Functions,15021d47109106236ab81620aa165e96,http://arxiv.org/abs/1407.2991v2
14784,"  Priced timed games (PTGs) are two-player zero-sum games played on the
infinite graph of configurations of priced timed automata where two players
take turns to choose transitions in order to optimize cost to reach target
states. Bouyer et al. and Alur, Bernadsky, and Madhusudan independently
proposed algorithms to solve PTGs with nonnegative prices under certain
divergence restriction over prices. Brihaye, Bruyere, and Raskin later provided
a justification for such a restriction by showing the undecidability of the
optimal strategy synthesis problem in the absence of this divergence
restriction. This problem for PTGs with one clock has long been conjectured to
be in polynomial time, however the current best known algorithm, by Hansen,
Ibsen-Jensen, and Miltersen, is exponential. We extend this picture by studying
PTGs with both negative and positive prices. We refine the undecidability
results for optimal strategy synthesis problem, and show undecidability for
several variants of optimal reachability cost objectives including reachability
cost, time-bounded reachability cost, and repeated reachability cost
objectives. We also identify a subclass with bi-valued price-rates and give a
pseudo-polynomial (polynomial when prices are nonnegative) algorithm to
partially answer the conjecture on the complexity of one-clock PTGs.
",thomas brihaye,,2014.0,,arXiv,Brihaye2014,True,,arXiv,Not available,Adding Negative Prices to Priced Timed Games,eae1eefdff1073426a6399a0c6a4d2fd,http://arxiv.org/abs/1404.5894v5
14785,"  Priced timed games (PTGs) are two-player zero-sum games played on the
infinite graph of configurations of priced timed automata where two players
take turns to choose transitions in order to optimize cost to reach target
states. Bouyer et al. and Alur, Bernadsky, and Madhusudan independently
proposed algorithms to solve PTGs with nonnegative prices under certain
divergence restriction over prices. Brihaye, Bruyere, and Raskin later provided
a justification for such a restriction by showing the undecidability of the
optimal strategy synthesis problem in the absence of this divergence
restriction. This problem for PTGs with one clock has long been conjectured to
be in polynomial time, however the current best known algorithm, by Hansen,
Ibsen-Jensen, and Miltersen, is exponential. We extend this picture by studying
PTGs with both negative and positive prices. We refine the undecidability
results for optimal strategy synthesis problem, and show undecidability for
several variants of optimal reachability cost objectives including reachability
cost, time-bounded reachability cost, and repeated reachability cost
objectives. We also identify a subclass with bi-valued price-rates and give a
pseudo-polynomial (polynomial when prices are nonnegative) algorithm to
partially answer the conjecture on the complexity of one-clock PTGs.
",gilles geeraerts,,2014.0,,arXiv,Brihaye2014,True,,arXiv,Not available,Adding Negative Prices to Priced Timed Games,eae1eefdff1073426a6399a0c6a4d2fd,http://arxiv.org/abs/1404.5894v5
14786,"  Priced timed games (PTGs) are two-player zero-sum games played on the
infinite graph of configurations of priced timed automata where two players
take turns to choose transitions in order to optimize cost to reach target
states. Bouyer et al. and Alur, Bernadsky, and Madhusudan independently
proposed algorithms to solve PTGs with nonnegative prices under certain
divergence restriction over prices. Brihaye, Bruyere, and Raskin later provided
a justification for such a restriction by showing the undecidability of the
optimal strategy synthesis problem in the absence of this divergence
restriction. This problem for PTGs with one clock has long been conjectured to
be in polynomial time, however the current best known algorithm, by Hansen,
Ibsen-Jensen, and Miltersen, is exponential. We extend this picture by studying
PTGs with both negative and positive prices. We refine the undecidability
results for optimal strategy synthesis problem, and show undecidability for
several variants of optimal reachability cost objectives including reachability
cost, time-bounded reachability cost, and repeated reachability cost
objectives. We also identify a subclass with bi-valued price-rates and give a
pseudo-polynomial (polynomial when prices are nonnegative) algorithm to
partially answer the conjecture on the complexity of one-clock PTGs.
",shankara krishna,,2014.0,,arXiv,Brihaye2014,True,,arXiv,Not available,Adding Negative Prices to Priced Timed Games,eae1eefdff1073426a6399a0c6a4d2fd,http://arxiv.org/abs/1404.5894v5
14787,"  Priced timed games (PTGs) are two-player zero-sum games played on the
infinite graph of configurations of priced timed automata where two players
take turns to choose transitions in order to optimize cost to reach target
states. Bouyer et al. and Alur, Bernadsky, and Madhusudan independently
proposed algorithms to solve PTGs with nonnegative prices under certain
divergence restriction over prices. Brihaye, Bruyere, and Raskin later provided
a justification for such a restriction by showing the undecidability of the
optimal strategy synthesis problem in the absence of this divergence
restriction. This problem for PTGs with one clock has long been conjectured to
be in polynomial time, however the current best known algorithm, by Hansen,
Ibsen-Jensen, and Miltersen, is exponential. We extend this picture by studying
PTGs with both negative and positive prices. We refine the undecidability
results for optimal strategy synthesis problem, and show undecidability for
several variants of optimal reachability cost objectives including reachability
cost, time-bounded reachability cost, and repeated reachability cost
objectives. We also identify a subclass with bi-valued price-rates and give a
pseudo-polynomial (polynomial when prices are nonnegative) algorithm to
partially answer the conjecture on the complexity of one-clock PTGs.
",lakshmi manasa,,2014.0,,arXiv,Brihaye2014,True,,arXiv,Not available,Adding Negative Prices to Priced Timed Games,eae1eefdff1073426a6399a0c6a4d2fd,http://arxiv.org/abs/1404.5894v5
14788,"  Priced timed games (PTGs) are two-player zero-sum games played on the
infinite graph of configurations of priced timed automata where two players
take turns to choose transitions in order to optimize cost to reach target
states. Bouyer et al. and Alur, Bernadsky, and Madhusudan independently
proposed algorithms to solve PTGs with nonnegative prices under certain
divergence restriction over prices. Brihaye, Bruyere, and Raskin later provided
a justification for such a restriction by showing the undecidability of the
optimal strategy synthesis problem in the absence of this divergence
restriction. This problem for PTGs with one clock has long been conjectured to
be in polynomial time, however the current best known algorithm, by Hansen,
Ibsen-Jensen, and Miltersen, is exponential. We extend this picture by studying
PTGs with both negative and positive prices. We refine the undecidability
results for optimal strategy synthesis problem, and show undecidability for
several variants of optimal reachability cost objectives including reachability
cost, time-bounded reachability cost, and repeated reachability cost
objectives. We also identify a subclass with bi-valued price-rates and give a
pseudo-polynomial (polynomial when prices are nonnegative) algorithm to
partially answer the conjecture on the complexity of one-clock PTGs.
",benjamin monmege,,2014.0,,arXiv,Brihaye2014,True,,arXiv,Not available,Adding Negative Prices to Priced Timed Games,eae1eefdff1073426a6399a0c6a4d2fd,http://arxiv.org/abs/1404.5894v5
14789,"  Priced timed games (PTGs) are two-player zero-sum games played on the
infinite graph of configurations of priced timed automata where two players
take turns to choose transitions in order to optimize cost to reach target
states. Bouyer et al. and Alur, Bernadsky, and Madhusudan independently
proposed algorithms to solve PTGs with nonnegative prices under certain
divergence restriction over prices. Brihaye, Bruyere, and Raskin later provided
a justification for such a restriction by showing the undecidability of the
optimal strategy synthesis problem in the absence of this divergence
restriction. This problem for PTGs with one clock has long been conjectured to
be in polynomial time, however the current best known algorithm, by Hansen,
Ibsen-Jensen, and Miltersen, is exponential. We extend this picture by studying
PTGs with both negative and positive prices. We refine the undecidability
results for optimal strategy synthesis problem, and show undecidability for
several variants of optimal reachability cost objectives including reachability
cost, time-bounded reachability cost, and repeated reachability cost
objectives. We also identify a subclass with bi-valued price-rates and give a
pseudo-polynomial (polynomial when prices are nonnegative) algorithm to
partially answer the conjecture on the complexity of one-clock PTGs.
",ashutosh trivedi,,2014.0,,arXiv,Brihaye2014,True,,arXiv,Not available,Adding Negative Prices to Priced Timed Games,eae1eefdff1073426a6399a0c6a4d2fd,http://arxiv.org/abs/1404.5894v5
14790,"  We study the performance of approximate Nash equilibria for linear congestion
games. We consider how much the price of anarchy worsens and how much the price
of stability improves as a function of the approximation factor $\epsilon$. We
give (almost) tight upper and lower bounds for both the price of anarchy and
the price of stability for atomic and non-atomic congestion games. Our results
not only encompass and generalize the existing results of exact equilibria to
$\epsilon$-Nash equilibria, but they also provide a unified approach which
reveals the common threads of the atomic and non-atomic price of anarchy
results. By expanding the spectrum, we also cast the existing results in a new
light. For example, the Pigou network, which gives tight results for exact Nash
equilibria of selfish routing, remains tight for the price of stability of
$\epsilon$-Nash equilibria but not for the price of anarchy.
",george christodoulou,,2008.0,,arXiv,Christodoulou2008,True,,arXiv,Not available,On the performance of approximate equilibria in congestion games,965af3ddfa05a87b0d62ae20a96d4772,http://arxiv.org/abs/0804.3160v2
14791,"  We study the performance of approximate Nash equilibria for linear congestion
games. We consider how much the price of anarchy worsens and how much the price
of stability improves as a function of the approximation factor $\epsilon$. We
give (almost) tight upper and lower bounds for both the price of anarchy and
the price of stability for atomic and non-atomic congestion games. Our results
not only encompass and generalize the existing results of exact equilibria to
$\epsilon$-Nash equilibria, but they also provide a unified approach which
reveals the common threads of the atomic and non-atomic price of anarchy
results. By expanding the spectrum, we also cast the existing results in a new
light. For example, the Pigou network, which gives tight results for exact Nash
equilibria of selfish routing, remains tight for the price of stability of
$\epsilon$-Nash equilibria but not for the price of anarchy.
",elias koutsoupias,,2008.0,,arXiv,Christodoulou2008,True,,arXiv,Not available,On the performance of approximate equilibria in congestion games,965af3ddfa05a87b0d62ae20a96d4772,http://arxiv.org/abs/0804.3160v2
14792,"  We study the performance of approximate Nash equilibria for linear congestion
games. We consider how much the price of anarchy worsens and how much the price
of stability improves as a function of the approximation factor $\epsilon$. We
give (almost) tight upper and lower bounds for both the price of anarchy and
the price of stability for atomic and non-atomic congestion games. Our results
not only encompass and generalize the existing results of exact equilibria to
$\epsilon$-Nash equilibria, but they also provide a unified approach which
reveals the common threads of the atomic and non-atomic price of anarchy
results. By expanding the spectrum, we also cast the existing results in a new
light. For example, the Pigou network, which gives tight results for exact Nash
equilibria of selfish routing, remains tight for the price of stability of
$\epsilon$-Nash equilibria but not for the price of anarchy.
",paul spirakis,,2008.0,,arXiv,Christodoulou2008,True,,arXiv,Not available,On the performance of approximate equilibria in congestion games,965af3ddfa05a87b0d62ae20a96d4772,http://arxiv.org/abs/0804.3160v2
14793,"  Game-theoretic models relevant for computer science applications usually
feature a large number of players. The goal of this paper is to develop an
analytical framework for bounding the price of anarchy in such models. We
demonstrate the wide applicability of our framework through instantiations for
several well-studied models, including simultaneous single-item auctions,
greedy combinatorial auctions, and routing games. In all cases, we identify
conditions under which the POA of large games is much better than that of
worst-case instances. Our results also give new senses in which simple auctions
can perform almost as well as optimal ones in realistic settings.
",michal feldman,,2015.0,,arXiv,Feldman2015,True,,arXiv,Not available,The Price of Anarchy in Large Games,cc2d5e36e476d9dec9f804d721f93269,http://arxiv.org/abs/1503.04755v2
14794,"  We study routing behavior in transportation networks with mixed autonomy,
that is, networks in which a fraction of the vehicles on each road are equipped
with autonomous capabilities such as adaptive cruise control that enable
reduced headways and increased road capacity. Motivated by capacity models
developed for such roads with mixed autonomy, we consider transportation
networks in which the delay on each road or link is an affine function of two
quantities: the number of vehicles with autonomous capabilities on the link and
the number of regular vehicles on the link. We particularly study the price of
anarchy for such networks, that is, the ratio of the total delay experienced by
selfish routing to the socially optimal routing policy. Unlike the case when
all vehicles are of the same type, for which the price of anarchy is known to
be bounded, we first show that the price of anarchy can be arbitrarily large
for such mixed autonomous networks. Next, we define a notion of asymmetry equal
to the maximum possible travel time improvement due to the presence of
autonomous vehicles. We show that when the degree of asymmetry of all links in
the network is bounded by a factor less than 4, the price of anarchy is
bounded. We also bound the bicriteria, which is a bound on the cost of
selfishly routing traffic compared to the cost of optimally routing additional
traffic. These bounds depend on the degree of asymmetry and recover classical
bounds on the price of anarchy and bicriteria in the case when no asymmetry
exists. Further, we show with examples that these bound are tight in particular
cases.
",daniel lazar,,2017.0,,arXiv,Lazar2017,True,,arXiv,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy,77131436034b7eb15cda554fd65c5bbc,http://arxiv.org/abs/1710.07867v1
14795,"  We study routing behavior in transportation networks with mixed autonomy,
that is, networks in which a fraction of the vehicles on each road are equipped
with autonomous capabilities such as adaptive cruise control that enable
reduced headways and increased road capacity. Motivated by capacity models
developed for such roads with mixed autonomy, we consider transportation
networks in which the delay on each road or link is an affine function of two
quantities: the number of vehicles with autonomous capabilities on the link and
the number of regular vehicles on the link. We particularly study the price of
anarchy for such networks, that is, the ratio of the total delay experienced by
selfish routing to the socially optimal routing policy. Unlike the case when
all vehicles are of the same type, for which the price of anarchy is known to
be bounded, we first show that the price of anarchy can be arbitrarily large
for such mixed autonomous networks. Next, we define a notion of asymmetry equal
to the maximum possible travel time improvement due to the presence of
autonomous vehicles. We show that when the degree of asymmetry of all links in
the network is bounded by a factor less than 4, the price of anarchy is
bounded. We also bound the bicriteria, which is a bound on the cost of
selfishly routing traffic compared to the cost of optimally routing additional
traffic. These bounds depend on the degree of asymmetry and recover classical
bounds on the price of anarchy and bicriteria in the case when no asymmetry
exists. Further, we show with examples that these bound are tight in particular
cases.
",samuel coogan,,2017.0,,arXiv,Lazar2017,True,,arXiv,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy,77131436034b7eb15cda554fd65c5bbc,http://arxiv.org/abs/1710.07867v1
14796,"  We study routing behavior in transportation networks with mixed autonomy,
that is, networks in which a fraction of the vehicles on each road are equipped
with autonomous capabilities such as adaptive cruise control that enable
reduced headways and increased road capacity. Motivated by capacity models
developed for such roads with mixed autonomy, we consider transportation
networks in which the delay on each road or link is an affine function of two
quantities: the number of vehicles with autonomous capabilities on the link and
the number of regular vehicles on the link. We particularly study the price of
anarchy for such networks, that is, the ratio of the total delay experienced by
selfish routing to the socially optimal routing policy. Unlike the case when
all vehicles are of the same type, for which the price of anarchy is known to
be bounded, we first show that the price of anarchy can be arbitrarily large
for such mixed autonomous networks. Next, we define a notion of asymmetry equal
to the maximum possible travel time improvement due to the presence of
autonomous vehicles. We show that when the degree of asymmetry of all links in
the network is bounded by a factor less than 4, the price of anarchy is
bounded. We also bound the bicriteria, which is a bound on the cost of
selfishly routing traffic compared to the cost of optimally routing additional
traffic. These bounds depend on the degree of asymmetry and recover classical
bounds on the price of anarchy and bicriteria in the case when no asymmetry
exists. Further, we show with examples that these bound are tight in particular
cases.
",ramtin pedarsani,,2017.0,,arXiv,Lazar2017,True,,arXiv,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy,77131436034b7eb15cda554fd65c5bbc,http://arxiv.org/abs/1710.07867v1
14797,"  This paper examines the behavior of the price of anarchy as a function of the
traffic inflow in nonatomic congestion games with multiple origin-destination
(O/D) pairs. Empirical studies in real-world networks show that the price of
anarchy is close to 1 in both light and heavy traffic, thus raising the
question: can these observations be justified theoretically? We first show that
this is not always the case: the price of anarchy may remain a positive
distance away from 1 for all values of the traffic inflow, even in simple
three-link networks with a single O/D pair and smooth, convex costs. On the
other hand, for a large class of cost functions (including all polynomials),
the price of anarchy does converge to 1 in both heavy and light traffic,
irrespective of the network topology and the number of O/D pairs in the
network. We also examine the rate of convergence of the price of anarchy, and
we show that it follows a power law whose degree can be computed explicitly
when the network's cost functions are polynomials.
",riccardo colini-baldeschi,,2017.0,,arXiv,Colini-Baldeschi2017,True,,arXiv,Not available,"When is selfish routing bad? The price of anarchy in light and heavy
  traffic",d34dfff78af759ec38c705afc90a97c9,http://arxiv.org/abs/1703.00927v2
14798,"  This paper examines the behavior of the price of anarchy as a function of the
traffic inflow in nonatomic congestion games with multiple origin-destination
(O/D) pairs. Empirical studies in real-world networks show that the price of
anarchy is close to 1 in both light and heavy traffic, thus raising the
question: can these observations be justified theoretically? We first show that
this is not always the case: the price of anarchy may remain a positive
distance away from 1 for all values of the traffic inflow, even in simple
three-link networks with a single O/D pair and smooth, convex costs. On the
other hand, for a large class of cost functions (including all polynomials),
the price of anarchy does converge to 1 in both heavy and light traffic,
irrespective of the network topology and the number of O/D pairs in the
network. We also examine the rate of convergence of the price of anarchy, and
we show that it follows a power law whose degree can be computed explicitly
when the network's cost functions are polynomials.
",roberto cominetti,,2017.0,,arXiv,Colini-Baldeschi2017,True,,arXiv,Not available,"When is selfish routing bad? The price of anarchy in light and heavy
  traffic",d34dfff78af759ec38c705afc90a97c9,http://arxiv.org/abs/1703.00927v2
14799,"  This paper examines the behavior of the price of anarchy as a function of the
traffic inflow in nonatomic congestion games with multiple origin-destination
(O/D) pairs. Empirical studies in real-world networks show that the price of
anarchy is close to 1 in both light and heavy traffic, thus raising the
question: can these observations be justified theoretically? We first show that
this is not always the case: the price of anarchy may remain a positive
distance away from 1 for all values of the traffic inflow, even in simple
three-link networks with a single O/D pair and smooth, convex costs. On the
other hand, for a large class of cost functions (including all polynomials),
the price of anarchy does converge to 1 in both heavy and light traffic,
irrespective of the network topology and the number of O/D pairs in the
network. We also examine the rate of convergence of the price of anarchy, and
we show that it follows a power law whose degree can be computed explicitly
when the network's cost functions are polynomials.
",panayotis mertikopoulos,,2017.0,,arXiv,Colini-Baldeschi2017,True,,arXiv,Not available,"When is selfish routing bad? The price of anarchy in light and heavy
  traffic",d34dfff78af759ec38c705afc90a97c9,http://arxiv.org/abs/1703.00927v2
14800,"  This paper examines the behavior of the price of anarchy as a function of the
traffic inflow in nonatomic congestion games with multiple origin-destination
(O/D) pairs. Empirical studies in real-world networks show that the price of
anarchy is close to 1 in both light and heavy traffic, thus raising the
question: can these observations be justified theoretically? We first show that
this is not always the case: the price of anarchy may remain a positive
distance away from 1 for all values of the traffic inflow, even in simple
three-link networks with a single O/D pair and smooth, convex costs. On the
other hand, for a large class of cost functions (including all polynomials),
the price of anarchy does converge to 1 in both heavy and light traffic,
irrespective of the network topology and the number of O/D pairs in the
network. We also examine the rate of convergence of the price of anarchy, and
we show that it follows a power law whose degree can be computed explicitly
when the network's cost functions are polynomials.
",marco scarsini,,2017.0,,arXiv,Colini-Baldeschi2017,True,,arXiv,Not available,"When is selfish routing bad? The price of anarchy in light and heavy
  traffic",d34dfff78af759ec38c705afc90a97c9,http://arxiv.org/abs/1703.00927v2
14801,"  Many algorithms that are originally designed without explicitly considering
incentive properties are later combined with simple pricing rules and used as
mechanisms. The resulting mechanisms are often natural and simple to
understand. But how good are these algorithms as mechanisms? Truthful reporting
of valuations is typically not a dominant strategy (certainly not with a
pay-your-bid, first-price rule, but it is likely not a good strategy even with
a critical value, or second-price style rule either). Our goal is to show that
a wide class of approximation algorithms yields this way mechanisms with low
Price of Anarchy.
  The seminal result of Lucier and Borodin [SODA 2010] shows that combining a
greedy algorithm that is an $\alpha$-approximation algorithm with a
pay-your-bid payment rule yields a mechanism whose Price of Anarchy is
$O(\alpha)$. In this paper we significantly extend the class of algorithms for
which such a result is available by showing that this close connection between
approximation ratio on the one hand and Price of Anarchy on the other also
holds for the design principle of relaxation and rounding provided that the
relaxation is smooth and the rounding is oblivious.
  We demonstrate the far-reaching consequences of our result by showing its
implications for sparse packing integer programs, such as multi-unit auctions
and generalized matching, for the maximum traveling salesman problem, for
combinatorial auctions, and for single source unsplittable flow problems. In
all these problems our approach leads to novel simple, near-optimal mechanisms
whose Price of Anarchy either matches or beats the performance guarantees of
known mechanisms.
",paul dutting,,2015.0,,arXiv,Dütting2015,True,,arXiv,Not available,Algorithms as Mechanisms: The Price of Anarchy of Relax-and-Round,391cf610e06070cd699a7c0acbb5f2ba,http://arxiv.org/abs/1511.09208v1
14802,"  Game-theoretic models relevant for computer science applications usually
feature a large number of players. The goal of this paper is to develop an
analytical framework for bounding the price of anarchy in such models. We
demonstrate the wide applicability of our framework through instantiations for
several well-studied models, including simultaneous single-item auctions,
greedy combinatorial auctions, and routing games. In all cases, we identify
conditions under which the POA of large games is much better than that of
worst-case instances. Our results also give new senses in which simple auctions
can perform almost as well as optimal ones in realistic settings.
",nicole immorlica,,2015.0,,arXiv,Feldman2015,True,,arXiv,Not available,The Price of Anarchy in Large Games,cc2d5e36e476d9dec9f804d721f93269,http://arxiv.org/abs/1503.04755v2
14803,"  Many algorithms that are originally designed without explicitly considering
incentive properties are later combined with simple pricing rules and used as
mechanisms. The resulting mechanisms are often natural and simple to
understand. But how good are these algorithms as mechanisms? Truthful reporting
of valuations is typically not a dominant strategy (certainly not with a
pay-your-bid, first-price rule, but it is likely not a good strategy even with
a critical value, or second-price style rule either). Our goal is to show that
a wide class of approximation algorithms yields this way mechanisms with low
Price of Anarchy.
  The seminal result of Lucier and Borodin [SODA 2010] shows that combining a
greedy algorithm that is an $\alpha$-approximation algorithm with a
pay-your-bid payment rule yields a mechanism whose Price of Anarchy is
$O(\alpha)$. In this paper we significantly extend the class of algorithms for
which such a result is available by showing that this close connection between
approximation ratio on the one hand and Price of Anarchy on the other also
holds for the design principle of relaxation and rounding provided that the
relaxation is smooth and the rounding is oblivious.
  We demonstrate the far-reaching consequences of our result by showing its
implications for sparse packing integer programs, such as multi-unit auctions
and generalized matching, for the maximum traveling salesman problem, for
combinatorial auctions, and for single source unsplittable flow problems. In
all these problems our approach leads to novel simple, near-optimal mechanisms
whose Price of Anarchy either matches or beats the performance guarantees of
known mechanisms.
",thomas kesselheim,,2015.0,,arXiv,Dütting2015,True,,arXiv,Not available,Algorithms as Mechanisms: The Price of Anarchy of Relax-and-Round,391cf610e06070cd699a7c0acbb5f2ba,http://arxiv.org/abs/1511.09208v1
14804,"  Many algorithms that are originally designed without explicitly considering
incentive properties are later combined with simple pricing rules and used as
mechanisms. The resulting mechanisms are often natural and simple to
understand. But how good are these algorithms as mechanisms? Truthful reporting
of valuations is typically not a dominant strategy (certainly not with a
pay-your-bid, first-price rule, but it is likely not a good strategy even with
a critical value, or second-price style rule either). Our goal is to show that
a wide class of approximation algorithms yields this way mechanisms with low
Price of Anarchy.
  The seminal result of Lucier and Borodin [SODA 2010] shows that combining a
greedy algorithm that is an $\alpha$-approximation algorithm with a
pay-your-bid payment rule yields a mechanism whose Price of Anarchy is
$O(\alpha)$. In this paper we significantly extend the class of algorithms for
which such a result is available by showing that this close connection between
approximation ratio on the one hand and Price of Anarchy on the other also
holds for the design principle of relaxation and rounding provided that the
relaxation is smooth and the rounding is oblivious.
  We demonstrate the far-reaching consequences of our result by showing its
implications for sparse packing integer programs, such as multi-unit auctions
and generalized matching, for the maximum traveling salesman problem, for
combinatorial auctions, and for single source unsplittable flow problems. In
all these problems our approach leads to novel simple, near-optimal mechanisms
whose Price of Anarchy either matches or beats the performance guarantees of
known mechanisms.
",eva tardos,,2015.0,,arXiv,Dütting2015,True,,arXiv,Not available,Algorithms as Mechanisms: The Price of Anarchy of Relax-and-Round,391cf610e06070cd699a7c0acbb5f2ba,http://arxiv.org/abs/1511.09208v1
14805,"  Price of anarchy, the performance ratio, which could characterize the loss of
efficiency of the distributed supply chain management compared with the
integrated supply chain management is discussed by utilizing newsvendor problem
in single period which is well-known. In particular, some of remarkable
distributed policies are handled, the performance ratios in each case which
have been investigated in the previous works are analyzed theoretically and the
tighter upper bound of price of anarchy and the lower bound are presented.
Furthermore our approach is developed based on a generalized framework and a
geometric interpretation of price of anarchy is appeared via the literature of
convex optimization.
",t. shinzato,,2009.0,,arXiv,Shinzato2009,True,,arXiv,Not available,"Improved and Developed Upper Bound of Price of Anarchy in Two Echelon
  Case",4ec6481c509fff334e388eefdaabd201,http://arxiv.org/abs/0906.5489v1
14806,"  Price of anarchy, the performance ratio, which could characterize the loss of
efficiency of the distributed supply chain management compared with the
integrated supply chain management is discussed by utilizing newsvendor problem
in single period which is well-known. In particular, some of remarkable
distributed policies are handled, the performance ratios in each case which
have been investigated in the previous works are analyzed theoretically and the
tighter upper bound of price of anarchy and the lower bound are presented.
Furthermore our approach is developed based on a generalized framework and a
geometric interpretation of price of anarchy is appeared via the literature of
convex optimization.
",i. kaku,,2009.0,,arXiv,Shinzato2009,True,,arXiv,Not available,"Improved and Developed Upper Bound of Price of Anarchy in Two Echelon
  Case",4ec6481c509fff334e388eefdaabd201,http://arxiv.org/abs/0906.5489v1
14807,"  We present a new class of vertex cover and set cover games. The price of
anarchy bounds match the best known constant factor approximation guarantees
for the centralized optimization problems for linear and also for submodular
costs -- in contrast to all previously studied covering games, where the price
of anarchy cannot be bounded by a constant (e.g. [6, 7, 11, 5, 2]). In
particular, we describe a vertex cover game with a price of anarchy of 2. The
rules of the games capture the structure of the linear programming relaxations
of the underlying optimization problems, and our bounds are established by
analyzing these relaxations. Furthermore, for linear costs we exhibit linear
time best response dynamics that converge to these almost optimal Nash
equilibria. These dynamics mimic the classical greedy approximation algorithm
of Bar-Yehuda and Even [3].
",georgios piliouras,,2012.0,,arXiv,Piliouras2012,True,,arXiv,Not available,LP-based Covering Games with Low Price of Anarchy,bfe323321ed7081918544235a10439a8,http://arxiv.org/abs/1203.0050v1
14808,"  We present a new class of vertex cover and set cover games. The price of
anarchy bounds match the best known constant factor approximation guarantees
for the centralized optimization problems for linear and also for submodular
costs -- in contrast to all previously studied covering games, where the price
of anarchy cannot be bounded by a constant (e.g. [6, 7, 11, 5, 2]). In
particular, we describe a vertex cover game with a price of anarchy of 2. The
rules of the games capture the structure of the linear programming relaxations
of the underlying optimization problems, and our bounds are established by
analyzing these relaxations. Furthermore, for linear costs we exhibit linear
time best response dynamics that converge to these almost optimal Nash
equilibria. These dynamics mimic the classical greedy approximation algorithm
of Bar-Yehuda and Even [3].
",tomas valla,,2012.0,,arXiv,Piliouras2012,True,,arXiv,Not available,LP-based Covering Games with Low Price of Anarchy,bfe323321ed7081918544235a10439a8,http://arxiv.org/abs/1203.0050v1
14809,"  We present a new class of vertex cover and set cover games. The price of
anarchy bounds match the best known constant factor approximation guarantees
for the centralized optimization problems for linear and also for submodular
costs -- in contrast to all previously studied covering games, where the price
of anarchy cannot be bounded by a constant (e.g. [6, 7, 11, 5, 2]). In
particular, we describe a vertex cover game with a price of anarchy of 2. The
rules of the games capture the structure of the linear programming relaxations
of the underlying optimization problems, and our bounds are established by
analyzing these relaxations. Furthermore, for linear costs we exhibit linear
time best response dynamics that converge to these almost optimal Nash
equilibria. These dynamics mimic the classical greedy approximation algorithm
of Bar-Yehuda and Even [3].
",laszlo vegh,,2012.0,,arXiv,Piliouras2012,True,,arXiv,Not available,LP-based Covering Games with Low Price of Anarchy,bfe323321ed7081918544235a10439a8,http://arxiv.org/abs/1203.0050v1
14810,"  This paper studies the performance of Mobile Ad hoc Networks (MANETs) when
the nodes, that form a Poisson point process, selfishly choose their Medium
Access Probability (MAP). We consider goodput and delay as the performance
metric that each node is interested in optimizing taking into account the
transmission energy costs. We introduce a pricing scheme based on the
transmission energy requirements and compute the symmetric Nash equilibria of
the game in closed form. It is shown that by appropriately pricing the nodes,
the selfish behavior of the nodes can be used to achieve the social optimum at
equilibrium. The Price of Anarchy is then analyzed for these games. For the
game with delay based utility, we bound the price of anarchy and study the
effect of the price factor. For the game with goodput based utility, it is
shown that price of anarchy is infinite at the price factor that achieves the
global optima.
",manjesh hanawal,,2011.0,,arXiv,Hanawal2011,True,,arXiv,Not available,Stochastic Geometry based Medium Access Games in Mobile Ad hoc Networks,45e56fd4186ed4418c25e6f7a998c2c9,http://arxiv.org/abs/1112.3741v2
14811,"  This paper studies the performance of Mobile Ad hoc Networks (MANETs) when
the nodes, that form a Poisson point process, selfishly choose their Medium
Access Probability (MAP). We consider goodput and delay as the performance
metric that each node is interested in optimizing taking into account the
transmission energy costs. We introduce a pricing scheme based on the
transmission energy requirements and compute the symmetric Nash equilibria of
the game in closed form. It is shown that by appropriately pricing the nodes,
the selfish behavior of the nodes can be used to achieve the social optimum at
equilibrium. The Price of Anarchy is then analyzed for these games. For the
game with delay based utility, we bound the price of anarchy and study the
effect of the price factor. For the game with goodput based utility, it is
shown that price of anarchy is infinite at the price factor that achieves the
global optima.
",eitan altman,,2011.0,,arXiv,Hanawal2011,True,,arXiv,Not available,Stochastic Geometry based Medium Access Games in Mobile Ad hoc Networks,45e56fd4186ed4418c25e6f7a998c2c9,http://arxiv.org/abs/1112.3741v2
14812,"  This paper studies the performance of Mobile Ad hoc Networks (MANETs) when
the nodes, that form a Poisson point process, selfishly choose their Medium
Access Probability (MAP). We consider goodput and delay as the performance
metric that each node is interested in optimizing taking into account the
transmission energy costs. We introduce a pricing scheme based on the
transmission energy requirements and compute the symmetric Nash equilibria of
the game in closed form. It is shown that by appropriately pricing the nodes,
the selfish behavior of the nodes can be used to achieve the social optimum at
equilibrium. The Price of Anarchy is then analyzed for these games. For the
game with delay based utility, we bound the price of anarchy and study the
effect of the price factor. For the game with goodput based utility, it is
shown that price of anarchy is infinite at the price factor that achieves the
global optima.
",francois baccelli,,2011.0,,arXiv,Hanawal2011,True,,arXiv,Not available,Stochastic Geometry based Medium Access Games in Mobile Ad hoc Networks,45e56fd4186ed4418c25e6f7a998c2c9,http://arxiv.org/abs/1112.3741v2
14813,"  Game-theoretic models relevant for computer science applications usually
feature a large number of players. The goal of this paper is to develop an
analytical framework for bounding the price of anarchy in such models. We
demonstrate the wide applicability of our framework through instantiations for
several well-studied models, including simultaneous single-item auctions,
greedy combinatorial auctions, and routing games. In all cases, we identify
conditions under which the POA of large games is much better than that of
worst-case instances. Our results also give new senses in which simple auctions
can perform almost as well as optimal ones in realistic settings.
",brendan lucier,,2015.0,,arXiv,Feldman2015,True,,arXiv,Not available,The Price of Anarchy in Large Games,cc2d5e36e476d9dec9f804d721f93269,http://arxiv.org/abs/1503.04755v2
14814,"  We study {\em bottleneck congestion games} where the social cost is
determined by the worst congestion of any resource. These games directly relate
to network routing problems and also job-shop scheduling problems. In typical
bottleneck congestion games, the utility costs of the players are determined by
the worst congested resources that they use. However, the resulting Nash
equilibria are inefficient, since the price of anarchy is proportional on the
number of resources which can be high. Here we show that we can get smaller
price of anarchy with the bottleneck social cost metric. We introduce the {\em
polynomial bottleneck games} where the utility costs of the players are
polynomial functions of the congestion of the resources that they use. In
particular, the delay function for any resource $r$ is $C_{r}^\M$, where $C_r$
is the congestion measured as the number of players that use $r$, and $\M \geq
1$ is an integer constant that defines the degree of the polynomial. The
utility cost of a player is the sum of the individual delays of the resources
that it uses. The social cost of the game remains the same, namely, it is the
worst bottleneck resource congestion: $\max_{r} C_r$. We show that polynomial
bottleneck games are very efficient and give price of anarchy
$O(|R|^{1/(\M+1)})$, where $R$ is the set of resources. This price of anarchy
is tight, since we demonstrate a game with price of anarchy
$\Omega(|R|^{1/(\M+1)})$, for any $\M \geq 1$. We obtain our tight bounds by
using two proof techniques: {\em transformation}, which we use to convert
arbitrary games to simpler games, and {\em expansion}, which we use to bound
the price of anarchy in a simpler game.
",rajgopal kannan,,2010.0,,arXiv,Kannan2010,True,,arXiv,Not available,Polynomial Bottleneck Congestion Games with Optimal Price of Anarchy,1abcadede6a3253a6cc12bedfe8712f1,http://arxiv.org/abs/1010.4812v1
14815,"  We study {\em bottleneck congestion games} where the social cost is
determined by the worst congestion of any resource. These games directly relate
to network routing problems and also job-shop scheduling problems. In typical
bottleneck congestion games, the utility costs of the players are determined by
the worst congested resources that they use. However, the resulting Nash
equilibria are inefficient, since the price of anarchy is proportional on the
number of resources which can be high. Here we show that we can get smaller
price of anarchy with the bottleneck social cost metric. We introduce the {\em
polynomial bottleneck games} where the utility costs of the players are
polynomial functions of the congestion of the resources that they use. In
particular, the delay function for any resource $r$ is $C_{r}^\M$, where $C_r$
is the congestion measured as the number of players that use $r$, and $\M \geq
1$ is an integer constant that defines the degree of the polynomial. The
utility cost of a player is the sum of the individual delays of the resources
that it uses. The social cost of the game remains the same, namely, it is the
worst bottleneck resource congestion: $\max_{r} C_r$. We show that polynomial
bottleneck games are very efficient and give price of anarchy
$O(|R|^{1/(\M+1)})$, where $R$ is the set of resources. This price of anarchy
is tight, since we demonstrate a game with price of anarchy
$\Omega(|R|^{1/(\M+1)})$, for any $\M \geq 1$. We obtain our tight bounds by
using two proof techniques: {\em transformation}, which we use to convert
arbitrary games to simpler games, and {\em expansion}, which we use to bound
the price of anarchy in a simpler game.
",costas busch,,2010.0,,arXiv,Kannan2010,True,,arXiv,Not available,Polynomial Bottleneck Congestion Games with Optimal Price of Anarchy,1abcadede6a3253a6cc12bedfe8712f1,http://arxiv.org/abs/1010.4812v1
14816,"  We study {\em bottleneck congestion games} where the social cost is
determined by the worst congestion of any resource. These games directly relate
to network routing problems and also job-shop scheduling problems. In typical
bottleneck congestion games, the utility costs of the players are determined by
the worst congested resources that they use. However, the resulting Nash
equilibria are inefficient, since the price of anarchy is proportional on the
number of resources which can be high. Here we show that we can get smaller
price of anarchy with the bottleneck social cost metric. We introduce the {\em
polynomial bottleneck games} where the utility costs of the players are
polynomial functions of the congestion of the resources that they use. In
particular, the delay function for any resource $r$ is $C_{r}^\M$, where $C_r$
is the congestion measured as the number of players that use $r$, and $\M \geq
1$ is an integer constant that defines the degree of the polynomial. The
utility cost of a player is the sum of the individual delays of the resources
that it uses. The social cost of the game remains the same, namely, it is the
worst bottleneck resource congestion: $\max_{r} C_r$. We show that polynomial
bottleneck games are very efficient and give price of anarchy
$O(|R|^{1/(\M+1)})$, where $R$ is the set of resources. This price of anarchy
is tight, since we demonstrate a game with price of anarchy
$\Omega(|R|^{1/(\M+1)})$, for any $\M \geq 1$. We obtain our tight bounds by
using two proof techniques: {\em transformation}, which we use to convert
arbitrary games to simpler games, and {\em expansion}, which we use to bound
the price of anarchy in a simpler game.
",athanasios vasilakos,,2010.0,,arXiv,Kannan2010,True,,arXiv,Not available,Polynomial Bottleneck Congestion Games with Optimal Price of Anarchy,1abcadede6a3253a6cc12bedfe8712f1,http://arxiv.org/abs/1010.4812v1
14817,"  The price of anarchy (PoA) has been widely used in static games to quantify
the loss of efficiency due to noncooperation. Here, we extend this concept to a
general differential games framework. In addition, we introduce the price of
information (PoI) to characterize comparative game performances under different
information structures, as well as the price of cooperation to capture the
extent of benefit or loss a player accrues as a result of altruistic behavior.
We further characterize PoA and PoI for a class of scalar linear quadratic
differential games under open-loop and closed-loop feedback information
structures. We also obtain some explicit bounds on these indices in a large
population regime.
",tamer basar,,2011.0,,arXiv,Basar2011,True,,arXiv,Not available,"Prices of Anarchy, Information, and Cooperation in Differential Games",b99994dc98f6268f776fd0f00d7a22f5,http://arxiv.org/abs/1103.2579v1
14818,"  The price of anarchy (PoA) has been widely used in static games to quantify
the loss of efficiency due to noncooperation. Here, we extend this concept to a
general differential games framework. In addition, we introduce the price of
information (PoI) to characterize comparative game performances under different
information structures, as well as the price of cooperation to capture the
extent of benefit or loss a player accrues as a result of altruistic behavior.
We further characterize PoA and PoI for a class of scalar linear quadratic
differential games under open-loop and closed-loop feedback information
structures. We also obtain some explicit bounds on these indices in a large
population regime.
",quanyan zhu,,2011.0,,arXiv,Basar2011,True,,arXiv,Not available,"Prices of Anarchy, Information, and Cooperation in Differential Games",b99994dc98f6268f776fd0f00d7a22f5,http://arxiv.org/abs/1103.2579v1
14819,"  We study network formation with n players and link cost \alpha > 0. After the
network is built, an adversary randomly deletes one link according to a certain
probability distribution. Cost for player v incorporates the expected number of
players to which v will become disconnected. We show existence of equilibria
and a price of stability of 1+o(1) under moderate assumptions on the adversary
and n \geq 9.
  As the main result, we prove bounds on the price of anarchy for two special
adversaries: one removes a link chosen uniformly at random, while the other
removes a link that causes a maximum number of player pairs to be separated.
For unilateral link formation we show a bound of O(1) on the price of anarchy
for both adversaries, the constant being bounded by 10+o(1) and 8+o(1),
respectively. For bilateral link formation we show O(1+\sqrt{n/\alpha}) for one
adversary (if \alpha > 1/2), and \Theta(n) for the other (if \alpha > 2
considered constant and n \geq 9). The latter is the worst that can happen for
any adversary in this model (if \alpha = \Omega(1)). This points out
substantial differences between unilateral and bilateral link formation.
",lasse kliemann,,2012.0,,arXiv,Kliemann2012,True,,arXiv,Not available,The Price of Anarchy for Network Formation in an Adversary Model,7245126714ce33527ac06c5a6ae4ecc9,http://arxiv.org/abs/1202.5025v1
14820,"  We study assignment games in which jobs select machines, and in which certain
pairs of jobs may conflict, which is to say they may incur an additional cost
when they are both assigned to the same machine, beyond that associated with
the increase in load. Questions regarding such interactions apply beyond
allocating jobs to machines: when people in a social network choose to align
themselves with a group or party, they typically do so based upon not only the
inherent quality of that group, but also who amongst their friends (or enemies)
choose that group as well. We show how semi-smoothness, a recently introduced
generalization of smoothness, is necessary to find tight or near-tight bounds
on the price of total anarchy, and thus on the quality of correlated and Nash
equilibria, for several natural job-assignment games with interacting jobs. For
most cases, our bounds on the price of total anarchy are either exactly 2 or
approach 2. We also prove new convergence results implied by semi-smoothness
for our games. Finally we consider coalitional deviations, and prove results
about the existence and quality of Strong equilibrium.
",elliot anshelevich,,2013.0,,arXiv,Anshelevich2013,True,,arXiv,Not available,"Assignment Games with Conflicts: Price of Total Anarchy and Convergence
  Results via Semi-Smoothness",e4ddcb9842b0f5c8de15ad733006d458,http://arxiv.org/abs/1304.5149v2
14821,"  We study assignment games in which jobs select machines, and in which certain
pairs of jobs may conflict, which is to say they may incur an additional cost
when they are both assigned to the same machine, beyond that associated with
the increase in load. Questions regarding such interactions apply beyond
allocating jobs to machines: when people in a social network choose to align
themselves with a group or party, they typically do so based upon not only the
inherent quality of that group, but also who amongst their friends (or enemies)
choose that group as well. We show how semi-smoothness, a recently introduced
generalization of smoothness, is necessary to find tight or near-tight bounds
on the price of total anarchy, and thus on the quality of correlated and Nash
equilibria, for several natural job-assignment games with interacting jobs. For
most cases, our bounds on the price of total anarchy are either exactly 2 or
approach 2. We also prove new convergence results implied by semi-smoothness
for our games. Finally we consider coalitional deviations, and prove results
about the existence and quality of Strong equilibrium.
",john postl,,2013.0,,arXiv,Anshelevich2013,True,,arXiv,Not available,"Assignment Games with Conflicts: Price of Total Anarchy and Convergence
  Results via Semi-Smoothness",e4ddcb9842b0f5c8de15ad733006d458,http://arxiv.org/abs/1304.5149v2
14822,"  We study assignment games in which jobs select machines, and in which certain
pairs of jobs may conflict, which is to say they may incur an additional cost
when they are both assigned to the same machine, beyond that associated with
the increase in load. Questions regarding such interactions apply beyond
allocating jobs to machines: when people in a social network choose to align
themselves with a group or party, they typically do so based upon not only the
inherent quality of that group, but also who amongst their friends (or enemies)
choose that group as well. We show how semi-smoothness, a recently introduced
generalization of smoothness, is necessary to find tight or near-tight bounds
on the price of total anarchy, and thus on the quality of correlated and Nash
equilibria, for several natural job-assignment games with interacting jobs. For
most cases, our bounds on the price of total anarchy are either exactly 2 or
approach 2. We also prove new convergence results implied by semi-smoothness
for our games. Finally we consider coalitional deviations, and prove results
about the existence and quality of Strong equilibrium.
",tom wexler,,2013.0,,arXiv,Anshelevich2013,True,,arXiv,Not available,"Assignment Games with Conflicts: Price of Total Anarchy and Convergence
  Results via Semi-Smoothness",e4ddcb9842b0f5c8de15ad733006d458,http://arxiv.org/abs/1304.5149v2
14823,"  The Generalized Second Price (GSP) auction is the primary auction used for
monetizing the use of the Internet. It is well-known that truthtelling is not a
dominant strategy in this auction and that inefficient equilibria can arise. In
this paper we study the space of equilibria in GSP, and quantify the efficiency
loss that can arise in equilibria under a wide range of sources of uncertainty,
as well as in the full information setting. The traditional Bayesian game
models uncertainty in the valuations (types) of the participants. The
Generalized Second Price (GSP) auction gives rise to a further form of
uncertainty: the selection of quality factors resulting in uncertainty about
the behavior of the underlying ad allocation algorithm. The bounds we obtain
apply to both forms of uncertainty, and are robust in the sense that they apply
under various perturbations of the solution concept, extending to models with
information asymmetries and bounded rationality in the form of learning
strategies.
  We present a constant bound (2.927) on the factor of the efficiency loss
(\emph{price of anarchy}) of the corresponding game for the Bayesian model of
partial information about other participants and about ad quality factors. For
the full information setting, we prove a surprisingly low upper bound of 1.282
on the price of anarchy over pure Nash equilibria, nearly matching a lower
bound of 1.259 for the case of three advertisers. Further, we do not require
that the system reaches equilibrium, and give similarly low bounds also on the
quality degradation for any no-regret learning outcome. Our conclusion is that
the number of advertisers in the auction has almost no impact on the price of
anarchy, and that the efficiency of GSP is very robust with respect to the
belief and rationality assumptions imposed on the participants.
",ioannis caragiannis,,2012.0,,arXiv,Caragiannis2012,True,,arXiv,Not available,"Bounding the inefficiency of outcomes in generalized second price
  auctions",afa8437918c95216d24e097281ad5381,http://arxiv.org/abs/1201.6429v2
14824,"  Game-theoretic models relevant for computer science applications usually
feature a large number of players. The goal of this paper is to develop an
analytical framework for bounding the price of anarchy in such models. We
demonstrate the wide applicability of our framework through instantiations for
several well-studied models, including simultaneous single-item auctions,
greedy combinatorial auctions, and routing games. In all cases, we identify
conditions under which the POA of large games is much better than that of
worst-case instances. Our results also give new senses in which simple auctions
can perform almost as well as optimal ones in realistic settings.
",tim roughgarden,,2015.0,,arXiv,Feldman2015,True,,arXiv,Not available,The Price of Anarchy in Large Games,cc2d5e36e476d9dec9f804d721f93269,http://arxiv.org/abs/1503.04755v2
14825,"  The Generalized Second Price (GSP) auction is the primary auction used for
monetizing the use of the Internet. It is well-known that truthtelling is not a
dominant strategy in this auction and that inefficient equilibria can arise. In
this paper we study the space of equilibria in GSP, and quantify the efficiency
loss that can arise in equilibria under a wide range of sources of uncertainty,
as well as in the full information setting. The traditional Bayesian game
models uncertainty in the valuations (types) of the participants. The
Generalized Second Price (GSP) auction gives rise to a further form of
uncertainty: the selection of quality factors resulting in uncertainty about
the behavior of the underlying ad allocation algorithm. The bounds we obtain
apply to both forms of uncertainty, and are robust in the sense that they apply
under various perturbations of the solution concept, extending to models with
information asymmetries and bounded rationality in the form of learning
strategies.
  We present a constant bound (2.927) on the factor of the efficiency loss
(\emph{price of anarchy}) of the corresponding game for the Bayesian model of
partial information about other participants and about ad quality factors. For
the full information setting, we prove a surprisingly low upper bound of 1.282
on the price of anarchy over pure Nash equilibria, nearly matching a lower
bound of 1.259 for the case of three advertisers. Further, we do not require
that the system reaches equilibrium, and give similarly low bounds also on the
quality degradation for any no-regret learning outcome. Our conclusion is that
the number of advertisers in the auction has almost no impact on the price of
anarchy, and that the efficiency of GSP is very robust with respect to the
belief and rationality assumptions imposed on the participants.
",christos kaklamanis,,2012.0,,arXiv,Caragiannis2012,True,,arXiv,Not available,"Bounding the inefficiency of outcomes in generalized second price
  auctions",afa8437918c95216d24e097281ad5381,http://arxiv.org/abs/1201.6429v2
14826,"  The Generalized Second Price (GSP) auction is the primary auction used for
monetizing the use of the Internet. It is well-known that truthtelling is not a
dominant strategy in this auction and that inefficient equilibria can arise. In
this paper we study the space of equilibria in GSP, and quantify the efficiency
loss that can arise in equilibria under a wide range of sources of uncertainty,
as well as in the full information setting. The traditional Bayesian game
models uncertainty in the valuations (types) of the participants. The
Generalized Second Price (GSP) auction gives rise to a further form of
uncertainty: the selection of quality factors resulting in uncertainty about
the behavior of the underlying ad allocation algorithm. The bounds we obtain
apply to both forms of uncertainty, and are robust in the sense that they apply
under various perturbations of the solution concept, extending to models with
information asymmetries and bounded rationality in the form of learning
strategies.
  We present a constant bound (2.927) on the factor of the efficiency loss
(\emph{price of anarchy}) of the corresponding game for the Bayesian model of
partial information about other participants and about ad quality factors. For
the full information setting, we prove a surprisingly low upper bound of 1.282
on the price of anarchy over pure Nash equilibria, nearly matching a lower
bound of 1.259 for the case of three advertisers. Further, we do not require
that the system reaches equilibrium, and give similarly low bounds also on the
quality degradation for any no-regret learning outcome. Our conclusion is that
the number of advertisers in the auction has almost no impact on the price of
anarchy, and that the efficiency of GSP is very robust with respect to the
belief and rationality assumptions imposed on the participants.
",panagiotis kanellopoulos,,2012.0,,arXiv,Caragiannis2012,True,,arXiv,Not available,"Bounding the inefficiency of outcomes in generalized second price
  auctions",afa8437918c95216d24e097281ad5381,http://arxiv.org/abs/1201.6429v2
14827,"  The Generalized Second Price (GSP) auction is the primary auction used for
monetizing the use of the Internet. It is well-known that truthtelling is not a
dominant strategy in this auction and that inefficient equilibria can arise. In
this paper we study the space of equilibria in GSP, and quantify the efficiency
loss that can arise in equilibria under a wide range of sources of uncertainty,
as well as in the full information setting. The traditional Bayesian game
models uncertainty in the valuations (types) of the participants. The
Generalized Second Price (GSP) auction gives rise to a further form of
uncertainty: the selection of quality factors resulting in uncertainty about
the behavior of the underlying ad allocation algorithm. The bounds we obtain
apply to both forms of uncertainty, and are robust in the sense that they apply
under various perturbations of the solution concept, extending to models with
information asymmetries and bounded rationality in the form of learning
strategies.
  We present a constant bound (2.927) on the factor of the efficiency loss
(\emph{price of anarchy}) of the corresponding game for the Bayesian model of
partial information about other participants and about ad quality factors. For
the full information setting, we prove a surprisingly low upper bound of 1.282
on the price of anarchy over pure Nash equilibria, nearly matching a lower
bound of 1.259 for the case of three advertisers. Further, we do not require
that the system reaches equilibrium, and give similarly low bounds also on the
quality degradation for any no-regret learning outcome. Our conclusion is that
the number of advertisers in the auction has almost no impact on the price of
anarchy, and that the efficiency of GSP is very robust with respect to the
belief and rationality assumptions imposed on the participants.
",maria kyropoulou,,2012.0,,arXiv,Caragiannis2012,True,,arXiv,Not available,"Bounding the inefficiency of outcomes in generalized second price
  auctions",afa8437918c95216d24e097281ad5381,http://arxiv.org/abs/1201.6429v2
14828,"  The Generalized Second Price (GSP) auction is the primary auction used for
monetizing the use of the Internet. It is well-known that truthtelling is not a
dominant strategy in this auction and that inefficient equilibria can arise. In
this paper we study the space of equilibria in GSP, and quantify the efficiency
loss that can arise in equilibria under a wide range of sources of uncertainty,
as well as in the full information setting. The traditional Bayesian game
models uncertainty in the valuations (types) of the participants. The
Generalized Second Price (GSP) auction gives rise to a further form of
uncertainty: the selection of quality factors resulting in uncertainty about
the behavior of the underlying ad allocation algorithm. The bounds we obtain
apply to both forms of uncertainty, and are robust in the sense that they apply
under various perturbations of the solution concept, extending to models with
information asymmetries and bounded rationality in the form of learning
strategies.
  We present a constant bound (2.927) on the factor of the efficiency loss
(\emph{price of anarchy}) of the corresponding game for the Bayesian model of
partial information about other participants and about ad quality factors. For
the full information setting, we prove a surprisingly low upper bound of 1.282
on the price of anarchy over pure Nash equilibria, nearly matching a lower
bound of 1.259 for the case of three advertisers. Further, we do not require
that the system reaches equilibrium, and give similarly low bounds also on the
quality degradation for any no-regret learning outcome. Our conclusion is that
the number of advertisers in the auction has almost no impact on the price of
anarchy, and that the efficiency of GSP is very robust with respect to the
belief and rationality assumptions imposed on the participants.
",brendan lucier,,2012.0,,arXiv,Caragiannis2012,True,,arXiv,Not available,"Bounding the inefficiency of outcomes in generalized second price
  auctions",afa8437918c95216d24e097281ad5381,http://arxiv.org/abs/1201.6429v2
14829,"  The Generalized Second Price (GSP) auction is the primary auction used for
monetizing the use of the Internet. It is well-known that truthtelling is not a
dominant strategy in this auction and that inefficient equilibria can arise. In
this paper we study the space of equilibria in GSP, and quantify the efficiency
loss that can arise in equilibria under a wide range of sources of uncertainty,
as well as in the full information setting. The traditional Bayesian game
models uncertainty in the valuations (types) of the participants. The
Generalized Second Price (GSP) auction gives rise to a further form of
uncertainty: the selection of quality factors resulting in uncertainty about
the behavior of the underlying ad allocation algorithm. The bounds we obtain
apply to both forms of uncertainty, and are robust in the sense that they apply
under various perturbations of the solution concept, extending to models with
information asymmetries and bounded rationality in the form of learning
strategies.
  We present a constant bound (2.927) on the factor of the efficiency loss
(\emph{price of anarchy}) of the corresponding game for the Bayesian model of
partial information about other participants and about ad quality factors. For
the full information setting, we prove a surprisingly low upper bound of 1.282
on the price of anarchy over pure Nash equilibria, nearly matching a lower
bound of 1.259 for the case of three advertisers. Further, we do not require
that the system reaches equilibrium, and give similarly low bounds also on the
quality degradation for any no-regret learning outcome. Our conclusion is that
the number of advertisers in the auction has almost no impact on the price of
anarchy, and that the efficiency of GSP is very robust with respect to the
belief and rationality assumptions imposed on the participants.
",renato leme,,2012.0,,arXiv,Caragiannis2012,True,,arXiv,Not available,"Bounding the inefficiency of outcomes in generalized second price
  auctions",afa8437918c95216d24e097281ad5381,http://arxiv.org/abs/1201.6429v2
14830,"  The Generalized Second Price (GSP) auction is the primary auction used for
monetizing the use of the Internet. It is well-known that truthtelling is not a
dominant strategy in this auction and that inefficient equilibria can arise. In
this paper we study the space of equilibria in GSP, and quantify the efficiency
loss that can arise in equilibria under a wide range of sources of uncertainty,
as well as in the full information setting. The traditional Bayesian game
models uncertainty in the valuations (types) of the participants. The
Generalized Second Price (GSP) auction gives rise to a further form of
uncertainty: the selection of quality factors resulting in uncertainty about
the behavior of the underlying ad allocation algorithm. The bounds we obtain
apply to both forms of uncertainty, and are robust in the sense that they apply
under various perturbations of the solution concept, extending to models with
information asymmetries and bounded rationality in the form of learning
strategies.
  We present a constant bound (2.927) on the factor of the efficiency loss
(\emph{price of anarchy}) of the corresponding game for the Bayesian model of
partial information about other participants and about ad quality factors. For
the full information setting, we prove a surprisingly low upper bound of 1.282
on the price of anarchy over pure Nash equilibria, nearly matching a lower
bound of 1.259 for the case of three advertisers. Further, we do not require
that the system reaches equilibrium, and give similarly low bounds also on the
quality degradation for any no-regret learning outcome. Our conclusion is that
the number of advertisers in the auction has almost no impact on the price of
anarchy, and that the efficiency of GSP is very robust with respect to the
belief and rationality assumptions imposed on the participants.
",eva tardos,,2012.0,,arXiv,Caragiannis2012,True,,arXiv,Not available,"Bounding the inefficiency of outcomes in generalized second price
  auctions",afa8437918c95216d24e097281ad5381,http://arxiv.org/abs/1201.6429v2
14831,"  In general, the games are played on a host graph, where each node is a
selfish independent agent (player) and each edge has a fixed link creation cost
\alpha. Together the agents create a network (a subgraph of the host graph)
while selfishly minimizing the link creation costs plus the sum of the
distances to all other players (usage cost). In this paper, we pursue two
important facets of the network creation game. First, we study extensively a
natural version of the game, called the cooperative model, where nodes can
collaborate and share the cost of creating any edge in the host graph. We prove
the first nontrivial bounds in this model, establishing that the price of
anarchy is polylogarithmic in n for all values of &#945; in complete host
graphs. This bound is the first result of this type for any version of the
network creation game; most previous general upper bounds are polynomial in n.
Interestingly, we also show that equilibrium graphs have polylogarithmic
diameter for the most natural range of \alpha (at most n polylg n). Second, we
study the impact of the natural assumption that the host graph is a general
graph, not necessarily complete. This model is a simple example of nonuniform
creation costs among the edges (effectively allowing weights of \alpha and
\infty). We prove the first assemblage of upper and lower bounds for this
context, stablishing nontrivial tight bounds for many ranges of \alpha, for
both the unilateral and cooperative versions of network creation. In
particular, we establish polynomial lower bounds for both versions and many
ranges of \alpha, even for this simple nonuniform cost model, which sharply
contrasts the conjectured constant bounds for these games in complete (uniform)
graphs.
",erik demaine,,2009.0,,"26th International Symposium on Theoretical Aspects of Computer
  Science STACS 2009 (2009) 301-312",Demaine2009,True,,arXiv,Not available,The Price of Anarchy in Cooperative Network Creation Games,91daa61a3dc6fcff54d274bc6f3807ac,http://arxiv.org/abs/0902.1400v1
14832,"  In general, the games are played on a host graph, where each node is a
selfish independent agent (player) and each edge has a fixed link creation cost
\alpha. Together the agents create a network (a subgraph of the host graph)
while selfishly minimizing the link creation costs plus the sum of the
distances to all other players (usage cost). In this paper, we pursue two
important facets of the network creation game. First, we study extensively a
natural version of the game, called the cooperative model, where nodes can
collaborate and share the cost of creating any edge in the host graph. We prove
the first nontrivial bounds in this model, establishing that the price of
anarchy is polylogarithmic in n for all values of &#945; in complete host
graphs. This bound is the first result of this type for any version of the
network creation game; most previous general upper bounds are polynomial in n.
Interestingly, we also show that equilibrium graphs have polylogarithmic
diameter for the most natural range of \alpha (at most n polylg n). Second, we
study the impact of the natural assumption that the host graph is a general
graph, not necessarily complete. This model is a simple example of nonuniform
creation costs among the edges (effectively allowing weights of \alpha and
\infty). We prove the first assemblage of upper and lower bounds for this
context, stablishing nontrivial tight bounds for many ranges of \alpha, for
both the unilateral and cooperative versions of network creation. In
particular, we establish polynomial lower bounds for both versions and many
ranges of \alpha, even for this simple nonuniform cost model, which sharply
contrasts the conjectured constant bounds for these games in complete (uniform)
graphs.
",mohammadtaghi hajiaghayi,,2009.0,,"26th International Symposium on Theoretical Aspects of Computer
  Science STACS 2009 (2009) 301-312",Demaine2009,True,,arXiv,Not available,The Price of Anarchy in Cooperative Network Creation Games,91daa61a3dc6fcff54d274bc6f3807ac,http://arxiv.org/abs/0902.1400v1
14833,"  In general, the games are played on a host graph, where each node is a
selfish independent agent (player) and each edge has a fixed link creation cost
\alpha. Together the agents create a network (a subgraph of the host graph)
while selfishly minimizing the link creation costs plus the sum of the
distances to all other players (usage cost). In this paper, we pursue two
important facets of the network creation game. First, we study extensively a
natural version of the game, called the cooperative model, where nodes can
collaborate and share the cost of creating any edge in the host graph. We prove
the first nontrivial bounds in this model, establishing that the price of
anarchy is polylogarithmic in n for all values of &#945; in complete host
graphs. This bound is the first result of this type for any version of the
network creation game; most previous general upper bounds are polynomial in n.
Interestingly, we also show that equilibrium graphs have polylogarithmic
diameter for the most natural range of \alpha (at most n polylg n). Second, we
study the impact of the natural assumption that the host graph is a general
graph, not necessarily complete. This model is a simple example of nonuniform
creation costs among the edges (effectively allowing weights of \alpha and
\infty). We prove the first assemblage of upper and lower bounds for this
context, stablishing nontrivial tight bounds for many ranges of \alpha, for
both the unilateral and cooperative versions of network creation. In
particular, we establish polynomial lower bounds for both versions and many
ranges of \alpha, even for this simple nonuniform cost model, which sharply
contrasts the conjectured constant bounds for these games in complete (uniform)
graphs.
",hamid mahini,,2009.0,,"26th International Symposium on Theoretical Aspects of Computer
  Science STACS 2009 (2009) 301-312",Demaine2009,True,,arXiv,Not available,The Price of Anarchy in Cooperative Network Creation Games,91daa61a3dc6fcff54d274bc6f3807ac,http://arxiv.org/abs/0902.1400v1
14834,"  In general, the games are played on a host graph, where each node is a
selfish independent agent (player) and each edge has a fixed link creation cost
\alpha. Together the agents create a network (a subgraph of the host graph)
while selfishly minimizing the link creation costs plus the sum of the
distances to all other players (usage cost). In this paper, we pursue two
important facets of the network creation game. First, we study extensively a
natural version of the game, called the cooperative model, where nodes can
collaborate and share the cost of creating any edge in the host graph. We prove
the first nontrivial bounds in this model, establishing that the price of
anarchy is polylogarithmic in n for all values of &#945; in complete host
graphs. This bound is the first result of this type for any version of the
network creation game; most previous general upper bounds are polynomial in n.
Interestingly, we also show that equilibrium graphs have polylogarithmic
diameter for the most natural range of \alpha (at most n polylg n). Second, we
study the impact of the natural assumption that the host graph is a general
graph, not necessarily complete. This model is a simple example of nonuniform
creation costs among the edges (effectively allowing weights of \alpha and
\infty). We prove the first assemblage of upper and lower bounds for this
context, stablishing nontrivial tight bounds for many ranges of \alpha, for
both the unilateral and cooperative versions of network creation. In
particular, we establish polynomial lower bounds for both versions and many
ranges of \alpha, even for this simple nonuniform cost model, which sharply
contrasts the conjectured constant bounds for these games in complete (uniform)
graphs.
",morteza zadimoghaddam,,2009.0,,"26th International Symposium on Theoretical Aspects of Computer
  Science STACS 2009 (2009) 301-312",Demaine2009,True,,arXiv,Not available,The Price of Anarchy in Cooperative Network Creation Games,91daa61a3dc6fcff54d274bc6f3807ac,http://arxiv.org/abs/0902.1400v1
14835,"  Game-theoretic models relevant for computer science applications usually
feature a large number of players. The goal of this paper is to develop an
analytical framework for bounding the price of anarchy in such models. We
demonstrate the wide applicability of our framework through instantiations for
several well-studied models, including simultaneous single-item auctions,
greedy combinatorial auctions, and routing games. In all cases, we identify
conditions under which the POA of large games is much better than that of
worst-case instances. Our results also give new senses in which simple auctions
can perform almost as well as optimal ones in realistic settings.
",vasilis syrgkanis,,2015.0,,arXiv,Feldman2015,True,,arXiv,Not available,The Price of Anarchy in Large Games,cc2d5e36e476d9dec9f804d721f93269,http://arxiv.org/abs/1503.04755v2
14836,"  Assume that a treasure is placed in one of $M$ boxes according to a known
distribution and that $k$ searchers are searching for it in parallel during $T$
rounds. We study the question of how to incentivize selfish players so that the
success probability, namely, the probability that at least one player finds the
treasure, would be maximized. We focus on congestion policies $C(s)$ that
specify the reward that a player receives if it is one of $s$ players that
(simultaneously) find the treasure for the first time. We show that the
exclusive policy, in which $C(1)=1$ and $C(s)=0$ for $s>1$, yields a price of
anarchy of $(1-(1-{1}/{k})^{k})^{-1}$. This is the best possible price among
all symmetric reward mechanisms. For this policy, we also have an explicit
description of a symmetric equilibrium, which is in some sense unique, and
moreover enjoys the best success probability among all symmetric profiles. For
general congestion policies, we show how to polynomially find, for any
$\theta>0$, a symmetric multiplicative $(1+\theta)(1+C(k))$-equilibrium.
  Together with a reward policy, a central entity can suggest players to play a
particular profile at equilibrium. For such purposes, we advocate the use of
symmetric equilibria. Besides being fair, symmetric equilibria can also become
highly robust to crashes of players. Indeed, in many cases, despite the fact
that some small fraction of players crash, symmetric equilibria remain
efficient in terms of their group performances and, at the same time, serve as
approximate equilibria. We show that this principle holds for a class of games,
which we call monotonously scalable games. This applies in particular to our
search game, assuming the natural sharing policy, in which $C(s)=1/s$. For the
exclusive policy, this general result does not hold, but we show that the
symmetric equilibrium is nevertheless robust under mild assumptions.
",amos korman,,2018.0,,arXiv,Korman2018,True,,arXiv,Not available,"Cooperative Search Games: Symmetric Equilibria, Robustness, and Price of
  Anarchy",98467e60f947e6897f2ba0ce466fc8bd,http://arxiv.org/abs/1811.01270v1
14837,"  Assume that a treasure is placed in one of $M$ boxes according to a known
distribution and that $k$ searchers are searching for it in parallel during $T$
rounds. We study the question of how to incentivize selfish players so that the
success probability, namely, the probability that at least one player finds the
treasure, would be maximized. We focus on congestion policies $C(s)$ that
specify the reward that a player receives if it is one of $s$ players that
(simultaneously) find the treasure for the first time. We show that the
exclusive policy, in which $C(1)=1$ and $C(s)=0$ for $s>1$, yields a price of
anarchy of $(1-(1-{1}/{k})^{k})^{-1}$. This is the best possible price among
all symmetric reward mechanisms. For this policy, we also have an explicit
description of a symmetric equilibrium, which is in some sense unique, and
moreover enjoys the best success probability among all symmetric profiles. For
general congestion policies, we show how to polynomially find, for any
$\theta>0$, a symmetric multiplicative $(1+\theta)(1+C(k))$-equilibrium.
  Together with a reward policy, a central entity can suggest players to play a
particular profile at equilibrium. For such purposes, we advocate the use of
symmetric equilibria. Besides being fair, symmetric equilibria can also become
highly robust to crashes of players. Indeed, in many cases, despite the fact
that some small fraction of players crash, symmetric equilibria remain
efficient in terms of their group performances and, at the same time, serve as
approximate equilibria. We show that this principle holds for a class of games,
which we call monotonously scalable games. This applies in particular to our
search game, assuming the natural sharing policy, in which $C(s)=1/s$. For the
exclusive policy, this general result does not hold, but we show that the
symmetric equilibrium is nevertheless robust under mild assumptions.
",yoav rodeh,,2018.0,,arXiv,Korman2018,True,,arXiv,Not available,"Cooperative Search Games: Symmetric Equilibria, Robustness, and Price of
  Anarchy",98467e60f947e6897f2ba0ce466fc8bd,http://arxiv.org/abs/1811.01270v1
14838,"  We define what ""Price Impact"" means, and how it is measured and modelled in
the recent literature. Although this notion seems to convey the idea of a
forceful and intuitive mechanism, we discuss why things might not be that
simple. Empirical studies show that while the correlation between signed order
flow and price changes is strong, the impact of trades on prices is neither
linear in volume nor permanent. Impact allows private information to be
reflected in prices, but by the same token, random fluctuations in order flow
must also contribute to the volatility of markets.
",j. bouchaud,,2009.0,,arXiv,Bouchaud2009,True,,arXiv,Not available,Price Impact,79b336e3338d1b439396ecf2a51a5a45,http://arxiv.org/abs/0903.2428v1
14839,"  There exist several methods how more general options can be priced with call
prices. In this article, we extend these results to cover a wider class of
options and market models. In particular, we introduce a new pricing formula
which can be used to price more general options if prices for call options and
digital options are known for every strike price. Moreover, we derive similar
results for barrier type options. As a consequence, we obtain a static hedging
for general options in the general class of models. Our result can be utilised
in several significant applications. As a simple example, we derive an upper
bound for the value of a general American option with convex payoff and
characterise conditions under which the value of this option equals to the
value of the corresponding European option.
",lauri viitasaari,,2012.0,,arXiv,Viitasaari2012,True,,arXiv,Not available,Option prices with call prices,b2c2079d081c0930f23300fc440306ff,http://arxiv.org/abs/1207.6205v3
14840,"  We give exponential lower bounds on the Price of Stability (PoS) of weighted
congestion games with polynomial cost functions. In particular, for any
positive integer $d$ we construct rather simple games with cost functions of
degree at most $d$ which have a PoS of at least $\varOmega(\Phi_d)^{d+1}$,
where $\Phi_d\sim d/\ln d$ is the unique positive root of equation
$x^{d+1}=(x+1)^d$. This essentially closes the huge gap between $\varTheta(d)$
and $\Phi_d^{d+1}$ and asymptotically matches the Price of Anarchy upper bound.
We further show that the PoS remains exponential even for singleton games. More
generally, we also provide a lower bound of $\varOmega((1+1/\alpha)^d/d)$ on
the PoS of $\alpha$-approximate Nash equilibria, even for singleton games. All
our lower bounds extend to network congestion games, and hold for mixed and
correlated equilibria as well.
  On the positive side, we give a general upper bound on the PoS of
$\alpha$-approximate Nash equilibria, which is sensitive to the range $W$ of
the player weights and the approximation parameter $\alpha$. We do this by
explicitly constructing a novel approximate potential function, based on
Faulhaber's formula, that generalizes Rosenthal's potential in a continuous,
analytic way. From the general theorem, we deduce two interesting corollaries.
First, we derive the existence of an approximate pure Nash equilibrium with PoS
at most $(d+3)/2$; the equilibrium's approximation parameter ranges from
$\varTheta(1)$ to $d+1$ in a smooth way with respect to $W$. Secondly, we show
that for unweighted congestion games, the PoS of $\alpha$-approximate Nash
equilibria is at most $(d+1)/\alpha$.
",george christodoulou,,2018.0,,arXiv,Christodoulou2018,True,,arXiv,Not available,The Price of Stability of Weighted Congestion Games,55fb9fcc5dc3a2aaf9c908c3ec18d987,http://arxiv.org/abs/1802.09952v2
14841,"  We give exponential lower bounds on the Price of Stability (PoS) of weighted
congestion games with polynomial cost functions. In particular, for any
positive integer $d$ we construct rather simple games with cost functions of
degree at most $d$ which have a PoS of at least $\varOmega(\Phi_d)^{d+1}$,
where $\Phi_d\sim d/\ln d$ is the unique positive root of equation
$x^{d+1}=(x+1)^d$. This essentially closes the huge gap between $\varTheta(d)$
and $\Phi_d^{d+1}$ and asymptotically matches the Price of Anarchy upper bound.
We further show that the PoS remains exponential even for singleton games. More
generally, we also provide a lower bound of $\varOmega((1+1/\alpha)^d/d)$ on
the PoS of $\alpha$-approximate Nash equilibria, even for singleton games. All
our lower bounds extend to network congestion games, and hold for mixed and
correlated equilibria as well.
  On the positive side, we give a general upper bound on the PoS of
$\alpha$-approximate Nash equilibria, which is sensitive to the range $W$ of
the player weights and the approximation parameter $\alpha$. We do this by
explicitly constructing a novel approximate potential function, based on
Faulhaber's formula, that generalizes Rosenthal's potential in a continuous,
analytic way. From the general theorem, we deduce two interesting corollaries.
First, we derive the existence of an approximate pure Nash equilibrium with PoS
at most $(d+3)/2$; the equilibrium's approximation parameter ranges from
$\varTheta(1)$ to $d+1$ in a smooth way with respect to $W$. Secondly, we show
that for unweighted congestion games, the PoS of $\alpha$-approximate Nash
equilibria is at most $(d+1)/\alpha$.
",martin gairing,,2018.0,,arXiv,Christodoulou2018,True,,arXiv,Not available,The Price of Stability of Weighted Congestion Games,55fb9fcc5dc3a2aaf9c908c3ec18d987,http://arxiv.org/abs/1802.09952v2
14842,"  We give exponential lower bounds on the Price of Stability (PoS) of weighted
congestion games with polynomial cost functions. In particular, for any
positive integer $d$ we construct rather simple games with cost functions of
degree at most $d$ which have a PoS of at least $\varOmega(\Phi_d)^{d+1}$,
where $\Phi_d\sim d/\ln d$ is the unique positive root of equation
$x^{d+1}=(x+1)^d$. This essentially closes the huge gap between $\varTheta(d)$
and $\Phi_d^{d+1}$ and asymptotically matches the Price of Anarchy upper bound.
We further show that the PoS remains exponential even for singleton games. More
generally, we also provide a lower bound of $\varOmega((1+1/\alpha)^d/d)$ on
the PoS of $\alpha$-approximate Nash equilibria, even for singleton games. All
our lower bounds extend to network congestion games, and hold for mixed and
correlated equilibria as well.
  On the positive side, we give a general upper bound on the PoS of
$\alpha$-approximate Nash equilibria, which is sensitive to the range $W$ of
the player weights and the approximation parameter $\alpha$. We do this by
explicitly constructing a novel approximate potential function, based on
Faulhaber's formula, that generalizes Rosenthal's potential in a continuous,
analytic way. From the general theorem, we deduce two interesting corollaries.
First, we derive the existence of an approximate pure Nash equilibrium with PoS
at most $(d+3)/2$; the equilibrium's approximation parameter ranges from
$\varTheta(1)$ to $d+1$ in a smooth way with respect to $W$. Secondly, we show
that for unweighted congestion games, the PoS of $\alpha$-approximate Nash
equilibria is at most $(d+1)/\alpha$.
",yiannis giannakopoulos,,2018.0,,arXiv,Christodoulou2018,True,,arXiv,Not available,The Price of Stability of Weighted Congestion Games,55fb9fcc5dc3a2aaf9c908c3ec18d987,http://arxiv.org/abs/1802.09952v2
14843,"  We give exponential lower bounds on the Price of Stability (PoS) of weighted
congestion games with polynomial cost functions. In particular, for any
positive integer $d$ we construct rather simple games with cost functions of
degree at most $d$ which have a PoS of at least $\varOmega(\Phi_d)^{d+1}$,
where $\Phi_d\sim d/\ln d$ is the unique positive root of equation
$x^{d+1}=(x+1)^d$. This essentially closes the huge gap between $\varTheta(d)$
and $\Phi_d^{d+1}$ and asymptotically matches the Price of Anarchy upper bound.
We further show that the PoS remains exponential even for singleton games. More
generally, we also provide a lower bound of $\varOmega((1+1/\alpha)^d/d)$ on
the PoS of $\alpha$-approximate Nash equilibria, even for singleton games. All
our lower bounds extend to network congestion games, and hold for mixed and
correlated equilibria as well.
  On the positive side, we give a general upper bound on the PoS of
$\alpha$-approximate Nash equilibria, which is sensitive to the range $W$ of
the player weights and the approximation parameter $\alpha$. We do this by
explicitly constructing a novel approximate potential function, based on
Faulhaber's formula, that generalizes Rosenthal's potential in a continuous,
analytic way. From the general theorem, we deduce two interesting corollaries.
First, we derive the existence of an approximate pure Nash equilibrium with PoS
at most $(d+3)/2$; the equilibrium's approximation parameter ranges from
$\varTheta(1)$ to $d+1$ in a smooth way with respect to $W$. Secondly, we show
that for unweighted congestion games, the PoS of $\alpha$-approximate Nash
equilibria is at most $(d+1)/\alpha$.
",paul spirakis,,2018.0,,arXiv,Christodoulou2018,True,,arXiv,Not available,The Price of Stability of Weighted Congestion Games,55fb9fcc5dc3a2aaf9c908c3ec18d987,http://arxiv.org/abs/1802.09952v2
14844,"  Motivated by recent progress on pricing in the AI literature, we study
marketplaces that contain multiple vendors offering identical or similar
products and unit-demand buyers with different valuations on these vendors. The
objective of each vendor is to set the price of its product to a fixed value so
that its profit is maximized. The profit depends on the vendor's price itself
and the total volume of buyers that find the particular price more attractive
than the price of the vendor's competitors. We model the behaviour of buyers
and vendors as a two-stage full-information game and study a series of
questions related to the existence, efficiency (price of anarchy) and
computational complexity of equilibria in this game. To overcome situations
where equilibria do not exist or exist but are highly inefficient, we consider
the scenario where some of the vendors are subsidized in order to keep prices
low and buyers highly satisfied.
",ioannis caragiannis,,2015.0,,arXiv,Caragiannis2015,True,,arXiv,Not available,"Efficiency and complexity of price competition among single-product
  vendors",e0b4332b238fc647754a827a61d92de9,http://arxiv.org/abs/1502.03945v2
14845,"  Motivated by recent progress on pricing in the AI literature, we study
marketplaces that contain multiple vendors offering identical or similar
products and unit-demand buyers with different valuations on these vendors. The
objective of each vendor is to set the price of its product to a fixed value so
that its profit is maximized. The profit depends on the vendor's price itself
and the total volume of buyers that find the particular price more attractive
than the price of the vendor's competitors. We model the behaviour of buyers
and vendors as a two-stage full-information game and study a series of
questions related to the existence, efficiency (price of anarchy) and
computational complexity of equilibria in this game. To overcome situations
where equilibria do not exist or exist but are highly inefficient, we consider
the scenario where some of the vendors are subsidized in order to keep prices
low and buyers highly satisfied.
",xenophon chatzigeorgiou,,2015.0,,arXiv,Caragiannis2015,True,,arXiv,Not available,"Efficiency and complexity of price competition among single-product
  vendors",e0b4332b238fc647754a827a61d92de9,http://arxiv.org/abs/1502.03945v2
14846,"  Motivated by recent progress on pricing in the AI literature, we study
marketplaces that contain multiple vendors offering identical or similar
products and unit-demand buyers with different valuations on these vendors. The
objective of each vendor is to set the price of its product to a fixed value so
that its profit is maximized. The profit depends on the vendor's price itself
and the total volume of buyers that find the particular price more attractive
than the price of the vendor's competitors. We model the behaviour of buyers
and vendors as a two-stage full-information game and study a series of
questions related to the existence, efficiency (price of anarchy) and
computational complexity of equilibria in this game. To overcome situations
where equilibria do not exist or exist but are highly inefficient, we consider
the scenario where some of the vendors are subsidized in order to keep prices
low and buyers highly satisfied.
",panagiotis kanellopoulos,,2015.0,,arXiv,Caragiannis2015,True,,arXiv,Not available,"Efficiency and complexity of price competition among single-product
  vendors",e0b4332b238fc647754a827a61d92de9,http://arxiv.org/abs/1502.03945v2
14847,"  Motivated by recent progress on pricing in the AI literature, we study
marketplaces that contain multiple vendors offering identical or similar
products and unit-demand buyers with different valuations on these vendors. The
objective of each vendor is to set the price of its product to a fixed value so
that its profit is maximized. The profit depends on the vendor's price itself
and the total volume of buyers that find the particular price more attractive
than the price of the vendor's competitors. We model the behaviour of buyers
and vendors as a two-stage full-information game and study a series of
questions related to the existence, efficiency (price of anarchy) and
computational complexity of equilibria in this game. To overcome situations
where equilibria do not exist or exist but are highly inefficient, we consider
the scenario where some of the vendors are subsidized in order to keep prices
low and buyers highly satisfied.
",george krimpas,,2015.0,,arXiv,Caragiannis2015,True,,arXiv,Not available,"Efficiency and complexity of price competition among single-product
  vendors",e0b4332b238fc647754a827a61d92de9,http://arxiv.org/abs/1502.03945v2
14848,"  Motivated by recent progress on pricing in the AI literature, we study
marketplaces that contain multiple vendors offering identical or similar
products and unit-demand buyers with different valuations on these vendors. The
objective of each vendor is to set the price of its product to a fixed value so
that its profit is maximized. The profit depends on the vendor's price itself
and the total volume of buyers that find the particular price more attractive
than the price of the vendor's competitors. We model the behaviour of buyers
and vendors as a two-stage full-information game and study a series of
questions related to the existence, efficiency (price of anarchy) and
computational complexity of equilibria in this game. To overcome situations
where equilibria do not exist or exist but are highly inefficient, we consider
the scenario where some of the vendors are subsidized in order to keep prices
low and buyers highly satisfied.
",nikos protopapas,,2015.0,,arXiv,Caragiannis2015,True,,arXiv,Not available,"Efficiency and complexity of price competition among single-product
  vendors",e0b4332b238fc647754a827a61d92de9,http://arxiv.org/abs/1502.03945v2
14849,"  Motivated by recent progress on pricing in the AI literature, we study
marketplaces that contain multiple vendors offering identical or similar
products and unit-demand buyers with different valuations on these vendors. The
objective of each vendor is to set the price of its product to a fixed value so
that its profit is maximized. The profit depends on the vendor's price itself
and the total volume of buyers that find the particular price more attractive
than the price of the vendor's competitors. We model the behaviour of buyers
and vendors as a two-stage full-information game and study a series of
questions related to the existence, efficiency (price of anarchy) and
computational complexity of equilibria in this game. To overcome situations
where equilibria do not exist or exist but are highly inefficient, we consider
the scenario where some of the vendors are subsidized in order to keep prices
low and buyers highly satisfied.
",alexandros voudouris,,2015.0,,arXiv,Caragiannis2015,True,,arXiv,Not available,"Efficiency and complexity of price competition among single-product
  vendors",e0b4332b238fc647754a827a61d92de9,http://arxiv.org/abs/1502.03945v2
14850,"  We consider non-cooperative unsplittable congestion games where players share
resources, and each player's strategy is pure and consists of a subset of the
resources on which it applies a fixed weight. Such games represent unsplittable
routing flow games and also job allocation games. The congestion of a resource
is the sum of the weights of the players that use it and the player's cost
function is the sum of the utilities of the resources on its strategy. The
social cost is the total weighted sum of the player's costs. The quality of
Nash equilibria is determined by the price of anarchy ($PoA$) which expresses
how much worse is the social outcome in the worst equilibrium versus the
optimal coordinated solution. In the literature the predominant work has only
been on games with polynomial utility costs, where it has been proven that the
price of anarchy is bounded by the degree of the polynomial. However, no
results exist on general bounds for non-polynomial utility functions.
  Here, we consider general versions of these games in which the utility of
each resource is an arbitrary non-decreasing function of the congestion. In
particular, we consider a large family of superpolynomial utility functions
which are asymptotically larger than any polynomial. We demonstrate that for
every such function there exist games for which the price of anarchy is
unbounded and increasing with the number of players (even if they have
infinitesimal weights) while network resources remain fixed. We give tight
lower and upper bounds which show this dependence on the number of players.
Furthermore we provide an exact characterization of the $PoA$ of all congestion
games whose utility costs are bounded above by a polynomial function.
Heretofore such results existed only for games with polynomial cost functions.
",rajgopal kannan,,2013.0,,arXiv,Kannan2013,True,,arXiv,Not available,"The Price of Anarchy is Unbounded for Congestion Games with
  Superpolynomial Latency Costs",7adf8776a947e69dd90c7a76aa5a93d5,http://arxiv.org/abs/1308.4101v1
14851,"  We consider non-cooperative unsplittable congestion games where players share
resources, and each player's strategy is pure and consists of a subset of the
resources on which it applies a fixed weight. Such games represent unsplittable
routing flow games and also job allocation games. The congestion of a resource
is the sum of the weights of the players that use it and the player's cost
function is the sum of the utilities of the resources on its strategy. The
social cost is the total weighted sum of the player's costs. The quality of
Nash equilibria is determined by the price of anarchy ($PoA$) which expresses
how much worse is the social outcome in the worst equilibrium versus the
optimal coordinated solution. In the literature the predominant work has only
been on games with polynomial utility costs, where it has been proven that the
price of anarchy is bounded by the degree of the polynomial. However, no
results exist on general bounds for non-polynomial utility functions.
  Here, we consider general versions of these games in which the utility of
each resource is an arbitrary non-decreasing function of the congestion. In
particular, we consider a large family of superpolynomial utility functions
which are asymptotically larger than any polynomial. We demonstrate that for
every such function there exist games for which the price of anarchy is
unbounded and increasing with the number of players (even if they have
infinitesimal weights) while network resources remain fixed. We give tight
lower and upper bounds which show this dependence on the number of players.
Furthermore we provide an exact characterization of the $PoA$ of all congestion
games whose utility costs are bounded above by a polynomial function.
Heretofore such results existed only for games with polynomial cost functions.
",costas busch,,2013.0,,arXiv,Kannan2013,True,,arXiv,Not available,"The Price of Anarchy is Unbounded for Congestion Games with
  Superpolynomial Latency Costs",7adf8776a947e69dd90c7a76aa5a93d5,http://arxiv.org/abs/1308.4101v1
14852,"  We consider non-cooperative unsplittable congestion games where players share
resources, and each player's strategy is pure and consists of a subset of the
resources on which it applies a fixed weight. Such games represent unsplittable
routing flow games and also job allocation games. The congestion of a resource
is the sum of the weights of the players that use it and the player's cost
function is the sum of the utilities of the resources on its strategy. The
social cost is the total weighted sum of the player's costs. The quality of
Nash equilibria is determined by the price of anarchy ($PoA$) which expresses
how much worse is the social outcome in the worst equilibrium versus the
optimal coordinated solution. In the literature the predominant work has only
been on games with polynomial utility costs, where it has been proven that the
price of anarchy is bounded by the degree of the polynomial. However, no
results exist on general bounds for non-polynomial utility functions.
  Here, we consider general versions of these games in which the utility of
each resource is an arbitrary non-decreasing function of the congestion. In
particular, we consider a large family of superpolynomial utility functions
which are asymptotically larger than any polynomial. We demonstrate that for
every such function there exist games for which the price of anarchy is
unbounded and increasing with the number of players (even if they have
infinitesimal weights) while network resources remain fixed. We give tight
lower and upper bounds which show this dependence on the number of players.
Furthermore we provide an exact characterization of the $PoA$ of all congestion
games whose utility costs are bounded above by a polynomial function.
Heretofore such results existed only for games with polynomial cost functions.
",paul spirakis,,2013.0,,arXiv,Kannan2013,True,,arXiv,Not available,"The Price of Anarchy is Unbounded for Congestion Games with
  Superpolynomial Latency Costs",7adf8776a947e69dd90c7a76aa5a93d5,http://arxiv.org/abs/1308.4101v1
14853,"  This paper studies the performance of Mobile Ad hoc Networks (MANETs) when
the nodes, that form a Poisson point process, selfishly choose their Medium
Access Probability (MAP). We consider goodput and delay as the performance
metric that each node is interested in optimizing taking into account the
transmission energy costs. We introduce a pricing scheme based on the
transmission energy requirements and compute the symmetric Nash equilibria of
the game in closed form. It is shown that by appropriately pricing the nodes,
the selfish behavior of the nodes can be used to achieve the social optimum at
equilibrium. The Price of Anarchy is then analyzed for these games. For the
game with delay based utility, we bound the price of anarchy and study the
effect of the price factor. For the game with goodput based utility, it is
shown that price of anarchy is infinite at the price factor that achieves the
global optima.
",manjesh hanawal,,2011.0,,arXiv,Hanawal2011,True,,arXiv,Not available,Stochastic Geometry based Medium Access Games in Mobile Ad hoc Networks,45e56fd4186ed4418c25e6f7a998c2c9,http://arxiv.org/abs/1112.3741v2
14854,"  This paper studies the performance of Mobile Ad hoc Networks (MANETs) when
the nodes, that form a Poisson point process, selfishly choose their Medium
Access Probability (MAP). We consider goodput and delay as the performance
metric that each node is interested in optimizing taking into account the
transmission energy costs. We introduce a pricing scheme based on the
transmission energy requirements and compute the symmetric Nash equilibria of
the game in closed form. It is shown that by appropriately pricing the nodes,
the selfish behavior of the nodes can be used to achieve the social optimum at
equilibrium. The Price of Anarchy is then analyzed for these games. For the
game with delay based utility, we bound the price of anarchy and study the
effect of the price factor. For the game with goodput based utility, it is
shown that price of anarchy is infinite at the price factor that achieves the
global optima.
",eitan altman,,2011.0,,arXiv,Hanawal2011,True,,arXiv,Not available,Stochastic Geometry based Medium Access Games in Mobile Ad hoc Networks,45e56fd4186ed4418c25e6f7a998c2c9,http://arxiv.org/abs/1112.3741v2
14855,"  This paper studies the performance of Mobile Ad hoc Networks (MANETs) when
the nodes, that form a Poisson point process, selfishly choose their Medium
Access Probability (MAP). We consider goodput and delay as the performance
metric that each node is interested in optimizing taking into account the
transmission energy costs. We introduce a pricing scheme based on the
transmission energy requirements and compute the symmetric Nash equilibria of
the game in closed form. It is shown that by appropriately pricing the nodes,
the selfish behavior of the nodes can be used to achieve the social optimum at
equilibrium. The Price of Anarchy is then analyzed for these games. For the
game with delay based utility, we bound the price of anarchy and study the
effect of the price factor. For the game with goodput based utility, it is
shown that price of anarchy is infinite at the price factor that achieves the
global optima.
",francois baccelli,,2011.0,,arXiv,Hanawal2011,True,,arXiv,Not available,Stochastic Geometry based Medium Access Games in Mobile Ad hoc Networks,45e56fd4186ed4418c25e6f7a998c2c9,http://arxiv.org/abs/1112.3741v2
14856,"  Price of anarchy, the performance ratio, which could characterize the loss of
efficiency of the distributed supply chain management compared with the
integrated supply chain management is discussed by utilizing newsvendor problem
in single period which is well-known. In particular, some of remarkable
distributed policies are handled, the performance ratios in each case which
have been investigated in the previous works are analyzed theoretically and the
tighter upper bound of price of anarchy and the lower bound are presented.
Furthermore our approach is developed based on a generalized framework and a
geometric interpretation of price of anarchy is appeared via the literature of
convex optimization.
",t. shinzato,,2009.0,,arXiv,Shinzato2009,True,,arXiv,Not available,"Improved and Developed Upper Bound of Price of Anarchy in Two Echelon
  Case",4ec6481c509fff334e388eefdaabd201,http://arxiv.org/abs/0906.5489v1
14857,"  Price of anarchy, the performance ratio, which could characterize the loss of
efficiency of the distributed supply chain management compared with the
integrated supply chain management is discussed by utilizing newsvendor problem
in single period which is well-known. In particular, some of remarkable
distributed policies are handled, the performance ratios in each case which
have been investigated in the previous works are analyzed theoretically and the
tighter upper bound of price of anarchy and the lower bound are presented.
Furthermore our approach is developed based on a generalized framework and a
geometric interpretation of price of anarchy is appeared via the literature of
convex optimization.
",i. kaku,,2009.0,,arXiv,Shinzato2009,True,,arXiv,Not available,"Improved and Developed Upper Bound of Price of Anarchy in Two Echelon
  Case",4ec6481c509fff334e388eefdaabd201,http://arxiv.org/abs/0906.5489v1
14858,"  One of the main results shown through Roughgarden's notions of smooth games
and robust price of anarchy is that, for any sum-bounded utilitarian social
function, the worst-case price of anarchy of coarse correlated equilibria
coincides with that of pure Nash equilibria in the class of weighted congestion
games with non-negative and non-decreasing latency functions and that such a
value can always be derived through the, so called, smoothness argument. We
significantly extend this result by proving that, for a variety of (even
non-sum-bounded) utilitarian and egalitarian social functions and for a broad
generalization of the class of weighted congestion games with non-negative (and
possibly decreasing) latency functions, the worst-case price of anarchy of
$\epsilon$-approximate coarse correlated equilibria still coincides with that
of $\epsilon$-approximate pure Nash equilibria, for any $\epsilon\geq 0$. As a
byproduct of our proof, it also follows that such a value can always be
determined by making use of the primal-dual method we introduced in a previous
work. It is important to note that our scenario of investigation is beyond the
scope of application of the robust price of anarchy (for as it is currently
defined), so that our result seems unlikely to be alternatively proved via the
smoothness framework.
",vittorio bilo,,2014.0,,arXiv,Bilò2014,True,,arXiv,Not available,"On the Robustness of the Approximate Price of Anarchy in Generalized
  Congestion Games",b3824cf34c3bebf933438e9bfca9df90,http://arxiv.org/abs/1412.0845v1
14859,"  This paper examines the behavior of the price of anarchy as a function of the
traffic inflow in nonatomic congestion games with multiple origin-destination
(O/D) pairs. Empirical studies in real-world networks show that the price of
anarchy is close to 1 in both light and heavy traffic, thus raising the
question: can these observations be justified theoretically? We first show that
this is not always the case: the price of anarchy may remain a positive
distance away from 1 for all values of the traffic inflow, even in simple
three-link networks with a single O/D pair and smooth, convex costs. On the
other hand, for a large class of cost functions (including all polynomials),
the price of anarchy does converge to 1 in both heavy and light traffic,
irrespective of the network topology and the number of O/D pairs in the
network. We also examine the rate of convergence of the price of anarchy, and
we show that it follows a power law whose degree can be computed explicitly
when the network's cost functions are polynomials.
",riccardo colini-baldeschi,,2017.0,,arXiv,Colini-Baldeschi2017,True,,arXiv,Not available,"When is selfish routing bad? The price of anarchy in light and heavy
  traffic",d34dfff78af759ec38c705afc90a97c9,http://arxiv.org/abs/1703.00927v2
14860,"  This paper examines the behavior of the price of anarchy as a function of the
traffic inflow in nonatomic congestion games with multiple origin-destination
(O/D) pairs. Empirical studies in real-world networks show that the price of
anarchy is close to 1 in both light and heavy traffic, thus raising the
question: can these observations be justified theoretically? We first show that
this is not always the case: the price of anarchy may remain a positive
distance away from 1 for all values of the traffic inflow, even in simple
three-link networks with a single O/D pair and smooth, convex costs. On the
other hand, for a large class of cost functions (including all polynomials),
the price of anarchy does converge to 1 in both heavy and light traffic,
irrespective of the network topology and the number of O/D pairs in the
network. We also examine the rate of convergence of the price of anarchy, and
we show that it follows a power law whose degree can be computed explicitly
when the network's cost functions are polynomials.
",roberto cominetti,,2017.0,,arXiv,Colini-Baldeschi2017,True,,arXiv,Not available,"When is selfish routing bad? The price of anarchy in light and heavy
  traffic",d34dfff78af759ec38c705afc90a97c9,http://arxiv.org/abs/1703.00927v2
14861,"  This paper examines the behavior of the price of anarchy as a function of the
traffic inflow in nonatomic congestion games with multiple origin-destination
(O/D) pairs. Empirical studies in real-world networks show that the price of
anarchy is close to 1 in both light and heavy traffic, thus raising the
question: can these observations be justified theoretically? We first show that
this is not always the case: the price of anarchy may remain a positive
distance away from 1 for all values of the traffic inflow, even in simple
three-link networks with a single O/D pair and smooth, convex costs. On the
other hand, for a large class of cost functions (including all polynomials),
the price of anarchy does converge to 1 in both heavy and light traffic,
irrespective of the network topology and the number of O/D pairs in the
network. We also examine the rate of convergence of the price of anarchy, and
we show that it follows a power law whose degree can be computed explicitly
when the network's cost functions are polynomials.
",panayotis mertikopoulos,,2017.0,,arXiv,Colini-Baldeschi2017,True,,arXiv,Not available,"When is selfish routing bad? The price of anarchy in light and heavy
  traffic",d34dfff78af759ec38c705afc90a97c9,http://arxiv.org/abs/1703.00927v2
14862,"  This paper examines the behavior of the price of anarchy as a function of the
traffic inflow in nonatomic congestion games with multiple origin-destination
(O/D) pairs. Empirical studies in real-world networks show that the price of
anarchy is close to 1 in both light and heavy traffic, thus raising the
question: can these observations be justified theoretically? We first show that
this is not always the case: the price of anarchy may remain a positive
distance away from 1 for all values of the traffic inflow, even in simple
three-link networks with a single O/D pair and smooth, convex costs. On the
other hand, for a large class of cost functions (including all polynomials),
the price of anarchy does converge to 1 in both heavy and light traffic,
irrespective of the network topology and the number of O/D pairs in the
network. We also examine the rate of convergence of the price of anarchy, and
we show that it follows a power law whose degree can be computed explicitly
when the network's cost functions are polynomials.
",marco scarsini,,2017.0,,arXiv,Colini-Baldeschi2017,True,,arXiv,Not available,"When is selfish routing bad? The price of anarchy in light and heavy
  traffic",d34dfff78af759ec38c705afc90a97c9,http://arxiv.org/abs/1703.00927v2
14863,"  We study {\em bottleneck routing games} where the social cost is determined
by the worst congestion on any edge in the network. In the literature,
bottleneck games assume player utility costs determined by the worst congested
edge in their paths. However, the Nash equilibria of such games are inefficient
since the price of anarchy can be very high and proportional to the size of the
network. In order to obtain smaller price of anarchy we introduce {\em
exponential bottleneck games} where the utility costs of the players are
exponential functions of their congestions. We find that exponential bottleneck
games are very efficient and give a poly-log bound on the price of anarchy:
$O(\log L \cdot \log |E|)$, where $L$ is the largest path length in the
players' strategy sets and $E$ is the set of edges in the graph. By adjusting
the exponential utility costs with a logarithm we obtain games whose player
costs are almost identical to those in regular bottleneck games, and at the
same time have the good price of anarchy of exponential games.
",rajgopal kannan,,2010.0,10.1007/978-3-642-16170-4_20,arXiv,Kannan2010,True,,arXiv,Not available,Bottleneck Routing Games with Low Price of Anarchy,9e3676835c35143114e69790cc570af5,http://arxiv.org/abs/1003.4307v1
14864,"  We study {\em bottleneck routing games} where the social cost is determined
by the worst congestion on any edge in the network. In the literature,
bottleneck games assume player utility costs determined by the worst congested
edge in their paths. However, the Nash equilibria of such games are inefficient
since the price of anarchy can be very high and proportional to the size of the
network. In order to obtain smaller price of anarchy we introduce {\em
exponential bottleneck games} where the utility costs of the players are
exponential functions of their congestions. We find that exponential bottleneck
games are very efficient and give a poly-log bound on the price of anarchy:
$O(\log L \cdot \log |E|)$, where $L$ is the largest path length in the
players' strategy sets and $E$ is the set of edges in the graph. By adjusting
the exponential utility costs with a logarithm we obtain games whose player
costs are almost identical to those in regular bottleneck games, and at the
same time have the good price of anarchy of exponential games.
",costas busch,,2010.0,10.1007/978-3-642-16170-4_20,arXiv,Kannan2010,True,,arXiv,Not available,Bottleneck Routing Games with Low Price of Anarchy,9e3676835c35143114e69790cc570af5,http://arxiv.org/abs/1003.4307v1
14865,"  We study routing behavior in transportation networks with mixed autonomy,
that is, networks in which a fraction of the vehicles on each road are equipped
with autonomous capabilities such as adaptive cruise control that enable
reduced headways and increased road capacity. Motivated by capacity models
developed for such roads with mixed autonomy, we consider transportation
networks in which the delay on each road or link is an affine function of two
quantities: the number of vehicles with autonomous capabilities on the link and
the number of regular vehicles on the link. We particularly study the price of
anarchy for such networks, that is, the ratio of the total delay experienced by
selfish routing to the socially optimal routing policy. Unlike the case when
all vehicles are of the same type, for which the price of anarchy is known to
be bounded, we first show that the price of anarchy can be arbitrarily large
for such mixed autonomous networks. Next, we define a notion of asymmetry equal
to the maximum possible travel time improvement due to the presence of
autonomous vehicles. We show that when the degree of asymmetry of all links in
the network is bounded by a factor less than 4, the price of anarchy is
bounded. We also bound the bicriteria, which is a bound on the cost of
selfishly routing traffic compared to the cost of optimally routing additional
traffic. These bounds depend on the degree of asymmetry and recover classical
bounds on the price of anarchy and bicriteria in the case when no asymmetry
exists. Further, we show with examples that these bound are tight in particular
cases.
",daniel lazar,,2017.0,,arXiv,Lazar2017,True,,arXiv,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy,77131436034b7eb15cda554fd65c5bbc,http://arxiv.org/abs/1710.07867v1
14866,"  We study routing behavior in transportation networks with mixed autonomy,
that is, networks in which a fraction of the vehicles on each road are equipped
with autonomous capabilities such as adaptive cruise control that enable
reduced headways and increased road capacity. Motivated by capacity models
developed for such roads with mixed autonomy, we consider transportation
networks in which the delay on each road or link is an affine function of two
quantities: the number of vehicles with autonomous capabilities on the link and
the number of regular vehicles on the link. We particularly study the price of
anarchy for such networks, that is, the ratio of the total delay experienced by
selfish routing to the socially optimal routing policy. Unlike the case when
all vehicles are of the same type, for which the price of anarchy is known to
be bounded, we first show that the price of anarchy can be arbitrarily large
for such mixed autonomous networks. Next, we define a notion of asymmetry equal
to the maximum possible travel time improvement due to the presence of
autonomous vehicles. We show that when the degree of asymmetry of all links in
the network is bounded by a factor less than 4, the price of anarchy is
bounded. We also bound the bicriteria, which is a bound on the cost of
selfishly routing traffic compared to the cost of optimally routing additional
traffic. These bounds depend on the degree of asymmetry and recover classical
bounds on the price of anarchy and bicriteria in the case when no asymmetry
exists. Further, we show with examples that these bound are tight in particular
cases.
",samuel coogan,,2017.0,,arXiv,Lazar2017,True,,arXiv,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy,77131436034b7eb15cda554fd65c5bbc,http://arxiv.org/abs/1710.07867v1
14867,"  We study routing behavior in transportation networks with mixed autonomy,
that is, networks in which a fraction of the vehicles on each road are equipped
with autonomous capabilities such as adaptive cruise control that enable
reduced headways and increased road capacity. Motivated by capacity models
developed for such roads with mixed autonomy, we consider transportation
networks in which the delay on each road or link is an affine function of two
quantities: the number of vehicles with autonomous capabilities on the link and
the number of regular vehicles on the link. We particularly study the price of
anarchy for such networks, that is, the ratio of the total delay experienced by
selfish routing to the socially optimal routing policy. Unlike the case when
all vehicles are of the same type, for which the price of anarchy is known to
be bounded, we first show that the price of anarchy can be arbitrarily large
for such mixed autonomous networks. Next, we define a notion of asymmetry equal
to the maximum possible travel time improvement due to the presence of
autonomous vehicles. We show that when the degree of asymmetry of all links in
the network is bounded by a factor less than 4, the price of anarchy is
bounded. We also bound the bicriteria, which is a bound on the cost of
selfishly routing traffic compared to the cost of optimally routing additional
traffic. These bounds depend on the degree of asymmetry and recover classical
bounds on the price of anarchy and bicriteria in the case when no asymmetry
exists. Further, we show with examples that these bound are tight in particular
cases.
",ramtin pedarsani,,2017.0,,arXiv,Lazar2017,True,,arXiv,Not available,The Price of Anarchy for Transportation Networks with Mixed Autonomy,77131436034b7eb15cda554fd65c5bbc,http://arxiv.org/abs/1710.07867v1
14868,"  This article studies the user behavior in non-atomic congestion games. We
consider non-atomic congestion games with continuous and non-decreasing
functions and investigate the limit of the price of anarchy when the total user
volume approaches infinity. We deepen the knowledge on {\em asymptotically well
designed games} \cite{Wu2017Selfishness}, {\em limit games}
\cite{Wu2017Selfishness}, {\em scalability} \cite{Wu2017Selfishness} and {\em
gaugeability} \cite{Colini2017b} that were recently used in the limit analyses
of the price of anarchy for non-atomic congestion games. We develop a unified
framework and derive new techniques that allow a general limit analysis of the
price of anarchy. With these new techniques, we are able to prove a global
convergence on the price of anarchy for non-atomic congestion games with
arbitrary polynomial price functions and arbitrary user volume vector
sequences. Moreover, we show that these new techniques are very flexible and
robust and apply also to non-atomic congestion games with price functions of
other types. In particular, we prove that non-atomic congestion games with
regularly varying price functions are also asymptotically well designed,
provided that the price functions are slightly restricted. Our results greatly
generalize recent results. In particular, our results further support the view
with a general proof that selfishness need not be bad for non-atomic congestion
games.
",zijun wu,,2018.0,,arXiv,Wu2018,True,,arXiv,Not available,Selfishness need not be bad: a general proof,efffb13f5f963500aaf516ee09909dd8,http://arxiv.org/abs/1805.07762v1
14869,"  This article studies the user behavior in non-atomic congestion games. We
consider non-atomic congestion games with continuous and non-decreasing
functions and investigate the limit of the price of anarchy when the total user
volume approaches infinity. We deepen the knowledge on {\em asymptotically well
designed games} \cite{Wu2017Selfishness}, {\em limit games}
\cite{Wu2017Selfishness}, {\em scalability} \cite{Wu2017Selfishness} and {\em
gaugeability} \cite{Colini2017b} that were recently used in the limit analyses
of the price of anarchy for non-atomic congestion games. We develop a unified
framework and derive new techniques that allow a general limit analysis of the
price of anarchy. With these new techniques, we are able to prove a global
convergence on the price of anarchy for non-atomic congestion games with
arbitrary polynomial price functions and arbitrary user volume vector
sequences. Moreover, we show that these new techniques are very flexible and
robust and apply also to non-atomic congestion games with price functions of
other types. In particular, we prove that non-atomic congestion games with
regularly varying price functions are also asymptotically well designed,
provided that the price functions are slightly restricted. Our results greatly
generalize recent results. In particular, our results further support the view
with a general proof that selfishness need not be bad for non-atomic congestion
games.
",rolf mohring,,2018.0,,arXiv,Wu2018,True,,arXiv,Not available,Selfishness need not be bad: a general proof,efffb13f5f963500aaf516ee09909dd8,http://arxiv.org/abs/1805.07762v1
14870,"  This article studies the user behavior in non-atomic congestion games. We
consider non-atomic congestion games with continuous and non-decreasing
functions and investigate the limit of the price of anarchy when the total user
volume approaches infinity. We deepen the knowledge on {\em asymptotically well
designed games} \cite{Wu2017Selfishness}, {\em limit games}
\cite{Wu2017Selfishness}, {\em scalability} \cite{Wu2017Selfishness} and {\em
gaugeability} \cite{Colini2017b} that were recently used in the limit analyses
of the price of anarchy for non-atomic congestion games. We develop a unified
framework and derive new techniques that allow a general limit analysis of the
price of anarchy. With these new techniques, we are able to prove a global
convergence on the price of anarchy for non-atomic congestion games with
arbitrary polynomial price functions and arbitrary user volume vector
sequences. Moreover, we show that these new techniques are very flexible and
robust and apply also to non-atomic congestion games with price functions of
other types. In particular, we prove that non-atomic congestion games with
regularly varying price functions are also asymptotically well designed,
provided that the price functions are slightly restricted. Our results greatly
generalize recent results. In particular, our results further support the view
with a general proof that selfishness need not be bad for non-atomic congestion
games.
",dachuan xu,,2018.0,,arXiv,Wu2018,True,,arXiv,Not available,Selfishness need not be bad: a general proof,efffb13f5f963500aaf516ee09909dd8,http://arxiv.org/abs/1805.07762v1
14871,"  Many algorithms that are originally designed without explicitly considering
incentive properties are later combined with simple pricing rules and used as
mechanisms. The resulting mechanisms are often natural and simple to
understand. But how good are these algorithms as mechanisms? Truthful reporting
of valuations is typically not a dominant strategy (certainly not with a
pay-your-bid, first-price rule, but it is likely not a good strategy even with
a critical value, or second-price style rule either). Our goal is to show that
a wide class of approximation algorithms yields this way mechanisms with low
Price of Anarchy.
  The seminal result of Lucier and Borodin [SODA 2010] shows that combining a
greedy algorithm that is an $\alpha$-approximation algorithm with a
pay-your-bid payment rule yields a mechanism whose Price of Anarchy is
$O(\alpha)$. In this paper we significantly extend the class of algorithms for
which such a result is available by showing that this close connection between
approximation ratio on the one hand and Price of Anarchy on the other also
holds for the design principle of relaxation and rounding provided that the
relaxation is smooth and the rounding is oblivious.
  We demonstrate the far-reaching consequences of our result by showing its
implications for sparse packing integer programs, such as multi-unit auctions
and generalized matching, for the maximum traveling salesman problem, for
combinatorial auctions, and for single source unsplittable flow problems. In
all these problems our approach leads to novel simple, near-optimal mechanisms
whose Price of Anarchy either matches or beats the performance guarantees of
known mechanisms.
",paul dutting,,2015.0,,arXiv,Dütting2015,True,,arXiv,Not available,Algorithms as Mechanisms: The Price of Anarchy of Relax-and-Round,391cf610e06070cd699a7c0acbb5f2ba,http://arxiv.org/abs/1511.09208v1
14872,"  Many algorithms that are originally designed without explicitly considering
incentive properties are later combined with simple pricing rules and used as
mechanisms. The resulting mechanisms are often natural and simple to
understand. But how good are these algorithms as mechanisms? Truthful reporting
of valuations is typically not a dominant strategy (certainly not with a
pay-your-bid, first-price rule, but it is likely not a good strategy even with
a critical value, or second-price style rule either). Our goal is to show that
a wide class of approximation algorithms yields this way mechanisms with low
Price of Anarchy.
  The seminal result of Lucier and Borodin [SODA 2010] shows that combining a
greedy algorithm that is an $\alpha$-approximation algorithm with a
pay-your-bid payment rule yields a mechanism whose Price of Anarchy is
$O(\alpha)$. In this paper we significantly extend the class of algorithms for
which such a result is available by showing that this close connection between
approximation ratio on the one hand and Price of Anarchy on the other also
holds for the design principle of relaxation and rounding provided that the
relaxation is smooth and the rounding is oblivious.
  We demonstrate the far-reaching consequences of our result by showing its
implications for sparse packing integer programs, such as multi-unit auctions
and generalized matching, for the maximum traveling salesman problem, for
combinatorial auctions, and for single source unsplittable flow problems. In
all these problems our approach leads to novel simple, near-optimal mechanisms
whose Price of Anarchy either matches or beats the performance guarantees of
known mechanisms.
",thomas kesselheim,,2015.0,,arXiv,Dütting2015,True,,arXiv,Not available,Algorithms as Mechanisms: The Price of Anarchy of Relax-and-Round,391cf610e06070cd699a7c0acbb5f2ba,http://arxiv.org/abs/1511.09208v1
14873,"  Many algorithms that are originally designed without explicitly considering
incentive properties are later combined with simple pricing rules and used as
mechanisms. The resulting mechanisms are often natural and simple to
understand. But how good are these algorithms as mechanisms? Truthful reporting
of valuations is typically not a dominant strategy (certainly not with a
pay-your-bid, first-price rule, but it is likely not a good strategy even with
a critical value, or second-price style rule either). Our goal is to show that
a wide class of approximation algorithms yields this way mechanisms with low
Price of Anarchy.
  The seminal result of Lucier and Borodin [SODA 2010] shows that combining a
greedy algorithm that is an $\alpha$-approximation algorithm with a
pay-your-bid payment rule yields a mechanism whose Price of Anarchy is
$O(\alpha)$. In this paper we significantly extend the class of algorithms for
which such a result is available by showing that this close connection between
approximation ratio on the one hand and Price of Anarchy on the other also
holds for the design principle of relaxation and rounding provided that the
relaxation is smooth and the rounding is oblivious.
  We demonstrate the far-reaching consequences of our result by showing its
implications for sparse packing integer programs, such as multi-unit auctions
and generalized matching, for the maximum traveling salesman problem, for
combinatorial auctions, and for single source unsplittable flow problems. In
all these problems our approach leads to novel simple, near-optimal mechanisms
whose Price of Anarchy either matches or beats the performance guarantees of
known mechanisms.
",eva tardos,,2015.0,,arXiv,Dütting2015,True,,arXiv,Not available,Algorithms as Mechanisms: The Price of Anarchy of Relax-and-Round,391cf610e06070cd699a7c0acbb5f2ba,http://arxiv.org/abs/1511.09208v1
14874,"  We present a new class of vertex cover and set cover games. The price of
anarchy bounds match the best known constant factor approximation guarantees
for the centralized optimization problems for linear and also for submodular
costs -- in contrast to all previously studied covering games, where the price
of anarchy cannot be bounded by a constant (e.g. [6, 7, 11, 5, 2]). In
particular, we describe a vertex cover game with a price of anarchy of 2. The
rules of the games capture the structure of the linear programming relaxations
of the underlying optimization problems, and our bounds are established by
analyzing these relaxations. Furthermore, for linear costs we exhibit linear
time best response dynamics that converge to these almost optimal Nash
equilibria. These dynamics mimic the classical greedy approximation algorithm
of Bar-Yehuda and Even [3].
",georgios piliouras,,2012.0,,arXiv,Piliouras2012,True,,arXiv,Not available,LP-based Covering Games with Low Price of Anarchy,bfe323321ed7081918544235a10439a8,http://arxiv.org/abs/1203.0050v1
14875,"  We present a new class of vertex cover and set cover games. The price of
anarchy bounds match the best known constant factor approximation guarantees
for the centralized optimization problems for linear and also for submodular
costs -- in contrast to all previously studied covering games, where the price
of anarchy cannot be bounded by a constant (e.g. [6, 7, 11, 5, 2]). In
particular, we describe a vertex cover game with a price of anarchy of 2. The
rules of the games capture the structure of the linear programming relaxations
of the underlying optimization problems, and our bounds are established by
analyzing these relaxations. Furthermore, for linear costs we exhibit linear
time best response dynamics that converge to these almost optimal Nash
equilibria. These dynamics mimic the classical greedy approximation algorithm
of Bar-Yehuda and Even [3].
",tomas valla,,2012.0,,arXiv,Piliouras2012,True,,arXiv,Not available,LP-based Covering Games with Low Price of Anarchy,bfe323321ed7081918544235a10439a8,http://arxiv.org/abs/1203.0050v1
14876,"  We present a new class of vertex cover and set cover games. The price of
anarchy bounds match the best known constant factor approximation guarantees
for the centralized optimization problems for linear and also for submodular
costs -- in contrast to all previously studied covering games, where the price
of anarchy cannot be bounded by a constant (e.g. [6, 7, 11, 5, 2]). In
particular, we describe a vertex cover game with a price of anarchy of 2. The
rules of the games capture the structure of the linear programming relaxations
of the underlying optimization problems, and our bounds are established by
analyzing these relaxations. Furthermore, for linear costs we exhibit linear
time best response dynamics that converge to these almost optimal Nash
equilibria. These dynamics mimic the classical greedy approximation algorithm
of Bar-Yehuda and Even [3].
",laszlo vegh,,2012.0,,arXiv,Piliouras2012,True,,arXiv,Not available,LP-based Covering Games with Low Price of Anarchy,bfe323321ed7081918544235a10439a8,http://arxiv.org/abs/1203.0050v1
14877,"  We study {\em bottleneck congestion games} where the social cost is
determined by the worst congestion of any resource. These games directly relate
to network routing problems and also job-shop scheduling problems. In typical
bottleneck congestion games, the utility costs of the players are determined by
the worst congested resources that they use. However, the resulting Nash
equilibria are inefficient, since the price of anarchy is proportional on the
number of resources which can be high. Here we show that we can get smaller
price of anarchy with the bottleneck social cost metric. We introduce the {\em
polynomial bottleneck games} where the utility costs of the players are
polynomial functions of the congestion of the resources that they use. In
particular, the delay function for any resource $r$ is $C_{r}^\M$, where $C_r$
is the congestion measured as the number of players that use $r$, and $\M \geq
1$ is an integer constant that defines the degree of the polynomial. The
utility cost of a player is the sum of the individual delays of the resources
that it uses. The social cost of the game remains the same, namely, it is the
worst bottleneck resource congestion: $\max_{r} C_r$. We show that polynomial
bottleneck games are very efficient and give price of anarchy
$O(|R|^{1/(\M+1)})$, where $R$ is the set of resources. This price of anarchy
is tight, since we demonstrate a game with price of anarchy
$\Omega(|R|^{1/(\M+1)})$, for any $\M \geq 1$. We obtain our tight bounds by
using two proof techniques: {\em transformation}, which we use to convert
arbitrary games to simpler games, and {\em expansion}, which we use to bound
the price of anarchy in a simpler game.
",rajgopal kannan,,2010.0,,arXiv,Kannan2010,True,,arXiv,Not available,Polynomial Bottleneck Congestion Games with Optimal Price of Anarchy,1abcadede6a3253a6cc12bedfe8712f1,http://arxiv.org/abs/1010.4812v1
14878,"  We study {\em bottleneck congestion games} where the social cost is
determined by the worst congestion of any resource. These games directly relate
to network routing problems and also job-shop scheduling problems. In typical
bottleneck congestion games, the utility costs of the players are determined by
the worst congested resources that they use. However, the resulting Nash
equilibria are inefficient, since the price of anarchy is proportional on the
number of resources which can be high. Here we show that we can get smaller
price of anarchy with the bottleneck social cost metric. We introduce the {\em
polynomial bottleneck games} where the utility costs of the players are
polynomial functions of the congestion of the resources that they use. In
particular, the delay function for any resource $r$ is $C_{r}^\M$, where $C_r$
is the congestion measured as the number of players that use $r$, and $\M \geq
1$ is an integer constant that defines the degree of the polynomial. The
utility cost of a player is the sum of the individual delays of the resources
that it uses. The social cost of the game remains the same, namely, it is the
worst bottleneck resource congestion: $\max_{r} C_r$. We show that polynomial
bottleneck games are very efficient and give price of anarchy
$O(|R|^{1/(\M+1)})$, where $R$ is the set of resources. This price of anarchy
is tight, since we demonstrate a game with price of anarchy
$\Omega(|R|^{1/(\M+1)})$, for any $\M \geq 1$. We obtain our tight bounds by
using two proof techniques: {\em transformation}, which we use to convert
arbitrary games to simpler games, and {\em expansion}, which we use to bound
the price of anarchy in a simpler game.
",costas busch,,2010.0,,arXiv,Kannan2010,True,,arXiv,Not available,Polynomial Bottleneck Congestion Games with Optimal Price of Anarchy,1abcadede6a3253a6cc12bedfe8712f1,http://arxiv.org/abs/1010.4812v1
14879,"  We study {\em bottleneck congestion games} where the social cost is
determined by the worst congestion of any resource. These games directly relate
to network routing problems and also job-shop scheduling problems. In typical
bottleneck congestion games, the utility costs of the players are determined by
the worst congested resources that they use. However, the resulting Nash
equilibria are inefficient, since the price of anarchy is proportional on the
number of resources which can be high. Here we show that we can get smaller
price of anarchy with the bottleneck social cost metric. We introduce the {\em
polynomial bottleneck games} where the utility costs of the players are
polynomial functions of the congestion of the resources that they use. In
particular, the delay function for any resource $r$ is $C_{r}^\M$, where $C_r$
is the congestion measured as the number of players that use $r$, and $\M \geq
1$ is an integer constant that defines the degree of the polynomial. The
utility cost of a player is the sum of the individual delays of the resources
that it uses. The social cost of the game remains the same, namely, it is the
worst bottleneck resource congestion: $\max_{r} C_r$. We show that polynomial
bottleneck games are very efficient and give price of anarchy
$O(|R|^{1/(\M+1)})$, where $R$ is the set of resources. This price of anarchy
is tight, since we demonstrate a game with price of anarchy
$\Omega(|R|^{1/(\M+1)})$, for any $\M \geq 1$. We obtain our tight bounds by
using two proof techniques: {\em transformation}, which we use to convert
arbitrary games to simpler games, and {\em expansion}, which we use to bound
the price of anarchy in a simpler game.
",athanasios vasilakos,,2010.0,,arXiv,Kannan2010,True,,arXiv,Not available,Polynomial Bottleneck Congestion Games with Optimal Price of Anarchy,1abcadede6a3253a6cc12bedfe8712f1,http://arxiv.org/abs/1010.4812v1
14880,"  We reconsider the well-studied Selfish Routing game with affine latency
functions. The Price of Anarchy for this class of games takes maximum value
4/3; this maximum is attained already for a simple network of two parallel
links, known as Pigou's network. We improve upon the value 4/3 by means of
Coordination Mechanisms.
  We increase the latency functions of the edges in the network, i.e., if
$\ell_e(x)$ is the latency function of an edge $e$, we replace it by
$\hat{\ell}_e(x)$ with $\ell_e(x) \le \hat{\ell}_e(x)$ for all $x$. Then an
adversary fixes a demand rate as input. The engineered Price of Anarchy of the
mechanism is defined as the worst-case ratio of the Nash social cost in the
modified network over the optimal social cost in the original network.
Formally, if $\CM(r)$ denotes the cost of the worst Nash flow in the modified
network for rate $r$ and $\Copt(r)$ denotes the cost of the optimal flow in the
original network for the same rate then [\ePoA = \max_{r \ge 0}
\frac{\CM(r)}{\Copt(r)}.]
  We first exhibit a simple coordination mechanism that achieves for any
network of parallel links an engineered Price of Anarchy strictly less than
4/3. For the case of two parallel links our basic mechanism gives 5/4 = 1.25.
Then, for the case of two parallel links, we describe an optimal mechanism; its
engineered Price of Anarchy lies between 1.191 and 1.192.
",george christodoulou,,2012.0,,arXiv,Christodoulou2012,True,,arXiv,Not available,"Improving the Price of Anarchy for Selfish Routing via Coordination
  Mechanisms",4be3c513934c852b23cd089bb63dc014,http://arxiv.org/abs/1202.2877v2
14881,"  We reconsider the well-studied Selfish Routing game with affine latency
functions. The Price of Anarchy for this class of games takes maximum value
4/3; this maximum is attained already for a simple network of two parallel
links, known as Pigou's network. We improve upon the value 4/3 by means of
Coordination Mechanisms.
  We increase the latency functions of the edges in the network, i.e., if
$\ell_e(x)$ is the latency function of an edge $e$, we replace it by
$\hat{\ell}_e(x)$ with $\ell_e(x) \le \hat{\ell}_e(x)$ for all $x$. Then an
adversary fixes a demand rate as input. The engineered Price of Anarchy of the
mechanism is defined as the worst-case ratio of the Nash social cost in the
modified network over the optimal social cost in the original network.
Formally, if $\CM(r)$ denotes the cost of the worst Nash flow in the modified
network for rate $r$ and $\Copt(r)$ denotes the cost of the optimal flow in the
original network for the same rate then [\ePoA = \max_{r \ge 0}
\frac{\CM(r)}{\Copt(r)}.]
  We first exhibit a simple coordination mechanism that achieves for any
network of parallel links an engineered Price of Anarchy strictly less than
4/3. For the case of two parallel links our basic mechanism gives 5/4 = 1.25.
Then, for the case of two parallel links, we describe an optimal mechanism; its
engineered Price of Anarchy lies between 1.191 and 1.192.
",kurt mehlhorn,,2012.0,,arXiv,Christodoulou2012,True,,arXiv,Not available,"Improving the Price of Anarchy for Selfish Routing via Coordination
  Mechanisms",4be3c513934c852b23cd089bb63dc014,http://arxiv.org/abs/1202.2877v2
14882,"  We reconsider the well-studied Selfish Routing game with affine latency
functions. The Price of Anarchy for this class of games takes maximum value
4/3; this maximum is attained already for a simple network of two parallel
links, known as Pigou's network. We improve upon the value 4/3 by means of
Coordination Mechanisms.
  We increase the latency functions of the edges in the network, i.e., if
$\ell_e(x)$ is the latency function of an edge $e$, we replace it by
$\hat{\ell}_e(x)$ with $\ell_e(x) \le \hat{\ell}_e(x)$ for all $x$. Then an
adversary fixes a demand rate as input. The engineered Price of Anarchy of the
mechanism is defined as the worst-case ratio of the Nash social cost in the
modified network over the optimal social cost in the original network.
Formally, if $\CM(r)$ denotes the cost of the worst Nash flow in the modified
network for rate $r$ and $\Copt(r)$ denotes the cost of the optimal flow in the
original network for the same rate then [\ePoA = \max_{r \ge 0}
\frac{\CM(r)}{\Copt(r)}.]
  We first exhibit a simple coordination mechanism that achieves for any
network of parallel links an engineered Price of Anarchy strictly less than
4/3. For the case of two parallel links our basic mechanism gives 5/4 = 1.25.
Then, for the case of two parallel links, we describe an optimal mechanism; its
engineered Price of Anarchy lies between 1.191 and 1.192.
",evangelia pyrga,,2012.0,,arXiv,Christodoulou2012,True,,arXiv,Not available,"Improving the Price of Anarchy for Selfish Routing via Coordination
  Mechanisms",4be3c513934c852b23cd089bb63dc014,http://arxiv.org/abs/1202.2877v2
14883,"  This article studies the user behavior in non-atomic congestion games. We
consider non-atomic congestion games with continuous and non-decreasing
functions and investigate the limit of the price of anarchy when the total user
volume approaches infinity. We deepen the knowledge on {\em asymptotically well
designed games} \cite{Wu2017Selfishness}, {\em limit games}
\cite{Wu2017Selfishness}, {\em scalability} \cite{Wu2017Selfishness} and {\em
gaugeability} \cite{Colini2017b} that were recently used in the limit analyses
of the price of anarchy for non-atomic congestion games. We develop a unified
framework and derive new techniques that allow a general limit analysis of the
price of anarchy. With these new techniques, we are able to prove a global
convergence on the price of anarchy for non-atomic congestion games with
arbitrary polynomial price functions and arbitrary user volume vector
sequences. Moreover, we show that these new techniques are very flexible and
robust and apply also to non-atomic congestion games with price functions of
other types. In particular, we prove that non-atomic congestion games with
regularly varying price functions are also asymptotically well designed,
provided that the price functions are slightly restricted. Our results greatly
generalize recent results. In particular, our results further support the view
with a general proof that selfishness need not be bad for non-atomic congestion
games.
",zijun wu,,2018.0,,arXiv,Wu2018,True,,arXiv,Not available,Selfishness need not be bad: a general proof,efffb13f5f963500aaf516ee09909dd8,http://arxiv.org/abs/1805.07762v1
14884,"  This article studies the user behavior in non-atomic congestion games. We
consider non-atomic congestion games with continuous and non-decreasing
functions and investigate the limit of the price of anarchy when the total user
volume approaches infinity. We deepen the knowledge on {\em asymptotically well
designed games} \cite{Wu2017Selfishness}, {\em limit games}
\cite{Wu2017Selfishness}, {\em scalability} \cite{Wu2017Selfishness} and {\em
gaugeability} \cite{Colini2017b} that were recently used in the limit analyses
of the price of anarchy for non-atomic congestion games. We develop a unified
framework and derive new techniques that allow a general limit analysis of the
price of anarchy. With these new techniques, we are able to prove a global
convergence on the price of anarchy for non-atomic congestion games with
arbitrary polynomial price functions and arbitrary user volume vector
sequences. Moreover, we show that these new techniques are very flexible and
robust and apply also to non-atomic congestion games with price functions of
other types. In particular, we prove that non-atomic congestion games with
regularly varying price functions are also asymptotically well designed,
provided that the price functions are slightly restricted. Our results greatly
generalize recent results. In particular, our results further support the view
with a general proof that selfishness need not be bad for non-atomic congestion
games.
",rolf mohring,,2018.0,,arXiv,Wu2018,True,,arXiv,Not available,Selfishness need not be bad: a general proof,efffb13f5f963500aaf516ee09909dd8,http://arxiv.org/abs/1805.07762v1
14885,"  This article studies the user behavior in non-atomic congestion games. We
consider non-atomic congestion games with continuous and non-decreasing
functions and investigate the limit of the price of anarchy when the total user
volume approaches infinity. We deepen the knowledge on {\em asymptotically well
designed games} \cite{Wu2017Selfishness}, {\em limit games}
\cite{Wu2017Selfishness}, {\em scalability} \cite{Wu2017Selfishness} and {\em
gaugeability} \cite{Colini2017b} that were recently used in the limit analyses
of the price of anarchy for non-atomic congestion games. We develop a unified
framework and derive new techniques that allow a general limit analysis of the
price of anarchy. With these new techniques, we are able to prove a global
convergence on the price of anarchy for non-atomic congestion games with
arbitrary polynomial price functions and arbitrary user volume vector
sequences. Moreover, we show that these new techniques are very flexible and
robust and apply also to non-atomic congestion games with price functions of
other types. In particular, we prove that non-atomic congestion games with
regularly varying price functions are also asymptotically well designed,
provided that the price functions are slightly restricted. Our results greatly
generalize recent results. In particular, our results further support the view
with a general proof that selfishness need not be bad for non-atomic congestion
games.
",dachuan xu,,2018.0,,arXiv,Wu2018,True,,arXiv,Not available,Selfishness need not be bad: a general proof,efffb13f5f963500aaf516ee09909dd8,http://arxiv.org/abs/1805.07762v1
14886,"  We study a game with \emph{strategic} vendors who own multiple items and a
single buyer with a submodular valuation function. The goal of the vendors is
to maximize their revenue via pricing of the items, given that the buyer will
buy the set of items that maximizes his net payoff.
  We show this game may not always have a pure Nash equilibrium, in contrast to
previous results for the special case where each vendor owns a single item. We
do so by relating our game to an intermediate, discrete game in which the
vendors only choose the available items, and their prices are set exogenously
afterwards.
  We further make use of the intermediate game to provide tight bounds on the
price of anarchy for the subset games that have pure Nash equilibria; we find
that the optimal PoA reached in the previous special cases does not hold, but
only a logarithmic one.
  Finally, we show that for a special case of submodular functions, efficient
pure Nash equilibria always exist.
",omer lev,,2014.0,,arXiv,Lev2014,True,,arXiv,Not available,The Pricing War Continues: On Competitive Multi-Item Pricing,792f641016203119a075a13a64709e13,http://arxiv.org/abs/1408.0258v1
14887,"  In this paper we consider the price of anarchy (PoA) in multi-commodity flows
where the latency or delay function on an edge has a heterogeneous dependency
on the flow commodities, i.e. when the delay on each link is dependent on the
flow of individual commodities, rather than on the aggregate flow. An
application of this study is the performance analysis of a network with
differentiated traffic that may arise when traffic is prioritized according to
some type classification. This study has implications in the debate on
net-neutrality. We provide price of anarchy bounds for networks with $k$ (types
of) commodities where each link is associated with heterogeneous polynomial
delays, i.e. commodity $i$ on edge $e$ faces delay specified by
$g_{i1}(e)f^{\theta}_1(e) + g_{i2}(e)f^{\theta}_2(e) + \ldots +
g_{ik}(e)f^{\theta}_k(e) + c_i(e), $ where $f_i(e)$ is the flow of the $i$th
commodity through edge $e$, $\theta \in {\cal N}$, $g_{i1}(e), g_{i2}(e),
\ldots, g_{ik}(e)$ and $c_i(e)$ are nonnegative constants. We consider both
atomic and non-atomic flows.
  For networks with decomposable delay functions where the delay induced by a
particular commodity is the same, i.e. delays on edge $e$ are defined by
$a_1(e)f_1^\theta(e) + a_2(e)f_2^\theta(e) + \ldots + c(e)$ where $\forall j ,
\forall e: g_{1j}(e) = g_{2j}(e) = \ldots = a_j(e)$, we show an improved bound
on the price of anarchy.
  Further, we show bounds on the price of anarchy for uniform latency functions
where each edge of the network has the same delay function.
",sanjiv kapoor,,2014.0,,arXiv,Kapoor2014,True,,arXiv,Not available,Price of Anarchy with Heterogeneous Latency Functions,15021d47109106236ab81620aa165e96,http://arxiv.org/abs/1407.2991v2
14888,"  In this paper we consider the price of anarchy (PoA) in multi-commodity flows
where the latency or delay function on an edge has a heterogeneous dependency
on the flow commodities, i.e. when the delay on each link is dependent on the
flow of individual commodities, rather than on the aggregate flow. An
application of this study is the performance analysis of a network with
differentiated traffic that may arise when traffic is prioritized according to
some type classification. This study has implications in the debate on
net-neutrality. We provide price of anarchy bounds for networks with $k$ (types
of) commodities where each link is associated with heterogeneous polynomial
delays, i.e. commodity $i$ on edge $e$ faces delay specified by
$g_{i1}(e)f^{\theta}_1(e) + g_{i2}(e)f^{\theta}_2(e) + \ldots +
g_{ik}(e)f^{\theta}_k(e) + c_i(e), $ where $f_i(e)$ is the flow of the $i$th
commodity through edge $e$, $\theta \in {\cal N}$, $g_{i1}(e), g_{i2}(e),
\ldots, g_{ik}(e)$ and $c_i(e)$ are nonnegative constants. We consider both
atomic and non-atomic flows.
  For networks with decomposable delay functions where the delay induced by a
particular commodity is the same, i.e. delays on edge $e$ are defined by
$a_1(e)f_1^\theta(e) + a_2(e)f_2^\theta(e) + \ldots + c(e)$ where $\forall j ,
\forall e: g_{1j}(e) = g_{2j}(e) = \ldots = a_j(e)$, we show an improved bound
on the price of anarchy.
  Further, we show bounds on the price of anarchy for uniform latency functions
where each edge of the network has the same delay function.
",junghwan shin,,2014.0,,arXiv,Kapoor2014,True,,arXiv,Not available,Price of Anarchy with Heterogeneous Latency Functions,15021d47109106236ab81620aa165e96,http://arxiv.org/abs/1407.2991v2
14889,"  Two important metrics for measuring the quality of routing paths are the
maximum edge congestion $C$ and maximum path length $D$. Here, we study
bicriteria in routing games where each player $i$ selfishly selects a path that
simultaneously minimizes its maximum edge congestion $C_i$ and path length
$D_i$. We study the stability and price of anarchy of two bicriteria games:
  - {\em Max games}, where the social cost is $\max(C,D)$ and the player cost
is $\max(C_i, D_i)$. We prove that max games are stable and convergent under
best-response dynamics, and that the price of anarchy is bounded above by the
maximum path length in the players' strategy sets. We also show that this bound
is tight in worst-case scenarios.
  - {\em Sum games}, where the social cost is $C+D$ and the player cost is
$C_i+D_i$. For sum games, we first show the negative result that there are game
instances that have no Nash-equilibria. Therefore, we examine an approximate
game called the {\em sum-bucket game} that is always convergent (and therefore
stable). We show that the price of anarchy in sum-bucket games is bounded above
by $C^* \cdot D^* / (C^* + D^*)$ (with a poly-log factor), where $C^*$ and
$D^*$ are the optimal coordinated congestion and path length. Thus, the
sum-bucket game has typically superior price of anarchy bounds than the max
game. In fact, when either $C^*$ or $D^*$ is small (e.g. constant) the social
cost of the Nash-equilibria is very close to the coordinated optimal $C^* +
D^*$ (within a poly-log factor). We also show that the price of anarchy bound
is tight for cases where both $C^*$ and $D^*$ are large.
",costas busch,,2008.0,,arXiv,Busch2008,True,,arXiv,Not available,Bicretieria Optimization in Routing Games,26876e1c48d964e85ae3e45f3c57bdfd,http://arxiv.org/abs/0801.4851v1
14890,"  Two important metrics for measuring the quality of routing paths are the
maximum edge congestion $C$ and maximum path length $D$. Here, we study
bicriteria in routing games where each player $i$ selfishly selects a path that
simultaneously minimizes its maximum edge congestion $C_i$ and path length
$D_i$. We study the stability and price of anarchy of two bicriteria games:
  - {\em Max games}, where the social cost is $\max(C,D)$ and the player cost
is $\max(C_i, D_i)$. We prove that max games are stable and convergent under
best-response dynamics, and that the price of anarchy is bounded above by the
maximum path length in the players' strategy sets. We also show that this bound
is tight in worst-case scenarios.
  - {\em Sum games}, where the social cost is $C+D$ and the player cost is
$C_i+D_i$. For sum games, we first show the negative result that there are game
instances that have no Nash-equilibria. Therefore, we examine an approximate
game called the {\em sum-bucket game} that is always convergent (and therefore
stable). We show that the price of anarchy in sum-bucket games is bounded above
by $C^* \cdot D^* / (C^* + D^*)$ (with a poly-log factor), where $C^*$ and
$D^*$ are the optimal coordinated congestion and path length. Thus, the
sum-bucket game has typically superior price of anarchy bounds than the max
game. In fact, when either $C^*$ or $D^*$ is small (e.g. constant) the social
cost of the Nash-equilibria is very close to the coordinated optimal $C^* +
D^*$ (within a poly-log factor). We also show that the price of anarchy bound
is tight for cases where both $C^*$ and $D^*$ are large.
",rajgopal kannan,,2008.0,,arXiv,Busch2008,True,,arXiv,Not available,Bicretieria Optimization in Routing Games,26876e1c48d964e85ae3e45f3c57bdfd,http://arxiv.org/abs/0801.4851v1
14891,"  Logit-response dynamics (Alos-Ferrer and Netzer, Games and Economic Behavior
2010) are a rich and natural class of noisy best-response dynamics. In this
work we revise the price of anarchy and the price of stability by considering
the quality of long-run equilibria in these dynamics. Our results show that
prior studies on simpler dynamics of this type can strongly depend on a
synchronous schedule of the players' moves. In particular, a small noise by
itself is not enough to improve the quality of equilibria as soon as other very
natural schedules are used.
",paolo penna,,2015.0,,arXiv,Penna2015,True,,arXiv,Not available,"The price of anarchy and stability in general noisy best-response
  dynamics",b9651f2f9cf555443b0c1be864a579d8,http://arxiv.org/abs/1512.04017v1
14892,"  Selfish Network Creation focuses on modeling real world networks from a
game-theoretic point of view. One of the classic models by Fabrikant et al.
[PODC'03] is the network creation game, where agents correspond to nodes in a
network which buy incident edges for the price of $\alpha$ per edge to minimize
their total distance to all other nodes. The model is well-studied but still
has intriguing open problems. The most famous conjectures state that the price
of anarchy is constant for all $\alpha$ and that for $\alpha \geq n$ all
equilibrium networks are trees.
  We introduce a novel technique for analyzing stable networks for high
edge-price $\alpha$ and employ it to improve on the best known bounds for both
conjectures. In particular we show that for $\alpha > 4n-13$ all equilibrium
networks must be trees, which implies a constant price of anarchy for this
range of $\alpha$. Moreover, we also improve the constant upper bound on the
price of anarchy for equilibrium trees.
",davide bilo,,2017.0,,arXiv,Bilò2017,True,,arXiv,Not available,On the Tree Conjecture for the Network Creation Game,e4dfb9b2b9a8ccdb29154eb8440065a6,http://arxiv.org/abs/1710.01782v2
14893,"  Selfish Network Creation focuses on modeling real world networks from a
game-theoretic point of view. One of the classic models by Fabrikant et al.
[PODC'03] is the network creation game, where agents correspond to nodes in a
network which buy incident edges for the price of $\alpha$ per edge to minimize
their total distance to all other nodes. The model is well-studied but still
has intriguing open problems. The most famous conjectures state that the price
of anarchy is constant for all $\alpha$ and that for $\alpha \geq n$ all
equilibrium networks are trees.
  We introduce a novel technique for analyzing stable networks for high
edge-price $\alpha$ and employ it to improve on the best known bounds for both
conjectures. In particular we show that for $\alpha > 4n-13$ all equilibrium
networks must be trees, which implies a constant price of anarchy for this
range of $\alpha$. Moreover, we also improve the constant upper bound on the
price of anarchy for equilibrium trees.
",pascal lenzner,,2017.0,,arXiv,Bilò2017,True,,arXiv,Not available,On the Tree Conjecture for the Network Creation Game,e4dfb9b2b9a8ccdb29154eb8440065a6,http://arxiv.org/abs/1710.01782v2
14894,"  We study the price of anarchy of mechanisms in the presence of risk-averse
agents. Previous work has focused on agents with quasilinear utilities,
possibly with a budget. Our model subsumes this as a special case but also
captures that agents might be less sensitive to payments than in the
risk-neutral model. We show that many positive price-of-anarchy results proved
in the smoothness framework continue to hold in the more general risk-averse
setting. A sufficient condition is that agents can never end up with negative
quasilinear utility after playing an undominated strategy. This is true, e.g.,
for first-price and second-price auctions. For all-pay auctions, similar
results do not hold: We show that there are Bayes-Nash equilibria with
arbitrarily bad social welfare compared to the optimum.
",thomas kesselheim,,2018.0,,arXiv,Kesselheim2018,True,,arXiv,Not available,Price of Anarchy for Mechanisms with Risk-Averse Agents,ad484a322aaaa22a7888e231d66590dc,http://arxiv.org/abs/1804.09468v1
14895,"  We study the price of anarchy of mechanisms in the presence of risk-averse
agents. Previous work has focused on agents with quasilinear utilities,
possibly with a budget. Our model subsumes this as a special case but also
captures that agents might be less sensitive to payments than in the
risk-neutral model. We show that many positive price-of-anarchy results proved
in the smoothness framework continue to hold in the more general risk-averse
setting. A sufficient condition is that agents can never end up with negative
quasilinear utility after playing an undominated strategy. This is true, e.g.,
for first-price and second-price auctions. For all-pay auctions, similar
results do not hold: We show that there are Bayes-Nash equilibria with
arbitrarily bad social welfare compared to the optimum.
",bojana kodric,,2018.0,,arXiv,Kesselheim2018,True,,arXiv,Not available,Price of Anarchy for Mechanisms with Risk-Averse Agents,ad484a322aaaa22a7888e231d66590dc,http://arxiv.org/abs/1804.09468v1
14896,"  We study the Price of Anarchy of simultaneous first-price auctions for buyers
with submodular and subadditive valuations. The current best upper bounds for
the Bayesian Price of Anarchy of these auctions are e/(e-1) [Syrgkanis and
Tardos 2013] and 2 [Feldman et al. 2013], respectively. We provide matching
lower bounds for both cases even for the case of full information and for mixed
Nash equilibria via an explicit construction.
  We present an alternative proof of the upper bound of e/(e-1) for first-price
auctions with fractionally subadditive valuations which reveals the worst-case
price distribution, that is used as a building block for the matching lower
bound construction.
  We generalize our results to a general class of item bidding auctions that we
call bid-dependent auctions (including first-price auctions and all-pay
auctions) where the winner is always the highest bidder and each bidder's
payment depends only on his own bid.
  Finally, we apply our techniques to discriminatory price multi-unit auctions.
We complement the results of [de Keijzer et al. 2013] for the case of
subadditive valuations, by providing a matching lower bound of 2. For the case
of submodular valuations, we provide a lower bound of 1.109. For the same class
of valuations, we were able to reproduce the upper bound of e/(e-1) using our
non-smooth approach.
",george christodoulou,,2013.0,,arXiv,Christodoulou2013,True,,arXiv,Not available,"Tight Bounds for the Price of Anarchy of Simultaneous First Price
  Auctions",d63eed1ac82b5d665751b5bd2483ebe6,http://arxiv.org/abs/1312.2371v3
14897,"  We study a game with \emph{strategic} vendors who own multiple items and a
single buyer with a submodular valuation function. The goal of the vendors is
to maximize their revenue via pricing of the items, given that the buyer will
buy the set of items that maximizes his net payoff.
  We show this game may not always have a pure Nash equilibrium, in contrast to
previous results for the special case where each vendor owns a single item. We
do so by relating our game to an intermediate, discrete game in which the
vendors only choose the available items, and their prices are set exogenously
afterwards.
  We further make use of the intermediate game to provide tight bounds on the
price of anarchy for the subset games that have pure Nash equilibria; we find
that the optimal PoA reached in the previous special cases does not hold, but
only a logarithmic one.
  Finally, we show that for a special case of submodular functions, efficient
pure Nash equilibria always exist.
",joel oren,,2014.0,,arXiv,Lev2014,True,,arXiv,Not available,The Pricing War Continues: On Competitive Multi-Item Pricing,792f641016203119a075a13a64709e13,http://arxiv.org/abs/1408.0258v1
14898,"  We study the Price of Anarchy of simultaneous first-price auctions for buyers
with submodular and subadditive valuations. The current best upper bounds for
the Bayesian Price of Anarchy of these auctions are e/(e-1) [Syrgkanis and
Tardos 2013] and 2 [Feldman et al. 2013], respectively. We provide matching
lower bounds for both cases even for the case of full information and for mixed
Nash equilibria via an explicit construction.
  We present an alternative proof of the upper bound of e/(e-1) for first-price
auctions with fractionally subadditive valuations which reveals the worst-case
price distribution, that is used as a building block for the matching lower
bound construction.
  We generalize our results to a general class of item bidding auctions that we
call bid-dependent auctions (including first-price auctions and all-pay
auctions) where the winner is always the highest bidder and each bidder's
payment depends only on his own bid.
  Finally, we apply our techniques to discriminatory price multi-unit auctions.
We complement the results of [de Keijzer et al. 2013] for the case of
subadditive valuations, by providing a matching lower bound of 2. For the case
of submodular valuations, we provide a lower bound of 1.109. For the same class
of valuations, we were able to reproduce the upper bound of e/(e-1) using our
non-smooth approach.
",annamaria kovacs,,2013.0,,arXiv,Christodoulou2013,True,,arXiv,Not available,"Tight Bounds for the Price of Anarchy of Simultaneous First Price
  Auctions",d63eed1ac82b5d665751b5bd2483ebe6,http://arxiv.org/abs/1312.2371v3
14899,"  We study the Price of Anarchy of simultaneous first-price auctions for buyers
with submodular and subadditive valuations. The current best upper bounds for
the Bayesian Price of Anarchy of these auctions are e/(e-1) [Syrgkanis and
Tardos 2013] and 2 [Feldman et al. 2013], respectively. We provide matching
lower bounds for both cases even for the case of full information and for mixed
Nash equilibria via an explicit construction.
  We present an alternative proof of the upper bound of e/(e-1) for first-price
auctions with fractionally subadditive valuations which reveals the worst-case
price distribution, that is used as a building block for the matching lower
bound construction.
  We generalize our results to a general class of item bidding auctions that we
call bid-dependent auctions (including first-price auctions and all-pay
auctions) where the winner is always the highest bidder and each bidder's
payment depends only on his own bid.
  Finally, we apply our techniques to discriminatory price multi-unit auctions.
We complement the results of [de Keijzer et al. 2013] for the case of
subadditive valuations, by providing a matching lower bound of 2. For the case
of submodular valuations, we provide a lower bound of 1.109. For the same class
of valuations, we were able to reproduce the upper bound of e/(e-1) using our
non-smooth approach.
",alkmini sgouritsa,,2013.0,,arXiv,Christodoulou2013,True,,arXiv,Not available,"Tight Bounds for the Price of Anarchy of Simultaneous First Price
  Auctions",d63eed1ac82b5d665751b5bd2483ebe6,http://arxiv.org/abs/1312.2371v3
14900,"  We study the Price of Anarchy of simultaneous first-price auctions for buyers
with submodular and subadditive valuations. The current best upper bounds for
the Bayesian Price of Anarchy of these auctions are e/(e-1) [Syrgkanis and
Tardos 2013] and 2 [Feldman et al. 2013], respectively. We provide matching
lower bounds for both cases even for the case of full information and for mixed
Nash equilibria via an explicit construction.
  We present an alternative proof of the upper bound of e/(e-1) for first-price
auctions with fractionally subadditive valuations which reveals the worst-case
price distribution, that is used as a building block for the matching lower
bound construction.
  We generalize our results to a general class of item bidding auctions that we
call bid-dependent auctions (including first-price auctions and all-pay
auctions) where the winner is always the highest bidder and each bidder's
payment depends only on his own bid.
  Finally, we apply our techniques to discriminatory price multi-unit auctions.
We complement the results of [de Keijzer et al. 2013] for the case of
subadditive valuations, by providing a matching lower bound of 2. For the case
of submodular valuations, we provide a lower bound of 1.109. For the same class
of valuations, we were able to reproduce the upper bound of e/(e-1) using our
non-smooth approach.
",bo tang,,2013.0,,arXiv,Christodoulou2013,True,,arXiv,Not available,"Tight Bounds for the Price of Anarchy of Simultaneous First Price
  Auctions",d63eed1ac82b5d665751b5bd2483ebe6,http://arxiv.org/abs/1312.2371v3
14901,"  We introduce a new class of games, called social contribution games (SCGs),
where each player's individual cost is equal to the cost he induces on society
because of his presence. Our results reveal that SCGs constitute useful
abstractions of altruistic games when it comes to the analysis of the robust
price of anarchy. We first show that SCGs are altruism-independently smooth,
i.e., the robust price of anarchy of these games remains the same under
arbitrary altruistic extensions. We then devise a general reduction technique
that enables us to reduce the problem of establishing smoothness for an
altruistic extension of a base game to a corresponding SCG. Our reduction
applies whenever the base game relates to a canonical SCG by satisfying a
simple social contribution boundedness property. As it turns out, several
well-known games satisfy this property and are thus amenable to our reduction
technique. Examples include min-sum scheduling games, congestion games, second
price auctions and valid utility games. Using our technique, we derive mostly
tight bounds on the robust price of anarchy of their altruistic extensions. For
the majority of the mentioned game classes, the results extend to the more
differentiated friendship setting. As we show, our reduction technique covers
this model if the base game satisfies three additional natural properties.
",mona rahn,,2013.0,,arXiv,Rahn2013,True,,arXiv,Not available,Bounding the Inefficiency of Altruism Through Social Contribution Games,4c24aad216959f9b0c63da01ffad5c9d,http://arxiv.org/abs/1308.2497v1
14902,"  We introduce a new class of games, called social contribution games (SCGs),
where each player's individual cost is equal to the cost he induces on society
because of his presence. Our results reveal that SCGs constitute useful
abstractions of altruistic games when it comes to the analysis of the robust
price of anarchy. We first show that SCGs are altruism-independently smooth,
i.e., the robust price of anarchy of these games remains the same under
arbitrary altruistic extensions. We then devise a general reduction technique
that enables us to reduce the problem of establishing smoothness for an
altruistic extension of a base game to a corresponding SCG. Our reduction
applies whenever the base game relates to a canonical SCG by satisfying a
simple social contribution boundedness property. As it turns out, several
well-known games satisfy this property and are thus amenable to our reduction
technique. Examples include min-sum scheduling games, congestion games, second
price auctions and valid utility games. Using our technique, we derive mostly
tight bounds on the robust price of anarchy of their altruistic extensions. For
the majority of the mentioned game classes, the results extend to the more
differentiated friendship setting. As we show, our reduction technique covers
this model if the base game satisfies three additional natural properties.
",guido schafer,,2013.0,,arXiv,Rahn2013,True,,arXiv,Not available,Bounding the Inefficiency of Altruism Through Social Contribution Games,4c24aad216959f9b0c63da01ffad5c9d,http://arxiv.org/abs/1308.2497v1
14903,"  We study the Price of Anarchy of mechanisms for the well-known problem of
one-sided matching, or house allocation, with respect to the social welfare
objective. We consider both ordinal mechanisms, where agents submit preference
lists over the items, and cardinal mechanisms, where agents may submit
numerical values for the items being allocated. We present a general lower
bound of $\Omega(\sqrt{n})$ on the Price of Anarchy, which applies to all
mechanisms. We show that two well-known mechanisms, Probabilistic Serial, and
Random Priority, achieve a matching upper bound. We extend our lower bound to
the Price of Stability of a large class of mechanisms that satisfy a common
proportionality property, and show stronger bounds on the Price of Anarchy of
all deterministic mechanisms.
",george christodoulou,,2015.0,,arXiv,Christodoulou2015,True,,arXiv,Not available,Social Welfare in One-Sided Matching Mechanisms,c43b510327841e6f698a46c5aad8f8f6,http://arxiv.org/abs/1502.03849v2
14904,"  We study the Price of Anarchy of mechanisms for the well-known problem of
one-sided matching, or house allocation, with respect to the social welfare
objective. We consider both ordinal mechanisms, where agents submit preference
lists over the items, and cardinal mechanisms, where agents may submit
numerical values for the items being allocated. We present a general lower
bound of $\Omega(\sqrt{n})$ on the Price of Anarchy, which applies to all
mechanisms. We show that two well-known mechanisms, Probabilistic Serial, and
Random Priority, achieve a matching upper bound. We extend our lower bound to
the Price of Stability of a large class of mechanisms that satisfy a common
proportionality property, and show stronger bounds on the Price of Anarchy of
all deterministic mechanisms.
",aris filos-ratsikas,,2015.0,,arXiv,Christodoulou2015,True,,arXiv,Not available,Social Welfare in One-Sided Matching Mechanisms,c43b510327841e6f698a46c5aad8f8f6,http://arxiv.org/abs/1502.03849v2
14905,"  We study the Price of Anarchy of mechanisms for the well-known problem of
one-sided matching, or house allocation, with respect to the social welfare
objective. We consider both ordinal mechanisms, where agents submit preference
lists over the items, and cardinal mechanisms, where agents may submit
numerical values for the items being allocated. We present a general lower
bound of $\Omega(\sqrt{n})$ on the Price of Anarchy, which applies to all
mechanisms. We show that two well-known mechanisms, Probabilistic Serial, and
Random Priority, achieve a matching upper bound. We extend our lower bound to
the Price of Stability of a large class of mechanisms that satisfy a common
proportionality property, and show stronger bounds on the Price of Anarchy of
all deterministic mechanisms.
",soren frederiksen,,2015.0,,arXiv,Christodoulou2015,True,,arXiv,Not available,Social Welfare in One-Sided Matching Mechanisms,c43b510327841e6f698a46c5aad8f8f6,http://arxiv.org/abs/1502.03849v2
14906,"  We study the Price of Anarchy of mechanisms for the well-known problem of
one-sided matching, or house allocation, with respect to the social welfare
objective. We consider both ordinal mechanisms, where agents submit preference
lists over the items, and cardinal mechanisms, where agents may submit
numerical values for the items being allocated. We present a general lower
bound of $\Omega(\sqrt{n})$ on the Price of Anarchy, which applies to all
mechanisms. We show that two well-known mechanisms, Probabilistic Serial, and
Random Priority, achieve a matching upper bound. We extend our lower bound to
the Price of Stability of a large class of mechanisms that satisfy a common
proportionality property, and show stronger bounds on the Price of Anarchy of
all deterministic mechanisms.
",paul goldberg,,2015.0,,arXiv,Christodoulou2015,True,,arXiv,Not available,Social Welfare in One-Sided Matching Mechanisms,c43b510327841e6f698a46c5aad8f8f6,http://arxiv.org/abs/1502.03849v2
14907,"  We study the Price of Anarchy of mechanisms for the well-known problem of
one-sided matching, or house allocation, with respect to the social welfare
objective. We consider both ordinal mechanisms, where agents submit preference
lists over the items, and cardinal mechanisms, where agents may submit
numerical values for the items being allocated. We present a general lower
bound of $\Omega(\sqrt{n})$ on the Price of Anarchy, which applies to all
mechanisms. We show that two well-known mechanisms, Probabilistic Serial, and
Random Priority, achieve a matching upper bound. We extend our lower bound to
the Price of Stability of a large class of mechanisms that satisfy a common
proportionality property, and show stronger bounds on the Price of Anarchy of
all deterministic mechanisms.
",jie zhang,,2015.0,,arXiv,Christodoulou2015,True,,arXiv,Not available,Social Welfare in One-Sided Matching Mechanisms,c43b510327841e6f698a46c5aad8f8f6,http://arxiv.org/abs/1502.03849v2
14908,"  We study a game with \emph{strategic} vendors who own multiple items and a
single buyer with a submodular valuation function. The goal of the vendors is
to maximize their revenue via pricing of the items, given that the buyer will
buy the set of items that maximizes his net payoff.
  We show this game may not always have a pure Nash equilibrium, in contrast to
previous results for the special case where each vendor owns a single item. We
do so by relating our game to an intermediate, discrete game in which the
vendors only choose the available items, and their prices are set exogenously
afterwards.
  We further make use of the intermediate game to provide tight bounds on the
price of anarchy for the subset games that have pure Nash equilibria; we find
that the optimal PoA reached in the previous special cases does not hold, but
only a logarithmic one.
  Finally, we show that for a special case of submodular functions, efficient
pure Nash equilibria always exist.
",craig boutilier,,2014.0,,arXiv,Lev2014,True,,arXiv,Not available,The Pricing War Continues: On Competitive Multi-Item Pricing,792f641016203119a075a13a64709e13,http://arxiv.org/abs/1408.0258v1
14909,"  We study the Price of Anarchy of mechanisms for the well-known problem of
one-sided matching, or house allocation, with respect to the social welfare
objective. We consider both ordinal mechanisms, where agents submit preference
lists over the items, and cardinal mechanisms, where agents may submit
numerical values for the items being allocated. We present a general lower
bound of $\Omega(\sqrt{n})$ on the Price of Anarchy, which applies to all
mechanisms. We show that two well-known mechanisms, Probabilistic Serial, and
Random Priority, achieve a matching upper bound. We extend our lower bound to
the Price of Stability of a large class of mechanisms that satisfy a common
proportionality property, and show stronger bounds on the Price of Anarchy of
all deterministic mechanisms.
",jinshan zhang,,2015.0,,arXiv,Christodoulou2015,True,,arXiv,Not available,Social Welfare in One-Sided Matching Mechanisms,c43b510327841e6f698a46c5aad8f8f6,http://arxiv.org/abs/1502.03849v2
14910,"  We study Nash equilibria and the price of anarchy in the classic model of
Network Creation Games introduced by Fabrikant et al. In this model every agent
(node) buys links at a prefixed price $\alpha > 0$ in order to get connected to
the network formed by all the $n$ agents. In this setting, the reformulated
tree conjecture states that for $\alpha > n$, every Nash equilibrium network is
a tree. Moreover, Demaine et al. conjectured that the price of anarchy for this
model is constant. Since it was shown that the price of anarchy for trees is
constant, if the tree conjecture were true, then the price of anarchy would be
constant for $\alpha > n$.
  Up to now it has been proved that the \PoA is constant $(i)$ in the
\emph{lower range}, for $\alpha = O(n^{1-\delta})$ with $\delta \geq
\frac{1}{\log n}$ and $(ii)$ in the \emph{upper range}, for $\alpha > 4n-13$.
In contrast, the best upper bound known for the price of anarchy for the
remaining range is $2^{O(\sqrt{\log n})}$.
  In this paper we give new insights into the structure of the Nash equilibria
for $\alpha > n$ and we enlarge the range of the parameter $\alpha$ for which
the price of anarchy is constant. Specifically, we prove that the price of
anarchy is constant for $\alpha > n(1+\epsilon)$ by showing that every
equilibrium of diameter greater than some prefixed constant is a tree.
",c. alvarez,,2018.0,,arXiv,Àlvarez2018,True,,arXiv,Not available,On the Constant Price of Anarchy Conjecture,5eb57c3468f41ab4e358fb5b5a34f28c,http://arxiv.org/abs/1809.08027v1
14911,"  We study Nash equilibria and the price of anarchy in the classic model of
Network Creation Games introduced by Fabrikant et al. In this model every agent
(node) buys links at a prefixed price $\alpha > 0$ in order to get connected to
the network formed by all the $n$ agents. In this setting, the reformulated
tree conjecture states that for $\alpha > n$, every Nash equilibrium network is
a tree. Moreover, Demaine et al. conjectured that the price of anarchy for this
model is constant. Since it was shown that the price of anarchy for trees is
constant, if the tree conjecture were true, then the price of anarchy would be
constant for $\alpha > n$.
  Up to now it has been proved that the \PoA is constant $(i)$ in the
\emph{lower range}, for $\alpha = O(n^{1-\delta})$ with $\delta \geq
\frac{1}{\log n}$ and $(ii)$ in the \emph{upper range}, for $\alpha > 4n-13$.
In contrast, the best upper bound known for the price of anarchy for the
remaining range is $2^{O(\sqrt{\log n})}$.
  In this paper we give new insights into the structure of the Nash equilibria
for $\alpha > n$ and we enlarge the range of the parameter $\alpha$ for which
the price of anarchy is constant. Specifically, we prove that the price of
anarchy is constant for $\alpha > n(1+\epsilon)$ by showing that every
equilibrium of diameter greater than some prefixed constant is a tree.
",a. messegue,,2018.0,,arXiv,Àlvarez2018,True,,arXiv,Not available,On the Constant Price of Anarchy Conjecture,5eb57c3468f41ab4e358fb5b5a34f28c,http://arxiv.org/abs/1809.08027v1
14912,"  We introduce a framework for studying the effect of cooperation on the
quality of outcomes in utility games. Our framework is a coalitional analog of
the smoothness framework of non-cooperative games. Coalitional smoothness
implies bounds on the strong price of anarchy, the loss of quality of
coalitionally stable outcomes, as well as bounds on coalitional versions of
coarse correlated equilibria and sink equilibria, which we define as
out-of-equilibrium myopic behavior as determined by a natural coalitional
version of best-response dynamics.
  Our coalitional smoothness framework captures existing results bounding the
strong price of anarchy of network design games. We show that in any monotone
utility-maximization game, if each player's utility is at least his marginal
contribution to the welfare, then the strong price of anarchy is at most 2.
This captures a broad class of games, including games with a very high price of
anarchy. Additionally, we show that in potential games the strong price of
anarchy is close to the price of stability, the quality of the best Nash
equilibrium.
",yoram bachrach,,2013.0,,arXiv,Bachrach2013,True,,arXiv,Not available,Strong Price of Anarchy and Coalitional Dynamics,0af31fdf9e7e188adbdb7f97879422ab,http://arxiv.org/abs/1307.2537v1
14913,"  We introduce a framework for studying the effect of cooperation on the
quality of outcomes in utility games. Our framework is a coalitional analog of
the smoothness framework of non-cooperative games. Coalitional smoothness
implies bounds on the strong price of anarchy, the loss of quality of
coalitionally stable outcomes, as well as bounds on coalitional versions of
coarse correlated equilibria and sink equilibria, which we define as
out-of-equilibrium myopic behavior as determined by a natural coalitional
version of best-response dynamics.
  Our coalitional smoothness framework captures existing results bounding the
strong price of anarchy of network design games. We show that in any monotone
utility-maximization game, if each player's utility is at least his marginal
contribution to the welfare, then the strong price of anarchy is at most 2.
This captures a broad class of games, including games with a very high price of
anarchy. Additionally, we show that in potential games the strong price of
anarchy is close to the price of stability, the quality of the best Nash
equilibrium.
",vasilis syrgkanis,,2013.0,,arXiv,Bachrach2013,True,,arXiv,Not available,Strong Price of Anarchy and Coalitional Dynamics,0af31fdf9e7e188adbdb7f97879422ab,http://arxiv.org/abs/1307.2537v1
14914,"  We introduce a framework for studying the effect of cooperation on the
quality of outcomes in utility games. Our framework is a coalitional analog of
the smoothness framework of non-cooperative games. Coalitional smoothness
implies bounds on the strong price of anarchy, the loss of quality of
coalitionally stable outcomes, as well as bounds on coalitional versions of
coarse correlated equilibria and sink equilibria, which we define as
out-of-equilibrium myopic behavior as determined by a natural coalitional
version of best-response dynamics.
  Our coalitional smoothness framework captures existing results bounding the
strong price of anarchy of network design games. We show that in any monotone
utility-maximization game, if each player's utility is at least his marginal
contribution to the welfare, then the strong price of anarchy is at most 2.
This captures a broad class of games, including games with a very high price of
anarchy. Additionally, we show that in potential games the strong price of
anarchy is close to the price of stability, the quality of the best Nash
equilibrium.
",eva tardos,,2013.0,,arXiv,Bachrach2013,True,,arXiv,Not available,Strong Price of Anarchy and Coalitional Dynamics,0af31fdf9e7e188adbdb7f97879422ab,http://arxiv.org/abs/1307.2537v1
14915,"  We introduce a framework for studying the effect of cooperation on the
quality of outcomes in utility games. Our framework is a coalitional analog of
the smoothness framework of non-cooperative games. Coalitional smoothness
implies bounds on the strong price of anarchy, the loss of quality of
coalitionally stable outcomes, as well as bounds on coalitional versions of
coarse correlated equilibria and sink equilibria, which we define as
out-of-equilibrium myopic behavior as determined by a natural coalitional
version of best-response dynamics.
  Our coalitional smoothness framework captures existing results bounding the
strong price of anarchy of network design games. We show that in any monotone
utility-maximization game, if each player's utility is at least his marginal
contribution to the welfare, then the strong price of anarchy is at most 2.
This captures a broad class of games, including games with a very high price of
anarchy. Additionally, we show that in potential games the strong price of
anarchy is close to the price of stability, the quality of the best Nash
equilibrium.
",milan vojnovic,,2013.0,,arXiv,Bachrach2013,True,,arXiv,Not available,Strong Price of Anarchy and Coalitional Dynamics,0af31fdf9e7e188adbdb7f97879422ab,http://arxiv.org/abs/1307.2537v1
14916,"  In opinion formation games with directed graphs, a bounded price of anarchy
is only known for weighted Eulerian graphs. Thus, we bound the price of anarchy
for a more general class of directed graphs with conditions intuitively meaning
that each node does not influence the others more than she is influenced, where
the bounds depend on such difference (in a ratio). We also show that there
exists an example just slightly violating the conditions with an unbounded
price of anarchy.
",po-an chen,,2016.0,,arXiv,Chen2016,True,,arXiv,Not available,"Bounds on the Price of Anarchy for a More General Class of Directed
  Graphs in Opinion Formation Games",71498db9becfc458fbea1323a91a1554,http://arxiv.org/abs/1602.02527v2
14917,"  In opinion formation games with directed graphs, a bounded price of anarchy
is only known for weighted Eulerian graphs. Thus, we bound the price of anarchy
for a more general class of directed graphs with conditions intuitively meaning
that each node does not influence the others more than she is influenced, where
the bounds depend on such difference (in a ratio). We also show that there
exists an example just slightly violating the conditions with an unbounded
price of anarchy.
",yi-le chen,,2016.0,,arXiv,Chen2016,True,,arXiv,Not available,"Bounds on the Price of Anarchy for a More General Class of Directed
  Graphs in Opinion Formation Games",71498db9becfc458fbea1323a91a1554,http://arxiv.org/abs/1602.02527v2
14918,"  In opinion formation games with directed graphs, a bounded price of anarchy
is only known for weighted Eulerian graphs. Thus, we bound the price of anarchy
for a more general class of directed graphs with conditions intuitively meaning
that each node does not influence the others more than she is influenced, where
the bounds depend on such difference (in a ratio). We also show that there
exists an example just slightly violating the conditions with an unbounded
price of anarchy.
",chi-jen lu,,2016.0,,arXiv,Chen2016,True,,arXiv,Not available,"Bounds on the Price of Anarchy for a More General Class of Directed
  Graphs in Opinion Formation Games",71498db9becfc458fbea1323a91a1554,http://arxiv.org/abs/1602.02527v2
14919,"  We study a game with \emph{strategic} vendors who own multiple items and a
single buyer with a submodular valuation function. The goal of the vendors is
to maximize their revenue via pricing of the items, given that the buyer will
buy the set of items that maximizes his net payoff.
  We show this game may not always have a pure Nash equilibrium, in contrast to
previous results for the special case where each vendor owns a single item. We
do so by relating our game to an intermediate, discrete game in which the
vendors only choose the available items, and their prices are set exogenously
afterwards.
  We further make use of the intermediate game to provide tight bounds on the
price of anarchy for the subset games that have pure Nash equilibria; we find
that the optimal PoA reached in the previous special cases does not hold, but
only a logarithmic one.
  Finally, we show that for a special case of submodular functions, efficient
pure Nash equilibria always exist.
",jeffery rosenschein,,2014.0,,arXiv,Lev2014,True,,arXiv,Not available,The Pricing War Continues: On Competitive Multi-Item Pricing,792f641016203119a075a13a64709e13,http://arxiv.org/abs/1408.0258v1
14920,"  We consider the well-studied game-theoretic version of machine scheduling in
which jobs correspond to self-interested users and machines correspond to
resources. Here each user chooses a machine trying to minimize her own cost,
and such selfish behavior typically results in some equilibrium which is not
globally optimal: An equilibrium is an allocation where no user can reduce her
own cost by moving to another machine, which in general need not minimize the
makespan, i.e., the maximum load over the machines.
  We provide tight bounds on two well-studied notions in algorithmic game
theory, namely, the price of anarchy and the strong price of anarchy on machine
scheduling setting which lies in between the related and the unrelated machine
case. Both notions study the social cost (makespan) of the worst equilibrium
compared to the optimum, with the strong price of anarchy restricting to a
stronger form of equilibria. Our results extend a prior study comparing the
price of anarchy to the strong price of anarchy for two related machines
(Epstein, Acta Informatica 2010), thus providing further insights on the
relation between these concepts. Our exact bounds give a qualitative and
quantitative comparison between the two models. The bounds also show that the
setting is indeed easier than the two unrelated machines: In the latter, the
strong price of anarchy is $2$, while in ours it is strictly smaller.
",cong chen,,2017.0,,arXiv,Chen2017,True,,arXiv,Not available,"Selfish Jobs with Favorite Machines: Price of Anarchy vs Strong Price of
  Anarchy",2e346561b331f1e9787c035fd7877512,http://arxiv.org/abs/1709.06367v1
14921,"  We consider the well-studied game-theoretic version of machine scheduling in
which jobs correspond to self-interested users and machines correspond to
resources. Here each user chooses a machine trying to minimize her own cost,
and such selfish behavior typically results in some equilibrium which is not
globally optimal: An equilibrium is an allocation where no user can reduce her
own cost by moving to another machine, which in general need not minimize the
makespan, i.e., the maximum load over the machines.
  We provide tight bounds on two well-studied notions in algorithmic game
theory, namely, the price of anarchy and the strong price of anarchy on machine
scheduling setting which lies in between the related and the unrelated machine
case. Both notions study the social cost (makespan) of the worst equilibrium
compared to the optimum, with the strong price of anarchy restricting to a
stronger form of equilibria. Our results extend a prior study comparing the
price of anarchy to the strong price of anarchy for two related machines
(Epstein, Acta Informatica 2010), thus providing further insights on the
relation between these concepts. Our exact bounds give a qualitative and
quantitative comparison between the two models. The bounds also show that the
setting is indeed easier than the two unrelated machines: In the latter, the
strong price of anarchy is $2$, while in ours it is strictly smaller.
",paolo penna,,2017.0,,arXiv,Chen2017,True,,arXiv,Not available,"Selfish Jobs with Favorite Machines: Price of Anarchy vs Strong Price of
  Anarchy",2e346561b331f1e9787c035fd7877512,http://arxiv.org/abs/1709.06367v1
14922,"  We consider the well-studied game-theoretic version of machine scheduling in
which jobs correspond to self-interested users and machines correspond to
resources. Here each user chooses a machine trying to minimize her own cost,
and such selfish behavior typically results in some equilibrium which is not
globally optimal: An equilibrium is an allocation where no user can reduce her
own cost by moving to another machine, which in general need not minimize the
makespan, i.e., the maximum load over the machines.
  We provide tight bounds on two well-studied notions in algorithmic game
theory, namely, the price of anarchy and the strong price of anarchy on machine
scheduling setting which lies in between the related and the unrelated machine
case. Both notions study the social cost (makespan) of the worst equilibrium
compared to the optimum, with the strong price of anarchy restricting to a
stronger form of equilibria. Our results extend a prior study comparing the
price of anarchy to the strong price of anarchy for two related machines
(Epstein, Acta Informatica 2010), thus providing further insights on the
relation between these concepts. Our exact bounds give a qualitative and
quantitative comparison between the two models. The bounds also show that the
setting is indeed easier than the two unrelated machines: In the latter, the
strong price of anarchy is $2$, while in ours it is strictly smaller.
",yinfeng xu,,2017.0,,arXiv,Chen2017,True,,arXiv,Not available,"Selfish Jobs with Favorite Machines: Price of Anarchy vs Strong Price of
  Anarchy",2e346561b331f1e9787c035fd7877512,http://arxiv.org/abs/1709.06367v1
14923,"  We study Nash equilibria and the price of anarchy in the classical model of
Network Creation Games introduced by Fabrikant et al. In this model every agent
(node) buys links at a prefixed price $\alpha>0$ in order to get connected to
the network formed by all the $n$ agents. In this setting, the reformulated
tree conjecture states that for $\alpha > n$, every Nash equilibrium network is
a tree. Since it was shown that the price of anarchy for trees is constant, if
the tree conjecture were true, then the price of anarchy would be constant for
$\alpha >n$. Moreover, Demaine et al. conjectured that the price of anarchy for
this model is constant.
  Up to now the last conjecture has been proven in (i) the \emph{lower range},
for $\alpha = O(n^{1-\epsilon})$ with $\epsilon \geq \frac{1}{\log n}$ and (ii)
in the \emph{upper range}, for $\alpha > 65n$. In contrast, the best upper
bound known for the price of anarchy for the remaining range is
$2^{O(\sqrt{\log n})}$.
  In this paper we give new insights into the structure of the Nash equilibria
for different ranges of $\alpha$ and we enlarge the range for which the price
of anarchy is constant. Regarding the upper range, we prove that every Nash
equilibrium is a tree for $\alpha > 17n$ and that the price of anarchy is
constant even for $\alpha > 9n$. In the lower range, we show that any Nash
equilibrium for $\alpha < n/C$ with $C > 4$, induces an
$\epsilon-$distance-almost-uniform graph.
",carme alvarez,,2017.0,,arXiv,Àlvarez2017,True,,arXiv,Not available,Network Creation Games: Structure vs Anarchy,9df5b1088c0ce99dd6ba973d2129736d,http://arxiv.org/abs/1706.09132v2
14924,"  We study Nash equilibria and the price of anarchy in the classical model of
Network Creation Games introduced by Fabrikant et al. In this model every agent
(node) buys links at a prefixed price $\alpha>0$ in order to get connected to
the network formed by all the $n$ agents. In this setting, the reformulated
tree conjecture states that for $\alpha > n$, every Nash equilibrium network is
a tree. Since it was shown that the price of anarchy for trees is constant, if
the tree conjecture were true, then the price of anarchy would be constant for
$\alpha >n$. Moreover, Demaine et al. conjectured that the price of anarchy for
this model is constant.
  Up to now the last conjecture has been proven in (i) the \emph{lower range},
for $\alpha = O(n^{1-\epsilon})$ with $\epsilon \geq \frac{1}{\log n}$ and (ii)
in the \emph{upper range}, for $\alpha > 65n$. In contrast, the best upper
bound known for the price of anarchy for the remaining range is
$2^{O(\sqrt{\log n})}$.
  In this paper we give new insights into the structure of the Nash equilibria
for different ranges of $\alpha$ and we enlarge the range for which the price
of anarchy is constant. Regarding the upper range, we prove that every Nash
equilibrium is a tree for $\alpha > 17n$ and that the price of anarchy is
constant even for $\alpha > 9n$. In the lower range, we show that any Nash
equilibrium for $\alpha < n/C$ with $C > 4$, induces an
$\epsilon-$distance-almost-uniform graph.
",arnau messegue,,2017.0,,arXiv,Àlvarez2017,True,,arXiv,Not available,Network Creation Games: Structure vs Anarchy,9df5b1088c0ce99dd6ba973d2129736d,http://arxiv.org/abs/1706.09132v2
14925,"  We consider auctions in which greedy algorithms, paired with first-price or
critical-price payment rules, are used to resolve multi-parameter combinatorial
allocation problems. We study the price of anarchy for social welfare in such
auctions. We show for a variety of equilibrium concepts, including Bayes-Nash
equilibrium and correlated equilibrium, the resulting price of anarchy bound is
close to the approximation factor of the underlying greedy algorithm.
",brendan lucier,,2009.0,,arXiv,Lucier2009,True,,arXiv,Not available,Price of Anarchy for Greedy Auctions,def5707856fe837896222751ea1b7d1a,http://arxiv.org/abs/0909.0892v2
14926,"  We consider auctions in which greedy algorithms, paired with first-price or
critical-price payment rules, are used to resolve multi-parameter combinatorial
allocation problems. We study the price of anarchy for social welfare in such
auctions. We show for a variety of equilibrium concepts, including Bayes-Nash
equilibrium and correlated equilibrium, the resulting price of anarchy bound is
close to the approximation factor of the underlying greedy algorithm.
",allan borodin,,2009.0,,arXiv,Lucier2009,True,,arXiv,Not available,Price of Anarchy for Greedy Auctions,def5707856fe837896222751ea1b7d1a,http://arxiv.org/abs/0909.0892v2
14927,"  This paper examines the behavior of the price of anarchy as a function of the
traffic inflow in nonatomic congestion games with multiple origin-destination
(O/D) pairs. Empirical studies in real-world networks show that the price of
anarchy is close to 1 in both light and heavy traffic, thus raising the
question: can these observations be justified theoretically? We first show that
this is not always the case: the price of anarchy may remain a positive
distance away from 1 for all values of the traffic inflow, even in simple
three-link networks with a single O/D pair and smooth, convex costs. On the
other hand, for a large class of cost functions (including all polynomials),
the price of anarchy does converge to 1 in both heavy and light traffic,
irrespective of the network topology and the number of O/D pairs in the
network. We also examine the rate of convergence of the price of anarchy, and
we show that it follows a power law whose degree can be computed explicitly
when the network's cost functions are polynomials.
",riccardo colini-baldeschi,,2017.0,,arXiv,Colini-Baldeschi2017,True,,arXiv,Not available,"When is selfish routing bad? The price of anarchy in light and heavy
  traffic",d34dfff78af759ec38c705afc90a97c9,http://arxiv.org/abs/1703.00927v2
14928,"  One of the main results shown through Roughgarden's notions of smooth games
and robust price of anarchy is that, for any sum-bounded utilitarian social
function, the worst-case price of anarchy of coarse correlated equilibria
coincides with that of pure Nash equilibria in the class of weighted congestion
games with non-negative and non-decreasing latency functions and that such a
value can always be derived through the, so called, smoothness argument. We
significantly extend this result by proving that, for a variety of (even
non-sum-bounded) utilitarian and egalitarian social functions and for a broad
generalization of the class of weighted congestion games with non-negative (and
possibly decreasing) latency functions, the worst-case price of anarchy of
$\epsilon$-approximate coarse correlated equilibria still coincides with that
of $\epsilon$-approximate pure Nash equilibria, for any $\epsilon\geq 0$. As a
byproduct of our proof, it also follows that such a value can always be
determined by making use of the primal-dual method we introduced in a previous
work. It is important to note that our scenario of investigation is beyond the
scope of application of the robust price of anarchy (for as it is currently
defined), so that our result seems unlikely to be alternatively proved via the
smoothness framework.
",vittorio bilo,,2014.0,,arXiv,Bilò2014,True,,arXiv,Not available,"On the Robustness of the Approximate Price of Anarchy in Generalized
  Congestion Games",b3824cf34c3bebf933438e9bfca9df90,http://arxiv.org/abs/1412.0845v1
14929,"  We study {\em bottleneck routing games} where the social cost is determined
by the worst congestion on any edge in the network. In the literature,
bottleneck games assume player utility costs determined by the worst congested
edge in their paths. However, the Nash equilibria of such games are inefficient
since the price of anarchy can be very high and proportional to the size of the
network. In order to obtain smaller price of anarchy we introduce {\em
exponential bottleneck games} where the utility costs of the players are
exponential functions of their congestions. We find that exponential bottleneck
games are very efficient and give a poly-log bound on the price of anarchy:
$O(\log L \cdot \log |E|)$, where $L$ is the largest path length in the
players' strategy sets and $E$ is the set of edges in the graph. By adjusting
the exponential utility costs with a logarithm we obtain games whose player
costs are almost identical to those in regular bottleneck games, and at the
same time have the good price of anarchy of exponential games.
",rajgopal kannan,,2010.0,10.1007/978-3-642-16170-4_20,arXiv,Kannan2010,True,,arXiv,Not available,Bottleneck Routing Games with Low Price of Anarchy,9e3676835c35143114e69790cc570af5,http://arxiv.org/abs/1003.4307v1
14930,"  We study {\em bottleneck routing games} where the social cost is determined
by the worst congestion on any edge in the network. In the literature,
bottleneck games assume player utility costs determined by the worst congested
edge in their paths. However, the Nash equilibria of such games are inefficient
since the price of anarchy can be very high and proportional to the size of the
network. In order to obtain smaller price of anarchy we introduce {\em
exponential bottleneck games} where the utility costs of the players are
exponential functions of their congestions. We find that exponential bottleneck
games are very efficient and give a poly-log bound on the price of anarchy:
$O(\log L \cdot \log |E|)$, where $L$ is the largest path length in the
players' strategy sets and $E$ is the set of edges in the graph. By adjusting
the exponential utility costs with a logarithm we obtain games whose player
costs are almost identical to those in regular bottleneck games, and at the
same time have the good price of anarchy of exponential games.
",costas busch,,2010.0,10.1007/978-3-642-16170-4_20,arXiv,Kannan2010,True,,arXiv,Not available,Bottleneck Routing Games with Low Price of Anarchy,9e3676835c35143114e69790cc570af5,http://arxiv.org/abs/1003.4307v1
14931,"  This paper examines the behavior of the price of anarchy as a function of the
traffic inflow in nonatomic congestion games with multiple origin-destination
(O/D) pairs. Empirical studies in real-world networks show that the price of
anarchy is close to 1 in both light and heavy traffic, thus raising the
question: can these observations be justified theoretically? We first show that
this is not always the case: the price of anarchy may remain a positive
distance away from 1 for all values of the traffic inflow, even in simple
three-link networks with a single O/D pair and smooth, convex costs. On the
other hand, for a large class of cost functions (including all polynomials),
the price of anarchy does converge to 1 in both heavy and light traffic,
irrespective of the network topology and the number of O/D pairs in the
network. We also examine the rate of convergence of the price of anarchy, and
we show that it follows a power law whose degree can be computed explicitly
when the network's cost functions are polynomials.
",roberto cominetti,,2017.0,,arXiv,Colini-Baldeschi2017,True,,arXiv,Not available,"When is selfish routing bad? The price of anarchy in light and heavy
  traffic",d34dfff78af759ec38c705afc90a97c9,http://arxiv.org/abs/1703.00927v2
14932,"  This paper examines the behavior of the price of anarchy as a function of the
traffic inflow in nonatomic congestion games with multiple origin-destination
(O/D) pairs. Empirical studies in real-world networks show that the price of
anarchy is close to 1 in both light and heavy traffic, thus raising the
question: can these observations be justified theoretically? We first show that
this is not always the case: the price of anarchy may remain a positive
distance away from 1 for all values of the traffic inflow, even in simple
three-link networks with a single O/D pair and smooth, convex costs. On the
other hand, for a large class of cost functions (including all polynomials),
the price of anarchy does converge to 1 in both heavy and light traffic,
irrespective of the network topology and the number of O/D pairs in the
network. We also examine the rate of convergence of the price of anarchy, and
we show that it follows a power law whose degree can be computed explicitly
when the network's cost functions are polynomials.
",panayotis mertikopoulos,,2017.0,,arXiv,Colini-Baldeschi2017,True,,arXiv,Not available,"When is selfish routing bad? The price of anarchy in light and heavy
  traffic",d34dfff78af759ec38c705afc90a97c9,http://arxiv.org/abs/1703.00927v2
14933,"  This paper examines the behavior of the price of anarchy as a function of the
traffic inflow in nonatomic congestion games with multiple origin-destination
(O/D) pairs. Empirical studies in real-world networks show that the price of
anarchy is close to 1 in both light and heavy traffic, thus raising the
question: can these observations be justified theoretically? We first show that
this is not always the case: the price of anarchy may remain a positive
distance away from 1 for all values of the traffic inflow, even in simple
three-link networks with a single O/D pair and smooth, convex costs. On the
other hand, for a large class of cost functions (including all polynomials),
the price of anarchy does converge to 1 in both heavy and light traffic,
irrespective of the network topology and the number of O/D pairs in the
network. We also examine the rate of convergence of the price of anarchy, and
we show that it follows a power law whose degree can be computed explicitly
when the network's cost functions are polynomials.
",marco scarsini,,2017.0,,arXiv,Colini-Baldeschi2017,True,,arXiv,Not available,"When is selfish routing bad? The price of anarchy in light and heavy
  traffic",d34dfff78af759ec38c705afc90a97c9,http://arxiv.org/abs/1703.00927v2
14934,"  When many independent users try to route traffic through a network, the flow
can easily become suboptimal as a consequence of congestion of the most
efficient paths. The degree of this suboptimality is quantified by the
so-called ""price of anarchy"" (POA), but so far there are no general rules for
when to expect a large POA in a random network. Here I address this question by
introducing a simple model of flow through a network with randomly-placed
""congestible"" and ""incongestible"" links. I show that the POA is maximized
precisely when the fraction of congestible links matches the percolation
threshold of the lattice. Both the POA and the total cost demonstrate critical
scaling near the percolation threshold.
",brian skinner,,2014.0,10.1103/PhysRevE.91.052126,"Phys. Rev. E 91, 052126 (2015)",Skinner2014,True,,arXiv,Not available,The price of anarchy is maximized at the percolation threshold,f0fac6b2bb36c6f9ab817e3e00f2dafe,http://arxiv.org/abs/1404.2935v3
14935,"  There have been great efforts in studying the cascading behavior in social
networks such as the innovation diffusion, etc. Game theoretically, in a social
network where individuals choose from two strategies: A (the innovation) and B
(the status quo) and get payoff from their neighbors for coordination, it has
long been known that the Price of Anarchy (PoA) of this game is not 1, since
the Nash equilibrium (NE) where all players take B (B Nash) is inferior to the
one all players taking A (A Nash). However, no quantitative analysis has been
performed to give an accurate upper bound of PoA in this game.
  In this paper, we adopt a widely used networked coordination game setting [3]
to study how bad a Nash equilibrium can be and give a tight upper bound of the
PoA of such games. We show that there is an NE that is slightly worse than the
B Nash. On the other hand, the PoA is bounded and the worst NE cannot be much
worse than the B Nash. In addition, we discuss how the PoA upper bound would
change when compatibility between A and B is introduced, and show an intuitive
result that the upper bound strictly decreases as the compatibility is
increased.
",xilun chen,,2014.0,,arXiv,Chen2014,True,,arXiv,Not available,Price of Anarchy of Innovation Diffusion in Social Networks,86808bfea4915eec5d565a78fdee54c8,http://arxiv.org/abs/1407.7319v1
14936,"  We study Nash equilibria and the price of anarchy in the classic model of
Network Creation Games introduced by Fabrikant et al. In this model every agent
(node) buys links at a prefixed price $\alpha > 0$ in order to get connected to
the network formed by all the $n$ agents. In this setting, the reformulated
tree conjecture states that for $\alpha > n$, every Nash equilibrium network is
a tree. Moreover, Demaine et al. conjectured that the price of anarchy for this
model is constant. Since it was shown that the price of anarchy for trees is
constant, if the tree conjecture were true, then the price of anarchy would be
constant for $\alpha > n$.
  Up to now it has been proved that the \PoA is constant $(i)$ in the
\emph{lower range}, for $\alpha = O(n^{1-\delta})$ with $\delta \geq
\frac{1}{\log n}$ and $(ii)$ in the \emph{upper range}, for $\alpha > 4n-13$.
In contrast, the best upper bound known for the price of anarchy for the
remaining range is $2^{O(\sqrt{\log n})}$.
  In this paper we give new insights into the structure of the Nash equilibria
for $\alpha > n$ and we enlarge the range of the parameter $\alpha$ for which
the price of anarchy is constant. Specifically, we prove that the price of
anarchy is constant for $\alpha > n(1+\epsilon)$ by showing that every
equilibrium of diameter greater than some prefixed constant is a tree.
",c. alvarez,,2018.0,,arXiv,Àlvarez2018,True,,arXiv,Not available,On the Constant Price of Anarchy Conjecture,5eb57c3468f41ab4e358fb5b5a34f28c,http://arxiv.org/abs/1809.08027v1
14937,"  There have been great efforts in studying the cascading behavior in social
networks such as the innovation diffusion, etc. Game theoretically, in a social
network where individuals choose from two strategies: A (the innovation) and B
(the status quo) and get payoff from their neighbors for coordination, it has
long been known that the Price of Anarchy (PoA) of this game is not 1, since
the Nash equilibrium (NE) where all players take B (B Nash) is inferior to the
one all players taking A (A Nash). However, no quantitative analysis has been
performed to give an accurate upper bound of PoA in this game.
  In this paper, we adopt a widely used networked coordination game setting [3]
to study how bad a Nash equilibrium can be and give a tight upper bound of the
PoA of such games. We show that there is an NE that is slightly worse than the
B Nash. On the other hand, the PoA is bounded and the worst NE cannot be much
worse than the B Nash. In addition, we discuss how the PoA upper bound would
change when compatibility between A and B is introduced, and show an intuitive
result that the upper bound strictly decreases as the compatibility is
increased.
",chenxia wu,,2014.0,,arXiv,Chen2014,True,,arXiv,Not available,Price of Anarchy of Innovation Diffusion in Social Networks,86808bfea4915eec5d565a78fdee54c8,http://arxiv.org/abs/1407.7319v1
14938,"  Price of anarchy, the performance ratio, which could characterize the loss of
efficiency of the distributed supply chain management compared with the
integrated supply chain management is discussed by utilizing newsvendor problem
in single period which is well-known. In particular, some of remarkable
distributed policies are handled, the performance ratios in each case which
have been investigated in the previous works are analyzed theoretically and the
tighter upper bound of price of anarchy and the lower bound are presented.
Furthermore our approach is developed based on a generalized framework and a
geometric interpretation of price of anarchy is appeared via the literature of
convex optimization.
",t. shinzato,,2009.0,,arXiv,Shinzato2009,True,,arXiv,Not available,"Improved and Developed Upper Bound of Price of Anarchy in Two Echelon
  Case",4ec6481c509fff334e388eefdaabd201,http://arxiv.org/abs/0906.5489v1
14939,"  Price of anarchy, the performance ratio, which could characterize the loss of
efficiency of the distributed supply chain management compared with the
integrated supply chain management is discussed by utilizing newsvendor problem
in single period which is well-known. In particular, some of remarkable
distributed policies are handled, the performance ratios in each case which
have been investigated in the previous works are analyzed theoretically and the
tighter upper bound of price of anarchy and the lower bound are presented.
Furthermore our approach is developed based on a generalized framework and a
geometric interpretation of price of anarchy is appeared via the literature of
convex optimization.
",i. kaku,,2009.0,,arXiv,Shinzato2009,True,,arXiv,Not available,"Improved and Developed Upper Bound of Price of Anarchy in Two Echelon
  Case",4ec6481c509fff334e388eefdaabd201,http://arxiv.org/abs/0906.5489v1
14940,"  We reconsider the well-studied Selfish Routing game with affine latency
functions. The Price of Anarchy for this class of games takes maximum value
4/3; this maximum is attained already for a simple network of two parallel
links, known as Pigou's network. We improve upon the value 4/3 by means of
Coordination Mechanisms.
  We increase the latency functions of the edges in the network, i.e., if
$\ell_e(x)$ is the latency function of an edge $e$, we replace it by
$\hat{\ell}_e(x)$ with $\ell_e(x) \le \hat{\ell}_e(x)$ for all $x$. Then an
adversary fixes a demand rate as input. The engineered Price of Anarchy of the
mechanism is defined as the worst-case ratio of the Nash social cost in the
modified network over the optimal social cost in the original network.
Formally, if $\CM(r)$ denotes the cost of the worst Nash flow in the modified
network for rate $r$ and $\Copt(r)$ denotes the cost of the optimal flow in the
original network for the same rate then [\ePoA = \max_{r \ge 0}
\frac{\CM(r)}{\Copt(r)}.]
  We first exhibit a simple coordination mechanism that achieves for any
network of parallel links an engineered Price of Anarchy strictly less than
4/3. For the case of two parallel links our basic mechanism gives 5/4 = 1.25.
Then, for the case of two parallel links, we describe an optimal mechanism; its
engineered Price of Anarchy lies between 1.191 and 1.192.
",george christodoulou,,2012.0,,arXiv,Christodoulou2012,True,,arXiv,Not available,"Improving the Price of Anarchy for Selfish Routing via Coordination
  Mechanisms",4be3c513934c852b23cd089bb63dc014,http://arxiv.org/abs/1202.2877v2
14941,"  We reconsider the well-studied Selfish Routing game with affine latency
functions. The Price of Anarchy for this class of games takes maximum value
4/3; this maximum is attained already for a simple network of two parallel
links, known as Pigou's network. We improve upon the value 4/3 by means of
Coordination Mechanisms.
  We increase the latency functions of the edges in the network, i.e., if
$\ell_e(x)$ is the latency function of an edge $e$, we replace it by
$\hat{\ell}_e(x)$ with $\ell_e(x) \le \hat{\ell}_e(x)$ for all $x$. Then an
adversary fixes a demand rate as input. The engineered Price of Anarchy of the
mechanism is defined as the worst-case ratio of the Nash social cost in the
modified network over the optimal social cost in the original network.
Formally, if $\CM(r)$ denotes the cost of the worst Nash flow in the modified
network for rate $r$ and $\Copt(r)$ denotes the cost of the optimal flow in the
original network for the same rate then [\ePoA = \max_{r \ge 0}
\frac{\CM(r)}{\Copt(r)}.]
  We first exhibit a simple coordination mechanism that achieves for any
network of parallel links an engineered Price of Anarchy strictly less than
4/3. For the case of two parallel links our basic mechanism gives 5/4 = 1.25.
Then, for the case of two parallel links, we describe an optimal mechanism; its
engineered Price of Anarchy lies between 1.191 and 1.192.
",kurt mehlhorn,,2012.0,,arXiv,Christodoulou2012,True,,arXiv,Not available,"Improving the Price of Anarchy for Selfish Routing via Coordination
  Mechanisms",4be3c513934c852b23cd089bb63dc014,http://arxiv.org/abs/1202.2877v2
14942,"  We reconsider the well-studied Selfish Routing game with affine latency
functions. The Price of Anarchy for this class of games takes maximum value
4/3; this maximum is attained already for a simple network of two parallel
links, known as Pigou's network. We improve upon the value 4/3 by means of
Coordination Mechanisms.
  We increase the latency functions of the edges in the network, i.e., if
$\ell_e(x)$ is the latency function of an edge $e$, we replace it by
$\hat{\ell}_e(x)$ with $\ell_e(x) \le \hat{\ell}_e(x)$ for all $x$. Then an
adversary fixes a demand rate as input. The engineered Price of Anarchy of the
mechanism is defined as the worst-case ratio of the Nash social cost in the
modified network over the optimal social cost in the original network.
Formally, if $\CM(r)$ denotes the cost of the worst Nash flow in the modified
network for rate $r$ and $\Copt(r)$ denotes the cost of the optimal flow in the
original network for the same rate then [\ePoA = \max_{r \ge 0}
\frac{\CM(r)}{\Copt(r)}.]
  We first exhibit a simple coordination mechanism that achieves for any
network of parallel links an engineered Price of Anarchy strictly less than
4/3. For the case of two parallel links our basic mechanism gives 5/4 = 1.25.
Then, for the case of two parallel links, we describe an optimal mechanism; its
engineered Price of Anarchy lies between 1.191 and 1.192.
",evangelia pyrga,,2012.0,,arXiv,Christodoulou2012,True,,arXiv,Not available,"Improving the Price of Anarchy for Selfish Routing via Coordination
  Mechanisms",4be3c513934c852b23cd089bb63dc014,http://arxiv.org/abs/1202.2877v2
14943,"  Many algorithms that are originally designed without explicitly considering
incentive properties are later combined with simple pricing rules and used as
mechanisms. The resulting mechanisms are often natural and simple to
understand. But how good are these algorithms as mechanisms? Truthful reporting
of valuations is typically not a dominant strategy (certainly not with a
pay-your-bid, first-price rule, but it is likely not a good strategy even with
a critical value, or second-price style rule either). Our goal is to show that
a wide class of approximation algorithms yields this way mechanisms with low
Price of Anarchy.
  The seminal result of Lucier and Borodin [SODA 2010] shows that combining a
greedy algorithm that is an $\alpha$-approximation algorithm with a
pay-your-bid payment rule yields a mechanism whose Price of Anarchy is
$O(\alpha)$. In this paper we significantly extend the class of algorithms for
which such a result is available by showing that this close connection between
approximation ratio on the one hand and Price of Anarchy on the other also
holds for the design principle of relaxation and rounding provided that the
relaxation is smooth and the rounding is oblivious.
  We demonstrate the far-reaching consequences of our result by showing its
implications for sparse packing integer programs, such as multi-unit auctions
and generalized matching, for the maximum traveling salesman problem, for
combinatorial auctions, and for single source unsplittable flow problems. In
all these problems our approach leads to novel simple, near-optimal mechanisms
whose Price of Anarchy either matches or beats the performance guarantees of
known mechanisms.
",paul dutting,,2015.0,,arXiv,Dütting2015,True,,arXiv,Not available,Algorithms as Mechanisms: The Price of Anarchy of Relax-and-Round,391cf610e06070cd699a7c0acbb5f2ba,http://arxiv.org/abs/1511.09208v1
14944,"  Many algorithms that are originally designed without explicitly considering
incentive properties are later combined with simple pricing rules and used as
mechanisms. The resulting mechanisms are often natural and simple to
understand. But how good are these algorithms as mechanisms? Truthful reporting
of valuations is typically not a dominant strategy (certainly not with a
pay-your-bid, first-price rule, but it is likely not a good strategy even with
a critical value, or second-price style rule either). Our goal is to show that
a wide class of approximation algorithms yields this way mechanisms with low
Price of Anarchy.
  The seminal result of Lucier and Borodin [SODA 2010] shows that combining a
greedy algorithm that is an $\alpha$-approximation algorithm with a
pay-your-bid payment rule yields a mechanism whose Price of Anarchy is
$O(\alpha)$. In this paper we significantly extend the class of algorithms for
which such a result is available by showing that this close connection between
approximation ratio on the one hand and Price of Anarchy on the other also
holds for the design principle of relaxation and rounding provided that the
relaxation is smooth and the rounding is oblivious.
  We demonstrate the far-reaching consequences of our result by showing its
implications for sparse packing integer programs, such as multi-unit auctions
and generalized matching, for the maximum traveling salesman problem, for
combinatorial auctions, and for single source unsplittable flow problems. In
all these problems our approach leads to novel simple, near-optimal mechanisms
whose Price of Anarchy either matches or beats the performance guarantees of
known mechanisms.
",thomas kesselheim,,2015.0,,arXiv,Dütting2015,True,,arXiv,Not available,Algorithms as Mechanisms: The Price of Anarchy of Relax-and-Round,391cf610e06070cd699a7c0acbb5f2ba,http://arxiv.org/abs/1511.09208v1
14945,"  Many algorithms that are originally designed without explicitly considering
incentive properties are later combined with simple pricing rules and used as
mechanisms. The resulting mechanisms are often natural and simple to
understand. But how good are these algorithms as mechanisms? Truthful reporting
of valuations is typically not a dominant strategy (certainly not with a
pay-your-bid, first-price rule, but it is likely not a good strategy even with
a critical value, or second-price style rule either). Our goal is to show that
a wide class of approximation algorithms yields this way mechanisms with low
Price of Anarchy.
  The seminal result of Lucier and Borodin [SODA 2010] shows that combining a
greedy algorithm that is an $\alpha$-approximation algorithm with a
pay-your-bid payment rule yields a mechanism whose Price of Anarchy is
$O(\alpha)$. In this paper we significantly extend the class of algorithms for
which such a result is available by showing that this close connection between
approximation ratio on the one hand and Price of Anarchy on the other also
holds for the design principle of relaxation and rounding provided that the
relaxation is smooth and the rounding is oblivious.
  We demonstrate the far-reaching consequences of our result by showing its
implications for sparse packing integer programs, such as multi-unit auctions
and generalized matching, for the maximum traveling salesman problem, for
combinatorial auctions, and for single source unsplittable flow problems. In
all these problems our approach leads to novel simple, near-optimal mechanisms
whose Price of Anarchy either matches or beats the performance guarantees of
known mechanisms.
",eva tardos,,2015.0,,arXiv,Dütting2015,True,,arXiv,Not available,Algorithms as Mechanisms: The Price of Anarchy of Relax-and-Round,391cf610e06070cd699a7c0acbb5f2ba,http://arxiv.org/abs/1511.09208v1
14946,"  Logit-response dynamics (Alos-Ferrer and Netzer, Games and Economic Behavior
2010) are a rich and natural class of noisy best-response dynamics. In this
work we revise the price of anarchy and the price of stability by considering
the quality of long-run equilibria in these dynamics. Our results show that
prior studies on simpler dynamics of this type can strongly depend on a
synchronous schedule of the players' moves. In particular, a small noise by
itself is not enough to improve the quality of equilibria as soon as other very
natural schedules are used.
",paolo penna,,2015.0,,arXiv,Penna2015,True,,arXiv,Not available,"The price of anarchy and stability in general noisy best-response
  dynamics",b9651f2f9cf555443b0c1be864a579d8,http://arxiv.org/abs/1512.04017v1
14947,"  We study Nash equilibria and the price of anarchy in the classic model of
Network Creation Games introduced by Fabrikant et al. In this model every agent
(node) buys links at a prefixed price $\alpha > 0$ in order to get connected to
the network formed by all the $n$ agents. In this setting, the reformulated
tree conjecture states that for $\alpha > n$, every Nash equilibrium network is
a tree. Moreover, Demaine et al. conjectured that the price of anarchy for this
model is constant. Since it was shown that the price of anarchy for trees is
constant, if the tree conjecture were true, then the price of anarchy would be
constant for $\alpha > n$.
  Up to now it has been proved that the \PoA is constant $(i)$ in the
\emph{lower range}, for $\alpha = O(n^{1-\delta})$ with $\delta \geq
\frac{1}{\log n}$ and $(ii)$ in the \emph{upper range}, for $\alpha > 4n-13$.
In contrast, the best upper bound known for the price of anarchy for the
remaining range is $2^{O(\sqrt{\log n})}$.
  In this paper we give new insights into the structure of the Nash equilibria
for $\alpha > n$ and we enlarge the range of the parameter $\alpha$ for which
the price of anarchy is constant. Specifically, we prove that the price of
anarchy is constant for $\alpha > n(1+\epsilon)$ by showing that every
equilibrium of diameter greater than some prefixed constant is a tree.
",a. messegue,,2018.0,,arXiv,Àlvarez2018,True,,arXiv,Not available,On the Constant Price of Anarchy Conjecture,5eb57c3468f41ab4e358fb5b5a34f28c,http://arxiv.org/abs/1809.08027v1
14948,"  We generalize the notions of user equilibrium and system optimum to
non-atomic congestion games with stochastic demands. We establish upper bounds
on the price of anarchy for three different settings of link cost functions and
demand distributions, namely, (a) affine cost functions and general
distributions, (b) polynomial cost functions and general positive-valued
distributions, and (c) polynomial cost functions and the normal distributions.
All the upper bounds are tight in some special cases, including the case of
deterministic demands.
",chenlan wang,,2013.0,,arXiv,Wang2013,True,,arXiv,Not available,Price of Anarchy for Non-atomic Congestion Games with Stochastic Demands,39c018e2806cbe8809675f1bc41b60e6,http://arxiv.org/abs/1310.4874v1
14949,"  We generalize the notions of user equilibrium and system optimum to
non-atomic congestion games with stochastic demands. We establish upper bounds
on the price of anarchy for three different settings of link cost functions and
demand distributions, namely, (a) affine cost functions and general
distributions, (b) polynomial cost functions and general positive-valued
distributions, and (c) polynomial cost functions and the normal distributions.
All the upper bounds are tight in some special cases, including the case of
deterministic demands.
",xuan doan,,2013.0,,arXiv,Wang2013,True,,arXiv,Not available,Price of Anarchy for Non-atomic Congestion Games with Stochastic Demands,39c018e2806cbe8809675f1bc41b60e6,http://arxiv.org/abs/1310.4874v1
14950,"  We generalize the notions of user equilibrium and system optimum to
non-atomic congestion games with stochastic demands. We establish upper bounds
on the price of anarchy for three different settings of link cost functions and
demand distributions, namely, (a) affine cost functions and general
distributions, (b) polynomial cost functions and general positive-valued
distributions, and (c) polynomial cost functions and the normal distributions.
All the upper bounds are tight in some special cases, including the case of
deterministic demands.
",bo chen,,2013.0,,arXiv,Wang2013,True,,arXiv,Not available,Price of Anarchy for Non-atomic Congestion Games with Stochastic Demands,39c018e2806cbe8809675f1bc41b60e6,http://arxiv.org/abs/1310.4874v1
14951,"  We model the formation of networks as the result of a game where by players
act selfishly to get the portfolio of links they desire most. The integration
of player strategies into the network formation model is appropriate for
organizational networks because in these smaller networks, dynamics are not
random, but the result of intentional actions carried through by players
maximizing their own objectives. This model is a better framework for the
analysis of influences upon a network because it integrates the strategies of
the players involved. We present an Integer Program that calculates the price
of anarchy of this game by finding the worst stable graph and the best
coordinated graph for this game. We simulate the formation of the network and
calculated the simulated price of anarchy, which we find tends to be rather
low.
",shaun lichter,,2011.0,,arXiv,Lichter2011,True,,arXiv,Not available,"The Calculation and Simulation of the Price of Anarchy for Network
  Formation Games",4c51f321c4d44cae6c28c44271499b26,http://arxiv.org/abs/1108.4115v2
14952,"  We model the formation of networks as the result of a game where by players
act selfishly to get the portfolio of links they desire most. The integration
of player strategies into the network formation model is appropriate for
organizational networks because in these smaller networks, dynamics are not
random, but the result of intentional actions carried through by players
maximizing their own objectives. This model is a better framework for the
analysis of influences upon a network because it integrates the strategies of
the players involved. We present an Integer Program that calculates the price
of anarchy of this game by finding the worst stable graph and the best
coordinated graph for this game. We simulate the formation of the network and
calculated the simulated price of anarchy, which we find tends to be rather
low.
",christopher griffin,,2011.0,,arXiv,Lichter2011,True,,arXiv,Not available,"The Calculation and Simulation of the Price of Anarchy for Network
  Formation Games",4c51f321c4d44cae6c28c44271499b26,http://arxiv.org/abs/1108.4115v2
14953,"  We model the formation of networks as the result of a game where by players
act selfishly to get the portfolio of links they desire most. The integration
of player strategies into the network formation model is appropriate for
organizational networks because in these smaller networks, dynamics are not
random, but the result of intentional actions carried through by players
maximizing their own objectives. This model is a better framework for the
analysis of influences upon a network because it integrates the strategies of
the players involved. We present an Integer Program that calculates the price
of anarchy of this game by finding the worst stable graph and the best
coordinated graph for this game. We simulate the formation of the network and
calculated the simulated price of anarchy, which we find tends to be rather
low.
",terry friesz,,2011.0,,arXiv,Lichter2011,True,,arXiv,Not available,"The Calculation and Simulation of the Price of Anarchy for Network
  Formation Games",4c51f321c4d44cae6c28c44271499b26,http://arxiv.org/abs/1108.4115v2
14954,"  Uncoordinated individuals in human society pursuing their personally optimal
strategies do not always achieve the social optimum, the most beneficial state
to the society as a whole. Instead, strategies form Nash equilibria which are
often socially suboptimal. Society, therefore, has to pay a price of anarchy
for the lack of coordination among its members. Here we assess this price of
anarchy by analyzing the travel times in road networks of several major cities.
Our simulation shows that uncoordinated drivers possibly waste a considerable
amount of their travel time. Counterintuitively,simply blocking certain streets
can partially improve the traffic conditions. We analyze various complex
networks and discuss the possibility of similar paradoxes in physics.
",hyejin youn,,2007.0,10.1103/PhysRevLett.101.128701,arXiv,Youn2007,True,,arXiv,Not available,"The Price of Anarchy in Transportation Networks: Efficiency and
  Optimality Control",4cf9433cab8dc9e2bbd3267853f6cfac,http://arxiv.org/abs/0712.1598v4
14955,"  Uncoordinated individuals in human society pursuing their personally optimal
strategies do not always achieve the social optimum, the most beneficial state
to the society as a whole. Instead, strategies form Nash equilibria which are
often socially suboptimal. Society, therefore, has to pay a price of anarchy
for the lack of coordination among its members. Here we assess this price of
anarchy by analyzing the travel times in road networks of several major cities.
Our simulation shows that uncoordinated drivers possibly waste a considerable
amount of their travel time. Counterintuitively,simply blocking certain streets
can partially improve the traffic conditions. We analyze various complex
networks and discuss the possibility of similar paradoxes in physics.
",michael gastner,,2007.0,10.1103/PhysRevLett.101.128701,arXiv,Youn2007,True,,arXiv,Not available,"The Price of Anarchy in Transportation Networks: Efficiency and
  Optimality Control",4cf9433cab8dc9e2bbd3267853f6cfac,http://arxiv.org/abs/0712.1598v4
14956,"  Uncoordinated individuals in human society pursuing their personally optimal
strategies do not always achieve the social optimum, the most beneficial state
to the society as a whole. Instead, strategies form Nash equilibria which are
often socially suboptimal. Society, therefore, has to pay a price of anarchy
for the lack of coordination among its members. Here we assess this price of
anarchy by analyzing the travel times in road networks of several major cities.
Our simulation shows that uncoordinated drivers possibly waste a considerable
amount of their travel time. Counterintuitively,simply blocking certain streets
can partially improve the traffic conditions. We analyze various complex
networks and discuss the possibility of similar paradoxes in physics.
",hawoong jeong,,2007.0,10.1103/PhysRevLett.101.128701,arXiv,Youn2007,True,,arXiv,Not available,"The Price of Anarchy in Transportation Networks: Efficiency and
  Optimality Control",4cf9433cab8dc9e2bbd3267853f6cfac,http://arxiv.org/abs/0712.1598v4
14957,"  In opinion formation games with directed graphs, a bounded price of anarchy
is only known for weighted Eulerian graphs. Thus, we bound the price of anarchy
for a more general class of directed graphs with conditions intuitively meaning
that each node does not influence the others more than she is influenced, where
the bounds depend on such difference (in a ratio). We also show that there
exists an example just slightly violating the conditions with an unbounded
price of anarchy.
",po-an chen,,2016.0,,arXiv,Chen2016,True,,arXiv,Not available,"Bounds on the Price of Anarchy for a More General Class of Directed
  Graphs in Opinion Formation Games",71498db9becfc458fbea1323a91a1554,http://arxiv.org/abs/1602.02527v2
14958,"  We introduce a framework for studying the effect of cooperation on the
quality of outcomes in utility games. Our framework is a coalitional analog of
the smoothness framework of non-cooperative games. Coalitional smoothness
implies bounds on the strong price of anarchy, the loss of quality of
coalitionally stable outcomes, as well as bounds on coalitional versions of
coarse correlated equilibria and sink equilibria, which we define as
out-of-equilibrium myopic behavior as determined by a natural coalitional
version of best-response dynamics.
  Our coalitional smoothness framework captures existing results bounding the
strong price of anarchy of network design games. We show that in any monotone
utility-maximization game, if each player's utility is at least his marginal
contribution to the welfare, then the strong price of anarchy is at most 2.
This captures a broad class of games, including games with a very high price of
anarchy. Additionally, we show that in potential games the strong price of
anarchy is close to the price of stability, the quality of the best Nash
equilibrium.
",yoram bachrach,,2013.0,,arXiv,Bachrach2013,True,,arXiv,Not available,Strong Price of Anarchy and Coalitional Dynamics,0af31fdf9e7e188adbdb7f97879422ab,http://arxiv.org/abs/1307.2537v1
14959,"  In opinion formation games with directed graphs, a bounded price of anarchy
is only known for weighted Eulerian graphs. Thus, we bound the price of anarchy
for a more general class of directed graphs with conditions intuitively meaning
that each node does not influence the others more than she is influenced, where
the bounds depend on such difference (in a ratio). We also show that there
exists an example just slightly violating the conditions with an unbounded
price of anarchy.
",yi-le chen,,2016.0,,arXiv,Chen2016,True,,arXiv,Not available,"Bounds on the Price of Anarchy for a More General Class of Directed
  Graphs in Opinion Formation Games",71498db9becfc458fbea1323a91a1554,http://arxiv.org/abs/1602.02527v2
14960,"  In opinion formation games with directed graphs, a bounded price of anarchy
is only known for weighted Eulerian graphs. Thus, we bound the price of anarchy
for a more general class of directed graphs with conditions intuitively meaning
that each node does not influence the others more than she is influenced, where
the bounds depend on such difference (in a ratio). We also show that there
exists an example just slightly violating the conditions with an unbounded
price of anarchy.
",chi-jen lu,,2016.0,,arXiv,Chen2016,True,,arXiv,Not available,"Bounds on the Price of Anarchy for a More General Class of Directed
  Graphs in Opinion Formation Games",71498db9becfc458fbea1323a91a1554,http://arxiv.org/abs/1602.02527v2
14961,"  We study Nash equilibria and the price of anarchy in the classic model of
Network Creation Games introduced by Fabrikant et al. In this model every agent
(node) buys links at a prefixed price $\alpha > 0$ in order to get connected to
the network formed by all the $n$ agents. In this setting, the reformulated
tree conjecture states that for $\alpha > n$, every Nash equilibrium network is
a tree. Moreover, Demaine et al. conjectured that the price of anarchy for this
model is constant. Since it was shown that the price of anarchy for trees is
constant, if the tree conjecture were true, then the price of anarchy would be
constant for $\alpha > n$.
  Up to now it has been proved that the \PoA is constant $(i)$ in the
\emph{lower range}, for $\alpha = O(n^{1-\delta})$ with $\delta \geq
\frac{1}{\log n}$ and $(ii)$ in the \emph{upper range}, for $\alpha > 4n-13$.
In contrast, the best upper bound known for the price of anarchy for the
remaining range is $2^{O(\sqrt{\log n})}$.
  In this paper we give new insights into the structure of the Nash equilibria
for $\alpha > n$ and we enlarge the range of the parameter $\alpha$ for which
the price of anarchy is constant. Specifically, we prove that the price of
anarchy is constant for $\alpha > n(1+\epsilon)$ by showing that every
equilibrium of diameter greater than some prefixed constant is a tree.
",c. alvarez,,2018.0,,arXiv,Àlvarez2018,True,,arXiv,Not available,On the Constant Price of Anarchy Conjecture,5eb57c3468f41ab4e358fb5b5a34f28c,http://arxiv.org/abs/1809.08027v1
14962,"  We study Nash equilibria and the price of anarchy in the classic model of
Network Creation Games introduced by Fabrikant et al. In this model every agent
(node) buys links at a prefixed price $\alpha > 0$ in order to get connected to
the network formed by all the $n$ agents. In this setting, the reformulated
tree conjecture states that for $\alpha > n$, every Nash equilibrium network is
a tree. Moreover, Demaine et al. conjectured that the price of anarchy for this
model is constant. Since it was shown that the price of anarchy for trees is
constant, if the tree conjecture were true, then the price of anarchy would be
constant for $\alpha > n$.
  Up to now it has been proved that the \PoA is constant $(i)$ in the
\emph{lower range}, for $\alpha = O(n^{1-\delta})$ with $\delta \geq
\frac{1}{\log n}$ and $(ii)$ in the \emph{upper range}, for $\alpha > 4n-13$.
In contrast, the best upper bound known for the price of anarchy for the
remaining range is $2^{O(\sqrt{\log n})}$.
  In this paper we give new insights into the structure of the Nash equilibria
for $\alpha > n$ and we enlarge the range of the parameter $\alpha$ for which
the price of anarchy is constant. Specifically, we prove that the price of
anarchy is constant for $\alpha > n(1+\epsilon)$ by showing that every
equilibrium of diameter greater than some prefixed constant is a tree.
",a. messegue,,2018.0,,arXiv,Àlvarez2018,True,,arXiv,Not available,On the Constant Price of Anarchy Conjecture,5eb57c3468f41ab4e358fb5b5a34f28c,http://arxiv.org/abs/1809.08027v1
14963,"  We study Nash equilibria and the price of anarchy in the classical model of
Network Creation Games introduced by Fabrikant et al. In this model every agent
(node) buys links at a prefixed price $\alpha>0$ in order to get connected to
the network formed by all the $n$ agents. In this setting, the reformulated
tree conjecture states that for $\alpha > n$, every Nash equilibrium network is
a tree. Since it was shown that the price of anarchy for trees is constant, if
the tree conjecture were true, then the price of anarchy would be constant for
$\alpha >n$. Moreover, Demaine et al. conjectured that the price of anarchy for
this model is constant.
  Up to now the last conjecture has been proven in (i) the \emph{lower range},
for $\alpha = O(n^{1-\epsilon})$ with $\epsilon \geq \frac{1}{\log n}$ and (ii)
in the \emph{upper range}, for $\alpha > 65n$. In contrast, the best upper
bound known for the price of anarchy for the remaining range is
$2^{O(\sqrt{\log n})}$.
  In this paper we give new insights into the structure of the Nash equilibria
for different ranges of $\alpha$ and we enlarge the range for which the price
of anarchy is constant. Regarding the upper range, we prove that every Nash
equilibrium is a tree for $\alpha > 17n$ and that the price of anarchy is
constant even for $\alpha > 9n$. In the lower range, we show that any Nash
equilibrium for $\alpha < n/C$ with $C > 4$, induces an
$\epsilon-$distance-almost-uniform graph.
",carme alvarez,,2017.0,,arXiv,Àlvarez2017,True,,arXiv,Not available,Network Creation Games: Structure vs Anarchy,9df5b1088c0ce99dd6ba973d2129736d,http://arxiv.org/abs/1706.09132v2
14964,"  We study Nash equilibria and the price of anarchy in the classical model of
Network Creation Games introduced by Fabrikant et al. In this model every agent
(node) buys links at a prefixed price $\alpha>0$ in order to get connected to
the network formed by all the $n$ agents. In this setting, the reformulated
tree conjecture states that for $\alpha > n$, every Nash equilibrium network is
a tree. Since it was shown that the price of anarchy for trees is constant, if
the tree conjecture were true, then the price of anarchy would be constant for
$\alpha >n$. Moreover, Demaine et al. conjectured that the price of anarchy for
this model is constant.
  Up to now the last conjecture has been proven in (i) the \emph{lower range},
for $\alpha = O(n^{1-\epsilon})$ with $\epsilon \geq \frac{1}{\log n}$ and (ii)
in the \emph{upper range}, for $\alpha > 65n$. In contrast, the best upper
bound known for the price of anarchy for the remaining range is
$2^{O(\sqrt{\log n})}$.
  In this paper we give new insights into the structure of the Nash equilibria
for different ranges of $\alpha$ and we enlarge the range for which the price
of anarchy is constant. Regarding the upper range, we prove that every Nash
equilibrium is a tree for $\alpha > 17n$ and that the price of anarchy is
constant even for $\alpha > 9n$. In the lower range, we show that any Nash
equilibrium for $\alpha < n/C$ with $C > 4$, induces an
$\epsilon-$distance-almost-uniform graph.
",arnau messegue,,2017.0,,arXiv,Àlvarez2017,True,,arXiv,Not available,Network Creation Games: Structure vs Anarchy,9df5b1088c0ce99dd6ba973d2129736d,http://arxiv.org/abs/1706.09132v2
14965,"  We consider auctions in which greedy algorithms, paired with first-price or
critical-price payment rules, are used to resolve multi-parameter combinatorial
allocation problems. We study the price of anarchy for social welfare in such
auctions. We show for a variety of equilibrium concepts, including Bayes-Nash
equilibrium and correlated equilibrium, the resulting price of anarchy bound is
close to the approximation factor of the underlying greedy algorithm.
",brendan lucier,,2009.0,,arXiv,Lucier2009,True,,arXiv,Not available,Price of Anarchy for Greedy Auctions,def5707856fe837896222751ea1b7d1a,http://arxiv.org/abs/0909.0892v2
14966,"  We consider auctions in which greedy algorithms, paired with first-price or
critical-price payment rules, are used to resolve multi-parameter combinatorial
allocation problems. We study the price of anarchy for social welfare in such
auctions. We show for a variety of equilibrium concepts, including Bayes-Nash
equilibrium and correlated equilibrium, the resulting price of anarchy bound is
close to the approximation factor of the underlying greedy algorithm.
",allan borodin,,2009.0,,arXiv,Lucier2009,True,,arXiv,Not available,Price of Anarchy for Greedy Auctions,def5707856fe837896222751ea1b7d1a,http://arxiv.org/abs/0909.0892v2
14967,"  We introduce a framework for studying the effect of cooperation on the
quality of outcomes in utility games. Our framework is a coalitional analog of
the smoothness framework of non-cooperative games. Coalitional smoothness
implies bounds on the strong price of anarchy, the loss of quality of
coalitionally stable outcomes, as well as bounds on coalitional versions of
coarse correlated equilibria and sink equilibria, which we define as
out-of-equilibrium myopic behavior as determined by a natural coalitional
version of best-response dynamics.
  Our coalitional smoothness framework captures existing results bounding the
strong price of anarchy of network design games. We show that in any monotone
utility-maximization game, if each player's utility is at least his marginal
contribution to the welfare, then the strong price of anarchy is at most 2.
This captures a broad class of games, including games with a very high price of
anarchy. Additionally, we show that in potential games the strong price of
anarchy is close to the price of stability, the quality of the best Nash
equilibrium.
",vasilis syrgkanis,,2013.0,,arXiv,Bachrach2013,True,,arXiv,Not available,Strong Price of Anarchy and Coalitional Dynamics,0af31fdf9e7e188adbdb7f97879422ab,http://arxiv.org/abs/1307.2537v1
14968,"  We consider the well-studied game-theoretic version of machine scheduling in
which jobs correspond to self-interested users and machines correspond to
resources. Here each user chooses a machine trying to minimize her own cost,
and such selfish behavior typically results in some equilibrium which is not
globally optimal: An equilibrium is an allocation where no user can reduce her
own cost by moving to another machine, which in general need not minimize the
makespan, i.e., the maximum load over the machines.
  We provide tight bounds on two well-studied notions in algorithmic game
theory, namely, the price of anarchy and the strong price of anarchy on machine
scheduling setting which lies in between the related and the unrelated machine
case. Both notions study the social cost (makespan) of the worst equilibrium
compared to the optimum, with the strong price of anarchy restricting to a
stronger form of equilibria. Our results extend a prior study comparing the
price of anarchy to the strong price of anarchy for two related machines
(Epstein, Acta Informatica 2010), thus providing further insights on the
relation between these concepts. Our exact bounds give a qualitative and
quantitative comparison between the two models. The bounds also show that the
setting is indeed easier than the two unrelated machines: In the latter, the
strong price of anarchy is $2$, while in ours it is strictly smaller.
",cong chen,,2017.0,,arXiv,Chen2017,True,,arXiv,Not available,"Selfish Jobs with Favorite Machines: Price of Anarchy vs Strong Price of
  Anarchy",2e346561b331f1e9787c035fd7877512,http://arxiv.org/abs/1709.06367v1
14969,"  We consider the well-studied game-theoretic version of machine scheduling in
which jobs correspond to self-interested users and machines correspond to
resources. Here each user chooses a machine trying to minimize her own cost,
and such selfish behavior typically results in some equilibrium which is not
globally optimal: An equilibrium is an allocation where no user can reduce her
own cost by moving to another machine, which in general need not minimize the
makespan, i.e., the maximum load over the machines.
  We provide tight bounds on two well-studied notions in algorithmic game
theory, namely, the price of anarchy and the strong price of anarchy on machine
scheduling setting which lies in between the related and the unrelated machine
case. Both notions study the social cost (makespan) of the worst equilibrium
compared to the optimum, with the strong price of anarchy restricting to a
stronger form of equilibria. Our results extend a prior study comparing the
price of anarchy to the strong price of anarchy for two related machines
(Epstein, Acta Informatica 2010), thus providing further insights on the
relation between these concepts. Our exact bounds give a qualitative and
quantitative comparison between the two models. The bounds also show that the
setting is indeed easier than the two unrelated machines: In the latter, the
strong price of anarchy is $2$, while in ours it is strictly smaller.
",paolo penna,,2017.0,,arXiv,Chen2017,True,,arXiv,Not available,"Selfish Jobs with Favorite Machines: Price of Anarchy vs Strong Price of
  Anarchy",2e346561b331f1e9787c035fd7877512,http://arxiv.org/abs/1709.06367v1
14970,"  We consider the well-studied game-theoretic version of machine scheduling in
which jobs correspond to self-interested users and machines correspond to
resources. Here each user chooses a machine trying to minimize her own cost,
and such selfish behavior typically results in some equilibrium which is not
globally optimal: An equilibrium is an allocation where no user can reduce her
own cost by moving to another machine, which in general need not minimize the
makespan, i.e., the maximum load over the machines.
  We provide tight bounds on two well-studied notions in algorithmic game
theory, namely, the price of anarchy and the strong price of anarchy on machine
scheduling setting which lies in between the related and the unrelated machine
case. Both notions study the social cost (makespan) of the worst equilibrium
compared to the optimum, with the strong price of anarchy restricting to a
stronger form of equilibria. Our results extend a prior study comparing the
price of anarchy to the strong price of anarchy for two related machines
(Epstein, Acta Informatica 2010), thus providing further insights on the
relation between these concepts. Our exact bounds give a qualitative and
quantitative comparison between the two models. The bounds also show that the
setting is indeed easier than the two unrelated machines: In the latter, the
strong price of anarchy is $2$, while in ours it is strictly smaller.
",yinfeng xu,,2017.0,,arXiv,Chen2017,True,,arXiv,Not available,"Selfish Jobs with Favorite Machines: Price of Anarchy vs Strong Price of
  Anarchy",2e346561b331f1e9787c035fd7877512,http://arxiv.org/abs/1709.06367v1
14971,"  We introduce a framework for studying the effect of cooperation on the
quality of outcomes in utility games. Our framework is a coalitional analog of
the smoothness framework of non-cooperative games. Coalitional smoothness
implies bounds on the strong price of anarchy, the loss of quality of
coalitionally stable outcomes, as well as bounds on coalitional versions of
coarse correlated equilibria and sink equilibria, which we define as
out-of-equilibrium myopic behavior as determined by a natural coalitional
version of best-response dynamics.
  Our coalitional smoothness framework captures existing results bounding the
strong price of anarchy of network design games. We show that in any monotone
utility-maximization game, if each player's utility is at least his marginal
contribution to the welfare, then the strong price of anarchy is at most 2.
This captures a broad class of games, including games with a very high price of
anarchy. Additionally, we show that in potential games the strong price of
anarchy is close to the price of stability, the quality of the best Nash
equilibrium.
",yoram bachrach,,2013.0,,arXiv,Bachrach2013,True,,arXiv,Not available,Strong Price of Anarchy and Coalitional Dynamics,0af31fdf9e7e188adbdb7f97879422ab,http://arxiv.org/abs/1307.2537v1
14972,"  We introduce a framework for studying the effect of cooperation on the
quality of outcomes in utility games. Our framework is a coalitional analog of
the smoothness framework of non-cooperative games. Coalitional smoothness
implies bounds on the strong price of anarchy, the loss of quality of
coalitionally stable outcomes, as well as bounds on coalitional versions of
coarse correlated equilibria and sink equilibria, which we define as
out-of-equilibrium myopic behavior as determined by a natural coalitional
version of best-response dynamics.
  Our coalitional smoothness framework captures existing results bounding the
strong price of anarchy of network design games. We show that in any monotone
utility-maximization game, if each player's utility is at least his marginal
contribution to the welfare, then the strong price of anarchy is at most 2.
This captures a broad class of games, including games with a very high price of
anarchy. Additionally, we show that in potential games the strong price of
anarchy is close to the price of stability, the quality of the best Nash
equilibrium.
",vasilis syrgkanis,,2013.0,,arXiv,Bachrach2013,True,,arXiv,Not available,Strong Price of Anarchy and Coalitional Dynamics,0af31fdf9e7e188adbdb7f97879422ab,http://arxiv.org/abs/1307.2537v1
14973,"  We introduce a framework for studying the effect of cooperation on the
quality of outcomes in utility games. Our framework is a coalitional analog of
the smoothness framework of non-cooperative games. Coalitional smoothness
implies bounds on the strong price of anarchy, the loss of quality of
coalitionally stable outcomes, as well as bounds on coalitional versions of
coarse correlated equilibria and sink equilibria, which we define as
out-of-equilibrium myopic behavior as determined by a natural coalitional
version of best-response dynamics.
  Our coalitional smoothness framework captures existing results bounding the
strong price of anarchy of network design games. We show that in any monotone
utility-maximization game, if each player's utility is at least his marginal
contribution to the welfare, then the strong price of anarchy is at most 2.
This captures a broad class of games, including games with a very high price of
anarchy. Additionally, we show that in potential games the strong price of
anarchy is close to the price of stability, the quality of the best Nash
equilibrium.
",eva tardos,,2013.0,,arXiv,Bachrach2013,True,,arXiv,Not available,Strong Price of Anarchy and Coalitional Dynamics,0af31fdf9e7e188adbdb7f97879422ab,http://arxiv.org/abs/1307.2537v1
14974,"  We introduce a framework for studying the effect of cooperation on the
quality of outcomes in utility games. Our framework is a coalitional analog of
the smoothness framework of non-cooperative games. Coalitional smoothness
implies bounds on the strong price of anarchy, the loss of quality of
coalitionally stable outcomes, as well as bounds on coalitional versions of
coarse correlated equilibria and sink equilibria, which we define as
out-of-equilibrium myopic behavior as determined by a natural coalitional
version of best-response dynamics.
  Our coalitional smoothness framework captures existing results bounding the
strong price of anarchy of network design games. We show that in any monotone
utility-maximization game, if each player's utility is at least his marginal
contribution to the welfare, then the strong price of anarchy is at most 2.
This captures a broad class of games, including games with a very high price of
anarchy. Additionally, we show that in potential games the strong price of
anarchy is close to the price of stability, the quality of the best Nash
equilibrium.
",milan vojnovic,,2013.0,,arXiv,Bachrach2013,True,,arXiv,Not available,Strong Price of Anarchy and Coalitional Dynamics,0af31fdf9e7e188adbdb7f97879422ab,http://arxiv.org/abs/1307.2537v1
14975,"  We study the performance of approximate Nash equilibria for linear congestion
games. We consider how much the price of anarchy worsens and how much the price
of stability improves as a function of the approximation factor $\epsilon$. We
give (almost) tight upper and lower bounds for both the price of anarchy and
the price of stability for atomic and non-atomic congestion games. Our results
not only encompass and generalize the existing results of exact equilibria to
$\epsilon$-Nash equilibria, but they also provide a unified approach which
reveals the common threads of the atomic and non-atomic price of anarchy
results. By expanding the spectrum, we also cast the existing results in a new
light. For example, the Pigou network, which gives tight results for exact Nash
equilibria of selfish routing, remains tight for the price of stability of
$\epsilon$-Nash equilibria but not for the price of anarchy.
",george christodoulou,,2008.0,,arXiv,Christodoulou2008,True,,arXiv,Not available,On the performance of approximate equilibria in congestion games,965af3ddfa05a87b0d62ae20a96d4772,http://arxiv.org/abs/0804.3160v2
14976,"  We study the performance of approximate Nash equilibria for linear congestion
games. We consider how much the price of anarchy worsens and how much the price
of stability improves as a function of the approximation factor $\epsilon$. We
give (almost) tight upper and lower bounds for both the price of anarchy and
the price of stability for atomic and non-atomic congestion games. Our results
not only encompass and generalize the existing results of exact equilibria to
$\epsilon$-Nash equilibria, but they also provide a unified approach which
reveals the common threads of the atomic and non-atomic price of anarchy
results. By expanding the spectrum, we also cast the existing results in a new
light. For example, the Pigou network, which gives tight results for exact Nash
equilibria of selfish routing, remains tight for the price of stability of
$\epsilon$-Nash equilibria but not for the price of anarchy.
",elias koutsoupias,,2008.0,,arXiv,Christodoulou2008,True,,arXiv,Not available,On the performance of approximate equilibria in congestion games,965af3ddfa05a87b0d62ae20a96d4772,http://arxiv.org/abs/0804.3160v2
14977,"  We introduce a framework for studying the effect of cooperation on the
quality of outcomes in utility games. Our framework is a coalitional analog of
the smoothness framework of non-cooperative games. Coalitional smoothness
implies bounds on the strong price of anarchy, the loss of quality of
coalitionally stable outcomes, as well as bounds on coalitional versions of
coarse correlated equilibria and sink equilibria, which we define as
out-of-equilibrium myopic behavior as determined by a natural coalitional
version of best-response dynamics.
  Our coalitional smoothness framework captures existing results bounding the
strong price of anarchy of network design games. We show that in any monotone
utility-maximization game, if each player's utility is at least his marginal
contribution to the welfare, then the strong price of anarchy is at most 2.
This captures a broad class of games, including games with a very high price of
anarchy. Additionally, we show that in potential games the strong price of
anarchy is close to the price of stability, the quality of the best Nash
equilibrium.
",eva tardos,,2013.0,,arXiv,Bachrach2013,True,,arXiv,Not available,Strong Price of Anarchy and Coalitional Dynamics,0af31fdf9e7e188adbdb7f97879422ab,http://arxiv.org/abs/1307.2537v1
14978,"  We study the performance of approximate Nash equilibria for linear congestion
games. We consider how much the price of anarchy worsens and how much the price
of stability improves as a function of the approximation factor $\epsilon$. We
give (almost) tight upper and lower bounds for both the price of anarchy and
the price of stability for atomic and non-atomic congestion games. Our results
not only encompass and generalize the existing results of exact equilibria to
$\epsilon$-Nash equilibria, but they also provide a unified approach which
reveals the common threads of the atomic and non-atomic price of anarchy
results. By expanding the spectrum, we also cast the existing results in a new
light. For example, the Pigou network, which gives tight results for exact Nash
equilibria of selfish routing, remains tight for the price of stability of
$\epsilon$-Nash equilibria but not for the price of anarchy.
",paul spirakis,,2008.0,,arXiv,Christodoulou2008,True,,arXiv,Not available,On the performance of approximate equilibria in congestion games,965af3ddfa05a87b0d62ae20a96d4772,http://arxiv.org/abs/0804.3160v2
14979,"  We study network formation with n players and link cost \alpha > 0. After the
network is built, an adversary randomly deletes one link according to a certain
probability distribution. Cost for player v incorporates the expected number of
players to which v will become disconnected. We show existence of equilibria
and a price of stability of 1+o(1) under moderate assumptions on the adversary
and n \geq 9.
  As the main result, we prove bounds on the price of anarchy for two special
adversaries: one removes a link chosen uniformly at random, while the other
removes a link that causes a maximum number of player pairs to be separated.
For unilateral link formation we show a bound of O(1) on the price of anarchy
for both adversaries, the constant being bounded by 10+o(1) and 8+o(1),
respectively. For bilateral link formation we show O(1+\sqrt{n/\alpha}) for one
adversary (if \alpha > 1/2), and \Theta(n) for the other (if \alpha > 2
considered constant and n \geq 9). The latter is the worst that can happen for
any adversary in this model (if \alpha = \Omega(1)). This points out
substantial differences between unilateral and bilateral link formation.
",lasse kliemann,,2012.0,,arXiv,Kliemann2012,True,,arXiv,Not available,The Price of Anarchy for Network Formation in an Adversary Model,7245126714ce33527ac06c5a6ae4ecc9,http://arxiv.org/abs/1202.5025v1
14980,"  Globally operating suppliers face the rising challenge of wholesale pricing
under scarce data about retail demand, in contrast to better informed, locally
operating retailers. At the same time, as local businesses proliferate, markets
congest and retail competition increases. To capture these strategic
considerations, we employ the classic Cournot model and extend it to a
two-stage supply chain with an upstream supplier who operates under demand
uncertainty and multiple downstream retailers who compete over quantity. The
supplier's belief about retail demand is modeled via a continuous probability
distribution function F. If F has the decreasing generalized mean residual life
property, then the supplier's optimal pricing policy exists and is the unique
fixed point of the mean residual life function. We evaluate the realized Price
of Uncertainty and show that there exist demand levels for which market
performs better when the supplier prices under demand uncertainty. In general,
performance worsens for lower values of realized demand. We examine the effects
of increasing competition on supply chain efficiency via the realized Price of
Anarchy and complement our findings with numerical results.
",costis melolidakis,,2018.0,,arXiv,Melolidakis2018,True,,arXiv,Not available,"Measuring Market Performance with Stochastic Demand: Price of Anarchy
  and Price of Uncertainty",0e5c02fa1e961208e06a0a9d9fe884c3,http://arxiv.org/abs/1808.04701v1
14981,"  We introduce a framework for studying the effect of cooperation on the
quality of outcomes in utility games. Our framework is a coalitional analog of
the smoothness framework of non-cooperative games. Coalitional smoothness
implies bounds on the strong price of anarchy, the loss of quality of
coalitionally stable outcomes, as well as bounds on coalitional versions of
coarse correlated equilibria and sink equilibria, which we define as
out-of-equilibrium myopic behavior as determined by a natural coalitional
version of best-response dynamics.
  Our coalitional smoothness framework captures existing results bounding the
strong price of anarchy of network design games. We show that in any monotone
utility-maximization game, if each player's utility is at least his marginal
contribution to the welfare, then the strong price of anarchy is at most 2.
This captures a broad class of games, including games with a very high price of
anarchy. Additionally, we show that in potential games the strong price of
anarchy is close to the price of stability, the quality of the best Nash
equilibrium.
",milan vojnovic,,2013.0,,arXiv,Bachrach2013,True,,arXiv,Not available,Strong Price of Anarchy and Coalitional Dynamics,0af31fdf9e7e188adbdb7f97879422ab,http://arxiv.org/abs/1307.2537v1
14982,"  Globally operating suppliers face the rising challenge of wholesale pricing
under scarce data about retail demand, in contrast to better informed, locally
operating retailers. At the same time, as local businesses proliferate, markets
congest and retail competition increases. To capture these strategic
considerations, we employ the classic Cournot model and extend it to a
two-stage supply chain with an upstream supplier who operates under demand
uncertainty and multiple downstream retailers who compete over quantity. The
supplier's belief about retail demand is modeled via a continuous probability
distribution function F. If F has the decreasing generalized mean residual life
property, then the supplier's optimal pricing policy exists and is the unique
fixed point of the mean residual life function. We evaluate the realized Price
of Uncertainty and show that there exist demand levels for which market
performs better when the supplier prices under demand uncertainty. In general,
performance worsens for lower values of realized demand. We examine the effects
of increasing competition on supply chain efficiency via the realized Price of
Anarchy and complement our findings with numerical results.
",stefanos leonardos,,2018.0,,arXiv,Melolidakis2018,True,,arXiv,Not available,"Measuring Market Performance with Stochastic Demand: Price of Anarchy
  and Price of Uncertainty",0e5c02fa1e961208e06a0a9d9fe884c3,http://arxiv.org/abs/1808.04701v1
14983,"  Globally operating suppliers face the rising challenge of wholesale pricing
under scarce data about retail demand, in contrast to better informed, locally
operating retailers. At the same time, as local businesses proliferate, markets
congest and retail competition increases. To capture these strategic
considerations, we employ the classic Cournot model and extend it to a
two-stage supply chain with an upstream supplier who operates under demand
uncertainty and multiple downstream retailers who compete over quantity. The
supplier's belief about retail demand is modeled via a continuous probability
distribution function F. If F has the decreasing generalized mean residual life
property, then the supplier's optimal pricing policy exists and is the unique
fixed point of the mean residual life function. We evaluate the realized Price
of Uncertainty and show that there exist demand levels for which market
performs better when the supplier prices under demand uncertainty. In general,
performance worsens for lower values of realized demand. We examine the effects
of increasing competition on supply chain efficiency via the realized Price of
Anarchy and complement our findings with numerical results.
",constandina koki,,2018.0,,arXiv,Melolidakis2018,True,,arXiv,Not available,"Measuring Market Performance with Stochastic Demand: Price of Anarchy
  and Price of Uncertainty",0e5c02fa1e961208e06a0a9d9fe884c3,http://arxiv.org/abs/1808.04701v1
14984,"  We study a pricing game in multi-hop relay networks where nodes price their
services and route their traffic selfishly and strategically. In this game,
each node (1) announces pricing functions which specify the payments it demands
from its respective customers depending on the amount of traffic they route to
it and (2) allocates the total traffic it receives to its service providers.
The profit of a node is the difference between the revenue earned from
servicing others and the cost of using others' services. We show that the
socially optimal routing of such a game can always be induced by an equilibrium
where no node can increase its profit by unilaterally changing its pricing
functions or routing decision. On the other hand, there may also exist
inefficient equilibria. We characterize the loss of efficiency by deriving the
price of anarchy at inefficient equilibria. We show that the price of anarchy
is finite for oligopolies with concave marginal cost functions, while it is
infinite for general topologies and cost functions.
",yufang xi,,2007.0,,arXiv,Xi2007,True,,arXiv,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in
  Multi-hop Relay Networks",e983f63277e6307e3324b1309d3f6ca9,http://arxiv.org/abs/0709.2721v2
14985,"  We study a pricing game in multi-hop relay networks where nodes price their
services and route their traffic selfishly and strategically. In this game,
each node (1) announces pricing functions which specify the payments it demands
from its respective customers depending on the amount of traffic they route to
it and (2) allocates the total traffic it receives to its service providers.
The profit of a node is the difference between the revenue earned from
servicing others and the cost of using others' services. We show that the
socially optimal routing of such a game can always be induced by an equilibrium
where no node can increase its profit by unilaterally changing its pricing
functions or routing decision. On the other hand, there may also exist
inefficient equilibria. We characterize the loss of efficiency by deriving the
price of anarchy at inefficient equilibria. We show that the price of anarchy
is finite for oligopolies with concave marginal cost functions, while it is
infinite for general topologies and cost functions.
",edmund yeh,,2007.0,,arXiv,Xi2007,True,,arXiv,Not available,"Pricing, Competition, and Routing for Selfish and Strategic Nodes in
  Multi-hop Relay Networks",e983f63277e6307e3324b1309d3f6ca9,http://arxiv.org/abs/0709.2721v2
14986,"  Game-theoretic models relevant for computer science applications usually
feature a large number of players. The goal of this paper is to develop an
analytical framework for bounding the price of anarchy in such models. We
demonstrate the wide applicability of our framework through instantiations for
several well-studied models, including simultaneous single-item auctions,
greedy combinatorial auctions, and routing games. In all cases, we identify
conditions under which the POA of large games is much better than that of
worst-case instances. Our results also give new senses in which simple auctions
can perform almost as well as optimal ones in realistic settings.
",michal feldman,,2015.0,,arXiv,Feldman2015,True,,arXiv,Not available,The Price of Anarchy in Large Games,cc2d5e36e476d9dec9f804d721f93269,http://arxiv.org/abs/1503.04755v2
14987,"  Game-theoretic models relevant for computer science applications usually
feature a large number of players. The goal of this paper is to develop an
analytical framework for bounding the price of anarchy in such models. We
demonstrate the wide applicability of our framework through instantiations for
several well-studied models, including simultaneous single-item auctions,
greedy combinatorial auctions, and routing games. In all cases, we identify
conditions under which the POA of large games is much better than that of
worst-case instances. Our results also give new senses in which simple auctions
can perform almost as well as optimal ones in realistic settings.
",nicole immorlica,,2015.0,,arXiv,Feldman2015,True,,arXiv,Not available,The Price of Anarchy in Large Games,cc2d5e36e476d9dec9f804d721f93269,http://arxiv.org/abs/1503.04755v2
14988,"  Game-theoretic models relevant for computer science applications usually
feature a large number of players. The goal of this paper is to develop an
analytical framework for bounding the price of anarchy in such models. We
demonstrate the wide applicability of our framework through instantiations for
several well-studied models, including simultaneous single-item auctions,
greedy combinatorial auctions, and routing games. In all cases, we identify
conditions under which the POA of large games is much better than that of
worst-case instances. Our results also give new senses in which simple auctions
can perform almost as well as optimal ones in realistic settings.
",brendan lucier,,2015.0,,arXiv,Feldman2015,True,,arXiv,Not available,The Price of Anarchy in Large Games,cc2d5e36e476d9dec9f804d721f93269,http://arxiv.org/abs/1503.04755v2
14989,"  Game-theoretic models relevant for computer science applications usually
feature a large number of players. The goal of this paper is to develop an
analytical framework for bounding the price of anarchy in such models. We
demonstrate the wide applicability of our framework through instantiations for
several well-studied models, including simultaneous single-item auctions,
greedy combinatorial auctions, and routing games. In all cases, we identify
conditions under which the POA of large games is much better than that of
worst-case instances. Our results also give new senses in which simple auctions
can perform almost as well as optimal ones in realistic settings.
",tim roughgarden,,2015.0,,arXiv,Feldman2015,True,,arXiv,Not available,The Price of Anarchy in Large Games,cc2d5e36e476d9dec9f804d721f93269,http://arxiv.org/abs/1503.04755v2
14990,"  Game-theoretic models relevant for computer science applications usually
feature a large number of players. The goal of this paper is to develop an
analytical framework for bounding the price of anarchy in such models. We
demonstrate the wide applicability of our framework through instantiations for
several well-studied models, including simultaneous single-item auctions,
greedy combinatorial auctions, and routing games. In all cases, we identify
conditions under which the POA of large games is much better than that of
worst-case instances. Our results also give new senses in which simple auctions
can perform almost as well as optimal ones in realistic settings.
",vasilis syrgkanis,,2015.0,,arXiv,Feldman2015,True,,arXiv,Not available,The Price of Anarchy in Large Games,cc2d5e36e476d9dec9f804d721f93269,http://arxiv.org/abs/1503.04755v2
14991,"  The congestion pricing is an efficient allocation approach to mediate demand
and supply of network resources. Different from the previous pricing using
Affine Marginal Cost (AMC), we focus on studying the game between network
coding and routing flows sharing a single link when users are price
anticipating based on an Average Cost Sharing (ACS) pricing mechanism. We
characterize the worst-case efficiency bounds of the game compared with the
optimal, i.e., the price-of anarchy (POA), which can be low bound 50% with
routing only. When both network coding and routing are applied, the POA can be
as low as 4/9. Therefore, network coding cannot improve the POA significantly
under the ACS. Moreover, for more efficient use of limited resources, it
indicates the sharing users have a higher tendency to choose network coding.
",wang gang,,2011.0,,arXiv,Gang2011,True,,arXiv,Not available,"The Price of Anarchy (POA) of network coding and routing based on
  average pricing mechanism",a0e7cdbbea82825b12d0fd725dfcc644,http://arxiv.org/abs/1110.4175v1
14992,"In a system in which noncooperative agents share a common resource, we propose the ratio between the worst possible Nash equilibrium and the social optimum as a measure of the effectiveness of the system. Deriving upper and lower bounds for this ratio in a model in which several agents share a very simple network leads to some interesting mathematics, results, and open problems.",elias koutsoupias,Not given,1999.0,Not given,Not given,Koutsoupias1999,Not given,Not given,Manual,Not given,Worst-case equilibria,78e8ea55c8249b215be207468d8153ad,https://dl.acm.org/citation.cfm?id=1764944
14993,"In a system in which noncooperative agents share a common resource, we propose the ratio between the worst possible Nash equilibrium and the social optimum as a measure of the effectiveness of the system. Deriving upper and lower bounds for this ratio in a model in which several agents share a very simple network leads to some interesting mathematics, results, and open problems.",	christos papadimitriou,Not given,1999.0,Not given,Not given,Koutsoupias1999,Not given,Not given,Manual,Not given,Worst-case equilibria,78e8ea55c8249b215be207468d8153ad,https://dl.acm.org/citation.cfm?id=1764944